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PRIMED-AI: Translating Models to Clinic (UG3/UH3 Clinical Trial Optional)

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Contract Overview

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

AI Contract Overview

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The NIH Common Fund, along with other NIH Institutes and Centers, plans to release a Notice of Funding Opportunity under the program titled Precision Medicine with Artificial Intelligence - Integrating Imaging with Multimodal Data (PRIMED-AI). This initiative aims to support the development of innovative, reliable, and cost-effective AI tools that integrate clinical imaging with various health data types to improve personalized medicine for patients managing chronic and other health conditions. The Translating Model to Clinic component of the program will employ a two-phase approach: starting with rigorous AI model development through retrospective analysis of large and interoperable multimodal datasets to enhance diagnostic, prognostic, or therapeutic decision-making, and subsequently moving promising models toward evaluation of their real-world clinical utility as AI-driven Clinical Decision Support tools. Applications are not yet being solicited; this announcement serves to provide potential applicants with adequate time to build collaborative partnerships and design responsive projects. The funding opportunity will utilize the UG3/UH3 activity code, allowing investigators with expertise in analyzing and testing large, interoperable multimodal datasets to prepare for future submission. The NIH encourages interested researchers to begin conceptualizing proposals aligned with the program’s goals to leverage artificial intelligence in advancing personalized medical care. Point of contact for inquiries is Sahana N. Kukke, PhD, reachable via email or phone at the NIH Office of the Director.

General Info

NIH funding opportunity for AI tools integrating imaging and multimodal data to enhance personalized medicine.

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) View NAICS

Place of Performance

Not specified

Set-Aside

NONE

Documents

(0)

No documents available

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Timeline

Posted

forecast

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Organization & Contact Information

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AgencyDepartment Of Health And Human Services → National Institutes Of Health
Contacts1 person available
OfficeUS
Organization / Agency
Department Of Health And Human Services → National Institutes Of Health
Office AddressUS
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’s Translating Model to Clinic initiative will use a biphasic mechanism to initially focus on rigorous AI model building through the retrospective analysis and testing of large, interoperable multimodal datasets, laying a robust foundation for improved diagnostic accuracy, prognostic prediction, or therapeutic guidance where current methods fall short. Projects demonstrating strong potential and model readiness will advance to evaluating the real-world clinical utility of the AI-driven Clinical Decision Support (CDS) tool. 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/UH3 activity code. Investigators with expertise and insights into analysis and testing of large, interoperable multimodal datasets are encouraged to begin to consider applying for this new NOFO.

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