Request for Information: NIH Precision Medicine Cohort

Notice Number: NOT-OD-15-096

Key Dates
Release Date: April 20, 2015
Response Date: May 7, 2015   

Related Announcements

Issued by
National Institutes of Health (NIH)


This Request for Information (RFI) seeks feedback to help guide the National Institutes of Health (NIH) in creating a longitudinal cohort of 1 million or more Americans who have volunteered to participate in research as part of the President’s proposed Precision Medicine Initiative. Participants will be asked to give consent for extensive characterization of biologic specimens (potentially including cell populations, proteins, metabolites, RNA, and DNA whole-genome sequencing, if/when costs permit) and behavioral and environmental data, all linked to their electronic health records (EHRs). Qualified researchers from many organizations will, with appropriate protection of participant confidentiality, have access to the cohort's de-identified data for research and analysis.

Precision medicine is the application of prevention and treatment strategies that take individual variability into account.  This is not a new concept but opportunities for evidence-based precision medicine have greatly expanded recently due to the development of better large-scale biologic databases and computational tools, among other things.  What is needed is a research resource for developing and validating new approaches to precision medicine that could be used to guide clinical practice ultimately to improve health. The goals of the NIH Precision Medicine Cohort are to enable better assessment of disease risk, understand disease mechanisms, and predict optimal therapy for a broad range of diseases through the study of a large group of people who have volunteered to provide data and biospecimens over time to a cadre of researchers pursuing these research goals.  These data will also enable observational studies of drugs and devices and potentially prompt more rigorous interventional studies that address specific questions.

Characteristics of such a large-scale study that might maximize its research value may include: 1) a sufficiently large number of participants to achieve adequate power for common disorders and reasonable representation of rare disorders; 2) intentional over-sampling of populations underrepresented in research to permit meaningful inferences about these groups and to study health disparities; 3) a broad age range to provide information on disorders from infancy to old age; 4) a broad range of genetic backgrounds and environmental exposures; 5) a broad array of clinical and laboratory information, not limited to any single disease, as well as patient reported outcomes; 6) sophisticated dietary, other lifestyle, and environmental exposure assessment, preferably provided directly from participants using mobile devices and wearable sensors; 7) access to comprehensive electronic health data on participants for baseline, follow-up, and possibly also retrospective (prior to study entry) data collection, as well as return of actionable results for use in their clinical care; 8) return of appropriate information and results to participants as they desire; 9) collection and storage of biological specimens; 10) access to study data and biologic materials to qualified researchers to empower research on many diseases by researchers in many sectors; 11) community engagement in the design and implementation of the study, including a state-of-the-art consent process, to allow multiple uses of the data, regular feedback to participants about findings and progress; and 12) a study design that ensures a high follow-up rate.

Sharing data consistent with achieving the goals of this project and in accordance with the NIH’s data sharing policies will be expected.

Background Information

On January 20, 2015, President Obama announced a new Precision Medicine Initiative for fiscal year 2016 in his State of the Union address, and expanded on the announcement at a White House event on January 30, 2015.  On that same day, Drs. Francis Collins and Harold Varmus published a Perspective in the New England Journal of Medicine, “A New Initiative on Precision Medicine.”  Opportunities and obstacles for developing such a cohort were explored in a preliminary way in a February 2015 NIH workshop, “Building a Large U.S. Research Cohort.”  Steps arising from that workshop include establishing a Working Group of the Advisory Committee to the Director (ACD), NIH, to develop a plan for creating and managing this large research cohort.  To ensure that the Working Group’s contributions can be incorporated into the funding plan for fiscal year 2016, a report will be delivered to the ACD in September 2015.  Funding solicitations to establish the cohort, if warranted, will be developed shortly thereafter for award in mid- to late fiscal 2016.

Information Requested

The NIH seeks information on characteristics, purpose, or other overall aspects in the development and implementation of a large U.S. precision medicine cohort. Information is also sought regarding existing and potentially new entities that have the capability to identify and follow ideally 10,000 or more participants and, if combined with other research entities, could comprise a longitudinal cohort of 1 million or more Americans. The participants should consent to joining this large U.S. cohort and provide their medical, genomic, and other health-related data, with appropriate protections, for broad research use.  A research entity could be a health care system, research network, cohort study or consortium, or other entity such as a longitudinal study using digital-based research platforms.

Ideally, participants from a research entity should be able to provide comprehensive clinical information via electronic health data that can be harmonized with data from multiple other systems or networks. Participants may come from ongoing studies with several previously measured phenotypes, stored biological specimens, and proven high quality DNA.  Participants may also be recruited de novo.  Participants may have been ascertained at random or by disease status.  Biological samples and associated data should be available and transferrable.  Participants should be accessible for consent or re-consent for data sharing, whole genome sequencing and other biologic measures, multi-use (ability to perform analysis of multiple traits and measures, not just one single disease), and call-back for consent for further in-depth study.

The NIH seeks comments on any or all of, but not limited to, the following topics:

A. General topics on the development and implementation of this large U.S. cohort.

1) The optimal study design and sample size for a large U.S. precision medicine cohort.

2) Data to be collected at baseline and follow-up, including mode of collection and frequency and length of follow-up.

3) Potential research questions that could be uniquely or more efficiently and effectively pursued in a large U.S. precision medicine cohort.

4) Any other suggestions for NIH to consider in the development and implementation of such a research cohort.

B. Suggestions for existing or potentially new research entities (a health care system, research network, cohort study or consortium, or other entities such as longitudinal studies using digital-based platforms) that might be combined into a large U.S. cohort.  Providing the following information would be useful when suggesting research entities.

1) The capability of the existing or potentially new research entity to efficiently identify and follow 10,000 or more participants who are likely to consent to providing their medical and other health-related data, biospecimens, and genomic data for broad research use, including in sub-group analysis that could help assess various treatment effects and outcomes.  It would also be useful to provide the rationale that potential participants are likely to consent, as well as experience with and ability to participate in central IRB and a master contract agreement to streamline enrollment of the precision medicine cohort.

2) The capability for the research entity to provide individual-level participant data, particularly those from electronic health data (including both electronic health record and payer data), that can be integrated into a standard format to create a combined large longitudinal precision medicine cohort.

3) The capability for the research entity to track and retain the participants for several years of follow up.  The race/ethnic composition, sex, and age distribution of participants from the research entity likely to consent, by standard U.S. Census categories, would also be helpful. The NIH especially seeks information about studies of populations underrepresented in research and those with phenotypes or disorders of high public health and human impact. Additional information that would be of use includes: for health care systems, the current patient turnover rate and efforts that can be made to capture longitudinal data from clinical visits outside of the system and to continue follow participants who leave the system entirely; and for ongoing cohort studies, the retention rate to date.


All responses must be submitted online via the following website: by May 7, 2015. Response to this RFI is voluntary. Responders are free to address any or all of the categories listed above; respondents should not feel compelled to address all listed issues. Please note that the text box for each topic has a maximum limit of approximately 250 words.

This RFI is for planning purposes only and should not be construed as a solicitation for applications or as an obligation on the part of the Government to provide support for any ideas identified in response to it. Please note that the United States Government will not pay for the preparation of any information submitted or for its use of that information.

Responses will be compiled and may be shared publically. We look forward to your input and hope that you will share this RFI document with your colleagues.  Updates to this document, if any, will be noted. Please check before submission.


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