Bristol Myers Squibb (BMS) is expanding its investment in artificial intelligence by deploying NVIDIA's latest AI computing platform to accelerate drug discovery and development, becoming the first life sciences company to adopt the chipmaker's DGX SuperPOD powered by the new Vera Rubin architecture. The move reflects the growing role of high-performance AI infrastructure in pharmaceutical research, where companies are increasingly using advanced computing to shorten development timelines and improve the success rate of experimental medicines.
The deployment builds on a collaboration between BMS and NVIDIA that began nearly three years ago, when the pharmaceutical company first introduced an earlier-generation DGX SuperPOD into its research operations. The new system represents a significant upgrade in computing capability, enabling researchers to process substantially larger AI models while improving energy efficiency. According to NVIDIA, the Vera Rubin architecture delivers up to ten times greater performance per megawatt than the previous generation, allowing organisations to scale AI workloads without a proportional increase in power consumption.
BMS said the expanded computing capacity will support AI across its drug discovery and development programmes, including oncology, hematology, cardiovascular disease, immunology and neuroscience. Researchers expect the additional computational power to evaluate a much larger number of potential drug candidates during the early stages of development, helping identify promising compounds more quickly before they move into laboratory testing and clinical trials.
Robert Plenge, Chief Research Officer at Bristol Myers Squibb, said the enhanced infrastructure would allow the company to examine significantly more drug candidates than previously possible. He also noted that AI tools are already helping reduce the time required to produce medicines for clinical testing by around 20 to 30 percent, with further improvements anticipated as AI models continue to evolve. One experimental treatment for sickle cell disease currently in clinical development was identified through AI-enabled research, according to the company.
Greg Meyers, Chief Digital and Technology Officer at BMS, said the investment reflects the rapidly growing computing requirements created by larger AI models being deployed across the company's research organisation. He added that AI is now being used across all of the company's small-molecule drug programmes and the majority of its large-molecule research initiatives, making scalable infrastructure increasingly important.
The announcement comes as pharmaceutical companies worldwide continue to expand investments in AI infrastructure. Drugmakers are increasingly applying generative AI, machine learning and foundation models to identify biological targets, design new molecules, analyse clinical data and improve decision-making throughout the drug development process. While AI is not expected to replace laboratory research or clinical validation, it is increasingly viewed as a tool that can improve efficiency and reduce the time required to move promising therapies into human trials.
For NVIDIA, the partnership further strengthens its presence in the healthcare sector, where demand for specialised AI infrastructure continues to grow alongside enterprise adoption of generative AI. For Bristol Myers Squibb, the investment underscores how computing power is becoming a strategic asset in pharmaceutical innovation, with AI playing a larger role in helping researchers discover and develop new medicines more efficiently.