Upcoming Webinar — Improving Pose Prediction Models for Drug Discovery

 

A recent study challenges the current benchmarks in protein–ligand pose prediction. While machine learning has revolutionized this field, many models still fall short of capturing the true biological relevance of protein–ligand interactions.

 

This webinar will present new perspectives on how to evaluate and improve pose prediction models more rigorously.

 

The authors will share their findings, discuss implications for drug discovery, and propose a more robust framework for evaluating pose prediction models.

 

⏰Tuesday 9^th September 2025 at 15:00 (BST)/ 16:00 (CEST)/ 10:00 (EDT) 

 

REGISTER

 

Who should attend:

• Drug Discovery Researchers;
• Data scientists;
• Scientists in computational biology, cheminformatics, and structural biology.

 

Speakers:

• David Errington, Senior AI Research Scientist from Recursion.
• Cedric Bouysset, Cheminformatics Research Scientist from Recursion.