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Healthcare and Life Sciences Leaders Build on NVIDIA to Advance Drug Discovery and Expand Patient Care

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Healthcare and Life Sciences Leaders Build on NVIDIA to Advance Drug Discovery and Expand Patient Care

GTC Berlin—NVIDIA today announced collaborations with leading global healthcare and research organizations to advance protein design — including through a newly released open model, RFD4-Proteina — accelerate drug discovery and bring greater precision to cancer care.

Life sciences researchers must search vast biological design spaces and aim to shorten the cycle between computational design and laboratory testing to discover new medicines. Cancer care teams face a different challenge: translating complex imaging and treatment data into precise plans for each patient.

NVIDIA open models, accelerated computing and physical intelligence can help experts evaluate more possibilities faster, from designing new proteins to planning adaptive radiotherapy.

“Agentic and physical AI are opening new possibilities across medicine, from designing proteins and powering autonomous laboratories to improving personalized cancer care,” said Kimberly Powell, vice president of healthcare at NVIDIA. “Together with healthcare and life science leaders, we’re accelerating scientific discovery and advancing more precise, accessible care around the world.”

NVIDIA and the UW Institute for Protein Design Introduce RFD4-Proteina
Proteins are molecular tools that perform many of life’s essential tasks, and designing new versions could open paths to new medicines, diagnostics and industrial applications. But finding a protein capable of performing a designed function requires searching an immense range of possible designs.

NVIDIA and the UW Medicine Institute for Protein Design are debuting RFD4-Proteina, a new NVIDIA BioNeMo™ open model that combines programmable protein design with search capabilities.

The model generates targeted protein designs, enabling scientists and agents to search and refine designs using molecular inputs, constraints and scoring objectives.


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