Scaling Blind Challenges: A New Partnership with Radial and the Astera Institute
We are excited to announce that OpenADMET has received new grant funding from Radial, the life sciences division of the Astera Institute.
Latest
OpenADMET’s CYP challenge is underway
The heme-coming ball has begun
Do Our CYP Structural Alerts Actually Work?
Medicinal chemistry groups frequently rely on mental lists of structural alerts to predict CYP inhibition, yet these heuristics are rarely tested against real data. What happens when we evaluate these alerts using 7,800 experimental measurements?
Throwing Everything AND the Kitchen Sink at CheMeleon
We attempted to improve the CheMeleon foundation model. We were ultimately unsuccessful, but we learned valuable lessons about foundational training along the way.
Announcing OpenADMET’s CYP inhibition blind challenge
Who will be the Heme-coming queen?
Model, take the wheel! Part II: multi-fidelity, cost-aware active learning
We extend our previous active learning analysis to choose not just which compound to test, but which assay to run. Utilizing both primary screens and full dose-response measurements cuts the cost of finding actives by more than half, without costing the model any accuracy.
OpenADMET Quarterly Newsletter Q2 2026
Our quarterly newsletter detailing our progress, goals and priorities.
It’s the End of the PXR Challenge as We Know It (and I feel fine)
Announcing the results of the PXR Blind Challenge — and the public release of the largest high-quality PXR induction dataset ever made available, with over 11,000 compounds.
Not invited to the party? How to make proprietary ADMET insights more accessible
How do you train robust deep learning models when most of the high-quality data is proprietary? Discover how to enrich multitask ADMET predictions using a public proxy for proprietary learnings.
Cofolding? I hardly know her! - Cofolding Methods on ADMET Targets
Part 1 of a series on cofolding methods for ADMET targets: using structure prediction to model protein–ligand complexes for key Avoidome anti-targets like PXR and CYP3A4.
Woah, we’re halfway there…
We're halfway through the PXR Blind Challenge: unblinding the first data, freezing the leaderboard, and stepping into Phase 2 — plus a look at the response so far and what's next.
Navigating PXR Chemical Space with High-Throughput Chemistry and Standard-Free Quantification
With Octant, we use direct-to-biology high-throughput chemistry and standard-free quantification to explore PXR chemical space far beyond commercial libraries, part of OpenADMET's effort to map the Avoidome.
Models
Model, take the wheel: active learning with pEC50 data
Synthesizing and assaying compounds is slow and costly. Sean Colby explores whether active learning can use what a model already knows to guide which pEC50 data to acquire next.
Blind Challenges
Peak Performance or Just Noise?
Benchmarks are everywhere in ML — but when is a leaderboard gap real? Jon Swain on the statistics of comparing blind challenge entries and separating genuine performance from noise.
Data
Pregnane X Receptor PDB structure re-refinement
Improving 66 Pregnane X Receptor structures from the Protein Data Bank using modern refinement protocols to enhance ligand model quality.
Infrastructure
Running the OpenADMET stack on AMD GPUs with ROCm
A step-by-step guide to setting up a consumer AMD GPU workstation with ROCm to run the full openadmet-models stack, including dual-boot Linux setup.
Blind Challenges
Predicting PXR Induction - We have liftoff
Launch details for the PXR induction challenge, including the dataset, rules, and practical guidance for participants.
Blind Challenges
Lessons Learned from the OpenADMET-ExpansionRx Blind Challenge: Can We Trust Zero-Shot ADMET Predictions?
Lessons and reflections from the OpenADMET-ExpansionRx blind challenge — evaluating whether zero-shot ADMET predictions can be trusted in real drug discovery settings.
Blind Challenges
Announcing the next OpenADMET Blind Challenge: Predicting PXR Induction
An introduction to the next blind challenge and why blinded datasets remain important for realistic benchmarking.
Models
A Hot, Fresh, & New Clearance Model
A look at OpenADMET's clearance modeling work and the broader challenge of generalizing across chemical space.
Data
Building the OpenADMET Data Engine
A behind-the-scenes look at the infrastructure and strategy required to generate useful ADMET datasets at scale.
Blind Challenges
Lessons Learned from the OpenADMET - ExpansionRx Blind Challenge
Authors: Maria Castellanos, Hugo MacDermott-Opeskin, Jon Ainsley, Pat Walters DOI: 10.5281/zenodo.21784567 The ExpansionRx challenge, launched on October 27, 2025, closed two weeks ago! We are extremely grateful to everyone who participated and made this incredible learning experience possible for the ML and ADMET communities. After releasing
Blind Challenges
The OpenADMET - ExpansionRx Blind Challenge has Come to an End
Authors: Maria Castellanos, Hugo MacDermott-Opeskin DOI: 10.5281/zenodo.21784497 Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties can make or break the preclinical and clinical development of small molecules. At OpenADMET we aim to address the unpredictable nature of these properties through open science, generating high-quality experimental
Models
OpenADMET's Inaugural Model Release
OpenADMET's first public model release — predictive models for key ADMET properties, built on open data and designed for the drug discovery community.