Project Details

Information Exchange and Data Transformation (INFORMED) Initiative 

The Food and Drug Administration (FDA) seeks to create a big data environment comprised of aggregated datasets from new drug applications (NDAs), electronic medical records, wearable technologies, and social media networks to support meta-analyses and other data explorations that can yield groundbreaking scientific and regulatory insights.

Internal Project Team

  • Sean Khozin, MD, MPH, Senior Medical Officer, OHOP, FDA (Project Lead)
  • Geoffrey Kim, MD, Division Director, Division of Oncology Products 1, OHOP, FDA
  • Richard Pazdur, MD, Office Director, OHOP, FDA (Executive Sponsor)

We are not currently accepting applications for this position. 

Check out our open EIR positions here.

Project Summary

The Problem

As the world’s leading drug regulatory agency, FDA has a large and growing repository of clinical trial data from NDA submissions on the safety and efficacy of drugs in many diseases and patient populations. FDA’s experience conducting meta-analyses (analyses of data aggregated from multiple clinical trials) has yielded important findings beyond those discovered in the individual studies. However, such analyses occur infrequently due to the lack of efficient and cost-effective mechanisms of aggregating and transforming multiple independent datasets. Furthermore, emerging data from sources such as electronic medical records, wearable technologies, biometric monitoring devices, and social media networks have created new opportunities for conducting novel analyses that are not currently performed in a systematic manner.

The Proposed Solution

The Office of Hematology and Oncology Products (OHOP) at FDA, which is responsible for making safe and effective drugs for cancer and hematologic conditions available to the public, seeks to develop a big data environment for clinical trials and other emerging data sources for novel explorations and analyses. This initiative involves the following core components:

  1. Transformation of FDA’s existing clinical trial datasets into a common standard;
  2. Development of a big data environment for storage and mining of transformed datasets; and
  3. Incorporation of diverse pipelines of data (e.g. electronic medical records, wearable technologies, biometric monitoring devices, social media networks) into the big data environment

The EIR will serve as the catalyst for organizing efforts in support of the core components of the initiative. The EIR will lead the development of new methods to transform datasets to support current internal projects, such as the newly launched effort to develop predictive tools for serious adverse events of small molecule kinase inhibitors. The results of this work have the potential to significantly impact the way adverse events associated with new targeted cancer therapies are estimated, and will serve as a blueprint for future predictive modeling projects. The EIR will also initiate the development of a scalable big data environment through collaboration with FDA’s internal teams and building strategic partnerships (e.g., academic and public-private partnerships) in support of the initiative.

The EIR will help create a sustainable institutional framework for continued growth of the initiative by working with FDA leadership to develop policies and procedures governing the use and maintenance of the big data environment.

Potential Impact

The big data environment, and the ecosystem of internal and external partners, will allow conducting large scale analyses of multiple datasets to address important questions that cannot be answered by analysis of data from single clinical trials or a limited number of data sources. For example, the big data environment can be used to test hypotheses on developing new therapies for rare cancers and small genetic subsets; understanding serious adverse events that occur infrequently in a single clinical trial but can be characterized by analyzing aggregated datasets; running virtual clinical trials; and creating mathematical models for different diseases to inform future clinical trial designs. The big data environment will be able to support a learning health system where science, technology, analytics, incentives, and culture are aligned for continuous improvement and innovation and new knowledge is captured as a primary outcome of the ecosystem experience to serve FDA’s mission of protecting and advancing the public health.

Desired Skills for Entrepreneur-in-Residence

FDA seeks an EIR with the following skills:

  • Demonstrated leadership experience in development and implementation of complex technology solutions involving multiple stakeholders;
  • Ability to think strategically; and
  • A creative thinker and disruptive innovator.

About the EIR Program

The HHS Entrepreneurs-in-Residence (EIR) program helps HHS teams identify, recruit and onboard external talent to tackle high-priority challenges in health and human services. EIRs bring skill sets to an internal project team that are difficult to find within government to complete a high-impact project in about one year.