BMS is set to strengthen its AI-driven drug discovery capabilities through a new collaboration with NVIDIA, deploying a DGX SuperPOD powered by the company’s next-generation Vera Rubin AI computing platform.
The investment is designed to increase the company’s computational capacity, improve energy efficiency and support the development of more sophisticated research models across several therapeutic areas.
According to the company, this will provide the most powerful and energy efficient single owned NVIDIA infrastructure in the life sciences sector.
BMS stated that the Vera Rubin architecture can deliver up to 10 times greater performance per megawatt, enabling researchers to undertake larger AI workloads without a proportional increase in energy consumption.
Greg Meyers, Chief Digital and Technology Officer, BMS, commented: “We’re committed to translating AI into real outcomes for patients which requires infrastructure built to match that ambition.”
The investment builds on almost three years of collaboration supporting the company’s research and development activities and reflects the growing role of AI across oncology, haematology, cardiovascular disease, immunology and neuroscience.
The company reported that AI has already become integrated into several stages of medicine discovery. AI agents that automate target identification and validation were said to save scientists weeks of manual work, allowing more time for hypothesis testing and scientific decision making.
The company also highlighted its “Predict First” approach, in which AI-generated predictions inform experimental design before laboratory work begins. According to BMS, this approach now informs every small molecule programme and most large molecule programmes.
The strategy forms part of an integrated learning system that spans target identification through to clinical proof of concept and is intended to improve confidence in decisions throughout medicine development.
Robert Plenge, Executive Vice President and Chief Research Officer, BMS said: “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.”
BMS stated that the expanded AI infrastructure will underpin its vision of hybrid intelligence, in which AI systems work alongside researchers.
The expanded computing platform is expected to support the development of next generation foundation models trained on the company’s proprietary scientific data, alongside biological AI capabilities and agent-based research workflows.
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