Program Snapshot

The NIH Common Fund’s Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) program will combine clinical imaging with other types of health data (“multimodal data”) to develop innovative artificial intelligence (AI)-powered clinical decision support (CDS) tools to enable new personalized medicine strategies.

CDS tools are designed to help healthcare providers make informed decisions about a patient’s care by pulling information from all forms of medical data, including imaging and all other health measures. These tools help clinicians make decisions more efficiently and in a more holistic way by providing evidence-based and patient-specific recommendations. These recommendations are based on more information than a clinician could reasonably review during a single session with a patient. Ultimately, CDS tools improve patient outcomes and quality of care.

AI is revolutionizing the development of CDS tools. Increasingly powerful AI algorithms offer new opportunities to rapidly combine vast amounts of patient data, including clinical imaging, on an individual level. These advancements have the potential to empower CDS tools to be more robust, more accurate, and even more personalized. Although clinical imaging plays a vital role in prediction, diagnosis, treatment, and outcome assessment, weaving together imaging with other health data during the development of AI-based CDS tools remains challenging.

The PRIMED-AI program will support the development and adoption of innovative, reliable, and cost-effective AI-based CDS tools that combine clinical imaging with other types of health data to enhance care for patients with wide-ranging health conditions. Accomplishing this goal will revolutionize the delivery of personalized medicine and substantially improve quality of health for the American people. 

PRIMED-AI will be centered around the following four foundational components: (1) combining imaging and non-imaging data, (2) developing AI tools, (3) implementing these tools in the clinic, and (4) building trust and coordination amongst researchers, clinicians, and patients. The program will bring together these groups to participate in the following efforts: 

• Directly targeting specific, unmet clinical needs by supporting the creation of sophisticated AI models to aid clinical decision making for individual patients.
• Accelerating translation of AI-enabled, image-based, multimodal CDS tools into practical clinical use.
• Empowering academic-industrial partnerships that will develop AI-based technologies that leverage multiple data types, with the goal of enhancing the commercialization potential of novel AI algorithms.
• Generating a validation framework for rigorous, impartial assessment of the overall dependability of AI models developed across the PRIMED-AI ecosystem and beyond.
• Supporting software tool development to address anticipated needs in key areas, as well as the development of standardized processes to support this emerging field.
• Enhancing communication between physicians, scientists, and patients within the PRIMED-AI space.
• Creating a logistics center to maximize the impact of the program through administrative and evaluative support, as well as facilitation of strategic outreach and engagement.

PRIMED-AI funding opportunities are expected to be announced starting in Summer 2025. 

To learn more about PRIMED-AI strategic planning activities, visit the strategic planning page.