Eli Lilly and Nvidia plan new AI lab to speed drug discovery

The doctor will see you now. It’s an AI agent with a visitor badge — and an eight-figure monthly burn.

Nvidia and Eli Lilly announced Monday that they’re launching a co-innovation AI lab aimed at speeding up drug discovery — a five-year commitment of over $1 billion, built around accelerated, closed-loop discovery that’s meant to “industrialize” AI models and accelerate clinical development. The companies will co-locate at a new Bay Area site so teams can work together in real time, with the opening targeted for the end of March.

Kimberly Powell, Nvidia’s vice president of healthcare, linked the scaling plan to Nvidia’s future hardware, saying Lilly’s newly deployed AI factory is expected to grow into a hybrid cloud environment powered by future Nvidia Vera Rubin systems, alongside Nvidia’s DGX cloud capacity. For Nvidia, that’s the kind of detail that turns a partnership into something sturdier than a headline: a multiyear plan that’s already looking past the current generation of machines.

“By combining Lilly's deep domain expertise in drug discovery and Nvidia's expertise in AI and accelerated computing,” Powell said, “we are building the future of how medicines will be designed and developed.”

Her description of what the lab will do leans hard on data generation — the unglamorous ingredient that determines whether “AI drug discovery” behaves like a discipline or a demo. She said a major focus will be on producing “amazing training data” through large-scale lab work, creating “ground truth data in the lab” to train biology foundation models with multimodal data, then tightening the loop between hypotheses and discovery. And that’s the premise behind the whole setup: better experiments create better data; better data creates better models; better models make the next experiments more targeted — a feedback loop engineered for throughput.

In a press release, Lilly’s chief information and digital officer, Diogo Rau, described the lab as a shift in how discovery gets done. “We see this as a catalyst for the capabilities that will define the next era of drug discovery,” he said. “By working with Nvidia, we’re uniting massive compute, specialized talent and the ability to shape data at immense scale.” He added: “We’re moving toward a future where discovery is driven by rapid experimentation and increasingly customized models.”

Powell’s version of the same bet leans hard on data creation — “ground truth data in the lab” produced through large-scale lab work — because biology models only get as good as the inputs you can defend. The scope goes beyond early R&D. Powell said the companies will explore applying accelerated computing and advanced AI across Lilly’s business, from manufacturing to commercial operations. That’s a wide mandate — and a familiar one for Nvidia, which tends to start with the sexiest workflow and then angle for the rest of the enterprise stack once the infrastructure is in place.