Priscilla Chan

Priscilla Chan is a pediatrician and co-founder of the Chan Zuckerberg Initiative (CZI) and Biohub. Her work centers on supporting biological research, building scientific tools and bringing AI researchers together with scientists, physicians and patients. In a consequential joint announcement on November 6, 2025, Chan and Mark Zuckerberg made Biohub their primary philanthropic priority, pledging to dedicate the vast majority of their resources to it.[3][4][5]

In June 2025, Chan explained CZI’s sharper focus on biology and AI as a decision about where its resources and expertise could do the most good. She said the organization would retain meaningful support for education and its local community. The November founders’ announcement set out a tools–data–models sequence: bring scientists and engineers together in their own laboratories, build tools for observing biology, generate datasets, and train AI models toward virtual cells and immune systems. CZI would provide infrastructure and support for their initiatives.[3][4]

Chan describes her physician experience and Zuckerberg’s engineering background as complementary contributions to this effort. In the November 2025 Latent Space interview, she emphasized the combination of scientific talent, AI research, wet laboratories, compute, physicians and patients. She also drew a boundary around their role: Biohub was building fundamental understanding of cells and molecules, with partners needed to carry that work through to clinical impact. Alex Rives leads CZI’s scientific work at the intersection of AI and biology through Biohub.[1][2]

Chan argues that useful biological modeling depends on understanding how and where data were collected and connecting AI researchers with the people gathering them. She also emphasizes making it easy for others to contribute. In November 2025, she reported that the RNA-transcriptome corpus available through CELLxGENE covered 125 million cells, estimating that their organization was responsible for about 25% of the data and the wider ecosystem supplied 75%. She presented this as an example of seeding a shared scientific resource rather than generating everything within one institution.[1]

Her account of the technical challenge extends beyond collecting more cells. Gene-expression data reveal cellular activity; imaging locates structures in space; dynamic imaging adds change over time. Chan calls for connecting those dimensions and developing stain-free and dye-free methods for observing cells. As another example of linking observations, she described correlating detailed X-ray images of deceased organs with living patients’ MRI or CT images. These were research approaches she discussed, rather than a completed unified model.[1]

Chan’s proposed validation cycle is concrete: test a model’s prediction in the wet lab, determine whether the predicted result occurred, and feed the experimental outcome back into the model. Asked how that cycle could scale to large numbers of verifications, she answered, “I don’t know the answer to that yet.” She nevertheless sees a nearer-term benefit: models could reduce the risk of ambitious hypotheses, helping scientists explore larger ideas despite the expense and slowness of laboratory experiments.[1]

“I have to bring it back to the patient,” Chan said when asked what success would look like. Her examples included using models to investigate genetic variants of unknown significance: how a variant changes cellular behavior and whether that change contributes to disease. She also described the prospect of choosing medication according to an individual’s biology, rather than relying on prolonged trial and error. These are aspirations for precision medicine; she explicitly said they were building the basic science and would need others to develop its clinical applications.[1]

Chan’s view of medicine alongside AI retains a role for clinical judgment, care and compassion. She argues that doctors will still need to assess individual situations and help patients understand why a treatment makes sense, building trust in both science and the clinical pathway. In her July 2026 Biohub update, she also highlighted patients and families as contributors to discovery through Rare As One, a network supporting patient-led rare-disease organizations.[1][5]

In that update, Chan praised models that scientists could use, improve and build on. She argued that predictive virtual-cell research requires more biological data than any one laboratory can generate, presenting the Virtual Biology Initiative as an invitation for researchers, institutions and partners to build a shared, open scientific foundation.[5]

Chan’s earlier clinical career supplies the context she gives for these priorities. She earned a bachelor’s degree in biology at Harvard and an MD at the University of California, San Francisco, where she also completed her pediatrics residency. Recalling her path in June 2025, she said she was the first in her family to attend college and taught elementary-school science for a year before medical school. She described eight years of combined work as a trainee and pediatrician at UCSF and San Francisco General.[2][3]

Chan links caring for children with rare diseases to seeing the limits of existing medicine and the need to advance basic science. She and Zuckerberg founded CZI in 2015 with work spanning disease, education and local communities. In her retrospective account, those clinical experiences informed its science mission: helping scientists cure, prevent and manage disease by the end of the century.[3][4]