Bridge to Artificial Intelligence (Bridge2AI) | The Common Fund

Program Snapshot

The NIH Common Fund’s Bridge to Artificial Intelligence (Bridge2AI) program will propel biomedical research forward by setting the stage for widespread adoption of artificial intelligence (AI) that tackles complex biomedical challenges beyond human intuition.

Resources from Bridge2AI Stage I

The first stage of the Bridge2AI program tackled a key gap in the biomedical research community by generating new “flagship” data sets and best practices for machine learning (ML) analysis. These datasets were collected and processed with AI modeling in mind. To complement these datasets, the program also developed: software, standards, tools, best practices and training materials for workforce development.

The resources generated by the first stage of the program are available through the Bridge2AI portal.

Bridge2AI Stage II

The second stage of the program will build upon the accomplishments of Stage 1 to use the generated data, tools and best practices to deliver trusted solutions to address major biomedical and behavioral health challenges.

The second stage of Bridge2AI will support two initiatives to propel AI health research:

Innovation Funnels – Using AI-ready datasets (including datasets from Bridge2AI Stage 1), the innovation funnels will create tools, devices, and novel insights that use AI to improve health.
Network for AI Health Science - The program will create a network for AI health science that will bring together a network of scientific experts to develop safety measures for responsible AI use and research. This network will also build a framework to inform future AI health sciences research.

Together, the Innovation Funnels and Research Network will generate an ecosystem of research teams that will use AI-enabled tools and solutions to address key health challenges. By improving health and promoting responsible use of AI in medicine, the program aims to build public trust in AI-informed health research and care.

To receive updates about funding opportunities and other program updates directly to your inbox, sign up for the Bridge2AI listserv.

Bridge2AI.org

Learn about the exciting work our researchers are doing. Visit the Portal

Team Building & Networking

Visit the Bridge2AI Platform (registration required) to hear from NIH leaders, watch videos from the June 2021 Team Building Activities, and join the conversation on Slack. Visit the Platform

The Promise of Bridge2AI

NIH Institute and Center Directors’ Welcome. Watch the Video

Health Relevance

Watch the Overview of the Bridge to Artificial Intelligence (Bridge2AI) video below to learn how Bridge2AI will propel biomedical research forward by setting the stage for widespread adoption of artificial intelligence (AI).

Program Updates

Registration open for the Bridge2AI Fall 2026 All Hands Meeting & Open House (Oct. 20-21) in Rockville, MD

Bridge2AI Approved for 2nd Stage, watch the Jan 2026 Council of Council presentation (starts at 04:03:00)

Bridge2AI investigator, Dr. Yael Bensoussan, shares how voice and AI could help detect disease on the Chasing Life podcast

Bridge2AI preliminary datasets now available

Funded Research

RFA-RM-21-023

PI Name	Institution Name	Title
BUI, ALEX (contact) BOUTROS, PAUL CHRISTOPHER PING, PEIPEI WATSON, KAROL E	UNIVERSITY OF CALIFORNIA LOS ANGELES	Building BRIDGEs: Coordinating Standards, Diversity, and Ethics to Advance Biomedical AI
MUNOZ-TORRES, MONICA CECILIA (contact) THESSEN, ANNE E	UNIVERSITY OF COLORADO DENVER	Integration, Dissemination and Evaluation(BRIDGE) Center for the NIH Bridge to Artificial Intelligence (BRIDGE2AI) Program
OHNO-MACHADO, LUCILA	UNIVERSITY OF CALIFORNIA, SAN DIEGO	A FAIR Bridge2AI Center (FABRIC)

OT2-Data-Generation-Projects-B2AI-051321-508.pdf (602.21 KB)

PI Name	Institution Name	Title
BENSOUSSAN, YAEL (contact) ELEMENTO, OLIVIER SIGARAS, ALEXANDROS RAMEAU, ANAIS JOHNSON, ALISTAIR RAVITSY, VARDIT BELISLE-PIPON, JEAN-CHRISTOPHE DORR, DAVID PAYNE, PHILIP POWELL, MARIA	UNIVERSITY OF SOUTH FLORIDA	Voice as a Biomarker of Health: Building an ethically sourced, bioaccoustic database to understand disease like never before (Precision Public Health: Using voice as a biomarker for human health, revealing how genomic variation, behavioral, and environmental factors affect individual and population health)
IDEKER, TREY (contact) CHEN, JAKE YUE CLARK, TIMOTHY KROGAN, NEVAN J LUNDBERG, EMMA MALI, PRASHANT RAVITSY, VARDIT SCHULZ, WADE LOREN	UNIVERSITY OF CALIFORNIA, SAN DIEGO	Building an Interpretable Genomic Translator Using Maps of Cell Architecture (Functional Genomics: Mapping spatiotemporal architecture of human cells to interpret cell structure/function in health and disease)
LEE, AARON (contact) LEE, CECILIA SUNGMIN	UNIVERSITY OF WASHINGTON	Multimodal Atlas of Disease for Artificial Intelligence: Generating datasets for pseudotime manifolds of health trajectories (MAD-AI) (Return to Health (Salutogenesis): Uncovering the details of how human health is restored after disease, using type 2 diabetes as a model)
ROSENTHAL, ERIC S (contact) BIHORAC, AZRA CLERMONT, GILLES CLIFFORD, GARI DAVID CORDES, ASHLEY HU, XIAO KAMALESWARAN, RISHIKESAN, MOORMAN, JOSEPH RANDALL RASHIDI, PARISA RUDIN, CYNTHIA STREKALOVA, YULIA A. WILLIAMS, ANDREW EWING WILLIAMS, ISHAN CANTY	MASSACHUSETTS GENERAL HOSPITAL	Patient-Focused Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AI (Clinical Care Informatics: Using imaging, clinical, and other data collected in an ICU setting for diagnosis and risk prediction)