Laude Institute awards $10 million to build an open healthcare AI center

A new UCSF–UC Berkeley center will work to connect healthcare with patients’ daily lives, combining wearable data, medical records and AI methods intended to help select care. A $10 million multiyear award from Laude Institute establishes the Center for Edge Medicine, one of four research labs selected through its Moonshots competition.

In its November 5 announcement, Edge Medicine described a program that brings data infrastructure, clinical practice and AI research into one initiative. It plans to demonstrate measurable improvements in patient care at UCSF, then adapt the approach to other conditions and health systems. Those improvements are a stated research goal, rather than an outcome delivered by the award.

A shared foundation for health data

The center’s foundation is JupyterHealth, open-source infrastructure built on Project Jupyter. The team describes it as a way to securely bring together information from wearables and medical records for patients, researchers and care teams. Its intended role is to connect information gathered outside the clinic with the health system, supporting care where people live and manage chronic disease.

There is already an early operational base. David Patterson, Laude Institute’s founding board chair and a UC Berkeley professor emeritus, said JupyterHealth v0.1 was running three operational pilots. He framed the investment around making healthcare data integration less custom-built, with shared infrastructure that others could adopt rather than recreate.

The open source approach is central to why this matters: if they can make healthcare data integration less bespoke, the value is enormous.

David Patterson, founding board chair of Laude Institute

UCSF supplies the first care prototype

The clinical starting point is an integrated Cardio-Kidney-Metabolic care model at UCSF, called iCKM. Edge Medicine identifies it as the center’s first prototype: a setting in which its proposed connection between everyday health information and clinical care can take shape. The center’s ambitions therefore include a care model, not just a collection of AI tools.

Its planned AI work includes clinical foundation models and reinforcement-learning methods, which the team says are intended to learn from patients and help choose care for each person. The center describes the care model itself as a learning system, linking its clinical work to the development of those methods.

Beyond that first prototype, the team has outlined several ways to extend the funded work:

• Invite interdisciplinary teams to propose uses of JupyterHealth through the Edge Medicine Innovation Challenge.
• Build an ecosystem of companies and builders around the open infrastructure.
• Train researchers working at the intersection of computation and health.

From seed award to a multiyear lab

The award follows a staged competition. Laude’s Moonshots program received 125 proposals from more than 600 researchers at 47 institutions. Edge Medicine was one of eight seed awardees in the spring and had six months to develop a full proposal. The team presented its vision at an October demo day in San Francisco before being selected as one of four labs.

The center is housed within UCSF and UC Berkeley’s Computational Precision Health initiative. Ida Sim leads the project, with Ahmed Alaa, Irene Chen, Fernando Pérez and Maya Petersen as co-principal investigators. Edge Medicine says all of the center’s work will be developed openly so others can adopt and extend it—a commitment that reaches beyond the initial UCSF care setting.