Lilly and Nvidia open joint AI lab for drug discovery with up to $1 billion
Lilly and Nvidia are spending up to $1 billion over five years on a joint AI lab aimed at drug discovery and manufacturing, work that would take years to reach patients.
Eli Lilly and Nvidia announced on January 12, 2026 that they will open a joint artificial intelligence lab focused on drug discovery, with the two companies investing up to $1 billion in talent, infrastructure and computing over five years [1]. The release describes it as a "first-of-its-kind AI co-innovation lab" and says the work is expected to begin in South San Francisco early this year [1].
The lab will be based in the San Francisco Bay Area and will put Lilly experts in biology, science and medicine side by side with Nvidia AI model builders and engineers [1]. The infrastructure will run on the Nvidia BioNeMo platform and the Nvidia Vera Rubin architecture [1]. The stated goal is to generate large-scale data and build AI models meant to speed medicine development [1].
The first phase centers on what the companies call a continuous learning system that tightly links Lilly's automated, or "agentic," wet labs with computational dry labs, allowing what the release describes as 24/7 AI-assisted experimentation to support biologists and chemists [1]. Under this "scientist-in-the-loop" framework, experiments and the data they produce are meant to feed back into AI model development on an ongoing basis [1]. The teams will focus on building what the companies call next-generation foundation and frontier models for biology and chemistry [1].
The initiative expands on Lilly's previously announced AI supercomputer, which the release calls the most powerful in the pharmaceutical industry and says was announced last fall [1]. That system, the release says, will train large biomedical foundation and frontier models for identifying, optimizing and validating new molecules [1].
"AI is transforming every industry, and its most profound impact will be in life sciences," Nvidia founder and CEO Jensen Huang said in the release [1]. "NVIDIA and Lilly are bringing together the best of our industries to invent a new blueprint for drug discovery — one where scientists can explore vast biological and chemical spaces in silico before a single molecule is made." [1]
Lilly chair and CEO David A. Ricks said combining the company's data and scientific knowledge with Nvidia's computing power and model-building expertise "could reinvent drug discovery as we know it" [1].
Beyond discovery, the companies say they will explore AI across clinical development, manufacturing and commercial operations, using multimodal models, agentic AI, robotics and digital twins [1]. The release says physical AI and robotics in the AI factory will help Lilly make high-demand medications and strengthen supply chain reliability [1]. Using Nvidia Omniverse libraries and RTX PRO Servers, the release says, Lilly can create digital twins of manufacturing lines to model, stress test and optimize supply chains before making physical changes [1]. The lab will also give the companies' startup ecosystems and researchers access to computing resources and expertise [1].
Why it matters for patients
This is research and manufacturing infrastructure, not a medicine. Nothing in the announcement changes which drugs are approved, what they cost, what insurance covers, or how they are prescribed [1]. Any treatment that comes out of this work would arrive years after the lab starts, and the release gives no timeline for a new medicine [1].
The most direct patient-facing claim is about supply: the release says robotics and digital-twin modeling are intended to help Lilly manufacture high-demand medications and make its supply chain more reliable [1]. It does not name specific medicines, and it does not say how much additional capacity is expected or when [1]. How the lab will be staffed, how many people will work there, and whether it will touch obesity, diabetes or any other specific disease area have not been disclosed [1].
Lilly's release includes a cautionary statement noting that there can be no guarantee the companies will realize the expected benefits of the collaboration, and that drug research, development and commercialization carry substantial risk and uncertainty [1].
What happens next
The lab's work is expected to begin in South San Francisco early this year, and the investment commitment runs up to five years [1]. No other milestones, hiring targets or product timelines were announced [1].
Sources
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