Global AI computing leader and pharmaceutical giant establish first-of-its-kind co-innovation laboratory in San Francisco Bay Area combining computational power, biological expertise, and physical AI systems.

San Francisco: NVIDIA Corporation and Eli Lilly and Company announced on January 2026, during the J.P. Morgan Healthcare Conference, the establishment of a groundbreaking AI co-innovation laboratory representing one of the pharmaceutical industry's largest disclosed artificial intelligence investments. The companies will jointly invest up to USD1 billion over five years in talent recruitment, computing infrastructure, and research operations to address fundamental challenges in drug discovery, clinical development, and pharmaceutical manufacturing. The Bay Area facility will co-locate Lilly's domain experts in biology, chemistry, and medicine with NVIDIA's leading AI researchers, model builders, and infrastructure engineers, creating a multidisciplinary team operating in a startup-style environment designed to foster breakthrough innovation unachievable through traditional pharmaceutical research paradigms.

The co-innovation lab's infrastructure will be built upon NVIDIA's BioNeMo platform an AI framework specifically designed for drug discovery applications and leverages next-generation NVIDIA Vera Rubin computing architecture to provide unprecedented computational power for the pharmaceutical industry. The collaboration will initially focus on creating continuous learning systems that tightly integrate Lilly's "agentic wet labs" (robotics-enabled physical experimentation facilities) with computational "dry labs" (AI modeling environments), enabling 24/7 AI-assisted experimentation operating in scientist-in-the-loop frameworks. This closed-loop system allows experimental results to continuously inform and improve AI models, while AI predictions guide subsequent experiments, dramatically compressing drug discovery timelines. Beyond drug discovery, the partnership will explore applying physical AI, robotics, and digital twin technologies across clinical trial design, manufacturing optimization, supply chain management, and commercial operations, potentially transforming pharmaceutical value chains end-to-end through AI integration.

According to Jensen Huang, Founder and Chief Executive Officer, NVIDIA, "AI is transforming every industry, and its most profound impact will be in life sciences. NVIDIA and Lilly are bringing together the best of our industries to invent a new blueprint for drug discovery one where scientists can explore vast biological and chemical spaces in silico before a single molecule is made. Through this collaboration, we're building a continuous learning system that turns science into engineering, enabling researchers to explore billions of molecular possibilities computationally before running a single physical experiment."

According to David A. Ricks, Chairman and Chief Executive Officer, Eli Lilly, "For nearly 150 years, we've been working to bring life-changing medicines to patients. Combining our volume of data and scientific knowledge with NVIDIA's computational power and model-building expertise could reinvent drug discovery as we know it. By bringing together world-class talent in a startup environment, we're creating the conditions for breakthroughs that neither company could achieve alone. This partnership represents Lilly's commitment to harnessing artificial intelligence not just as a tool, but as a fundamental transformation of how we discover, develop, and deliver medicines to patients worldwide."

According to TechSci Research, the NVIDIA-Lilly AI co-innovation lab exemplifies pharmaceutical industry strategic evolution toward computational-first drug discovery paradigms fundamentally reshaping R&D economics, timelines, and success probabilities. The USD1 billion five-year investment magnitude among the industry's largest single AI commitments reflects recognition that artificial intelligence represents not merely incremental efficiency improvement but transformational capability enabling exploration of chemical and biological search spaces exponentially larger than traditional experimental approaches permit. Traditional small molecule drug discovery involves screening millions of compounds through iterative synthesis-testing cycles requiring years and hundreds of millions of dollars, with >90% of candidates failing in clinical development. AI-enabled virtual screening can evaluate billions of molecular structures computationally in weeks, prioritizing synthesis efforts toward candidates with optimized predicted properties across efficacy, safety, manufacturability, and pharmacokinetic parameters dramatically improving development efficiency.

The partnership's emphasis on creating "continuous learning systems" integrating physical wet lab experimentation with computational modeling addresses pharmaceutical AI's critical challenge: model accuracy depends fundamentally on training data quality and relevance, yet existing datasets often lack coverage of novel chemical spaces or biological contexts central to breakthrough drug discovery. By tightly coupling AI predictions with robotic experimental validation in closed-loop frameworks, the collaboration generates proprietary datasets specifically designed to improve model performance on Lilly's therapeutic targets and chemical series creating competitive moats difficult for rivals to replicate without similar integrated infrastructure. The "agentic AI" component suggests autonomous systems capable of hypothesis generation, experimental design, result interpretation, and iterative refinement with minimal human intervention potentially enabling continuous experimentation operating 24/7 at scales impossible with human-dependent workflows.

The collaboration's extension beyond drug discovery into manufacturing, clinical operations, and supply chain optimization through digital twin technologies and physical AI represents recognition that pharmaceutical value chain transformation requires holistic approaches rather than point-solution deployments. NVIDIA Omniverse-powered digital twins enabling virtual simulation and optimization of manufacturing lines before physical implementation can dramatically reduce production ramp timelines, minimize costly manufacturing failures, and enhance supply chain resilience critical capabilities given recent pharmaceutical supply disruptions and surging demand for complex biologics and obesity treatments straining manufacturing capacity. The partnership structure combining Lilly's proprietary biological and chemical data, therapeutic area expertise, and regulatory knowledge with NVIDIA's computing infrastructure, AI model architectures, and engineering talent creates symbiotic value generation where neither company could achieve equivalent outcomes independently. TechSci Research anticipates this high-profile collaboration will catalyze similar pharmaceutical-AI company partnerships, accelerating industry-wide adoption of computational drug discovery while potentially fragmenting the landscape between companies accessing leading AI capabilities versus those relying on traditional approaches, with widening performance gaps favoring AI-enabled competitors.