NVIDIA and Lilly are putting together a blueprint for what is possible in the future of drug discovery, NVIDIA founder and CEO Jensen Huang told attendees at a fireside chat Monday with Dave Ricks, chair and CEO of Lilly.The conversation - which took place during the annual J.P. Morgan Healthcare Conference in San Francisco - focused on the announcement of a first-of-its-kind AI co-innovation lab by NVIDIA and Lilly.
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 initiative will bring together Lilly's world-leading expertise in the pharmaceutical industry with NVIDIA's leadership in AI to tackle one of humanity's greatest challenges: modeling the complexities of biology. The two companies will jointly invest up to $1 billion in talent, infrastructure and compute over five years to support the new lab, which will be based in the San Francisco Bay Area.
During the fireside chat, Ricks reflected on the painstaking work of drug discovery and AI's potential to transform the cycle of pharmaceutical invention.
Each small molecule discovery is like a work of art, he said. 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.
The lab will operate under a scientist-in-the-loop framework, where agentic wet labs are tightly connected to computational dry labs in a continuous learning system. This framework aims to enable experiments, data generation and AI model development to continuously inform and improve one another.
Machines are made to work day and night to solve this problem, Ricks said.
The co-innovation lab builds on Lilly's previously announced AI supercomputer - the biopharma industry's most powerful AI factory, an NVIDIA DGX SuperPOD with DGX B300 systems - which will train large-scale biomedical foundation and frontier models for drug discovery and development.
By integrating AI into drug discovery, Ricks explained, pharmaceutical researchers can rapidly simulate a massive number of possible molecules, test them at scale in silico and filter out promising candidates. The next challenge is to find more biological targets using AI.
The holy grail is that you put those two things together, and we can model the whole system at once, Ricks said.
Huang and Ricks also discussed Lilly's long history of harnessing computing for pharmaceutical research - and how diseases of the aging brain are the next frontier for drug discovery.
I can't imagine a more worthy field to apply computer science to, Huang said. Hopefully we can bend the arc of history.
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 some of the recent advancements, Huang raised a toast at J.P. Morgan Healthcare 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 J.P. Morgan Healthcare Conference. The honorees included:
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, which developed Pearl, a protein and small molecule structure prediction model.
Chris Gibson and Najat Khan, chairman and CEO, respectively, of Recursion, which developed 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, which was a major collaborator in the development of Evo 2, part of the Evo family of DNA language models.
Max Jaderberg, president of Isomorphic, which is extending the capabilities of AlphaFold, the defining family of protein structure and interaction models.
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, which developed the Chai family of generative AI models for molecular structure prediction and design.
Tom Miller, cofounder and CEO of Iambic Therapeutics, developer of the NeuralPLexer model family for flexible, accurate and fast structure prediction for proteins and small molecules.
Alex Rives, head of science at Biohub, which created the ESM family of leading protein language models.
Alex Zhavoronkov, CEO of Insilico Medicine, which built Pharma.AI, an integrated model suite spanning target discovery, generative chemistry and clinical prediction.
At J.P. Morgan Healthcare, NVIDIA also announced a major expansion of the NVIDIA BioNeMo platform for AI-driven biology and drug discovery with tools including:
NVIDIA Clara open models for predicting RNA structures and ensuring AI-designed drugs are practical to synthesize.
BioNeMo Recipes to accelerate and scale biological foundation model training
