Development and Testing of a Multi-use Frameworks Playbook for Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) (U01 Clinical Trial Not Allowed)
Below is a brief summary. Please check the full solicitation before applying (link in resources section).
Executive Summary:
The National Institutes of Health (NIH), through the Office of Strategic Coordination (Common Fund) and administered by the National Center for Advancing Translational Sciences (NCATS), is seeking applications to develop standardized frameworks that support the design, deployment, and adoption of multimodal artificial intelligence (AI) clinical decision support (CDS) tools.
Rather than funding development of a single AI application, this funding opportunity supports creation of practical frameworks—including standardized protocols, guidelines, and standard operating procedures—that will become part of the Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) Program "Playbook." These frameworks are intended to improve the development, validation, interoperability, and clinical adoption of multimodal AI tools that combine medical imaging with other health data.
Applicants must propose development of two or more distinct frameworks addressing separate framework topics. Projects that fail to propose at least two distinct frameworks will be considered non-responsive and will not be reviewed.
NIH intends to fund approximately five cooperative agreements through this opportunity.
Applications are due by October 09, 2026, at 5:00 PM local time of applicant organization. No late applications will be accepted.
How much funding would I receive?
NIH Common Fund intends to commit approximately:
Approximately $2,000,000 in FY2027
Approximately five awards, contingent upon availability of funds and receipt of a sufficient number of meritorious applications
Award budgets are limited to:
Up to $300,000 in direct costs per year
Project periods may be:
Up to two years
Budgets must reflect the actual needs of the proposed project.
What could I use the funding for?
Funding supports the design, development, and preliminary validation of practical frameworks that improve development and deployment of multimodal AI clinical decision support tools.
The resulting frameworks will populate the PRIMED-AI Playbook and are expected to be broadly usable across the biomedical AI community.
Applicants must develop two or more distinct framework topics, which may include areas such as:
AI-enabled scientific discovery
AI-ready dataset generation
Clinical AI training frameworks
Data quality
Data leakage prevention
Data lifecycle management
Model uncertainty
Data and model harmonization
Generalizability across clinical environments
Transparency and explainability
Model cards and data cards
Standards-based interoperability (including OMOP and FHIR)
Privacy-enhancing technologies
Regulatory navigation for clinical AI
Frameworks should:
Address imaging data together with other multimodal health data
Be practical and operational
Adapt to the rapidly evolving AI landscape
Clearly identify intended users
Describe applicable data and model classes
Define use cases and limitations
Be suitable for adoption by the broader research community
Awardees are expected to work collaboratively to develop a shared Playbook that minimizes duplication and supports interoperability across the PRIMED-AI Program.
Are there any additional benefits I would receive?
In addition to funding, award recipients become members of the NIH PRIMED-AI Consortium and participate in collaborative development of the national PRIMED-AI Playbook.
Award recipients will:
Collaborate with other Playbook awardees
Participate in the PRIMED-AI Steering Committee
Work with NIH program staff throughout the cooperative agreement
Contribute frameworks to the PRIMED-AI web portal
Participate in consortium meetings and working groups
Attend annual in-person consortium meetings
Participate in virtual tutorials and innovation meetings
Participate in an in-person framework showcase at the end of Year 2
Recipients also benefit from coordination with NIH staff, Validation Centers, Logistics Centers, and other funded PRIMED-AI projects to improve consistency, dissemination, and adoption of developed frameworks.
What is the timeline to apply and when would I receive funding?
Posted Date
June 30, 2026
Earliest Submission Date
September 09, 2026
Application Deadline
October 09, 2026, by 5:00 PM local time of applicant organization.
No late applications will be accepted.
Review timeline
Scientific Merit Review: March 2027
Advisory Council Review: May 2027
Earliest Start Date: July 2027
Projects may last for up to two years, with awardees expected to meet defined milestones throughout the project period.
Where does this funding come from?
This funding opportunity is offered by the National Institutes of Health (NIH) as part of the Common Fund, through the Office of Strategic Coordination (OSC). The program is administered by the National Center for Advancing Translational Sciences (NCATS) on behalf of NIH.
The funding supports the Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) Program, which aims to accelerate the development and adoption of innovative, reliable, cost-effective, and sustainable AI-based clinical decision support tools that integrate clinical imaging with multimodal health data.
This NOFO specifically supports development of standardized frameworks that will be compiled into the PRIMED-AI Playbook for use across the broader biomedical AI community.
Who is eligible to apply?
Eligible applicants include:
Higher Education Institutions
Public/state-controlled institutions of higher education
Private institutions of higher education
Nonprofit Organizations
Nonprofits with 501(c)(3) IRS status
Nonprofits without 501(c)(3) IRS status
For-Profit Organizations
Small businesses
For-profit organizations other than small businesses
Government Organizations
State governments
County governments
City or township governments
Special district governments
Federally recognized Tribal governments
Non-federally recognized Tribal governments
Eligible Federal agencies
U.S. territories or possessions
Other Eligible Organizations
Independent school districts
Public housing authorities
Native American Tribal organizations (other than federally recognized Tribal governments)
Faith-based organizations
Community-based organizations
Regional organizations
NIH Intramural Research Program investigators may also participate under the specific requirements described in the solicitation.
Individual Program Directors/Principal Investigators (PDs/PIs) may apply if they have the skills, knowledge, and resources necessary to carry out the proposed project and are affiliated with an eligible applicant organization.
Applicant organizations may submit more than one application, provided each application is scientifically distinct.
Who is not eligible to apply?
The following are not eligible to apply:
Non-domestic (non-U.S.) entities (foreign organizations)
Non-domestic components of U.S. organizations
Foreign components, as defined in the NIH Grants Policy Statement
Projects will also be considered non-responsive and will not be reviewed if they:
Do not propose two or more distinct frameworks for development.
Propose two methods addressing the same framework topic rather than two separate framework topics.
NIH will also not accept duplicate or substantially overlapping applications that violate NIH submission policies.
What companies and projects are likely to win?
The strongest applications will directly support the objectives of the PRIMED-AI Program by developing practical, broadly applicable frameworks that improve development and deployment of multimodal AI clinical decision support tools.
Competitive projects are likely to:
Propose at least two distinct framework topics.
Address important challenges in multimodal AI that integrate imaging with other health data.
Produce frameworks that are practical, flexible, and usable across multiple clinical environments.
Clearly identify intended users, applicable data types, use cases, and limitations.
Demonstrate expertise in AI framework development.
Include multidisciplinary teams with relevant stakeholders, such as clinicians, patients, software developers, regulators, and data scientists.
Present strong collaboration plans with other PRIMED-AI award recipients.
Include realistic milestones, timelines, and measurable performance metrics.
Promote clinical AI adoption through user feedback and iterative framework improvement.
Demonstrate how proposed frameworks will be shared and adopted by the broader research community.
NIH states that applications proposing frameworks that are duplicative of existing frameworks or represent only incremental advancements will be considered of low programmatic relevance, reducing their likelihood of funding.
How competitive will this solicitation be?
This funding opportunity is expected to be highly competitive.
NIH intends to make approximately five awards while committing approximately $2,000,000 in FY2027, contingent upon available funding and the receipt of a sufficient number of meritorious applications.
Applications will undergo NIH peer review and will be evaluated based on factors including:
Importance of the proposed research
Innovation
Scientific rigor
Feasibility
Investigator expertise
Institutional environment
In addition, reviewers will specifically evaluate:
The need for the proposed frameworks.
The benefit of the frameworks to multimodal AI and precision medicine.
Flexibility and usability across multiple clinical environments.
How well dependencies between framework types are addressed.
The quality of collaboration plans.
Plans to promote clinical AI adoption and innovation.
The experience of the project team in developing and deploying AI frameworks.
Following peer review, applications compete for funding based on:
Scientific and technical merit.
Availability of funds.
Relevance to PRIMED-AI program priorities.
Are there any restrictions I should know about?
Yes. Applicants should carefully review the program requirements before beginning an application.
Key restrictions include:
Clinical trials are not allowed
This NOFO only accepts applications that do not propose clinical trials. Applications may include activities involving human subjects that are not considered clinical trials.
You must propose at least two distinct frameworks
Each application must propose two or more distinct frameworks addressing separate framework topics.
Projects proposing only one framework, or multiple approaches to the same framework topic, will be considered non-responsive and will not be reviewed.
Frameworks must be broadly usable
All frameworks developed under this award are expected to:
Be shared with the broader research community.
Be suitable for inclusion in the PRIMED-AI Playbook.
Support extensibility and interoperability.
Clearly identify intended users, applicable data classes, use cases, and limitations.
Collaboration is required
Recipients will be expected to:
Participate in the PRIMED-AI Consortium.
Collaborate with other Playbook award recipients.
Participate in monthly Playbook Working Group meetings.
Participate in annual in-person Consortium meetings.
Attend virtual consortium activities.
Participate in an in-person framework showcase at the end of Year 2.
Data sharing requirements
Applicants must submit a Data Management and Sharing (DMS) Plan.
Recipients are expected to comply with PRIMED-AI Consortium policies regarding:
Data sharing
Software release
Metadata standards
Quality control
Public copyright licensing
Standardization requirements
Recipients are also required to engage with the Common Fund Data Ecosystem (CFDE) for dissemination of PRIMED-AI resources.
Registration requirements
Organizations must complete all required registrations before submitting an application, including:
System for Award Management (SAM)
Unique Entity Identifier (UEI)
eRA Commons
Program Directors/Principal Investigators must have:
An eRA Commons account
A linked ORCID ID
NIH notes that registration can take six weeks or longer, so applicants should begin the registration process as early as possible.
How long will it take me to prepare an application?
Applicants should expect this to be a significant proposal effort.
In addition to the standard NIH application requirements, applicants must prepare:
Two or more distinct framework concepts.
A detailed research strategy.
A draft framework layout.
Early standard operating procedures (SOPs).
Framework management plans.
A multidisciplinary team approach.
Collaboration plans with other PRIMED-AI award recipients.
A milestone plan with Gantt chart.
Performance metrics.
A Data Management and Sharing Plan.
Resource sharing information.
Required registrations for both the organization and PD(s)/PI(s).
Applicants must also budget for required consortium participation, including annual in-person meetings and the Year 2 framework showcase.
Because of these requirements, organizations should begin preparing well before the application deadline.
Applications are due by October 09, 2026, at 5:00 PM local time of applicant organization.
How can BW&CO help?
Developing a competitive NIH cooperative agreement application requires more than a strong technical concept. Applicants must also demonstrate program alignment, a clear development strategy, meaningful collaboration, measurable milestones, and compliance with NIH requirements.
BW&CO can help your team:
Assess whether your project aligns with the goals of the PRIMED-AI Program.
Refine your framework concepts to address NIH review criteria.
Develop a compelling research strategy and project narrative.
Create realistic milestones, timelines, and measurable deliverables.
Strengthen collaboration and management plans.
Prepare compliant budgets and application documents.
Review your application for responsiveness before submission.
Manage proposal development from kickoff through final submission.
Our team works with companies, universities, nonprofit organizations, and research institutions to prepare competitive federal funding applications while minimizing the administrative burden on technical teams.