AI-powered robotic systems perform surgery, biological simulations design novel drugs and virtual healthcare assistants handle patient questions. Are these scenes from a futuristic hospital? Nope – all are live demonstrations at the Nvidia GPU Technology Conference (GTC) 2025 in San Jose, California this week.
The convergence of AI with healthcare was only one of several topics discussed at the event, which attracted 25,000 attendees. Across 1,000 sessions, 2,000 speakers and almost 400 exhibitors, visitors could learn about the latest boundary-pushing achievements courtesy of physical AI, agentic AI and scientific discovery in such fields as climate research, cybersecurity, autonomous vehicles, humanoid robotics, healthcare delivery and personalized medicine.
“Biology is the largest unsolved problem that AI is now beginning to decipher,” Nvidia CEO Jensen Huang noted during his keynote address.
AI’s Role in Drug Discovery and Clinical Trials
Sessions at GTC explored the expanding role of AI in drug discovery and clinical trials. Discussions focused on how AI-powered platforms are enhancing molecular modeling, predicting drug interactions and improving trial recruitment through real-time data analysis.
Experts noted that AI is helping to accelerate the preclinical development process, with some AI-driven startups identifying potential drug candidates in significantly shorter timeframes than traditional methods.
Another session examined AI’s ability to streamline patient recruitment for clinical trials. Panelists discussed the use of generative AI models and real-world patient data to improve patient matching, with the goal of reducing recruitment bottlenecks and improving trial efficiency.
Transforming Microscopes with AI
Manu Prakash, PhD, Co-Founder of microscopy company Cephla and an Associate Professor at the Woods Institute for the Environment at Stanford University, displayed a low-cost AI-powered microscope designed to help health workers detect malaria and other diseases rapidly in communities around the world.
“This is the first machine that can do something like this in real time,” he said.. “One of the phenomenal aspects of this is we can train it not just for malaria — we can train it for any disease.”
Other organizations have begun training the system to identify sickle cell disease and tuberculosis.
“Sometimes, instruments with a little bit of intelligence can go an astronomical distance,” Prakash said.
Surgical Robotics and AI-Powered Diagnostics
A session on robotic-assisted surgery showcased how AI is being used to enhance precision in minimally invasive procedures, with new technology reducing processing latency for real-time surgical guidance. Nvidia highlighted its own Holoscan platform, which enables real-time AI-assisted decision-making in the operating room.
Discussions on AI-driven diagnostics highlighted the growing complexity of health data and the need for sophisticated computational tools. One session explored how AI is helping to analyze genomics and imaging data, assisting clinicians in detecting mutations, assessing treatment options and personalizing therapies.
Personalized Healthcare and AI Ethics
AI’s role in enabling precision medicine was a recurring theme. Sessions examined how AI-powered genomic analysis is advancing personalized treatment strategies.
As AI adoption increases, panelists also addressed the need to ensure patient privacy and avoid algorithmic biases so that healthcare outcomes are equitable.
Frances Arnold, PhD., Nobel Laureate in Chemistry from the California Institute of Technology, joined a panel on protein engineering and responsible innovation. The session examined how AI-driven structure prediction and protein design are advancing molecular engineering capabilities
Biology goes Digital
Nvidia discussed its recently announced Evo 2, the world's largest biology foundation model, trained on 9 trillion nucleotides, the building blocks for RNA and DNA.
Such models allow researchers to understand biological systems with unprecedented precision, potentially revolutionizing how scientists discover and develop new therapeutic approaches.
“We are starting to experience some exponential levels of biology intelligence by being able to represent biology in a computer,” said Kimberly Powell, Vice President of Healthcare and Life Sciences at Nvidia, during her keynote address.