Isomorphic Labs is reimagining the drug discovery process with an AI-first approach. At the heart of this work is a new way of thinking about biology. Max Jaderberg, chief AI officer, and Sergei Yakneen, chief technology officer at Isomorphic Labs joined the AI Podcast to explain why they look at biology as an information processing system. “We’re building generalizable AI models capable of learning from the entire universe of protein and chemical interactions,” Jaderberg said. “This fundamentally breaks from the target-specific, siloed approach of conventional drug development.” Isomorphic isn’t just working to optimize existing drug design workflows but completely rethinking how drugs are discovered — moving away from traditional methods that have historically been slow and inefficient. By modeling cellular processes with AI, Isomorphic’s teams can predict molecular interactions with exceptional accuracy. Their advanced AI models enable scientists to computationally simulate how potential therapeutics interact with their targets in complex biological systems. Using AI to reduce dependence on wet lab experiments accelerates the drug discovery pipeline and creates possibilities for addressing previously untreatable conditions. And that’s just the beginning. Isomorphic Labs envisions a future of precision medicine, where treatments are tailored to an individual’s unique molecular and genetic makeup. While regulatory hurdles and technical challenges remain, Jaderberg and Yakneen are optimistic and devoted to balancing ambitious innovation with scientific rigor. “We’re committed to proving our technology through real-world pharmaceutical breakthroughs,” said Jaderberg. Time Stamps 1:14 – How AI is boosting the drug discovery process. 17:25 – Biology as a computational system. 19:50 – Applications of AlphaFold 3 in pharmaceutical research. 23:05 – The future of precision and preventative medicine. You Might Also Like…  NVIDIA’s Jacob Liberman on Bringing Agentic AI to Enterprises Agentic AI enables developers to create intelligent multi-agent systems that reason, act and execute complex tasks with a degree of autonomy. Jacob Liberman, director of product management at NVIDIA, joined the NVIDIA AI Podcast to explain how agentic AI bridges the gap between powerful AI models and practical enterprise applications. Roboflow Helps Unlock Computer Vision for Every Kind of AI Builder Roboflow’s mission is to make the world programmable through computer vision. By simplifying computer vision development, the company helps bridge the gap between AI and the people looking to harness it. Cofounder and CEO Joseph Nelson discusses how Roboflow empowers users in manufacturing, healthcare and automotive to solve complex problems with visual AI. How World Foundation Models Will Advance Physical AI With NVIDIA’s Ming-Yu Liu AI models that can accurately simulate and predict outcomes in physical, real-world environments will enable the next generation of physical AI systems. Ming-Yu Liu, vice president of research at NVIDIA and an IEEE Fellow, explains the significance of world foundation models — powerful neural networks that can simulate physical environments.