PERSONALIZED HEALTH CARE: OPPORTUNITIES, PATHWAYS, RESOURCES

This initiative includes funding for genome-wide association studies, methods of analyzing gene-environment interactions, environmental “sensors” that detect exposure, and measurement of diet and physical activity.

Contents

Foreword by HHS Secretary Michael Leavitt.

Opportunities: Envisioning a New Kind of Health Care

Challenges: Prerequisites to Achieving Personalized Health Care

Pathways: Building Blocks of Personalized Health Care

Resources: HHS Programs Supporting Personalized Health Care

I. Expansion of the Science Base

• Human Genomics Research.
• Genome-Wide Association Studies
• Genes, Environment and Health Initiative
• Human Genome Epidemiology Network
• National Health and Nutrition Examination Survey
• Biomarkers Consortium
• NIH Biomarkers Projects
• Cancer Research Programs Supporting Personalized Health Care
  • National Cancer Institute
  • Office of Biorepositories and Biospecimen Research
  • National Program of Cancer Registries
• Heart, Lung, and Blood Research Programs Supporting PHC
• Eye Research Programs Supporting PHC

II.     Health Information Technology

• American Health Information Community
• Office of the National Coordinator for Health Information Technology
• Health Information Technology Initiative
• Health Information Technology for Safety Net Providers
• Use of Medicare Data To Support Research on Health Outcomes

III.    Intervention Development and Review

• Critical Path Initiative To Improve Medical Product Development
• Regulatory Submission of Genomic Data in Medical Product Development
• Review of Genetic Tests for Use in Clinical Practice
• Pharmacogenetics Research Network

IV.   Integration Into Clinical Practice

• Health Data Standards and Genetic Information Resources.
• Evaluation of Genomic Applications in Practice and Prevention
• Roadmap for Medical Research: Clinical and Translational Science Award Program
• Cancer Biomedical Informatics Grid (caBIG™)
• Promoting Quality in Genetic Testing
• CLIA Oversight of Genetic Testing
• Promoting Effective Communication Between Laboratories and Clinical Settings
• Genetic Testing Reference Materials Coordination Program
• Evidence-Based Practice
• Effective Health Care Program
• Centers for Education and Research on Therapeutics
• Accelerating Change and Transformation in Organizations and Networks
• Practice-Based Research Networks
• Health Resources and Services Administration Resources To Support PHC
• Genetic Services Program
• Genetic and Newborn Service Screening Regional Collaboratives
• National Hemophilia Program
• Sickle Cell Service Demonstration
• National Cord Blood Inventory
• C.W. Bill Young Cell Transplantation Program
• Newborn Screening Quality Assurance Program
• Genetic Testing and Newborn Screening Disease Information Portal
• Family History
• U.S. Surgeon General’s Family History Initiative
• Family History Public Health Initiative

V.    Privacy and Other Issues.

• Protecting the Privacy of Patient Health Information
• Secretary’s Advisory Committee on Genetics, Health, and Society
• National Committee on Vital and Health Statistics
• Advisory Committee on Heritable Disorders and Genetic Diseases in Newborns and Children.

Overview of Federal Health Care Delivery Programs

Glossary of Terms

HHS Agencies and Web Sites

HHS-Supported Web Sites of Interest

Foreword

Michael O. Leavitt
Secretary of Health and Human Services

In the coming years, new gene-based knowledge, combined with the advent of health information technology, can make possible a new kind of medical care for Americans: Personalized Health Care.

Of course, health care professionals have always aimed at making medical care as individualized as possible. But in truth, our ability to deliver the right care for each person has been limited.

We have had only partial understanding of human biology at the molecular and genetic levels, where each of us is biologically unique. Our understanding of each person’s particular susceptibility to diseases, as well as his or her individual responses to therapies, has been limited. Physicians diagnose and treat on the basis of symptoms that can be seen and felt. But they have not had access to the underlying biological processes, unique to each of us, that start with the “instructions” in our genes.

At the same time, even our systems for using the health care information that we possess have remained paper-based and siloed. Patient records, filed in different settings, can be difficult to access – a poor foundation for personalization of care.

Finally, we have yet to use the power of networked information that has transformed many other sectors. Despite growing complexity in health care, there is limited online support at the bedside to help health care professionals deliver the best standard of care for each patient. In addition, while controlled clinical trials remain the staple of progress in biomedical science, the additional wealth of information that might be reaped from millions of encounters in day-to-day medical practice remains untapped.

This is not to say that the progress made by American medicine has been anything but remarkable. But the opportunities that present themselves today hold the possibility of a transformation over the coming years and decades that is even more far-reaching. It involves not only breakthroughs in scientific knowledge but, equally important, the application of this knowledge on a patient-by-patient basis. We can see the possibility of health care that is increasingly calibrated to each patient and personally effective for each individual.

One part of the foundation for such a change is our rapidly growing understanding of the human genome and the processes it directs. We envision health care that could:

• predict our individual susceptibility to disease, based on genetic and other factors;
• provide more useful and person-specific tools for preventing disease, based on that knowledge of individual susceptibility;
• detect the onset of disease at the earliest moments, based on newly discovered chemical markers that arise from changes at the molecular level;
• preempt the progression of disease, as a result of early detection; and
• target medicines and dosages more precisely and safely to each patient, on the basis of genetic and other personal factors in individual response to drugs.

Another part of the foundation for personalized health care is the potential for health information technology to help develop new knowledge and put it to effective use. When health information exists in electronic form, capable of being shared securely, it can:

• make the patient’s complete health information available when and where needed;
• provide support to clinicians when they need it, to help them give patients the best standard of care, including information based on individual genetic and molecular factors;
• through secure networks, bring together masses of data from day-to-day medical practice to accelerate our understanding of which treatments work best, and to monitor for safety problems in real time; and
• use the medical evidence developed from such networks to understand differences in patients’ response to drugs and other therapies, learning who benefits from specific treatments, so that therapies can be targeted on a more individualized basis.

Personalized health care is information-based health care. It is health care that works better for each patient, based partly on scientific information that is new and partly on technology to make complex information useful. Whether it involves new biomedical knowledge, data networks for developing that knowledge, or computer supports to manage that knowledge, personalized health care is about a transformed role for information in health care.

This report is an early “reconnoitering,” a glimpse from the perspective of the Department of Health and Human Services (HHS) of the work that lies ahead to achieve personalized health care. From this early stage, we can outline the opportunity. We can roughly see the building plan and identify some of the key elements and pathways that must be traversed. We can recognize the importance of collaboration. We can identify broad prerequisites for personalized health care. And we can identify the HHS resources that are already in play.

We can also identify the need for standards in many new areas. More broadly, we can see the imperative for collaboration across the private and public sectors and across many disciplines and stakeholders.

Finally, 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 health care possible. In addition to developing the information, we must use it correctly.

One of my priorities as HHS Secretary is to help build a strong foundation for personalized health care. That means coordinating work across HHS agencies as well as addressing crosscutting issues, to ensure that new information and capabilities will be used appropriately.

We cannot entirely foresee how different health care may be in the coming decades. It seems inevitable that there will be a significant period of disruption and learning as new capabilities are developed and adopted. Nonetheless, it is incumbent on us to take steps now, even as basic knowledge and technologies are being developed, to anticipate and enable that future. The goal of the health care professional remains to deliver the right care to the right patient at the right time, and that is what personalized health care is about.

Personalized health care means knowing what works, knowing why it works, knowing who it works for, and applying that knowledge for patients. These goals may sound elementary, but a generation of effort lies before us in achieving them – perhaps one of the most complex science-based endeavors in our history. We approach it with high hopes and humility.

Opportunities: Envisioning a New Kind of Health Care

The potential of science to relieve human illness and suffering has long captured people’s hearts and imaginations. In the quest to realize that promise, funding from public, nonprofit, and private sectors converged in the 1980s, boosting the budgets for biomedical research beyond that of engineering and the physical sciences for the first time ever. Fueled by a budget that has nearly tripled in the last decade, biomedical research has become an engine that is now driving the health care system toward new frontiers.

The rate of growth has been exponential. Indeed, for more than 1,000 years, physicians had to rely upon what they could see, palpate, or intuit in order to diagnose, treat, and monitor patients. The last 100 years have brought deeper understanding, as researchers moved from the macroscopic to the microscopic level, learning of cells and cellular processes and fashioning tools and treatments born of these findings. The most recent decade broke all records. Systems biology, bioengineering, genomics, proteomics, nanotechnology, cellular and tissue engineering, bioimaging, computational methods, and advances in information technologies have all shuttled medicine into a molecular future at a pace that exceeds people’s ability to fathom it.

Looking Through a Medical Prism: Disease by Disease

Looking back, we can gain perspective on how far and how quickly we have come.

In 1940, physicians identified cancer by the tissues in which it resided and had access to few treatment options, except for surgery and medications with poorly tolerated side effects. Oncologists today are redefining cancer as the interplay of faulty genes and proteins, independent of tissue location. These are linked to biochemical pathways that are already providing “targets” for custom-designed, cocktail-style therapies.

Physicians in 1940 would not have known to counsel patients with potential heart disease about cholesterol and the risks of high-fat diets and high blood pressure. Often the first symptom of heart disease was sudden death. Now physicians view heart disease as a probability that can be reduced or prevented through knowledge of risk factors, changes in lifestyle, screening exams, medication, and surgical techniques.

Likewise, physicians in 1940 saw diabetes as a pronouncement of a short, restricted, and complication-plagued life. By contrast, contemporary physicians view diabetes as a disease to be managed over a patient’s long lifetime. Doctors today can offer their patients knowledge about its cause, tests for early detection, effective medications, and more sophisticated blood sugar monitoring devices.

And further, today, through clinical and health services research, we know that the progression of diabetes and cardiovascular disease may be significantly influenced by addictive diseases and depression, and that addictions may be a risk factor for some types of cancer. Current brain studies and research into the genetics and biological markers for substance use disorders have the potential to render care even more effective for conditions that are affected by substance abuse.

Personalized Health Care: The Culmination of Biotechnical and Medical Advances

As testimony to medicine’s swift progress and wide-scale success, people are living longer and healthier. While this is an event for celebration, it also presents other issues. Currently 13 percent of the U.S. population is older than 65 years. In the next 25 years, that number is expected to increase to 20 percent. As the population ages, we can expect its risk for diabetes, heart disease, cancer, Alzheimer’s, and other diseases, associated with mid to later life, to rise in tandem. Thus, America’s health system is now shifting to accommodate an older population prone to have complex illnesses caused by multiple factors.

Basic research advances in the context of these changing clinical imperatives have brought a signal point of transition. We anticipate an era of personalized health care. This is the shape of health care in the future: a system that is patient-centric and enables patients to make choices about their health management, with enhanced quality and safety.

Personalized health care is envisioned as a system in which doctors, pharmacists, and other health care providers customize treatment and management plans for individuals. It will be founded upon vast amounts of information that will be readily accessible at clinics and hospital bedsides. The driver is the many applications of information technology that have blossomed during the biomedical revolution. For example, tools like electronic capture will allow easy dissemination and flow of data about medical history, genetic variability, and even patient preferences. Patients will ultimately receive this information, specifically as it applies to them.

This is already happening. A woman with breast cancer now has the option of a predictive test that tells her whether her tumor bears a genetic signature. If she tests positive for the overproduction of a gene product called human epidermal growth factor 2 (HER-2), she is a good candidate for a companion drug called Herceptin, which reins in her excess HER-2 and nearly halves her risk of disease recurrence.

Similarly, a patient with chronic myelogenous leukemia (CML) has access to a diagnostic test that indicates the presence of a mutant gene, called Bcr-Abl. If a patient tests positive, he or she can take a drug called Gleevec, which binds specifically to the faulty gene’s product and so inhibits its cancer-causing action. Early studies show a 90 percent initial response rate in patients with CML and the hope of complete remission.

Personalized health care also offers the potential of gauging a person’s unique drug metabolism. In the doctor’s office, a patient can get a test that discerns whether he or she has a particular combination of 31 possible genetic variations in two liver enzymes, known as cytochrome P450, which together are responsible for metabolizing 40-45 percent of all drugs. The test is intended to help physicians fine tune dosage, based on molecular metabolism rather than previous crude weight estimation.

At its core, personalized health care opens the door to a future focused on disease prevention. This is best demonstrated by a current test for a woman’s predisposition for breast cancer. If she has certain BRCA1 or BRCA2 gene variations, she bears a higher lifetime risk of breast and ovarian cancer. A woman in this situation has the choice of increasing preventive measures, including mammography and clinical breast exams, ultrasound imaging, and biomarker detection. She may also choose to be more aggressive, opting for prophylactic surgery that removes at-risk tissue and/or chemoprevention through drugs such as tamoxifen.

Personalized Health Care Becomes the Norm: The Implications

HER-2, cytochrome P450, and other examples are special cases, but they represent first instances of personalized health care at work. Over time, such cases will amass until they reach a tipping point, when personalized health care becomes the norm rather than the anecdote. As that happens, personalized health care must involve the innovative application of such tools and the knowledge of how best to use them.

The key players in this transformation are health care providers. With new tools, doctors will play new roles. Where once physicians had to practice medicine much like an art form, using macroscopic tools to alleviate symptoms, personalized health care will provide molecular tools and information technology support to deliver care with greater precision, confidence, and individualization.

Making use of genomic profiling tests, large databases of predisposing factors, sophisticated monitoring devices that provide data in real time, and streamlined electronic patient records, physicians will better prevent disease, predict outcomes, and help patients heal faster through personalized care. Doctors also will have electronic tools that give real-time updates about, for example, drug contraindications and results of improved post-surveillance monitoring methods. With these aids, doctors will not have to waste time gathering redundant information. Rather, “smart” tools will enable physicians and nurses to use their time with patients more effectively and to better present choices of treatment and the implications that will follow.

This paves the way for a new doctor-patient relationship. Patients can have access to better communication tools. Interactive systems will allow patients to query electronically about health choices. Patients will have the opportunity to become more health literate and take more responsibility for their own health care. Experiencing fewer side effects and better efficacy of treatment, patients will be more likely to engage in their personalized treatment and management plans. They will be better enabled to view themselves as in control of their own health care. As such, they may be increasingly interested in assembling their own health care information, including individual genetic profiles, family history, past treatments, even personal preferences, into health portfolios – analogous to financial portfolios – to be managed with the help of health care planners, managers, and coaches. Doctors will be better positioned to work with teams of health care service providers who contribute and interpret complex information so they can better guide patients in their choices.

Health care providers, meanwhile, will be making changes of their own. With better screening and profiling tools, medicine can increasingly shift from a reactive and disease-focused model to a health maintenance and preventive care approach. Health care providers will have the ability to track patients through always-current electronic “charts,” available when needed for treatment. This will eliminate the need for repeated collection of histories and physicals, therefore saving time and cost.

Drug developers of the future may also see a cheaper, faster, safer system of discovery, development, and delivery. The current “linear” pipeline of product development should bend into a more “circular” channel. By making de-identified clinical information available on a large scale, the day-to-day delivery of health care can become a platform for research, as well as for quality and safety improvement. When large volumes of aggregated clinical data (stripped of personal identifiers) are available in real time, new avenues will be open to researchers for discovering better leads, more quickly and more closely in tune with real patient needs.

At the same time, with better molecular profiling tools, drug developers will also have the capacity to better tailor their treatment and screening technologies toward smaller numbers of patients. This means that pharmaceutical innovators will be enabled to move away from the blockbuster, one-size-fits-all approach. Instead, “mini-busters” can be targeted to well-identified subpopulations.

Finally, drug approval regulators will develop better models of clinical testing that are coupled with biomonitoring systems which track patients in real time. Overall, development will also shift toward prevention, including early diagnostic indicators as demand for such products increases in tune with patient and physician demand.

This vision of a new kind of health care rests on the achievements of the past, the gathering speed of advances in biomedicine and information technology, and decades of further work. But if the past is prologue to the future, we can expect the investment of time, talent, and resources to grow steadily and the speed of change to be rapid. Converging biomedical technology, medical practice, demographics, and policy initiatives offer a new vehicle to drive personalized health care forward.

Challenges

Prerequisites to Achieving Personalized Health Care

Some important crosscutting social, legal, and technical issues which are prerequisites for achieving personalized health care include the following:

Public Trust

The introduction of powerful genomic technologies into the health marketplace has the ability to positively impact us as individuals and as a society. Genomic information has unique potential to identify and predict the health outcomes of individuals and their families. Establishing the public’s trust for use of personal health and genetic information in electronic health care management systems will be key to ensuring public acceptance of new medical genetic technologies.

An overarching principle of personalized health care is that an individual’s predictive genetic information, when acquired for health care purposes, should be used only for health-related activities, and should not be used inappropriately in making employment or health insurance coverage decisions.

Genetic and Molecular Research

Building on the success of the Human Genome Project, research will emphasize characterizations of the genetic basis of disease and better understandings about the interdependence of genetic and environmental factors. Advances in our basic understanding of research results are bringing the scientific meaning of disease to new frontiers for clinical application. Using powerful consortia of research organizations, biomarkers (specific biological traits used to measure the progress of a disease or treatment) are being identified to better identify the biological underpinnings of specific pathologies.

Some of our research, development, and medical product review processes are focused on more effective, targeted therapies. This knowledge is being translated into clinical tests to monitor drug therapy, thereby enabling health care providers to select drugs that work safely for specific patients and conditions. To ensure widespread adoption of this important new technology, we need to ensure that medical genetic test information is both clinically and analytically valid.

Translation of Knowledge Into Clinical Practice

Rapid advances in technology, biomedical research, and medicine often take many years to be adopted throughout the health care delivery system. The rapid rate of scientific and medical advances outstrips the ability of clinicians and providers to remain up-to-date on the latest medical information. We need better and more efficient ways to provide useful information to support clinical decisions of health care providers and consumers. The lack of user-friendly information sources often hampers adoption of newer approaches, such as the incorporation of genetic testing practices in routine clinical decision-making.

To support the readiness of health professionals and change clinical practice patterns to reflect best practices, robust clinical decision support and information management tools will need to be integrated into electronic health records and other health information technology systems. New provider education in the use of genomic information is also likely to be needed.

Underlying improvement in the translation of advances into health care delivery and the adoption of best practices is the need for strong medical evidence. Personalized health care must be strongly aligned with the development and use of evidence-based care. At the same time, adoption of new tests, therapies, and techniques will be strongly affected by evidence of their clinical and economic value. The development of medical evidence focused on patient outcomes, and the ability to compare alternatives, will be an increasingly important element of health care. The development of systems for developing evidence from the health care delivery can add significantly to the evidence base and to growing knowledge of individual variations in response to treatments.

New Processes and Relationships in Product Development

New demands on medical product review will point toward improved integration of government and industry roles and responsibilities. The relationship of industry and academia in basic research and development will continue to undergo change driven by shared responsibilities in technology development and genomic applications reflected in funding methods and intellectual property management. In the short term, this will be manifested by shared support of research projects to validate technological approaches to assess molecular, genetic, and imaging parameters in medical product development. Agreements for sharing precompetitive data (especially meaning broadly applicable findings developed through cooperative processes, or otherwise made available for use without patent exclusivity) among public and private entities, particularly of genomic databases, will broaden discovery opportunities, enhance safety assessment, and diminish investment risks in targeted molecular therapies and diagnostics. Additionally, new dynamics may emerge in employer/employee relationships in supporting personalized health care programs through incentives and Web-based information tools.

As the health care system focuses on disease prevention and preemption through personalized approaches based on risk assessments, these advances will drive a need for new reimbursement strategies and other incentives. Personalized health care disease management approaches will be evidence-based. The advancements in health information technology, improvements in standardized phenotypic characterization of disease parameters, and increased understanding of unique biological factors responsible for individual differences in health and disease will lead to more informative clinical trial data. Over the next decade, the effects of these steps will result in better information about what works for which patient, which will not only strengthen measures of quality of care, but also improve efficiency in new product development and evaluation. An achievable objective for the future is a richer science and information base that will maximize opportunities for clinical development of new technologies.

Health Information Technology and Knowledge Management

Underpinning personalized health care is the confluence of two powerful tools: information technology and knowledge management. These forces will provide individualized health care know-how at an unprecedented level. The full potential of these forces cannot be realized unless electronic systems, clinical databases, and knowledge repositories employ interoperable standards and definitions.

While innovation in technology to collect information is a key step, data collection alone will not support personalized health care. As technological capabilities develop across the health care system, better information based on individual differences will aid in future medical product evaluations and postmarketing assessments of safety and efficacy.

There is an increasing need for, and value placed upon, integrated datasets and higher quality information about efficacy and safety outcomes. Using integrated databases, the ability to assimilate and relate experiences is enabling new predictive power for outcomes in disease management. Until now, this could only be modeled at a population level. Personalized health care should equate not only with an emphasis on more effective health outcomes but also with prevention and safer health interventions. These interoperable systems and networks will improve the practice of medical care and the health of the consumer and drive increased adoption of these important new technologies.

Pathways

Building Blocks of Personalized Health Care

The achievement of personalized health care (PHC) rests on a dual foundation: the growing base of biomedical knowledge (especially related to genomic knowledge) and the adoption of interoperable health information technology.

To this foundation must be added the development of clinically useful products. In order to achieve that goal, appropriate regulatory structures will be needed to support innovation and adoption of safe and effective drugs, diagnostics, and procedures.

Finally, integrating personalized health care into clinical practice will depend on the development of medical evidence demonstrating that these approaches work for clinicians and patients. It will also depend on education and support for health care professionals to translate new knowledge into clinically useful procedures.

Expansion of the Science Base

The Human Genome Project has been successfully completed, and work is continuing to explore the next steps. That work includes learning about the complex biological interactions that result in health and disease conditions, as well as the interactions between genetic factors and our environment and lifestyles. Some salient elements include:

• Continued genome sequencing and mapping: Building on the foundational work of the Human Genome Project, projects continue to refine our understanding of genetic structure and functions. An important example is The Cancer Genome Atlas, a comprehensive effort to understand the molecular basis of cancer. (NIH)
• Genome-wide association studies: These studies are a kind of medical detective work, matching the genetic profiles of large numbers of patients in clinical trials with their health conditions. These associations can help uncover patterns that point toward the roles of different genetic elements in health and disease. (NIH)
• Genes and environment: The complex relationship between genetics and environmental factors, including factors like nutrition and physical activity, help determine each person’s health. The Genes, Environment and Health Initiative (NIH)and the Human Genome Epidemiology Network (CDC) are early efforts in understanding this relationship.
• Population genetics: To help make genetic information useful, it is important to know the prevalence of genetic mutations and other factors in the population. This information can also be useful in targeting public health activities. Existing health surveys are used to compile this information. (CDC, HRSA, NIH)
• The “Omics”: Extensive work is needed to understand molecular biological elements beyond the focus on DNA and RNA. In particular, research is needed regarding proteomics, metabolomics, and epigenetics. (NIH)
• Computational biology: With 3 billion DNA base pairs and 20,000 active genes in each individual’s genetic makeup, development of information is dependent on sophisticated computing power. The computing tools needed for genetic and molecular biology research are in a constant state of invention. (NIH)
• Biomarker identification: Chemical and other markers that indicate specific biological activities can provide useful tools for clinical diagnosis and treatment as well as help to speed product development. A public/private Biomarkers Consortium has been formed to help identify useful biomarkers. (FDA, NIH)

Health Information Technology

Personalizing health care depends on interoperable health information technology. Health IT can make patient information available when and where it is needed. Health informatics can also help clinicians manage complex information and deliver “best practice” care.

• Technical standards and policies: The American Health Information Community (AHIC) is a Federal advisory committee chartered to make recommendations to the Secretary of HHS on how to accelerate the development and adoption of health information technology, including harmonization of health IT standards. Personalized health care starts with electronic health records that make complete and current patient information available when needed. (ONC)
• Genetic information in electronic health records: AHIC’s Personalized Health Care Workgroup is developing recommendations for the AHIC on standards for the future incorporation of personal genetic information in an electronic health record, including standards for family history. (ONC)
• Confidentiality, privacy, and security: AHIC’s Confidentiality, Privacy, and Security Workgroup is charged to make recommendations regarding the protection of personal health information in order to secure trust and support interoperable electronic health information exchange. (ONC, OCR, CMS)
• Clinical decision support: AHIC will recommend to the Secretary common elements for using electronic data technologies to support doctors, nurses, and hospitals in delivering high-quality care. (ONC)
• “Learning” health care: By aggregating large amounts of de-identified patient data from day-to-day medical practice, researchers can monitor safety and add rapidly to the evidence about what treatments work best and for whom. Combined with controlled clinical trials, this “learning” from practice through health IT can add significantly to effectiveness in health care. (AHRQ, CMS)
• Informatics and nomenclature: Deriving useful information from health care delivery will require standardization in measures and nomenclature, as well as sophisticated computer programming. (NIH, ONC)
• Quality improvement and health IT adoption: Demonstrations of health IT in a variety of health care settings will measure the impact on quality of care and the dynamics of health IT adoption in real-world situations. (AHRQ, HRSA)

Intervention Development and Review

Personalized health care should result in more effective drugs aimed at narrower populations, as well as a more prominent role for diagnostic tests and for co-development of diagnostic and drug products. Regulatory guidance is being developed to support effective development of drugs, diagnostics, and other tools aimed at smaller populations and more precise disease conditions.

• “Critical Path”: The Critical Path Initiative has identified 76 scientific and regulatory areas where progress is needed to improve and expand the science base for medical product development. Critical Path enables collaborations with other agencies, regulated industry, and interested public and private health care organizations in building the science base for improved regulation. (FDA)
• Submission of genomic data: New and voluntary approaches for submission of data, as well as other guidance for innovators in the field of personalized health care products, are being developed. (FDA, CDC, NIH)
• Evaluation of genetic tests:FDA is working to facilitate the development of the in vitro diagnostics that will be utilized in personalized health care, and CMS is carrying out its action plan for oversight of genetic testing. (FDA, CMS, AHRQ)
• Pharmacogenomics: Individuals respond differently to drugs. The use of personal genetic information in prescribing the optimal medications for each patient is a promising area of personalized health care. Pharmaceutical developers are encouraged to voluntarily submit genetic data with new drug applications to help learn more about this potential. Clinical research studies are also under way with specific drugs, notably the widely used anticoagulant warfarin, which involves sensitive dosing decisions. (FDA, NIH, AHRQ)
• Bioinformatics: Computer modeling may help predict drug effectiveness and safety, including effects on individuals based on genetic factors. Successful modeling could help accelerate drug development and review. (FDA, NIH)

Integration Into Clinical Practice

The adoption of scientific advances into clinical practice has typically been slow. New genetic elements will pose additional challenges for health care providers. An important element for achieving personalized health care will be support for clinicians in delivering high-quality care to every patient, including appropriate use of new genomic-based approaches.

• Evidence-based practice: With health IT data networks, health care can increasingly be based on broad evidence of effectiveness. For gene-based tests and therapies in particular, evidence from clinical practice can supplement the narrower data developed in formal trials and thus give clinicians stronger evidence for adopting these approaches. (AHRQ, CMS)
• Provider and consumer education: New medical tools will be useful only if they are trusted and used by health care professionals and patients. Communities and professional groups will need to be engaged in learning new practices. CaBIG, the Cancer Biomedical Informatics Grid, is a leading example, linking researchers, patients, and physicians throughout the cancer community to learn new practices and feed back into research. (NIH, HRSA, AHRQ)
• Knowledge management and decision support tools: An important element of health IT will be clinical decision support to help providers deliver “the right care to the right person at the right time.” Knowledge management tools will also play a part in delivery of more complex care based on genetic testing and therapy. (ONC, AHRQ, HRSA)
• Effective use of genetic tests: More than 1,000 genetic tests are now available, but clinicians and consumers need support in determining the appropriate and effective use of such tests. The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) project is a potential model for providing needed guidance. (CDC, CMS, FDA, AHRQ, HRSA)
• Family history: Collection of family history information can be a powerful early tool for improving care and building the base for personalized health care. (CDC, NHGRI, ONC, Office of the Surgeon General)
• Costs and reimbursement: The value delivered by new personalized health care products will need to be demonstrated and evidence of effectiveness shown. New approaches in rewarding high quality and value through reimbursement techniques are being tried. (CMS)

The Importance of Collaboration

In any scientific endeavor today, collaboration is important. For personalized health care, it is at the heart of the project. Collaboration among different stakeholders, and across public and private sector lines, is not merely key to achieving the goal, it is the essence of the goal itself. “Personalizing” health care means aligning resources across the health sector, from the researcher and the regulator to the clinic and the payer, so that their efforts converge and adjust for each patient. Patient-centric care depends on collaboration for the patient’s benefit.

Standards

The concept of using gene-based factors and health information technology together to personalize health care is at an early stage. As we build the foundation, it is especially important to agree on standards in order to create common interfaces, measurements, and vocabularies. Standards are essential both for collaboration in building a system, and for enabling future value-enhancing competition.

Data and technical standards are critical to the advancement of the national health IT agenda and achieving the intended health goals and outcomes. By harmonizing standards, different information systems, networks, and software applications will be able to “speak the same language” and work together technically to manage and use consistent, accurate,  and useful health information for providers and consumers. For this reason, harmonizing interoperability standards is a priority for the Secretary of HHS, and with the advice of the American Health Information Community, the Secretary will continue to recognize interoperability standards.

Standards of performance are also important in nourishing a market for health IT. When providers invest in health IT, they need to have measures to demonstrate the value of their purchase. With AHIC’s guidance, the Secretary recognized a number of performance standards for health IT systems last year that were then incorporated into the process by which health IT products and systems are certified by the Certification Commission for Health Information Technology.

Standards are equally important in research. An important challenge in seeking out the associations between genetic factors and health will be standard nomenclatures, especially for health and disease conditions. An early start has been made with SNOMED, a broad collaborative effort carried out with HHS support to establish a standardized vocabulary of clinical and pathology terms. NIH, FDA and other agencies continue to bring together stakeholders for extensive further work in these areas.

Agreements on nomenclature and standards for outcome measurement will also be important as we seek to use data from clinical practice to add to our base of evidence about the effectiveness of treatments and to improve quality of care.

These are only a few examples of collaborative efforts that are under way to build the base of standards that will help accumulate information, transform information into knowledge, improve care, and create new value.

Translation and Teamwork

Our health care system has historically been slow in translating research advances or even adopting simple quality-improving techniques into daily clinical practice. To successfully adopt “best practices,” including quality-driven variations in care between individuals, we will need collaboration at two levels. First, lines of communication among researchers and clinicians need to be open and active. Perhaps more important, strong collaborative “teamwork” approaches in health care settings themselves can make the greatest difference in patient safety and quality of care. Changes in the culture of clinical settings to enable measurement of outcomes and make care more patient-centric can take time and effort, but they are also an important part of personalizing health care.

Building a “Learning” System in Health Care

Doctors and researchers have always learned from their care delivery, but only a few health care institutions have systematically gathered data from patient encounters over time to help determine which treatments are most effective and for whom. Interoperable health IT can make it possible to reap this kind of learning from the broad terrain of day-to-day clinical practice. This approach would depend on cooperation among entities that possess patient data, including their agreement on effective protections for privacy of personal data. In the end, it would actually represent a “collaboration” by patients in a systemwide process of health data development. Large amounts of de-identified patient data from normal health care delivery would become a platform for discovery – a resource for research and a tool for improved safety and quality of care.

The Patient as Participant

Patients are typically seen as the recipients of care. An important ideal of personalized health care is to better enable patients themselves to be participants and guides in their own health care. This is not simply a matter of encouraging personal responsibility for making healthy choices, or becoming more actively involved in choices based on personal preferences or value. More fundamentally, as genomic and other factors give each of us an increasingly distinct and unique health profile, it is hoped that a sense of ownership and personal expertise will grow. Patients will increasingly possess both the information and the sense of authority that will help them become partners in their own care, helped by professionals who are increasingly seen as advisors and “coaches.”

Secretary’s Initiative in Personalized Health Care:

Using Information Correctly

Genomic information and health information technology both convey new power. As we seek to use that power to improve care and health, we need to exercise the wisdom and discretion to avoid misusing it. In the end, the usefulness of these advances will depend on public trust. That trust must be fostered and protected.

A starting point is to avoid misusing genetic information to deny employment or health insurance to individuals. While genetic discrimination has not emerged as a significant problem at this time, surveys show that Americans are concerned about the possibilities for abuse in the future, and they want protections put in place. The Administration supports Federal law to prohibit such misuses.

A leading objective throughout HHS agencies is to build a strong foundation for personalized health care. HHS Secretary Michael Leavitt has launched a PHC initiative, with several cross-cutting elements:

• The President’s budget for 2008 includes $15 million in startup funding to create a new electronic network that would draw together data from major health data repositories. This distributed network would be a prototype for a “learning health care system.” De-identified data from day-to-day health care practice would enable researchers to add to our base of medical evidence on effectiveness and safety of alternative treatments.
• The American Health Information Community (AHIC) is charged with developing recommendations for consensus standards and other actions that would support President Bush’s goal of electronic health records for most Americans by 2014. This year, the AHIC has also formed a new workgroup to develop recommendations for the AHIC on standards for including genetic test information and family history in electronic health records.
• Efforts are under way in HHS to consider issues relating to the use of genetic test information to improve quality of health care within the framework of providing protections for the patient’s privacy.
• As a result of the advances in technology development and increased medical knowledge about the roles of genes in health and disease, greater use of genetic tests in health care is anticipated. To prepare for this, HHS is also examining opportunities to help facilitate medical product development and encourage innovation, while taking into account potential processes to assess safe and effective health care applications. The goal is to ensure a coherent framework across HHS agencies and to support value and innovation in genetic testing applications in health care.
• Many new research projects are establishing databases of genomic information from clinical studies. HHS is working to maximize the benefits that derive from federally sponsored research resources by considering common approaches for the availability of their data to the research community.

These steps represent a systems strategy. They are aimed at building a foundation that will use new methods of genetic analysis to better manage a patient’s disease or predisposition to a disease, while at the same time facilitating the discovery and testing of new products. They emphasize the development of standards to derive the greatest possible benefit as health information technology brings about exchange of health information, including better bridges between research and health care delivery.

The end goal is to transform the effectiveness of treatments provided for each patient, while building understanding and trust among providers and patients in a new kind of health care.

I.    Expansion of the Science Base

Human Genomics Research

National Human Genome Research Institute, National Institutes of Health
http://www.genome.gov/

Description

The National Human Genome Research Institute’s (NHGRI’s) predecessor, the National Center for Human Genome Research (NCHGR), was established in 1989 for the purpose of leading NIH’s component of the Human Genome Project, the international, public effort to sequence all 3 billion DNA base pairs of the human genetic blueprint. The Human Genome Project was completed in April 2003, under budget and ahead of schedule. In January, the National Human Genome Research Institute celebrated its 10th anniversary as an Institute of the National Institutes of Health (NIH), marking a decade that saw genomics emerge as a powerful research tool and looking ahead to an era in which genomics will transform medical care

Status and Next Steps

• During its first 7 years, NCHGR devoted much of its energy to developing the technologies and techniques needed to map and ultimately sequence the human genome. Because the public Human Genome Project placed all the resulting data in freely available, public databases, the sequence of the human genome became available for anyone to use anywhere in the world to conduct medical research and advance the cause of human health.
• NHGRI’s Genome Sequencing Program is responsible for the administration and support of research directed to the highly efficient construction of physical maps, large-scale sequencing, and genomic resource production for entire genomes.
• The Human Genome Project quickly showed that humans are more than 99 percent identical at the genetic level; that is, the order of genetic letters As, Ts, Cs, and Gs is almost precisely the same between any two individuals. Researchers also realized that the 0.1 percent genetic difference between people – where a genetic single letter is different – may hold the key to why some are more susceptible to a disease, such as cancer or a mental illness, than someone else. Such inherited genetic differences, or variations, may well explain why diseases, such as diabetes, run in families. Researchers call single-letter differences SNPs and estimate that 10 million would need to be evaluated to predict disease risk, a prohibitively high number of differences if 10 millionSNPs had to be tested in every individual. Later studies showed that only some 500,000 SNPs needed to be tested across the genome to assess a person’s genetic variation. These technical advances led researchers to organize the International HapMap Project, a coordinated effort to map genetic variation in populations of people from Africa, Asia, and Europe. The HapMap produced a catalog of common variations across the entire human genome that has been used to quickly and cheaply assess all the common variants in an individual. This capability laid the foundation for genome-wide association studies to identify the genetic underpinnings of common illnesses (described later). See http://www.hapmap.org/.
• But even acquiring the sequence of the human genome and starting to understand genetic variation were only the first steps in understanding how the human genome works; researchers now need to understand what it does and how it works. Estimates suggested that only a few percent of the human genome actually encoded proteins, the workhorses of the living cells that make up the body. To begin to understand the genome’s dynamism, The NHGRI launched a public research consortium named ENCODE (http://www.genome.gov/10005107), the Encyclopedia Of DNA Elements, in September 2003, to carry out a project to identify all functional elements in the human genome sequence. The project is being conducted in three phases: a pilot project phase, a technology development phase, and a planned production phase. Major findings from the pilot project were published in two scientific journals, Nature and Genome Research, in mid-June; details can be found at http://genome.gov/25521622.
• Since 1990, NHGRI has been investing funds to develop and improve DNA sequencing technologies. DNA sequencing costs have fallen dramatically, more than fiftyfold over the past decade. The goal of this technology development program is to reduce the cost of sequencing a human-sized genome to $1,000. Several new NHGRI-supported technologies aimed at an intermediate goal of $100,000 per genome are now reaching the market place and others show strong potential to become commercially available within the next 5 years. Beyond the intermediate goal, another set of investigators are being supported to develop revolutionary technologies to sequence a human genome extremely inexpensively (conveniently referred to as the “$1,000 genome”). Having the ability to sequence an individual genome so inexpensively would not only dramatically stimulate biomedical research, but would also support personalized health care goals. Researchers envision a day when anyone can have his or her genome sequenced, one time, as part of routine medical care and have access to it in some digital form, such as on a CD-ROM or a flash memory card. Physicians would then use a computer to screen that individual genome for genetically increased risks to common disease, such as cancer or diabetes, as well as use that information to predict which medical interventions will best work to prevent the disease from occurring, treat it effectively if it does, and select therapies that cause the fewest unwanted adverse reactions or side effects. In many ways, these technical genome-sequencing innovations will be needed to make personalized health care economically feasible for all.

Genome-Wide Association Studies

National Institutes of Health
http://grants.nih.gov/grants/gwas/index.htm

Description

The NIH is advancing a series of research initiatives known as genome-wide association studies (GWAS) that will identify common genetic factors that influence health and disease. The information derived from such studies will be essential for developing new approaches to reduce disease burden, promote health, and understand individual differences in health. GWAS are currently defined as any study of genetic variation across the entire human genome that is designed to identify genetic associations with observable traits (such as blood pressure or weight), or the presence or absence of a disease or condition.

Researchers have known since the first analysis of the draft human genome sequence in 2000 that people are 99.9 percent identical at the genetic level. Within that 0.1 percent, where people differ one from the other, however, lies the reason why one person has a higher risk of a common disease, such as diabetes, than someone else. Studies show that common variations exist across the genome; GWAS will systematically associate the common variations with specific common diseases. Whereas past genetic research found strong effects from single gene defects that caused rare inherited diseases, such as cystic fibrosis or muscular dystrophy, GWAS will identify many genetic variations that, when summed, produce an increased relative risk for common diseases, such as cancer or Alzheimer’s disease. The genetic variations identified by GWAS may also identify combinations of genetic variation that confer good health (i.e., lower relative risks) and even show doctors which medications will best work to treat an individual with a given genetic makeup.

In many ways, the results from GWAS will provide the information physicians need to interpret an individual’s genome once it has been sequenced by the technologies described in the sequencing technology section above.

Those results will be arriving rapidly over the next few years. The diseases for which results already are available include age-related eye diseases, Parkinson’s disease, attention deficit hyperactivity disorder (ADHD), schizophrenia, and psoriasis.

In addition, recent reports have appeared in the scientific literature on a wide range of GWAS findings, including:

1. Type 2 diabetes:Three scientific reports in April, including one involving NHGRI, linked 10 genes to Type 2 diabetes.
2. Coronary heart disease:Two studies linked genetic markers on chromosome 9 with coronary heart disease and heart attacks. Moreover, one of the genetic variants in the heart studies appeared in the same region as a genetic variant in the Type 2 diabetes studies reported earlier in the month.
3. Adult obesity:One study linked one form of a single gene to body mass index and discovered it predisposes to childhood and adult obesity.
4. Adult height: Another study linked a gene variation to height in different populations around the world.
5. AIDS: The first GWA study of an infectious disease provided new insights into why some patients suffer less harm during an acute infection with human immunodeficiency virus (HIV) than others who are less able to suppress the virus that causes AIDS. The insights may well lead to more effective treatments.
6. Age-related macular degeneration: One of the earliest modern GWAS discoveries found a relationship of a gene involved in an inflammatory response with a type of blindness that occurs in elderly individuals. The discovery immediately suggested a therapeutic intervention that should slow the progression of the blindness.
7. Results from numerous other disease-related GWA studies have begun producing results on various disorders, such as glaucoma, Type 1 diabetes, breast cancer, Crohn’s disease, prostate cancer, rheumatoid arthritis, multiple sclerosis, and asthma. Results from illnesses being studied with the GWAS strategy have risen dramatically, and equally dramatic results can be expected in the next few years.

Other advances are expected from large-scale projects launched by several of the NIH’s Institutes and Centers, including the Framingham Genetic Research Study, launched by the National Heart, Lung, and Blood Institute in February 2007, in which 9,000 participants of the long-running Framingham Heart Study will undergo genomic analysis. The National Cancer Institute (NCI) also launched a GWAS aimed at identifying the genes involved in cancers of the breast and prostate. The 3-year, $14 million initiative was launched in 2006.

Through a series of GWA studies, using samples from existing case-control studies of patients with common diseases, these projects will contribute to the identification of genetic pathways that make us more susceptible to these diseases and thus facilitate discovery of new molecular targets for prevention, diagnosis, and treatment.

Status and Next Steps

• After a period of public consultation, the NIH in August released a new policy for Genome-Wide Association Studies supported and conducted by NIH. The policy addresses (1) data-sharing procedures, (2) data-access principles, (3) intellectual property, and (4) issues regarding the protection of research participants through all phases of GWAS. Many of the principles contained in the policy reflect and extend existing NIH polices and other recent NIH discussions. The GWAS policy will be applicable to competing grant applications, proposals for contracts, and intramural research projects beginning on January 25, 2008. The policy can be accessed at http://www.genome.gov/19518660.

The National Library of Medicine (NLM) recently initiated a new database known as dbGaP to distribute data from GWAS. dbGaP, the database of Genotype and Phenotype, will for the first time provide a central location for interested parties to see all study documentation and to view summaries of the measured variables in an organized and searchable Web format. Already, the NIH database of Genotype and Phenotype (dbGaP) makes data from several GWA studies freely available to researchers around the world. See http://www.ncbi.nlm.nih.gov/sites/entrez?db=gap.

Genes, Environment and Health Initiative

National Institutes of Health
http://www.gei.nih.gov/

Description                                                                       

On February 8, 2006, Health and Human Services Secretary Michael O. Leavitt announced a plan to implement a Genes, Environment and Health Initiative (GEI). The GEI will have two main components:

• The Genetics Program is a pipeline for analyzing genetic variation in groups of patients with specific illnesses.
• The Exposure Biology Program is an environmental technology development program to produce and validate new methods for monitoring environmental exposures that interact with a genetic variation to result in human diseases. The program importantly also includes developing new methods for identifying individual biological response to environmental exposures.

This initiative includes funding for genome-wide association studies, methods of analyzing gene-environment interactions, environmental “sensors” that detect exposure, and measurement of diet and physical activity.

Status and Next Steps

In September, NIH announced the first round of first-year funding under GEI, committing $40 million in new funding provided for the initiative, in addition to another $9 million provided by two NIH Institutes to support GEI-related studies. In the first year, NIH will fund eight genome-wide association studies, two genotyping centers, a coordinating center, and more than 30 environmental technology projects. Details can be found at http://www.nih.gov/news/pr/sep2007/nhgri-04.htm.

GWA studies will focus on the genetics of addiction, coronary heart disease, lung cancer, Type 2 diabetes, maternal metabolism and birth weight, prematurity, and oral clefts. Environmental studies will include 34 projects on the development of sensors for personal exposure assessment, measurement of psychological stress and addictive substances, diet and physical activity, and biological response indicators of environmental stress.

Human Genome Epidemiology Network

Centers for Disease Control and Prevention
http://www.cdc.gov/genomics/hugenet

Description

The Human Genome Epidemiology Network (HuGENet^TM) is a voluntary, international collaboration committed to translating genetic research findings into opportunities for preventive medicine and public health. HuGENet^TM promotes the integration and synthesis of population-based epidemiologic data describing the interactions of genetic variants with modifiable risk factors and their joint contributions to disease risk.Established by the Centers for Disease Control and Prevention (CDC) in 1998, HuGENet^TM now includes coordinating centers in the United Kingdom, Canada, and Greece. The network’s free online resources include a weekly summary of new scientific articles on human genome epide­miology, a searchable database, case studies for training, and information on workshops and publications.

Status and Next Steps

• HuGENet™ collaborators recently published “A road map for efficient and reliable human genome epidemiology” in Nature Genetics [2006;38(1):3-5], describing a Network of Investigator Networks for sharing best practices, tools, and methods for analysis of associations between genetic variation and common diseases.
• In 2006, HuGENet™ published an online handbook for systematic reviews and meta-analyses (http://www.cdc.gov/genomics/hugenet/reviews/guidelines.htm), which are peer-reviewed and published in partnership with 10 scientific journals. Currently, 58 HuGE Reviews are available online.
• HuGE Pub Lit, the curated, searchable database based on weekly sweeps of PubMed, currently contains more than 26,000 citations indexed by gene, health outcome, and personal or environmental factors.
• Criteria for evaluating the evidence for gene-disease association were drafted at an international meeting in Venice in November 2006 and are awaiting publication.
• CDC will continue to collaborate with national and international partners to provide leadership, guidance, and support for the collection and synthesis of population-based data on genetic variation in health and disease.

National Health and Nutrition Examination Survey

Centers for Disease Control and Prevention
http://www.cdc.gov/nchs/nhanes.htm

Description

The National Health Survey Act of 1956 provided the authority for a continuing survey to provide current statistical data on the amount, distribution, and effects of illness and disability in the United States. National Health and Nutrition Examination Survey (NHANES)was created to fulfill the purpose of this act.

NHANES provides a basis for personalized health care by providing databases, infrastructure, and research capabilities to understand individual differences in risk factors for disease and practical information to guide patient care decision-making.

Status and Next Steps

NHANES data are collected from a representative sample of communities throughout the United States.

The current NHANES is the eighth in a series of national examination studies conducted in the United States since 1960. The goals of NHANES are as follows:

• To estimate the number and percentage of persons in the U.S. population and designated subgroups with selected diseases and risk factors.
• To monitor trends in the prevalence, awareness, treatment, and control of selected diseases.
• To monitor trends in risk behaviors and environmental exposures.
• To analyze risk factors for selected diseases.
• To study the relationship between diet, nutrition, and health.
• To explore emerging public health issues and new technologies.
• To establish a national probability sample of specimens for genetic analyses:

–      CDC has defined a “top 100” list of genetic variants of public health significance, and is currently leading a collaborative effort with the NCI to determine how common these variants are in the U.S. population, using over 7,000 biologic specimens collected in NHANES III. This work will be completed later this year and will provide a foundation for further studies to understand how genetic variation contributes to human disease.

CDC and the CDC Foundation are launching a new initiative, Beyond Gene Discovery (BGD), to measure hundreds of thousands of genetic variants in about 15,000 NHANES biologic specimens, and to coordinate the comprehensive analysis of associations among variations in genotype, phenotype, and gene-environment interaction.

Biomarkers Consortium

http://www.fnih.org/Biomarkers%20Consortium/Biomarkers_home.shtml

Description

The development of biomarkers is being carried out by work in several NIH Institutes, as well as through the Biomarkers Consortium. The Consortium is a public-private biomedical research partnership of the Foundation for the NIH that involves a variety of public and private stakeholders including the NIH; U.S. Food and Drug Administration (FDA); Centers for Medicare & Medicaid Services (CMS); pharmaceutical, biotechnology, diagnostics, and medical device industries; nonprofit organizations and associations; and advocacy groups. The goals include accelerating disease-specific research and ensuring that safe, innovative, and effective medicines and diagnostics are expeditiously developed to address health care needs, improve medical care, and promote and improve public health. The Biomarkers Consortium facilitates personalized health care by developing tools and information that facilitate understanding about individual differences in disease conditions.

Status and Next Steps

The Consortium’s first project will be to qualify a method to use imaging methods to detect tumor response to new chemotherapy agents. A method known as fluorodeoxyglucose positron emission tomography (FDG-PET) is considered a potential biomarker for response of cancer to treatment. FDG-PET measures glucose uptake by tumors using a radioactive form of fluorine incorporated in a sugar molecule. Tissues that accumulate radioactive glucose are visible through positron emission tomography (PET), an imaging method to detect gamma rays.

Researchers believe that FDG-PET could become a tool for gauging a cancer patient’s response to chemotherapy or radiation by accurately measuring tumor metabolism. Physicians will thereby rapidly know whether the tumor is responding to therapy or when to switch therapies to provide the best chance for curing or managing the cancer. FDG-PET can also assist clinical research and drug development by helping to assess a study subject’s response to investigational drugs.

Initially, the Consortium will focus its FDG-PET efforts on non-Hodgkin’s lymphoma and lung cancer. Non-Hodgkin’s lymphoma strikes over 55,000 Americans each year and kills close to 20,000 according to the NCI. Lung cancer makes up 13 percent of all cancer cases in the United States. More than 170,000 individuals are diagnosed with lung cancer each year, and close to that number die from the disease. Although it was once thought to almost exclusively be caused by smoking, approximately 13 percent of lung cancer patients have never smoked.

NIH Biomarkers Projects

National Institute of Arthritis and Musculoskeletal and Skin Diseases

The Osteoarthritis Initiative

The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) places a high priority on studies to identify risk factors and biomarkers of disease in an effort to facilitate the early identification of signs and symptoms and to develop interventions that are more effective. To this end, the Institute will continue its commitment to a novel public-private partnership to improve prevention of osteoarthritis (OA), or degenerative joint disease. The Osteoarthritis Initiative (OAI) is a long-term effort, developed with support from numerous NIH components and private sector sponsors, and with the participation of the FDA, to create a publicly available research resource to identify and evaluate biomarkers of OA for use in clinical research. The study has 4,800 participants who are at high risk for knee OA, and, as of early FY 2007, clinical data from approximately 2,000 of them were available for research projects. Over the next 5 years, the OAI will provide an unparalleled, state-of-the-art longitudinal database of images and clinical outcome information to researchers worldwide to facilitate the discovery of biomarkers for development and progression of OA. In this effort, a biomarker would be a physical sign or biological substance that indicates changes in bone or cartilage. Today, 35 million people, 13 percent of the U.S. population, are ages 65 and older, and more than half of them have radiological evidence of OA in at least one joint. By 2030, an estimated 20 percent of Americans, about 70 million people, will have passed their 65th birthday and will be at increased risk for OA.

National Institute of Diabetes and Digestive and Kidney Diseases

Biomarkers Predicting Disease Onset and Progression

The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) has a long track record of successfully promoting the development of biomarkers for a number of diseases within its research mission that have transformed patient care. However, additional biomarkers are urgently needed to aid in predicting disease as well as monitoring disease progression and response to therapy. The NIDDK is spearheading several efforts to pursue potential biomarkers, such as (1) Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) II, which is following 200 patients (who were part of the original CRISP study) who have autosomal-dominant PKD. The goal is to verify findings of the initial CRISP study and determine whether changes in anatomic characteristics of their kidneys as measured by magnetic resonance imaging are useful in providing surrogate measures for disease progression, (2) Chronic Renal Insufficiency Cohort Study (CRIC) and Chronic Kidney Disease in Children (CKiD), which will be looking for nontraditional biomarkers for cardiovascular disease risk, chronic kidney disease progression, and cognitive changes (in children), (3) Biomarker Development for Diabetic Complications, which encourages research on biomarkers that can help identify patients with diabetes who are at particular risk for various comorbidities, and (4) Development of Disease Biomarkers, which will provide resources to demonstrate that candidate biomarkers meaningfully reflect actual disease processes. The Initiative’s scope includes well-defined human diseases of liver, kidney, genitourinary tract, and digestive and hematologic systems; endocrine and metabolic disorders; diabetes and its complications; and obesity. New biomarkers not only may improve ability to predict disease, but also can be used to measure effects of new candidate therapies and aid in the design and conduct of clinical trials.

National Institute of Neurological Disorders and Stroke

Biomarkers for Neurodegeneration

Biomarkers can enhance the treatment of individual patients and expedite clinical trials of new therapies by predicting who is likely to develop a disease and who might benefit from or be harmed by a particular treatment, or by giving early indications of how a disease is progressing or whether a therapy is working. The National Institute of Neurological Disorders and Stroke (NINDS) strategic and disease specific plans have highlighted the importance of biomarkers, and the Institute is supporting increasing numbers of biomarker studies in disorders that include Alzheimer’s disease, brain tumors, epilepsy, Huntington’s disease, multiple sclerosis, Parkinson’s disease, stroke, traumatic brain injury, and cognitive impairment in HIV infection, as well as biomarkers to indicate exposure to chemical nerve agents. The NIH Neuroscience Blueprint, in which NINDS participates, is soliciting additional studies of biomarkers for neurodegeneration in FY 2007. As one example of biomarkers studies, NINDS intramural researchers are conducting the BioMS study in conjunction with a multisite extramural Phase III clinical trial of combination therapies for multiple sclerosis, the CombiRx trial. BioMS is applying genetic mapping, gene expression studies, histocompatibility typing, and proteomics technology to data from up to 1,000 patients in the clinical trial and will relate the findings back to the clinical outcome data and the brain imaging from the CombiRx trial to identify biomarkers.

National Institute on Alcohol Abuse and Alcoholism

Alcoholism-Related Biomarkers

Alcoholism is often a hidden disease. Unlike other abused drugs, the majority of alcohol molecules in the body are rapidly metabolized to carbon dioxide and water. Therefore in the absence of accurate self-report it is difficult to detect when an individual is consuming alcohol in a harmful pattern. A small fraction of alcohol, however, is metabolized to form other compounds that have a longer half-life. The National Institute on Alcohol Abuse and Alcoholism (NIAAA) is exploring the utility of such biomarkers so that individuals who are drinking in a harmful manner can be identified and receive the appropriate intervention before their drinking leads to adverse health outcomes. Biomarkers can also be used to identify individuals who have relapsed to harmful drinking. Specifically, there is encouraging research on nonoxidative markers of alcohol including ethyl glucuronide (EtG), ethyl sulfate, and phosphatidyl ethanol that NIAAA will continue to pursue in addition to using state-of-the-art technologies to develop additional biomarkers. Biomarkers will also be a valuable tool in assessing in utero exposure to alcohol in newborn infants. Specifically, fatty acid ethyl esters are being actively tested as markers for exposure to alcohol in the last few months of gestation. An indication of alcohol exposure during pregnancy would be predictive of children who should be assessed for neurological and physical deficits.

Cancer Research Programs Supporting Personalized Health Care

National Cancer Institute, National Institutes of Health

Description

The Cancer Genome Atlas (TCGA) (http://cancergenome.nih.gov/index.asp) is a comprehensive and coordinated effort to accelerate the understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. The pilot project will assess the feasibility of a full-scale effort to systematically explore the entire spectrum of genomic changes involved in cancer of the brain, lung, and ovary. The Cancer Genome Atlas Pilot Project establishes an integrated network of core resources and specialized genome characterization and genome sequencing centers that will work together to form a system that selects genes and regions in order to drive high-throughput cancer genome sequencing. The project contributes to personalized health care by establishing the mechanisms and individual differences in the genetic causes of these types of cancer. TCGA is jointly supported by NCI and the National Human Genome Research Institute.

The NCI is launching the NCI Community Cancer Centers Program (NCCCP) (http://www.cancer.gov/researchandfunding/ncccp-pilot-program) as a pilot program to bring the latest scientific advances and the highest level of innovative and integrated, multispecialty care to a much larger population of cancer patients. The overarching goal is to bring science, early-phase clinical research, and optimal evidence-based therapies to patients in their home communities. Pilot sites will also share best practices and refine the overall concept as a prelude to launching a new national network of research-driven cancer care at the community level.

Status and Next Steps

• Researchers have found that a unique pattern of activity for genes in cells located in the tissue surrounding a liver tumor can accurately predict whether the cancer will spread to other parts of the liver or to other parts of the body. They have also identified new biomarkers that may be useful in diagnosing early disease.
• A large-scale analysis of data on breast cancer risk has concluded that a common variation in the gene caspase-8 (CASP8) is associated with a somewhat lower risk of the disease. Variants are small changes that occur in a gene sequence.
• Scientists have discovered how human T cell leukemia virus type 1 (HTLV-1), which infects about 20 million people worldwide, evades being held in check by one of the body’s natural defense mechanisms. (An active infection with HTLV-1 leads to T cell leukemia in up to 5 percent of all cases worldwide.)

These programs are part of an infrastructure that will develop resources to support discovery of new genetic markers of cancer that can be used to identify individuals at risk for them. Completion of these pilot projects will establish a research capability to support individualized approaches to health care.

Office of Biorepositories and Biospecimen Research
National Cancer Institute, National Institutes of Health
http://biospecimens.cancer.gov/

Description

The Office of Biorepositories and Biospecimen Research (OBBR) was established at the NCI in 2005 to facilitate and accelerate the development of personalized cancer medicine by ensuring the availability of high-quality, clinically annotated human specimens for postgenomic cancer research. Toward this end, the OBBR is committed to the development of evidence-based standards of biospecimen acquisition, processing, and storage that optimally preserve the quality and integrity of biospecimens for molecular analysis and ensure reproducibility of molecular tests performed on those specimens. Such standards will become the standards of pathology/laboratory medicine practice in an era of personalized medicine.

Status and Next Steps

• In order to create a baseline to assess, improve, and ensure the quality of human biospecimen resources, the OBBR has developed a comprehensive set of state-of-the-science guidelines for biobanking, NCI Best Practices for Biospecimen Resources. The Best Practices, accepted in final form by the National Cancer Advisory Board in June 2007, will serve as the national standard, while OBBR engages in a stepwise process of increasing the scientific base for further data-driven standards and operating procedures that are molecular analysis platform-appropriate.
• The Best Practices guidelines also have served as the basis for a comprehensive set of Biospecimen Resource Evaluation Criteria (the BRET) developed by the OBBR that can be used to objectively assess the quality of any existing or planned biospecimen resources based on the current state of the science.
• The OBBR has developed an intramural Biospecimen Research Network (BRN) and an extramural program known as Biospecimen Research for Molecular Medicine to systematically investigate the effects of acquisition, processing, and storage variables on biomolecular profiles in specimens. Such data will form the scientific basis of data-driven procedures for patient specimen handling in molecular medicine.
• The OBBR has established collaborations on data-driven protocol development with authoritative professional organizations like the College of American Pathologists that can both monitor implementation through its Laboratory Accreditation Program and educate its constituents about the importance and practicalities of compliance with these new standards.
• The Best Practices guidelines advocate cost recovery but not profit-generating business models for biospecimen resources. In order to help biospecimen resources define actual costs in a modular fashion that can be customized to any given resource model, OBBR has undertaken a Biobanking Economics initiative and plans to publish guidance for cost recovery on the basis of the findings.
• The OBBR is collaborating in transformative, large-scale NCI strategic initiatives that will enable personalized medicine in which the principles of high-quality shared biospecimen resources are critical for achieving the research goals. Such projects include those that emphasize high-quality biospecimens as shared resources for cancer researchers, such as the NCI Community Cancer Centers Program; caBIG™ projects; The Cancer Genome Atlas; Clinical Proteomic Technologies Assessment for Cancer; and the Nanotechnology Alliance.
• The OBBR also has established collaborations with other major initiatives outside the NCI, nationally and internationally, to achieve global harmonization of approaches to biospecimen issues throughout the translational research enterprise. Projects include the Interagency (NCI, FDA, CMS) Oncology Task Force and the Biomarkers Collaborative (NCI, FDA, AACR).
• The OBBR is committed to the development of educational tools and resources for all potential stakeholders (public, professional, private) that address the spectrum of issues related to human biospecimens in order to align interested constituencies on the importance of high-quality shared biospecimen resources. Projects include OBBR Web site enhancements for biospecimen research and resource data sharing; development of educational programs for professionals; outreach to patient advocacy groups; and development of hands-on training programs for biobankers.

National Program of Cancer Registries
Centers for Disease Control and Prevention
http://www.cdc.gov/cancer/npcr/

Description

State-based cancer registries are data systems that collect, manage, and analyze data about cancer cases and cancer deaths. In each State, medical facilities (including hospitals, physicians’ offices, therapeutic radiation facilities, freestanding surgical centers, and pathology laboratories) report these data to a central cancer registry. Established by Congress through the Cancer Registries Amendment Act in 1992, and administered by the CDC, the National Program of Cancer Registries (NPCR) collects data on the occurrence of cancer; type, extent, and location of the cancer; and type of initial treatment.

Status and Next Steps

• Before NPCR was established, 10 States had no registry, and most States with registries lacked the resources and legislative support they needed to gather complete data. Today, NPCR supports central cancer registries in 45 States, the District of Columbia, Puerto Rico, the Republic of Palau, and the Virgin Islands. These data represent 96 percent of the U.S. population. Together, NPCR and the NCI’s Surveillance, Epidemiology, and End Results (SEER) Program collect data for the entire U.S. population.
• Since 2002, CDC and NCI have combined their data sources to publish annual Federal cancer statistics in the United States Cancer Statistics (USCS): Incidence and Mortality report, produced in collaboration with the North American Association of Central Cancer Registries. This year’s report includes cancer incidence data from registries covering 96 percent of the U.S. population, and mortality data from all States and the District of Columbia.
• CDC has collaborated with NPCR-funded programs to define, test, and release NPCR data in WONDER, an online reporting system hosted at CDC. This new system, launched in early 2006, allows more access to NPCR data than previously was available. Finding critical data that can help guide and evaluate interventions focused on cancer prevention and control now is easier than ever.
• NPCR has developed software programs to make the process of submitting data easier for hospitals. By standardizing the way data are checked for validity, EDITS software improves data quality. Hospitals also can use any of the Registry Plus suite of programs for routine or special data collection. CDC provides and distributes these software programs, which are compliant with national standards, free of charge to the public health community.

Heart, Lung, and Blood Research Programs Supporting PHC

National Heart, Lung, and Blood Institute, National Institutes of Health
http://www.nhlbi.nih.gov/

Description

The National Heart, Lung, and Blood Institute (NHLBI), in collaboration with the Boston University School of Medicine, have launched a comprehensive new effort to enable identification of genes underlying cardiovascular and other chronic diseases. The new effort, the Framingham SNP Health Association Resource (SHARe), builds upon the long-running Framingham Heart Study (FHS) and will involve up to 500,000 genetic analyses of the DNA of 9,000 study participants across three generations.

Previous NIH-funded research charted the pattern of genetic variation in the human genome and demonstrated that common but minute variations, called single nucleotide polymorphisms (SNPs), in human DNA can be used to identify genetic contributions to common diseases. The Framingham SHARe will provide an incomparable resource for investigators that will enable them to combine the wealth of data collected over the years in the FHS on disease and disease risk factors with the new genetic data to identify genetic variants that predispose individuals to cardiovascular and other major chronic diseases.

Status and Next Steps

• This year, the Framingham Heart Study will be reporting results on a Genome-Wide Association Study.DNA from each of approximately 8,000 participants across all three generations will be studied for about 500,000 unique genetic changes. Using computer programs, researchers will relate this large catalogue of genetic results to many of the clinical and laboratory measurements that have been made in study participants during their examinations. Researchers hope to be able to identify genetic variations that are most strongly related to study participant characteristics such as levels of cholesterol, systolic blood pressure, obesity, and diabetes, and to disease occurrences such as heart attack, stroke, and osteoporosis.
• Research recently evaluated multiple biomarkers for the prediction of first major cardiovascular events and death. The newer biomarkers such as natriuretic peptides, C-reactive protein, fibrinogen, urinary albumin, and homocysteine were compared with established risk factors such as high blood pressure, diabetes, and high cholesterol. Measuring several biomarkers simultaneously, referred to as the “multimarker” approach, has enabled the scientists to stratify risk. They found that persons with high multimarker scores had a risk of death four times as great and a risk of major cardiovascular events almost two times as great as persons with low multimarker scores.

Eye Research Programs Supporting PHC

National Eye Institute, National Institutes of Health
http://www.nei.nih.gov/

Description

Over the past 15 years, nearly 500 genes that contribute to inherited eye diseases have been identified. Disease-causing mutations are associated with many ocular diseases, including glaucoma, cataracts, strabismus, corneal dystrophies and a number of forms of retinal degenerations. This remarkable new genetic information highlights the significant inroads that are being made in understanding the medical basis of human ophthalmic diseases. As a result, gene-based therapies are actively being pursued to ameliorate ophthalmic genetic diseases that were once considered untreatable. This project will support better understanding of new ways to personalize prevention and treatment of vision loss. The National Ophthalmic Disease Genotyping Network (eyeGENE^TM) is at http://www.nei.nih.gov/resources/eyegene.asp.

Status and Next Steps

• The first organizational meeting of the eyeGENE^TM was convened January 10-11, 2006, to discuss the milestones necessary to launch the eyeGENE^TM initiative. Participants included members of the ophthalmic, optometric, and genetic communities. Experts in bioethics and Federal regulatory requirements were also present as were members of the international vision research community.
• A team of researchers has determined that variations in certain genes involved in fighting infection can successfully predict the risk of developing age-related macular degeneration (AMD), the leading cause of blindness in white Americans older than age 60. Researchers identified a genetic variant that is associated with an increased risk of developing AMD. Future goals include:

–      Discovery of genetic causes of eye diseases

–      A pathway for determining accurate diagnostic genotyping to patients with inherited eye diseases

–      Improved public and professional awareness of genotype/phenotype resources for persons with inherited diseases that affect the visual system, their clinicians, and scientists studying these diseases

–      Large datasets necessary to identify novel genetic risk factors for ocular diseases

–      Refinement/standardization of clinical descriptive terminology for complex ocular diseases

–      A shared database of genotype/phenotype information

II.   Health Information Technology

American Health Information Community

http://www.hhs.gov/healthit/

Description

The American Health Information Community (AHIC) was chartered in 2005 to make recommendations to the Secretary of HHS on how to accelerate the development and adoption of health information technology. AHIC was formed to help advance efforts to reach President Bush’s goal for most Americans to have electronic health records within 10 years. It provides input and recommendations to HHS on how to make health records digital and interoperable and ensure that the privacy and security of those records are protected, in a smooth, market-led way.

Status and Next Steps

In May 2006, the AHIC delivered its first set of recommendations to the Secretary of HHS. The Secretary officially accepted these recommendations, which were in four areas of focus:

• Consumer Empowerment. To create a consumer-directed and secure electronic health-care registration information and medication history for patients.
• Chronic Care. To use secure messaging, such as e-mail, for communication between patients and their health-care providers.
• Electronic Health Records. To create standardized, secure records of past and current laboratory test results that are accessible by health professionals.
• Biosurveillance. To enable the transfer of standardized and de-identified health data to authorized public health agencies within 24 hours.

In addition, AHIC has made significant progress in standards harmonization:

• The AHIC recommended three sets of “Interoperability Specifications” approved by the Health Information Technology Standards Panel (HITSP), a standards panel established by the American National Standards Institute (ANSI) to help in harmonizing hundreds of competing standards. Secretary Leavitt accepted these standards, which form the basis of interoperability.

In 2006, AHIC created three new workgroups to make recommendations to the AHIC, which in turn will provide recommendations to the Secretary:

• Confidentiality, Privacy, and Security
• Health Care Quality
• Personalized Health Care

Information on the PHC Workgroup is at http://www.hhs.gov/healthit/ahic/healthcare/.

Office of the National Coordinator for Health Information Technology

Office of the Secretary of HHS
http://www.hhs.gov/healthit/onc/mission/

Description

The Office of the National Coordinator for Health Information Technology (ONC) provides counsel to the Secretary of HHS and Departmental leadership for the development and nationwide implementation of an interoperable health information technology infrastructure. The ONC also provides management of and logistical support for the AHIC. The National Coordinator for Health Information Technology serves as the Secretary’s principal advisor on the development, application, and use of health information technology.

Status and Next Steps

Accomplishments leading up to 2007 have laid the foundation of a robust health information technology (IT) initiative that is already bringing value to health care consumers and providers. With the organizations and contracts in place and a standards process established, additional progress in the year ahead will be rapid.

• Product Certification. The Certification Commission for Healthcare Information Technology (CCHIT) certified more than 80 ambulatory—or clinician office-based—electronic health record products. The CCHIT seal of approval is awarded to products that meet baseline criteria for functionality, security, and interoperability. This certification encourages adoption IT by assuring providers that their systems can be a part of the future of health IT. See http://www.cchit.org.
• Changes to Regulations.HHS issued new regulations to allow certain arrangements in which a hospital or other health care entity donates health IT and training services to physicians and other health care providers. These new regulations will accelerate adoption by giving physicians and other health care providers increased access to EHR software and assistance in implementing health IT. See http://www.hhs.gov/healthit/certification/stark/.
• Health IT Adoption Measurement. Through a contract with George Washington University, a health IT adoption survey of physician offices was conducted to establish the baseline for current physician use of electronic health records at 10 percent. The survey also identified the criteria necessary to measure success in encouraging further adoption.
• Nationwide Health Information Network.Four prototype architectures for a Nationwide Health Information Network (NHIN) were delivered in January 2007. These prototypes were developed with functional requirements and security and business models for health information exchange. Their delivery marks the beginning of the next phase of NHIN work – to connect the prototypes and State and regional health information exchange efforts in “trial implementations” that will make up the NHIN. See http://www.hhs.gov/healthit/healthnetwork/background/.
• Privacy and Security Across State Lines.To ensure that all patients’ privacy is consistently protected regardless of where they receive care, a regular forum will convene State leaders to reach consensus on cross-border issues of privacy, security, physician licensure, and health care practice, and the States’ roles in health information exchange. In addition, a nationwide summary of State privacy and security assessments, solutions, and implementation plans was recently published. See http://www.healthit.ahrq.gov/privacyandsecurity.
• The Federal Health Care Delivery System.Plans will be completed across the Federal Government to implement the requirements of the President’s 2006 Executive Order on Value-Driven Health Care in a consistent and effective manner. These plans will apply to the Federal Government’s adoption of interoperable health IT within its own delivery system and the contracts it negotiates. See http://www.hhs.gov/valuedriven.

Health Information Technology Initiative

Agency for Healthcare Research and Quality
http://healthit.ahrq.gov

Description

The Agency for Healthcare Research and Quality (AHRQ) initiative on health information technology is a key element of the Nation’s 10-year strategy to bring health care into the 21st century by advancing the use of information technology. The AHRQ initiative includes more than $166 million in grants and contracts in 41 States to support and stimulate investment in health IT, especially in rural and underserved areas. Through these and other projects, AHRQ and its partners will identify challenges to health IT adoption and use, solutions and best practices for making health IT work, and tools that will help hospitals and clinicians successfully incorporate new IT.

Status and Next Steps

In 2004, AHRQ established the AHRQ National Resource Center for Health Information Technology to advance the goals of modernizing health care through the best and most effective use of IT. In addition to providing technical assistance, the National Resource Center shares new knowledge and findings that have the potential to transform everyday clinical practice. AHRQ’s National Resource Center is committed to advancing our national goal of modernizing health care through the best and most effective use of IT. AHRQ has invested more than $166 million in grants and contracts in 41 States to support and stimulate investment in health IT, especially in rural and underserved areas.

AHRQ has awarded contracts to six States—Colorado, Delaware, Indiana, Rhode Island, Tennessee, and Utah—totaling $34.70 million to help them lead the way in regional health information exchange and collaboration. These States are expanding networks for communication and information-sharing among health care providers, laboratories, major purchasers of health care, public and private payers, hospitals, ambulatory care facilities, home health care providers, and long-term care providers.

Most of AHRQ’s health IT grants are 3-year projects, and the five contracts for statewide systems are 5-year projects. These grants and contracts were awarded in the fall of 2004. However, AHRQ will not wait to begin collecting and releasing observations from these projects. Information and interim findings garnered from the projects, as well as from other AHRQ activities, will be shared as quickly as possible through the National Resource Center.

Health Information Technology for Safety Net Providers

Health Resources and Services Administration
http://www.hrsa.gov/healthit/

Description

The Health Resources and Services Administration (HRSA) provides grants and technical assistance for safety net providers to promote the adoption and effective use of health information technology, including electronic medical records and telehealth. HRSA is also working with ONC, CMS, AHRQ, NIH, and CDC to ensure that safety net providers are considered in all HIT adoption efforts.

Status and Next Steps

In support of the President’s Health Center Initiative and his goal of universal adoption of electronic health records (EHR) by 2014, HRSA will award up to 8 grants totaling $9.7 million to promote EHR implementation through either a “Health Center Controlled Network” that links several health centers or a large single health center with 30 or more sites. Funds must be used to implement EHRs in at least 15 sites.

The grants support the use of EHRs as a tool to improve the safety, quality, efficiency, and effectiveness of health care delivery. They also will test the ability of health centers and other safety-net providers to adopt and effectively use EHRs, create sustainable business models for deploying HIT, and leverage initiatives and resources to improve quality and health outcomes.

HRSA also is working to expand the number of users of a HRSA Web portal called the HRSA Health Information Technology Community. The site provides a “virtual” meeting place for users, most of whom are staff from health centers, health center networks, and primary care associations. Users take part in online discussions, share documents, and exchange tools and resources on using electronic technology to promote patient safety and quality of care. HRSA will expand access to the site to organizations that receive grants from HRSA’s HIV/AIDS Bureau, Maternal and Child Health Bureau, Office of Rural Health Policy, and Office for the Advancement of Telehealth.

Use of Medicare Data To Support Research on Health Outcomes

Centers for Medicare & Medicaid Services
http://www.cms.hhs.gov/

Description

Medicare is the largest health insurance program in the country, and it possesses data on claims, treatments, and outcomes that can be of great value in measuring and improving quality and safety of care. The large volume of Medicare data can help define the effectiveness of treatments for increasingly narrow subgroups of the population – especially the effects of drugs among older Americans. Several opportunities are being pursued for sharing Medicare data in a manner that protects individual privacy while yielding valuable information about treatment effectiveness and value.

Status and Next Steps

Coverage with Evidence Development. For treatments and products where clinical information is limited but promising, Medicare has already instituted a process for providing coverage that is contingent on the collection of new evidence to document effectiveness, called Coverage with Evidence Development (CED). The CMS issued a final guidance document on July 12, 2006, describing the CED concept. This CED guidance describes two processes: coverage with appropriateness determination (CAD) and coverage with study participation (CSP).

• CMS is using registries to provide data for the two national coverage determinations (NCDs) that require CAD: ACC-NCDR registry for implantable cardiac defibrillators and the National Oncologic PET Registry for FDG-PET for cancer.
• There are four NCDs that require CSP: cochlear implantation,PET (FDG) for Alzheimer’s disease, anticancer chemotherapy for colorectal cancer, and home use of oxygen. Two of these have trials running: 9 NCI-sponsored clinical trials of anticancer chemotherapy for colorectal cancer and other cancers and an NIH-approved trial evaluating the value of FDG-PET imaging in patients with dementia.

Part D Data. Medicare is also proposing to make available information about drug claims that is available as a result of the Part D drug benefit. On October 18, 2006, the CMS posted a Notice of Proposed Rulemaking that would allow HHS and CMS to use Part D claims data to evaluate Medicare’s prescription drug program. Under the proposed rule, other Federal agencies and external researchers would also be able to use the prescription drug data under the same safeguards that exist for Medicare’s other data. This would allow the use of Part D claims information that is being collected for payment purposes for other research, analysis, reporting, and other public health functions.

• Research questions that have been previously addressed through analysis of Part A (hospital insurance) and Part B (medical insurance) claims have contributed to very significant improvements in public health, have been critical in assessing the quality of care and costs of care for patients in the Medicare program, and have in many cases spurred other types of research. The final regulation allowing the use of Part D claims data is expected to be published later in 2007.

III.  Intervention Development and Review

Critical Path Initiative To Improve Medical Product Development

U.S. Food and Drug Administration
http://www.fda.gov/oc/initiatives/criticalpath/

Description

The Critical Path Initiative is the FDA effort to stimulate and facilitate a national effort to modernize the scientific process through which a potential human drug, biological product, or medical device is transformed from a discovery or “proof of concept” into a medical product.

Status and Next Steps

In keeping with its mission, FDA issued a report, Challenges and Opportunities on the Critical Path to New Medical Products in 2004 to address the growing crisis in moving basic discoveries to the market, where they can be made available to patients. The report evaluates how the crisis came about and offers a way forward. It highlights examples of Agency efforts that have improved the critical path and discusses opportunities for future efforts. Finally, the report calls for a joint effort of industry, academia, and the FDA to identify key problems and develop targeted solutions.

In March 2006, FDA published the second of two reports on the Critical Path to medical product development, Critical Path Opportunities Report and List. The Opportunities Report and List presented 76 specific scientific opportunities that, if undertaken, would help modernize the Critical Path sciences. The opportunities were identified through extensive outreach with patient groups, the pharmaceutical industry, academia, other Federal agencies, and other health-related organizations. More than 30 projects were launched in 2006: http://www.fda.gov/oc/initiatives/criticalpath/opportunities06.html.

In May 2007, FDA issued a report on Critical Path Opportunities for Generic Drugs: http://www.fda.gov/oc/initiatives/criticalpath/reports/generic.html.

Below are listed some key Critical Path collaborations and research activities currently under way with FDA participation. The activities are organized according to the priority topics discussed in the Opportunities Report and List, also available on the Critical Path Web page http://www.fda.gov/oc/initiatives/criticalpath/opportunities06.html. Priority topics include the following:

• Better Evaluation Tools
• Streamlining Clinical Trials
• Harnessing Bioinformatics
• Moving Manufacturing into the 21^st Century
• Developing Products to Address Urgent Public Health Needs
• Specific At-Risk Populations – Pediatrics

Regulatory Submission of Genomic Data in Medical Product Development

U.S. Food and Drug Administration
http://www.fda.gov/cder/genomics/default.htm

Description

The FDA published Guidance for Industry in 2005 entitled Pharmacogenomic Data Submissions. In this guidance, the concept of a voluntary genomic data submission (VGDS) was described along with the FDA’s view of the benefits of submitting exploratory genomic data to FDA. In addition the format, process, and review of VGDS were delineated in detail. In 2004, the FDA Interdisciplinary Pharmacogenomic Review Group (IPRG) was organized as a multicenter, multidisciplinary body to review VGDS.

VGDS Process. Over 40 VGDSs throughout the past 3 years have focused on exploratory genomic biomarkers, their use in preclinical and clinical drug development, diagnostic test validation, clinical enrichment study design, assay validation, and data analysis. Submissions have come from a variety of companies including large PhRMA companies, small drug development specialty companies, platform manufacturers, and diagnostic companies. Therapeutic areas covered by VGDS include alcoholism, Alzheimer’s disease, anti-infective therapies, asthma, depression, diabetes, hypertension, obesity, oncology, and rheumatoid arthritis. VGDSs have also had a major impact on discussions about clinical trial design. Major questions submitted within several VGDSs have focused on the design of clinical trials to qualify exploratory biomarkers in a co-development context. VGDSs have also encouraged submissions of genomic data as a part of INDs, NDAs, and BLAs. Consults for genomic data in regulatory submissions have increased on a par with VGDS meetings.

VGDSs have been submitted to FDA. VGDSs have served to facilitate bilateral exchange and training of regulatory scientists on the technology and application of genomic biomarkers. They have also familiarized industry with the review capabilities within the regulatory authorities and allowed regulators to share their thinking about genomics. Experience gained through VGDS has led to the development of a Pilot Process for Qualification of Biomarkers for use in regulatory decisions.

Over the past 3 years, genomic biomarkers have been supplemented by proteomic, metabolomic, imaging, and fluorescence-activated cell sorting assays. For this reason, the VGDS program has been called the Voluntary Biomarker Data Submission program, or VXDS where X indicates a biomarker from one of many scientific domains.

VGDS guidance can be seen at http://www.fda.gov/cber/gdlns/pharmdtasubcomp.pdf, and FDA-EMEA VGDS guiding principles can be seen at http://www.fda.gov/cder/genomics/FDAEMEA.pdf.

Status and Next Steps

VXDS and Education.The newer VXDS process has also become a source of information for the development of educational offerings in personalized medicine. Gaps in the integration of genomic diagnostic tests into medical practice can be bridged with the learning through multidisciplinary educational programs for physicians, nurses, pharmacists, laboratory personnel, and others associated with personalized medicine. Didactic and Web-based courses are being developed by the FDA.

Companion Guidance for the Pharmacogenomic Guidance.A Companion Guidance for the Pharmacogenomics Guidance has been drafted to recommend protocols in the generation of genomic data from microarrays where a consensus exists for their use and to encourage a discussion leading to a consensus where it is currently lacking. This Companion Guidance has its roots in VXDSs and the experience the FDA has gained from these VXDSs regarding the need for a consensus on how genomic data are generated, reported, and reviewed.

Microarray Quality Control Consortium. This experience has also led to the development of collaborative consortia such as the Microarray Quality Control Consortium (MAQC) to identify sources of variability in the generation of genomic data from microarrays. In its initial phase, MAQC identified sources of variability in the generation of differential gene expression data. MAQC is currently in a second phase, focused on the identification of sources of variability in the determination of predictive genomic signatures.

Predictive Safety Testing Consortium.A collaborative consortium has also been developed to help bridge the gap between exploratory and qualified biomarkers. The Predictive Safety Testing Consortium (PSTC) is working through the C-Path Institute to share data, biomarkers, and nonclinical and clinical samples for the qualifications of nonclinical and clinical biomarkers of safety. The PSTC is a key tool in taking drug-independent exploratory biomarkers into qualification through the Pilot Process for Qualification of Biomarkers.

Review of Genetic Tests for Use in Clinical Practice

U.S. Food and Drug Administration
www.fda.gov/cdrh/oivd

Description

FDA regulates commercially distributed test kits and systems in a comprehensive and transparent manner and ensures quality of these tests through premarket review, application of requirements for good manufacturing practices, and application of a system for postmarket patient safety surveillance. While FDA regulation is not the only path to market for genetic tests and other biomarkers for use in personalized medicine, it provides unique assurances of product quality and safety through a program of independent validation of test performance and labeling.

To date FDA has cleared about a dozen cutting-edge new diagnostics for use in promoting personalized medicine including such tests as the Roche AmpliChip CYP450 test, the Third Wave test for UGT1A1, three tests for cystic fibrosis, the Veridex Circulating Tumor Cell Assay, and the first U.S.-cleared expression array – the Agendia MammaPrint. There are dozens more novel diagnostic devices in the developmental pipeline. Cleared and approved product reviews are prominently published on the Office of In Vitro Diagnostic Devices Web page (see Web page above) in two databases: the 510(k) database for some Class I and most Class II products and the PMA database for most Class III products. Summaries of FDA reviews are a matter of public record and can be used by inform