CEOs of NVIDIA and Lilly Share ‘Blueprint for What Is Possible’ in AI and Drug Discovery
Source: NVIDIA AI Blog
NVIDIA & Lilly Unveil a “Blueprint for the Future of Drug Discovery”
Jensen Huang (NVIDIA founder & CEO) and Dave Ricks (Chair & CEO, Lilly) discussed the partnership during a fireside chat at the J.P. Morgan Healthcare Conference (San Francisco, 2026).
The Announcement
NVIDIA and Lilly are launching a first‑of‑its‑kind AI co‑innovation lab to reinvent drug discovery.
Read the official press release:
“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,” said Huang.
“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.”
Key points
- Investment: Up to $1 billion over five years (talent, infrastructure, compute).
- Location: San Francisco Bay Area.
- Goal: Combine Lilly’s pharmaceutical expertise with NVIDIA’s AI leadership to model the complexities of biology.
Fireside Chat Highlights
| Speaker | Quote |
|---|---|
| Dave Ricks | “Each small molecule discovery is like a work of art. If we can make that an engineering problem… think of the impact on human life.” |
| Dave Ricks | “Machines are made to work day and night to solve this problem.” |
| Jensen Huang | “I can’t imagine a more worthy field to apply computer science to. Hopefully we can bend the arc of history.” |
Scientist‑in‑the‑Loop Framework
- Agentic wet labs ↔ computational dry labs
- Continuous learning loop: experiments → data → AI model → new experiments.
Building on Lilly’s AI Supercomputer
Lilly previously announced the biopharma industry’s most powerful AI factory:
- Hardware: NVIDIA DGX SuperPOD with DGX B300 systems.
- Purpose: Train large‑scale biomedical foundation and frontier models for drug discovery and development.
“The holy grail is that you put those two things together, and we can model the whole system at once.” – Ricks
Looking Ahead
- Accelerated molecule simulation: AI can screen millions of candidates in silico, dramatically shortening the discovery cycle.
- Target discovery: Next frontier is using AI to identify new biological targets, especially for age‑related brain diseases.
The partnership aims to turn drug discovery from an artisanal craft into an engineering discipline, leveraging AI to improve human health at scale.
NVIDIA at J.P. Morgan Healthcare
NVIDIA’s full‑stack AI platform is accelerating the creation and deployment of leading foundation models across digital biology and drug discovery. To recognize recent advancements, Jensen Huang raised a toast at the J.P. Morgan Healthcare Conference in honor of about a dozen leaders in the field — and the AI models they’ve pioneered.
“In the last 10 years, we’ve advanced AI 1 million times,” Huang said. “I believe that over the next 10 years you will enjoy the same adventure that I’ve enjoyed in our generation … and so for each one of you — for your happy new‑year present and a thank you for everything that you do for the industry and for the future of humanity — I give to you a DGX Spark.”
Over a dozen leaders in AI and drug discovery received NVIDIA DGX Spark systems signed by NVIDIA founder and CEO Jensen Huang at the conference.
Honorees
- Zach Carpenter, CEO of VantAI – developer of the Neo model family for co‑folding and design across all biological molecules.
- Gabriele Corso, CEO of Boltz – creator of one of the most well‑established open‑source families of biomolecular models.
- Evan Feinberg, CEO of Genesis Molecular AI – developers of Pearl, a protein‑ and small‑molecule structure‑prediction model.
- Chris Gibson and Najat Khan, Chairman and CEO of Recursion – creators of the OpenPhenom vision‑transformer model for microscopy data.
- Glen Gowers, CEO of Basecamp Research – creator of EDEN, a biodiversity‑scale genome language‑model family.
- Brian Hie, Innovation Investigator at the Arc Institute – major collaborator on Evo 2, part of the Evo DNA‑language‑model family.
- Max Jaderberg, President of Isomorphic – extending the capabilities of AlphaFold, the defining protein‑structure and interaction model family.
- Simon Kohl, CEO of Latent Labs – developer of the Latent‑X family of generative models for protein sequence and structure.
- Joshua Meier, CEO of Chai Discovery – creators of the Chai family of generative AI models for molecular‑structure prediction and design.
- Tom Miller, Co‑founder and CEO of Iambic Therapeutics – developers of the NeuralPLexer model family for fast, accurate structure prediction of proteins and small molecules.
- Alex Rives, Head of Science at Biohub – creators of the ESM family of leading protein‑language models.
- Alex Zhavoronkov, CEO of Insilico Medicine – builders of Pharma.AI, an integrated suite spanning target discovery, generative chemistry, and clinical prediction.
NVIDIA BioNeMo Platform Expansion
At the conference NVIDIA announced a major expansion of the NVIDIA BioNeMo platform for AI‑driven biology and drug discovery, adding tools such as:
- NVIDIA Clara open models for RNA‑structure prediction and for ensuring AI‑designed drugs are synthetically tractable.
- BioNeMo Recipes to accelerate and scale foundation‑model training, customization, and deployment.
- BioNeMo data‑processing libraries (e.g., nvMolKit, a GPU‑accelerated cheminformatics toolkit for molecular design).
Partnerships & Highlights
- Thermo Fisher Scientific – collaboration to build autonomous‑lab infrastructure using NVIDIA’s full‑stack AI computing.
- Multiply Labs – showcased work from this San Francisco startup that offers end‑to‑end robotic systems to automate cell‑therapy manufacturing at scale.
J.P. Morgan Healthcare is the world’s largest healthcare investment symposium, attracting over 8,000 global professionals—including investors, policymakers, and executives—from across the healthcare industry.
Additional Resources
- 🎧 Audio recording of the conference session
- 📄 Presentation deck by Kimberly Powell, VP of Healthcare at NVIDIA – discusses AI’s impact across healthcare.