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CEOs NVIDIA & Lilly: AI & Drug Discovery Blueprint

CEOs NVIDIA & Lilly: AI & Drug Discovery Blueprint

January 14, 2026 Lisa Park Tech

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)

Table of Contents

  • VantAI, Boltz, and Genesis Molecular ‌AI: Current Status (January 14, 2026)
    • VantAI and ‍the Neo Model Family
    • Boltz and ​Open-Source Biomolecular Models
    • Genesis Molecular AI ⁤and ‍Protein design

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.

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