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D2M-AIP is the discovery-end component of PRIMED-AI, the NIH Common Fund's new Precision Medicine with AI: Integrating Imaging with Multimodal Data program, which the NIH Council of Councils approved as a Common Fund program on April 21, 2025 and which launched five coordinated funding opportunities in 2026.
The specific target here is AI-enabled, image-centered, multimodal clinical decision support tools - systems that fuse clinical imaging with other health data streams such as genomics, pathology, laboratory values and electronic health records - developed explicitly as Software as a Medical Device. Two features distinguish this announcement from ordinary NIH AI funding.
First, the academic-industrial partnership requirement is structural rather than decorative: projects are meant to be pre-competitive collaborations positioned for eventual commercialization, so a purely academic team without an industry partner is unlikely to be competitive.
Second, the phased UG3/UH3 mechanism means the award is gated - the UG3 phase (up to $450,000 direct costs per year) funds development against defined milestones, and transition to the UH3 phase (up to $800,000 direct costs per year) depends on meeting them. Applicants should write the milestone plan as a first-class part of the proposal rather than an afterthought.
The emphasis on novel data integration and new AI model development means incremental applications of existing architectures to a new dataset will read poorly; reviewers are looking for methodological advance paired with a credible regulatory and deployment path.
Eligibility is broad, including foreign organizations, which is unusual among the five PRIMED-AI announcements - the Validation Center, Logistics Center and Playbook opportunities all exclude foreign entities. Teams whose tool is already a validated prototype rather than a concept should look instead at the companion Model-to-Clinic announcement, RFA-RM-27-013, which shares this deadline.
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Or search similar grants →According to the current listing, eligibility includes: Eligible applicants include higher education institutions (public and private), nonprofit organizations with and without 501(c)(3) status, small businesses, for-profit organizations, local, state and federal governments, Indian/Native American tribal governments and organizations, faith-based and community-based organizations, and foreign organizations - the broadest eligibility among the five PRIMED-AI announcements. Projects must develop AI-enabled, image-centered, multimodal clinical decision support tools as Software as a Medical Device, integrating clinical imaging with other health data, and must be structured as pre-competitive academic-industrial partnerships positioned for future commercialization. Applications must emphasize novel data integration and/or new AI model development. The award uses a phased UG3/UH3 cooperative agreement structure with milestone-gated transition between phases; the total project period may not exceed five years. The opportunity opens September 19, 2026 with applications due October 19, 2026, and additional review cycles follow in March 2027, May 2027 and July 2027. Confirm the full requirements in the official notice before applying.
The current listing shows applicants may request up to $450,000 in direct costs per year during the UG3 phase and up to $800,000 in direct costs per year during the UH3 phase, over a total project period not exceeding five years. That implies a typical full award value on the order of $3,000,000 to $3,500,000 in direct costs across both phases. The NIH Common Fund intends to fund approximately 6 to 8 UG3/UH3 awards under this announcement. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for NIH Common Fund PRIMED-AI RFA-RM-27-012 Data-to-Model Academic-Industrial Partnerships (D2M-AIP) for AI-Enabled Multimodal Clinical Decision Support are due October 19, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
NIH Common Fund PRIMED-AI RFA-RM-27-012 Data-to-Model Academic-Industrial Partnerships (D2M-AIP) for AI-Enabled Multimodal Clinical Decision Support is funded by U.S. National Institutes of Health (NIH) Common Fund, Office of Strategic Coordination, administered by the National Cancer Institute (NCI). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The FY2026 Department of Defense Multidisciplinary University Research Initiative (MURI) program supports basic research in science and engineering at U.S. institutions of higher education, with emphasis on multidisciplinary research where more than one traditional discipline interacts. The Army, Navy, and Air Force basic research offices are seeking applications across 22 topic areas including artificial intelligence and autonomy, information sensing and processing, and systems manipulation. MURI grants typically provide $1.25 million to $1.5 million per year for three years with option to extend two additional years. Approximately $170 million in total funding is available annually across all topics. The program is administered through the Office of Naval Research (ONR), Army Research Office (ARO), and Air Force Office of Scientific Research (AFOSR).
The NSF Convergence Accelerator is a grant from the National Science Foundation (NSF) that funds multidisciplinary teams working to solve national-scale societal challenges through convergence research and innovation. Launched in 2019 under NSF's Directorate for Technology, Innovation and Partnerships, the program operates in two phases: Phase 1 awards are up to $750,000, with successful teams advancing to larger Phase 2 awards. Eligible applicants include institutions of higher education and nonprofit or for-profit organizations. Track I and Track K focus on specific high-priority topics announced each funding cycle. The next deadline is June 15, 2026. Proposals must comply with updated NSF research security policies effective July 2025.
The AI3 Action Institute is a federal effort to build dedicated AI capacity within Native communities rather than fund a single applied AI project. The awardee establishes and operates an AI resource hub for Native communities, providing technology information, facilitating information sharing and technology deployment across tribal and Native-serving organizations, and conducting stakeholder engagement and coalition building across industry, government and academic sectors. Notably, allowable costs cover short-to-medium-term staff costs including the Institute's director as well as facility setup - a recognition that the binding constraint in this space is institutional infrastructure and staffing, not project ideas. The financial structure is the detail that most shapes strategy: with a $2,500,000 floor, a $3,500,000 ceiling and $3,500,000 in total expected program funding across a three-year period, this is effectively a single-award competition, so applicants should assume they are competing for the entire program rather than for a slot in a cohort. Eligibility is restricted to Native-serving entities - federally recognized Indian tribes, incorporated non-federally or state-recognized tribes, consortia of Indian tribes, Native community-based organizations, Urban Indian Organizations, Alaska Native villages and entities, Native Hawaiian serving agencies, Native Pacific Islander serving agencies, and tribal colleges and universities. That eligibility list is broader than many ACF opportunities, extending to Native Hawaiian and Pacific Islander serving agencies as well as tribal entities. Applicants should expect the strongest proposals to combine an existing convening role in Native technology or education with a realistic plan for standing up durable staff capacity within the grant period, since a hub that dissolves when funding ends would not serve the program's purpose. The deadline is August 27, 2026, and applications are submitted through Grants.gov under opportunity number 362270.
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