The National Institutes of Health (NIH) is expanding its investment in artificial intelligence, seeking applicants to coordinate a new nationwide research network designed to accelerate the development, evaluation and adoption of AI-powered clinical decision support tools. The move signals a broader federal push to integrate AI into precision medicine and clinical research.
The funding opportunity is one of five that the NIH’s Common Fund released June 30. Together they officially launch a new program, dubbed Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI). Applications for the first of the five opportunities are due Oct. 2.
The program is built around clinical decision support (CDS) tools, which the NIH describes as software systems built into clinical workflows to help determine a course of action in patient care.
According to the NIH, clinical imaging drives diagnosis and treatment, but developers building AI-based support tools have generally worked with imaging in isolation, not incorporating other kinds of patient data. Most tools built so far, the agency says, work from just one kind of image, usually a radiology scan or an eye scan.
Officials note that because health reflects a mix of clinical, biological, genetic, environmental and social factors, the program will pair imaging with complementary data, including electronic health records, laboratory results, wearable sensor data and medical reports. The NIH describes imaging as the anchor for that combination and the foundation on which the AI models will get built and tested.
The agency split the five program opportunities in this round across the stages that a tool has to clear before it eventually reaches patients, with the coordination role arriving last. Two of the opportunities fund the building of the tools themselves, with one supporting academic and industry teams working together at what the NIH calls the pre-competitive stage, where about eight awards are expected. The other backs projects that take validated prototypes and push them toward clinical use.
Evaluation runs alongside that work. The third opportunity would establish a center to independently verify and evaluate what the program produces. The fourth would fund projects developing standardized processes for responsible model use, error mitigation and preparation for regulatory approval.
The fifth opportunity is the main coordination role, sitting at the far end of the sequence. The recipient would handle governance and outreach, build the public portal where the program’s tools are published and work to encourage clinical AI adoption among healthcare and AI organizations. The NIH also wants outside input included in the process via an external advisory group and a community review board, giving patients, clinicians and software developers a say in the program’s direction.
The NIH developed the program through a landscape analysis, a public request for information and a planning workshop, then approved PRIMED-AI as a Common Fund program in April 2025. The approval came months before the federal government launched a major governmentwide AI research initiative.
Two of the five program opportunities ask recipients to coordinate with these other federal AI infrastructure efforts, with both naming the Genesis Mission as an example. That initiative, launched by executive order in November 2025 and led by the Department of Energy (DOE), is a national effort to apply AI to scientific research. It is built around a shared platform that would connect federal researchers to data, computing power and AI tools. The White House said July 22 that more than $5 billion in federal commitments would expand the mission, with more than 15 federal agencies participating.
The NIH has its own role in that initiative, through an effort called the Bio Genesis Mission that targets areas including the root causes of chronic disease, pediatric cancer and drug discovery. It sits apart from the PRIMED-AI program, though NIH Director Jay Bhattacharya said more than $1.2 billion in already obligated fiscal 2026 funding and planned fiscal 2027 funding across the agency lines up with those research areas.
Organizations that will not submit their own application may still find a way in. The NIH has set aside part of the coordination award for collaborations and requires that most of that money go to organizations other than the award recipient itself. The American College of Radiology, for example, has already said it wants to work with potential applicants and directed interested organizations to its Center for Research and Innovation.
Deadlines run through Oct. 19 across the five opportunities, with the coordination award expected as early as July 2027. According to officials, the NIH will stay involved after the awards have been distributed, including rendering final determination on whether recipients meet milestones.
The NIH has also posted informational webinars and scheduled live question-and-answer sessions with program staff. More federal AI funding is expected in the meantime, with Bhattacharya saying additional opportunities tied to the Bio Genesis Mission would follow.
Photo by Parentingupstream from Pixabay
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