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This is the responsible-AI and governance strand of the NIH Common Fund's PRIMED-AI program, and it is by a wide margin the most accessible of the program's five announcements - two years, up to $300,000 in direct costs per year, roughly five awards, and no requirement to build a clinical tool or assemble an industrial partnership.
What it funds instead is methodological infrastructure: standardized, reusable frameworks that address the recurring problems in multimodal AI clinical decision support, drawn from a defined list of topics including data quality, data harmonization across heterogeneous sources, model transparency, patient privacy, and regulatory navigation.
A specific structural requirement shapes the whole application - proposals must develop and test two or more distinct frameworks on separate topics, so a deep single-topic proposal will not satisfy the announcement.
The word testing carries real weight here as well; NIH is not funding position papers or consensus documents but frameworks that are empirically exercised against realistic multimodal health data and imaging scenarios, so applicants should plan concrete validation work into a compressed two-year timeline.
Because the output is meant to serve the wider PRIMED-AI consortium and eventually the field, teams that combine informatics or AI methods expertise with genuine regulatory, bioethics or data-governance depth are better positioned than pure methods groups. The award mechanism is U01 with clinical trials not allowed, and foreign entities are ineligible.
For research groups interested in trustworthy and responsible health AI but lacking the scale for the program's multi-million dollar center or tool-development awards, this is the natural entry point into PRIMED-AI, and the modest budget makes it realistic for a single well-composed interdisciplinary team.
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Or search similar grants →According to the current listing, eligibility includes: Eligible applicants include higher education institutions, nonprofit organizations with and without 501(c)(3) status, for-profit organizations both small and large, state, local and tribal governments, and faith-based organizations. Foreign entities are not eligible. The award uses the U01 research project cooperative agreement mechanism with clinical trials not allowed. Applications must propose the development and testing of two or more distinct frameworks addressing separate topics selected from the announcement's listed areas, which include data quality, data harmonization, transparency, privacy and regulatory navigation for multimodal AI clinical decision support tools that integrate imaging with complementary health data. Frameworks must be empirically tested, not merely described. Budgets are capped at $300,000 in direct costs per year for a maximum project period of two years. Approximately five awards are anticipated from approximately $2,000,000 committed in FY2027. Applications are due October 9, 2026 by 5:00 PM local time. Confirm the full requirements in the official notice before applying.
The current listing shows applicants may request up to $300,000 in direct costs per year for a maximum project period of two years, giving a maximum award value of approximately $600,000 in direct costs. NIH intends to commit approximately $2,000,000 in FY2027 and anticipates making about five 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-27-011 Development and Testing of a Multi-use Frameworks Playbook for Responsible Multimodal Health AI are due October 9, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
NIH Common Fund PRIMED-AI RFA-RM-27-011 Development and Testing of a Multi-use Frameworks Playbook for Responsible Multimodal Health AI is funded by U.S. National Institutes of Health (NIH) Common Fund, Office of Strategic Coordination, administered by the National Center for Advancing Translational Sciences (NCATS). 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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