Artificial intelligence could lead the way to a new paradigm for solving biology’s complex problems in a holistic fashion, world recognized computer scientist Eric Xing told an audience as part of the Princeton Laboratory for Artificial Intelligence’s inaugural Distinguished Lecture Series event.

The lecture, titled “Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All Levels,” was hosted March 7 by AI for Accelerating Invention, one of the AI Lab’s three research initiatives. 

It was the first of four distinguished lectures organized by the AI Lab in the spring semester, with the goal to bring speakers to campus whose research demonstrates the transformative impact AI could have across disciplines. 

The next distinguished lecture, featuring Google DeepMind research scientist Been Kim, will be hosted by Natural and Artificial Minds on March 28. Princeton Language and Intelligence will host distinguished lectures on April 4 and 11.

In his talk, Xing, who is the founding president of the Mohamed bin Zayed University of Artificial Intelligence, laid out his vision for an AI-Driven Digital Organism, a system of integrated multiscale foundation models, that he said could predict, simulate and program biology at all levels, from molecules to cells to individuals.

This digital organism would allow scientists to break down silos between different areas of study, he said, putting biological and medical problems into a much broader context. 

“I would argue that every human health problem is essentially an etiological problem of our skills,” Xing said. “If someone comes down with a disease, or if your cell has a lesion, we can actually go all the way down to the genetics to trace out the cause, and go all the way up to the organism or even the population to unleash the impact.”

Xing described an approach to constructing the digital organism, presented some early results, and described how his digital organism could open up a platform for predicting, simulating and programming biology. This technology could eventually help us better decode life, he said, giving rise to a new wave of better-guided wet-lab experimentation and better-informed reasoning.