This time, I sit down with Jakob Zeitler, an expert in causal inference and machine learning, to explore how AI-driven experimentation is reshaping drug R&D. If you’ve ever wondered how active learning can revolutionize drug discovery, or why machine learning in pharma is both promising and problematic, this one’s for you.

🔹 Jakob’s Journey: From early coding to cutting-edge research at Oxford University and Matterhorn Studio

🔹 Pharma’s Efficiency Problem: Why drug development keeps getting more expensive and how AI might fix it

🔹 Active Learning 101: How AI decides which experiment to run next (smarter, not harder!)

🔹 Machine Learning in Drug Discovery: Where it works, where it fails, and why we need more than one “AlphaFold”

🔹 "Lab-in-the-Loop": The future of AI-powered experimentation in pharma

🔹 Adopting AI in R&D" Practical steps for pharma leaders looking to integrate active learning today