PRIMED-AI: Data-to-Model Academic-Industrial Partnerships (D2M-AIP) for Precision Medicine with AI: Integrating Imaging with Multimodal Data (UG3/UH3 Clinical Trial Optional)
National Institutes of Health
Award ceiling
—Award floor
—Posted
Jun 30, 2026Closes
Oct 19, 2026Location eligibility
No specific state restriction found in this listing — check the full opportunity for details.Categories: Health
Eligible applicants: Public housing authorities/Indian housing authorities, For profit organizations other than small businesses, Special district governments, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education, Small businesses, Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education, Others (see text field entitled "Additional Information on Eligibility" for clarification), County governments, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), City or township governments, Independent school districts, Private institutions of higher education, State governments
Description
The overarching goal of this notice of funding opportunity (NOFO) and its companion opportunities is to establish the Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) Program to support development of innovative, reliable, cost-effective, and sustainable multimodal AI-based clinical decision support (CDS) tools. PRIMED-AI CDS tools are based on the integration of clinical imaging with other types of multimodal health data to enhance care for patients with a wide range of health conditions. The PRIMED-AI Program seeks to catalyze the adoption of AI-based CDS tools into clinical workflows to enable novel personalized medicine strategies that address significant health challenges. The purpose of this Notice of Funding Opportunity (NOFO) is to catalyze the development and testing of Artificial Intelligence (AI)-enabled, image-centered, multimodal Clinical Decision Support (CDS) tools, developed in pursuance as Software as a Medical Device (SaMD). These projects are expected to have high potential for demonstrable, positive impact on patient outcomes and/or healthcare processes.