Bristol Myers Squibb (BMS) announced an expansion of its compute infrastructure through the deployment of an Nvidia DGX SuperPOD with DGX Vera Rubin NVL72 systems.

According to the company, the move will give it the most powerful and energy-efficient single-owned Nvidia infrastructure in life sciences and builds on nearly three years of collaboration between BMS and Nvidia, while also extending a foundation that BMS first established when it deployed DGX SuperPOD infrastructure to support its research and development activities.^1,2

The Vera Rubin architecture delivers up to ten times greater performance per megawatt than its predecessor, allowing BMS to pursue more computationally intensive AI workloads across drug discovery without a proportional increase in energy consumption.¹ The cluster is also expected to support BMS's scientific programs across oncology, hematology, cardiovascular disease, immunology and neuroscience.

How is BMS already using AI?

BMS described two specific applications that illustrate its current approach. First, AI agents that automate target identification and validation save scientists weeks of manual work, redirecting human effort toward hypothesis testing and high-value scientific decisions.¹ Second, the company's "Predict First" methodology, in which AI-generated predictions shape experimental design before bench work begins, now informs the design of every small molecule program and the majority of its large molecule programs.

Together, these applications reflect what BMS describes as an integrated, AI-powered learning system that spans target identification through clinical proof of concept, with the goal of helping scientists make higher-confidence decisions at each stage of development.¹

"Drug discovery is a sequence of decisions made under uncertainty, and better decisions come from better evidence, faster," said Robert Plenge, executive vice president and chief research officer at Bristol Myers Squibb. "This infrastructure lets us learn from every experiment and every clinical readout to sharpen the next hypothesis, allowing BMS scientists to spend less time on manual work and more time on the questions that require human judgment. The goal isn't speed for its own sake; it's raising the probability that each program we advance is the right one."

What is the broader vision?

BMS framed the expanded infrastructure as central to what it calls a hybrid intelligence model, a way of working in which AI co-scientists and human researchers operate in close coordination. Under this model, AI systems handle the execution of complex, data-intensive tasks while scientists focus on direction, interpretation and decisions that require deep domain expertise.

The Vera Rubin cluster will serve as the computational backbone for that model, supporting the development of next-generation foundation models trained on BMS's proprietary data accumulated over decades.¹ The model will also draw on BioNeMo, Nvidia's platform for biological AI, and power the agentic workflows that allow researchers to evaluate hypotheses at a scale previously not achievable.

"BMS has made a deliberate bet on AI, and we are beginning to see it pay off in our pipeline and operations," said Greg Meyers, chief digital and technology officer at Bristol Myers Squibb. "Expanding our compute capabilities with Nvidia gives our researchers and teams across the business the scale they need to keep BMS at the leading edge of what AI can do for drug discovery and development."

Rory Kelleher, senior director of business development, healthcare and life sciences at Nvidia, noted that the partnership is designed to convert decades of proprietary scientific data into actionable intelligence. "With Nvidia Vera Rubin and BioNeMo Agent Toolkit, BMS has the ability to transform that enterprise scientific data into proprietary intelligence and give agents domain-specific tooling that help scientists explore biology, design molecules and evaluate hypotheses at unprecedented scale," Kelleher said.

Sources

1. Bristol Myers Squibb to Build the Most Powerful AI Factory in Life Sciences with Nvidia Bristol Myers Squibb July 20, 2026 https://news.bms.com/news/details/2026/Bristol-Myers-Squibb-to-Build-the-Most-Powerful-AI-Factory-in-Life-Sciences-with-NVIDIA/default.aspx
2. Computational Science Accelerates Research Innovation at Bristol Myers Squibb Nvidia Date Accessed July 20, 2026 https://www.nvidia.com/en-us/case-studies/computational-science-accelerates-research-innovation-at-bristol-myers-squibb/