Secondary Analysis and Integration of Existing Data to Elucidate Cancer Risk and Related Outcomes (R01 Clinical Trial Not Allowed)
Can you apply?
This grant is for researchers studying cancer risk using existing datasets and databases. Eligible applicants typically include academic researchers, research institutions, and independent research organizations with a strong scientific foundation. Applicants must be affiliated with a domestic institution and have the capacity to manage federal research funding. Direct clinical trials are not permitted; secondary analysis and data integration approaches are required.
Geographic scope includes U.S. domestic institutions and territories. International collaborations may be allowed as components of U.S.-led projects. Cancer-related research topics are prioritized, particularly studies examining risk factors, etiology, and health outcomes using retrospective or secondary data sources.
This grant is for researchers studying cancer risk using existing datasets and databases. Eligible applicants typically include academic researchers, research institutions, and independent research organizations with a strong scientific foundation. Applicants must be affiliated with a domestic institution and have the capacity to manage federal research funding. Direct clinical trials are not permitted; secondary analysis and data integration approaches are required.
Geographic scope includes U.S. domestic institutions and territories. International collaborations may be allowed as components of U.S.-led projects. Cancer-related research topics are prioritized, particularly studies examining risk factors, etiology, and health outcomes using retrospective or secondary data sources.
Program description
Through this Notice of Funding Opportunity (NOFO), the National Cancer Institute (NCI) along with other participating Institutes encourages submission of applications proposing to conduct secondary data analysis and integration of existing datasets and database resources, with the ultimate aim to elucidate cancer risk and related outcomes (e.g., risk prediction or reduction, survival, or response to treatment, etc.). The goal of this initiative is to address key scientific questions relevant to cancer by supporting the analysis of existing clinical, environmental, surveillance, health services, vital statistics, behavioral, lifestyle, genomic, and molecular profiles data. Applicants are encouraged to leverage and perform innovative analyses of the existing data. Applications may include new research aims that are being addressed with existing data, new or advanced methods of analyses, or novel combinations and integration of datasets that allow the exploration of important scientific questions in cancer research.
Who can apply
Eligible applicants
- 501(c)(3) Public Charity
- City / Municipal Government
- County Government
- Nonprofits
- Private University
- Public Authority
- Public K-12 School
- Public University
- Small Business (SBA-defined)
- Special District
- State Government
- Tribal Nation
- Tribal Organization
Details
This grant is for researchers studying cancer risk using existing datasets and databases. Eligible applicants typically include academic researchers, research institutions, and independent research organizations with a strong scientific foundation. Applicants must be affiliated with a domestic institution and have the capacity to manage federal research funding. Direct clinical trials are not permitted; secondary analysis and data integration approaches are required.
Geographic scope includes U.S. domestic institutions and territories. International collaborations may be allowed as components of U.S.-led projects. Cancer-related research topics are prioritized, particularly studies examining risk factors, etiology, and health outcomes using retrospective or secondary data sources.
How to apply
Application links
Required documents
- SF-424 (R&R) application form
- Project Narrative (research plan)
- Detailed Budget and Budget Justification
- Biographical Sketches (all key personnel)
- Data Management and Sharing Plan
- Letters of Data Access/Collaboration
- References
- Facilities and Administrative Resources description
Program contact
- 👤 National Institutes of Health
- 📧 grantsinfo@nih.gov
- 📞 301-402-2541
Funding track record
Recent awards under CFDA 93.121 from the last 3 years — real organizations that won funding through this same program.
Top 10 Largest Recent Awards
-
$443,702,768
-
$32,310,944
-
$31,252,186
-
$29,535,192
-
$23,987,187
-
$23,513,241
-
$18,362,716
-
$16,829,492
-
$15,691,075
-
$14,460,130
Top States by Funding
- WA 2 awards $451.4M
- CA 13 awards $134.6M
- MI 4 awards $75.8M
- PA 4 awards $67.6M
- MA 5 awards $39.0M
Source: USAspending.gov — federal spending transparency. Data covers last 3 years.
Funding history
Annual funding for this program — Federal obligations (CFDA 93.172). How funding has trended year over year.
| 2024 | $452,727,668 | |
| 2025 | $423,878,429 | |
| 2026 est. | $9,989,158 |
FAQ
Who can apply for this grant?
Research institutions, universities, and domestic organizations with research capacity. Individuals must have institutional affiliation and appropriate research credentials.
What type of research is supported?
Secondary data analysis and data integration studies examining cancer risk. Direct clinical trials are not allowed under this specific mechanism.
What is the typical project timeline?
NIH R01 grants typically support 3-5 year projects. Check the funding opportunity for specific permitted project periods.
How competitive is this funding?
R01 mechanisms are highly competitive, typically funding 15-25% of applications. Strong preliminary data and clear innovation are essential.
What is the funding range?
R01 awards vary widely based on scientific scope and institutional structure. Budget limitations typically apply per NIH guidelines for your institution type.
💡 Tips for applicants
- Use existing, well-documented datasets with clear data-sharing agreements already in place. This demonstrates feasibility and reduces reviewer concerns.
- Develop a compelling research question that cancer epidemiology cannot answer with current published literature. Show why your analysis fills a genuine gap.
- Assemble a team with complementary expertise in cancer research, biostatistics, and data science. Clear role definition strengthens applications.
- Include a detailed data management and analysis plan with specific computational methods. Reviewers assess technical soundness carefully.
- Address reproducibility and data sharing plans upfront. NIH expects transparency about how you'll make results publicly accessible.
⚠️ Common mistakes
Proposing a study design that mimics a clinical trial. NIH will reject applications involving intervention or prospective data collection.
Underestimating the complexity of secondary data analysis. Reviewers reject applications with vague analytic plans or insufficient statistical detail.
Failing to demonstrate access to the proposed datasets before submission. Contingent data access is a major red flag for federal reviewers.
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