Two of the biggest names riding the AI-fueled market surge are taking their partnership deeper—and into the lab.
Eli Lilly and Nvidia announced a new AI co-innovation lab backed by more than $1 billion in investment over five years, aimed squarely at accelerating how new medicines are discovered, tested, and developed. The announcement was made during the 2026 J.P. Morgan Healthcare Conference in San Francisco, a venue increasingly known for major biotech and AI reveals.
The new facility, expected to open in the Bay Area by the end of March, will bring scientists from both companies together in one physical location—pairing Nvidia’s computing firepower with Lilly’s real-world lab infrastructure.
From Algorithms to Actual Experiments
Unlike many AI drug discovery efforts that live mostly in software, this lab is designed to stay grounded in physical experimentation.
According to Nvidia, the focus will be on “closed-loop discovery”—a system where AI models generate hypotheses, those ideas are tested in real labs, and the results immediately feed back into improving the models. The goal is speed, but also accuracy: fewer dead ends, earlier signals, and smarter decisions before drugs reach costly clinical trials.
Nvidia will contribute its full healthcare AI stack, including biology-focused foundation models, multimodal AI systems, agentic workflows, and DGX Cloud supercomputing. Lilly, meanwhile, brings decades of drug development expertise, proprietary data, and wet-lab capabilities.
An Expansion of the ‘AI Factory’ Vision
This new lab builds on an earlier initiative where Nvidia began helping Lilly develop what the company has described as an “AI factory”—a massive computing environment purpose-built for pharmaceutical research.
Lilly executives have framed the shift as more than automation. The company increasingly sees AI not as a supporting tool, but as an active collaborator in scientific discovery—one that can explore vast chemical and biological possibilities faster than human teams alone.
AI Beyond the Molecule
The partnership also stretches well beyond drug discovery.
Nvidia says its physical AI and robotics platforms—Omniverse, Isaac, and Jetson—could be deployed inside Lilly’s manufacturing operations. These systems allow companies to create digital twins of labs and factories, simulate workflows, and automate repetitive or contamination-prone tasks.
At the conference, Nvidia highlighted real-world examples where robotics-driven lab automation could dramatically cut costs and increase throughput, particularly in complex areas like cell therapy manufacturing.
A Growing Open Biology Ecosystem
The timing matters. Lilly has been steadily opening its AI ecosystem through initiatives like TuneLab, which gives biotech startups access to its drug discovery models while feeding new data back into Lilly’s systems.
Nvidia, for its part, is expanding BioNeMo into a broader open development platform for biology, complete with datasets, training recipes, and models designed for tasks like RNA structure prediction, molecular reasoning, and toxicity screening.
Together, the companies are positioning themselves at the center of a growing intersection between AI infrastructure and life sciences.
Why This Matters
Drug development is notoriously slow, risky, and expensive. Even modest improvements in early-stage discovery can ripple across the entire pharmaceutical pipeline—cutting costs, reducing failures, and potentially bringing treatments to patients faster.
By tightly coupling AI models with real lab data, Lilly and Nvidia are betting they can change not just timelines, but the underlying process itself.
This isn’t just another tech-pharma collaboration. It’s a $1 billion experiment in whether AI can fundamentally reshape how modern medicine gets made.