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PRIMED-AI: Multi-use Framework Playbooks (UG3 Clinical Trial Not Allowed)

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Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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The National Institutes of Health, under the Department of Health and Human Services, is soliciting applications for the Precision Medicine with Artificial Intelligence - Integrating Imaging with Multimodal Data (PRIMED-AI) program under solicitation RFA-RM-27-011. This initiative aims to develop innovative, reliable, and cost-effective AI-based tools that integrate clinical imaging with various other health data types to improve personalized medicine for patients with chronic and other health conditions. Specifically, the Playbook initiative focuses on creating frameworks for the responsible use of AI models, error mitigation, technical data and algorithm management, data ontology, and the preparation for regulatory approvals such as those from the FDA. The program utilizes the UG3 activity code and seeks U01 cooperative agreement applications to design, develop, and preliminarily validate multimodal AI clinical decision support tools. These projects must deliver a playbook consisting of actionable guidelines, protocols, and standard operating procedures for reliable deployment. The notice was posted on June 6, 2025, with an open date of September 9, 2026, and an application deadline of October 9, 2026. The NIH encourages collaborative investigations that combine expertise in AI-driven integration of multiscale health data and harmonization processes for the development and validation of multimodal AI technologies.

General Info

NIH seeks U01 applications for AI tools integrating clinical imaging and multimodal health data.

Agency

Department Of Health And Human Services → National Institutes Of Health

NAICS

541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)

Place of Performance

Not specified

Set-Aside

NONE

Documents

0

No documents available

Documents will appear here when they are available.

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Organization & Contact Information

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AgencyDepartment Of Health And Human Services → National Institutes Of Health
Contacts1 person available
OfficeUSA
Organization / AgencyDepartment Of Health And Human Services → National Institutes Of Health
Office AddressUSA
Contacts
Sahana N. Kukke PhD Office of the Director/NIH Common Fund
contact@example.gov
+1 (555) 000-0000

Full Description

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The NIH Common Fund, with other NIH Institutes and Centers (ICs), intends to publish a Notice of Funding Opportunity (NOFO) to solicit applications for the Precision Medicine with Artificial Intelligence - Integrating Imaging with Multimodal Data (PRIMED-AI) program, which seeks to develop innovative, reliable, and cost-effective AI-based tools that integrate clinical imaging with other health data types to enhance personalized medicine for patients with chronic and other health conditions. The program’sPlaybook initiative will fund the development and initial testing of discrete projects that deliver “playbooks” of frameworks for responsible use of PRIMED-AI models, error mitigation and technical management of data and algorithms, data ontology/linkage, and preparation for regulatory approval​ (e.g., FDA). Applications are not being solicited at this time. Notice is being provided to allow potential applicants sufficient time to develop meaningful collaborations and responsive projects. This NOFO will utilize the UG3 activity code. Investigators with expertise and insights into AI-driven integration of clinical imaging with other complex and multiscale health data are encouraged to begin to consider applying for this new NOFO. In addition, collaborative investigations combining expertise in harmonization processes for appropriate development and validation of multimodal AI tools to develop AI-based technologies leveraging multimodal data will be encouraged and these investigators should also begin considering applying for this application.

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