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

<p><span style="color: rgb(51, 51, 51);">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&nbsp;</span><strong style="color: rgb(51, 51, 51);">Precision Medicine with Artificial Intelligence - Integrating Imaging with Multimodal Data (PRIMED-AI) program, which seeks&nbsp;</strong><span style="color: rgb(51, 51, 51);">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</span><strong style="color: rgb(51, 51, 51);">&nbsp;Translating Model to Clinic initiative</strong><span style="color: rgb(51, 51, 51);">&nbsp;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.&nbsp;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.&nbsp;This NOFO will utilize the UG3/UH3 activity code. Investigators with expertise and insights into&nbsp;analysis and testing of large, interoperable multimodal datasets are encouraged to begin to consider applying for this new NOFO.</span></p>