From Wet Lab to RL Env: 10,000 Drug-Discovery Campaigns in a Weekend — Ian Quigley, Leash Bio
About this episode
From the show’s notesFrom a four-billion-measurement Kaggle competition to models that recognize a molecule’s chemist, Leash Bio is testing what AI actually learns about chemistry. Co-founder and CEO Ian Quigley joins Brandon Anderson and RJ Honicky to explain how Leash makes DNA-encoded libraries (DELs) produce clean, reproducible protein–small-molecule binding data—and why collecting the right experiments matters as much as choosing a model.
We go deep on hidden shortcuts in public datasets, Hermes’ comparison with Boltz, and the protein mutations that expose memorization. Ian explains how Leash’s measured chemical landscapes can become a sandbox for reasoning agents, with rapid experimental feedback and thousands of medicinal chemistry campaigns. We also examine the limits of DELs, moving hits toward medicines, the economics of AI drug discovery, and the experimental bottlenecks that still need solving.
Read the show’s notes in full
We discuss: • How DNA-encoded libraries use barcodes and sequencing to screen millions of molecules • Catching DNA-binding artifacts with multiple barcodes per molecule • Why Leash prioritizes reproducible measurements across many protein targets • The BELKA Kaggle competition: four billion measurements, around 2,000 teams, and no better than chance on an unseen chemical library • Clever Hans in ChEMBL: learning who made a molecule instead of the chemistry • Hermes, simple baselines, careful data splits, and comparisons with Boltz • Activity cliffs, engineered protein mutations, and models that memorize protein “nicknames” • Agents reasoning about structure–activity relationships in plain English • More than 10,000 medicinal chemistry campaigns in a weekend • Going from DEL hits to mouse PK/PD, and the case for pills on difficult targets • The Kosuri paradox: if you can collect the data, why do you need the model? • Experimental know-how, detecting misfolded proteins, and scaling purification
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Show Notes: latent.space/publish/post/22031…
Ian Quigley — Leash Bio
• LinkedIn: linkedin.com/in/iquigley
• Leash Bio:
• Leash blog:
