1. What is the PRIMED-AI consortium?

The “PRIMED-AI consortium” constitutes members of PRIMED-AI, excluding NIH program staff. The “PRIMED-AI Program” is an umbrella term encompassing the consortium, NIH staff, and overall programmatic objectives.

2. Can I submit a late application due to my recent peer review service?

No.

3. Can one institution apply to multiple NOFOs?

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

4. Can foreign organizations apply?

No. Non-domestic (non-U.S.) entities (foreign organizations) are not eligible to apply. Non-domestic (non-U.S.) components of U.S. Organizations are also not eligible to apply.

5. Are there specific considerations for applications involving the NIH Intramural Research Program?

Title	RFA number	Considerations for Intramural Involvement
Validation Center	RFA-RM-27-014	Extramural only: Intramural investigators are not eligible to participate in these NOFOs.
Logistics Center	RFA-RM-27-015	Extramural only: Intramural investigators are not eligible to participate in these NOFOs.
Development and Testing of a Multi-use Frameworks Playbook	RFA-RM-27-011	Extramural and intramural competition: The requests by NIH intramural scientists will be limited to the incremental costs required for participation. As such, these requests will 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 or F&A costs). These costs may include salary for staff to be specifically hired under a temporary appointment for the project, consultant costs, equipment, supplies, travel, and other items typically listed under Other Expenses. Applicants should indicate the number of person-months devoted to the project, even if no funds are requested for salary and fringe benefits. Applications from the NIH Intramural Program, either as primary applicants or as collaborators, submitted in response to this NOFO must include a current (i.e. within 2 months of application due date) letter from the Scientific Director of their Division indicating that the intramural scientist will be able to collaborate on the project.
Data-to-Model Academic-Industrial Partnerships	RFA-RM-27-012	Extramural only: 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. 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, the 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.
Model-to-Clinic	RFA-RM-27-013	Extramural only: 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. 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, the 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.

6. Can microscopy-based imaging of biospecimens ex vivo like digital pathology represent the primary imaging data type/technique in PRIMED-AI award applications?

No, microscopy-based imaging of biospecimens ex vivo (e.g., digital pathology) cannot represent the primary imaging data type.

7. Can EEG and/or EKG/ECG imaging represent the primary imaging data type/technique in PRIMED-AI award applications?

No, EEG and/or EKG/ECG imaging, even if high density, cannot represent the primary imaging data type.

8. Can data derived from non-human sources be incorporated into PRIMED-AI award applications?

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.

9. Can non-DICOM standard imaging be incorporated in PRIMED-AI award applications?

Digital Imaging and Communications in Medicine (DICOM) standard, the most widely used by the community to address interoperability challenges, 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.

10. What is an Error Mitigation and Technical Management Plan?

Applicants for the Validation Center, Data-to-Model Academic-Industrial Partnerships, and Model-to-Clinic funding opportunities must submit a required Error Mitigation and Technical Management Plan as a separate attachment. Guidance on what should be included in this document is provided here. Applications that lack this required attachment are incomplete, will not be reviewed, and will be withdrawn. The Error Mitigation and Technical Management Plan may be revised during the award period in accordance with Consortium policies and updated NIH guidance.

1. How does PRIMED-AI define “benchmark datasets”?

To the PRIMED-AI program, benchmark datasets consist of carefully curated and labeled data that are essential for validating and comparing models developed in the PRIMED-AI Consortium.

2. How does PRIMED-AI define “clinical decision support (CDS) tool”?

PRIMED-AI defines clinical decision support (CDS) tools as 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.

3. How does PRIMED-AI define “clinical imaging”?

PRIMED-AI defines clinical imaging as 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 within the PRIMED-AI Program, which will form the basis for AI algorithm development and testing of clinical decision support (CDS) tools.

4. How does PRIMED-AI define “harmonization”?

PRIMED-AI defines harmonization as 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.

5. How does PRIMED-AI define “interoperability”?

PRIMED-AI defines interoperability as 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.

6. How does PRIMED-AI define “multimodal data (MMD)”?

PRIMED-AI defines multimodal data as 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.

7. How does PRIMED-AI define “Playbook”?

PRIMED-AI defines a Playbook as 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.

8. How does PRIMED-AI define “Precision Medicine”?

Sometimes called personalized medicine or individualized medicine, precision 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.

9. How does PRIMED-AI define “real-world data”?

PRIMED-AI defines real world data as data relating to patient health status and/or the delivery of health care that is routinely collected from a variety of sources during everyday clinical practice, rather than from clinical trials or controlled experiments. Within the PRIMED-AI framework, this typically encompasses multimodal data—such as electronic health records (EHRs), clinical imaging (radiology, pathology, fMRI etc.), laboratory test results, claims/billing data, and wearable sensor data. RWD is essential for training, testing, and externally validating Clinical Decision Support (CDS) tools to ensure the AI models are accurate, generalizable, and perform reliably across diverse, real-world patient populations.

10. How does PRIMED-AI define “uncertainty quantification”?

To PRIMED-AI, uncertainty quantification is measuring or quantifying the impact of uncertainties in complex systems, including quantifying the confidence in outcomes predicted by multimodal AI models.

11. How does PRIMED-AI define “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.

12. How does PRIMED-AI define “verification”?

PRIMED-AI defines verification as the process by which data integrity and construction of models is assessed for appropriateness within the context of use or intended purpose.

1. What is the NIH Common Fund?

The NIH Common Fund is a funding entity within NIH that supports bold scientific programs that catalyze discovery across all biomedical and behavioral research. These programs create a space where investigators and multiple NIH Institutes, Centers, and Offices collaborate on innovative research expected to address high priority challenges for NIH as a whole and make a broader impact in the scientific community.

• We make substantial investments in time-limited, goal-driven programs in order to change significantly the trajectory of biomedical research.
• Our programs accelerate emerging science, enhance the biomedical research workforce, remove research roadblocks, and support high-risk high-reward science in ways that no other entity is likely or able to do.
• We gather diverse input from NIH leadership, staff, and the broad biomedical research community to plan our programs.
• We assemble consortia of multidisciplinary, innovative researchers who collaborate to tackle a shared, ambitious goal.
• We manage our programs in partnership with nominated experts from the NIH Institutes and Centers.
• We design our programs so that each deliverable will spur subsequent biomedical advances that otherwise would not be possible without our strategic investment.
• For more information on the Common Fund, visit: https://commonfund.nih.gov/about

2. What is the NIH Common Fund’s Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) program?

PRIMED-AI seeks to combine clinical imaging with other health data types to develop innovative AI-powered clinical decision support tools for personalized medicine. 

The program will tackle complex clinical challenges by bringing together clinicians, and patients to create reliable, cost-effective, accessible, and sustainable AI health solutions that accelerate biomedical research. PRIMED-AI is a uniquely collaborative, catalytic, cross‐cutting way of transforming the delivery of personalized medicine through the emerging medical AI landscape.

3. What is the goal of the PRIMED-AI Program?

The overall goal of the PRIMED-AI program is to catalyze the development and adoption of innovative AI-based clinical decision support tools that integrate clinical imaging with multimodal non-imaging clinical data to enable reliable, cost-effective, accessible, and sustainable precision medicine workflows for diagnosis, treatment, and quality of health. The program subgoals include: 

1. Imaging-Multimodal Data Integration: Facilitate access and integration of clinical images and multimodal data
2. AI Algorithm and Tool Development: Develop and iterate on AI-based algorithms and tools to support clinical diagnosis, management, and prediction
3. Clinical Implementation: Test PRIMED-AI clinical decision support tools to catalyze new precision medicine approaches
4. Building Trust & Coordination: Coordinate activities to ensure program and community cohesion, adaptability, scientific validation & rigor, and operational transparency
    

4. How did the NIH arrive at these scientific and operational needs for a program focused on integrating imaging with multimodal data using AI?

Common Fund strategic planning is regularly conducted to identify research areas that address key roadblocks in biomedical research or that represent emerging scientific opportunities ripe for Common Fund investments. AI-facilitated integration of imaging with multimodal data was identified as an area of research that would benefit from Common Fund investment for a variety of reasons:

• AI and machine learning (ML) infrastructure and capabilities are rapidly building and expanding.
• Clinical imaging is often siloed from other health data.
• There is great opportunity to develop trusting relationships between patients, clinicians, and data scientists in the pursuit of reliable, cost-effective, accessible, and sustainable AI health solutions.

The NIH Common Fund directed strategic planning activities to inform the basis of the PRIMED-AI program. More information about these activities can be found here.

5. How will the PRIMED-AI program components interact with each other?

PRIMED-AI award recipients will participate in the PRIMED-AI Consortium to collaborate effectively with each other to maximize the chances of overall success of the entire PRIMED-AI Program. This includes but is not limited to sharing relevant data and sequestration strategies, adhering to standardized evaluation protocols, systematic use of benchmarked datasets, and regular submission of CDS tools for independent validation by the Validation Center.

More specifically, the Logistics Center will provide the administrative infrastructure necessary to facilitate and coordinate PRIMED-AI activities to maximize the impact of the PRIMED-AI Program. This includes serving administrative, evaluation, and outreach functions. AI-enabled Clinical Decision Support (CDS) tools developed by program award recipients will be comprehensively evaluated and characterized by the Validation Center. Frameworks developed in the PRIMED-AI playbook will address program objectives. 

Applicants are 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 interconnections with other aspects of the PRIMED-AI Program.

6. How long will the program last?

The first phase of the Program was cleared at the April 2025 Council of Councils meeting for five years. If the first phase is successful, there will be a proposal for a second phase to be considered by the Council of Councils.

7. Where can I find more information?

Announcements and regular updates will be posted on the program website. Receive updates directly by signing up for the listserv.

8. Who should I contact with questions?

All inquiries can be sent to [email protected].

1. What is the PRIMED-AI consortium?

The “PRIMED-AI consortium” constitutes members of PRIMED-AI, excluding NIH program staff. The “PRIMED-AI Program” is an umbrella term encompassing the consortium, NIH staff, and overall programmatic objectives.

2. Can I submit a late application due to my recent peer review service?

No.

3. Can one institution apply to multiple NOFOs?

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

4. Can foreign organizations apply?

No. Non-domestic (non-U.S.) entities (foreign organizations) are not eligible to apply. Non-domestic (non-U.S.) components of U.S. Organizations are also not eligible to apply.

5. Are there specific considerations for applications involving the NIH Intramural Research Program?

Title	RFA Number	Considerations for Intramural Involvement
Validation Center	RFA-RM-27-014	Extramural only: Intramural investigators are not eligible to participate in these NOFOs.
Logistics Center	RFA-RM-27-015	Extramural only: Intramural investigators are not eligible to participate in these NOFOs.
Development and Testing of a Multi-use Frameworks Playbook	RFA-RM-27-011	Extramural and intramural competition: The requests by NIH intramural scientists will be limited to the incremental costs required for participation. As such, these requests will 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 or F&A costs). These costs may include salary for staff to be specifically hired under a temporary appointment for the project, consultant costs, equipment, supplies, travel, and other items typically listed under Other Expenses. Applicants should indicate the number of person-months devoted to the project, even if no funds are requested for salary and fringe benefits. Applications from the NIH Intramural Program, either as primary applicants or as collaborators, submitted in response to this NOFO must include a current (i.e. within 2 months of application due date) letter from the Scientific Director of their Division indicating that the intramural scientist will be able to collaborate on the project.
Data-to-Model Academic-Industrial Partnerships	RFA-RM-27-012	Extramural only: 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. 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, the 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.
Model-to-Clinic	RFA-RM-27-013	Extramural only: 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. 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, the 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.

6. Can microscopy-based imaging of biospecimens ex vivo like digital pathology represent the primary imaging data type/technique in PRIMED-AI award applications?

No, microscopy-based imaging of biospecimens ex vivo (e.g., digital pathology) cannot represent the primary imaging data type.

7. Can EEG and/or EKG/ECG imaging represent the primary imaging data type/technique in PRIMED-AI award applications?

No, EEG and/or EKG/ECG imaging, even if high density, cannot represent the primary imaging data type.

8. Can data derived from non-human sources be incorporated into PRIMED-AI award applications?

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.

9. Can non-DICOM standard imaging be incorporated in PRIMED-AI award applications?

Digital Imaging and Communications in Medicine (DICOM) standard, the most widely used by the community to address interoperability challenges, 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.

10. What is an Error Mitigation and Technical Management Plan?

Applicants for the Validation Center, Data-to-Model Academic-Industrial Partnerships, and Model-to-Clinic funding opportunities must submit a required Error Mitigation and Technical Management Plan as a separate attachment. Guidance on what should be included in this document is provided here. Applications that lack this required attachment are incomplete, will not be reviewed, and will be withdrawn. The Error Mitigation and Technical Management Plan may be revised during the award period in accordance with Consortium policies and updated NIH guidance.

1. How does PRIMED-AI define “benchmark datasets”?

To the PRIMED-AI program, benchmark datasets consist of carefully curated and labeled data that are essential for validating and comparing models developed in the PRIMED-AI Consortium.

2. How does PRIMED-AI define “clinical decision support (CDS) tool”?

PRIMED-AI defines clinical decision support (CDS) tools as 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.

3. How does PRIMED-AI define “clinical imaging”?

PRIMED-AI defines clinical imaging as 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 within the PRIMED-AI Program, which will form the basis for AI algorithm development and testing of clinical decision support (CDS) tools.

4. How does PRIMED-AI define “harmonization”?

PRIMED-AI defines harmonization as 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.

5. How does PRIMED-AI define “interoperability”?

PRIMED-AI defines interoperability as 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.

6. How does PRIMED-AI define “multimodal data (MMD)”?

PRIMED-AI defines multimodal data as 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.

7. How does PRIMED-AI define “Playbook”?

PRIMED-AI defines a Playbook as 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.

8. How does PRIMED-AI define “Precision Medicine”?

Sometimes called personalized medicine or individualized medicine, precision 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.

9. How does PRIMED-AI define “real-world data”?

PRIMED-AI defines real world data as data relating to patient health status and/or the delivery of health care that is routinely collected from a variety of sources during everyday clinical practice, rather than from clinical trials or controlled experiments. Within the PRIMED-AI framework, this typically encompasses multimodal data—such as electronic health records (EHRs), clinical imaging (radiology, pathology, fMRI etc.), laboratory test results, claims/billing data, and wearable sensor data. RWD is essential for training, testing, and externally validating Clinical Decision Support (CDS) tools to ensure the AI models are accurate, generalizable, and perform reliably across diverse, real-world patient populations.

10. How does PRIMED-AI define “uncertainty quantification”?

To PRIMED-AI, uncertainty quantification is measuring or quantifying the impact of uncertainties in complex systems, including quantifying the confidence in outcomes predicted by multimodal AI models.

11. How does PRIMED-AI define “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.

12. How does PRIMED-AI define “verification”?

PRIMED-AI defines verification as the process by which data integrity and construction of models is assessed for appropriateness within the context of use or intended purpose.

1. What is the announcement number of this NOFO?

RFA-RM-27-014

2. What is the purpose of this announcement?

The purpose of this NOFO is to solicit applications for the creation of a Validation Center for the PRIMED-AI Program to serve as a dedicated hub for the comprehensive evaluation and characterization of AI-enabled, image-based, multimodal CDS tools developed by the PRIMED-AI Consortium, to ensure these tools are reliable, reproducible, and generalizable.  The Validation Center will focus on verification, validation, interoperability, and uncertainty quantification to comprehensively characterize performance of the CDS tools developed by the program. The core functions of the Validation Center will involve the systematic validation of PRIMED-AI Consortium deliverables, including those emerging from award recipients under the Playbook, Data-to-Model Academic-Industrial Partnerships, and Model-to-Clinic NOFOs.

3. How many awards will be funded?

The program anticipates funding one award.

4. What is the award budget?

$2,000,000 direct costs for the first year and up to $3,200,000 direct costs for the remaining four years of the project.

5. When are applications due?

The receipt date is October 2, 2026. All applications are due by 5:00 PM local time of applicant organization. 

6. To whom can I reach out with questions about this announcement?

All questions are welcome. Please reach out to [email protected] and indicate which funding opportunity your question relates to.

What are the key dates in the timeline for planning our application?

1. Are Letters of Intent (LOI) required?

No, NIH no longer requests or accepts Letters of Intent.

2. What are the requirements for Multi-PD/PI (MPI) and other Validation Center staff?

A multi-PD/PI application is required - one PD/PI is expected to commit at least 2 person months annually and the other(s) should devote at least 1 person month each. The PRIMED-AI Program will have regular conference calls and meetings. Applicants should request funds for 2-6 group members to attend annual meetings, Consortium-led tutorials, and open innovation meetings, as appropriate. The Validation Center should budget at least 6 person months for a dedicated project manager/director (PM/PD) for the project with the appropriate scientific expertise and project management responsibilities, who would support the PI(s) with project management. The PM/PD will be the primary liaison with the PRIMED-AI Program and Steering Committee.

3. How do I submit my application?

Organizations must submit applications to Grants.gov (the online portal to find and apply for grants across all Federal agencies). Applicants must then complete the submission process by tracking the status of the application in the eRA Commons, NIH’s electronic system for grants administration. NIH and Grants.gov systems check the application against many of the application instructions upon submission. Errors must be corrected and a changed/corrected application must be submitted to Grants.gov on or before the application due date and time.  If a Changed/Corrected application is submitted after the deadline, the application will be considered late. Applications that miss the due date and time are subjected to the NIH Grants Policy Statement Section 2.3.9.2 Electronically Submitted Applications. 

Applicants are responsible for viewing their application before the due date in the eRA Commons to ensure accurate and successful submission.

Check back for additional questions.

1. What is the announcement number of this NOFO?

RFA-RM-27-015

2. What is the purpose of this announcement?

The purpose of this NOFO is to establish a Logistics Center for the PRIMED-AI Program to facilitate and coordinate PRIMED-AI activities to maximize impact for the PRIMED-AI community.  Within the Logistics Center, three integrated Cores will serve the functions of Administration, Evaluation, and Outreach for the PRIMED-AI Consortium. It is expected that the Logistics Center will work closely with other PRIMED-AI consortium members to collect, curate and disseminate information regarding tools developed by the PRIMED-AI award recipients, and will facilitate widespread access and awareness across the relevant scientific, patient, and clinical communities.

3. How many awards will be funded?

The program anticipates funding one award.

4. What is the award budget?

$575,000 direct costs for the first year and up to $2,500,000 direct costs per year for the remaining four years of the project.

5. When are applications due?

The receipt date is October 2, 2026. All applications are due by 5:00 PM local time of applicant organization. 

6. To whom can I reach out with questions about this announcement?

All questions are welcome. Please reach out to [email protected] and indicate which funding opportunity your question relates to.

What are the key dates in the timeline for planning our application?

1. Are Letters of Intent (LOI) required?

No, NIH no longer requests or accepts Letters of Intent.

2. What are the requirements for Multi-PD/PI (MPI) and other Logistics Center staff?

A multi-PD/PI application is required - one PD/PI is expected to commit at least 2 person months annually and the other(s) should devote at least 1 person month each.

The Logistics Center is responsible for managing in person meetings and regular conference calls. Budgets should reflect costs associated with managing and hosting these meetings, both in person and virtual.  Applicants should also request funds for 2-6 group members to attend annual in person meetings, Program-led tutorials, and open innovation meetings, as appropriate.

The Logistics Center should budget at least 6 person months for a dedicated project manager/director (PM/PD) for the project with the appropriate scientific expertise and project management responsibilities, who would support the PI(s) with project management. The PM/PD will be the primary liaison with the PRIMED-AI Program and Steering Committee.

3. How do I submit my application?

Organizations must submit applications to Grants.gov (the online portal to find and apply for grants across all Federal agencies). Applicants must then complete the submission process by tracking the status of the application in the eRA Commons, NIH’s electronic system for grants administration. NIH and Grants.gov systems check the application against many of the application instructions upon submission. Errors must be corrected and a changed/corrected application must be submitted to Grants.gov on or before the application due date and time.  If a Changed/Corrected application is submitted after the deadline, the application will be considered late. Applications that miss the due date and time are subjected to the NIH Grants Policy Statement Section 2.3.9.2 Electronically Submitted Applications. 

Applicants are responsible for viewing their application before the due date in the eRA Commons to ensure accurate and successful submission.

1. Are the required $2.5M in restricted funds from the R&R budget included within the $2.5M annual direct-cost cap for Years 2–5, or is this value in addition to the funds available for Logistics Center operations and administrative functions? 

Yes, the $2.5M total cost restricted funds must be included in the $2.5M direct cost budget cap for years 2-5 – this is not in addition to the $2.5M direct cost budget cap.  This means that direct costs associated with restricted funds as well as the logistics center itself must fall under the $2.5M direct cost cap.  Direct costs associated with the restricted funds must be entered under the “Other Expenses” category of the budget section.  The amount of direct costs requested for the logistics center as well as the restricted funds must reflect the needs of the proposed project and may not exceed $2.5M direct costs each year for years 2-5.

1. What is the announcement number of this NOFO?

RFA-RM-27-011

2. What is the purpose of this announcement?

The purpose of this NOFO is to solicit applications for the design, development, and preliminary validation of robust frameworks for the application of multimodal-artificial intelligence (AI) models for clinical use. Frameworks developed through these awards would populate a "playbook", defined as a collection of actionable guidelines, standardized protocols, and/or standard operating procedures (SOPs) for reliable and effective development and deployment of multimodal AI tools.  It is expected that the frameworks delineated in this playbook will directly address PRIMED-AI objectives and needs, while also remaining flexible enough to enable sufficient extensibility and interoperability for use across a broad spectrum of multimodal biomedical AI applications, both internal and external to the PRIMED-AI Program.

3. How many awards will be funded?

The program anticipates funding five awards.

4. What is the award budget?

$300,000 direct costs per year.

5. When are applications due?

The receipt date is October 9, 2026. All applications are due by 5:00 PM local time of applicant organization. 

6. To whom can I reach out with questions about this announcement?

All questions are welcome. Please reach out to [email protected] and indicate which funding opportunity your question relates to.

What are the key dates in the timeline for planning our application?

1. Are Letters of Intent (LOI) required?

No, NIH no longer requests or accepts Letters of Intent.

2. How do I submit my application?

Organizations must submit applications to Grants.gov (the online portal to find and apply for grants across all Federal agencies). Applicants must then complete the submission process by tracking the status of the application in the eRA Commons, NIH’s electronic system for grants administration. NIH and Grants.gov systems check the application against many of the application instructions upon submission. Errors must be corrected and a changed/corrected application must be submitted to Grants.gov on or before the application due date and time.  If a Changed/Corrected application is submitted after the deadline, the application will be considered late. Applications that miss the due date and time are subjected to the NIH Grants Policy Statement Section 2.3.9.2 Electronically Submitted Applications. 

Applicants are responsible for viewing their application before the due date in the eRA Commons to ensure accurate and successful submission.

1. Are Playbook awardees allowed to create innovative software tools as part of their framework?

Yes, software tools are allowable as submissions to this NOFO as long as they address the underlying need of the framework selected.

2. Can the Playbook be comprised of code or is it intended to be written guidance only?

Code is allowable as part of the framework, however, as stated in the NOFO, all frameworks developed under this NOFO and the resulting playbook are expected to be shared and adopted by the broader research community and must be designed in such a way as to ensure that this is achievable.  Any framework developed under this NOFO that incorporates code will need to ensure that enough written guidance is provided to allow the broader research community to utilize the framework.

3. How many frameworks can I propose to develop?

All applicants are required to propose at least two distinct frameworks, but more are allowable if feasible within the proposed team expertise, budget and two year award time period.  Please keep in mind that applications proposing frameworks or methods that are duplicative to existing frameworks or are incremental advancement to existing frameworks will be considered of low programmatic relevance, which will decrease likelihood of funding.

4. Is anything considered non-responsive to this NOFO?

Yes, projects that do not propose two or more distinct frameworks for development will be considered non-responsive and will not be reviewed. Each applicant is required to propose two or more distinct frameworks for development – the frameworks should be on two separate framework topics, rather than two methods of addressing the same framework topic.

5. Are NIH Intramural Research Labs allowed to apply?

Yes, applications may be submitted by or include collaborations with NIH intramural research programs.  Special budgetary requirements are associated with inclusion of intramural labs and are included under Section IV. Application and Submission Information, 2. Content and Form of Application Submission, R&R Budget. Please also keep in mind that applications from the NIH Intramural Program submitted in response to this NOFO must include a current (i.e. within 2 months of application due date) letter from the Scientific Director of their Division indicating that the intramural scientist will be able to collaborate on the project.

6. How does my planned interaction with other components of the PRIMED-AI Program need to be addressed in my application?

All PD(s)/PI(s) funded under the PRIMED-AI Program will be expected to participate in PRIMED-AI Consortium activities, including attending and participating in Steering Committee meetings and accepting and implementing the consensus guidelines and procedures, as appropriate.  In addition, , all Playbook award recipients are required to establish a Playbook working group that will enable the recipients to coordinate development of the final playbook product and ensure minimal overlap between each of the recipients.  This Playbook working group will be required to meet at least monthly to streamline playbook development, and PIs of Playbook projects are expected to participate in these meetings.  When applying, all applicants are required to include a Consortium Collaboration Plan to briefly describe their plans to work with other Playbook award recipients, the Logistics Center for dissemination and web portal inclusion, and the Validation Center to harmonize processes for appropriate development and validation of multimodal AI tools.

1. What is the announcement number of this NOFO?

RFA-RM-27-012

2. What is the purpose of this announcement?

The purpose of the Data-to-Model Academic-Industrial Partnership (D2M-AIP) NOFO is to support multi-sector and multi-disciplinary research teams, including investigators from both academia and industry, to create mutually beneficial opportunities for partners in the pre-competitive development stage.  D2M-AIP projects are primarily focused on the integration and harmonization of novel multiscale, multimodal data with clinical imaging data and the development and testing of truly novel AI-enabled, image-centered, multimodal CDS tools, developed in pursuance as Software as a Medical Device (SaMD). D2M-AIP projects will leverage existing resources across the partnership, such as high-performance computing capabilities and access to clinical data, to generate robust validation data and engage with regulators, positioning the technology for rapid post-award translation into a viable and impactful clinical product.

3. What is the focus of Phase 1 (the UG3 phase)?

The UG3 phase is expected to focus on systematic PRIMED-AI CDS tool development and comprehensive technical validation, which will generally rely on retrospective or de-identified, curated datasets for technical validation. This phase will last up to 2 years.

4. What is the focus of Phase 2 (the UH3 phase)?

Following successful transition, the UH3 phase is expected to focus on further development of the PRIMED-AI CDS tool and validation of the tool's potential for delivering future clinical value.

5. How many awards will be funded?

The program anticipates funding six to eight awards.

6. What is the award budget?

$450,000 in direct costs per year for the UG3 phase and $800,000 in direct costs per year for the UH3 phase.

7. When are applications due?

The receipt date is October 19, 2026. All applications are due by 5:00 PM local time of applicant organization. 

8. To whom can I reach out with questions about this announcement?

All questions are welcome. Please reach out to [email protected] and indicate which funding opportunity your question relates to.

What are the key dates in the timeline for planning our application?

1. Are Letters of Intent (LOI) required?

No, NIH no longer requests or accepts Letters of Intent.

2. Are clinical trials allowed?

While they are 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 describe the trial thoroughly and provide strong justification for their chosen design. If a trial is proposed as part of a D2M-AIP project, it is anticipated that such trials will focus primarily on the efficacy of the developed CDS tools and be evaluated within de novo dedicated prospective trials or evaluated leveraging ongoing or planned trials to assess CDS performance as secondary objectives, integrating with existing infrastructure and data streams.

3. How do I submit my application?

Organizations must submit applications to Grants.gov (the online portal to find and apply for grants across all Federal agencies). Applicants must then complete the submission process by tracking the status of the application in the eRA Commons, NIH’s electronic system for grants administration. NIH and Grants.gov systems check the application against many of the application instructions upon submission. Errors must be corrected and a changed/corrected application must be submitted to Grants.gov on or before the application due date and time.  If a Changed/Corrected application is submitted after the deadline, the application will be considered late. Applications that miss the due date and time are subjected to the NIH Grants Policy Statement Section 2.3.9.2 Electronically Submitted Applications. 

Applicants are responsible for viewing their application before the due date in the eRA Commons to ensure accurate and successful submission.

1. What is the distinction between the Data-to-Models: An Academic-Industrial Partnership (RFA-RM-27-012) and the Model-to-Clinic (RFA-RM-27-013) NOFOs?

The Data-to-Model Academic-Industrial Partnership (D2M-AIP) NOFO is intended for applications from academic and industrial partners proposing commercially-driven projects. The primary innovation for D2M-AIP projects lies in the novel integration of complex datasets and the development of new AI models, followed by rigorous analytical validation and performance testing. These projects are not required to conduct clinical validation studies within the award period, though they may propose to do so. The goal is to develop and de-risk novel AI technologies through academic-industrial collaboration to a stage where they are primed for subsequent commercialization and translation. 

The Model-to-Clinic (M2C) NOFO is intended for applications that explicitly focus on broad adoption of AI models into practical clinical use, with a primary emphasis on the clinical endpoint. M2C projects will start with a promising AI model and must assess and validate the PRIMED-AI CDS tool's clinical performance, utility, and impact in real-world healthcare settings. The projects should also address other challenges arising from adoption of the PRIMED-AI CDS tools in clinical workflow and associated adoption cost and feasibility.  M2C projects do not require an industrial partner or a commercial driver, though collaboration with end-users and potential dissemination partners is strongly encouraged. 

2. M2C seems like an extension of D2M-AIP without the mandatory partnership between industry and academia. Can I apply to both D2M-AIP and M2C?

You can apply to both NOFOs, but those applications must be scientifically distinct. An NIH applicant generally cannot send the same application (or highly overlapping applications) to multiple NOFOs at the same time. The NIH prohibits duplicate applications under review simultaneously to ensure fair, independent evaluations. 

• Choose the D2M-AIP NOFO if your project: Is commercially-driven and led by an academic-industrial partnership; has its primary innovation in novel data integration and/or new AI model development; and will focus on analytical validation and performance testing, without a requirement for clinical validation studies. 
• Choose the M2C NOFO if your project: Has a primary focus on assessing clinical adoption and clinical impact; will translate a promising AI model into a clinical workflow; and will conduct required clinical validation studies to evaluate the tool’s real-world utility and feasibility for adoption in the real world clinical care environment. 

3. I'm not affiliated with an academic institution but the institution I am affiliated with has a clinical institute and research infrastructure. Am I still eligible to apply for the D2M-AIP?

At least one PI must be from the applicant academic institution with expertise in preclinical and/or translational AI research, but may include additional institutions to ensure the group has a critical mass of expertise to accomplish the goals of the project.

1. What is the announcement number of this NOFO?

RFA-RM-27-013

2. What is the purpose of this announcement?

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.

3. What is the focus of Phase 1 (the UG3 phase)?

The UG3 phase is expected to focus on the robust development and technical validation of CDS tools, preparing them for subsequent clinical application. This phase will last up to 2 years.

4. What is the focus of Phase 2 (the UH3 phase)?

Following successful transition, the UH3 phase is expected to focus 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.

5. How many awards will be funded?

The program anticipates funding six to eight awards.

6. What is the award budget?

$450,000 in direct costs per year for the UG3 phase and $1,000,000 in direct costs per year for the UH3 phase.

7. When are applications due?

The receipt date is October 19, 2026. All applications are due by 5:00 PM local time of applicant organization. 

8. To whom can I reach out with questions about this announcement?

All questions are welcome. Please reach out to [email protected] and indicate which funding opportunity your question relates to.

What are the key dates in the timeline for planning our application?

1. Are Letters of Intent (LOI) required?

No, NIH no longer requests or accepts Letters of Intent.

2. Are clinical trials allowed?

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.

3. How do I submit my application?

Organizations must submit applications to Grants.gov (the online portal to find and apply for grants across all Federal agencies). Applicants must then complete the submission process by tracking the status of the application in the eRA Commons, NIH’s electronic system for grants administration. NIH and Grants.gov systems check the application against many of the application instructions upon submission. Errors must be corrected and a changed/corrected application must be submitted to Grants.gov on or before the application due date and time.  If a Changed/Corrected application is submitted after the deadline, the application will be considered late. Applications that miss the due date and time are subjected to the NIH Grants Policy Statement Section 2.3.9.2 Electronically Submitted Applications. 

Applicants are responsible for viewing their application before the due date in the eRA Commons to ensure accurate and successful submission.

1. What is the distinction between the Model-to-Clinic (RFA-RM-27-013) and the Data-to-Models: An Academic-Industrial Partnership (RFA-RM-27-012) NOFOs?

The Data-to-Model Academic-Industrial Partnership (D2M-AIP) NOFO is intended for applications from academic and industrial partners proposing commercially-driven projects. The primary innovation for D2M-AIP projects lies in the novel integration of complex datasets and the development of new AI models, followed by rigorous analytical validation and performance testing. These projects are not required to conduct clinical validation studies within the award period, though they may propose to do so. The goal is to develop and de-risk novel AI technologies through academic-industrial collaboration to a stage where they are primed for subsequent commercialization and translation. 

The Model-to-Clinic (M2C) NOFO is intended for applications that explicitly focus on broad adoption of AI models into practical clinical use, with a primary emphasis on the clinical endpoint. M2C projects will start with a promising AI model and must assess and validate the PRIMED-AI CDS tool's clinical performance, utility, and impact in real-world healthcare settings. The projects should also address other challenges arising from adoption of the PRIMED-AI CDS tools in clinical workflow and associated adoption cost and feasibility.  M2C projects do not require an industrial partner or a commercial driver, though collaboration with end-users and potential dissemination partners is strongly encouraged. 

2. M2C seems like an extension of D2M-AIP without the mandatory partnership between industry and academia. Can I apply to both D2M-AIP and M2C?

You can apply to both NOFOs, but those applications must be scientifically distinct. An NIH applicant generally cannot send the same application (or highly overlapping applications) to multiple NOFOs at the same time. The NIH prohibits duplicate applications under review simultaneously to ensure fair, independent evaluations. 

• Choose the D2M-AIP NOFO if your project: Is commercially-driven and led by an academic-industrial partnership; has its primary innovation in novel data integration and/or new AI model development; and will focus on analytical validation and performance testing, without a requirement for clinical validation studies. 
• Choose the M2C NOFO if your project: Has a primary focus on assessing clinical adoption and clinical impact; will translate a promising AI model into a clinical workflow; and will conduct required clinical validation studies to evaluate the tool’s real-world utility and feasibility for adoption in the real world clinical care environment.