Inside Helical: Bio Foundation Models, Virtual Cells, and the Future of AI-Native Drug Discovery

🎙 Tech and Drugs – Episode #11Inside Helical: Bio Foundation Models, Virtual Cells, and the Future of AI-Native Drug DiscoveryThis week I sat down with Rick Schneider, co-founder and CEO of Helical, a Luxembourg-based startup on a mission to democratize bio foundation models.Rick and his team are building something ambitious: an open, AI-native platform that lets pharma and biotech teams actually use large DNA, RNA, and single-cell foundation models, without needing their own supercomputer or an internal army of ML researchers. From training cutting-edge mRNA models on the Luxembourg HPC MeluXina to releasing beginner-friendly open-source tools, Helical is shaping the next generation of AI for science.What we cover:✔️ Rick’s journey from “almost doctor” to engineer, AI specialist, and now biotech founder✔️ What bio foundation models really are… and why unlabeled sequencing data changes the game✔️ Why one model will never solve all of biology, and why Helical is proudly model-agnostic✔️ How the field is inching toward a “virtual cell” built by combining multimodal model embeddings✔️ Pharma’s real bottlenecks: data scarcity, batch effects, validation culture, and… organizational speed✔️ How Helical enables lab-in-the-loop workflows without operating a lab themselves✔️ The explosion of new bio models, and how Helical helps teams evaluate what’s hype vs. useful✔️ Why shifting more hypothesis testing in silico could finally compress drug discovery timelinesIf you’re curious about where bio foundation models are heading, how pharma should rethink its AI stack, or what it means to build a truly AI-native biotech platform, this conversation with Rick is packed with insights.