Latest Post
May 13, 2026
Peak Performance or Just Noise?
Examining statistical methods for comparing ML model performance in blind challenges — which approaches give reliable leaderboard rankings while accounting for noise?
Read More →Examining statistical methods for comparing ML model performance in blind challenges — which approaches give reliable leaderboard rankings while accounting for noise?
Read More →An open science effort to improve prediction of safety and toxicity for small molecules through high-quality data, mechanistic insight, and machine learning.
Benchmarking activity and structure prediction on a large dataset of human PXR-active compounds, with both an activity track and a structure track.
Predictive models and experimental datasets from OpenADMET blind challenges and data generation efforts.
Updates on blind challenges, new models, datasets, and lessons learned from the OpenADMET community.
Science seminars, challenge webinars, and workshop recordings from the OpenADMET community.
See the Open Molecular Software Foundation team and our Governing Board.
A perspective on how blind challenges can help the field honestly evaluate and advance predictive modeling in drug discovery.