Catalio Conversations

Explore the future of drug development with AI that could compress decades of research into just years! Joining us at Catalio Conversations is Tom Miller, co-founder of Iambic, where he reveals how combining cutting-edge neural models with high-throughput experimentation is rewriting the rules of pharmaceutical innovation – think a cancer drug designed, optimized, and FDA-approved in under two years!Tom's journey from Caltech professor to drug discovery entrepreneur – alongside co-founder Fred Manby – offers a masterclass in turning academic breakthroughs into real-world medicines. From Iambic's game-changing Neuroplexer model that predicts exactly how drugs bind to proteins, to their landmark cancer candidate IM1363, this episode pulls back the curtain on what genuinely AI-powered drug discovery looks like. And with strategic partnerships with Lundbeck, Revolution Medicines, and Takeda already in place, Iambic isn't just promising the future – they're building it.Perfect for life sciences leaders, AI enthusiasts, and anyone curious about the next frontier of medicine, this episode reveals the paradigm shifts redefining what's possible in pharma. Don't miss this front-row seat to the biggest leap in pharmaceutical history – the next blockbuster cancer drug might already be designed by an algorithm, waiting to save your life.Timestamped Summary: 00:00 - Introduction to Catalio Conversations and guest Tom Miller00:29 - Tom’s journey from Caltech professor to drug innovator01:28 - Collaboration with co-founder Fred Manby01:55 - Balancing scientific integrity with entrepreneurial agility02:21 - Lessons from early Iambic experiments03:13 - AI prediction and high-throughput experimentation03:43 - Defining drug targets and designing molecules04:11 - Neuroplexer in predicting drug-protein binding05:06 - Multi-property optimization in discovery06:24 - Rapid development of cancer candidate IM136306:49 - AI reducing drug development timelines07:16 - Industry impact of AI-designed medicines07:59 - Partnerships with Lundbeck and Revolution Medicines08:55 - Building credibility through collaborations09:21 - Genuine AI transformation vs. superficial branding09:45 - Scaling advantage of AI-powered discovery10:36 - AI’s potential in biological complexity11:31 - Future of AI in drug development12:24 - Iambic’s identity: AI platform or drug company?13:21 - Future goals for Iambic and industry impact14:13 - Promising targets like transcription factors14:42 - Closing remarks and encouragement for innovation

Unlock the future of drug discovery with AI-powered robots that could revolutionize science as we know it! Joining us at Catalio Conversations is Michelle Lee, CEO of Medra AI, where she reveals how combining AI & robotics is creating the world's most advanced autonomous labs – think 100 robots working overnight to accelerate cures for disease! Michelle’s journey from chemical engineering and AI research to leading Medra’s groundbreaking "physical AI scientists" offers a blueprint for turning science fiction into reality. Looking ahead, Michelle envisions a world where entire drug pipelines are fully autonomous, enabling any scientist to create life-changing medicines. Perfect for life sciences leaders, AI enthusiasts, as well as tech-curious or business-curious viewers eager to see what’s next, this episode reveals the seismic shifts that will define the next decade of scientific discovery. Don’t miss this glimpse into the autonomous labs of tomorrow – because the next genetic breakthrough could come from a robot, not a human.Timestamped summary:0:03 - Introduction: Welcome to Catalio Conversations0:31 - Michelle Lee's Journey: Discussing the realization of the need for AI and robotics in biology.1:00 - Alpha Fold Inspiration: The impact of Alpha Fold 2 on Michelle's vision.1:25 - Data Generation with Robotics: How robots can scale up experimentation.1:53 - Cultural Values at Medra: Insights from Michelle's diverse experiences.2:21 - Medra's Interdisciplinary Approach: Combining engineering, AI, and biology.3:13 - Physical AI Scientists: Differentiating from traditional lab automation.4:08 - Challenges in Data Generation: The need for more and better data.5:00 - Robotics in Experimentation: Solving data quantity and quality issues.5:54 - Real Lab Stories: How Medra improved data generation for a client.7:09 - Overcoming Skepticism: Transitioning from industrial to physical AI.8:00 - Early Challenges at Medra: Learning from initial business strategies.9:25 - Partnership Model: Medra's collaborative approach with clients.10:17 - Recognition by Genentech: Being named a partner in AI strategy.11:05 - Building Trust: Importance of fast communication and transparency.11:56 - Future of Labs: Vision for autonomous labs and their impact.12:43 - Empowering Scientists: Enabling scientists to start their own companies.13:10 - Quick Fire Questions: Myths and future bets in AI and life sciences.14:05 - Conclusion: Closing remarks and invitation to subscribe.