Simpler Grants.gov #RFA-RM-27-011

NIH Solicitation for Multimodal AI Frameworks and Playbook Development (PRIMED-AI Program)

This opportunity from the National Institutes of Health (NIH) seeks proposals for the PRIMED-AI Program, focused on advancing clinical artificial intelligence (AI): - Government Buyer: - National Institutes of Health (NIH) - Program Objective: - Design, develop, and preliminarily validate robust frameworks for multimodal AI models in clinical settings - Integrate clinical imaging with other health data to create innovative, reliable, and sustainable AI-based clinical decision support (CDS) tools - Populate a 'playbook' with actionable guidelines, standardized protocols, and standard operating procedures (SOPs) for developing and deploying multimodal AI tools - Products/Services Requested: - Development of flexible, interoperable frameworks for biomedical AI applications - No specific hardware or software products, part numbers, or OEMs are named - Unique/Notable Requirements: - Frameworks must support a wide range of biomedical AI applications - Eligibility is restricted: foreign organizations and non-U.S. components of U.S. organizations are not eligible to apply - Total program funding is $2,000,000, with a minimum award of $300,000 - No OEMs or specific vendors are mentioned in the solicitation

Description

This funding opportunity aims to establish the PRIMED-AI Program to support the development of innovative, reliable, cost-effective, and sustainable multimodal AI-based clinical decision support tools. These tools integrate clinical imaging with other multimodal health data to improve patient care across various health conditions. The program seeks applications for designing, developing, and preliminarily validating robust frameworks for multimodal AI models for clinical use. The resulting frameworks will form a "playbook" of guidelines, protocols, and standard operating procedures for effective development and deployment of multimodal AI tools, ensuring flexibility and interoperability across biomedical AI applications.

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