The National Institutes of Health (NIH), under the U.S. Department of Health and Human Services, is forecasting a new funding opportunity titled "PRIMED-AI: Academic-Industrial Partnerships (UG3/UH3 Clinical Trial Optional)." This opportunity is part of the NIH Common Fund’s broader initiative and involves collaboration with various NIH Institutes and Centers. The goal is to support the development of artificial intelligence (AI)-based tools that integrate clinical imaging and multimodal health data to enhance the delivery of personalized medicine, particularly for chronic and complex conditions.
The program encourages academic-industrial partnerships that are capable of addressing challenges in data integration and interoperability in its initial phase. A follow-up phase will focus on the development, validation, and performance testing of AI algorithms. The funding will be administered through the UG3/UH3 cooperative agreement mechanism, which is designed for phased innovation projects that require milestone-driven transitions between stages.
Eligible applicants include a wide range of organizations such as state and county governments, independent school districts, public and private institutions of higher education, public housing authorities, non-profits with 501(c)(3) status, tribal organizations (both federally and non-federally recognized), small businesses, and other for-profit organizations. No cost sharing or matching requirements are stipulated, and clinical trials are optional under this opportunity.
The estimated total funding available for the program is $2.9 million. While the award ceiling and floor amounts are not yet specified, this figure reflects the aggregate financial scope across all selected projects. The opportunity is projected to be posted on July 1, 2025, with applications due by November 1, 2025. Awards are anticipated to be announced by September 1, 2026, with the project start date set for the same day. This forecast allows potential applicants to begin establishing meaningful partnerships and prepare comprehensive proposals in advance.
The NIH strongly encourages investigators experienced in developing AI tools from medical imaging and integrating multimodal clinical data to consider this opportunity. In particular, teams combining expertise in academic and industrial collaboration are ideal candidates. While applications are not currently being solicited, the notice provides ample time for the formation of interdisciplinary partnerships.
For further information, interested parties should contact Sahana N. Kukke, PhD, at the Office of the Director, NIH Common Fund. She can be reached by phone at 301-402-3756 or via email at ODPRIMED-AI@od.nih.gov.
The notice suggests forming meaningful partnerships in advance and preparing responsive projects that align with the dual-phase funding structure.
