PRIMED-AI: Translating Models to Clinic (UG3/UH3 Clinical Trial Optional)

The National Institutes of Health (NIH), through the NIH Common Fund and in collaboration with other participating NIH Institutes and Centers, has announced its intent to publish a Notice of Funding Opportunity under the PRIMED-AI program, formally titled Precision Medicine with Artificial Intelligence - Integrating Imaging with Multimodal Data. This initiative seeks to accelerate the development and clinical translation of artificial intelligence-based tools that integrate imaging data with other forms of health information, advancing the field of precision medicine for individuals with chronic and other complex health conditions. By combining multimodal data sources, the program aims to overcome current limitations in diagnostic accuracy, prognostic prediction, and therapeutic guidance. The PRIMED-AI Translating Models to Clinic initiative will employ a biphasic UG3/UH3 cooperative agreement structure. The UG3 phase will focus on rigorous model development, leveraging retrospective analyses of large-scale, interoperable multimodal datasets. Applicants will be expected to demonstrate the reliability, reproducibility, and potential clinical utility of their proposed models. Successful projects with clear promise for translation will advance to the UH3 phase, which will emphasize the evaluation of real-world clinical utility in patient care settings. This staged approach ensures that only the most robust and clinically relevant AI models progress to clinical implementation. The scope of funding is intended to support innovative AI approaches that integrate imaging data with other modalities such as genomics, electronic health records, laboratory results, and wearable or sensor-based data. Projects should address clear gaps where existing methods are inadequate and propose clinically meaningful solutions that can improve health outcomes. Cost sharing or matching is not required, lowering barriers for participation from a broad range of institutions and organizations. With an estimated total program funding of $10.2 million, NIH anticipates making multiple awards, though the exact number and size of awards remain unspecified in this forecast. Eligibility is broad and includes nonprofits with 501(c)(3) status, for-profit organizations, small businesses, state and local governments, institutions of higher education (public and private), independent school districts, public housing authorities, Native American tribal governments and organizations, and county governments. This wide eligibility reflects NIH’s interest in drawing expertise from diverse sectors of the biomedical and technological ecosystem. Individuals are not listed as eligible applicants. Organizations are encouraged to form collaborative teams that bring together expertise in AI, data science, clinical research, and implementation science. The forecasted publication date for the full funding opportunity is December 11, 2025, with an estimated application due date of February 11, 2026. The estimated award and project start date are both December 1, 2026, with funding anticipated for fiscal year 2027. Applications will be submitted through standard NIH and Grants.gov channels, and prospective applicants should begin building partnerships and preparing datasets in anticipation of the upcoming release. The opportunity is categorized under Health, with cooperative agreements as the funding instrument type. Contact for this opportunity is provided as Sahana N. Kukke, PhD, of the NIH Office of the Director, reachable at 301-402-3756 or via ODPRIMED-AI@od.nih.gov. While applications are not yet being accepted, this forecast serves to allow adequate time for research teams to assemble strong, competitive proposals. Interested applicants should monitor Grants.gov and NIH communications for the official release of the Notice of Funding Opportunity and detailed application instructions.

Notice recommends that interested parties begin forming collaborations and preparing proposals early.