Bristol Myers Squibb Expands Nvidia-Powered AI Computing Infrastructure

Bristol Myers Squibb (BMS) has announced plans to expand its computing infrastructure through the deployment of an NVIDIA DGX SuperPOD equipped with DGX Vera Rubin NVL72 systems. According to the company, the addition will provide what it describes as the most powerful and energy-efficient single-owned NVIDIA infrastructure in the life sciences sector.

The expanded system is intended to increase the computational resources available to BMS scientific and research teams. The company said the Vera Rubin architecture can deliver up to ten times greater performance per megawatt than its predecessor, allowing larger and more sophisticated artificial intelligence workloads to be run without a proportional increase in energy consumption.

The announcement builds on a collaboration between BMS and Nvidia that began nearly three years ago when BMS first introduced NVIDIA DGX SuperPOD infrastructure to support research and development activities. The latest expansion is intended to support the growing use of AI across the company’s scientific programs in oncology, hematology, cardiovascular disease, immunology and neuroscience.

Greg Meyers, BMS’ Chief Digital and Technology Officer, said the company’s investment in artificial intelligence is producing results in both its pipeline and operations. He stated, “BMS has made a deliberate bet on AI, and we are beginning to see it pay off in our pipeline and operations.”

BMS said it has incorporated AI into multiple stages of medicine discovery and development. The company cited the use of AI agents for target identification and validation, noting that these tools save scientists weeks of manual work and allow greater focus on hypothesis testing and scientific decision-making.

The company also highlighted its “Predict First” methodology, in which AI-generated predictions are used to inform experimental design before laboratory work begins. According to BMS, AI now informs the design of every small-molecule program and the majority of its large-molecule programs. These efforts form part of a broader approach aimed at creating an integrated AI-powered learning system that spans target identification through clinical proof of concept and helps scientists make higher-confidence decisions at each stage.

Robert Plenge, Executive Vice President and Chief Research Officer at BMS, said the new infrastructure is intended to help researchers spend less time on manual tasks and more time on work that requires human judgment. He also said the goal is to increase the probability that the programs advanced by the company are the right ones.

BMS described the expanded agreement as a step toward its vision of “hybrid intelligence,” a model in which AI co-scientists and human researchers operate in close coordination. Under this approach, AI systems handle the execution of complex, data-intensive tasks while scientists focus on direction, interpretation, and decisions requiring human expertise.

The Vera Rubin cluster will serve as the computational backbone for that strategy. BMS said it will support the development of next-generation foundation models trained on the company’s proprietary data and may draw on capabilities from BioNeMo, Nvidia’s platform for biological AI. The infrastructure is also expected to power agentic workflows that allow researchers to evaluate hypotheses at a scale that BMS said would have been unachievable just a few years ago.

A BMS spokesperson shared that the company views these investments as complementary components of a broader AI strategy. In addition to its work with Nvidia, BMS has recently entered AI-related collaborations involving Anthropic’s Claude and Microsoft. Elsewhere, Nvidia has also expanded its presence in the pharmaceutical sector through initiatives with companies including Lilly, while Roche and Qiagen have announced AI-related efforts involving Nvidia technology.

NVIDIA continues to strengthen its role in healthcare innovation as Bristol Myers Squibb expands its AI computing infrastructure using advanced technologies from the leading AI chipmaker. The investment is designed to accelerate scientific research, improve computational capabilities, and support the development of next-generation therapies through artificial intelligence and high-performance computing.

NVIDIA Powers Bristol Myers Squibb’s AI Expansion

By leveraging NVIDIA accelerated computing platforms, Bristol Myers Squibb aims to process massive biomedical datasets more efficiently and reduce the time required for complex research workflows. AI-powered infrastructure enables scientists to analyze genomic information, identify promising drug candidates, and simulate biological processes with greater speed and accuracy.