Today, I’m joined by Héctor García Martín, a Staff Scientist at Lawrence Berkeley National Laboratory. A pioneer in metabolic engineering and computational biology, Héctor has spent over a decade decoding microbial systems, everything from termite guts to genome-scale flux models, to unlock sustainable biomanufacturing.

Now, he’s leading the charge in self-driving labs: AI-powered, robotic systems that automate experiments, predict biological behavior, and accelerate the design of microbes that produce fuels, medicines, and materials.

In this episode, we’ll dive into why biology has traditionally proven so hard to engineer, how AI and robotics are changing that, and where this revolution is headed next. I hope you enjoy my discussion with Hector Garcia Martin.

01:12              Meet Hector Garcia Martin

12:47              Introduction to the Berkeley National Laboratory

14:42              Challenges in synthetic biology

17:21              How unpredictability complicates biomanufacturing

19:30              Self-driving labs at the nexus of AI, robotics, and biomanufacturing

22:23               How is AI integrated into optimize enzyme expression

28:01               Where is the market for self-driving labs?

28:47               The future of synthetic biology

32:24               The most exciting trends in AI-driven biomanufacturing

34:10               The expected impacts of self-driving labs on everyday life

35:28               Advice for aspiring scientists

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To dive deeper into the topic: 

• Synthetic Biology @ Labiotech
• European biotech: trends to watch in 2025
• The coming of age of European synthetic biology