The NIH Common Fund PRIMED-AI Data-to-Model Academic–Industrial Partnerships (D2M-AIP) program supports multidisciplinary teams developing new AI-enabled clinical decision-support tools that combine clinical imaging with multimodal health data.
The program brings academic and industry partners together to integrate complex datasets, develop and validate novel AI models, and move promising technologies toward regulatory readiness and future clinical use. Projects must use clinical imaging as the anchor data type and integrate at least one additional data modality.
Eligibility Criteria
- Applications must include a designated MPI from at least one academic institution.
- Applications must also include a designated MPI from at least one industry partner.
- Eligible organizations include universities, nonprofit research organizations, small businesses, and other for-profit organizations.
- Foreign organizations are eligible to apply.
- Projects must develop an AI-enabled, image-centered, multimodal clinical decision-support tool.
- Clinical imaging must serve as the primary anchor data type.
- Projects focused only on basic AI/ML methods without a clear translational clinical goal are not eligible.
Funding Details
- UG3 phase: Up to $450,000 in direct costs per year
- UH3 phase: Up to $800,000 in direct costs per year
- Total duration: Up to 5 year
- UG3 phase: up to approximately 2 years
- NIH expects to fund approximately 6–8 awards.
Deadline
- Posted: June 30, 2026
- Applications opened: September 19, 2026
- Application deadline: October 19, 2026, at 5:00 PM local time of the applicant organization
- Scientific merit review: March 2027
- Advisory Council review: May 2027
- Earliest project start: July 2027
Further Information
- Funding opportunity number: RFA-RM-27-012
- Funding mechanism: UG3/UH3 Cooperative Agreement
- Projects should include a clear commercialization and regulatory strategy.
- Official NIH PRIMED-AI Funding Opportunities