Secondary Analysis and Integration of Existing Data to Elucidate Cancer Risk and Related Outcomes (R01 Clinical Trial Not Allowed)
National Institutes of Health (NIH)
Estimated funding amount: $350,000
Maximum project duration: 5 years
To support innovative analyses of existing datasets to elucidate cancer risk and related outcomes.
Encourages submission of applications proposing secondary data analysis and integration.
Researchers and institutions involved in cancer research.
Participants in secondary data analysis.
Eligible organization types include higher education institutions, nonprofits, for-profit organizations, small businesses, local and state governments, and federal agencies.
Non-domestic entities (foreign organizations) are also eligible.
Open to U.S. and non-U.S. entities.
No specific geographic limitations mentioned.
Focus on secondary data analysis related to cancer risk and outcomes.
Encourages innovative methods and integration of existing datasets.
Budget limited to $350,000 direct costs per year.
No cost-sharing required.
Applications due by 5:00 PM local time of applicant organization.
Funding opportunity posted on November 18, 2024, with a response date of September 7, 2026.
No restrictions on prior grant funding mentioned.
Applicants may submit more than one application if scientifically distinct.
Applications must follow the instructions in the Research (R) Instructions in the How to Apply - Application Guide.
Applications evaluated for scientific and technical merit.
Overall impact score based on significance, innovation, rigor, and feasibility.
Applications will undergo peer review and a second level of review by the national Advisory Council or Board.
Scientific and technical merit, availability of funds, and relevance to program priorities.
Applications must not propose to collect or generate new data except for limited validation of key findings.
Challenges in finding and including datasets representing underrepresented populations.
Encourages collaboration with investigators holding publicly and non-publicly available datasets.
Innovative approaches to data analysis may provide a competitive edge.
Leveraging existing datasets effectively.
Demonstrating innovative analytical methods.
Proposing to collect new data outside the allowed scope.
Engage with NIH program officials to discuss research relevance.
Focus on innovative data integration and analysis methods.