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D2M-AIP is the discovery-end component of PRIMED-AI, the NIH Common Fund's new Precision Medicine with AI: Integrating Imaging with Multimodal Data program, which the NIH Council of Councils approved as a Common Fund program on April 21, 2025 and which launched five coordinated funding opportunities in 2026.
The specific target here is AI-enabled, image-centered, multimodal clinical decision support tools - systems that fuse clinical imaging with other health data streams such as genomics, pathology, laboratory values and electronic health records - developed explicitly as Software as a Medical Device. Two features distinguish this announcement from ordinary NIH AI funding.
First, the academic-industrial partnership requirement is structural rather than decorative: projects are meant to be pre-competitive collaborations positioned for eventual commercialization, so a purely academic team without an industry partner is unlikely to be competitive.
Second, the phased UG3/UH3 mechanism means the award is gated - the UG3 phase (up to $450,000 direct costs per year) funds development against defined milestones, and transition to the UH3 phase (up to $800,000 direct costs per year) depends on meeting them. Applicants should write the milestone plan as a first-class part of the proposal rather than an afterthought.
The emphasis on novel data integration and new AI model development means incremental applications of existing architectures to a new dataset will read poorly; reviewers are looking for methodological advance paired with a credible regulatory and deployment path.
Eligibility is broad, including foreign organizations, which is unusual among the five PRIMED-AI announcements - the Validation Center, Logistics Center and Playbook opportunities all exclude foreign entities. Teams whose tool is already a validated prototype rather than a concept should look instead at the companion Model-to-Clinic announcement, RFA-RM-27-013, which shares this deadline.
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Or search similar grants →According to the current listing, eligibility includes: Eligible applicants include higher education institutions (public and private), nonprofit organizations with and without 501(c)(3) status, small businesses, for-profit organizations, local, state and federal governments, Indian/Native American tribal governments and organizations, faith-based and community-based organizations, and foreign organizations - the broadest eligibility among the five PRIMED-AI announcements. Projects must develop AI-enabled, image-centered, multimodal clinical decision support tools as Software as a Medical Device, integrating clinical imaging with other health data, and must be structured as pre-competitive academic-industrial partnerships positioned for future commercialization. Applications must emphasize novel data integration and/or new AI model development. The award uses a phased UG3/UH3 cooperative agreement structure with milestone-gated transition between phases; the total project period may not exceed five years. The opportunity opens September 19, 2026 with applications due October 19, 2026, and additional review cycles follow in March 2027, May 2027 and July 2027. Confirm the full requirements in the official notice before applying.
The current listing shows applicants may request up to $450,000 in direct costs per year during the UG3 phase and up to $800,000 in direct costs per year during the UH3 phase, over a total project period not exceeding five years. That implies a typical full award value on the order of $3,000,000 to $3,500,000 in direct costs across both phases. The NIH Common Fund intends to fund approximately 6 to 8 UG3/UH3 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-27-012 Data-to-Model Academic-Industrial Partnerships (D2M-AIP) for AI-Enabled Multimodal Clinical Decision Support 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 RFA-RM-27-012 Data-to-Model Academic-Industrial Partnerships (D2M-AIP) for AI-Enabled Multimodal Clinical Decision Support is funded by U.S. National Institutes of Health (NIH) Common Fund, Office of Strategic Coordination, administered by the National Cancer Institute (NCI). 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.
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.
Read articleNIH's FY2026 omnibus adds a Phase IIB Strategic Breakthrough Award up to $30M — but it requires a 100% outside match. Here's who it's for and how to plan.
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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