Project Summary: Overall BRIDGE Center The promise of using Big Data for precision medicine, drug discovery, and a host of other challenges has remained elusive. Social and technical barriers have limited our ability to leverage our collective data assets to address biomedical and behavioral health challenges; Artificial Intelligence (AI) solutions present an opportunity to overcome these barriers. The NIH has established the Bridge to Artificial Intelligence (Bridge2AI, or B2AI) program to catalyze AI solutions to a set of community-defined “Grand Challenges.” This concerted effort will lay the groundwork to promote the widespread adoption of AI and to ensure that it leads to trustworthy, inclusive research innovations that have a significant, positive impact on human health. The BRIDGE Center proposal includes Administrative, Teaming, Skills and Workforce Development, and Standards Cores, chosen to coincide with the Core teams’ unique and complementary expertise in large-scale team science, standards development and dissemination, innovative training approaches, and community building. The vision for the BRIDGE Center is to engage all participants within and beyond the B2AI community through carefully considered social and technical mechanisms and operational excellence, with the goal of creating a dynamic, productive, and inclusive community that builds upon each other’s work in a deeply collaborative manner. The mission of the BRIDGE Center is to complement the Bridge2AI Data Generation Projects (DGPs) by supporting the integration, dissemination, and evaluation of Bridge2AI work products and teams. We propose to achieve that mission through three aims. Aim 1 focuses on integrating across the Bridge2AI Program. Specifically, we will foster group identity to create opportunities and incentives for transdisciplinary learning; establish human & machine-understandable standards, practices, and vocabularies across B2AI; and deploy technology to promote transparency and scalability across the B2AI program. Aim 2 creates and promotes opportunities to evaluate and improve B2AI products and activities including (1) employing community-based evaluation within and across DGPs, (2) deploying data-driven evaluation and improvement of B2AI products and processes, and (3) establishing and maintaining diversity in B2AI data, people, and team structures through a continuous process of evaluation and refinement. Aim 3 focuses on sustainable dissemination of products, knowledge, best practices and “lessons learned” from B2AI thereby ensuring broad, long-lasting distribution and impact. Taken together, these Aims will create a BRIDGE Center that fosters broad community engagement, inclusivity, and trust to successfully integrate activities and knowledge across the B2AI Program; disseminate products, best practices, and skill development materials/activities; and continually assess and improve all aspects of the Bridge2AI program with input from external stakeholder communities.

Narrative: Bridge2AI Center The promise of using Big Data for precision medicine, drug discovery, and a host of other challenges has remained elusive; barriers to effectively leveraging Artificial Intelligence (AI) and Machine Learning (ML) are both serious and varied — occurring at every stage of the development lifecycle from data to standards to tools and algorithms. Our Bridge to AI Center will engage the scientific community across this lifecycle in order to ensure that data are ethically sourced, machine-understandable, and easily integrated with other data. These advances will catalyze AI solutions to complex biomedical challenges.