Global pharmaceutical giants race to partner with NVIDIA as AI-powered drug discovery heats up

Lilly and NVIDIA Announce $1 Billion Co-Innovation Lab

Eli Lilly and NVIDIA announced a co-innovation lab worth up to $1 billion over five years at the J.P. Morgan Healthcare Conference on January 12, 2026. The partnership represents one of the largest disclosed AI collaborations in the pharmaceutical industry.

The lab, to be located in the San Francisco Bay Area, is expected to open by the end of March. It will co-locate Lilly scientists with NVIDIA AI engineers to build a continuous 24/7 experimentation loop connecting wet labs with computational dry labs.

"Each small molecule discovery is like a work of art," said Lilly CEO David Ricks at a JPM fireside chat with NVIDIA CEO Jensen Huang. "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."

Ricks described the ultimate goal: "The holy grail is that you put those [molecule simulation and target identification] together, and we can model the whole system at once"—simulating molecules and identifying biological targets simultaneously.

Pharma's Most Powerful Supercomputer

The lab announcement extends a relationship that began with Lilly's October 2025 plan for a major AI supercomputer. The 1,016 Blackwell Ultra GPU system, rated at more than 9 exaflops of AI performance, was unveiled at NVIDIA GTC Washington, D.C. on October 28, 2025, as "the most powerful supercomputer owned and operated by a pharmaceutical company."

The lab's compute stack will run on NVIDIA's BioNeMo platform and the upcoming Vera Rubin architecture, which NVIDIA says will deliver up to 10x reduction in inference token cost versus Blackwell.

The first technical priority: a "continuous learning" system that cycles data between robotic lab equipment and AI models around the clock, so each experiment improves the next. Beyond discovery, Lilly will use NVIDIA Omniverse and RTX PRO Servers to build digital twins of manufacturing lines for virtual stress-testing before making changes on the floor.

"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."

The investment fits within Lilly's $50 billion commitment to U.S. manufacturing and R&D expansion. The system runs on 100% renewable electricity and uses liquid cooling from chilled water infrastructure, aligning with the company's 2030 carbon neutrality goals.

Merck and NVIDIA Launch KERMT Drug Discovery Model

Preceding the Lilly-NVIDIA mega deal, pharmaceutical giant Merck and NVIDIA rolled out a new small-molecule drug model called KERMT in December 2025.

According to a paper published in the journal Drug Discovery Today, researchers have introduced more than 200 drug discovery foundation models in the last three years, with 40% growth per quarter.

KERMT is pretrained on more than 11 million molecules, then fine-tuned for various tasks specific to industrial drug discovery workflows. Alan Cheng, Merck's senior director of data science, said the model could help scientists better predict how a given molecule will behave in the body, potentially catching problems before researchers invest in months of testing.

"Traditionally, scientists spend months running physical and biological tests to understand ADMET properties: absorption, distribution, metabolism, excretion, and toxicity," Cheng explained. "These steps are essential because a promising compound can fail late in development if it is toxic or has poor exposure at the therapeutic target."

Cheng noted that AI is already "speeding up the early stages of drug development dramatically," sometimes cutting timelines by 30% or more while improving drug candidate quality and reducing costs.

With NVIDIA's infrastructure support, Merck was able to speed up KERMT's calculation time and reduce memory usage compared to the underlying GROVER model. KERMT and TEDDY, Merck's genomics-focused foundation model, are already deployed directly to scientists' desktops and embedded in real-time design cycles. Both models have been released as open source.

NVIDIA's Expanding Pharma Partnership Network

NVIDIA has built direct AI infrastructure partnerships with an expanding roster of major pharmaceutical companies:

Anthropic has also entered the life sciences AI market with the launch of Claude for Life Sciences, aimed at expediting biotech R&D.

Outlook: Promise and Challenges in AI Drug Discovery

Despite the emergence of numerous drug discovery foundation models over the past three years, the technology has yet to yield fully approved drugs. The pipeline process for new drugs can take years, and nine in 10 clinical drug candidates fail.

However, the industry expects AI to dramatically shorten preclinical phases and increase success rates. Merck's Cheng predicted that "oncology, cardiovascular, and immunology, where we have a promising pipeline, are likely to see early impact."

Lilly-NVIDIA's $1 billion investment and Merck's open-source model releases signal that pharma-AI convergence has entered a full-scale industrialization phase. As global pharmaceutical companies intensify their AI infrastructure competition, a fundamental transformation in drug development paradigms is accelerating.