The Precision Medicine Initiative Cohort Program

Building a Research Foundation for 21st Century Medicine

Executive Summary

In his State of the Union Address on January 20, 2015, President Obama announced his intention to launch a Precision Medicine Initiative (PMI) “to bring us closer to curing diseases like cancer and diabetes, and to give all of us access to the personalized information we need to keep ourselves and our families healthier.” Ten days later, at a White House event with patients, advocates, scientists, and industry leaders, the President shared his vision for the Initiative to enhance innovation in biomedical research with the ultimate goal of moving the U.S. into an era where medical treatment can be tailored to each patient.

Screen Shot 2015-10-31 at 2.05.45 PMPrecision medicine is an approach to disease treatment and prevention that seeks to maximize effectiveness by taking into account individual variability in genes, environment, and lifestyle. Precision medicine seeks to redefine our understanding of disease onset and progression, treatment response, and health outcomes through the more precise measurement of molecular, environmental, and behavioral factors that contribute to health and disease. This understanding will lead to more accurate diagnoses, more rational disease prevention strategies, better treatment selection, and the development of novel therapies. Coincident with advancing the science of medicine is a changing culture of medical practice and medical research that engages individuals as active partners – not just as patients or research subjects. We believe the combination of a highly engaged population and rich biological, health, behavioral, and environmental data will usher in a new and more effective era of American healthcare.

In order to achieve the President’s ambitious plan, the PMI Cohort Program (PMI-CP) will build a large research cohort of one million or more Americans that will provide the platform for expanding our knowledge of precision medicine approaches and that will benefit the nation for many years to come. In March of 2015, NIH Director Dr. Francis Collins formed the PMI Working Group of the Advisory Committee to the Director to develop a plan for creating and managing such a research cohort. To help carry out its charge, the Working Group engaged with stakeholders and members of the public through workshops and requests for information, focusing on issues related to the design and oversight of the cohort. Public engagement, as well as internal discussions among the Working Group, led to the vision for the design and utility of the cohort program outlined in this report. The report includes recommendations in six areas critical to the development, implementation, and oversight of the PMI-CP: cohort assembly, participant engagement, data, biobanking, policy, and governance. In addition to the recommendations, the Working Group outlined the potential utility and unique opportunities that could be addressed by the PMI cohort.

Capabilities of the PMI cohort

Thanks to advances in genomic technologies, data collection and storage, computational analysis, and mobile health applications over the last decade, the creation of a large-scale precision medicine cohort is now possible in a way that it was not before. The Working Group identified a number of high-value scientific opportunities or use cases that could be used to inform the design of the PMI cohort. These use cases include: development of quantitative estimates of risk for a range of diseases by integrating environmental exposures, genetic factors, and gene-environment interactions; identification of determinants of individual variation in efficacy and safety of commonly used therapeutics; discovery of biomarkers that identify people with increased or decreased risk of developing common diseases; use of mobile health (mHealth) technologies to correlate activity, physiologic measures and environmental exposures with health outcomes; determination of the health impact of heterozygous loss of function mutations; development new disease classifications and relationships; empowerment of participants with data and information to improve their own health; and creation of a platform to enable trials of targeted therapy.

These scientific opportunities will be explored in stages throughout the life of the PMI cohort and should not be considered as an exhaustive list. Rather, as the richness of the data increases and technology evolves, additional capabilities of the cohort will emerge.

Specific Recommendations for the PMI-CP and PMI Cohort. The Working Group offers recommendations, major and minor, to guide the development of the PMI-CP and the PMI cohort. What follows is a summary of the major findings and recommendations. References to specific numbered recommendations, where appropriate, are included in parentheses.

Cohort Assembly

The Working Group supports the initial goal to include one million volunteers, and suggests that the cohort should continue to grow over time. The Working Group envisions the PMI cohort as a new, broadly accessible, national research resource of volunteers specifically consented as part of the PMI-CP. To be useful to the goals of PMI, the Working Group recommends that all potential participants in the PMI cohort must agree to share their health data, provide a biospecimen, and be recontacted for future research (3.1). The Working Group also recommends that the PMI cohort reflect the diversity of the U.S. (3.2).

The Working Group identifies two distinct methods to recruit participants (3.4). The first approach is designed to enable any individual living in America to volunteer for the PMI cohort (3.3). These “direct volunteers” would consent to be part of the PMI cohort, agree to be recontacted, undertake a PMI baseline health exam, and provide a biospecimen. They would share available health data by either directing their electronic health record (EHR) data to the PMI-CP and/or by undergoing an initial exam with a health care provider. The second approach would be to collaborate with healthcare provider organizations (HPOs) to recruit participants (3.5). HPOs would recruit participants, consent them for participation in the PMI cohort, conduct a PMI baseline exam, collect a biospecimen, and share EHR data with the PMI-CP. When selecting HPOs to join the PMI-CP, the Working Group recommends that NIH consider the contribution of the HPO to the overall diversity of the PMI cohort, the robustness of the EHR, and expected length of follow-up for participants. With robust implementation, the Working Group expects the PMI-CP to be able to recruit at least one million participants over about four years.

Participant Engagement

The Working Group recommends that the PMI cohort be developed using a highly interactive and proactive participation model, where cohort participants are encouraged to engage in all aspects of the cohort. In addition to providing feedback and input during planning and implementation phases of the cohort, participants should have significant representation on PMI-CP governance and oversight committees (4.1). The Working Group recognizes that building and 3 maintaining trust is a critical component to a successful, ongoing, collaborative relationship with participants and the public at large, and recommends the development of a set of guiding principles that apply to all PMI cohort stakeholders (4.2). To ensure that participant-related interactions remain consistent throughout the PMI-CP, the Working Group recommends that activities related to engagement and communications be organized and managed by a central entity (4.3, 4.4). However, the PMI-CP would still benefit from collaborating with a variety of organizations in support of the PMI cohort, to maximize its outreach potential. The Working Group also recommends that the PMI-CP use a standardized consent protocol to ensure consistency in the terms and conditions that all PMI cohort participants agree to. The PMI cohort consent protocol should give participants the option to join supplementary or complementary studies outside the PMI cohort (4.5, 4.6). The Working Group recommends that the PMI-CP return to each participant their own results and aggregated results from its studies to all participants (4.7). Participants should be able to set preferences to dictate how much personal information they receive, and be able to change their preferences throughout their participation in the PMI-CP. To oversee the development and implementation of policies related to the return of aggregate and individual results to participants, the Working Group recommends that a subcommittee with significant participant representation be formed as part of the PMI-CP governance structure (4.8).

Data Considerations

Successful development of the PMI-CP will require a combination of well-proven and innovative methods and technologies for data collection and management. Guided by the scientific opportunities, the PMI-CP should anticipate and collect a diverse set of data types, beginning with a core set of high-value variables to be acquired during enrollment from all PMI cohort participants. Together, these will constitute a core data set that will enable both cohort-wide analyses and identification of subcohorts eligible to participate in specialized studies (5.1). The Working Group recommends that the initial core data set acquired from all PMI cohort participants be collected and stored centrally (5.13, 5.23). The PMI-CP should seek to align its core data set with other comparable core data sets where possible. The recommended initial core data set includes data from EHRs, health insurance organizations, participant surveys, mHealth technologies, and biologic investigations, and would be expected to grow with time. Efficient structuring and management of data is important to the success of the PMI-CP. Toward this end, the Working Group recommends use of a common data model to organize data similarly across HPOs and from direct volunteers, where possible, while recognizing that many data types useful from clinical investigation may not easily be transformed to an existing or created standard at this time (5.20, 5.23). The best approach will balance normalization of only the highest value data initially for all participants followed by on-demand data curation of other data as driven by scientific demand. In addition, the Working Group recommends that existing data standards and common data models be leveraged where possible (5.25, 5.26), while recognizing that standards do not exist for many emerging modalities, such as a number of sensor technologies. The Working Group recommends early selection of commonly used mHealth technologies to gain experience in use and integration of these new modalities.

[Editor’s Note: read complete report, here].

For excellent context listen to From Bench to Bedside How Precision Medicine Is Changing the Future via Francis Collins, MD Follow on twitter via @NIHDirector

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