aiqbench takeMachine Learning

This article details Leash Bio's breakthrough in managing DNA Encoded Libraries (DELs) to generate high-quality, reproducible datasets for training AI models in drug discovery. The core focus is on leveraging this specific biological data to enable "lab-in-the-loop" simulations and train AI agents capable of verifiable scientific reasoning in chemistry. By addressing the notorious noise in DEL assays, the work directly advances the application of machine learning to solve complex protein-ligand binding problems.

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Lab-in-the-Loop at Compute Speed — Ian Quigley, Leash Bio

Latent SpaceOctober 14, 20264 min read

How Leash Bio tamed DELs, the assay that traumatizes everyone, and used the data to catch cheating models. And why that same data is perfect for AI agents learning to think like chemists.

A few years ago I stumbled upon Leash Bio’s Substack, and was hooked. Be it their Kaggle competition that showed that no, we really haven’t solved protein-ligand binding, or their crazy discovery that knowing a molecule’s author is perhaps all you need to know to predict how good it is. Their substack — or at least Owl Posting’s1 deep dive on them — should be required reading for any scientist trying to do chemistry with AI. So I was super excited to finally…

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