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PRIMED-AI is a new NIH Common Fund programme, Precision Medicine with AI: Integrating Imaging with Multimodal Data, which combines medical imaging with other health data to build AI-powered clinical decision support tools for personalised medicine.
This opportunity, RFA-RM-27-014, funds the programme's Validation Center: a dedicated hub that independently evaluates and characterises the AI-enabled, image-based multimodal clinical decision support tools developed elsewhere in the consortium. The structural logic matters for applicants.
NIH has separated tool-building from tool-validation and is paying separately for the second, which signals institutional recognition that self-reported performance claims from developing teams are not sufficient evidence for clinical AI. The Center's remit covers verification, validation, interoperability and uncertainty quantification, so the deliverable is a reproducible evaluation capability rather than a set of papers.
It operates as a U54 cooperative agreement, meaning NIH staff are substantively involved and the Center must work in concert with the PRIMED-AI Logistics Center and the Data-to-Model and Model-to-Clinic award recipients. The RFA was released on 30 June 2026 with applications due 2 October 2026.
For academic groups that have built credible AI evaluation methodology, particularly in radiology, imaging informatics or biostatistics, this is an unusually direct route to becoming the reference evaluator for a major federal AI health programme, and the position carries influence over how clinical AI performance gets measured well beyond the life of the award.
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Or search similar grants →According to the current listing, eligibility includes: Eligibility follows standard NIH Common Fund rules for U54 specialised centre cooperative agreements. Applicants are expected to be United States research institutions, including public and private institutions of higher education, non-profit research organisations, and in principle for-profit entities, hospitals and government organisations, though a university or academic medical centre with established imaging-informatics and biostatistics capacity is the realistic applicant profile. The substantive requirement is demonstrated capability in independent evaluation of AI models rather than in developing them, which means teams need expertise spanning measurement science, verification and validation methodology, interoperability standards and uncertainty quantification, plus the governance structures to handle other institutions' models and data without conflict of interest. Because this is a cooperative agreement rather than a grant, the successful applicant accepts substantial NIH programmatic involvement and a formal obligation to coordinate with other PRIMED-AI awardees, which is a genuine constraint on scientific autonomy and should be assessed before applying. Clinical trials are not allowed under this award, so proposals built around prospective patient recruitment are mismatched to the mechanism. Applications are due 2 October 2026, following release of the RFA on 30 June 2026, and must be submitted through Grants.gov against the full announcement text, which governs over any summary. A single Validation Center is anticipated. Prospective applicants should read the full RFA at the NIH Guide and confirm current terms with the PRIMED-AI programme staff listed on the Common Fund site, since Common Fund programmes periodically reissue opportunities. Confirm the full requirements in the official notice before applying.
The current listing shows the Validation Center award provides up to 2,000,000 US dollars, and because that figure is published as a single ceiling without a separate floor, amount_min and amount_max are both recorded as 2,000,000. The award is a U54 cooperative agreement, which means NIH programme staff participate substantively in the work rather than simply monitoring it, and applicants should budget for the coordination overhead that implies: regular steering committee participation, data and methods sharing across the PRIMED-AI consortium, and responsiveness to consortium-wide decisions about evaluation protocols. The money is not for developing AI tools. It funds the infrastructure and methodological capacity to independently verify, validate and characterise tools that other PRIMED-AI awardees build, covering verification and validation methodology, interoperability testing, and uncertainty quantification. That makes the realistic cost structure heavily weighted toward staff, biostatistical and measurement-science expertise, and computing for repeated evaluation runs, rather than toward data acquisition or clinical recruitment. Applicants should note that a single Validation Center is anticipated, so this is a winner-take-all competition rather than a pool, and that the 2,000,000 dollar figure should be read against a multi-year project period in which a substantial fraction goes to sustaining an evaluation service for the rest of the consortium. Institutions without an existing track record in AI model evaluation, measurement science or regulatory-grade validation will find the bar high. Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was October 2, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
NIH Common Fund PRIMED-AI Validation Center (U54) RFA-RM-27-014 for Independent Evaluation of AI-Enabled Image-Based Multimodal Clinical Decision Support Tools is funded by U.S. National Institutes of Health (NIH) Common Fund, Office of Strategic Coordination, Division of Program Coordination, Planning and Strategic Initiatives. 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 ONR Long Range Broad Agency Announcement (N00014-25-S-B001) is the Office of Naval Research's primary mechanism for soliciting research proposals across all naval science and technology priority areas. The BAA accepts proposals on a rolling basis through September 30, 2026 and covers ONR's full spectrum of research interests with particular emphasis on AI-related topics including autonomous maritime systems, human-machine teaming, machine learning for sensor fusion, cooperative autonomous swarm technology, undersea autonomy, and AI-enabled decision superiority. Proposals can be funded through multiple mechanisms including individual investigator grants, the Young Investigator Program (~$510K over 3 years for early-career faculty), and Multidisciplinary University Research Initiative (MURI) awards ($1.5M/year for 3-5 years for research teams). ONR recommends contacting relevant program officers before submitting to discuss alignment with current research priorities. The BAA supports basic research (6.1), applied research (6.2), and advanced technology development (6.3) across the full range of naval-relevant science and engineering disciplines.
RFA-RM-27-015 funds a single Logistics Center as the coordinating hub of the NIH Common Fund's PRIMED-AI program, Precision Medicine with AI: Integrating Imaging with Multimodal Data. The award is a cooperative agreement, meaning substantial NIH scientific and programmatic involvement is built in rather than incidental, and it is administered by NIBIB on behalf of the Common Fund. The Center operates through three integrated cores: Administration, which runs the steering committees and develops consortium policies; Evaluation, which assesses progress across the funded portfolio; and Outreach, which maintains a web portal for sharing AI-based clinical decision support tools and facilitates engagement between researchers, clinicians and patient communities. The strategic point for applicants is that this is the only coordinating award in a multi-award program whose other components, the Data-to-Model Academic-Industrial Partnerships, Model-to-Clinic and Multi-use Frameworks Playbook RFAs, are separately competed and separately funded. The Logistics Center therefore does not generate its own AI models; it is scored on its capacity to run a consortium, set data and tool-sharing policy, and build infrastructure that makes other teams' clinical decision support tools discoverable and reusable. Applications are due by 5:00 PM local time of the applicant organization on the date specified for the relevant review cycle, with an earliest project start date of 2 October 2026 and a maximum project period of five years.
RFA-RM-27-011 funds the development and testing of a multi-use frameworks playbook for precision medicine with AI, within the NIH Common Fund's PRIMED-AI programme. Where other PRIMED-AI awards build tools, validate them or move them toward the clinic, this one produces the shared methodology: a reusable framework that other teams can apply when integrating medical imaging with multimodal health data to build AI-based clinical decision support. The premise is that the field repeatedly re-solves the same design problems, and that codifying frameworks for data harmonisation, model development, evaluation and clinical integration is a public good worth funding separately. Funding is up to 300,000 US dollars per year for two years, which makes this the most accessible entry point into a major NIH AI health programme for groups with strong methodological credentials but without the institutional scale to host a centre. Crucially, the deliverable is to be developed and tested, not merely written, so proposals need a concrete validation plan showing the playbook works when applied by teams other than its authors. The RFA was released on 30 June 2026 with applications due 9 October 2026, the second of the five PRIMED-AI deadlines. For informatics methodologists, implementation scientists and groups working on AI reporting and reproducibility standards, this is a rare opportunity in which methodological synthesis is the funded product rather than a byproduct.
NOT-RM-26-004 asks the public for NIH-wide research challenges worth a 10-year, cross-institute program. There is no budget, no biosketch, no page limit, and no award. What there is: the five criteria every Common Fund investment has met since 2006, a new bullet about small-lab burden, and a fund whose FY 2026 request came in at $347.4 million — down 49.3 percent.
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Read articleThe NIH Common Fund launched PRIMED-AI — Precision Medicine with AI: Integrating Imaging with Multimodal Data — as five coordinated funding opportunities (RFA-RM-27-011 through -015) that build a full pipeline from standards to clinic. Here is how the Playbook, Data-to-Model partnerships, Model-to-Clinic translation, Validation Center, and Logistics Center fit together, what each pays, who is eligible, and how to position before the October 2026 deadlines.
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