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PRIMED-AI is a new NIH Common Fund program that pairs medical imaging with other modalities of health data to build AI-powered clinical decision support tools for precision medicine, and the Data-to-Model Academic-Industrial Partnerships (D2M-AIP) component is its data-and-model engine.
Issued as RFA-RM-27-012 under a UG3/UH3 phased cooperative agreement, it funds multidisciplinary academic-industrial teams to take a defined clinical problem, assemble or harmonise the multimodal data needed to address it, and produce a validated AI model intended to function as a software-based medical device.
The distinguishing feature relative to ordinary NIH AI grants is the mandatory industrial partnership: NIH is explicit that the translational path from a research model to a regulated clinical tool runs through companies that can carry regulatory submission, deployment and post-market surveillance, and applications without a substantive industry partner are not what this mechanism is for.
The UG3 phase establishes the data foundation and demonstrates technical feasibility; the UH3 phase, gated on milestone achievement and NIH approval, carries the model toward clinical implementation and prospective validation. Approximately six to eight awards are expected.
PRIMED-AI as a whole launched five coordinated funding opportunities in July 2026 covering data-to-model partnerships, model-to-clinic translation, a validation centre, a logistics centre and a multi-use frameworks playbook, and applicants should read D2M-AIP alongside the Model-to-Clinic announcement (RFA-RM-27-013) to pick the right entry point: D2M-AIP is for teams that still need to build the model, while Model-to-Clinic is for teams that already have a validated prototype.
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Or search similar grants →According to the current listing, eligibility includes: Eligibility is broad by NIH standards. Applications are accepted from public and private institutions of higher education, non-profit organisations other than institutions of higher education, for-profit organisations including small businesses, state and local governments, Native American tribal organisations, and other eligible agencies of the federal government. Non-domestic (non-U.S.) entities, that is foreign organisations, are eligible to apply, and foreign components of U.S. organisations are allowed, which is unusual for a Common Fund translational program and opens the mechanism to international consortia. The funding instrument is a cooperative agreement, meaning NIH program staff participate substantively in the conduct of the project, and applicants who prefer investigator-driven autonomy should understand that this is a managed-team mechanism with required participation in PRIMED-AI consortium activities, data-sharing commitments and interaction with the program's separately funded Validation and Logistics Centers. No cost sharing is required. There is no letter of intent requirement for the related Model-to-Clinic announcement and applicants should check the D2M-AIP announcement for its own letter of intent expectations. The critical substantive eligibility consideration is the academic-industrial partnership structure: teams must document a genuine industry collaborator with the capability to pursue regulatory authorisation and clinical deployment, not a letter of support. Applications are due 19 October 2026. Transition from the UG3 to the UH3 phase requires achievement of negotiated milestones and NIH approval and is not guaranteed. Confirm the full requirements in the official notice before applying.
The current listing shows applicants may request a budget appropriate to the proposed scope of work but may not exceed 450,000 US dollars in direct costs per year during the UG3 phase and 800,000 US dollars in direct costs per year during the UH3 phase, so amount_min is recorded as 450,000 and amount_max as 800,000 US dollars on a per-year direct-cost basis. The practical envelope is considerably larger than either single figure because the combined UG3 plus UH3 project period may run up to five years: a team that moves through a two-year UG3 and a three-year UH3 can draw roughly 3.3 million US dollars in direct costs across the award, before facilities and administrative costs are layered on top, and the full-cost total will therefore commonly land in the five to six million dollar range at a typical academic indirect rate. The NIH Common Fund intends to make approximately six to eight UG3/UH3 awards under this announcement, which makes the competition unusually concentrated for a Common Fund mechanism and means that a budget request close to the ceiling is normal rather than aggressive. The structure matters for planning: the UG3 phase ceiling is low relative to the cost of assembling multimodal imaging cohorts, so applicants should treat UG3 as the data-partnership and feasibility stage and reserve the model-training and prospective-evaluation costs for the better-funded UH3 phase. Transition between phases is not automatic; it depends on meeting pre-specified UG3 milestones and on NIH administrative review, so the 800,000 dollar annual figure should be treated as contingent rather than committed at the point of award. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for NIH Common Fund PRIMED-AI Data-to-Model Academic-Industrial Partnerships (D2M-AIP) for Precision Medicine with AI Integrating Imaging with Multimodal Data (RFA-RM-27-012, UG3/UH3) 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 Data-to-Model Academic-Industrial Partnerships (D2M-AIP) for Precision Medicine with AI Integrating Imaging with Multimodal Data (RFA-RM-27-012, UG3/UH3) is funded by U.S. National Institutes of Health (NIH), Common Fund, Office of the Director, Precision Medicine with AI (PRIMED-AI) Program. 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.
The 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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