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Increasing health data collection and reporting requirements of public and commercial payers also place financial and operational pressures on hospitals, physician practices, and other providers.,, These efforts, intended to improve health quality and cost control, include pilot and other programs covering multiple care settings and include an increasing array of information related to quality of care (e.g., longitudinal health databases and patient registries), provider performance, and use of health services and technologies. While national provider adoption of electronic health records, data capture systems, and information technology remains low (~23%-27%), broader adoption would be a necessary prerequisite for personalized health care.
At present, while data on individual patient variability (e.g., diagnostic test information) is included in some data reporting initiatives, there is not yet a comprehensive data reporting approach centered on personalized medicine or personalized health care. Recently introduced bills (S.3822, the Genomics and Personalized Medicine Act of 2006 and H.R.1321, the Medicare Advanced Laboratory Diagnostics Act of 2007) would incorporate data reporting elements, but are unclear regarding incentives for providers, diagnostics manufacturers, reference laboratories, and other stakeholders that would defray the costs associated with data reporting, database maintenance, and data access or analysis.
Integration of HIT certainly holds great potential for improving health care efficiency, quality, and cost, but must also be balanced against the practical business and operational impacts on key health stakeholders. Integration of HIT is one important component of the ability to offer personalized health care, but well-developed provider organizations driven by appropriate system incentives and underpinned by organizational supports and systems also will be necessary to support personalized health care across the diverse array of provider organizations in the US.
The aforementioned considerations are a modest sample of the policy, business, and translational issues associated with integration of personalized health practices with established and standardized health delivery models. They are, however, illustrative of the complex challenges facing those involved in health care reform and in efforts supporting the transition to personalized health care. The remainder of this paper will consider elements necessary for professional societies to play a leadership role in evolution of personalized health practice, given the pressures and implementation issues presented.
How Professional Societies Can Contribute to Elements Important to Personalized Health Care
There are hundreds of scientific and clinical specialty and other societies (professional societies) in the US that may be relevant to advancement of personalized health care. Each professional society has its own mission and vision, unique focus, and range of service offerings that are relevant to members and external stakeholders. Professional societies offer great value to the health care field by serving a myriad of functions, including but not limited to continuing medical education; development of clinical practice guidelines; informing health policies and practice standards; refining research standards, decision tools and business practices; and serving as a venue for health stakeholder collaboration and communication.
For purposes of this paper, societies relevant to the support and advancement of personalized health care would fall into the general categories identified in Table 2.
While the majority of professional societies are nonprofit organizations, it is important to note that these organizations are service-oriented businesses. They certainly help to advance science and health practice, but also protect the interest of their members. As such, professional society success and viability depend on development of offerings valuable to member’s education, decision making, and business operations. Development of niche-oriented or unique areas of emphasis that are sustainable in relation to competing offerings of other professional offerings and other stakeholders (e.g., conference coordinating businesses, government and commercial agencies) is also common.
As with any other business, professional societies also have financial, staff, and other limitations that influence the scope and nature of the activities that they can feasibly engage in. In other words, no single professional society has the capacity to “be all things to all people” and play a role in all activities relevant to personalized health care. Despite the potential interest in or importance of any particular topic or effort, society activities must be identified and prioritized based on alignment with mission, key objectives, capabilities, and member needs.
Understanding the specific areas of focus of a relevant professional society is important to identifying the role that it may play in advancing health services or policy changes. Is the organization message-oriented (e.g., in the context of policy making), content-oriented (e.g., development of clinical practice guidelines and standards), or both? Key activities relevant to personalized health care that professional societies currently engage in include, but are not limited to the following activities. Many organizations will engage in more than one, but not all of these activities.
1. Clinician education, training, and certification:
Professional societies have historically played a fundamental role in offering services that support continuing medical education. Education and training can be delivered in a variety of forms including a peer-reviewed journal operated by the society, newsletters, Webinars, and white papers on key clinical topics. Professional conferences and workshops are also important venues for learning about the latest trends in technology, health services delivery and management, and their implications for future business practices.
Many societies also offer formal training and certification necessary to maintain current licensure for clinical professionals. Others, such as the American College of Cardiology and American Society of Clinical Oncology develop and offer interactive educational portals and resources for physicians that cover a range of topics aimed at keeping practicing clinicians current on clinical, business, and policy issues important to their practice.
2. Clinician decision support and information management:
Within the current “age of information overload,” the efficiency of accessing and managing information key to clinical decision making is important to appropriate health care decision making. Although existing systems may range from broad information interfaces to very specific applications such as drug dosing (e.g., safe dosing the anticoagulant warfarin for prevention of thrombosis and embolism) or targeted therapy selection, most decision support systems are not generally maintained by professional societies. Expansion of complex molecular diagnostics and need to improve treatment use and outcomes will escalate the need for such systems as adjuncts to standard clinical practice in the near future. As these systems continue to develop, professional societies will contribute to ensure appropriate alignment and currency for clinical practice.As use of genetic and biomarker-based information is increasingly implemented in clinical practice, physician decision support systems that incorporate evidence-based practices and decision steps will need to expand or evolve to accommodate information on individuality. It will also be important to understand how and to what extent health care processes and decision tools that emphasize standardization (e.g., clinical practice guidelines, clinical pathways, quality programs) should incorporate individual patient information to balance potential improved outcomes of individualized care with the costs of this approach.
3. Patient education and decision support:
Some professional societies emphasize patient education and informed clinical decision making. This mission includes providing basic education on disease pathology and outcomes, diagnosis, and treatment alternatives, implications for patient subpopulations, and other resources helpful to the patient. The American Diabetes Association (ADA), American Heart Association (AHA), American Cancer Society (ACS), and many others have highly diversified offerings targeted to the individual patient. Others, such as the National Patient Advocate Foundation (NPAF), collaborate with a variety of health stakeholders to ensure that the patient’s perspective is appropriately included and represented in clinical practice change and health care reform initiatives.Given the rapid expansion of available diagnostics and treatments, including those related to gene-based and personalized medicine, and the resulting maze of complex choices, patient-oriented information for informed decision making is important. Further, as cost shifting places greater responsibility for health services payment for on individual patients, evidence characterizing the benefits, risks, and value of health services is essential to informed decision making. While basic patient decision support systems have evolved, significant room is available for additional support from professional societies and other health stakeholders, particularly as interoperable health information technologies mature.
4. Health outcomes research and new health technology evaluation:One of the most important roles that professional societies play is in education, communication, and evaluation of new medical evidence supporting diagnosis, treatment, and health services delivery. This role includes not only vetting the findings of clinical studies, but also providing input on methodologies for study design, good clinical and laboratory practices, and evidence review. In general, such contributions include but are not limited to the following areas:
5. Health quality and pay-for-performance standards:
Development of health quality measures is another activity that some societies engage in. Health quality measures, like clinical practice guidelines, are evidence-based and focused on characterizing standards of clinical practice and patient care. As previously discussed, these measures are often used in provider and physician performance management programs, including P4P programs that tie financial incentives to performance.
While some societies such as the National Quality Forum (NQF), National Committee on Quality Assurance (NCQA), and the Leapfrog Group focus on health quality evaluation and measure development, medical specialty societies may also contribute by translating elements of evidence-based clinical practice guidelines into health quality measures useful in P4P approaches. The extent to which information on individual variation will be integrated into health quality measures is currently uncertain because these approaches leverage quality and efficiency gains based on standardizing health care delivery.
6. Educate and inform evolving health management practices and operational models:
Although most professional societies focus efforts on clinical aspects of medical education, many also provide education, training, resources, and certification related to business management of provider, payer, and other health-related organizations. For example, the National Association of Managed Care Physicians (NAMCP) conducts medical director training “academies” to teach the business skills that clinically-oriented physicians will need to succeed in provider and payer administrative roles. Where personalized health practices will affect processes (e.g., clinical pathways or guidelines, quality measurement and P4P programs) that have financial and operational implications for professional society members, future member training may include education on the implications of individualized health information on health management practices and provider operations.
7. Stakeholder collaboration, communication, and coordination:
Professional societies currently play an essential role in bringing together key health stakeholders (e.g., payers, providers, employers, manufacturers, policy makers) to advance debate and seek solutions regarding emerging health care issues. Professional societies often have much broader “reach” (versus individual stakeholders) into diverse stakeholder groups that can be utilized to address issues and challenges through workshops, advisory councils, and other initiatives. Some personalized health issues are likely to be sufficiently complex that they will warrant collaboration among professional societies (and other stakeholders) to appropriately address certain education, operational, or health policy issues.
Likewise, since professional societies represent a group of health professionals with similar interests, the collective “voice” of the society is often more influential than individual members or member organizations acting alone. Accordingly, societies may also develop opinion and policy statements, practice standards, decision tools, and business practice recommendations, which could include topics germane to personalized health care. The conferences hosted by professional societies provide virtually unparalleled opportunities for addressing health care issues through open sessions, workshops, collaborative initiatives and even informal dialogue among stakeholders.
8. Rational health policy development that supports viable business models and care delivery practices focused on personalized health care:
The activities of professional societies include not only commercial stakeholders such as payers, providers, health technology manufacturers, and HIT companies, but also public stakeholders in government and policy (e.g., CMS, FDA, AHRQ, and CDC). Professional societies have historically worked on a variety of levels to directly and indirectly inform rational health policy development that supports quality clinical practice and innovation in health delivery. For example, life sciences industry organizations such as the Advanced Medical Technology Association (AdvaMed), the Biotechnology Industry Organization (BIO) and others regularly interact with a medical specialty societies and policy makers to inform thoughtful development of health policies that support appropriate health technology adoption and use on a range of topics particularly relevant to personalized health practice.
While not all professional societies are directly involved in the policy making process, most play a role in education and stimulation of healthy debate and discussion of key health services delivery and management issues. In the emerging era of integration of information on individual variation, broad engagement of professional societies will be critical to development and refinement of sound health policies that integrate personalized health care approaches into standardized and complex policy and delivery scenarios. As personalized health care approaches themselves become accepted as standard over time, professional societies will also be important contributors to implementation and harmonization efforts in the global health care environment.
Although professional societies currently play a role in many activities necessary for successful implementation of personalized health practices, emphasis and participation in particular activities will vary markedly by organization. Accordingly, level of interest and willingness to devote resources to personalized health care initiatives will depend upon the organization’s mission, nature of offerings (e.g., content development, message development, policy processes), availability of funding, and relevancy to members. However, as personalized health practices evolve, it is clear that professional societies are poised to facilitate collaboration among key stakeholders and play a role in development of processes, standards, and business practices that incorporate information on individual variation.
Assumptions Regarding Future Dynamics of Health Care Delivery
To understand the role that professional societies may play in supporting transition to personalized health practices, it is important to consider the implications of health care trends and the future dynamics of health care delivery. For purposes of discussion, we will assume a timeline of 3 to 5 years following the publication of this paper and evaluate the likely state of certain factors, listed below, important to broad implementation of personalized health practices and implications for professional societies.
Factor 1: Gene-based and Other Molecular Tests are Routinely Used in Patient Management
While events such as sequencing the human genome have markedly advanced our scientific knowledge, the reality is that a tremendous amount of additional research will be necessary to understand how and in what ways information on individual variation can be used in routine clinical practice. The process of science and clinical discovery simply takes time, even given the rapid pace of technological innovation and emphasis on accelerating the translation of research into practice. Despite the promise of personalized health care, the convergence of science, medicine, and technology will not occur overnight. In general, it takes up to 20 years to move a new treatment or intervention from research into clinical practice.
At present, while use of diagnostic tests is routine in clinical practice, application of complex molecular diagnostics remains comparatively limited for a variety of reasons. These reasons include, but are not limited to physician and patient educational needs, uncertain reimbursement scenarios, and complexity of interpretation. However, as biomarkers are increasingly studied in clinical trials in the coming years, evidence linking diagnostic test information to treatment selection and health services delivery issues will expand in tandem. At present there are approximately 121 drug labels in the US that contain pharmacogenomic information, 69 of which refer to human genomic biomarkers, which is a fair beginning for personalized medicine following publication of a complete draft of the human genome in 2003. Recent efforts, such as the partnership announced in October 2008 between the FDA and Medco (one of the largest pharmacy benefits management organizations), are poised to further accelerate associations between pharmacogenomics and treatment decision making.
Another key challenge will be overcoming educational barriers for use of some complex tests in physician decision making, particularly in the context of general and family practice., To fully integrate personalized health care, it will be important to create an environment where physician ordering and interpretation and patterns of test use linked to treatment selection/utilization are standard practice. It is likely that expanded emphasis on personalized medicine and information management will occur in clinical and health care management training programs in the next 3 to 5 years, and this is already occurring in academic settings that train new health professionals. To expedite this educational process, professional societies can play a key role in creating and supporting medical education and certification programs, training on emerging decision support systems, and promoting a learning and collaborative environment for personalized health care.
Factor 2: US HTA and Reimbursement Infrastructure Sufficiently Enables Personalized Health Care
While 55% to 65% of US medical and pharmacy directors and physician decision makers feel that personalized medicine will be transformative and usher in new paradigms of personalized care delivery, a recent survey conducted by the National Association of Managed Care Physicians (NAMCP) indicates that these gatekeepers and decision makers recognize the following key challenges facing personalized health care:
Many of these issues relate to processes for evidence-based practice, HTA, and translation of research into clinical practice. At present, there is significant uncertainty regarding evidentiary requirements and decision criteria for diagnostics, drug-diagnostic combinations, costly biologics and other scenarios relevant to personalized health care, particularly from the perspective of third-party payers and policy makers., Because of this uncertainty, public and commercial payers (e.g., CMS and the Blue Cross Blue Shield Association), government-affiliated groups (e.g., EGAPP), and private organizations (e.g., ECRI Institute, Hayes, Inc.) are beginning to develop approaches to overcome these obstacles, fill existing gaps, and provide information relevant to decision makers. Professional societies can liaise with these stakeholders to ensure that clinical and methodological perspectives and implementation issues are appropriately aligned will “real world” decision making needs.
Recent authoritative reports produced by the Institute of Medicine; the Secretary’s Advisory Committee on Genetics, Health and Society; and AdvaMed have also cited significant insufficiencies in the reimbursement systems associated with molecular diagnostics. Insufficiencies include HTA and coverage processes associated with diagnostics, as well as medical coding and payment approaches that do not keep pace with technological development or do not appropriately reflect the value of tests to patient care and health outcomes.,, As some of these barriers to innovation and expansion of personalized health practice are addressed over the coming 3 to 5 years, professional societies can play an important role in informing development of rational policies and health delivery practices.
Factor 3: Prevention and Risk Assessment Approaches that Incorporate Genetic Testing are Standard Practice
In large part, incentives in the US health care delivery system are geared to support “sickness care” and not “wellness care” that focuses on early disease identification and prevention. Because of the large volume and costs associated with preventive health efforts, including screening of asymptomatic patients at risk for disease development, the evidentiary threshold for demonstrating value is high and uptake has been historically limited. For example, Medicare statute prevents use of screening and prevention tests, except as amended by Congress. Since the late 1960s, fewer than 20 diagnostic tests have been approved for screening applications, including coverage of staple tests such as cholesterol testing, prostate-specific antigen testing, fecal occult blood testing and diabetic screening. Additionally, as employment longevity has decreased in the US, commercial health plans have historically been reluctant to support preventive testing for beneficiaries that may only remain in the plan for 12 to 24 months in scenarios where disease may occurs years later.
Greater emphasis from a variety of stakeholders and different incentive structures supporting preventive health services will be necessary to fully realize personalized health efforts in the coming years. Professional societies can play a variety of roles in supporting advancement of preventive health services, ranging from providing input on the viability and business implications of preventive health strategies and applicability of emerging technologies to influencing appropriate policies that support “wellness care.” Efforts may also include member education and training on how preventive and disease management programs can incorporate information on individual variation and maintain efficiencies gained by practice standardization.
Factor 4: Electronic Health Records and Decision Support Systems are a Mainstay in Hospital and Multi-physician Practices
As previously discussed, low provider adoption of electronic health records (EHR) and lack of interoperable health information systems will limit our ability to provide personalized health services. Further, the decision support tools that would improve processes for leveraging individual health information are presently in an early stage of development. Despite government, commercial MCOs, and other initiatives that provide incentives for providers to quickly adopt these systems , issues such as perceived benefit/burden tradeoffs associated with this capital investment, implementation concerns, the pace of technology turnover, and lack of standardized approaches will remain substantial barriers to acceptance over the next 3 to 5 years.
Factors that would be necessary to support EHRs and decision support systems adoption and implementation for personalized health practices include:
The government and private sector must provide strong incentives to support uptake of interoperable health information systems and their evolution as broadly adopted and routine tools to guide care practice. Sound policy and payment incentives that encourage well-developed provider organizations in addition to data reporting requirements that currently provide disincentives for nonparticipation will expedite HIT uptake and use.
As health information capabilities and knowledge networks evolve, professional societies may play a role in developing the content of clinical decision support systems and/or managing population-level data from member organizations if business incentives are appropriate to support these actions. Professional societies must consider either the availability of a suitable customer base willing to pay to access this information or the viability of partnering opportunities with HER vendors or physician practices/health systems.
Factor 5: Provider Education and Certification is Increasingly Tied to Health Care Quality and Best Practices Initiatives
Provider education delivered by both academic educational centers and professional societies has recently increased emphasis on topics such as use of biomarkers in medical decision making, disease prevention and management, implications of genomics and personalized medicine on managed care, and trends in electronic health records and quality/performance management programs. However, education offerings relevant to personalized health care are currently geared towards making the fundamentals of this topic comprehensible to providers, payers, and other health stakeholders. Further, medical certification and licensure requirements for many physicians do not yet include elements of personalized health care, but will likely need to in the future.
As clinical standards and quality measures emerge that incorporate elements of personalized health practice, professional societies can play a strong role in creation of tools that are appropriately aligned with health delivery practices and patient needs. Such tools, if supported by federally-funded initiatives and MCOs, are likely to initially target high cost/high need chronic disease areas (e.g., diabetes, heart disease, cancer).
However, the extent to which patient-specific guidelines and measures incorporating elements of individual variation will be implemented into quality management and health reform efforts is currently uncertain. At present, the majority of clinical guidelines often lack appropriate specificity for development of quality and performance measures, without adding individual variability into the mix., In addition, the ability to which we can incorporate personalized health information into clinical decision support systems is still a nascent area with significant room for development.
Factor 6: Professional Societies Play a Key Role in Evidence Evaluation and Implementation of Knowledge into Clinical Practice
Professional societies have historically played a key role in the translation of new knowledge and technology into clinical practice. It is reasonable to assume that in the future, this role will extend to personalized health practice. However, the pace of innovation and our capacity for generating information outstrips our capacity to translate new knowledge into meaningful health improvements. As such, professional societies will serve to help clinicians and other stakeholders adapt to technological innovation, information management, and new business practices that are the foundation elements of personalized health care.
Education on the expanding range of new diagnostic and treatment technologies will be critical to correct use of personalized health care technologies. Professional societies can aid in the evaluation and introduction of new technologies and clinical practices by serving as an interface between various health stakeholders, including payers, providers, and technology developers. As previously discussed, this mediation will occur through activities such as providing input on methods and standards for health outcomes and comparative effectiveness research, development of clinical practice guidelines and health quality measures, and informing development of practical tools for knowledge management and clinical/business decision making.
As part of the process of knowledge transfer, professional and scientific societies may also play a role in the conceptualization and validation of viable business models for personalized health care. In part, this can be accomplished by hosting conferences, workshops, and focus groups that address issues relevant to personalized health care practice and policy. As business models emerge, society activities will also include training of physicians and other clinical care providers to ensure that health delivery processes and standards appropriately incorporate knowledge of genetics and individual variation.
A Framework for Professional Societies to Play a Role in Enabling Delivery of Personalized Health Care
What Framework is Needed to Address Personalized Health Care?: In considering a framework that HHS might adopt to encourage uptake and implementation of personalized health care practices, it is important to recognize key barriers and then align strategic initiatives to overcome them. The validation, adoption, and diffusion of personalized health care practices may be limited by several barriers, many of which are common to introduction of any new health technologies and/or changes in clinical practice or standards of care (see Table 3).
In the case of personalized health care, failure to overcome any one of these barriers will influence not only the rate and range of stakeholder acceptance, but also holds the potential to forestall integration of some practice applications altogether. For example the level of uptake of health information management systems and business model implications are two factors that would broadly delay personalized health care efforts on the whole. Another key factor is that the concept of personalized health care is sufficiently comprehensive that unless it is broken down into actionable elements, it will be difficult to address and operationalize.
These action categories (including associated barriers), form a very general framework from which HHS and key health stakeholders can parcel out and address elements critical to implementing personalized health care. While not specific to personalized health care, it should be noted that a variety of US government initiatives geared towards addressing these barriers are already in motion.
For example, the National Institutes of Health (NIH) and the AHRQ have implemented a variety of initiatives aimed at addressing translation of research into practice over the past decade., The Centers for Disease Control and Prevention (CDC) and FDA have also made strides in recent years regarding integration on information on patient variability into technology evaluation and population-health programs. Likewise, in 2004 President George W. Bush outlined a plan to support adoption of interoperable EHRs and issued an Executive Order to create a National Coordinator for Health Information Technology within the Office of the Secretary of HHS to facilitate this plan. These are just a few examples of existing HHS efforts that can be leveraged to explore opportunities for improving personalized health practice.
Understanding how to weave personalized health care into this framework in a manner that is not duplicative of existing efforts is also an important consideration for HHS, but outside of the scope of this white paper. Factors such as strong leadership support, data to support implementation start-up and evaluation, degree of required organizational change, collaboration requirements, sustainability planning, and dissemination infrastructure have played significant roles in the overall rate of adoption and diffusion and would also be relevant to making progress against a framework for personalized health care. By clearly defining objectives and anticipated outcomes, the approaches and relevant stakeholders necessary to advance personalized health care will be more transparent and easier to accomplish and will enable appropriate prioritization among objectives.
Integrating Professional Societies Into a Framework that Supports Personalized Health Care: As strategies for operationalizing personalized health care practices continue to move forward, professional societies will play a pivotal role, both in regard to short-term evaluation and planning, as well as long-term implementation support. Such organizations are unique in their ability to connect key health stakeholders, provide a neutral grounds for healthy debate and discussion, enable educational and health practice tools and solutions, and support “big picture” objectives outside of the capacity of individual member or affiliate organizations.
In regard to engaging professional societies in efforts targeting personalized health care practices, many societies may embrace the promise of personalized health care, but remain uncertain about specific action steps and their implications for members. Because professional societies operate as any other business, the greater the clarity of a proposed engagement, the easier the evaluation of relevance and participation becomes.
As HHS supports key practice and policy efforts in this area, the following business and operational requirements will be key to anticipating the scope and nature of relevant professional society participation:
Similar to the manner in which barriers to personalized medicine may limit adoption and uptake, it will be important for HHS and other stakeholders in the vanguard of personalized health care to anticipate the extent to which specific initiatives will appeal to professional societies. The more closely aligned the desired objective is with these requirements, the greater the likelihood of securing participation.
The Road Ahead: Enabling the Personalized Health Care Environment
Personalized health care is a complex concept involving many aspects of health quality and efficiency improvement. Because the concept is broad and far reaching, it will be challenging to predict and plan for all of the health delivery and systemic implications of increasing integration of individual variability in health practice. While initial steps will likely be addressed on a scenario-by-scenario basis, it will be important to maintain perspective on the implications for health care delivery on the whole as personalized health care unfolds.
Information inputs envisioned for personalized health care appear to be potentially boundless and complex. In an age of information overload, it will be essential to channel knowledge into decision support systems, “smart tools,” and delivery approaches that better inform health decisions and presumably generate better health outcomes.  If integrated effectively, these changes in health care delivery may also refocus our current “sickness-based” system on disease prediction and prevention. The most effective models will balance standardization, best practices, and population gains with personalized health care practices, with greater emphasis placed on one or the other as appropriate to the scenario.
It is clear that professional societies have a fundamental role to play in the new era of personalized health care. While some issues and operational processes will lend themselves to personalization more readily that others, professional societies are cognizant of the potential benefits of personalized health care in a US health environment facing serious challenges and hard decisions. Appropriate engagement of professional societies around specific and well-defined personalized health care issues will require complex orchestration and planning on the part of HHS. Nevertheless, weaving professional societies into decision and implementation steps is likely to confer far reaching benefits by mobilizing key stakeholders and establishing a rational and balanced pathway forward.
Successful implementation of personalized health care will rely on the ability of key health stakeholders to work collaboratively towards practical and sustainable health solutions. Policy makers, professional organizations, payers, providers, employers, health technology manufacturers, and patients must all develop a common understanding of the cause and effect of decisions regarding integration of personalized health practices, including implications for particular stakeholders or market segments. In light of escalating health care costs and threats to sustainable provision of health services, the opportunities represented by personalized health care are great, as is the price of failure to collaboratively forge well founded solutions for the road ahead.
The authors would also like to acknowledge William T. McGivney, Chief Executive Officer of the National Comprehensive Cancer Network; William C. Williams III, President, National Association of Managed Care Physicians; Bradford Walters, Chief Medical Officer, RTI International; Samuel L. Warburton Jr., Professor and Chief, Duke Community and Family Medicine, Steve Ubl, President, Advanced Medical Technology Association, Marylin Dix-Smith, President, International Society for Pharmacogeconomics and Outcomes Research, and Janet M. Corrigan, President and CEO, National Quality Forum for their thoughts and contributions.
The Role of the Academic Medical Center
Source: McKinsey & Company
The translation of genome based discoveries, novel biomarkers, and predictive models from bench to bedside are fundamental to the development of PHC. A four-phase framework (T1, T2, T3, and T4) has been proposed by Khoury, et al., to describe this “translational continuum” (Table 1). A successful PHC application will need to traverse discovery to initial (“first in human”) health application (T1), clinical validation to evidence-based guidelines (T2), to general clinical practice (T3), and to population and public health impact (T4). The AMC will play a role in each phase and must partner and/or adapt its organization and policies to advance new health care models in order to achieve the full impact of these innovations.
|Translation research phase||Notation||Types of research|
|T1||Discovery to candidate health application||Phases I and II clinical trials; observational studies|
|T2||Health application to evidence-based practice guidelines||Phase II clinical trials; observational studies; evidence synthesis and guidelines development|
|T3||Practice guidelines to health practice||Dissemination research; implementation research; diffusion research Phase IV clinical trials|
|T4||Practice to population health impact||Outcomes research (included many disciplines); population monitoring of morbidity, mortality, benefits and risk|
AMCs are uniquely suited to discover and perform the preliminary development of the next generation of biomarkers. On AMC campuses the physical juxtaposition of academic research, medical education, leading technologies, and clinical care provides an excellent environment for investigators to develop an understanding of the unmet needs of the market, to discover novel solutions, and to validate their efficacy in experimental models and in clinical cohorts and test their utility in ‘real world’ healthcare delivery settings.
Academic researchers, unlike researchers in private industry whose budgets are primarily dictated by expected investment returns, have the freedom to explore new areas of science with less immediate regard to financial return on investment. Moreover, academic research aspires to operate with norms of Mertonian “open science” as opposed to the generally more proprietary model of R&D in industry. Consequently, AMCs can more readily collaborate, build off one another’s discoveries, and foster more “disruptive thinking” that can bring about new technologies and approaches and introduce entirely new capabilities, rather than incremental refinement and improvement on existing techniques.
AMCs: a strong record of innovation. Academic research institutions have contributed many of the discoveries leading to genomic technologies. The basic methods of DNA synthesis were pioneered at the University of Colorado by Marvin Carruthers. The Maxam-Gilbert DNA sequencing method was developed primarily at Harvard, and Sanger-Coulson sequencing at the University of Cambridge. The prototype for automated Sanger sequencing, using the four-color fluorescent method, was pioneered at Caltech. DNA-chip microarray technologies commercialized by Affymetrix and Agilent drew on Stanford research, and the Illumina bead-array technology grew out of analytical chemistry at Tufts University. Some of these methods were patented (four-color DNA sequencing, DNA lithography, bead-arrays); some were not (Sanger-Coulson and Maxam-Gilbert sequencing). Sequencing methods were widely adopted for academic research, but large-scale sequencing depended on instruments developed by Applied Biosystems and other firms, and microarray technologies were developed by many companies. Competition for the new generation of high-throughput DNA sequencing, en route to the $1,000 genome, is intense among several firms and academic researchers.
Academic research centers have also been deeply involved in another set of discoveries directly pertinent to the advance of genomics-guided medicine – the association of an individual’s molecular biology, both static (e.g., DNA sequence, gene copy numbers, and single nucleotide polymorphisms SNPs)) and dynamic (e.g., gene expression, protein and metabolite levels), with clinical phenotypes. Genomics-guided medicine has grown out of the quest for disease-associated genes that accelerated in the 1980s. This revolution began when genetic linkage maps were used to find mutations associated with Mendelian conditions such as Huntington’s disease and cystic fibrosis. It then expanded into Mendelian forms of diseases with multiple causes, such as Alzheimer’s disease, and inherited susceptibility to conditions such as breast and ovarian cancer or colon cancer. Genetic testing, once restricted to a handful of newborn screening tests, has expanded to include hundreds of tests. At the end of August 2008, for example, www.genetests.org listed 595 laboratories testing for 1610 conditions. With the commercialization of efficient discovery platforms for the measurement of dynamic biological parameters such as gene transcription factors, proteins and metabolites in the 1990’s, genomics-guided medicine expanded to include diagnosis and prognosis of non-Mendelian conditions. Hundreds of gene expression, protein, and metabolite “signatures” are under investigation at AMCs and diagnostic companies as potential tools for use in PHC. Arguably, these T1 research efforts are only possible because of the ability of academic investigators to ascertain and bank high quality clinical specimens from patients and to link these to robust clinical phenotypic data and longitudinal follow up and health outcomes (see below).
Cancer research today is a spectacularly promising example of the AMC’s role in shaping the future of genomics-based personalized cancer care. “The Cancer Genome Atlas,” collaboration between the National Cancer Institute and the National Human Genome Research Institute and several AMCs, aims to develop novel tools for the detection and treatment of cancer. This program utilizes technologies such as large-scale genome sequencing (of germ line and somatic DNA) to better understand the molecular basis of a variety of tumors (glioma, non-small cell lung cancers, and ovarian cancer). The overarching goal of this project is to improve capabilities for preventing, diagnosing, and treating cancer at a personalized level. This program and others will result in a paradigm of medical care is based on our ability to match accurate prognosis and proper therapy to the molecular characteristics of the individual and with the individual patient’s tumor. Whole-genome expression data from this effort and other in the AMCs are now being used routinely to identify subtypes of cancer not previously recognized by traditional methods of analysis: profiles and patterns that identify new subclasses of tumors, such as the distinction between acute myeloid leukemia and acute lymphoblastic leukemia, or Burkitt’s lymphoma from diffuse B cell lymphomas, without prior knowledge of the classes. More recently several genomic signatures that go beyond disease classification have been discovered and validated that predict prognosis and response to therapy for many solid tumors and hematologic malignancies., Much of the science that underlies associating genomic data with clinical decisions has and will continue to come from AMCs. For now, these technologies are mainly research tools, but they will surely become relevant to clinical decisions with the proper investment in their development.
Funding of innovation: A changing landscape. AMCs have been the main recipients of grants for health research, and home to most “public domain” research from which further research and practical applications arise. Innovative technologies described above have resulted in part from these funding streams. A survey estimated government and nonprofit genomics research and development (R&D) spending from 2004-2006 at $3 billion annually, in rough parity to a separate survey that estimated private genomics R&D at $3 billion., This balance between private and public genomics R&D is a dramatic change from the early 1990s, when private genomics funding was sparse. By 2000, however, the $2 billion R&D expenditures by publicly traded firms wholly or partially devoted to genomics and another $1 billion genomics R&D at established pharmaceutical and biotechnology firms exceeded the $1.8 billion reported in government and nonprofit R&D. Private genomics R&D is a major force now; AMCs are at the point of convergence between government and nonprofit funded genomics R&D and privately funded genomics, although we know of no estimate of private genomics R&D at AMCs. How these funding shifts will affect the balance between innovation in the AMCs and private firms is uncertain; public-private partnerships (see “A Call for Specialized Centers” below) may yield the greatest productivity from these investments, and AMCs will be essential elements of such partnerships.
Role of Intellectual Property in developing personalized medicine at AMCs. Academic institutions own a much larger share of patents relevant to DNA diagnostics and prognostics than in most other areas of technology, because much of the research studying linkages between genomic factors and disease is federally funded through the NIH or other government and nonprofit sources—with a disproportionately large fraction conducted at research institutions associated with medical schools. While AMCs account for somewhat less than 2 percent of patents overall, government funded research institutions accounted for 39 percent of DNA-based patents 1980-1993, a more than ten-fold enrichment of academic patent ownership compared to patents overall. A preliminary analysis of patents licensed by one major diagnostics firm, Athena Diagnostics, showed more than three-quarters of the relevant “gene” patents were owned by academic institutions.
This prominent role of academic research institutions suggests that sometimes AMCs will be patent owners, sometimes they will need to license patents owned by others, often they will be working in conditions of uncertainty about whether their research—and even more so, commercialization strategies—enjoy freedom to operate or will be subject to patent enforcement. This is starkly different from the patent regime long associated with protein and small-molecule therapeutics, where the zone of uncertainty is smaller because only one or a few key patents cover a small class of molecules. However for business plans being developed today, complex patent landscapes portend uncertainty for the future of DNA-based technologies.
The practice of AMCs governing patenting and licensing of genomic technologies, as both users of the inventions and also as patent-owners, is crucial. Academic institutions have emerged as owners of intellectual property for several reasons. The main reason is that the research they do is fully intended to have practical benefits, creating knowledge that enables development of products and services to improve health. Most health research falls squarely in what the late Donald Stokes called, “Pasteur’s Quadrant,” meaning it is both scientifically important and also has foreseeable practical use. It thus often produces results that can be patented because they are novel, useful, and inventive.
Universities, in the past, have patented some inventions, including drugs and vaccines. Thyroid hormone, vitamin D, warfarin, insulin, and antibiotics (although notably not penicillin) were first described in patents owned and administered by academic institutions. However, the level of academic patenting accelerated in the 1980s, mainly because of the science and technology being pursued, but also because the Bayh-Dole Act of 1980 clarified the default rules for ownership of patents. The Bayh-Dole Act increased consistency among federal R&D funding agencies and it codified the emerging practice of having grantee and contractor institutions own patent rights, rather than government retaining ownership of patents arising in federally funded research. Thus the Bayh-Dole created an incentive for academic institutions to seek patents so they could license them.
Academic institutions responded accordingly by getting many more patents, and this effect, as noted above, is particularly pronounced in DNA-based technologies. Commercial biotechnology in general, and genomics in particular, grew up almost entirely in the Bayh-Dole era, with incentives for universities and AMCs to patent inventions arising from research, and giving them control of licensing of the resulting intellectual property. The development of the Affymetrix chip technology, for example, drew upon Stanford research and personnel, entailed several grants directly to the nascent company, and benefited from federally funded research. The development of Illumina technology is also a classic Bayh-Dole story of a research idea at Tufts being developed by a startup firm with exclusive rights to university patents. In both cases, a big part of the first market for the resulting technology was academic health research, so universities were involved in creating the technologies and later benefited from the availability of powerful new instruments developed by startup firms.
Many DNA patents have been exclusively licensed, and many of the uses of those patents were not foreseen at the time the patents issued and licenses were signed. For DNA sequence patents exclusively licensed for the full patent duration of the patent, even if the exclusive rights were restricted to diagnostic use, these prior intellectual property rights could cast a shadow over the development of genome-wide diagnostics, or over the first-generation “personal genomics” services that have recently become possible through companies like Navigenics, 23andMe, deCODEme, SeqWright, and Knome. The degree to which a legacy of existing patents and licenses affects the future of multi-gene tests will depend on: (1) the specific language of patent claims, (2) specific terms under which the patents have been licensed, (3) the outcome of any cases that set precedents in litigation, and (4) decisions about whether and to what degree patent rights are enforced against the new uses.
As DNA patent holders and also users of the technologies, AMCs will be making these choices. It will be a challenge. Patents and their claims are public, but collecting and analyzing all the relevant patents and interpreting how their claims might affect for a multi-gene test is a daunting task fraught with uncertainty. It is made even more difficult because terms of licenses, which are crucial to determining the boundaries of intellectual property, are generally not public unless licensers and licensees choose to make them so. To the degree AMCs contribute to this inefficiency, they may impede the advance of genomic discoveries into medicine.
Despite this increased recognition of the role of human biospecimens as a critical enabler of genomics-based research and medical care, the state of storage of human biospecimens is largely in disarray. Most AMCs cannot readily access a list of samples stored on institutional premises, the conditions under which they are stored or the subjects who donated them. The current lack of standards and quality control procedures for sample procurement to biological analyses presents a significant challenge to developing studies of statistical and clinical value as well as to guide public health planning and raises issues concerning the appropriate use of these samples donated by human subjects. Working with the NIH, AMCs have made progress in standardizing practice to facilitate knowledge sharing across institutions. In 2004, the NCI initiated the Cancer Bioinformatics Information Grid (caBIG) to standardize data formats for genomic and phenotypic data captured in cancer research and to develop common research tools among more than 50 NCI-designated cancer centers. Specific biomedical research tools under development by caBIG include clinical trial management systems, tissue banks and pathology tools, imaging tools, and a rich collection of integrative cancer research applications.
Centralized biorepositories and standardized patient registries are aligned with the mission of AMCs and health systems to enable and enhance research opportunities as well as to assist in the structure to support health care delivery. Centralization will manage costs, create synergies and economies of scale, reduce liability, maintain high ethical standards, and enable compliance with applicable regulations. Research and funding opportunities will undoubtedly be enhanced through a centralized system that provides timely access to a large numbers of fully annotated samples, thereby minimizing the need to enroll new subjects and collect new specimens for each study. In addition, centralized biorepositories make costs more transparent and allow the AMC-investigator community to carry out its research and clinical mission more efficiently, rather than spend its time managing sample collections. Longitudinal cohort studies rich in epidemiologic data combined with biospecimen banking create unparalleled scientific power. As we discuss below, biospecimen banks are a not only a valuable source for discovery, but in cases where data has been collected over long periods of time, biobanks may allow for the efficient validation of biomarkers for their association with distant clinical endpoints that would be prohibitively expensive to validate prospectively.
Well-annotated biospecimens collections can also be leveraged successfully into academic-industry partnerships whose goal is improved diagnostics and therapeutics development. Merck & Co and Tampa's H. Lee Moffitt Cancer Center & Research Institute have formed a for-profit center, M2GEN, to collect tissues and clinical information of up to 30,000 consented research subjects with the aim of identifying biological differences that might explain variation in response to cancer drugs. The deal, valued at nearly $100M over five years, gives Merck exclusive access to the database for drug discovery purposes. In a second collaboration, this time with a for-profit company medical device company, Merck partnered with Fox Hollow Technologies, Inc. of Redwood, CA. The partnership provided Merck access to Fox Hollow’s collection of atherosclerotic plaques to test cardiovascular biomarkers for use as diagnostics and as tools for drug development. Similarly, BG Medicine – part of the High Risk Plaque (HRP) initiative, an industry consortium – is working with Duke University to identify biomarkers that identify patients at high risk for acute coronary syndromes using blood samples previously collected and stored by Duke’s cardiac catheterization laboratory. The samples are linked to health outcomes data longitudinally through patient care within the Duke University Health System. These examples underscore the fact that research into PHC, both in academia and industry, could be greatly enhanced by more ready access to annotated patient samples to validate and develop new biomarkers.
Biobanks at research consortia funded by the NCI have played a central role in the development of Genomic Health’s Oncotype Dx testing service to predict the risk of recurrence in early stage breast cancer patients. The initial list of candidate genes came from a search of the academic literature, mainly contributed by AMCs. Genomic Health refined its gene list and subsequently conducted two major validating clinical studies of the test entirely on tissues banked by the National Surgical Adjuvant Breast and Bowel Program (NSABP), a cooperative group based at the University of Pittsburgh. The two major cohorts used (B-14 and B-21) were collected in the 1980s. Without access to such tumor banks with “mature” clinical data, the T2 research necessary for clinical adoption would not have been possible in a timely or cost effective manner and investment and subsequent “translation” of the discovery would likely never have occurred. However, by carefully designed studies within the NSABP biobank cohorts, Genomic Health has been able to successfully launch Oncotype Dx and achieve reimbursement from most payers. Based in part on the data from these studies, the American Society of Clinical Oncologists (ASCO) has included Oncotype Dx in it most recent guidelines for the diagnosis and treatment of early stage breast cancer.
Demonstrating the clinical utility of most the newly discovered genomic or imaging biomarkers through appropriately powered, randomized clinical trials has proven difficult for academic researchers and industry alike. When asked why genomic discoveries are not advanced to practice, stakeholders in PHC cite the lack of both public and private funding for clinical studies to build an evidence base and the challenges of designing and executing studies in which the clinical endpoints are separated from the interventions by many years. Without clear evidentiary standards, investors cannot be certain of the level of funding necessary to achieve regulatory approval and payor acceptance of a new biomarker. In the face of this uncertainty, clinical validation is often left unfunded by the private sector. Indeed, there is a dearth of studies addressing the impact of new personalized medicine tools. In a survey of PubMed articles published between 2001 and 2006 on genomics and genetics in humans, only 2% of 336,169 manuscripts were classified as clinical trials. Of these trials, few were randomized.4 Recognizing the need to develop studies that demonstrate the clinical value of genomics to inform clinical decision making and provide value, the Centers for Disease Control (CDC) and the NIH announced at least three RFAs this year to foster these types of studies. The private sector has not been an enthusiastic funder of T2 research in personalized medicine. This is in stark contrast to clinical evidence produced each year funded by private industry to support the introduction of new therapeutics regulated by the FDA under the Pre-Market Approval (PMA) process for drugs, biologics, and devices. However, recently diagnostic development companies and the pharmaceutical industry have begun to, under certain scenarios, invest in personalized medicine and the T2 research studies necessary to drive their clinical adoption and prove their clinical utility.
The Government as sponsor of T2 research. CDC’s Evaluation of Genomic Applications in Practice and Prevention (EGAPP) working group has begun the process of culling from the literature the genetic and genomic tests that have promise to shift the way health care is delivered. The first EGAPP report on the use of pharmacogenetic testing for prescribing tricyclic antidepressants was released in December 2007. One of the areas EGAPP has identified for study is the use of gene expression profiles for prognosis in breast cancer – an area with a clear demand for a novel diagnostic solution. Of the women that receive adjuvant chemotherapy for node negative, estrogen receptor positive breast cancer, approximately 85% receive no clinical benefit over taking tamoxifen alone. Despite the lack of a prospective randomized clinical trial – the gold standard for proving the value of an experimental therapy – oncologists used RNA expression signatures for risk stratification and prognosis in breast cancer for more than 24,000 “treat” vs. “no-treat” decisions in 2007. A prospective cooperative group clinical trial (MINDACT) by the European Organization for Research and Treatment of Cancer aims to measure the effectiveness of a gene expression predictor of breast cancer prognosis to guiding adjuvant chemotherapy when compared to predictions based solely on the traditional clinical parameters for prognoses. An NCI-sponsored study (TailoRX) aims to utilize the Oncotype Dx test to identify low risk breast cancer patients unlikely to benefit from chemotherapy. A similar opportunity now exists to refine prognosis and redirect treatment in early stage lung cancer and a CALGB sponsored clinical trial has been developed to use an expression signature to randomize patients to surgical treatment with or without adjuvant chemotherapy. These are clear examples of T2 research in which AMCs in collaboration with government and industry are developing novel clinical trials infrastructures to evaluate the performance of genomic medicine tools to redefine disease phenotypes and refine therapeutic strategies.
Diagnostic companies as sponsors of T2 research. In previous decades, private diagnostic companies have been reluctant to sponsor or conduct extensive clinical trials to demonstrate the clinical utility of novel assays, genomic or otherwise. This reluctance to invest has been driven primarily by economics. Under the current payor system a diagnostics company is reimbursed fixed fees for any procedures necessary to perform a test. Typically, these fees do not provide sufficient excess margin to justify an investment in extensive clinical validation, let alone patient and physician education or clinical guidelines development. Moreover, reimbursement by insurance companies has not generally been contingent on proving clinical utility in formal trials. Instead, tests had to be deemed “non-investigational”. As a result, most diagnostics on the market today have arrived after floundering in “investigational use” status as evidence and awareness slowly build up over time. Typically, a diagnostic company will develop a commercial version of a new test only once the biomarker has been sufficiently validated and gained acceptance within the clinical community. As exemplified by troponin testing for cardiovascular injury in the setting of chest pain, the AMC has traditionally filled this validation role, often performing investigator-initiated trials and conducting the testing using their own, low-volume laboratory developed test (LDT), prior to the availability of a commercial test. This reluctance to invest in the validation of new diagnostics is often amplified when the performance characteristics of the technologies are less established – as is the case with many of the new genomic and multi-analyte platforms – and when the pathway to regulatory approval and ultimate clinical acceptance is less clear.
There is evidence, however, of a new model emerging for the investment in the development of novel personalized health diagnostics. The tests that receive such investment are often linked to expensive therapeutics and so can carry a high economic value. Under this new paradigm, a few private diagnostic companies, including Genomic Health, XDx, and Third Wave Technologies, have made the decision to invest in clinical trials conducted at AMCs, as well as the physician education and clinical guidelines development necessary to bring a novel test into widespread clinical use. This new model requires IP protection for the test, a clear path to a large market, and justification for a value-based price, which circumvents the traditional code-based reimbursement scheme. Only under these conditions can a private company be assured of an appropriate return on their investment.
A recent example of this new approach is the development of the Oncotype Dx testing service to predict the risk of recurrence in early stage breast cancer patients. Genomic Health invested over $100 million in the clinical development and marketing of the test. However, with a price point of $3,460 and an operating margin of over 60%, Genomic Health has a good chance of recouping its investment in the coming years. Genomic Health can justify its relatively high price for Oncotype Dx based on the potential value it brings to patients and their payers. By identifying those patients unlikely to experience a recurrence of their cancer and therefore unlikely to receive any benefit from adjuvant chemotherapy, the test can in theory reduce the amount of money spent on chemotherapy and the management of its complications.
Genomic Health was able to identify an application in which the potential to save healthcare resources was high compared with the cost to demonstrate the clinical utility of the test and engage the patient and physician communities. Also, by securing patent protection for their test, they have been able to limit direct competition. However, very few new personalized health applications will have such attractive economics. Many other genomic discoveries have the potential to have a positive impact on healthcare delivery, but lack a clear path to near-term commercial profitability. The uncertainty surrounding what will be required for clinical validation and to secure approval by regulators and payors, and the lack of clarity in existing patent law to ensure exclusivity in the market discourage investment in all but clear economic winners. Until significant policy changes are implemented to reduce the uncertainty in validation requirements, level of and time to reimbursement, and ability to practice both freely and exclusively with regard to intellectual property, private investment will likely be limited.
Pharmaceutical companies as sponsors of T2 research. The pharmaceutical industry has the potential to be a significant driver of personalized medicine using genomic information to inform drug development, approval, and clinical drug use. At the same time, pharmaceutical firms have long resisted stratification strategies in clinical development and the resulting ‘segmentation’ of markets. For the most part, pharmaceutical developers are utilizing genomic approaches to identify which populations benefit from drugs after they are approved. Drug manufacturers would be wise to undertake such studies prior to approval. The lessons of cetuximab and EGFR mutations - driven by AMC investigator initiated studies to better understand the populations most likely to benefit from these agents - and recent late-stage drug failures have sounded an alarm. Indeed the FDA’s Critical Path Initiative challenges industry to adopt the use of biomarkers throughout drug development. Voluntary Genomic Data Submissions to the FDA that began in 2005 encourage sponsors to incorporate genomics into their development plans heralding that this may be a requirement in the future. The recent addition of genetic testing to the FDA label for warfarin and the recent FDA approval of a microarray based test for the management of breast cancer as well as a test for tumor of unknown primary are clear signals that the regulatory environment will increasingly encourage medical product development based on genomic information. According to a recent survey by McKinsey and Co., biomarker R&D expenditures within
pharmaceutical firms in 2009 were estimated at $5.3 billion, up from $2.2 billion in 2003. This increase is targeted at the development of safety and pharmacokinetic biomarkers, and in so-called “companion diagnostics” – biomarkers that can accurately identify individuals with a high likelihood of response. Since most drugs show activity in only a fraction of patients, an industry-based strategy to use genomics to identify subgroups of patients most likely to benefit from their products in development will bring more personalized therapies to the market and will incorporate genomic testing into the labeling of the drugs ultimately approved.
AMC investigators are now designing studies to test the hypothesis that genomics can improve outcomes for existing and standard of care therapies. At the Duke Institute of Genome Sciences & Policy this has been adopted as a strategy for translating genomics into clinical medicine. The IGSP Clinical Genomics Studies Unit (CGSU) has been established with the goal of setting the standard for genome-based clinical trials (www.genomestohealth.org). This unit functions to vet the scientific merit of trials prospectively testing predictive genomic tests, assess technical and practical feasibility, and developing outcomes data to support clinical utility and cost effectiveness. A typical trial design that tests the ability of genetic or genomic information to improve clinical and economic outcomes underway in the CGSU is shown in figure 2 below.
Figure 2. Design of a clinical trial to test the utility of a molecular test to impact standard of care therapy decisions.
AMCs often face the vexing issues of conflict of interest that come with their role as neutral arbiters of the evidence surrounding use of medical technologies, both their benefits and their risks. “Opinion leaders” who influence the introduction and adoption of drugs, vaccines, biologics, and devices are typically drawn from prestigious AMCs. Congress is clearly concerned that the flow of money and other incentives for collaboration between academe and industry can also bias the research system in favor of corporate interests. The trade associations for the pharmaceutical, biotechnology and device industries have agreed to a succession of voluntary codes of conduct. The Association of American Medical Colleges has issued several reports that make recommendations for managing both individual and institution conflicts of interest. As the world’s largest single medical research laboratory, the NIH, tightened restrictions on its federal employee researchers in 2002. NIH also reminded its grantees and contractors of the need to have conflict-of-interest policies and its right to audit implementation of such policies in August 2008. The government is also engaged in formal rule-making that could alter the rules. Several states have passed laws limiting gifts to physicians or mandating reporting of gifts over a certain amount (usually $25 or $50); Senators Grassley and Kohl have proposed a federal law mandating reporting of gifts and payments. Conflict of interest was a feature of the national magazine for state legislatures in September 2008. Pennsylvania has funded a counter-detailing initiative to guide use of drugs, and many states have considered bills about direct-to-consumer advertising of medical products. Most of these proposed policy changes are primarily directed at drugs, but the policies are likely to spill over to change the overall system for introducing and adopting all new medical products and services, including genomic technologies.
The development and validation of clinical delivery models that support PHC is critical to its implementation and adoption. AMCs, for their part, have an opportunity to fundamentally change their approach to physician education, payment and incentive systems, and metrics of quality and efficiency and act as the first-line testing grounds for innovative T3 research. Moreover, by providing a platform with resident expertise in both clinical research and care delivery, AMCs have the opportunity to provide a common platform to all of the stakeholders for the conduct of the implantation, dissemination and health outcomes research necessary to see PHC brought into practice.
Although clinical care is a core mission of AMCs, as Snyderman and Yoedionio have suggested, academic medicine has not yet become engaged in the systematic exploration of more rational models for health care delivery required for personalized and prospective medicine.3 Only a handful of AMCs have developed comprehensive programs enabling prospective approaches to patient care. In 2003, for instance, Duke University initiated Duke Prospective Health (DPH), a personalized care, disease management, and wellness program for its employees. The program, which Duke University physicians helped develop and manage, sought to prevent or detect chronic conditions related to smoking, diet, exercise, and stress by having patients develop and use a Personal Health Plan to ameliorate their individual risk. The program has three main components: a Health Risk Assessment (HRA), Care Management, and Health Coaching:
Although the program is relatively new, preliminary analysis on 154 patients suggest that a multi-modality intervention reduced risk of CHD, by increasing exercise and improving weight loss. Duke is now initiating comprehensive PHC programs that use the DPH as a core delivery model in breast cancer, prostate cancer, diabetes, cardiovascular medicine, pharmacogenomics, and family history.
The premise of PHC is that by addressing health concerns pre-symptomatically – while interventions are more impactful and cost effective – health systems can improve health and lower the costs of health care. However, under the current economic models, any cost savings may not be realized by the health care providers bold enough to institute these changes. Currently, most payor systems do not reimburse for preventive services, except when Congress explicitly mandates it. Instead, reimbursement in the modern American health care system is driven by procedures and post-symptomatic interventions. Moreover, intensive in-patient procedures typically yield higher margins to the health systems than out-patient health monitoring and non-surgical interventions. PHC models, if successful, would shift patients from high-margin in-patient procedures to low-margin (or, at present, uncovered) out-patient screening and interventions. From the perspective of the healthcare systems’ finance department, PHC is a money-losing proposition. With such misaligned incentives, personalized medicine approaches may not receive as enthusiastic backing as if it were equally profitable as current procedures, and therefore incentives to innovate in this area of health care delivery are lacking.
Similar countervailing financial incentives combined with an overall lack of compelling clinical data on new personalized health tools make it difficult for payors to fully embrace PHC. It may seem financially prudent for a payor to reimburse for a diagnostic test that could identify high-risk individuals in situations where relatively low-cost interventions could prevent expensive surgical procedures in the future. However, identifying those tools can be difficult. We have already examined the relative lack of clinical data on such tools on which payers might be able to make that determination. This uncertainty is compounded by the fact that even if a molecular diagnostic is shown to work, there is no guarantee that healthcare providers and/or their patient will modify their behavior in response to the result – in which case the payer may end up paying for the test and the surgical intervention. Finally, there is the “hazard” of discontinuity of coverage; due to the fact that people shift health coverage plans over their lifetime, a payor that covers a diagnostic screening for an individual will not necessarily receive the benefits of a healthier client in the coming decades. In fact there is an incentive for people to “game the system” by enrolling in relatively expensive plans which cover PHC, then once testing is complete, shift to a relatively less expensive plan for their long-term care. There are a few examples of situations where PHC has been covered by insurance. For example, Aetna and Kaiser will cover genetic counseling services under many of
their plans. Aetna has even instituted a phone counseling service for its members. This may be financially motivated or for reasons of increasing service levels in a competitive health insurance market.
While all parties ultimately stand to gain from the implementation of PHC, economic incentives present significant barriers to realizing its implementation. It is incumbent upon AMCs to demonstrate leadership in the clinical delivery space by exploring new economic models, and serving as a common forum in which all stakeholders might share data and resources to overcome these barriers and work towards a scenario in which all parties benefit.
Personalized medicine will continue to meet resistance from individual practitioners unwilling to modify their patient management approach. Clinicians may resist if they feel that their judgment is being superseded by a test result or if they feel the way they have managed patients in the past was adequate. Without the proper systematic incentives in place, adherence to clinical guidelines and adoption of new therapeutics is often lackluster. For example, despite the publication of clinical evidence demonstrating the clinical utility of the use of beta-blockers for patients who were recovering from a myocardial infarction (MI) in 1981, in 1996 – 15 years after the landmark publications– these drugs were only prescribed to 62.5% of patients after an MI. However, once physicians were evaluated based on their adherence to clinical practice guidelines, adoption increased rapidly. The National Committee for Quality Assurance (NCQA) began tracking compliance with certain treatment guidelines, including the use of beta-blockers in MI patients, in 1996 and publically reporting results. By 2006, compliance of beta-blocker administration had improved to over 97%.56 The tendency to resist a change in practice holds true for all clinical care models, but will be especially true in the case of PHC. Adoption of new genomics-based tools will require health care providers to become familiar with new technologies and science and require continuing education on awareness on new PHC methods. AMC must make systemic changes in how health care providers are evaluated, compensated and trained if PHC is to be readily implemented and tie the concepts of PHC to quality, safety, and performance.
A core mission of the AMC is to train the healthcare workforce. As PHC services and diagnostic tools evolve, AMCs will need to develop training for the workforce that will be required to implement them. In our opinion, this is fundamental to bridging the third translational gap, T3, in the translational continuum. In this regard there is need to break new ground in medical education and to develop a national model for integrating knowledge of new molecular-based technologies in medical practice. The primary care workforce feels woefully unprepared to integrate genomics into regular practice. Consumers are enthusiastic about genetics and are hopeful about their impact but at the
same time they have a low knowledge base about genetics and genetic testing for common diseases. Education of health professionals and the public must be a priority to advance the use of genomics into healthcare. With the rapid advances in genomics research and developing technologies, it will be challenging to keep health professionals informed about the benefits, risks, and limitations of new tools as they become available. In addition, the public and health care workforce will need to understand the appropriate clinical applications of genomic tools -- including their benefits, risks and limitations, and how they may improve clinical management. Direct to consumer genomic testing has only served to greatly intensify the educational needs across the genomic medicine community from the lay public to health care providers to policy makers. Several surveys have documented the below average physician knowledge of genetics, but none has assessed knowledge of the newer field of genomics. The importance of education in the application of pharmacogenetics has been described, but at present there are no broad initiatives to orchestrate genetics and genomics education of medical professionals, trainees, and the public at large. Basic genomic literacy is a critical need for patients and physicians and communities to engage in genomic research and clinical studies required bring about a change in the care paradigms to support clinical genomics applications.
In 2003, Duke University School of Medicine it revamped its curriculum and set as a goal to “practice personalized health planning for long-range goals”. Although this has not yet happened on a school wide scale, fourth-year electives such as Integrative Medicine and Prospective Health and Health Promotion and Disease Prevention are available. The fundamental concepts underlying the theory and practice of PHC should become central parts of medical education.3 For the basic sciences, this would include teaching concepts of disease evolution from health and the role of predictive biomarkers in this process. Clinical education would include concepts of a medical evaluation comprising health risk prediction, current health status, pathogenesis tracking, pharmacogenetics, health planning, patient motivation, and disease management. To our knowledge, this has not yet occurred to any significant degree among U.S. medical schools or residency training programs. A strategy driven by the AMC community is essential to effect changes in the way the health care providers in medical and nursing students in the USA are trained in PHC.
An important and emerging concept that will facilitate the implementation of PHC is the PCMH or the American College of Physician’s “Advanced Medical Home”. Enabling both T3 and T4 research, the PCMH is a model for delivery of care that is provided by medical practices to strengthen the physician-patient relationship by focusing on delivering coordinated care in a prospective manner – similar to the Duke Prospective Healthcare model above - to patients, focusing more on prevention of disease and promotion of wellness, compared to the current system of focus on episodic care based on illnesses and patient complaints. Genomic medicine should be integrated into each of the principles of the PCMH (Table 2): Personal physician, Physician directed medical
practice, Whole person orientation, Coordination/Integration of Medical Care, Quality and safety, and Access.
The PCMH is an opportunity to improve clinical operations and outcomes for patients in a currently fragmented medical system. The concept of genomic and personalized medicine has synergy with the PCMH in the effort to better define risk of chronic disease for individual patients, and to redefine how health risk is communicated to patients. Ongoing strategies for delivery of genomic or imaging based risk assessment technologies that enable PHC should focus on integration with the PCMH.
Information technology will be a key component of both health care delivery and the T3 and T4 research that is needed for PHC. Past experience indicates that the new genomic interventions, like any new medical intervention, will remain significantly underutilized for some time without the concurrent introduction of supportive technologies. Moreover, genomic interventions may face even greater barriers to clinical adoption compared to more traditional medical interventions, due to such factors as patient concerns over genetic discrimination, limited clinician familiarity with the science, and the volume and complexity of the data that need to be considered. In recognizing this challenge, Secretary Leavitt announced in March 2007 HIT as a priority to support the achievement of personalized medicine.
The use of electronic medical records (EMRs) as a major component of HIT is expected to substantially improve the quality and efficiency of health care and provide an important vehicle to advance patient-centered personalized care. The use of EMRs in care delivery is expanding rapidly, especially among large integrated health delivery systems. The amount of clinically relevant molecular data and the number of resources devoted to research on genomic medicine are increasing in parallel. While the U.S. health system is fragmented, the large health systems that are adopting EMRs are becoming increasingly integrated, especially in adopting and implementing practice standards. Thus, a significant opportunity exists to incorporate various aspects of genetics, genomics, and predictive tools into the development of these emerging systems to facilitate adoption and clinical decision making.
An integral component of PHC is the application of family history to clinical care. Interest in collecting family history data as a routine part of care delivery is growing, as knowledge advances in linking family history of disease to patient risk. The need for the development of better family history tools has been highlighted by projects at the Centers for Disease Control (CDC) and by the U.S. Surgeon General’s Family History Initiative. However, these efforts have not directly addressed the integration of tools into the real-world scenario of busy physicians and a multiplicity of health record systems, and do not provide an adequate breadth of data capture necessary for research. The need for new tools is apparent; however, no such electronic family history tools have yet been developed, despite the availability of suitable technologies.
An important component of HHS’s vision for the role of HIT in PHC is the use of computer systems to provide clinical decision support (CDS), defined as the act of providing clinicians, patients and other health care stakeholders with pertinent knowledge and/or person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care. The HHS report entitled Realizing the Promise of Pharmacogenomics: Opportunities and Challenges, the HHS Secretary’s Advisory Committee on Genetics, Health, and Society identified the need for CDS tools as an important to realizing personalized pharmacotherapy.
CDS has been leveraged for many decades now to improve clinical decision making related to traditional medical interventions and when compared to other approaches to improve practice, CDS has generally been shown to be more effective and more likely to result in lasting improvements in clinical practice. However, an interim report from an ongoing RAND study indicates that none of the commercial electronic health record systems currently provide CDS to support genomic medicine. Thus, it appears that the CDS might be an important aspect of the delivery of information for clinical decision-making; however there has been little research or investment in CDS to optimally deliver information to healthcare providers to support practice of PHC.
The nuances in clinical decision-making in PHC already render many care scenarios complex. Access to an EMR and the ongoing codification of medical knowledge (i.e., Clinical Practice Guidelines or CPGs) will be essential to addressing this growing translational gap. CPGs greatly facilitate, but are not sufficient for translating knowledge to practice. Almost 2000 active CPGs exist in the US National Guideline Clearinghouse and an individual CPG may encompass dozens to hundreds of clinical recommendations. These recommendations will rapidly expand in the era of genomic and personalized medicine, and thus codification of knowledge will be essential to increasing its access. EMRs offer a platform to translate codified knowledge into real-time actionable processes. Genomic data will need to be accessed with other patient data located in disparate locations within the EMR and evaluated in relation to a rule set. Real time actionable recommendations and CDS will need to be created and supported by an integrated and intuitive visual display of information.
The EMR also offers an exciting opportunity for population and health outcomes (T4) research. It represents an economically efficient means of obtaining phenotypic data and biosamples for generating genotypic data and for validating discovery data as well as assessing public health impact of these discoveries on long term outcomes. The EMR thus represents a potentially large increase in efficiency for obtaining phenotypic data and can also be an extremely efficient tool for patient recruitment and biosample acquisition. The data federation initiated by the HMO Research Network (HMO RN) offers an example of a venue for the type of outcomes research needed to provide evidence that a PHC strategy will provide value. The network is a consortium of 15 research centers, each affiliated with a non-profit integrated health care delivery system, all of which have or are developing ambulatory care EMR systems. In addition to the development of best practices for research administration for multi-site collaborations, the HMO RN has initiated efforts to establish a Virtual Data Warehouse (VDW), to simplify data sharing among network participants. We encourage partnerships between AMCs and networks such as the HMO RN and mechanisms to fund them such that these data can be obtained expeditiously.
As indicated above, by sharing data and coordinating their efforts it may be possible for AMCs/health systems, payors, and diagnostics companies to study the penetration, dissemination and implementation of new personalized health tools and their effect on
health outcomes. This, of course, would even more powerful if common standards of reporting from EHRs were possible across health systems. The NIH’s Clinical and Translational Science Awards program that seeks to fund 60 centers of translational research as a consortium by 2011 may provide the foundation of infrastructure and standards required to begin to address these issues across AMCs as has been done by the HMO RN. This may be an opportunity for any national agenda for PHC to leverage the investment and emerging architectures in that program that span the breadth from the laboratory to the community. With open access to data, scholars and policy makers could determine the factors that affect clinical uptake and the resulting economic and health impact. It would be difficult for any of these parties to make these determinations independently in a reasonable timeframe.
Early examples of these novel partnerships are beginning to emerge. For example, the Mayo Clinic has partnered with Medco to evaluate test results from over 1,000 patients taking Warfarin. In another example, Kaiser Permanente of California partnered with Genomic Health and USC’s Keck Medical School to underwrite a study of the clinical utility of Oncotype DX within the Kaiser Permanente coverage population. In each case, the payor has been willing to sponsor additional clinical research when prior published research indicated both clinical validity and a potential to save costs and the test was already commercially available to test. However, these opportunities are relatively rare as few diagnostic programs have the resources or long history of use to provide the preliminary support.
Figure 3: Specialized Centers for Genomic and Personalized Medicine.
AMCs, while well positioned to discover and develop new tools, lack the resources, infrastructure, and skills to bring new personalized health discoveries into the market place and ultimately into clinical environment. By contrast, diagnostic companies typically have the infrastructure to make tests widely available: high-volume regulatory-compliant labs, sample collection and tracking, regulatory expertise, relationships with payors, marketing and physician education capabilities, but often lack the resources to mount an effective research and development effort to create the “content” for new diagnostic tests. Through intellectual property licensing and sponsored research agreements, academia and industry have shown that they can form synergistic partnerships to advance personalized medicine. However, even with their combined skills and resources, it has proven extremely difficult to navigate a personalized medicine program through the entire “translational continuum”. At the same time, payors are motivated to see effective models of PHC implemented and have the infrastructure and access to longitudinal data to contribute to important research on diffusion and community health impact.
Specialized centers for genomic and personalized medicine in AMCs – perhaps modeled programmatically after the Centers for Excellence in Women’s Health Program at the NIH – can be instrumental in integrating, facilitating and catalyzing the needs of government, academic and industry stakeholders by providing:
Currently there are no structured programs in genomic and personalized medicine. Several institutions have made the commitment (Duke University, Vanderbilt, Harvard, Johns Hopkins, University of Utah, Ohio State University) but none has done so with federal support. Moreover, the tasks required, we would argue, are larger than that any single AMC can tackle. To bring about the transformation in health care the genome has promised will require assembling diverse stakeholders focused on the application and translation of genomics with a goal of improving the health of individuals and driving efficiency in health care. These centers will thrive on their interdiscipinarity. Specialized centers housing basic genome science laboratories, clinical researchers, informaticians, clinicians, economists, health policy makers and in partnership with industry (pharmaceutical and diagnostic companies), and with health systems that will enable the scientific output of the genome to cross the chasm between bench and bedside. A series of Centers that focus on specific aspects of the challenges that learn and participate with one another would, in our opinion, be a major step forward in developing and enabling the continuum of strategies required for the fullest impact of genomic and other relevant information on PHC.
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Kevin A. Schulman, MD
Ana Valverde Vidal, MBA, CFA
D. Clay Ackerly, MSc
Center for Clinical and Genetic Economics
Duke University School of Medicine
The fulfillment of the promise of personalized healthcare will likely require not only technology innovation but the adoption of new business and organizational models to allow for the new technologies to take hold in a disruptive fashion. At the root of the problem lays the question as to whether we have the right public policies and private strategies to allow for innovation to take hold in the healthcare arena. The current paper discusses a framework for considering this question, and proposes potential policy solutions to enable the adoption of technologies to yield improvements in both quality and costs.
New technologies offer the potential for revolutionary changes in the practice of medicine, from molecular diagnostic tests that detect disease before symptoms are evident to patient profiling techniques that help predict which patients are most likely to benefit from or be harmed by specific therapies. These approaches and the extensive data they require will need to be supported by a new information architecture. This system has been described as personalized health care—treatments and services targeted to the specific biology of the individual, leading to potentially significant improvements in patient care. Although this vision has been articulated for several years, researchers are slowly gathering the information required to support the adoption of specific technologies that will be the crucial building blocks of the system. Other aspects of this vision are less developed, and the investment theses required to bring new technologies to market remain speculative.
At the policy level, there are recurring questions of the correct approach to innovation in health care. Do we have the right public policies and private strategies in place to foster innovation in the health care system? At the core of these discussions is a question of whether personalized health care will require a new approach to technology assessment and dissemination, one that embraces the tremendous potential of the vision of personalized medicine. What is the role of technology innovation in health care, and what should be the public policy responses to innovation?
Technology development and diffusion can offer new opportunities for patient benefit. In assessing the role of technology innovation, one field of scholarship has explored the relationship between technology innovation and organizational innovation. This line of inquiry presents a useful framework for discussions of the broader policy questions related to personalized medicine.
New technology often is accompanied by new business models. In competitive markets, innovation in technology enables new business models to use the advances of the new technology to offer cost or quality advantages to the end user. When successful, these new combinations of technology and business strategy are able to supersede their predecessors. This issue has been examined in detail by Christensen, who assessed the relationship between technology innovation and organizational innovation in the computer disk drive industry.
Christensen’s concept of “disruptive innovation” begins with an assumption that consumer demand for a given technology is normally distributed, with the tails of the consumer preference curve representing high-end users with specific needs and price insensitivity and the low-end users with limited needs and price sensitivity. Firms already in the marketplace offer their products to all users but develop their technologies to meet the needs of the high-end users, their most valued customers. High-end users are thought to be the most profitable consumers and to be the most articulate about their needs. To satisfy the demands of this group, firms improve their technologies over time within the constraints of an existing business model, an approach Christensen termed sustaining innovation. The resulting products and services target the needs of the most lucrative segments of the market.
Christensen’s key observation is that so-called sustaining innovation leads firms to develop products that possess capabilities far beyond the needs of the average consumer. This strategy creates opportunities for new firms to enter the market with new technologies and business models that focus on the more limited needs of average consumers. When successful, these new firms can supplant the existing firms in a process called “disruptive innovation.”
There are many examples of disruptive technologies. One includes digital photography, which was disruptive to photographic film, as initial digital cameras had worse picture quality than traditional film and the computer tools available to edit and share photos were still in their infancy. However, the convenience of digital photography grabbed a new market niche, and soon the quality of digital photography improved and in many ways surpassed film photography. Other examples include minicomputers, which were a disruptive innovation to the mainframe market; personal computers were in turn a disruptive innovation to the minicomputer market. Mobile telephones were disruptive to fixed-line telephones. This dynamic process of firm entry and firm exit from markets offers tremendous potential benefits to consumers over time in terms of reducing costs and improving the quality of products and services available in the marketplace.
In the health sector, it is difficult to identify examples of truly disruptive technologies. Some have argued that home glucose monitoring, coronary angioplasty, and the nurse practitioner model are examples of disruptive innovations in health care. However, none of these technologies has been able to fully disrupt the market. None has fundamentally changed the system of primary care or fostered the development of new and innovative models of health care delivery. In most cases, these innovations have been unable to develop into the type of disruptive innovations we see in other markets when the new replaces the old. Instead, technology has generally added to existing systems in the manner of sustaining innovation. Physicians have fought the entry of the nurse practitioner model, and payment regulations restrict nurse practitioners to a primary care role. The business model to offer a real-time interface between home glucose monitoring and the physician office has taken years to evolve. Furthermore, angioplasty relies on the same hospital-based model as cardiac surgery; the procedure is simply performed by a cardiologist instead of a cardiac surgeon.
In short, there is a lack of solid examples of disruptive innovation in health care. It is not difficult to discern why this might be the case. The health care industry exists through a relationship between business and government that is different from the computer disc drive industry that Christensen observed. These interactions, in the form of regulations, professional standards, and administrative procedures, create opportunities for incumbents to support the status quo by erecting barriers to market entry. The typical firm bringing a disruptive innovation to market is unable to meet these established rules, since it characteristically offers products or services with a narrower or more limited scope, a different business model and potentially a different customer focus from that of incumbent firms. An unintended consequence of this system is an environment that supports sustaining innovation over disruptive innovation. The health care market does not have the advantage of disruptive innovation to drive cost and quality improvements in the marketplace.
We have previously proposed the adoption of the definition of regulatory controls (“regulations”) offered by Berenson. Further, we have adopted this framework for both the public and private regulators in the healthcare market as administrative barriers. Regulation has the effect of developing a set of rules and standards for a market, including rules governing market expansion and a process for firm entry into a market. Regulations in health care include the governance of third party payments in health insurance a medical liability system based on the standard of care, or rules on hospital markets (certificate of need requirements). As we discussed above, new entrants may not meet these administrative criteria or may not be able to navigate this process. As a result, all of these regulations may inhibit entry of new business forms.
Market entry is a dynamic process. Given an equal opportunity, entry will be greater when profit opportunity is greatest and barriers to entry are lowest. Given the high cost of most services in health care and the inherent profitability of the system, the health care market should be an attractive opportunity for firm entry. Also, given the quaternary care model rampant in the marketplace, existing firms have developed capacity that outstrips the needs of most consumers (and have failed to provide the front-end services demanded by most consumers). So the lack of entry should not be ascribed to a lack of interest in the market by investors.
There is a constraint on entry in this simple model—the cost of entry. The cost of entry can be seen as the cost of complying with administrative processes to create a new business model, or the cost of complying with regulatory standards that require entrants to achieve the same form or capabilities as incumbents to enter the market. These requirements can increase the cost of entry to the point where entry is no longer attractive to new firms. Alternatively, these factors may alter the risk of any investment by increasing uncertainty regarding approval of a new business model.
The relative lack of firm entry has consequences throughout the health care marketplace, on both incumbents and new entrants. In the absence of new market entrants (or a viable threat of entrants), organizational innovation of existing firms lags or disappears. This lack of organizational innovation on the part of incumbent firms compounds the cost and quality consequences of firm trajectories comprised of sustaining innovation on the marketplace.
This discussion has emphasized the potential negative consequence of current regulatory and governance practices on the health care marketplace. Clearly, regulations serve an essential role in the healthcare system. However, by establishing a threshold above average consumer performance expectations, regulations may also preclude quality-enhancing, lower-cost innovations from entering the market. What can policy makers do to promote innovation and allow for these new technologies to enter this regulated marketplace? Another way of framing this question is, how should we take account of the negative externalities of a regulatory scheme on the marketplace?
One simplistic framework would suggest we should support adoption of disruptive innovations over sustaining innovations. This approach is clearly supported by the theoretical framework, but it contrasts with current technology adoption models, in which most technologies that reach the market are simply sustaining innovations that “add on” to existing technologies. For example, greater availability of angioplasty is now associated with more revascularization procedures per population among people older than 65 years. Similarly, the availability of more magnetic resonance imaging (MRI) units does not reduce the number of computed tomography (CT) scans performed.
Supporting disruptive over sustaining innovations is not a simple task. Disruptive innovation is not a result of technology innovation; rather, it is a combination of business and technology innovations. It is unclear from an assessment of a technology itself whether the business model is one that offers the potential for disruption. Second, although many products purport to be disruptive innovations, true disruptive innovations can only be identified in arrears when markets have changed as a result of the innovations. Even with these limitations, however, potential pathways forward could emerge.
First, not all types of innovation are, or should be, of equal interest to policy makers. In most markets, sustaining innovations are ones that enter the market continuously. New versions of Microsoft Windows and new models of the Apple iPod come to market with greater capabilities than previous versions at equal or lower prices. From this perspective, the regulatory approach could be one that expects sustaining innovation as a condition of remaining on the marketplace and limits the financial rewards to products or services over time. For example, imagine if we lowered the price for an MRI each year based on an index of computer costs in the broader marketplace.
The treatment of potentially disruptive innovations, however, could be considered quite differently. In the health care environment, disruptive innovations face tremendous uphill battles, with new combinations of technology and business models that have not previously existed. Based on the theory presented to this point, regulators could consider facilitating entry of these firms and technologies as a means of enhancing the price and quality of health care services for consumers. At the same time, regulators should curtail these incentives for firms and products that do not prove to be disruptive. This suggests that broader regulatory reform would accomplish the former goal of allowing access but at the expense of many sustaining innovations benefiting from the new framework. An alternative would be a time-dependent facilitated pathway for market entry that is unique to the regulatory framework we have constructed for health care. For example, policy makers could determine a mechanism to identify technologies with potential to become disruptive and to allow these technologies to enter the market in a disruptive fashion.
One such mechanism would be the creation of an Office of Personalized Medicine (OPM) charged with reviewing new technology applications to determine if they have the potential to become disruptive. With data and business cases presented by the owners of the technologies, the OPM would assess the ability of an innovation to transform health care delivery and treatment and to eventually lead to improvements in both outcomes and cost. Such a review mechanism would encourage technology owners to think beyond the novel characteristics of their proposals to consider early on other important business and operational features that would eventually determine if an innovation goes beyond being sustaining to become truly disruptive.
For innovations deemed disruptive by the OPM, policy makers could play an important role in providing incentives for these technologies to successfully enter the market. Owners of disruptive innovations could receive vouchers for accelerated review, or the innovations could command a premium in reimbursement negotiations. Regulators could even define a special regulatory pathway for these technologies, with distinct market approval and reimbursement criteria that would more closely align with the characteristics of these technologies. As an alternative, regulators could carve out “safe harbors” for these technologies, giving the owners of such innovations flexibility and time to change the prevailing business models in their sector. Following a model similar to ”coverage with evidence development” (CED) in the Centers for Medicare & Medicaid Services (CMS), innovations considered disruptive could be subject to special reimbursement mechanisms for a given period of time, altering the prevailing incentive system in the market place and enabling the new technology to take hold. For example, under the current encounter-based reimbursement system, health care providers have little incentive to acquire technologies that enhance service but reduce the number of encounters at the clinic, because such innovations would likely result in reduced revenues for the provider. Under a “safe harbor” mechanism, health care providers who use an OPM-labeled disruptive technology to remotely monitor patients would likely be able to bill for the informal communications that such technologies would generate (eg, e-mail consultations, phone conversations).
One clinical application for personalized medicine is targeted therapy for individual patients. The potential implication of this approach is to offer improved safety and efficacy for individual patients and have an immediate economic impact by avoiding therapies with low potential to be efficacious (although one would expect manufacturers to respond to this technology in terms of development and pricing strategies over time).
Currently, the regulatory pathway for development of diagnostic tests for personalized medicine applications is controversial depending on whether the test or the information from the test kit are the product. A company seeking approval for a novel molecular diagnostic test for which the test kit is being marketed requires approval from the Center for Devices and Radiological Health (CDRH) at the Food and Drug Administration (FDA).” CDRH classifies devices into three regulatory classes based on the anticipated use of the technology and the inherent risk. The class assignment determines the requirements for approval as well as the complexity of the marketing approval process (either premarket notification or the more stringent and lengthy premarket approval).
Alternatively, in vitro diagnostic devices can be developed and marketed under the Clinical Laboratory Improvement Act (CLIA) of 1988, which governs “laboratory-developed tests” (ie, tests performed in a single site where the test kit is not marketed; samples can come to the laboratory for this service from anywhere in the country). CLIA establishes three categories of testing on the basis of the complexity of the testing methodology: waived tests, tests of moderate complexity, and tests of high complexity. Laboratories performing moderate- or high-complexity testing must meet requirements for proficiency testing, patient test management, quality control, quality assurance, and personnel. However, CLIA-governed tests do not require FDA approval.
The distinction between these two separate pathways has created a special area of controversy for personalized medicine. Using gene expression technology, scientists have reported an ability to classify patients based on risk of disease recurrence. Although the technology is in its infancy, the FDA has raised concerns about the regulatory pathway for in vitro diagnostic multivariate index assays (IVDMIAs). These devices combine the values of multiple variables using an interpretation function to yield a single, patient-specific result that is intended for use in the diagnosis of disease, or in the cure, treatment or prevention of disease; and they provide a result with a nontransparent derivation that cannot be independently derived or verified by the end user.
Most IVDMIAs in the market are laboratory-developed tests marketed through the CLIA route, that is, tests developed by a single clinical laboratory for use in that laboratory alone. Given the strategy of not marketing the test kits and performing the tests at a single site, these tests did not fall within the scope of lab tests over which the FDA had generally exercised enforcement discretion. Concern over this space has led to a proposal to begin regulation of this market by the FDA, with the issuance by CDRH of draft guidance in July 2007. This regulatory issue has not yet been resolved.
In addition to regulatory approval, companies seeking to enter the market with new molecular diagnostic tests also must work with CMS to obtain reimbursement for their products. This separation of approval and reimbursement results from the different missions assigned to both FDA (approval) and CMS (reimbursement). FDA approval is based on meeting statutorily defined criteria of safety and effectiveness, and literally provides permission to market a product in the US. Implementation of these criteria varies by product category, but serves as a minimum set of criteria for entry into a market. FDA review and approval is not an assessment of value, uniqueness, nor a recommendation for use or funding of a product or technology. CMS review, on the other hand, is based on a statutorily defined standard of “reasonable and necessary” for the treatment of illness or injury. This standard for reimbursement is an assessment of whether a technology should be used in the care of Medicare beneficiaries. It is a relative standard and can be influenced by the existence of an unmet medical need, the existence of comparative therapies and the value of a new technology. In principle, the separation of approval and reimbursement provides an easier entry to the market for a technology (approval), and allows the sale of a product even if there is no reimbursement by CMS for the technology.
The CMS reimbursement process itself is a complex one. The process governs three key issues—coverage, coding, and payment: As we mentioned above, to be covered by Medicare under the Social Security Act, the new technology must be “reasonable and necessary” for the treatment of illness or injury; however, technologies that are predictive may not meet this standard since prevention is not considered medical treatment. Second, as medical claims processing has become automated, assignment of specific codes for new medical technologies has taken on a unique importance in the reimbursement process. If specific codes are not available for a new technology, payment for the technology cannot be differentiated from previous technologies. Finally, payment schemes in Medicare can vary from bundles (inpatient DRG payment) to specific (outpatient laboratory testing). When the technology will be reimbursed separately, a payment rate must be established.
Coverage, coding, and payment decisions are not necessarily made in any particular order, and the decisions can span a 12-month period. To add to the complexity, different components of CMS are responsible for different aspects of these decisions. The Office of Clinical Standards and Quality oversees national quality initiatives and includes the Coverage and Analysis Group and its three divisions, which are responsible for developing national coverage policy. Payment and coding decisions are developed by the Center for Medicare Management, with two groups and ten divisions potentially involved in the process. In addition, there is the possibility that different regional decisions can be made about these issues in the absence of a national decision.
In recent years, CMS has shown an awareness of the need to streamline this process and has taken several steps aimed at improving it. In 2004, the Council on Technology and Innovation (CTI) was established under the Medicare Prescription Drug, Improvement, and Modernization Act to serve as a coordination point for new medical technologies. In August 2008, the CTI published the Innovators’ Guide to Navigating CMS to assist stakeholders in understanding the processes used to determine coverage, coding, and payment. While serving to help technology developers understand the CMS process, the CTI group is not an expedited pathway to market for new technologies.
CMS has launched several demonstration projects to test innovations in reimbursement policy. For example, the CED policy provides an abbreviated pathway to Medicare coverage while still requiring further evaluation of a new technology. At the same time, CMS is working to make coding processes more efficient and has implemented a number of initiatives to reform one of its major coding systems, the Healthcare Common Procedure Coding System (HCPCS), while moving to replace the International Classification of Diseases, Ninth Revision, with the more flexible and clinically relevant Tenth Revision.
While these actions are steps in the right direction, a broader approach could help accelerate the access of disruptive innovations to the market. The OPM could play a significant role as a unifying and coordinating agency, acting as the single point of contact through the Department of Health and Human Services for technologies deemed disruptive. The OPM would help expedite the approval process by expertly understanding all the potential pathways involved and by helping the technology navigate the regulatory mesh. In this role, the OPM would act as an ombudsman for disruptive innovations that are seeking market approval. As described above, this process would not be open to all potential innovations but rather to those that, based on the technology characteristics and the proposed business model to implement them, are considered to have disruptive potential.
The consideration of disruptive potential would only be granted for a fixed period of time. If after such period the technology fails to deliver its disruptive promise and its novel business model fails to take hold, the OPM could elect to levy some penalties on the company, either monetary (to payback the competitive advantage gained through early market entry) or other (such as closing the OPM pathway for future innovations from the company for a given period). The intent is to make the penalty significant enough that companies will exercise best efforts to deliver on the disruptive promise of their innovations.
The OPM could build on these changes and work in tandem with the Council on Technology and Innovation, as well as the CMS Office of Research, Development and Information. Close communication between these groups would ensure tight coordination through the regulatory and reimbursement approval processes. The OPM could also work with these groups to expand current initiatives and create new, larger demonstration projects or safe harbors for disruptive innovations. The OPM would also have to follow a strict timeline to ensure a speedy decision about whether a technology will meet the OPM standard.
Much of this policy assessment has focused on the unique role of the Federal government in the health care marketplace. Private health plans often adopt much of their coding infrastructure from Medicare and can select to follow Medicare in coverage decisions. Thus, efforts to adopt these policies by the public sector will have effects on the private sector, as well. Creating transparency in the rationale for OPM decisions and communicating the results of evaluation of technology implementation can also help to shape decisions in the private sector. Separate study of the role of the private sector in fostering disruptive innovation merits further consideration.
Personalized medicine offers the potential for revolutionary change in the practice of medicine. It also provides a unique window into the relationship between new medical technologies, new business models for health care delivery, and the role of government in this unique marketplace. Using personalized medicine as a test of disruptive innovation in health care, we find the need for a different approach to these technologies in order for them to achieve their full potential. Achieving this result, however, is fraught with difficultly, as disruptive innovations are deemed truly disruptive only in arrears. Thus, our approach offers the potential that designations of a technology as potentially disruptive would provide competitive advantages to products or services that may not merit this consideration. A robust framework for continuing assessment (and the potential for penalties on misrepresented technologies) might help protect the integrity of this process. However, the benefits of unlocking the health care market to disruptive innovation seem to be worth the risk.
Frank L. Douglas PhD, MD - Senior Fellow
Lesa Mitchell - Vice President, Advancing Innovation
Ewing Marion Kauffman Foundation
In making a credible business case for investors and industry stakeholders to view personalized medicine as a viable business model, we not only must create excitement in the promise of personalized medicine, but also must find viable alternatives in addressing the barriers or risks surrounding the biomedical discovery and development models of today. Some of the risks we identify include IP issues, difficulties in validating targets, ability to rapidly achieve proof of concept, navigating the famed “Valley of Death,” and inefficiencies in the current clinical development process, as well as the need for new industry business models that predict an attractive return on investment. In this paper; however, we limit our discussion to the potential for personalized medicine to create efficiencies in the preclinical and clinical phases of drug innovation and generate economic returns. We also introduce unique industry collaboration mechanisms with nonprofit disease-focused organizations that serve an important role in de-risking aspects of drug discovery and clinical development in their respective disease sectors, as well as bridging early-stage funding needs. These collaborations and de-risking strategies could provide an important model for the further development and growth of the personalized medicine sector.
With respect to definition, we shall use the more general term “stratified medicine,” of which personalized medicine is the individualized member of a spectrum that includes empirical medicine, stratified medicine, and personalized medicine. In the latter two, a biomarker is critical in identifying sub-populations or strata of patients that can benefit from a therapeutic intervention that is related to that biomarker, or develops a therapy that specifically benefits an individual who possesses that biomarker. A biomarker also may identify strata of patients that might be susceptible to side effects from a particular therapy.
The increasing interest and excitement over the promise of stratified medicine is based on the promise of genomics, proteomics, and metabalomics to enable the researcher to identify genes and gene products that are relevant for disease, and to instruct the creation of the best therapies for patients with the respective diseases or side effect susceptibilities. This comes on the heels of the biopharmaceutical industry struggling to meet the increasing demands on its R&D investments while facing declining levels of productivity and innovation, and loss of revenue due to patent expirations. More than three dozen drugs are losing patent protection between 2007 and 2012, with an anticipated $67 billion loss in sales for the large pharmaceutical companies to generic competition. The industry has responded with pharmaceutical companies increasing R&D spending by 160 percent—from $15 billion to $39 billion from 1995 to 2005—and with similar increases in the biotech industry, with a 150 percent increase—from $8 billion to $20 billion—in R&D spending during the same period. Meanwhile, submissions for regulatory approval of new drugs and therapeutic indications declined from eighty-eight in 1995 to forty-four in 2004. Innovation in the sector also is continuing to decline, with only seventeen new molecular entities (NME) and two biologics approved in 2007, at a cost of $2.5 billion per NMEs approved, which is the lowest innovation-to-productivity level since 1983, when twelve NMEs were approved at a cost of $266 million per NME. (See Figure 1.)
Figure 1: A comparison of biotech and pharmaceutical R&D productivity. Source: Parexel’s Pharmaceutical R&D Statistical Sourcebook 2005/2006; Defined Health Analysis. NME, new molecular entity.
The decline in productivity and innovation has increased M&A and partnering activities among large biopharmaceutical companies at a record high in the last few years, with $150 billion generated through M&A transactions in 2006 and $22 billion in partnering deals for the same period. The strategy of focusing on a few drug candidates from their combined pipelines, with a focus on producing several “blockbuster” drugs that will generate at least $1 billion individually in peak annual global sales and be marketable to fifteen million patients or more, has not improved their productivity levels, resulting in increased delays in development time/costs and increasing cancellations of projects at later stages of development. Additionally, increasing regulatory pressures to conduct more lengthy and complex trials has added to the current $1 billion in drug development costs, of which half are attributable to the time value of money—that it takes eight to twelve years to get a drug to market. It is also the case that, even after a drug is marketed, 70 percent of the approved drugs do not meet or only match their R&D costs. Thus, with lower efficacy levels (40 percent to 60 percent) of most blockbuster drugs, as well as some high-profile successes of stratified medicines such as Genentech’s Herceptin and Novartis’ Gleevec, the industry is beginning to realize the deficiencies in the economics of the blockbuster business model, which is one of the drivers of increased interest and investment in the development of stratified medicine.
The identification of clinical biomarkers or diagnostics linked to gene expression profile of individual or sub-populations of patients is an essential feature of stratified or targeted medicine. This type of research attracts and often is best pursued by small biotech companies. One of the main challenges for these companies lies in the lack of early-stage funding to translate new discoveries into the clinic and, ultimately, to commercialization. With a narrowing access to public capital and venture capitalists increasingly reticent to invest in early-stage technology companies, smaller biotech companies increasingly are engaging in alternative financing mechanisms that often compromise their value in terms of access to future returns.
Various alternative financing mechanisms, including partnering and out-licensing, sale of royalty streams, and Contract Research Organization (CRO) financings, all include investment capital in exchange for future royalty rights or equity shares in the biotech company. Other innovative financing mechanisms do exist, such as collaborative development financing (CDF), where an investor provides capital and clinical expertise in exchange for licensing of a company’s pipeline, while the company maintains the “exclusive right to reacquire the drugs,” at prices determined at the time of the agreement. An example of a CDF arrangement is the 2006 Symphony Capitol and Isis Pharmaceuticals (“Isis”) collaboration, where Isis received $75 million to continue the development of its cholesterol-lowering (Phase II) and diabetes drug products (two in pre-clinical) and agreed to an exclusive purchase option for its products at an “annual rate of return that averages 32 percent and is 27 percent at the end of the anticipated” collaboration period. In 2007, Isis exercised its repurchase option, paying Symphony $131 million. Isis, in turn, executed collaboration agreements with Johnson & Johnson and Genzyme for the three molecules in the contract. These arrangements included upfront fees in the aggregate of $370 million with potential milestone payments of nearly $2 billion. (See Figure 2.)
Figure 2: Alternative financing sources for biotech companies
Most of the alternative financing mechanisms, however, are not necessarily accessible for many early-stage companies, as these companies may not have the types of products that meet the returns desired by larger companies and venture capitalists. A case in point is the lack of investment in orphan drugs or neglected disease areas. Aside from Genzyme, which has been one of the few successful orphan drug-focused companies with three drugs on the market, including a $1 billion-a-year treatment for Gaucher, and Novartis’ Gleevec, a treatment for chronic myeloid leukemia with $2.5 billion in 2006 sales, therapeutic discovery and development for orphan and neglected diseases often have been the bane of nonprofit foundations and patient advocacy organizations, many of whom have increasingly taken on a new role of bridging early-stage funding and development gaps in disease areas where the patient population often is less than 200,000, the FDA definition of orphan drugs.
To uncover mechanisms by which venture capitalists and biopharmaceutical companies—whose measures of success ultimately are captured in their return on investment (ROI)—could be incentivized to participate in developing stratified medicines, we have looked at the various activities of nonprofit foundations. In our view, these foundations, whose ultimate success is in bringing therapeutics and diagnostics to their patients, increasingly are engaged in “de-risking” strategies. In some cases, their target patient populations fall within the orphan disease category. Their strategies, however, not only fill important funding gaps but also have the objective of increasing the probability of success through their support activities.
Although the nonprofit foundations traditionally provide basic research grants to increase scientific knowledge in their disease sectors, some have since adopted a more investor-like approach—early-stage funding for proof of concept and target validation, as well as project management support and access to their network of scientific experts and research clinics critical in translating discoveries into the clinic.
One example of nonprofit disease organizations that provide early-stage funding for proof of concept and target validation is the Muscular Dystrophy Association (MDA). Through its Translational Research Program (TRP), MDA’s approach is to stratify its patient population based on various sub-sets of the disease, including Duchenne Muscular Dystrophy (DMD), Myotonic Muscular Dystrophy (MMD/DM), Fascioscapulohumeral Muscular Dystrophy (FSHD), Spinal Muscular Atrophy (SMA), Pompe Disease, and ALS, and seek to develop targeted therapies for the sub-patient populations. Of the $32 million in MDA’s 2007 annual R&D budget, $6 million was dedicated to its largest collaboration effort with ALS Therapy Development Institute (ALS-TDI), a nonprofit corporation, and $7 million was dedicated to industry collaborations. Muscular Dystrophy Association’s TRP provides four types of funding mechanisms for the industry—IND Planning Grant, Clinical Research Training Grant, Infrastructure Grant, and Corporate Grant—to catalyze early-stage development leading up to INDs and Phase I/II clinical trials. (See details of collaboration deal examples at Figure 3.)
|Disease Type & Company Grantees||Collaboration Description and Status|
|DMD/PTC Therapeutics||MDA provided PTC with an initial $1.5 million grant, enabling the company to begin developing PTC124, a medication with the potential to treat a significant portion of patients with DMD. In July 2008, PTC entered into a collaboration deal with Genzyme, where Genzyme will provide $100 million to PTC, with potential additional payment options, and will commercialize PTC124 outside the United States and Canada.|
|Pompe Disease (acid maltase deficiency)/Myozyme (approved 2006) from Genzyme||MDA provided supplemental funding of $150,000 to cover unreimbursed costs of patients participating in Genzyme’s clinical trials for Myozyme in infantile-onset Pompe disease. In 2007, Genzyme also found Myozyme effective for older children and adults with the disease.|
|ALS Therapy Development Institute (ALS-TDI)||MDA is collaborating with ALS-TDI to comprehensively characterize disease progression in ALS using animal models of neurodegeneration and ALS clinical samples. MDA committed $6 million annually for three years.|
To qualify for the TRP grants, the collaborating company is required to provide matching grants and agree to a collaboration contract that includes royalty-sharing agreements and march-in rights if the projects fail to meet milestone targets. Similar to a majority of the nonprofit disease organizations, MDA neither takes equity positions in the companies with which it collaborates, nor pursues IP ownership.
Another example of nonprofit disease organizations providing early-stage funding to industry includes the Industry Discovery & Development Partnerships (IDDP) Program of the Juvenile Diabetes Research Foundation (JDRF). IDDP’s main focus is to translate scientific discoveries into the clinic and support commercialization of therapeutics to treat type 1 diabetes. Of its $160 million research budget in 2008, $16 million will be dedicated to industry partnerships, which is a marked change. Previously, 100 percent of its research funding went to support basic science and exploratory research within academia. To date, IDDP has fostered twenty-four collaborations with industry, totaling $30 million in IDDP grants. IDDP’s development partnerships are generally two- to three-year contracts, and “are intended to provide support for promising mid-stage research programs (i.e., advancement of a pre-clinical-stage program to clinical trials, or “proof-of-concept” Phase II clinical testing of promising therapeutics.” By funding early-stage testing and validation of research, JDRF’s model of “de-risking” works to make it possible for its industry collaborators to advance their compounds from proof of concept to clinical development, attract additional financing, and eventually secure global licensing and marketing alliances with larger pharmaceutical companies. By funding and providing development support of early trials through IDDP, JDRF also sees this as a way to build evidence in persuading public and private payors to cover these novel technologies. A case in point is IDDP’s collaboration with Tolerx. JDRF provided early-stage, multi-million dollar funding for proof of concept trials in both animal models and early human trials for anti-CD3 antibodies (Otelixizumab) for the treatment of early-stage Type 1 diabetes in collaboration with academic researchers in the United States and Europe. To catalyze further development and commercialization of Otelixizumab, IDDP invested $3.5 million in an equity stake during Tolerx’s latest round of fundraising to conduct Phase II trials. This is the first project where IDDP has taken an equity position in a collaborating biotech company. As of October 2007, Tolerx entered into a strategic alliance deal with GSK to take the antibody through Phase III trials, with a total deal value potential up to $155 million. Figure 4 below also exemplifies the significant commitment IDDP has made to companies to support discovery, development, and commercialization of therapeutics and devices for type 1 diabetes.
Figure 4: IDDP Discovery and Development Pipeline
Few nonprofit disease organizations have created wholly owned nonprofit venture affiliates to navigate through the challenges of translating early-stage discoveries into the clinic or bridging the “Valley of Death.” These entities serve as catalysts on various scales, not only by providing variable funding options from annual to multi-year commitments averaging from thousands to multi-millions of dollars, but also by providing mechanisms to address the development challenges. These include: providing project management expertise and scientific, clinical, and development networks (in some cases CRO outsourcing networks) that can assist the collaborators. In terms of return on investment, most do not take equity positions in the companies they collaborate with; instead, some deals are royalty-based, in which the organizations get a multiple back if the drug is approved and, in some cases, additional compensation for extraordinary sales results. Additionally, in cases where collaboration programs suspend due to milestone failures, some organizations obtain worldwide rights to develop the products with an agreement to negotiate royalties to the original collaborator once their investment is recouped.
An example of a nonprofit disease organization that has created unique project management and target validation mechanisms is the Multiple Myeloma Research Consortium (MMRC), a supporting organization of the Multiple Myeloma Research Foundation (MMRF). Through a collaborative contractual arrangement with its fifteen research centers, the MMRF’s strategy is to incentivize biopharmaceutical companies to collaborate on the development of new drugs and therapies. The MMRC’s tri-focus on genomics and credentialing of molecular targets, validation of drugs, and its offering of multi-site clinical trial capabilities creates efficiencies that are critical in de-risking early-stage proof of concept and target validation. One of the MMRF’s strategies is to identify genetic complexities of multiple myeloma and to identify molecular targets by analyzing the MMRC’s tissue bank and patient data bank on disease onset and progression, with the goal of personalized medicine development. To assist in the process of validating new targets, the MMRC has created screening tools—including a panel of twelve extensively characterized myeloma cell lines with full genetic and biological characterization—to screen new drug candidates. The MMRC also has funded the Multiple Myeloma Genomics Initiative, investing $8 million in research funding over the past four years to analyze 250 patient tissue samples via gene expression profiling, comparative genomic hybridization and exon re-sequencing. To expedite and create efficiencies in conducting multi-site clinical trials of novel and combination therapies, the MMRC has created uniform contracts, clinical trial agreements, and correlative sciences agreements. (See Figure 5.) To further expedite the process, the MMRC provides supplemental project management to accelerate projects from protocol concept through trial conduct and provides clinical research coordinators for the MMRC members. The MMRF sees its main function as an integrator and facilitator of research and collaboration among biopharma companies with the research centers. Since 2003, the MMRF has helped bring four drugs to market, including Millennium Pharmaceutical’s Velcade in 2003, Celgene Pharmaceutical’s Thalomid® and Revlimide® in 2006, and Millennium Pharmaceutical/J&J Pharmaceutical’s Doxil® in 2007,  and has supported more than thirty compounds and combinations in trials or pre-clinical studies to date.
Figure 5: MMRC Clinical Trials. MMRC Trials and the year in which they have opened. A total of 15 trials have initiated in the MMRC since 2005. Abbreviations: R: Relapsed; R/R: Relapsed/Refractory; Rev: Revlimid; Dex: Dexamethasone; Vel: Velcae; IST: Investigator-sponsored trial. Unless marked as IST, all trials are company-sponsored. **Trials expected to open by year-end 2008.
From a funding perspective, 93 percent of the MMRF’s annual budget goes to research and related programming. Of these, in 2007, the MMRF earmarked approximately $15 million for R&D, with $2 million allocated for direct funding to biotechs.
One of the leading examples of a nonprofit venture affiliate is the Cystic Fibrosis Foundation Therapeutics, Inc. (CFFT), a wholly owned venture arm of the Cystic Fibrosis Foundation (CFF). CFFT’s focus is to develop stratified medicine based on CF-related genetic mutations, of which there are 1,400 on a single gene. To date, CFFT has successfully identified and is working on the development of therapies that target the basic defect of the disease, as well as those that will provide better options for disease management. Therapies that target the basic defect are based on various genetic mutations, including Delta F508, a genetic mutation present in 90 percent of cystic fibrosis (CF) patients, and G551D, which is present in 10 percent to 30 percent of CF patients. CFFT’s strategy is to invest in early-stage discovery and development. Their funding ranges from $50,000 to $25 million, with an average of $2 million to $4 million per year, with some multi-year commitments averaging $15 million to $20 million. CFFT’s successes in aiding drug discovery are measured in terms of increasing its pipeline, which has grown to more than thirty drug candidates. CFFT administers the collaboration contracts based on milestone successes, with pull-out rights for failures. It also invests in a wide range of technologies, from target identification, novel screening platforms, detection of new chemical compounds, and screening of existing compounds and drugs. In terms of return on investment, CFF does not take equity positions in the companies with which it collaborates; instead, some deals are royalty-based, in which CFF may get a multiple back and/or a percent of revenue if the drug is approved and, in some cases, receives additional compensation for extraordinary sales results. Should the development program suspend due to milestone failures, CFF obtains automatic worldwide rights to develop the product with an agreement to provide some royalties to the original collaborator once CFF’s investment is recouped. 
An example of CFFT’s largest industry collaboration to date includes a multi-year collaboration with Vertex Pharmaceuticals, Inc. (Vertex), in which CFFT provided an aggregate of $76 million from 2000-2008 to support the development of two compounds (VX-770 and VX-809), which target the functional restoration of the cystic fibrosis transmembrane conductance regulator (CFTR) protein, the protein responsible for the progression of cystic fibrosis. Through this collaboration, Vertex was able to develop VX-770 from discovery to Phase IIa, where it focused on how VX-770 affects CFTR protein function and clinical endpoints in CF patients with genotype G551D (affects approximately 4 percent of the 30,000 CF patient population in the United States), achieving positive interim results in March 2008. See other examples of CFFT’s portfolio in Table 6.
|Collaborating Company||Project Description||CFFT Investment|
|EPIX Pharmaceuticals, Inc.||Use of EPIX proprietary PREDICT technology to create a computerized 3-D model of CFTR protein, using the model to identify sites within Delta F508 mutation of CFTR and search their library of chemical compounds for a small molecule that may work on those sites. In 2007, EPIX discovered a molecule that, in the lab, restores function to Delta F508 CFTR in cells.||$52 million including an original $18 M research award over 3 years and a subsequent discovery and development award over 7 years.|
|FoldRx Pharmaceuticals, Inc.||Use of a novel screening platform to detect new chemical compounds that could improve the function of misfolded proteins, like the Delta F508 mutation.||$22 million over five years to use its high-throughput screening platform to discover and develop new compounds.|
|CombinatoRx, Inc.||Screening approximately 2,000 approved drugs individually or in combination for its impact on correcting Delta F508 in the lab.||Commitment up to $13.8 million.|
|Vertex Pharmaceuticals, Inc.||Development of VX-770, its first CFTR modulator clinical compound, which entered Phase II clinical in 2007. Also developing second compound known as “correctors,” VX-809.||$76 million to date for VX-770 and VX-809.|
Few large foundations, like the Gates Foundation through its Global Health Program (GHP), utilize independent nonprofit venture intermediaries to finance and manage the discovery and development of innovative therapies for neglected diseases affecting the developing world. GHP’s goal through its venture intermediaries is to accelerate R&D and provide global access to new vaccines, drugs, and other health tools that combat infectious diseases, including malaria, HIV/AIDS, TB, and pneumonia. The venture intermediaries serve “as a virtual pharma company looking for good ideas, progressing them to the point where proof of concept is achieved,” and de-risking projects to the point that big pharma may be incentivized to collaborate in developing the therapies. GHP is involved in the portfolio management of the venture intermediaries, but the intermediary conducts the project management. To date, GHP has committed $6 billion in global health grants to organizations and researchers worldwide, including $200 million to Medicine for Malaria Ventures (MMV) over five years.
The venture intermediaries, often called Product Development Public-Private Partnership (PDPs) entities, operate globally with a focus on providing R&D funding and project management expertise in the neglected disease areas such as Malaria and TB. MMV is one of the nonprofit venture intermediaries that the Gates Foundation and GHP funds. MMV’s role is to facilitate the discovery and development of innovative anti-malarial drug candidates into clinic. MMV does not conduct discovery or development itself but provides financial and project management support requiring milestone achievements and quick termination rights for those who fail to meet milestones. In return for its investments, MMV often seeks IP rights from the discovery and development projects it funds. In projects that it funds through commercialization, MMV will often negotiate for the delivery of drugs to poor developing countries at "no profit, no loss" basis. It also will retain the ability to license to multiple drug manufacturers. In cases where industry partnership fails during the development phase, MMV will either take full ownership of the IP or require an exclusive, worldwide, transferable license that is royalty free in malaria endemic countries.
In 2007, MMV invested more than $37 million in nearly forty projects that include four projects in late-stage Phase III clinical trials and three mini-portfolios with GlaxoSmithKline (GSK) (three projects), the Broad Foundation/Genzyme (five projects), and Novartis Institute for Tropical Diseases (NITD)/Novartis (nine projects). Clinical trials MMA supported in 2007 include: Collaboration with Novartis' submission to Swissmedic for approval of its first ACT (Coartem® Dispersible); Eurartesim® (with Sigma-Tau Pharmaceuticals, Inc.), which received orphan drug designation in the U.S. in 2006 and by the EU in 2008; and MMV/Shin-Poong Pharmaceuticals collaboration for Pyramax®. MMV has a wide platform in its collaboration with Shin-Poong, covering two pivotal trials for Plasmodium falciparum, trials for P. vivax, and also a new formulation specifically for small children.
MMV also has engaged in identifying new targets based on the genome sequence of Plasmodium falciparum, the main cause of human malaria, and has collaborated with Novartis and GSK to screen their collection of compounds that may be able to kill the malaria parasite. Out of more than three million compounds tested, more than 10,000 showed interesting activities at low micromolar concentrations. (See Figure 7.)
|Collaborating Company||Project Description||Amount Invested in 2007|
|MMV/Novartis (Coartem® Dispersible)||Phase III trial—Development of a pediatric dispersible tablet, Coartem® Dispersible, containing a fixed-dose combination of artemether and lumefantrine. (ACT)||$1.68 million|
|MMV/Sigma-Tau Pharmaceuticals, Inc. (Eurartesim®)||Phase III trial—Fixed-ratio drug combination of dihydroartemisinin and piperaquine, being developed to treat uncomplicated malaria.||$2.85 million|
|MMV/Shin-Poong Pharmaceuticals, Inc.||Phase III trial—Fixed-dose oral combination of artesunate with pyronaridine. The course of treatment is once a day for three days. Currently carrying out pivotal Phase III studies in Plasmodium falciparum and P. vivax patients to confirm safety and efficacy. A specific pediatric granule formulation also is being tested for safety and efficacy.||$12 million|
|MMV/GSK mini-portfolio(five projects)||Engaged in five separate projects ranging from 1) development of next-generation pyridones derivative; 2) development of a second-generation macrolide; 3) identification of additional potent falcipains inhibitors; 4) high-throughput screening assay to study the effect of the entire GSK library of compounds on the growth and death of P. falciparum (To date, the majority of the 1.5 million compounds have been screened in a high-throughput assay, and more than 10,000 hits have so far been identified with interesting activity. The goal for 2008 is to complete the screen, characterize the hits, and use chemo-informatic technologies to cluster them.); and 5) discovery program to screen new class of compounds, namely THiQ, that showed promising activity against P. falciparum from its previous Fab1 project.||US $2.2 million|
|MMV/Broad Institute of MIT and Harvard/ Genzyme mini-portfolio (three projects)||Engaged in three projects: 1) screening of the broad compound collection against whole parasite assays with expansion plans in 2008 to include more compounds from the Genzyme library; 2) identification of natural products for malaria treatment; and 3) use of proteomics technology to identify molecular targets. Targets for one of the natural products have been identified, allowing it to be developed for a molecular-based, high-throughput screening (HTS) assay. Focus is to continue identifying more molecular targets that will not only be essential for parasite growth, but tractable in terms of finding small-molecule inhibitors.||$1.6 million|
|MMV/NITD/Novartis mini-portfolio (nine projects)||Engaged in nine projects ranging from early-stage research into identifying new targets for liver stages of P. vivax infection, through to optimization of compounds based on artemisinin dimmers. Several projects are moving forward from early-stage hits to lead compounds. One is the chemistry strategy based on successful screening of more than two million compounds from the Novartis compound collection, which led to the selection of more than 6,000 active compounds.||$589,000|
As demonstrated above, the nonprofit disease organizations are having an impact on translating early-stage discoveries to development phases, not only by providing funding for proof of concept and target validation but also by providing project management and a ready-made network of scientific and clinical infrastructures to expedite and de-risk the development of novel therapies. These approaches are instructive for developing and funding early-stage development models for the stratified medicine sector, but are only part of the picture in making a business case for stratified medicine. We also must assess the clinical trial development risks and how the nonprofit disease organizations may contribute in de-risking clinical development and its applicability to stratified medicine, which will be discussed in the next segment of this paper.
The critical part of assessing potential return on biomedical product development hinges on the assessment of risk factors in terms of clinical development costs, time, and success probabilities to get to market. Although most venture capitalists and biopharmaceutical companies use their own valuation models to assess potential investment returns of biomedical products in development, a baseline industry average provides a snapshot of the development risk factors and possible mitigation strategies to employ through unique collaborative models with nonprofit disease organizations.
With increasingly complex and chronic diseases as potential targets for new biomedical innovations, the industry is continuing to face decreasing productivity and increasing clinical trial failure rates, adding to the increase in development risks in terms of cost/time. Currently, approximately 80 percent of Phase I trials are expected to fail (i.e., they have a 20 percent chance of successfully making it to market), and 70 percent are expected to fail in Phase II, with expected success rates from Phase III to market between 50 percent and 70 percent. New biologic molecular entities have slightly better success rates than those identified for new chemical entities.
These tools will play a significant role in de-risking the drug development process. Continued advancement in new genomics-based technologies and high throughput screening tools will improve researchers’ abilities to discover reliable clinical biomarkers that can stratify and enable the discovery of the best therapies for patients. For instance, use of clinical biomarkers early in the clinical trial process could help to decrease costs by identifying better responders, thereby reducing trial sample size to demonstrate efficacy and help to exclude patients early using toxicity biomarkers. In addition, stratifying for key biomarkers early in the trial process not only creates the possibility of shortening end-point observation times, but also creates the ability to gather data to improve the compound or alter the trial design altogether early on, allowing for educated data mining to better define the appropriate patient population. Additionally, the collection of DNA information from ongoing clinical studies, with patients’ consent, also offers the possibility to accelerate future research with increased efficiency. Shorter trials with specific results also have the advantage of expedited FDA reviews, as exemplified by FDA’s review and approval of Genentech/Roche’s breast cancer treatment, Herceptin, which took six months, or that of Novartis’ Gleevec, which took three months. It is anticipated that stratifying patients based on clinical biomarkers may reduce the cost of clinical trials by a factor of two to five, as it would help to narrow the test populations and commercialization time from the current ten to twelve years to five years or less.
The current industry expectations are the following—in Phase I of the clinical trials, twenty to eighty healthy volunteers are given a new drug compound to test for safety at a cost ranging from $8,000 to $15,000 per patient with an average time period of six months to a year. In Phase II, 100 to 300 patients are given the new drug compound to assess clinical efficacy and dosage levels at a cost ranging from $8,000 to $15,000 per patient, with an average time period of two to three years. In Phase III, 1,000 to 5,000 patients are tested, often in placebo-controlled, randomized, and double-blinded trials for efficacy and overall risk-benefit assessment at a cost of $4,000 to $7,500 per patient. These data sets, however, do not provide a clear picture of the real drivers of time/cost correlation. For instance, key drivers of time delay in clinical trials include difficulties in patient recruitment (this causes 33 percent to 66 percent of time delay) and data management
(8 percent to 14 percent), as well as difficulty in manufacturing and regulatory/ethics approvals, resulting in upwards of 75 percent of all U.S. trials experiencing delays of one to six months or more. With more than 40 percent to 50 percent of per-patient costs attributable to clinical operations, including project management, monitoring, and regulatory and data management, finding ways to mitigate delays and deploying strategies to increase efficiencies in the clinical process will be critical in decreasing risks associated with development costs/time. (See Figure 8.)
Figure 8: Clinical Trial Parameters
In identifying ways to de-risk the time/cost factors in clinical development, one of the emerging models is industry collaboration with nonprofit foundations which, at varying levels, offer mechanisms to expedite and create efficiencies such as readily accessible patient registries and databases, and a broad network of clinical and investigator sites that offer scientific expertise and support.
Patient recruitment in clinical trials, especially for specific disease indications, are extremely time consuming and often difficult, adding tremendously to clinical trial time/costs. One of the important de-risking mechanisms provided by the nonprofit disease organizations is access to their network of patient registries and databases. Although most organizations are at various stages of developing their patient registries, Cystic Fibrosis Foundation (CFF) has created an extensive infrastructure to serve this purpose. For instance, CFF accredits more than 115 cystic fibrosis care centers with ninety-five adult care programs and fifty affiliate programs nationwide, creating one of the largest patient registry databases among U.S. foundations, with information about more than 24,000 CF patients receiving care at one of the CF care centers. CFF’s database includes not only the patient contact information, but detailed information about genotypes, pulmonary function test (PFT) results, pancreatic enzyme uses, length of hospitalizations, home IV use and complications related to CF, which are critical in assessing trends and in clinical trial designs. The MMRC also has developed a patient database consisting of contact information from 165,000 patients and has launched a new initiative called the patient navigator program to identify and match patients with clinical trials.
One of the critical de-risking mechanisms in terms of development time/costs that many of the nonprofit disease organizations offer is their extensive network of clinical trial sites and expert investigators, as well as information about the ongoing trials in their networks. This offers the ability to conduct multi-site trials with expediency, combined knowledge, and access to quality data from the ongoing trials. Such clinical trial networks also provide the ability to scale up quickly in Phase III studies and, in some cases, conduct Phase IV studies. An important aspect about such a network is the nonprofit disease organizations’ collaborative approach to trials, as they often offer centralized review of clinical trial protocols, are able to set common policies to protect patient safety, establish standardized research procedures, share expertise among top researchers, and provide network-wide staff training.
CFF may be one of the leading organizations that, through its Therapeutics Development Network (TDN), offers access to its network of eighteen clinical research centers that specialize in conducting Phase I and II studies for treatment of CF. TDN centralizes and standardizes CF research while providing access to clinical trials data and CF experts through a centralized coordinating center at the Children’s Hospital in Seattle, Washington. To enlarge its network, CFF invested $3 million in 2007 in forty-five new research centers in twenty states nationwide to build an infrastructure to help with patient recruitment and to increase its clinical network. As discussed previously, the MMRF also offers a network of fifteen academic centers that collaborate in conducting multi-site clinical trials.
To increase efficiencies, productivity, and sustainability of conducting clinical trials in developing countries, MMV works with a network of international organizations such as the Malaria Clinical Trials Alliance (MCTA), Malaria Vaccine Initiative (MVI), and the INDEPTH Network. MCTA facilitates site preparation for effective conduct of Good Clinical Practices-compliant trials for malaria vaccines and therapies, while supporting the long-term development and sustainability of clinical trial sites in nine countries across Africa (Mozambique, Tanzania, Malawi, Gabon, Nigeria, Ghana, The Gambia, Kenya, and Senegal). MVV also works with the European & Developing Countries Clinical Trials Partnership (EDCTP) to facilitate Phase II and III clinical trials in HIV/AIDS, malaria, and tuberculosis in sub-Saharan Africa.
To reverse the trend of declining productivity and innovation, and embrace the new technological and scientific advances that will allow for safer and more effective treatment of diseases through stratified medicine, industry stakeholders must be open to unique models that could de-risk current drug development processes and increase their combined probabilities of success. Through our discussion, we have identified new collaborative mechanisms with nonprofit disease organizations that can not only help bridge some of the funding gaps in early-stage discovery and development of new technologies, but more importantly, de-risk the clinical process in terms of time and costs.
|Foundation||Academic Research Networks||Clinical Centers Networks||Tissue Banks||Patient Registries||Project Management|
In the short term, these mechanisms offer a model for the biopharmaceutical industry in how they can better work with existing nonprofit organizations to capitalize on their offerings. The elements of such a model would include biopharmaceutical companies collaborating with other groups, such as nonprofit foundations, who could establish and manage the programmatic research of networks of academic and investigators from small biotechnology companies, patient registries, and expert clinical centers. In return, large biopharmaceutical companies would provide some funding and commitment to take over the late-stage development of “de-risked” clinical candidates to approval and marketing. There could be several innovative ways to reward the nonprofits for their contribution without violating their mission or 501(c)(3) status.
A critical success factor in stratified medicine is the discovery of the biomarker and/or diagnostic kit. Intellectual property rights can be a potential barrier when there is only one supplier of the diagnostic kit, particularly if that kit has not been approved by regulatory bodies. This presents challenges in reimbursement, as well as potential liability issues if such a kit is used to qualify patients for a drug, and the specificity and sensitivity of the diagnostic test have not been established. This liability exists for both tests of efficacy and susceptibility to side effects. There is, therefore, need to address this downstream issue of potential biomarkers that are discovered in the NIH and other Biomarker consortia.
In summary, this paper focuses on ways to address two of the issues—return on investment and probability of success—that are barriers to the adoption of stratified medicine by large biopharmaceutical companies. The various activities of some foundations serve to identify the relevant patient subgroups and generate data to better qualify potential drug candidates. We call these “de-risking” activities, which not only fill gaps in funding, but improve the probability of success of the drug discovery and development effort. These diseases also are excellent examples where subgroups of patients might be discovered and stratified, and prospective health care—anticipation, prevention, intervention—as described by Dr. Ralph Snyderman, could be pursued on a more rational basis. Thus collaboration between large biopharmaceutical companies and disease foundations provides an interesting model within which several aspects of the development and implementation of prospective health care and stratified medicine might be assessed for technological and economic feasibility.
However, a broader challenge remains in the ability to scale these de-risking mechanisms to a larger set of disease sectors, and on the question of who will bear the cost of creating the necessary infrastructures. One possibility is the U.S. government; as such efforts would be consistent with both the FDA’s Critical Path Initiative and the NIH Road Map. We would argue that both the FDA and NIH, under these two initiatives, could encourage the collaborative model suggested in this paper, either by disease category, such as cancer, where there is a known familial or genetic predisposition for the disease. In addition, two areas need to be urgently evaluated or assessed: the barriers that present intellectual property rights pose to adoption of the collaborative model, and the financial value of the varying de-risking strategies that we have discussed. These are the questions we pose today in opening the discussion on how we can make a business case for the growth and adoption of stratified or personalized medicine in the near future.
*With special thanks to Lauren Choi, Counsel, Buchanan, Ingersoll & Rooney, for research and editorial assistance.
M. Kathleen Behrens
RS& Co. Venture Partners, IV, L.P.
Kleiner Perkins Caufield & Byers
Senior Policy Specialist
Medical Industry Group
National Venture Capital Association
Over the last decade, a series of key research developments in the fields of genetics and medicine have enabled the possibility of tailoring treatments for patients based upon the molecular basis of disease and/or the individual’s ability to respond to a specific treatment. This possibility has given rise to the emerging field of personalized medicine.
Personalized medicine represents a major leap in the evolution of healthcare because it enables care providers to deliver the right treatment to the right patient at the right time. This ability will not only lead to improved health outcomes and better qualities of life both during and after illness, but may also help lower costs through greater efficiency of treatment.
Much in the same way that it helped create the biotechnology industry through its investments in Genentech, the venture capital industry has played a critical role in driving the development of personalized medicine by helping to translate multiple breakthroughs in molecular medicine technology into marketable products. Venture-funded companies like Genomic Health, Inc., Monogram Biosciences and Adeza Biomedical Corp. have already made an impact on patient health. The next generation of companies is expanding into new therapeutic areas, some of which are utilizing novel technology platforms. Venture capital will likely remain the primary source of financing for young innovators in this space due to the extraordinary risk associated with investing in healthcare technologies.
Despite its enormous promise, personalized medicine faces a number of barriers at what has become a critical point in its development. Some of these stem from current regulatory policies and the uncertain reimbursement outlook for new technologies. Others have resulted from the recent turmoil in the capital markets. For each of these variables, even minute fluctuations and adjustments can alter the risk profile for even the most promising technology. Working in concert, they can price risk beyond levels acceptable even to venture capitalists – effectively stunting the development of emerging technologies and undercutting the incentive for future innovation.
Within these contexts, the purpose of this paper is to:
The venture capital industry drives innovation by turning ideas and advances in basic science into marketable products and services that improve people’s lives. They do this by identifying the most promising advances and then guiding their commercial development with expertise and funding.
Typically, venture capital concentrates on funding innovations that threaten to replace – or render obsolete – established products and services in a given marketplace. Venture capitalists use their expertise to find such “disruptive” technologies and evaluate which ones have the most market potential. Only the most promising advances get funded, and the venture capitalist typically takes an active role in guiding further development.
In this sense, the venture capital industry creates and maintains a de facto research and development pipeline for a wide variety of technology and knowledge-based industries. This role has become critical in recent years, as many public companies have slashed R&D budgets as a way to ease the quarterly scramble to meet earnings estimates. In some cases, venture capital has created entirely new industries.
The early-stage risk associated with disruptive innovations often precludes financing from traditional sources such as banks and public equity. Without someone to step in and assume this risk, many promising advances would have no capital for further development. By providing funding and expert guidance during this critical period, venture capitalists ensure that the most promising technologies have the best chance of making it to market – where they can make the greatest possible impact on quality of life.
By driving innovation in these ways, venture capital investment has fueled the development of many high-tech industries in the United States. These include biotechnology, medical devices, network security, on-line retailing, RFID and Web-based services. In fact, venture capital has helped to build innovative powerhouse companies such as Genentech, Microsoft, Google, Apple, Starbucks, Staples, eBay and FedEx.
The first venture capital firms date back to the 1930s and 1940s. Up through the 1970s, by which time venture capital had established itself as an industry and a profession, investors at these firms worked as “generalists” – investing in companies and ideas across various industries. The relatively small size of the industry permitted this lack of specialization. In 1980, for example, the National Venture Capital Association tracked only three sectors: life sciences, information technology and industrial/energy.
Beginning in the 1980s, the skill set required for venture investing grew along with the industry. Successful venture capitalists needed the industry experience and insight to determine which innovations offered the most promise, domain business expertise to advise entrepreneurs and technologists in building portfolio companies, and the experience to manage the multi-stage investment process for those companies. As a result, venture investors (and often their funds) began to concentrate their efforts on a few sectors in which the partners had the most experience and that offered the most opportunities to innovate – most commonly software, industrial/energy, biotechnology, medical devices and diagnostics, and media and entertainment. Today, an individual venture capitalist typically specializes in one or two related sectors -- e.g. biotechnology and medical devices.
Venture capital firms raise funds from investors – most commonly large institutions such as corporations, foundations and public entity pension plans, but also from individual investors. The partners in a venture firm also invest their own money in their funds. Venture fund managers are compensated through annual fees associated with managing fund investments, as well as a percentage (carried interest) of the profits derived from successful investments. The latter are offset by losses associated with unsuccessful investments.
Venture capitalists generate profits and losses from the funds they raise by making equity investments in a range of portfolio companies. The average timeframe for this process is typically seven to 10 years. Generally, venture capital is used to purchase an equity stake in a series of rounds of investments in each individual company. Because venture capitalists tend to make investments in young companies, those companies often do not have products or services to generate cash flow from operations. As a result, they are not sufficiently creditworthy to take on debt. For this reason, venture capital is known for taking the highest risk in the spectrum of stages (with the exception of the “angel” stage) in which capital can be invested in building and running companies. Venture investors do not typically loan funds to their portfolio companies unless it is provided on a short term basis and eventually gets converted into equity.
As is the case with most investing, venture funds require risk diversification—especially considering the fact that they invest in one of the highest-risk stages of investing and often must wait 10 years or longer to realize their returns. To mitigate this risk, some venture firms raise separate funds dedicated to specific industries, while others specialize by investing in a single industry with multiple segments that can contribute some risk diversification.
Most young companies raise capital in a series of investments. Venture investors can participate in some or all of these financings. Young companies need only small amounts of capital (relatively speaking) when starting out – perhaps to develop a “proof of principal” or to reach a benchmark demonstrating measurable progress with a product or service. This enables them to raise capital in a series of later stages, at which points they can achieve higher valuations than in earlier rounds and can sell less equity – i.e. experience less “dilution” from the price at which they sell/accept new capital. This also allows the venture investor to invest more capital in the company, but in a way that demonstrates a series of increasing valuations associated with favorable progress. More detail about this process can be found in Appendices A and B.
After purchasing equity in a portfolio company and nurturing it for many years, a venture capitalist generates a return for the investors in the fund by selling that equity. There are multiple ways to generate liquidity for these equity investments. Most commonly, the company sells equity in the public market – enabling the venture investor to sell all or some of its stock to public market investors – or the company is sold to another firm. In the latter case, the investors receive either stock or cash upon the sale of the investment, thus providing either immediate or eventual liquidity. Again, this typically happens between seven and 10 years after the initial investment.
Venture investors generally assume significant technology development risks; however, healthcare presents some unique and additional challenges. These largely relate to the added complexity of long product development timeframes (often associated with clinical trials), government regulation and significant capital requirements, as well as the complexity of reimbursement associated with the healthcare payor system. These factors add up to larger capital requirements on the part of venture capitalists (and other stakeholders) and an investment time horizon that stretches to 15 years or longer. All of these increase risk.
Despite these complexities and the additional patience required, the venture capital industry invested approximately $9 billion, or 30 percent of its total, in companies in the biotechnology (including pharmaceuticals and research tools companies), medical devices and healthcare services (including healthcare information technology) sectors in 2007.
Healthcare investing by the venture capital community for many years has been concentrated in the three areas mentioned above. During this period, the degree of specialization required for successful investing in each has increased. In large part, devices and biotechnology investments have been tied to new technological developments and related venture expertise, while services have met the needs of evolving healthcare delivery with a different set of skills and experience. Approximately 98 percent of the venture capital invested in healthcare (as measured by aggregate invested capital and number of investments) has been devoted to biotechnology and medical devices.
The venture capital industry played a critical role in creating the biotechnology industry during the 1970s and 1980s. During this period, researchers achieved a number of key advances in the fields of gene sequencing and expression technology, recombinant DNA technology and monoclonal antibody technology. (Not coincidentally, all of these provide the foundation for personalized medicine today.) At the time, however, there existed no process for translating these advances into commercial products. In these years, for example, when Cetus Corp. developed polymerase chain reaction (PCR) and Genentech began cloning insulin, established pharmaceutical companies simply weren’t inclined to take the risks involved in funding these advances. In both cases, venture capital stepped in to provide funding and management – helping both companies to advance their product development and creating a modern blueprint for building successful companies from innovations in medical technologies. Venture capital played a similar role during this time with biotech pioneers Amgen, Chiron, Biogen Idec and Genetics Institute, LLC.
Today, business models for biotechnology companies developing biopharmaceutical products continue to rely upon significant capital from both the venture industry and the public market. The capital is needed to sustain long product development cycles required for research and clinical studies, as well as manufacturing and product launch. Estimates vary for the cost of individual therapeutic products due to amortization of product failure costs along with successes; nonetheless cumulative individual product expense estimates range from $500 million to nearly $1 billion.
More so than in other industries, the risks associated with the increased costs and extended timeframes in the biotechnology sector preclude traditional sources of financing in the early stages of development. At the industry level, venture capitalists step in to not only fill the funding gap during the early stages, but also vet companies’ scientific platforms and assess their commercial viability. They also lend management expertise and strategic vision to the companies in which they choose to invest.
As described earlier, an important role of the venture capitalist is to help facilitate change within an industry. In the healthcare industry, the venture capitalist acts as an advocate not only for the entrepreneur but also for the patient by helping to drive advances in patient care – as demonstrated by the commercialization of advances in DNA research into biologic drugs (described in the previous section) and other treatments. Thanks to continued research and investment, these advances have in turn spawned personalized medicine, which uses these technologies to improve patient outcomes and potentially reduce costs in the long term.
Historically, diagnostic products have provided incremental and supplemental information to physicians and patients in managing care largely because they have contributed additional pieces of information to assemble into an overall assessment of disease and treatment.
New molecular diagnostics (or, personalized medicine) have the ability to raise the importance and value of the information derived from testing. Newer technologies enable the collection of data and analyses at a scale that was not previously possible – providing new insights about patients and diseases that can inform patient care and treatment. Also, new-generation tests may provide critical information for patient management, which in some circumstances may be as or more important than the value of existing therapies.
The foundation of personalized medicine lies within our efforts to better understand the biology of disease at the genetic and protein levels. Three technologies at the center of this effort are gene sequencing, gene expression and proteomics. Gene sequencing, made possible initially by Cetus’ development of PCR, enables researchers to clone DNA and thus amplify genetic material. Gene expression technology allows researchers to identify genes in patients that indicate the presence of, or an increased susceptibility to, a given disease. In addition, it also helps illuminate the development and growth of cancerous tumors. Proteomics examines the molecular biology of diseases, enabling researchers to identify individual proteins associated with specific disease states and susceptibilities.
All of these technologies – either in development or application – have been informed and/or advanced by the Human Genome Project, which generated large quantities of genetic and genomic information and helped enable the acceleration of the sequencing process. Researchers have then studied this information in great deal to better understand the link of genetics to diseases; included in these efforts are large scale studies of both patients and agents of disease.
At the most basic level, personalized medicine has two goals: understanding the molecular nature of a disease and understanding how an individual will respond to therapy.
One of the best-known examples of the former is Herceptin®, a drug developed and marketed by Genentech, one of the first biotechnology companies to emerge from the venture industry. The recognition of the role of HER2 over-expression in breast cancer patients has aided in patient selection for treatment with Herceptin®. An important advance in understanding the patient’s response to therapy is the ability to assess thiopurine (a group of chemotherapeutic agents) drug metabolism by measuring thiopurine methyltransferase (TPMT) activity in an individual patient. This advance has enabled physicians to identify which cancer patients are likely to suffer adverse effects from the treatment. However, the opportunity to bring applications of more recent technological developments to bear in personalizing healthcare is driving venture capital investors to start new companies in this field today.
Venture capitalists play a key role in building personalized medicine companies. They work with entrepreneurs to craft the business strategy, recruit the management team and often catalyze the key relationships necessary in building the business. While there is no formula for success, following a thoughtful process that addresses key issues increases the likelihood of success. Below are key early considerations in building a personalized medicine business:
While the above factors may seem relatively straightforward, all components must come together to build a successful business. One factor of particular importance is the availability of well-annotated clinical samples, which makes development more practical. Such samples can reduce the risk of getting to clinical trials, the cost of development and the duration of development. Consider this example: Genomic Health’s Oncotype DX® was developed using tissue archives that include data on each patient’s five- or 10-year outcome. Had this archive not been available, development would have required new tissue samples and a waiting period of five to 10 years to track the clinical course of the patient.
As described above, the goal of personalized healthcare or medicine is to tailor treatments for patients based upon their individual medication responses and the molecular basis of disease. This practice is evolving by addressing groups of patients that can be categorized by having similar susceptibilities and responses to therapy—in effect stratifying them by risk and response. While it is possible to envision a very broad range of future applications from these types of assessments, below are some examples of innovative personalized medicine companies funded by NVCA members. While the disease area may be different, these companies all have a common goal, providing answers to key clinical questions enabling better patient management.
Given that there is no shortage of clinical situations in which physicians could benefit from more information, many opportunities for the development of future products exist. The next generation of personalized medicine companies will continue to expand product offerings in oncology and cardiology, infectious disease and woman’s health. Young companies are also tackling new frontiers, such as autoimmune disease, neurodegenerative disease and psychiatric disease.
Potential Model 1: Avoiding adverse effects. A future healthcare system could use electronic health records to identify patients with adverse effects, enroll patients (both with and without the adverse event) in research studies and screen for genes or biomarkers associated with the adverse event. This is currently not practical, nor is it likely be in the very-near future – given that all patients would need to be tracked for all adverse events and all samples would have to be data-mined for genomic or proteomic correlations. However, today there is no system at all in place to call out the most likely targets for adverse effects research or to signal where or how payors will pay for cost-effective diagnostics that protect patients from prescriptions that will hurt them. Based on the risk and investment principles described so far, an optimal combination of public investment could be balanced with rewards for specific product development in the private marketplace. A model example would be the basic research that took place in warfarin pharmacogenomics, which discovered several genes playing a key role in warfarin metabolism. A number of private companies are now competing to market increasingly rapid tests for these genes.
Potential Model 2: Safety alert or early intervention systems. Modern electronic health record technology could incorporate existing knowledge of adverse event reactions and drug/drug interactions in an “interactive health record” that incorporates patient specific information, data-based best practices, and laboratory test results in real time. This could provide optimal treatment pathways and ongoing appropriate tests to anticipate and reduce adverse events and to ensure the optimal treatment of the patient. One venture capital-based firm, Proventys, Inc., is currently developing important tools in this space. New business models will develop the best marketplace strategies for this category of personalized health technology, such as interfaces with pharma management systems, physician offices and payors. This space will be accelerated by policy initiatives such as adoption of ICD-10 disease codes, and electronic health records that facilitate rapid (ideally, immediate) transmittal of key information between the billing entities such as physician offices, hospitals and specialty laboratories. The Harvard Medical School/Partners Healthcare Center for Genetics and Genomics (HPCGG) has emphasized that the current relationships among these entities are many-to-many systems, making the information technology problems impossible to solve. The simplest solution, which does not exist today, would be a central data repository which can be accessed with appropriate confidentiality protections and permissions to result in the development of much more sophisticated solutions.
As many of the preceding examples suggest, personalized medicine has the potential to transform the way care is delivered to patients across a full spectrum of conditions. To date, the healthcare system has caught only a small glimpse of the clinical and economic outcomes personalized medicine can yield. How soon these benefits can be fully realized depends on how quickly and effectively the healthcare industry can overcome the challenges inherent in harmonizing the interests of its multiple stakeholders. Clinicians, payors, manufacturers and health information technology firms alike will have to play meaningful roles in enabling innovations to fit into the context of the marketplace and achieve acceptance on a large scale.
The following provides a brief overview of challenges that key stakeholders face as the growth of personalized medicine accelerates in the coming years:
Clinicians: At the center of decision making. Through advances in personalized medicine, clinicians will be empowered to more precisely diagnose a patient’s condition and select the safest and most efficacious treatment based upon the patient’s unique clinical profile. However, the adoption of new technologies will pose a considerable challenge in the context of today’s busy medical practice. Among the challenges are (i) keeping pace with the proliferation of personalized medicine technologies (and the vendors providing them); (ii) identifying which patients are appropriate for the various technologies being introduced to the market; (iii) interpreting molecular diagnostic test results in the broader clinical context for their patients; (iv) processing the sheer volume and complexity of data to make personalized clinical decisions; (v) reviewing and understanding the scientific evidence supporting the new technologies prior to relying upon them in routine practice; (vi) understanding the various payor coverage determinations to ensure appropriate reimbursement; and (vii) implementing the necessary operational processes for handling biological samples and working with various personalized medicine vendors.
Payors: Driving value-based approaches. As current medical management strategies such as disease management mature, payors are seeking innovative solutions to help reduce variability in care and control the rise of medical costs. It is in the best interest of payors to support personalized approaches to care where better understanding of patients’ individual profiles (including their risks of an adverse event or potential response to a given therapeutic path) will guide better clinical decisions Payors can play an important role in shaping the emerging market for personalized medicine by (i) identifying the clinical areas of greatest unmet need through population-level medical claims data analysis; (ii) setting clear requirements for the technology validation necessary to secure reimbursement coverage; and (iii) supporting the appropriate utilization of emerging technologies through the implementation of novel, value-based reimbursement models.
Diagnostic and biopharmaceutical manufacturers: innovators and educators. Personalized medicine represents a significant paradigm shift for both the diagnostics and biopharmaceutical industries. Biopharmaceutical manufacturers must reassess the fundamentals of their business as they contemplate the attendant shift from discovering the next blockbuster drug to unlocking the enormous value of targeted therapeutics that serve more distinct and segmented populations of patients. Diagnostic manufacturers must effectively demonstrate the increased value of their technologies as they play a more central role in the personalization of care. These manufacturers will help accelerate the acceptance of their own innovations by (i) effectively validating their technologies to support both payor reimbursement and clinical adoption; (ii) educating clinicians in novel ways with sound scientific support to ensure the appropriate utilization of these new technologies; and (iii) investing in the ongoing innovation necessary to establish a sustainable personalized medicine market.
Health information technology (HIT) vendors: Vital enablers. For personalized medicine to evolve from the current discrete instances of esoteric testing and targeted therapeutics to a more sustainable and widely accepted approach to care, a foundational system of information technology is required. HIT vendors have a unique opportunity to provide the dynamic, point-of-care decision support necessary to support the broad adoption of personalized medicine. These vendors must (i) develop more robust information solutions focused on delivering high-value decision support that empowers clinicians; (ii) make data more accessible and actionable to the care team within their current workflow; (iii) establish effective approaches to health information exchange to allow for a comprehensive view of a patient’s medical history; and (iv) work with clinical data in novel ways to spur innovation while ensuring patient privacy and data security.
In prior sections, this paper illustrates the considerable extent to which innovation relies on the ability of entrepreneurs and technologists to develop products from advances in research and commercialize these products. This section focuses on the complexity of this task in the field of personalized medicine and the barriers to success that currently exist.
As described earlier, some of these barriers exist inherently in healthcare investing. The longer time horizon and increased capital commitments necessitated by complex product development and clinical trials provide two such barriers. Market-driven fluctuations in the availability of capital provide a third. While these economic barriers are simply part and parcel of the process, a number of policy issues –specifically with regard to regulation and reimbursement – also hinder the development of personalized medicine. These barriers are formidable and urgent, yet also within the government and the industry’s power to mitigate – if the two groups work together now to remove them.
Successful company development in personalized medicine involves simultaneously balancing:
A laboratory medicine test faces this transaction system:
Figure 1 shows arrows for just one payment pathway (in this case, a government payor). Other arrows would connect different payors to the laboratory. Note that the personalized medicine lab ultimately receives money originating from one of four sources (represented by rectangles): patient self-pay, from taxpayers via a government payor, or from an individual or an employer via private insurance.
The diagram risks understating the complexity of the information transactions involved. A national lab – even a one-test startup lab – must deal with hundreds of private and government payors. Each payor must make coverage and pricing decisions (which can involve complex technology assessments) about the test and each payor (at least in principle) needs to know something about the patient’s condition at the time of the test.
The arcane complexities of the insurer coding and pricing systems for laboratory tests have been well-documented. During the early investment stages, the venture capital firm must project five to 10 years in the future how physicians, patients, hospitals, private payors, government payors and the self-pay patients will respond to the test, as well as the test’s likely position in the marketplace relative to both existing alternatives and alternatives likely to be introduced in coming years. All of these factors must be tracked during, or informed by, optimally planned and staged investments which lead to the most efficient reduction in risk as the project develops and investments increase. (As shown earlier, with the reduction in risk, the projected value of the company increases substantially, which in turn makes a new investment round possible.)
Venture capital investors must evaluate the likely stances of third-party payors closely – a necessity that is very specific to the medical technologies sector. Generally, payors are concerned about two issues: 1) the overutilization of diagnostic tests and treatments and 2) the absolute costs of these tests. Thus, the challenges for venture capitalists regarding this new generation of molecular diagnostic tests stem from the fact that the development process is costly, as like theraputics, they often involve the productization of new technologies and large clinical trials. These factors in turn drive up prices for patients and payors.
However, entrepreneurs and developers of these technologies are willing to risk the concerns of payors because the results generated by them provide information of much higher value for patient care. Therefore, despite the initial higher cost, these diagnostic tests will ultimately lead to more cost-effective patient management for payors.
As discussed previously, the current products that are most strongly associated with personalized health care are molecular diagnostics. Today, far more is known about the molecular heterogeneity of major diseases, including cancer, than was known even 10 years ago. Research has made it clear that targeted and more effective medical treatments will often be unattainable unless physicians have precise molecular information about each patient’s disease. That is, there will be no “magic bullet” chemotherapy for “colon cancer” across all patients, but there may be a very effective treatment for those patients whose colon cancer expresses Gene X.
In many ways, these tests seem to be the easiest to integrate into the existing care delivery system. If Chemotherapy Drug X is effective when tumors express Gene X, then we can test those patients and prescribe the right drug to the right patient at the right time.
Although the integration of these tests into clinical care would seem like a fairly straightforward process, companies and investors have found two key factors providing barriers to innovation. These are 1) level of evidence for payor coverage and 2) legacy pricing systems.
Diagnostic tests: level of evidence for payor coverage. Payors are most experienced at performing technology assessments for drugs and for other therapeutic interventions (e.g. ultrasound for kidney stones.) Diagnostic tests present several difficulties for payors. First, few payor guidelines for technology assessment contain the same level of sophistication and granularity as the research that led to and supports the technology being assessed.  Some guidelines don’t even recognize the difference between diagnostic and therapeutic applications. Second, there are few guidelines on the degree to which clinical benefit can be extrapolated from test accuracy or retrospective studies, or whose extrapolation is credible and why. For example, imagine a researcher studies Gene X in an archive representing 100 colon cancer patients treated with drug XYZ. Only the 20 with Gene X responded, and responded well; the other 80 did not respond at all and quickly died. Should a randomized trial be conducted, where 80 percent of entrants will be treated with XYZ despite having Gene X? Can we assume Test X is necessary and impacts clinical care greatly? What if the numbers were less clear cut? The lack of consensus guidance leaves both innovators and payors with a great deal of uncertainty in how to evaluate diagnostic tests for coverage.
Diagnostic tests: reimbursement. Most traditional diagnostic tests long ago became commodities (such as a serum glucose test or a thyroid hormone test). Most payors pay fixed and inexpensive test prices related to Medicare’s laboratory fee schedule, which was established in 1984. Since then, many stakeholders have asserted that the reimbursement environment for novel diagnostics is much more challenging than the environment for other medical devices or drugs. In the U.S. payor system, new drugs are assigned specific codes for insurance claims and paid at market prices that are set relative to alternative drugs. The payor system for diagnostic tests has developed in a different and less consistent manner. Diagnostic tests are usually described by generic codes (e.g. microbiology antibody test) and paid at a fixed rate (say, $30). In the case of one novel molecular medicine test (the Oncotype DX® test), however, private insurers and Medicare have paid near list price – several thousand dollars in this case – for the test. High levels of uncertainty regarding “value-based pricing” of molecular diagnostics pose serious difficulties in the venture capital investment model because such uncertainty inverts the assumption of progressive risk reduction (the notion that a venture becomes less risky as it matures) outlined in prior sections. For example, in the case of a novel molecular test, the uncertainty over how Medicare will price it resides at the far end of the development and investment pathway; this uncertainty remains constant during progressively larger staged investments. Prices that converge on marginal costs are characteristic of mature and highly competitive markets, but make innovation impossible.
Changes, such as published guidance, which make coverage and reimbursement more predictable will reduce the overall level of risk for innovators and thus encourage innovation in ways that are otherwise costless to the system.
New molecular diagnostic tests primarily fall into classes of products defined by the Food and Drug Administration (FDA) as in vitro diagnostic (IVD) tests or in vitro diagnostic multivariate index assays (IVDMIAs). The former are often less complex than the latter, though precise regulatory definitions are still being actively reviewed as new products reach laboratories and the FDA.
Historically, oversight responsibility for in vitro diagnostic products has resided in both the FDA and the Center for Medicare and Medicaid Services (CMS). FDA approves the safety, efficacy and manufacture of IVDs under its authority to regulate medical devices, while CMS oversees compliance with performance standards for laboratories under the Clinical Laboratory Improvement Amendments of 1988 (CLIA). For many years, the FDA has exercised “enforcement discretion” for emerging diagnostic tests largely performed by specialized laboratories. However, in July 2007, the FDA published its most recent guidance on the topic, signaling the agency’s intent to actively review all current and new IVDMIAs that have not already been voluntarily submitted for review. This guidance has sparked significant dialogue within different industry groups, as well as between industry and the FDA.
The FDA’s regulation of IVDMIAs will follow the device evaluation path--where substantial equivalence to an existing, or “predicate”, device is established for the new test, or a more extensive, pre-market approval (PMA) path may be required. A number of new molecular diagnostic tests have been developed as Laboratory Developed Tests (LDTs, or “home brew” tests) for exclusive use in CLIA-certified laboratories and have not been reviewed by the FDA. The July IVDMIA guidance, when implemented, will require these tests and others under development to undergo more extensive regulatory evaluation, in some cases requiring clinical data that may or may not have been developed prior to their use as LDTs.
There are number of outstanding issues associated with new IVDMIA development and the FDA’s plans to actively review this class of tests. The outcome of this review could significantly influence innovation by the venture community. These include, but are not limited to:
As is the case with many new technologies, patient safety concerns must be balanced with regulatory processes. This must be done without defeating innovation, however.
This discussion has been devoted to the oversight of new molecular diagnostic tests largely for two reasons. First, the vast majority of venture-backed companies that are focused on personalizing healthcare are developing these types of products. Second, the issue is timely for the venture community as it weighs ongoing investment in companies developing new tests. However, regulatory decisions are also evolving for pharmaceutical product development--ones that anticipate incorporating new molecular technologies. For example, the FDA is discussing plans to require the collection of DNA samples from all patients participating in clinical trials, so that such material can be accessed in the future if drug-related safety issues arise. Further guidance from the FDA would also be constructive in updating the preliminary regulatory path for co-developed diagnostic and therapeutic products.
Thanks to continued federal funding and the extraordinary promise for improving health outcomes, advances in the fields that drive personalized medicine will continue. Demand for treatments and therapies based on these advances will also grow as people begin to understand aspects of their personal health in unprecedented detail and look to take greater control over that health. Given these realities, the question becomes: Will the industry be able to meet this demand by bringing advances in personalized medicine to the marketplace?
The fundamental process for bringing innovations in this sector to market probably won’t change. Federal and academic research will continue to move the science of personalized medicine forward. Innovation will continue to spring from small companies – as opposed to large institutions and corporations – because of the freedom and creativity they encourage. Venture capital will continue to step in during the critical early and middle stages to assume the risks inherent in building these companies.
Unfortunately, venture capital can only take personalized medicine and the innovative companies that drive it so far before the acute regulatory and reimbursement barriers discussed in the previous section begin to hinder development. The consequences of this inefficiency are significant – given personalized medicine’s potential for dramatically improving both the efficacy and efficiency of healthcare delivery. Together, these elements could play a major role in broader healthcare reform in the U.S. by reducing costs and enabling greater individual participation in health outcomes. Without a joint effort by government and industry players to remove or ease existing barriers, however, personalized medicine may never achieve its full potential.
Most young companies raise money in discrete stages. This practice enables the owners and their venture investors to raise funds at increasingly higher levels of valuation as the company’s assets grow and its risk profile improves. (See Appendix B for step-by-step details.)
The earliest round of financing is typically called either a “seed”, “first”, or “Series A” (denotes the legal name for the category of stock and investor) round. In most cases, it represents the first time that a company raises funds and usually garners a small amount of capital (i.e. between one and-several million dollars) from only one or a couple of investors. Funds raised during this round may contribute to product development and market research. Other uses include building a management team and developing a business plan if the initial steps are successful. This is a pre-marketing stage.
Subsequent rounds are called “follow-on” rounds – typically named “Series B, C, D” and so on. These rounds generally draw down larger amounts of capital from an increasing number of investors as the company’s needs grow. Series B capital often funds additional product development, product launch and initial marketing efforts. Once a company is producing and shipping its product and has growing accounts receivables and inventories, Series C capital may provide funds for an initial expansion. Beyond this point, the company may engage in additional rounds, or even begin to take on some debt and possibly sell equity to public market investors. Such late stage rounds are commonly called “mezzanine” rounds.
While many venture funds invest in both the early and follow-on rounds, some also specialize in the stage at which it makes its investments. For example, the unusual expertise and operational experience required for creating companies from scratch have given rise to funds specializing in seed round investment. Similarly, mezzanine rounds often call for funds that focus on taking companies public and/or selling them to other companies. Such funds are commonly affiliated with public market investor funds. Other funds, known as “crossover” funds, may specialize in investing in both the late private rounds of investment as well as the public market (although most venture funds in the healthcare space reserve the ability to make investments in their portfolio companies in both private and public rounds of investment).
The venture capital financing process begins when venture capital investors and the founding entrepreneur(s) of Company A negotiate a valuation that takes into account the company’s technology, experience and other assets, as well as the risks it entails. At the first stage of financing, the company has a much higher risk of failure than success and will require significant additional capital to develop its products. In this example, Company A has been valued at $10 million (most start-ups are valued below this amount, but it is a useful number for demonstration purposes).
Next, the founders of Company A raise capital by selling 40 percent of the company’s equity to “first round”, or Series A investors (i.e. venture capitalists). The company now holds $4 million in cash, with 40 percent of the firm’s equity held by venture capitalists and 60 percent owned by founders and employees.
Assume that Company A is successful in further product development and that the likelihood of success gradually increases (along with a commensurate reduction in risk of failure). In Year Three, the company demonstrates measurable progress and seeks additional capital at a “higher valuation”. For this second round (or Series B), the owners find new investors who believe that the pace of product development, competitive advantages and markets sizes for planned products, discounting new risk and return analyses for timing of liquidity and return on investment, value the company at $50 million. In this case, the 40 percent purchased earlier by Series A investors is now worth $20 million. One-half of the remaining $30 million of founder and employee value is sold to the Series B investors for $15 million. At this point the series A investors continue to own 40 percent of the company, the Series B investors own 30 percent of the company (1/2 x 60 percent), and the original founders and employees own 30 percent of the company (100 percent - 40 percent - 30 percent). The company has $15 million in new capital and has invested the original $4 million in product development.
At this time, typically, 70 percent of the board members will be represented by outside investors. They will look for the optimal exit strategy, such as taking the company public or selling to a larger firm. But in this example, at Series B, the company still has a limited chance of success and a reasonable chance that it will fail – in which scenario the $19 million that was raised will be lost.
“Progress in [personalized medicine] will characterize medicine
in the 21st century and extend life span much like the use of
antibiotics did in the 20th century.”
-- Gerald Levey, Provost and Dean, University of California,
Los Angeles School of Medicine, FasterCures Board member
The 20th century witnessed the greatest expansion of life expectancy in the history of humankind. The challenge for the 21st century is to not only extend the length, but to also improve the quality of life by preventing and defeating deadly and debilitating diseases. Across the spectrum - from basic science to clinical research to health services research - the impressive advances of recent decades in the biomedical, physical, computational, and behavioral and social sciences present unprecedented opportunities to improve human health and quality of life. Capitalizing on this reality will usher in an era of personalized medicine and solidify its place at the frontier of medical science.
The ultimate value of personalized medicine will be to improve treatment options for patients and prevent the onset of disease in the first place. But to realize these important gains, we need to transform our current research and healthcare systems from the outdated model of the last century to an integrated, information-based, high-quality, health-sustaining model that will extend life expectancy and improve the quality of life for generations to come.
To achieve this transformation the new system must focus on patients. How personal is personalized healthcare and what do consumers think about the advent of this era?
Embedded within each patient is the information – family history, medical records, lifestyle, biological samples, etc. – that is crucial to understanding, treating, and preventing disease. Patients need to be empowered by accurate information and armed with a clear understanding of the opportunities to:
To paint a complete picture and accurately represent the numerous patient perspectives on personalized healthcare, FasterCures conducted a qualitative research survey of disease research organizations, patient advocates, and patients to gauge understanding, awareness, and expectations of personalized healthcare and elucidate the issues that affect millions of Americans.
“Success is when everyone can learn which methods and treatments work,
and which don’t, in days instead of decades.”
-- Carol Diamond and Clay Shirky
In 1799, explorers unearthed in Egypt a stone slab – the Rosetta Stone – bearing parallel inscriptions in Greek, Egyptian hieroglyphic, and demotic characters, which made it possible to decipher the written language of the ancient Egyptians and the stories that it told about the people and their culture. Each of us is, in a sense, a Rosetta Stone, for within us is the information necessary to unlock the relationship of genetics, proteomics, behavior, nutrition, and environment to the emergence and, ultimately, the management of disease.
The three "languages" of our Rosetta Stone are medical records; biological material such as tissue, blood, and DNA; and our biology as observed in clinical research. By participating in clinical research – trials to test potential new therapies as well as epidemiological, observational, or natural history studies – and by providing tissue samples, blood, or medical histories, patients can provide critical information and resources, without which the search for cures and advancements in personalized medicine could slow to a halt.
Many respondents to our survey felt that the greatest payoff to personalized healthcare will come from leveraging the patient’s role in these critical areas:
It is interesting to note that the importance of tissue sample collection was generally not mentioned by our survey respondents. Some pointed out that patients can be uncomfortable with the notion of donating their tissue, and the time to educate patients about tissue donations for research is not at the moment a consent form is being signed for diagnosis or clinical care. Patients and patient groups must be brought into the process as partners in helping to ensure that the patient community understands how biobanks work, and the role they play in the clinical research infrastructure. FasterCures has a website devoted to this topic www.biobankcentral.org.
Respondents to our survey outlined how highly motivated their patients are to participate in clinical trials. For example, in the National Institutes of Health (NIH)-sponsored Alzheimer’s Disease Neuroimaging Initiative (ADNI) trial, the enrollment has exceeded the study program director’s expectations despite some of the painful medical procedures trial participants are undergoing.
Overall, patients who enter trials see it as part of their larger role of advancing science. One respondent said, “Within the cancer community, there is a profound altruistic feeling. They want to help by participating in trials, and the data shows that when they do, they feel positively about the experience.” Survey respondents did feel we need to incentivize more participation in clinical trials; otherwise, it will be hard to move personalized medicine forward.
Enabling research use of information collected in the patient care process could significantly accelerate medical research. EHRs and clinical databases and warehouses can make the work of specialists in one discipline widely accessible to specialists in many disciplines. EHR systems could speed data acquisition and searching, allow mass computing and sampling, and provide the research community access to a broader and more diverse patient population. Improvements made in EHR systems in response to research needs will ultimately serve clinical care needs as well.
“We must remember that the true foundation of this progress is public trust. It is not enough merely to develop the knowledge and information that will make personalized healthcare possible. In addition to developing the information, we must use it correctly.”
-- Michael O. Leavitt, Secretary of U.S. Department of Health and Human Services
It would be inaccurate to say there is only one patient community. There are hundreds, perhaps thousands of them, each defined by different experiences as their members manage disease from diagnosis through treatment and possibly cure. Patient awareness and understanding of personalized medicine and healthcare has begun, but it will be an ongoing process that will vary and evolve based on the disease.
The national discussion about personalized medicine has mostly occurred at the 30,000 foot level and has yet to comprehensively engage and permeate the broad array of patient communities with its myriad concerns.
In order to understand the key role of patients in driving the adoption of personalized healthcare approaches, FasterCures conducted a qualitative research survey of disease research organizations, patient advocates, and patients to determine understanding, awareness, and expectations of personalized healthcare. For the survey, we reached out to senior executives of 10 groups in the FasterCures Redstone Acceleration & Innovation Network (TRAIN). We also identified an additional five national organizations that are not in TRAIN that represent the issues related to diseases that affect millions of Americans.
TRAIN is a group of unique nonprofit foundations that fund medical research across a spectrum of diseases, from breast cancer to Parkinson’s disease. In many cases TRAIN’s member foundations have been created by patients and their families who are frustrated by the slow pace of change in the traditional medical research system. They represent the kind of organizations that are fast becoming the engine behind innovation in disease research – collaborative, mission-driven, strategic in their allocation of resources, and results-oriented. They are organizations that have a singular focus on, and a significant stake in, getting promising therapies from the laboratory bench to the patient’s bedside as rapidly as possible.
Figure 1 – FasterCures’ TRAIN Program
TRAIN has come together under the auspices of FasterCures – a nonprofit “action tank” whose mission is to save lives by saving time in the research, discovery and development of new medical solutions for deadly and debilitating diseases. The TRAIN network helps it members to more easily and effectively support each other’s efforts to produce better and faster results, and to bring their sense of the urgency about conducting more and better bench-to-bedside translational research to the medical research community as well as to the public at large.
FasterCures surveyed groups using email and telephone-based methods and attempted to reach representatives from a variety of diseases ranging from preventable to incurable. Specifically, representatives from the following groups were interviewed:
|Organization||Organization Overview||Contact, Title/Role||Outreach Mechanism|
|Accelerated Cure Project for Multiple Sclerosis||Organizes the research process for multiple sclerosis and encourages collaboration between research organizations and clinicians.||Art Mellor, President & CEO, Co-Founder, Director||E-mail Correspondence|
|Alpha-1 Foundation||Identifies those affected by Alpha-1 Antitrypsin Deficiency (Alpha-1) and improves the quality of their lives through support, education, advocacy, and to encourage participation in research. The Association has over 70 volunteer-led support groups around the U.S||John Walsh, President||Phone Interview|
|Alzheimer’s Association||Mission is to eliminate Alzheimer’s disease through the advancement of research; to provide and enhance care and support for all affected; and to reduce the risk of dementia through the promotion of brain health. The organization’s achievements and progress in the field have given thousands of people a better quality of life and brought hope for millions more.||Jennifer Zeitzer, Associate Director, Federal Policy||Phone Interview|
|American Heart Association||Nation’s oldest and largest voluntary health organization dedicated to building healthier lives, free of heart disease and stroke. In fiscal year 2006–07 the association invested more than $554 million in research, professional and public education, advocacy and community service programs to help all Americans live longer, healthier lives.||Derek Scholes, Government Relations Manager||Phone Interview|
|Autism Speaks||Focuses on increasing awareness of autism spectrum disorders, to funding research into the causes, prevention, treatments and cure for autism, and to advocating for the needs of affected families.||Nancy Jones, Program Director||Phone Interview|
|COPD Foundation||Mission is to develop and support programs which improve the quality of life through research, education, early diagnosis, and enhanced therapy for persons whose lives are impacted by Chronic Obstructive Pulmonary Disease.||John Walsh, President||Phone Interview|
|Epilepsy Therapy Development Project||Mission is to advance new therapies for people living with epilepsy; supports the commercialization of new therapies through direct grants and investments in promising academic and commercial projects.||Joyce Cramer, President||Phone Interview|
|Friends of Cancer Research||Raises awareness and provides public education on cancer research in order to accelerate the nation's progress toward better tools for the prevention, detection, and treatment of all cancers .||Jeff Allen, Executive Director||Phone Interview|
|Hydrocephalus Association||Provides support, education and advocacy for people whose lives have been touched by hydrocephalus and the professionals who work with them; advocates for increased research and funding to advance understanding, improve diagnosis and treatment, and find a cure.||Dory Kranz, Executive Director||E-mail Correspondence|
|Lance Armstrong Foundation||Focuses on cancer prevention, access to screening and care, research and quality of life for cancer survivors. LAF has raised more than $260 million for the fight against cancer.||Adam Michael Clark, Director of Health Policy||Phone Interview|
|Michael J. Fox Foundation for Parkinson’s Research||Mission is to ensure the development of a cure for Parkinson’s disease within the decade through an aggressively funded research agenda. The Foundation has funded over $126 million in research to date.||Debi Brooks, Co-Founder||Phone Interview|
|National Health Council||Represents 119 national health-related organizations working to bring quality health care to all people. Its core membership includes some 50 of the nation's leading voluntary health agencies representing about 100 million people with chronic diseases and/or disabilities. Other Council members include professional and membership associations, nonprofit organizations with an interest in health, and major pharmaceutical and biotechnology companies.||Myrl Weinberg, President||Phone Interview|
|Parkinson’s Action Network||Serves as the voice of Parkinson’s on numerous public policy issues affecting the Parkinson’s community.||Mary McGuire Richards, Deputy Chief Executive Officer||Phone Interview|
|Prostate Cancer Foundation||Provides funding for more than 1,400 research projects at nearly 150 institutions worldwide; advocates for greater awareness of prostate cancer and more government resources, resulting in a twenty-fold increase in government funding for prostate cancer.||Jonathan W. Simons, President & CEO||Phone Interview|
|Susan G. Komen for the Cure||Largest grassroots network of breast cancer survivors and activists fighting to save lives, empower people, ensure quality care for all and energize science to find the cures. Invested more than $1 billion in the fight against breast cancer in the world.||Elizabeth Thompson, Managing Director, Public and Medical Affairs||Phone Interview|
Additionally, FasterCures posted a description of the goals of this white paper along with several questions on PatientsLikeMe to solicit candid feedback from patients. We received responses from 32 patients. The responses we garnered from this process are woven throughout this white paper. More patients are turning turn to online tools like PatientsLikeMe where they interact to help improve their outcomes. The data they provide helps researchers learn how these diseases act in the real world.
Overall Perspectives About Personalized Healthcare
Respondents identified a wide spectrum of current applications of personalized medicine for specific diseases. Our survey found that patient awareness and understanding of personalized medicine has begun, but it will be an ongoing process and that educational process will vary based on the disease. Everyone interviewed had some understanding of what personalized healthcare was, and the potential benefits it will offer as we transition from a trial-and-error, one-size-fits all approach to treatment to one that is tailored to individuals. Respondents on PatientsLikeMe were aware of it in a general sense, but didn’t necessarily know that it was called personalized healthcare.
There were some differences in whether people thought personalized healthcare was simply a way to understand the genetic and individual basis of disease or rather another way to segment patient populations and offer tailored therapies.
Even among groups who characterize themselves as less engaged on this issue, there was still widespread acknowledgment that this is the direction in which 21st century medicine is heading. There was however, a sense that the leadership of the patient community lacked a clear sense of what was, and was not personalized medicine, identifying the need for additional work on definitions and illustrative examples. A wide spectrum of current applications of personalized medicine to specific diseases was represented by respondents including warfarin testing and BRAC1 for breast cancer.
Citing the Need for Patient-Centered Care
Some of the issues raised by the interviews were not always specific to personalized healthcare but instead represented challenges that patients have faced for years. Specifically, respondents expressed widespread frustration with the inability of the healthcare system to address each patient’s needs, and to efficiently and effectively coordinate care across providers and conditions. Personalized healthcare will not be immune to these challenges, and as innovative treatments and diagnostics grow more complex, it is a reasonable concern that the insufficiencies within coordination of care will become exacerbated.
The need for patient-focused care is increasingly more important as scientific discoveries bring us closer to personalized health care. “We need to address the medical and social goals of the whole person with multiple co-morbidities in the context of their individual life circumstances. We must try to get away from a purely medical model that offers only a disease-by-disease approach without consideration of personal desires such as living independently, remaining in the workforce or managing chronic pain,” offered Myrl Weinberg, President of the National Health Council, which represents over 120 member organizations including patient advocacy organizations.
"People with chronic conditions will interact with the health sector for the rest of their lives. If patients are an afterthought and not engaged at the front end of the research process, our collective opportunity to address the complicated medical and social needs of the whole person may be lost, and the scientific advances of personalized medicine and the expected benefits will be diminished,” said Weinberg.
Even more strongly, a patient said, “What I’ve experienced so far in most hospital environments is all but personalized… I felt more like cattle than a human being in general.”
If patients are an afterthought and are not engaged at the front end of the research process, the scientific advances of personalized medicine and the expected benefits to patients will be hindered. If patients are to be involved in clinical research leading to advancements in personalized healthcare, they need better information and a deeper understanding of it based on clear, concise, and accessible information.
A theme emerging from our analysis was that perspectives on personalized healthcare are directly shaped by the state of the science in a given disease area. All groups expressed knowledge of personalized healthcare and a majority had participated at some level in meetings and discussions on this topic. However, for diseases with a strong understanding of the mechanism causing the illness and associated targeted therapeutics, respondents offered an even more robust understanding and appreciation of personalized healthcare.
Many recognized the potential advances on the horizon for their disease area, but remarked that it still feels far enough away that it is difficult to reach and therefore difficult to plan for. “We are here and we are far away from personalized healthcare all at once,” mentioned one respondent. With some chronic diseases like heart disease it is difficult to project where the science will go, since its prevention and its treatment utilize both medical and public health approaches.
Co-morbidities are an increasing issue for many patient groups. For example, 65 percent of patients with chronic obstructive pulmonary disease (COPD) report six to ten co-morbidities, including conditions such as arthritis, diabetes, and cardiovascular disease. For example, in the case of Alzheimer’s disease, 96 percent of patients have other conditions and data shows that Medicare spends up to three times more for an Alzheimer’s patient with diabetes.
“Personalized healthcare of the future clearly needs to address co-morbidities,” asserted John Walsh, of the COPD Foundation. It will be important to recognize the interaction among different diseases and that personalized healthcare for one individual might require coordinating multiple treatments. Moreover, pharmacogenomics will play a crucial role in understanding efficacy and toxicity of drugs given to patients with co-morbid diseases.
All respondents clearly understood the benefits of personalized healthcare described by the Personalized Medicine Coalition as the “right treatment for the right person at the right time.” We found a consensus that it would be a significant advancement if the tools of personalized healthcare allow for earlier diagnosis and improved treatment success, including targeting drugs for use in people who will derive a benefit.
We found a dearth of understanding among respondents in the role personalized healthcare can play in avoiding drugs that will lead to adverse events. The removal of Vioxx from the market and the black box warning placed on other drugs attract big headlines in the media and patients are aware of these events. However, they do not always recognize that the identification of a drug causing severe side effects in a population subset is an advance in personalized healthcare. Some saw that future relabeling or warnings for medications could serve as teaching opportunities for the patient community about what personalized healthcare can offer.
Personalized healthcare has been defined as offering the promise of better care delivered more efficiently. In areas such as oncology, patients want better assurances that treatments will work for them. Particularly in cancer treatment, patients do not always have confidence that their treatment will be effective, thus they fear the side effects of a treatment that may not yield benefit. In the breast cancer community, survivors are focusing more on survivorship care plans that help them track the impact and potential for side effects of the treatments on their health down the road.
Impact of Personalized Healthcare on Costs
Many respondents felt it is difficult to completely predict how personalized healthcare will unfold in the next 10-15 years and its impact on escalating healthcare costs. If personalized healthcare can help reduce costs, everyone regarded this as a positive and important benefit. Most respondents mentioned that they saw costs going up before going down as a result of personalized healthcare.
Patient advocates believe that personalized healthcare will ultimately lower costs by:
Respondents thought the cost to develop targeted, personalized therapies could be higher than the costs of developing existing treatments and might be labeled for use in smaller market sizes which could increase drug pricing. Thus there is concern that as therapies become more tailored, they may also become more expensive, and that investment in drugs for lower incidence populations won’t get pursued. Uncertainty about how payers will integrate targeted therapeutics into coverage and reimbursement decisions exists.
Concerns about Personalized Healthcare
Drug Development. Respondents acknowledged that the drug development models that currently exist will have to evolve to prepare for the personalized healthcare advances. There needs to be a process in place that considers the implications of the creation and characterization of subgroups of patients within a disease by both pharmaceutical and biotechnology companies and by the U.S. Food and Drug Administration (FDA). There are opportunities within FDA to make sure all the required policies are in place to promote the advancement of personalized healthcare practices. A robust post-marketing system needs to be in place to identify safety risks as these drugs are used by a more heterogeneous population. Also, the research building blocks with FDA drug safety efforts need to be aligned to learn more about how drugs are experienced in a large population.
From the scientific perspective, data continues to come in on most diseases about the variability within the particular disease class. Scientists and advocates are increasingly discussing the possibility of different subtypes of their particular disease areas. For example, Parkinson’s disease (PD) patients present to their doctors with their own personal mix of symptoms that roughly categorize them as PD patients. When treated, these patients often experience highly varied responses to medications. This known heterogeneity is still generally overlooked if not ignored as treatment protocols consider all these patients in a single category of disease. In fact, recent “failures” in clinical trials in PD might more appropriately be viewed as “inconclusive” findings with pockets of treatment success but insufficient (underpowered) evidence to propel the trial to its next stage of investment and/or investigation. The Michael J. Fox Foundation for Parkinson’s Research (MJFF) is focused on attempting to better understand and characterize the “subtypes” of disease with the particular goal of improved patient selection for clinical trials in mind.
Also, some respondents raised the question of what needs to be done to facilitate the process of subgroup analysis and how to study different populations that respond differently to treatments. It was also acknowledged that even in areas where there are some targeted therapies identified, more research is needed. The work is not over when the initial finding is made. For example, new analysis of the data shows that women taking Tamoxifen can metabolize the drug differently.
“It is clear we need to find ways to do clinical trials that are faster and cheaper,” asserted Debi Brooks, Co-Founder of MJFF. “One of our strategies is to fund creation of tools that can contribute to improved trial design in the first place.” In addition to the continued work to identify subtypes of disease, MJFF has a collaborative project underway where the Parkinson’s Institute and the company 23andMe are working to validate web-based surveys that could provide a proof-of-concept for tools to enable more robust data collection in the clinical trials process. In smaller disease populations that have potential subpopulations of disease, improved and innovative clinical trial design to increase the power of smaller sample sizes will help researchers complete studies faster.
Additionally, until we have diagnostics that can identify who should receive which drug, patients want an improved adverse events reporting system that can contribute to research and development of such tests. One way to better understand extrinsic factors like drug-to-drug interactions, medical practice, diet, alcohol use and intrinsic factors like gender, genetics, and race is to establish systems that improve adverse event tracking. Currently the FDA is actively embarking on this task. In May 2008, FDA launched its Sentinel Initiative with the goal of creating and implementing a national, integrated, electronic system for monitoring product safety. This effort will strengthen FDA’s ability to monitor the performance of a product throughout its life cycle and enable real-time reporting of potential safety signals for medical products currently on the market.
Some respondents are concerned about genetic testing companies and want assurance these tests are accurate and that support systems and providers are ready and waiting after patients take the tests. The regulatory framework for these testing companies is still being created; the FDA does not evaluate these tests for accuracy, though a federal panel recently recommended stepped-up oversight. Different states have different regulations about the ordering of tests and the involvement of medical professionals; several states have ordered direct-to-consumer testing companies to stop selling their tests to residents of their states until they prove they have met that state's quality standards (which several companies subsequently did and received licenses to operate). Two major associations for genetics professionals disagree about whether any genetic tests are appropriate for sale directly to consumers without a medical intermediary. While regulators and medical professionals deliberate, the popularity of genetic testing in undeniably increasing, helped along by "genetic social networking" Web sites and program launches at venues such as the Mayo Clinic, Canyon Ranch Institute, and the Cleveland Clinic, opening whole new frontiers in the consumer information revolution.
Gatekeepers. Many respondents identified their patients’ need for a “medical home” to provide coordinated and targeted care. One patient said, “So, while providing more detailed tracking is helpful, one also needs a doctor who is receptive to that same tracking.” Some saw how this approach may create a situation where the provider serving as a gatekeeper may instead block or slow access to care. As patients have more and more access to information, and as they have mobilized, they want access to providers that will discuss options and a gatekeeper may stand in the way of that. Similarly, as therapies start to become available for subgroups of patients, there is concern about how the payer community will react. One respondent said, “What if treatment is only available if it works for everyone with our disease?”
There has been a lot of discussion in the past couple of years about comparative effectiveness. This is the approach that many healthcare stakeholders are turning to as a possible solution to curb healthcare spending. Comparative effectiveness research seeks to provide a cost-effective and efficient approach to identifying the best in drugs, devices, biologics, and medical procedures. However, as the drumbeat for comparative effectiveness intensifies, it is important to ensure that the law of averages doe not steer decision-makers away from treatment that demonstrates true patient benefit. Comparative effectiveness needs to allow for new research findings, as well as allow for diseases that may ultimately encompass hundreds of genetic variations and subtypes.
Privacy. There is lingering concern about whether individual test results and large datasets with personal information will be used against people for employment or insurance purposes. One respondent said that the passage of the Genetic Information Nondiscrimination Act (GINA) hasn’t assuaged those fears. (For more information about GINA, see page 18). However, a majority of the patient organization leaders we spoke with felt that privacy needed to be dealt with and closely monitored, but that it should not interfere with scientific and healthcare delivery advances. One respondent said, “We don’t want the politics of fear of privacy breaches to get in the way of the needed advances.”
Advances in 21st century healthcare will heavily depend on advances in genetic research and other medical solutions that fuel the search for new treatments and cures. The passage of the GINA allows patients to more confidently participate in studies that search for linkages between genes and disease, to enroll in clinical trials for new targeted drugs, or to provide samples for DNA analysis to optimize their own disease prevention and treatment.
Due to the lack of EHRs in many care systems, respondents noted that often patients’ records were private, even to them. Some felt that the general consumer population was more concerned about privacy than patients, many of whom understand the value that pooled data can provide to the understanding of their disease. However, some still have concerns about posting their data onto some of the online personal health records systems. One patient said, “One of the risks that is going to emerge very quickly is the privacy status of medical records held by companies which function as control repositories.”
The impact of the Health Insurance Portability and Accountability Act (HIPAA) and privacy were raised in the context of conducting research studies. In many disease areas, sample collection is becoming standard practice, and yet there is still confusion of what is and is not allowable under HIPAA. There was concern about the impact of restrictions on the speed at which research can be conducted, and the fact that patients continue to lose ground in battling their conditions with these delays.
In order to be truly effective with optimal impact, patient-centric and proactive healthcare practices must be supported by comprehensive education and communications efforts. The general public needs to understand genetic medicine - what it can and cannot do - and not be afraid of the power of this area of science. Healthcare providers need to be able to sift through the most recent advances in medicine and translate these into real-world scenarios, carefully putting the most promising developments into context for each patient. The doctor-patient relationship needs to be defined by clear and transparent lines of communication. It is vital that new developments brought about by personalized medicine approaches be managed and translated responsibly and effectively into tangible treatment protocols when appropriate.
Most felt that it would not be difficult to educate patients about the advances that will come from personalized healthcare. Patients are hungry for information, and many survey respondents mentioned how self-motivated their constituencies are. Many respondents cited the high motivation their constituencies have to accelerate the research process in order to have better treatments available.
One respondent felt that trusted messengers (e.g., medical associations, advocacy groups, the U.S. Surgeon General) could lead national efforts to educate consumers. It was pointed out that a major risk relates to unrealistic expectations by the patient. This patient said, “Sometimes, even with the right diagnosis and treatment, I won’t get better.”
It was felt that all stakeholders involved need to carry the messages to patients about the potential benefits personalized healthcare offers. Providers ranging from primary care physicians to specialists and all other providers that intersect with the patient communities need to be given tools to help them communicate these messages.
There is still a lot to learn about how patients will respond to detailed genetic profiling as that becomes a reality. One person said, “The jury is still out about how this will really be rolled out over time and how patients will manage this new information.”
Some groups talked about needing more documentation of successes in the area. “We need to have the demand for the science defined publicly so it is constituent driven.” Another respondent spoke of the flat funding for NIH and the concerns that it raises for the future pace of scientific advances. These comments speak to the need to engage fully with patients to be research advocates and suggests that the more motivated a patient is to get involved in a patient-oriented organization, the more likely they will be engaged in personalized healthcare.
There are several areas of healthcare that will be significantly affected by the adoption of a personalized medicine approach. Most notably, personalized healthcare alters the traditional model of healthcare delivery, shifting some responsibility toward the consumer while simultaneously requiring healthcare providers to process even more information. It also raises questions about:
Use of Genomics and Biomarkers to Predict Disease
An individual’s genetic and molecular profile, if accurately assessed, has the potential to predict predisposition to certain chronic diseases – for example, prostate cancer, glaucoma, Alzheimer’s disease, or heart disease – as well as guide disease prevention strategies and more effective use of therapies. Currently, many of these tests are predictive, rather than diagnostic, which means results are provided to otherwise healthy consumers as probabilities, or relative risks for an individual versus the general population. Most tests rely on SNP analysis or whole genome scans but others are based on non-DNA biomarkers associated with a particular pathological or physiological state.
As the technology for such testing – in particular genomic analysis – has advanced, the costs have decreased, which has spawned the growth of a new industry focused on personalized genomic services, frequently marketed directly to the consumer. Because in most cases the consumer can purchase the test and receive results without the direct involvement of a personal healthcare professional, several concerns have arisen.
Those advocating for more consumer involvement in test decisions believe that the slow pace of provider uptake and professional education, combined with more focus on consumer education and autonomy warrants such an approach.
A specific field in personal medicine is pharmacogenomics, sometimes called molecular medicine. Pharmacogenomics is based on identifying genetic factors that directly influence a person’s response to a drug. It has the potential to enhance understanding of disease etiology and diagnosis as well as the determinants of drug effects so better prescribing decisions can be made. What makes pharmacogenomics both unique and a challenge is that it melds the worlds of diagnosis and treatment in new and different ways. It is an application of genetics and pharmacology that brings genetic testing into the purview of primary care, well beyond the more traditional bounds of rare diseases, where genetic testing has its historical roots.
It is likely that in the future, drugs incorporating pharmacogenomic data will involve both a therapeutic agent and diagnostic test, wherein the diagnostic test will precede the prescription, which suggests a new model for healthcare delivery. Because pharmacogenomics can help physicians determine whether a proposed drug therapy is relevant to a given patient, this approach to clinical care has the potential to enhance preventative medicine and reduce the level of trial-and-error in patient management. As with the use of personalized genomics testing services, pharmacogenomics will increase the volume of information that will have to be processed and used by patients and their healthcare providers.
“…in the next 15 years the pharmacopoeia that we use for treating lots of disease will be very heavily influenced by the things we’re discovering right now about the molecular basis of disease. But that has the longest lead time, and so it won’t happen overnight for many conditions.”
-- Francis Collins, former Director of the National Human Genome Research Institute at the NIH
New Approach to Clinical Trials
One of the challenges of personalized healthcare lies in assessing outcomes. First, because some of these interventions are being offered directly to the consumer it will be difficult to follow consumers to assess effectiveness and other outcomes. Thus, it will be critical that there be some publicly funded studies in these areas.
Second, because the very nature of clinical evidence will become more focused on individuals and subpopulations, personalized healthcare challenges the notion of randomized clinical trials as the gold standard for testing the safety and efficacy of new diagnostics and drugs. Simple reliance on biomarkers may be a poor method of predicting outcomes.
At least for some time it will be critical to evaluate large numbers of people before understanding the relative role of any given variant and its significance in personalized healthcare. Weak predictability combined with our lack of understanding of the causal relationship between genes and drug responses makes it difficult and costly to conduct appropriate validation studies. These studies are probably going to have to be large-scale, prospective studies that measure genetics and other biomarkers over time and follow up with patients for long-term outcomes.
As such, analyzing evidence emerging from personalized medicine will require a different set of skills than those used in traditional clinical trials, combining diagnostic evidence with safety and efficacy evidence. Research will be needed to develop the best methods for collecting and analyzing evidence and large numbers of subjects will be needed for clinical trials.
Seizing Proven Opportunities
While nearly 10 percent of the drugs approved by the FDA include pharmacogenomic information in their labeling, only four have a sufficient body of evidence to support a requirement for genetic testing before treating a patient. Many other drug labels reference validated biomarkers and associated diagnostic assays, but these are only ‘recommended’ to provide additional information—not because evidence has shown their impact on outcomes to be variable or unreliable, but because there is no evidence regarding outcomes at all. This highlights a fundamental imbalance in the progress of pharmacogenomic research: more and more studies are linking genotype to the mechanisms of drug metabolism and/or efficacy, but few are taking the critical next step of tying modified dosing or selective use of drugs based on genotype to improved patient outcomes. Stakeholders have identified the lack of clinical evidence base as a critical barrier to integration of personalized medicine into routine practice. Making this connection to outcomes is necessary to realize personalized medicine’s promise.
The stakes are even higher since many of the drugs for which pharmacogenetic factors have been identified are often dangerous to patients and adverse reactions can be lethal. The FDA’s list of drugs with genetic biomarkers includes chemotherapy agents, anticoagulants, and neurologic agents—drugs whose side effects would exclude them from use were it not for the lack of suitable therapeutic options for patients with grave conditions. With more than 770,000 injuries and deaths due to adverse drug reactions and medication errors each year, elucidating whether genetic information can improve outcomes and reduce some of these events is critical to ensuring the safety of patients who take these drugs.
A growing body of research reveals the great promise of using an individual’s genetic information to guide his or her care; the next step for us is to seize that demonstrated opportunity by confirming whether this information can effect real change in short- and long-term patient outcomes. We can save patients’ time by building the evidence base as soon as possible so that caregivers can act on the promise of personalized medicine. We can save patients’ lives by defining how genetic tools can ensure a patient’s treatment is not only timely and beneficial, but safe.
“These are catch-all diseases (e.g., cardiovascular disease, Alzheimer’s disease,
rheumatoid arthritis, and cancer) that look the same, but when you scratch below
the surface, you begin to understand that the underlying physiology of similar phenotypes can be fundamentally different.”
-- John Sninsky, Vice President of Discovery Research at Celera
Precious patient resources are lost to medical research if individuals fear that genetic information, test results, or electronically stored health records might be used against them by insurers or employers. Public opinion has long reflected widespread anxiety about misuse of personal health information.
In a 2004 survey of 470 people with a family history of colorectal cancer, for example, about half said their concern about genetic discrimination was high, and that they would be significantly more likely to pay for genetic testing out of pocket, use an alias, or ask for test results to be excluded from their medical record. Dr. Francis Collins, former Director of the National Human Genome Research Institute, has said that “at the NIH, fear of genetic discrimination is the most commonly cited reason that people decline to participate in research on potentially life-saving genetic testing for colon cancer and breast cancer. One-third of eligible participants have declined on this basis.” People have been reluctant to know and act on genetic health risks, to their own detriment and society’s as a whole.
A patchwork of legislation at the state and national levels has tried to regulate the use and disclosure of personal health information, most prominently the 1996 HIPAA, which regulated the use and disclosure of such information by certain “covered entities.” Successfully navigating HIPAA and human research protections will be critical to advancing the science of personalized medicine. And in 2008, after 13 years of effort, Congress passed and the President signed the GINA, which advocates have called the critical civil rights bill for the genome era.
To summarize, GINA:
The health insurance provisions of the bill will take effect in May 2009 and the employment provisions will take effect in November 2009. GINA does not apply to members of the U.S. military, or to other forms of insurance such as life, disability, or long-term care.
It is expected that passage of GINA will boost demand for genetic tests, leading to improvements in care and more participation in research that involves the collection of genetic information. But the passage of legislation is not enough. There has to be effective education of the public and providers about the protections that GINA confers. That includes compelling demonstration of the benefits genetic testing and personalized medicine will bring to them as individuals, as well assurance that new tests and personalized treatments will be paid for.
In addition, the application of GINA’s protections must be clear and consistent. Lessons must be learned from the experience with HIPAA, whose provisions regarding privacy have been misinterpreted and over interpreted in ways that have been detrimental to the conduct of medical research. In a 2007 survey published in the Journal of the American Medical Association, more than two-thirds of epidemiologists reported that the HIPAA Privacy Rule has made research more difficult, adding a great deal of cost and time to study completion without a countervailing positive influence on subjects’ privacy.
And we need to continue to look beyond GINA at additional ways in which privacy concerns must be addressed in order to promote and facilitate the development of personalized healthcare. For instance, not addressed by GINA are all the security and privacy implications of the large databases of medical records tied to biological samples that will be required for the promise of personalized medicine to be realized.
Patient-centered care requires that patients be informed, proactive partners with their physicians when facing health decisions. But a major hurdle for patient-centeredness in personalized medicine is a lack of ‘genetic literacy’ or a fundamental understanding of genetics and health in the general public. Informed patients are critical to patient-centered care, but as personalized medicine techniques become more sophisticated and information more complex, caregivers will face steeper challenges in communicating effectively with patients of all education levels and backgrounds. Improving the genetic literacy of the general public will be an important step in empowering patients to seek and understand personalized medicine. As early as 1994, the National Research Council (NRC) was making calls for a "genetically literate public that understands basic biological research, understands elements of the personal and health implications of genetics, and participates effectively in public policy issues involving genetic information."
Unfortunately, the past 14 years have not seen the NRC’s vision realized. A 2006 study on public attitudes about evolution showed that on an index of genetic literacy, American adults scored a median of 4 on a 0-10 scale, indicating that many adults are not well-informed of genetics principles.Some studies have shown that minority populations of diverse cultures, in particular, have limited genetic knowledge despite a desire to know more about genetics and health.
There are a number of programs aimed at addressing these deficits in genetic knowledge in the public: for example, March of Dimes has launched its Consumer Genetics Education Network (CGEN) Project, a five-year program to address genetic literacy in underserved populations and to increase access to culturally and linguistically appropriate genetics education programs and services. The Health Resources and Services Administration funds the activities of the ‘Consumer Initiatives for Genetic Resources and Services’, a discretionary grant program through the Maternal and Child Health Bureau. Programs receiving grants provide education about genetics and genetic testing to patients, usually in the context of specific screening tests or conditions. Genetic Alliance is one of the recipients of MCHB grants to improve genetic literacy, and is also working with funding from Centers for Disease Control and Prevention to develop the Access to Credible Genetics (ATCG) Resources Network, a genetics information resource for patients with rare genetic diseases and their families and physicians. The National Human Genome Research Institute (NHGRI) at the National Institutes of Health also has active grants awarded to projects addressing genetic literacy among underserved groups.
Personalized healthcare promises to be curative, predictive, and preventive. Our qualitative survey of patient organizations and patients themselves found a shared anticipation of the cutting-edge possibilities of personalized healthcare advances, especially as seeds of innovation yield tangible tools that move this approach forward. However, patient involvement is central to generating a sea-change in the traditional model of healthcare delivery.
Realigning the promise of personalized healthcare requires effectively and efficiently shifting some responsibility to the consumer while simultaneously requiring healthcare providers to process even more information.
We offer a framework for multiple stakeholders in the healthcare delivery system to act on to make personalized healthcare a reality:
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 See FDA‘s Table of Valid Genomic Biomarkers in the Context of Approved Drug Labels, http://www.fda.gov/cder/genomics/genomic_biomarkers_table.htm.
 Deverka PA et al., “Integrating Molecular Medicine in the US Healthcare System: Opportunities, Barriers and Policy Challenges,” Clinical Pharmacology & Therapeutics, 2007; 82(4): 427-34.
 See Agency for Healthcare Research and Quality report, Reducing and Preventing Adverse Drug Events to Decrease Hospital Costs. Research in Action, Issue 1, March 2001, http://www.ahrq.gov/qual/aderia/aderia.htm.
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 Apse KA, et al., “Perceptions of genetic discrimination among at-risk relatives of colorectal cancer patients,” Genetics in Medicine, 6:510-516, 2004.
 Kibak P, “After long wait, GINA becomes law,” Clinical Laboratory News, July 2008.
 Carhart S, “Coming Century to Witness Major Changes as Hospitals Adapt to Personalized Medicine,” BNA’s Health Law Reporter, 17(25): 1155, 2008.
 See Genetics and Public Policy Center, www.DNApolicy.org
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 National Research Council report, Assessing genetic risks: implications for health and social policy, 1994, Washington, DC: National Academies Press.
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 See March of Dimes CGEN Project Website http://www.marchofdimes.com/professionals/15829_29466.asp
 Health Resources and Services Administration, Maternal Health Bureau, Consumer Initiatives for Genetic Resources and Services Abstract search, https://perfdata.hrsa.gov/mchb/DGISReports/Abstract/AbstractSearch.aspx, Last Accessed September 10, 2008.