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SAN FRANCISCO (AP) – Technology giant NVIDIA and pharmaceutical leader Eli Lilly and Company have unveiled plans for a pioneering artificial intelligence laboratory aimed at revolutionizing drug discovery through advanced computing and scientific collaboration.
The partnership, announced at the J.P. Morgan Healthcare Conference, involves a combined investment of up to $1 billion over the next five years to fund personnel, facilities and computing resources. This effort unites Lilly’s deep knowledge in biology, medicine and production with NVIDIA’s expertise in artificial intelligence and high-performance systems, creating a hub where experts from both fields will collaborate closely.
Situated in the San Francisco Bay Area, with operations set to launch in South San Francisco later this year, the facility will integrate Lilly specialists in scientific domains with NVIDIA’s AI developers and engineers. Their goal is to produce extensive datasets and sophisticated AI models that speed up the process of developing new treatments, relying on the NVIDIA BioNeMo platform as a foundational tool.
Artificial intelligence stands to reshape a high number of sectors, but its greatest potential lies in the context of life sciences, according to Jensen Huang, NVIDIA’s founder and chief executive. He described the initiative as a fresh approach to identifying potential drugs, where researchers can simulate enormous arrays of biological and chemical possibilities on computers before synthesizing any physical compounds.
David A. Ricks, Lilly’s chair and chief executive, highlighted the company’s long history of delivering transformative therapies over 150 years. He noted that merging Lilly’s extensive data and research insights with NVIDIA’s processing capabilities and AI development skills could fundamentally change how drugs are discovered. By fostering an innovative, startup-like atmosphere with elite talent, the collaboration opens doors to advancements that surpass what either organization could accomplish independently.
At the outset, the project will develop an ongoing learning framework that links Lilly’s hands-on laboratory experiments with digital simulations, facilitating round-the-clock AI-supported research to aid scientists and chemists. This interactive setup ensures that testing, data collection and model refinement evolve together in real time.
Using vast computing power, high-volume data creation and the BioNeMo system, the teams plan to construct advanced AI models tailored for biological and chemical applications. This builds upon Lilly’s AI supercomputer, introduced last autumn as the most potent in its field, which excels at training expansive models to pinpoint, refine and verify novel compounds quickly and precisely. That system also bolsters innovations in production processes, medical imaging and intelligent AI tools.
The scope extends past initial discovery to include AI applications in patient trials, manufacturing and business functions, incorporating diverse data models, autonomous AI systems, automation and virtual replicas. In particular, AI-driven robotics within the setup will boost Lilly’s ability to produce sought-after drugs and improve supply chain stability. Using NVIDIA Omniverse tools and RTX PRO Servers, the company can simulate and refine entire production networks virtually to anticipate and address issues prior to real-world implementation.
NVIDIA’s commitment to open-source AI equips businesses with essential models, datasets and software for practical applications, while its Inception program offers emerging companies guidance, along with access to NVIDIA’s technologies and resources. On Lilly’s side, the TuneLab platform grants biotechnology firms entry to curated AI models for drug development, drawn from years of proprietary information, and will soon incorporate NVIDIA Clara open models for healthcare and life sciences workflows.
This co-innovation lab will also benefit the broader networks of startups and academics connected to both companies by providing specialized knowledge and substantial computing support, positioning the effort to advance global progress in biomedical research.
