NVIDIA and Lilly launch a $1 billion AI co-innovation lab in San Francisco to transform drug discovery by integrating pharmaceutical expertise with advanced AI.
NVIDIA and Eli Lilly are charting “a blueprint for the future of drug discovery,” NVIDIA founder and CEO Jensen Huang said during a fireside chat with Dave Ricks, chair and CEO of Lilly, on Monday.
The discussion, held at the annual J.P. Morgan Healthcare Conference in San Francisco, highlighted the launch of a first-of-its-kind AI co-innovation lab by the two companies. The initiative aims to combine Lilly’s pharmaceutical expertise with NVIDIA’s leadership in artificial intelligence to address the complex challenges of modeling biological systems.
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“We’re systematically bringing together some of the brightest minds in the field of drug discovery and some of the brightest minds in computer science,” Huang said. “We’re going to have a lab where the expertise and the scale of that lab is sufficient to attract people who really want to do their life’s work at that intersection.”
Over the next five years, NVIDIA and Lilly plan to invest up to $1 billion in talent, infrastructure, and computing resources to support the San Francisco Bay Area–based lab, accelerating innovation in drug discovery and development.
During the fireside chat, Ricks reflected on the painstaking work of drug discovery and AI’s potential to transform the cycle of pharmaceutical invention.
“Each small molecule discovery is like a work of art,” he said. “If we can make that an engineering problem, versus this sort of discovery, this artisanal drug-making problem, think of the impact on human life.”
The lab will operate under a scientist-in-the-loop framework, where agentic wet labs are tightly connected to computational dry labs in a continuous learning system. This framework aims to enable experiments, data generation and AI model development to continuously inform and improve one another.
The co-innovation lab builds on Lilly’s previously announced AI supercomputer, the biopharma industry’s most powerful AI factory, an NVIDIA DGX SuperPOD with DGX B300 systems, which will train large-scale biomedical foundation and frontier models for drug discovery and development.
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By integrating AI into drug discovery, Ricks explained, pharmaceutical researchers can rapidly simulate a massive number of possible molecules, test them at scale in silico and filter out promising candidates. The next challenge is to find more biological targets using AI.
“The holy grail is that you put those two things together, and we can model the whole system at once,” Ricks said.
