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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.
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Or search similar grants →According to the current listing, eligibility includes: Standard NIH eligibility applies, covering United States higher education institutions, non-profit research organisations, for-profit entities including small businesses, hospitals, and state, local and tribal governments, with foreign components permitted only as specified in the full announcement. The realistic applicant is a methodologically strong team in biomedical informatics, imaging science, biostatistics or implementation science that can credibly claim authority to codify practice for a national programme. Substantively, the proposal must both develop and test the framework, which means the review will look for a specific testing design, ideally involving teams or datasets independent of the applicant, rather than a plan to publish a framework paper. Because the playbook is intended for multi-use adoption across the PRIMED-AI consortium, applicants should expect to coordinate with the programme's Validation Center, Logistics Center and tool-development awardees, and should budget co-design and dissemination time accordingly. The two-year, 300,000-dollar-per-year envelope constrains scope sharply: proposals requiring substantial primary data collection, large-scale compute or clinical recruitment are mismatched to this mechanism and should target the Data-to-Model or Model-to-Clinic opportunities instead. Applications are due 9 October 2026 following release on 30 June 2026 and must be submitted through Grants.gov. Prospective applicants should read the full RFA text in the NIH Guide, which governs over any third-party summary, and contact PRIMED-AI programme staff before investing in a full application, since Common Fund programmes are frequently reissued with revised terms. Confirm the full requirements in the official notice before applying.
The current listing shows this opportunity provides up to 300,000 US dollars per year for two years, so amount_min is recorded as 300,000, reflecting the single-year ceiling, and amount_max as 600,000, reflecting the full two-year total. Both figures are ceilings rather than expected awards. This is by a wide margin the smallest of the five PRIMED-AI opportunities, and the scale is a deliberate signal about the nature of the work: the playbook award is a methods and documentation project, not an infrastructure build or a clinical deployment. At 300,000 dollars a year the realistic budget supports a small core team, perhaps one to two full-time equivalents of senior methodological time plus coordination and writing support, and does not support substantial new data collection, large compute procurement or clinical study costs. Applicants proposing to generate new evidence rather than to synthesise and operationalise existing practice into a reusable framework will find the budget cannot carry the plan. The two-year period is short for a consortium-facing deliverable, which means the proposal needs a credible plan for producing a usable artefact early and iterating with other PRIMED-AI awardees rather than back-loading the output. Teams should also weigh that the playbook's value is largely in adoption by the rest of the consortium, so dissemination and co-design effort is a real budget line and not overhead. Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was October 9, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
NIH Common Fund PRIMED-AI Development and Testing of a Multi-use Frameworks Playbook RFA-RM-27-011 for Reusable AI Clinical Decision Support Methodology is funded by U.S. National Institutes of Health (NIH) Common Fund, Office of Strategic Coordination. 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.
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.
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.
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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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