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.
OpenADMET
Models
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.
Blind Challenges
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.
Models
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.
Models
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.
Blind Challenges
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.
Data
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.