On Jul. 29, 2025, Stanford Medicine researchers announced the creation a team of virtual scientists backed by artificial intelligence to help solve problems in their real-world lab. The new artificial intelligence-driven tool is meant to turbocharge scientific discovery: virtual labs. Modeled after a well-established Stanford School of Medicine research group, the virtual lab is complete with an AI principal investigator and seasoned scientists.

“Good science happens when we have deep, interdisciplinary collaborations where people from different backgrounds work together, and often that’s one of the main bottlenecks and challenging parts of research,” said James Zou, PhD, associate professor of biomedical data science who led a study detailing the development of the virtual lab. “In parallel, we’ve seen this tremendous advance in AI agents, which, in a nutshell, are AI systems based on language models that are able to take more proactive actions.”

The leap in capability gave Zou the idea to start training these models to mimic top-tier scientists in the same way that they think critically about a problem, research certain questions, pose different solutions based on a given area of expertise and bounce ideas off one another to develop a hypothesis worth testing. “There’s no shortage of challenges for the world’s scientists to solve,” said Zou. “The virtual lab could help expedite the development of solutions for a variety of problems.”

Already, Zou’s team has been able to demonstrate the AI lab’s potential after tasking the “team” to devise a better way to create a vaccine for SARS-CoV-2, the virus that causes COVID-19. And it took the AI lab only a few days.

For the SARS-CoV-2 project, for instance, the PI agent created an immunology agent, a computation biology agent and a machine learning agent. And, in every project, no matter the topic, there’s one agent that assumes the role of critic. Its job is to poke holes, caution against common pitfalls and provide constructive criticism to other agents. A paper describing the findings of the study was published July 29 in Nature.