CEOs NVIDIA & Lilly: AI & Drug Discovery Blueprint
- NVIDIA and Lilly are putting together "a blueprint for what is possible in the future of drug revelation," NVIDIA founder and CEO Jensen Huang told attendees at a...
- The conversation - which took place during the annual J.P.Morgan Healthcare Conference in San Francisco - focused on the announcement of a first-of-it's-kind AI co-innovation lab by NVIDIA...
- "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.
NVIDIA and Lilly are putting together ”a blueprint for what is possible in the future of drug revelation,” 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-it’s-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 progress 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
VantAI, Boltz, and Genesis Molecular AI: Current Status (January 14, 2026)
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As of January 14, 2026, VantAI, Boltz, and Genesis Molecular AI remain active companies in the rapidly evolving field of biomolecular AI, each focused on developing models for co-folding and design of biological molecules. Recent developments indicate continued investment and expansion within the sector, though specific details regarding each company’s progress vary.
VantAI and the Neo Model Family
VantAI, led by CEO Ach Carpenter, continues to develop its Neo model family.The Neo models are designed for co-folding and design across all biological molecules. VantAI announced a Series B funding round of $75 million on November 15, 2025, according to a press release on their official website,to accelerate the development and commercialization of the Neo platform. This funding will be used to expand the model’s capabilities and broaden its applications in drug discovery and materials science.
Detail: VantAI’s approach focuses on leveraging advanced machine learning techniques to predict the structure and function of complex biomolecules, enabling researchers to design novel proteins and therapies. The Neo platform aims to address limitations in existing methods by providing a more accurate and efficient way to model biomolecular interactions.
Example: In December 2025, VantAI published a peer-reviewed study in Nature biotechnology demonstrating the Neo model’s ability to accurately predict the structure of a previously unsolved protein complex, as reported by Nature Biotechnology.
Boltz and Open-Source Biomolecular Models
Boltz, under the leadership of CEO Gabriele Corso, maintains its position as a key contributor to the open-source biomolecular modeling community. Boltz is known for creating a well-established family of open-source biomolecular models. On January 5, 2026, Boltz released version 3.0 of its flagship model, “OpenFold,” as detailed in a blog post on the Boltz website, featuring improved accuracy and speed.
Detail: Boltz’s commitment to open-source development fosters collaboration and accelerates innovation in the field. The OpenFold models are widely used by researchers and developers worldwide, providing a valuable resource for biomolecular modeling and simulation.
Example: The National Institutes of Health (NIH) announced on December 20,2025,that it would be incorporating OpenFold 3.0 into its research infrastructure, according to an NIH press release, citing its potential to enhance drug discovery efforts.
Genesis Molecular AI and Protein design
Genesis Molecular AI, with Evan Feinberg as CEO, continues to focus on protein design. Genesis Molecular AI announced a partnership with pharmaceutical company, NovaPharm, on December 10, 2025, as stated in a Genesis Molecular AI press release, to develop novel protein therapeutics for cancer treatment. The collaboration will leverage Genesis Molecular AI’s protein design platform to create targeted therapies with improved efficacy and safety profiles.
Detail: Genesis Molecular AI’s technology utilizes generative AI to design proteins with specific properties and functions. This approach allows for the creation of proteins that are tailored to address specific therapeutic targets.
Example: NovaPharm invested $30 million in Genesis Molecular AI as part of the partnership agreement, according to NovaPharm’s investor relations page, demonstrating confidence in the company’s technology and potential.