Secondary Analysis and Integration of Existing Data to Elucidate Cancer Risk and Related Outcomes (R21 Clinical Trials Not Allowed)

The Secondary Analysis and Integration of Existing Data to Elucidate Cancer Risk and Related Outcomes funding opportunity is administered by the U.S. Department of Health and Human Services through the National Institutes of Health, with participation from the National Cancer Institute, National Human Genome Research Institute, National Institute on Aging, and National Institute of Dental and Craniofacial Research. This initiative reflects a broader federal commitment to maximizing the value of existing biomedical and population-level datasets by promoting their reuse for innovative cancer research. The program is structured as an R21 exploratory and developmental research grant mechanism, emphasizing early-stage, high-impact scientific inquiry. The purpose of this funding opportunity is to support projects that conduct secondary analysis and integration of existing datasets to better understand cancer risk, progression, and related outcomes. Applicants are encouraged to address key scientific questions using existing clinical, genomic, environmental, behavioral, and health services data. The program prioritizes research that can generate new insights without the need for primary data collection, instead leveraging already available datasets in novel ways. This includes combining datasets, applying advanced analytical techniques, or exploring previously unexamined hypotheses related to cancer etiology, prevention, and treatment outcomes. Funding is limited to direct costs of up to 275000 dollars over a maximum project period of two years, with no more than 200000 dollars allowed in any single year. The funding is intended for cost-effective studies that primarily rely on existing data resources, although up to 10 percent of the budget may be allocated toward generating new data strictly for validation purposes. Applicants must ensure that proposed activities remain within the scope of secondary analysis and do not involve clinical trials or extensive new data collection. Awardees are also expected to comply with NIH data sharing policies, including making cleaned datasets and analytical tools available to the research community when appropriate. Eligibility for this opportunity is broad and includes a wide range of domestic and international organizations. Eligible entities include higher education institutions, nonprofit organizations, for-profit companies, government agencies at all levels, and tribal organizations. Individual researchers must be affiliated with an eligible organization and possess the expertise and resources necessary to carry out the proposed research. Foreign organizations are permitted to apply, though specific restrictions apply to subawards involving foreign entities. Applications must be submitted electronically through approved NIH systems such as ASSIST, Grants.gov Workspace, or institutional system-to-system solutions. The application must follow the NIH Research (R) instructions and include detailed sections such as the research strategy, data management and sharing plan, and budget justification. The research strategy must clearly articulate the significance, innovation, and feasibility of the proposed work, including detailed descriptions of the datasets to be used and the analytical methods to be applied. Applications that do not adhere strictly to the submission guidelines may be rejected without review. The evaluation process is conducted through NIH’s peer review system, where applications are assessed based on scientific merit, including significance, innovation, rigor, feasibility, and investigator expertise. Projects are expected to demonstrate the potential for meaningful impact on cancer research and public health. Following peer review, applications undergo a second level of review by an advisory council before funding decisions are made. Awards are contingent upon the availability of funds and alignment with program priorities. The funding opportunity follows a recurring submission schedule with standard NIH due dates occurring multiple times per year. For example, submission deadlines include February, June, and October cycles, with corresponding review and award timelines extending several months beyond each deadline. Applications must be submitted by 500 PM local time on the due date. The current funding opportunity is active through November 17, 2026, and applicants are encouraged to apply early to allow time for corrections during the submission process.

Focus on innovative integration of multiple datasets; clearly justify dataset suitability and sample size; demonstrate feasibility within 2-year timeline; align with NIH data sharing priorities