About this file

This is a Request for Application (RFA) announcement for the Precision Medicine with Artificial Intelligence - Integrating Imaging with Multimodal Data (PRIMED-AI) program, issued by the National Institutes of Health (NIH) Common Fund in partnership with other NIH Institutes and Centers. The program seeks to develop innovative, reliable, cost-effective AI-based clinical decision support (CDS) tools that integrate clinical imaging with multimodal health data to enhance personalized medicine for patients with chronic and other health conditions. The funding mechanism is a Cooperative Agreement using the UG3/UH3 activity code under the Trans-NIH Research Support program (CFDA 93.310). Applications will be evaluated for scientific and technical merit through peer review, with funding decisions based on significance, approach, innovation, investigator competency, and resource adequacy. The program operates on a biphasic model: Phase 1 (UG3) focuses on rigorous AI model building through retrospective analysis and testing of large, interoperable multimodal datasets, while Phase 2 (UH3) advances promising projects to evaluate real-world clinical utility of the AI-driven CDS tool in actual clinical workflows.

Eligible applicants include domestic and foreign public or nonprofit organizations, universities, hospitals, research institutions, and for-profit entities. Recent awards under Trans-NIH Research Support have ranged from approximately $25,000 to $8.0 million in total obligated costs, with project durations typically spanning 2-5 years. Most awards are made to higher education institutions and nonprofit research organizations. Grantees must maintain financial and programmatic records for three years from the date of the annual Financial Status Report submission. The review cycle typically takes four to nine months. Projects must address unmet health challenges with high potential for demonstrable, positive impact on patient outcomes or healthcare processes, with particular emphasis on investigators with expertise in analysis and testing of large, interoperable multimodal datasets.

RFA-RM-27-013-Full-Announcement.html

Text of this file

Department of Health and Human Services

Part 1. Overview Information

Participating Organization(s)

National Institutes of Health (NIH)

Components of Participating Organizations

Office of Strategic Coordination (Common Fund)

This Notice of Funding (NOFO) is developed as a Common Fund initiative (https://commonfund.nih.gov/) through the Office of the NIH Director, Office of Strategic Coordination (https://commonfund.nih.gov/). All NIH Institutes and Centers participate in Common Fund initiatives. The NOFO will be administered by the National Institute of Mental Health on behalf of the NIH.

Note: Not all NIH Institutes, Centers, and Offices (ICOs) participate in Announcements. Applicants should carefully note which ICOs participate in this announcement and view their respective areas of research interest at the ICO-Specific Scientific Interests website. ICOs that do not participate in this announcement will not consider applications for funding.

Funding Opportunity Title

Model-to-Clinic (M2C) for Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) (UG3/UH3, Clinical Trial Optional)

Activity Code

UG3/UH3 Exploratory/Developmental Phased Award Cooperative Agreement

Announcement Type

New

Related Notices

Check for any recent Notices of NIH Policy Changes that may impact application requirements.

Funding Opportunity Number (FON)

RFA-RM-27-013

Companion Funding Opportunity

RFA-RM-27-011

, U01 Research Project (Cooperative Agreements)

RFA-RM-27-012

UG3/

UH3

Phase 1 Exploratory/Developmental Cooperative Agreement/Exploratory/Developmental Cooperative Agreement Phase II

RFA-RM-27-014

, U54 Specialized Center (Cooperative Agreements)

RFA-RM-27-015

, U24 Resource-Related Research Project (Cooperative Agreements)

Number of Applications

See Part 2, Section III. 3. Additional Information on Eligibility.

Assistance Listing Number(s)

93.310

Funding Opportunity Purpose

The overarching goal of this notice of funding opportunity (NOFO) and its companion opportunities is to establish the Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) Program to support development of innovative, reliable, cost-effective, and sustainable multimodal AI-based clinical decision support (CDS) tools. PRIMED-AI CDS tools are based on the integration of clinical imaging with other types of multimodal health data to enhance care for patients with a wide range of health conditions. The PRIMED-AI Program seeks to catalyze the adoption of AI-based CDS tools into clinical workflows to enable novel personalized medicine strategies that address significant health challenges.

The purpose of this NOFO is to catalyze the translation of Artificial Intelligence (AI)-enabled, image-centered, multimodal CDS tools, developed as Software as a Medical Device, from training and testing of prototypes towards clinical applications that address unmet health challenges in precision medicine. These projects are expected to have high potential for demonstrable, positive impact on patient outcomes and/or healthcare processes.

Funding Opportunity Goal(s)

The Office of Strategic Coordination (Common Fund) supports research and other projects that will accelerate fundamental biomedical discovery and translation of that knowledge into effective prevention strategies and new treatments.

Key Dates

Posted Date

June 30, 2026

Open Date (Earliest Submission Date)

September 19, 2026

Application Due Dates
Review and Award Cycles
New
Renewal / Resubmission / Revision (as allowed)
AIDS - New/Renewal/Resubmission/Revision, as allowed
Scientific Merit Review
Advisory Council Review
Earliest Start Date

October 19, 2026

Not Applicable

Not Applicable

March 2027
May 2027

July 2027

All applications are due by 5:00 PM local time of applicant organization.

Applicants are encouraged to apply early to allow adequate time to make any corrections to errors found in the application during the submission process by the due date.

No late applications will be accepted for this Notice of Funding Opportunity (NOFO).

Due Dates for E.O. 12372

Not Applicable

Expiration Date

October 20, 2026

Required Application Instructions

It is critical that applicants follow the instructions in the Research (R) Instructions in the How to Apply - Application Guide, except where instructed to do otherwise (in this NOFO or in a Notice from NIH Guide for Grants and Contracts).

Conformance to all requirements (both in the Application Guide and the NOFO) is required and strictly enforced. Applicants must read and follow all application instructions in the Application Guide as well as any program-specific instructions noted in Section IV. When the program-specific instructions deviate from those in the Application Guide, follow the program-specific instructions.

Applications that do not comply with these instructions may be delayed or not accepted for review.

There are several options available to submit your application through Grants.gov to NIH and Department of Health and Human Services partners. You must use one of these submission options to access the application forms for this opportunity.
Use the NIH ASSIST system to prepare, submit and track your application online.
Use an institutional system-to-system (S2S) solution to prepare and submit your application to Grants.gov and eRA Commons to track your application. Check with your institutional officials regarding availability.
Use Grants.gov Workspace to prepare and submit your application and eRA Commons to track your application.

Table of Contents

Part 1. Overview Information Key Dates Part 2. Full Text of Announcement Section I. Notice of Funding Opportunity Description Section II. Award Information Section III. Eligibility Information Section IV. Application and Submission Information Section V. Application Review Information Section VI. Award Administration Information Section VII. Agency Contacts Section VIII. Other Information

Part 2. Full Text of Announcement

Section I. Notice of Funding Opportunity Description

Purpose The Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) NOFOs seek to spur on the development of innovative, reliable, cost-effective, and sustainable multimodal AI-based clinical decision support (CDS) tools with the potential for transformational impact. Overall, the PRIMED-AI Program catalyzes the integration of clinical imaging with other types of multimodal health data that informs CDS tool development and testing in clinical workflows, which serves to enhance patient care for a wide range of health conditions.

The Model-to-Clinic (M2C) NOFO uniquely seeks projects that take CDS tools developed as Software as a Medical Device (SaMD), from validated prototypes to clinical applications.

M2C projects are structured as phased innovation awards (UG3/UH3) designed to advance multimodal AI-based CDS tools through progressive stages of development and validation.

UG3 Phase (Exploratory/Developmental): This initial phase focuses on establishing the technical and operational foundation for clinical translation. Projects will develop and refine AI models, regulatory preparations, clinical implementation infrastructure, deployment strategies, and demonstrate preliminary feasibility in target clinical settings. Milestones must be achieved before transitioning to the UH3 phase.

UH3 Phase (Advanced Development): Following successful completion of the UG3 phase, the UH3 phase emphasizes CDS model clinical implementation and validation. Projects will deploy CDS tools in clinical workflows; conduct prospective clinical studies to evaluate performance; demonstrate potential for impact and integration with existing health IT systems; and generate evidence for broader adoption and sustainability. Projects must demonstrate measurable potential for clinical impact and pathway(s) to sustained use beyond the award period.

The combined UG3/UH3 award period cannot exceed 5 years total. Transition from UG3 to UH3 requires achieving specified milestones and NIH approval.

M2C projects are expected to have high potential for demonstrable, positive impact on patient outcomes and/or healthcare processes.

Key Terms used in PRIMED-AI Program

Clinical decision support (CDS) tool. A type of software, computational model or digital system that is incorporated into clinical workflows to assist in determining a course of action related to patient care.
Clinical imaging. Any FDA-approved imaging modality used in patient care, including radiologic (e.g., radiographic, computed tomographic, magnetic resonance, molecular, radionuclide imaging), ophthalmologic (e.g., Optical Coherence Tomography), endoscopic, and dermatologic imaging, and video. Clinical imaging of human participants is intended to be the anchor data type that multimodal data are integrated with in the PRIMED-AI Program, which will form the basis for AI algorithm development and testing of CDS tools.
DICOM standard. Digital Imaging and Communications in Medicine (DICOM) standard, the most widely used by the community to address interoperability challenge, is strongly encouraged but not required. Inclusion of non-DICOM standard clinical imaging must include a plan to develop standards in conjunction with the PRIMED-AI community if none currently exist.
Harmonization. The process of bringing together data from different sources and ensuring that it is consistent, comparable, and compatible. This involves standardizing data formats, structures, and definitions so that data from various sources can be integrated and analyzed together effectively.
Interoperability. The ability for AI models and associated data and metadata to be understood and work across different AI platforms and have the potential to be used consistently across different health systems.
Multimodal data (MMD). Representing different types of data and information from multiple sources that may include multiple clinical imaging modalities and non-imaging health data (e.g., electronic health records, EEG, EKG, laboratory test results (-omics), wearable sensor data, medical reports). Multiscale data are encouraged; however, microscopy-based imaging of biospecimens ex vivo (e.g., digital pathology) cannot represent the sole imaging data type. Although non-human imaging and/or MMD data may have assisted in development of an AI-model, overt representation and reliance on data derived from non-human sources for CDS tool development, testing, and validation will be given low programmatic priority.
Playbook. A collection of actionable guidelines, standardized protocols, and/or standardized operating procedures for the reliable and effective development and deployment of multimodal clinical decision support tools. The Playbook is a collection of frameworks.
Precision Medicine. Sometimes called personalized medicine or individualized medicine, refers to a healthcare approach that uses information based on a patient's individual characteristics such as health measures, genotype, phenotype, environment, and lifestyle information to guide, tailor, and optimize decisions related to their medical care and management.
PRIMED-AI Consortium. The consortium constitutes members of PRIMED-AI excluding NIH program staff. PRIMED-AI Program is an umbrella term encompassing the consortium, NIH staff, and overall programmatic objectives.
Uncertainty Quantification.Measuring or quantifying the impact of uncertainties in complex systems, including quantifying the confidence in outcomes predicted by multimodal AI models.
Validation. Validation exists on a continuum in the PRIMED-AI Program. Analytical or technical validation is based on the evaluation of algorithmic performance and the ability of a multimodal AI model to make accurate predictions. Initially, a model or algorithm can meet expected performance on retrospective and/or entirely new clinical datasets within the confines of a specific hospital or healthcare system. It is useful locally (internally) but is not yet applicable (generalizable) to the wider real-world population. Subsequently, for clinical validation, a model or algorithm can be tested (externally) on new wider real-world population datasets to predict a meaningful outcome and meet regulatory criteria for the claimed use case. The PRIMED-AI Program anticipates validation of projects along this continuum as outlined in the NOFOs.
Verification. The process by which data integrity and construction of models is assessed for appropriateness within the context of use or intended purpose.

Background Clinical imaging plays a pivotal role in diagnosis, treatment, and assessment of health outcomes; however, it is often utilized in isolation from other types of data during the development of artificial intelligence (AI)-based clinical decision support (CDS) tools. Current AI applications typically leverage a single imaging modality from radiological or ophthalmological sources. Because health is shaped by a variety of interconnected factors–clinical, biological, genetic, environmental and social–the Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) Program seeks to integrate clinical imaging with relevant, complementary multimodal data (MMD). The overarching goal of the PRIMED-AI Program is to catalyze the development and adoption of innovative AI-based CDS tools into clinical workflows. The PRIMED-AI Program initiatives collectively aim to tackle complex clinical challenges by fostering cross-disciplinary collaboration to create innovative, reliable, cost-effective, and sustainable AI solutions that enable precision medicine strategies.

Prior to applying, applicants are encouraged to check the PRIMED-AI Program website for updates to relevant FAQs and informational webinars, and are also encouraged to read all companion NOFOs to ensure they are aware of the goals and responsibilities of all PRIMED-AI award recipients, including methods PRIMED-AI intends to utilize to address error mitigation and technical management. Familiarity with the companion NOFOs may better inform proposed M2C interconnections with other aspects of the PRIMED-AI Program.

M2C CDS tools aim to enhance diagnostic accuracy, optimize treatment, improve prognostic prediction, and streamline workflows for clinical decision-making through processing and integration of complex, multimodal data streams to ultimately improve patient outcomes and/or lower patient care costs. This initiative and its companion Data-to-Model Academic-Industrial Partnership (D2M-AIP) directly address a critical translational gap in AI research–the gap between promising AI prototypes developed in controlled research environments and robustly validated, clinically deployable CDS tools that function reliably in real-world healthcare settings. For the purpose of these NOFOs, applicants must demonstrate sufficient access to verified, comprehensive, and complex multimodal datasets as well as integration and harmonization of these data to address a target clinical application. Applicants to the M2C must have a technically validated AI prototype, defined as a model that has undergone technical validation at a minimum of a single site, or unimodally, or in retrospective data, or distinctly validated model types that need to be integrated (e.g., hybrid models that combine different types of data or logic such as machine learning-based with rule-based, or logic-based, neuromorphic based, or dynamical system theories).

During the PRIMED-AI project period, M2C projects must perform comprehensive technical and clinical validation, beyond single-site studies to ensure broad clinical applicability. Ultimately, the M2C NOFO aims to deliver a set of valuable and effective CDS tools able to perform appropriately in real-world clinical settings within a precision medicine framework.

The value of any CDS tool developed under this program is contingent upon its relevance, reliability, and broad clinical adoption to improve patient care and reduce patient care costs.

Distinction Between Model-to-Clinic (M2C) and Data-to-Model Academic Industrial Partnerships (D2M-AIP) NOFOs The PRIMED-AI Program includes two parallel NOFOs designed with distinct primary foci along the data-to-model-to-clinic continuum. To help applicants select the appropriate funding opportunity, the essential differences are summarized here:

M2C projects primarily focus on assessing clinical adoption and impact by translating a promising AI model(s) into a clinical workflow as CDS tools. M2C projects must conduct clinical validation studies to evaluate real-world utility for adoption in clinical care. M2C projects begin with a promising AI model and aim to assess and validate its clinical performance, utility, and impact in real-world healthcare settings. They should also address challenges related to adopting AI-assisted CDS tools in clinical workflows, including associated costs and feasibility.
D2M-AIP projects aim towards commercialization and are led by an academic-industrial partnership that primarily focuses on novel data integration and/or new AI model development. Projects proposed under D2M-AIP exist in the pre-competitive space and will emphasize technical validation and performance testing, without requiring clinical validation studies within the award period. The goal is to develop and de-risk novel AI technologies through collaboration, preparing them for future commercialization, adoption, and use of a CDS tool(s).

Key Requirements M2C projects supported by this NOFO will involve two distinct, milestone-driven phases of innovation research and development. In the UG3 phase, M2C award recipients will make the CDS tools deployable and generalizable across multiple sites, integrating comprehensive, large-scale, clinical imaging and multimodal datasets. In the UH3 phase, applicants apply these tools in the clinical setting with the potential for transformative impact on real-world challenges in precision medicine. Applications must be built upon the following five pillars (further specified in Section IV):

Data Quality and Governance for Model Development
Clinically Grounded AI Technology
Pathway to Implementation and Adoption
Integrated Multidisciplinary Team
Error Mitigation and Technical Management

Applications Not Responsive to this NOFO.

To be considered responsive, applications must align with the central goal of the PRIMED-AI Program.

The following types of applications will be considered non-responsive and will not be reviewed:

Projects primarily focused on basic research in AI/ML methodology without a clear and significant translational goal towards a specific clinical problem.
Projects that do not focus on the translation of a CDS tool that uses clinical imaging as the anchor data type, integrated with other multimodal data. Clinical imaging must be the modality that anchors the model. Digital pathology cannot represent the imaging anchor data type but may serve as a form of multimodal data. Projects where the primary focus is on a mechanistic biological research question and the AI technology and methods are already well-established, adapted, optimized, and validated for that context of use.
Applications proposing Phase III clinical trials as the primary scope of work. (Note: While this NOFO is "Clinical Trial Optional," large-scale, confirmatory Phase III trials are outside the scope).
Projects that do not define a targeted unmet clinical problem (intended use) on a clinical population (intended users) for the proposed CDS tool.
Projects without an existing prototype of an AI-powered, image-centered, multimodal CDS tool.

Investigators proposing NIH-defined clinical trials may refer to the Research Methods Resources website for information about developing statistical methods and study designs.

See Section VIII. Other Information for award authorities and regulations.

Section II. Award Information

Funding Instrument

Cooperative Agreement: A financial assistance mechanism used when there will be substantial Federal scientific or programmatic involvement. Substantial involvement means that, after award, NIH scientific or program staff will assist, guide, coordinate, or participate in project activities. See Section VI.2 for additional information about the substantial involvement for this NOFO.

Application Types Allowed

New

The OER Glossary and the How to Apply Application Guide provide details on these application types. Only those application types listed here are allowed for this NOFO.

Clinical Trial?

Optional: Accepting applications that either propose or do not propose clinical trial(s).

Need help determining whether you are doing a clinical trial?

Funds Available and Anticipated Number of Awards

The NIH Common Fund intends to commit funds for approximately 6-8 UG3/UH3 awards. The number of awards is contingent upon NIH appropriations and the submission of a sufficient number of meritorious applications.

Award Budget

Applicants should request a budget appropriate for the proposed scope of work, not to exceed $450,000 in direct costs per year for UG3 and $1,000,000 in direct costs for UH3 phases.

Award Project Period

The total project period for a UG3/UH3 award may not exceed 5 years.

NIH grants policies as described in the NIH Grants Policy Statement will apply to the applications submitted and awards made from this NOFO.

Section III. Eligibility Information

1. Eligible Applicants

Eligible Organizations

Higher Education Institutions - Includes all types
Public/State Controlled Institutions of Higher Education
Private Institutions of Higher Education

Nonprofits Other Than Institutions of Higher Education

Nonprofits with 501(c)(3) IRS Status (Other than Institutions of Higher Education)
Nonprofits without 501(c)(3) IRS Status (Other than Institutions of Higher Education)

For-Profit Organizations

Small Businesses
For-Profit Organizations (Other than Small Businesses)

Local Governments

State Governments
County Governments
City or Township Governments
Special District Governments
Indian/Native American Tribal Governments (Federally Recognized)
Indian/Native American Tribal Governments (Other than Federally Recognized).
Federal Governments
U.S. Federal Government Agencies (e.g., NIH Intramural Research Program, DOE National Laboratories) may participate as partners but are not eligible to apply as the primary applicant institution
U.S. Territory or Possession

Other

Independent School Districts

Public Housing Authorities/Indian Housing Authorities

Native American Tribal Organizations (other than Federally recognized tribal governments)

Faith-based or Community-based Organizations

Regional Organizations

Non-domestic (non-U.S.) Entities (Foreign Organizations)

Foreign Organizations/International Collaborations

Non-domestic (non-U.S.) Entities (Foreign Organizations) are eligible to apply.

Non-domestic (non-U.S.) components of U.S. Organizations are eligible to apply.

Foreign components, as defined in the NIH Grants Policy Statement, are allowed.

NIH will no longer issue awards (i.e., new, renewal, or non-competing continuation) to domestic or foreign entities that involve foreign subawards/subcontracts. All NIH-funded research involving foreign subawards/subcontracts must be submitted in response to a NOFO that is specifically designated for funded international collaborations. See NIH Grants Policy Statement 16.8 Collaborative International Research Awards.

Applications involving foreign subawards/subcontracts submitted in response to this NOFO will be deemed noncompliant and will not be considered for funding. This policy applies to all monetary international collaborations resulting in foreign subawards/subcontracts, however, it does not preclude unfunded international collaborations or foreign components, funding for foreign consultants, or procurement of unique equipment or supplies from foreign vendors.

Required Registrations

Applicant Organizations Applicant organizations must complete and maintain the following registrations as described in the How to Apply- Application Guide to be eligible to apply for or receive an award. All registrations must be completed prior to the application being submitted. Registration can take 6 weeks or more, so applicants should begin the registration process as soon as possible. Failure to complete registrations in advance of a due date is not a valid reason for a late submission, please reference the NIH Grants Policy Statement Section 2.3.9.2 Electronically Submitted Applications for additional information.

System for Award Management (SAM) – Applicants must complete and maintain an active registration, which requires renewal at least annually. The renewal process may require as much time as the initial registration. SAM registration includes the assignment of a Commercial and Government Entity (CAGE) Code for domestic organizations which have not already been assigned a CAGE Code. Foreign organizations must obtain a NATO Commercial and Government Entity (NCAGE) Code (in lieu of a CAGE code) in order to register in SAM. Unique Entity Identifier (UEI)- A UEI is issued as part of the SAM.gov registration process. The same UEI must be used for all registrations, as well as on the grant application.

eRA Commons - Once the unique organization identifier is established, organizations can register with eRA Commons in tandem with completing their Grants.gov registrations; all registrations must be in place by time of submission. eRA Commons requires organizations to identify at least one Signing Official (SO) and at least one Program Director/Principal Investigator (PD/PI) account in order to submit an application.
Grants.gov – Applicants must have an active SAM registration in order to complete the Grants.gov registration.

Program Directors/Principal Investigators (PD(s)/PI(s)) All PD(s)/PI(s) must have an eRA Commons account. PD(s)/PI(s) should work with their organizational officials to either create a new account or to affiliate their existing account with the applicant organization in eRA Commons. If the PD/PI is also the organizational Signing Official, they must have two distinct eRA Commons accounts, one for each role. Obtaining an eRA Commons account can take up to 2 weeks.

All PD(s)/PI(s) must be registered with ORCID. The personal profile associated with the PD(s)/PI(s) eRA Commons account must be linked to a valid ORCID ID. For more information on linking an ORCID ID to an eRA Commons personal profile see the ORCID topic in our eRA Commons online help.

Eligible Individuals (Program Director/Principal Investigator)

Any individual(s) with the skills, knowledge, and resources necessary to carry out the proposed research as the Program Director(s)/Principal Investigator(s) (PD(s)/PI(s)) is invited to work with their organization to develop an application for support.

For institutions/organizations proposing multiple PDs/PIs, visit the Multiple Program Director/Principal Investigator Policy and submission details in the Senior/Key Person Profile (Expanded) Component of the How to Apply-Application Guide.

Investigators from U.S. Federal Government Agencies (see eligibility statement above) may participate in this program as unpaid collaborators, co-Is, or unpaid consultants in accord with the Terms and Conditions provided in this NOFO. While their expertise and resources are highly valued, NIH intramural scientists cannot receive salary support or any other direct financial compensation from funds awarded through this extramural NOFO. Their involvement should be clearly outlined in the application, including a description of their scientific contribution, their number of person-months devoted to the project, and a formal letter of collaboration from their Institute/Center Scientific Director or equivalent, confirming their commitment to the project and that no grant funds will be used for their support or the operational costs of NIH intramural facilities. Any use of NIH intramural resources should be fully justified and approved by the relevant NIH Institute/Center. The grant applicant is responsible for writing the section of the grant that describes the proposed collaboration within the grant, which the NIH investigator should see and approve. Intellectual property will be managed in accord with established policy of the NIH in compliance with Executive Order 10096, as amended, 45 CFR Part 7; patent rights for inventions developed in NIH facilities are NIH property unless NIH waives its rights.

Specific Eligibility for Federally Funded Research and Development Centers (FFRDCs) and University Affiliated Research Centers (UARCs): FFRDCs and UARCs may not apply to this Research Opportunity Announcement as a prime performer/lead institution; however, subject to any restrictions (i.e., direct competition limitations as determined by the entity or potential limiting organizational conflicts of interest, agency sponsor related requirements and policies, etc.), FFRDCs and UARCs may be included as part the prime performer's proposal, as a sub-awardee. As with all prime/sub-awardee teaming arrangements, the Government will only have privity of contract with the prime performer, and all payments will be made through the prime awardee.

Foreign applicants

Will require strong justification
U.S. collaborators encouraged
Subawards for foreign investigators are not allowed
Unpaid foreign collaborators are allowed

2. Cost Sharing This NOFO does not require cost sharing as defined in the NIH Grants Policy Statement Section 1.2 Definition of Terms.

3. Additional Information on Eligibility Number of Applications

Applicant organizations may submit more than one application, provided that each application is scientifically distinct.

The NIH will not accept duplicate or highly overlapping applications under review at the same time, per NIH Grants Policy Statement Section 2.3.7.4 Submission of Resubmission Application. This means that the NIH will not accept:

A new (A0) application that is submitted before issuance of the summary statement from the review of an overlapping new (A0) or resubmission (A1) application.

A resubmission (A1) application that is submitted before issuance of the summary statement from the review of the previous new (A0) application.

An application that has substantial overlap with another application pending appeal of initial peer review (see NIH Grants Policy Statement 2.3.9.4 Similar, Essentially Identical, or Identical Applications).

Section IV. Application and Submission Information

1. Requesting an Application Package The application forms package specific to this opportunity must be accessed through ASSIST, Grants.gov Workspace or an institutional system-to-system solution. Links to apply using ASSIST or Grants.gov Workspace are available in Part 1 of this NOFO. See your administrative office for instructions if you plan to use an institutional system-to-system solution.

2. Content and Form of Application Submission It is critical that applicants follow the instructions in the Research (R) Instructions in the How to Apply - Application Guide except where instructed in this notice of funding opportunity to do otherwise (in this NOFO, in a policy notice, or other notice from NIH Guide for Grants and Contracts). Conformance to the requirements in the Application Guide is required and strictly enforced. Applications that are out of compliance with these instructions may be delayed or not accepted for review.

Page Limitations All page limitations described in the How to Apply- Application Guide and the Table of Page Limits must be followed.

Instructions for Application Submission

The following section supplements the instructions found in the How to Apply- Application Guide and should be used for preparing an application to this NOFO.

SF424(R&R) Cover All instructions in the How to Apply - Application Guide must be followed.

SF424(R&R) Project/Performance Site Locations All instructions in the How to Apply- Application Guide must be followed.

SF424(R&R) Other Project Information

SF424(R&R) Senior/Key Person Profile

R&R Budget

The budget request for this NOFO must distinguish between extramural costs and the costs associated with NIH intramural investigator participation. Extramural costs are those associated with the extramural investigator and the applicant organization.

Consistent with Section III eligibility requirements, NIH intramural investigators participate as unpaid collaborators and cannot receive salary support or any other direct financial compensation from funds awarded through this NOFO. However, applicants should identify and budget for reasonable costs of materials, supplies, and services necessary for the intramural investigator to carry out their proposed work (excluding salary, personnel costs, and operational costs of NIH intramural facilities). All use of NIH intramural resources must be fully justified in the budget justification and approved by the relevant NIH Institute/Center as confirmed in the letter of collaboration required in Section III.

Cost of NIH Intramural work Please note that the NIH Intramural Research program (IRP) costs and participation will not be included in the award paid to the grantee. However, cost of IRP reagents, consumables and data analysis (e.g. software licenses) should be submitted as a separate budget page in the application. IRP budgets may not include any salary and related fringe benefits for career, career conditional or other federal employees (civilian or uniformed service) with permanent appointments under existing position ceilings or any costs related to administrative or facilities support (equivalent to Facilities and Administrative costs). These costs may include salary for staff to be specifically hired under a temporary appointment for the project. The IRP budget may also include consultant costs, equipment, supplies, travel, and other items typically listed under other expenses. Funds can be requested for services by an external investigator or contractor as a subcontract/consortium including the applicable indirect (F&A) Extramural Grantee Costs Extramural costs may include such items as salary support for the extramural PD/PI and staff at the applicant organization, supplies, laboratory animals, data analysis, and other allowable costs for work performed at the (extramural) applicant organization, as well as travel costs for the extramural investigator(s).

The PD/PI and up to two other key personnel with complementary expertise are required to attend an annual in person Consortium meeting in Bethesda, MD, as well as virtual Consortium-led tutorials and open innovation meetings, as appropriate. Funds to attend these in person meetings should be budgeted in the application.

R&R Subaward Budget

PHS 398 Cover Page Supplement

PHS 398 Research Plan All instructions in the How to Apply - Application Guide must be followed, with the following additional instructions:

Applications must be built upon five core pillars, with a robust strategy for each. The first four pillars should be detailed within the 12-page application limit, while Pillar 5 must be submitted as a separate, required attachment. The entire strategy should be tailored to the specific aims of the project.

1. Data Quality and Governance for Model Development

Access to Clinical-Grade Imaging and Multimodal Datasets: Applicants must provide verifiable evidence of access to comprehensive, large-scale datasets essential for the project's entire lifecycle (development, technical validation, clinical validation). A 'Data Risk Assessment and Mitigation Plan' is required to address potential challenges in data access, quality, and sharing.
Data Fitness-for-Purpose Framework: Rather than general data sharing, applicants must present a systematic approach to data curation, harmonization, and quality management that ensures data is fit for the intended purpose of AI model development and validation. This framework must detail protocols for ensuring data integrity, tracking provenance, and addressing challenges inherent to multimodal data to ensure the resulting model is robust and reliable.

2. Clinically Grounded AI Technology

AI-Powered, Image-Centered, Multimodal CDS Tool: The central output must be a SaMD tool that integrates meso-to-macro scale clinical imaging with at least one other data modality (e.g., clinical lab tests, 'omics,' digital sensor data). The research plan must clearly articulate how clinical imaging will serves as the anchor data type for the project. The tool must address a clearly defined and significant unmet clinical need.
Robust AI Architecture: The proposal must describe an advanced analytical framework (e.g., deep learning, federated learning) optimized for multimodal data fusion. The architecture must be appropriate for the specific clinical task and data types.
End-User Design and Clinical Integration Plan: Applicants must provide a detailed plan for the proposed CDS tool's translation, deployment, and use within a clinical workflow. This plan should include:A discussion of the clinical problem and the current standard of care.
A clear description of the expected user group(s) and their clinical environments.
A concrete plan for how the CDS tool will be integrated into the clinical workflow.

3. Pathway to Implementation and Adoption

Clinical Adoption and Dissemination Strategy: Applicants should describe a compelling vision for the tool's clinical adoption and dissemination including proactive regulatory engagement.
Model Performance Monitoring System: All projects must include a plan for a system to track model performance and reliability. This plan must describe a post-deployment monitoring pipeline ready for clinical settings.

4. Integrated Multidisciplinary Team

Collaborative Structure: Applications may use a multiple PD/PI mechanism.
Core Multidisciplinary Expertise: Applicants must establish an inter-disciplinary, multi-institutional research team with the combined expertise necessary to address the proposed translational challenge. The team may include any number of participants and organizations necessary to assemble a critical mass of expertise and know-how for effective execution. The level of participation may vary among participants, based on the translational goals of the project. The team must possess the necessary expertise for the project's scope. Required expertise should include:Medical device/SaMD development
Data science (AI/multimodal data)
Relevant clinical domain knowledge
Regulatory science (either on the team or through consultation)
Implementing clinical workflows for healthcare systems
Additionally, NIH encourages proposed projects to include:Appropriate expertise to address user acceptance and human-AI interaction dynamics, for projects focusing on adoption and integration challenges.
Patient representatives or advocates to ensure patient-centered design principles are incorporated.
Investigator(s) and Environment Leadership Plan: All applications must include a comprehensive Leadership Plan. The arrangements for collaborations must allow administration of the joint effort as a single project. An organizational structure that clearly defines the partnership and relationships among the various components must be described in the Leadership Plan and illustrated in an organizational chart. This plan should also describePublication and Public Dissemination Policy: For publications and other public dissemination of information, policies to address the ordering and recognition of authors, and decisions about what material to publish, consistent with the interests of commercial partners (where applicable) should be presented.
Conflict resolution procedure: Including an escalation pathway for disagreements that cannot be resolved at the PI level must involve pre-agreed arbitration or mediation processes and must also detail joint governance structures, IP management agreements, and publication policies agreed upon by all partners.

Resource Allocation: Under terms and procedures to be defined in the Leadership Plan, the team has the responsibility and authority to use funds in the most productive way to achieve the goals defined at the time that the award is made. To accomplish these tasks, the PD(s)/PI(s) can adjust funding among M2C participants to support new partners or to reduce support to existing partners as needed.

5. Error Mitigation and Technical Management (Required Attachment) Applicants must submit a required Error Mitigation and Technical Management Plan as a separate attachment up to three pages in length that addresses all components listed in the linked guidance. The filename "Error Mitigation and Technical Management Plan.pdf" should be used for this attachment. This file name will be reflected in the final image bookmarking for easy access to reviewers.The Error Mitigation and Technical Management Plan may be revised during the award period in accordance with Consortium policies and updated NIH guidance.

Key Components of Phased Innovation Projects M2C projects are phased innovation awards consisting of linked awards (UG3/UH3) for each phase. Approach is divided into two distinct parts corresponding to the UG3 and UH3 phases. The total duration of the UG3 and UH3 phases cannot exceed 5 years. At the end of the Approach section for the UG3 and UH3 subsections, milestones and timelines should be provided under separate headings.

Phase 1 (UG3) - Rigorous AI Model Refinement and Technical Validation (Up to 2 Years) The UG3 phase focuses on the robust development and technical validation of CDS tools, preparing them for subsequent clinical application. All applicants must meet the following core requirements:

Rigorous Multimodal Data Management: Projects must incorporate the integration and analysis of diverse modalities and data sources, with clinical imaging as the anchoring modality. This necessitates rigorous data preparation procedures that address variability in data format, resolution, completeness, and quality across all sources.
Co-design: Employ a rigorous design approach that incorporates perspectives from different stakeholders including clinicians, patients, and other end-users. This systematic process must consider deployment context that could potentially influence both implementation success and user adoption. Co-design activities are required to begin during Phase 1 and continue throughout Phase 2.
Strategic Risk Mitigation: A clear identification of high-risk technical assumptions in the proposed AI methodology is required. The UG3 phase must incorporate specific, early milestones designed to stress-test and mitigate these assumptions using diverse, heterogeneous datasets representative of real-world clinical data. Proposals must detail quantifiable go/no-go criteria directly linked to the successful validation of these core technical assumptions, with a particular focus on factors impacting real-world applicability.
Proactive Regulatory Engagement: Active engagement with the Office of the National Coordinator for Health Information Technology and/or the U.S. Food and Drug Administration (FDA) is a requirement for all projects. This involves developing a formal Regulatory Pathway Assessment (https://www.fda.gov/patients/device-development-process/step-3-pathway-approval) that identifies the regulatory classification and evidentiary requirements for the proposed CDS innovation. This engagement must be formalized through a Q-submission, which is a mandatory milestone for progression to the UH3 phase.

Phase 2 (UH3) - Model Clinical Performance Testing Following successful transition this phase focuses on gathering compelling evidence of the CDS tool's real-world clinical utility, validating its feasibility for integration into the intended clinical workflows, and demonstrating its positive impact on patient outcomes and/or healthcare processes, thereby catalyzing its clinical adoption.

The total duration of the UG3 and UH3 phases cannot exceed 5 years. This phase may involve prospective studies, including clinical trials if appropriate, to gather evidence on the CDS tool's performance and potential impact in clinical settings.

UH3 Implementation Activities must include, but are not limited to:

Data Integration Implementation: Establish comprehensive and secure data integration processes to effectively combine clinical imaging with essential patient- and cohort-level data streams within clinical workflows prioritizing data security and privacy protection.
Multi-site Clinical Validation: Conduct clinical validation in a targeted healthcare delivery setting (e.g., community hospitals, large academic medical centers) to demonstrate the generalizability of performance across sites for the CDS tool in real-world settings. UH3 plans that propose error detection and mitigation protocols that are reliable across different patient populations and clinical contexts are strongly encouraged, in line with the fundamentals of precision medicine.
Continuous Monitoring Framework: A plan to implement robust methods for ongoing surveillance of model performance and reliability post-deployment, utilizing tools such as AI run charts or equivalent statistical monitoring methods. This framework should align with the FDA's guidance on post-market surveillance, https://www.fda.gov/regulatory-information/search-fda-guidance-documents/postmarket-surveillance-under-section-522-federal-food-drug-and-cosmetic-act.

While not required, applicants may propose to conduct clinical trials if appropriate and feasible within the project period. If a trial is proposed, the applicant must thoroughly describe it and provide strong justification for their chosen design. The work supported through an M2C award that includes clinical trial(s) shall be focused on the performance and effectiveness testing of the developed CDS tools in the real-world clinical workflow, and not on trial objectives outside of M2C scope (e.g., costs related to testing a therapeutic). M2C trials could be either de novo dedicated prospective trials or leverage ongoing or planned trials to assess CDS performance as secondary objectives, integrating with existing infrastructure and data streams.

Close collaboration with the PRIMED-AI Validation Center is required throughout Phase 2 (UH3), including:

Data and Strategy Sharing: Comprehensive sharing of relevant data (consistent with approved data sharing plans and IRB protocols) and the detailed sequestration strategy. The scope and parameters of this collaboration must be clearly defined and documented.
Standardized Evaluation: Strict adherence to standardized evaluation protocols established by the Validation Center to ensure consistency and comparability of results, where applicable.
Benchmark Utilization: Systematic use of shared benchmark datasets for comparative analysis and performance benchmarking against established standards, where applicable.
Independent Validation: Regular submission of CDS tools for independent validation by the Validation Center to ensure objective assessment of robustness, fairness, and performance across diverse datasets and clinical scenarios. Independent verification and validation are key activities. Credibility verification is an essential validation activity. Non-regulatory validation activities are necessary during the implementation, distribution, and deployment phase.

Timeline and Milestones A timeline (Gantt chart) including milestones is required for each phase (UG3/UH3). Milestones are goals that create go/no-go decision points in the project and must include clear and quantitative objective criteria for success. Annual milestones should function as indicators of a project's continued progress, thus revealing emergent difficulties, and will be used to evaluate the application not only in peer review but also in consideration of the awarded project for funding of non-competing award years. Milestones should be well-defined in the application. The following are particularly important:

Provide appropriately detailed (quantitative) criteria by which milestone achievement will be assessed.
Provide a detailed timeline for the anticipated attainment of each milestone and the overall goal.
Identify any impediments that could require an addendum to the research plan, milestones, and/or timeline with a discussion of alternative approaches.

Progression from the UG3 to the UH3 phase is a non-competitive transition contingent upon the successful achievement of all milestones and NIH administrative review. Criteria must be proposed by the applicant(s) and based on quantifiable model performance metrics including, but not limited to:

Quantitative Thresholds and Replicability: PIs must specify the quantitative performance and calibration thresholds (e.g., AUROC, F1-score, clinically relevant utility metric, and/or Expected Calibration Error) that the CDS tool is expected to consistently achieve on clinical imaging, multimodal datasets, and health measures and to ensure reliable probability predictions. These metrics and their corresponding thresholds must meet during independent evaluation by the PRIMED-AI Validation Center on a sequestered retrospective dataset. The plan must also describe how the reproducibility of these metrics will be confirmed during this independent assessment.
Regulatory Pathway Alignment: PIs must outline the specific, tangible outcomes from formal Q-submission to the FDA that will constitute a successful transition milestone. FDA feedback indicating agreement with a proposed regulatory pathway and key evidentiary requirements for market authorization must be documented.

Reporting and Sharing Milestones: The following reports and activities are required for all awardees:

Year 1: Awardees will begin to work with the PRIMED-AI Logistics Center, to establish agreements and policies regarding Intellectual Property (IP) management and data/model sharing with the Validation Center.

Year 2:Report from awardees describing the readiness of their algorithms for testing and sharing within the PRIMED-AI ecosystem.

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