Presenting on Our Approach to the OpenADMET PXR Blind Challenge Win

In July, Inductive took first place among 350+ researchers from pharma, biotech and AI labs in OpenADMET’s 2026 blind challenge to predict activation of PXR, a receptor that detects foreign compounds and induces the enzymes that clear them from the body. When a drug triggers that response, it can accelerate its own metabolism, alter dosing, and interfere with other medications: a failure mode that often isn't caught until mid-to-late lead optimization.

In this webinar, Duncan Muir, who led Inductive's PXR submission, walks through our approach end-to-end. He shares:

• How an early model, trained on the challenge's dose-response data, was strengthened with additional data types and then blended with a 3D model
• How error analysis, aided by our own AI assistant Indy, surfaced a pattern behind where the model was overpredicting
• How we built a proxy model to better represent the weak, hard-to-fit compounds

He closes with a look at where structural and biophysical methods might take PXR modeling next.

This challenge is part of a larger effort at Inductive. Alongside academic and industry collaborators, we're building toxicity and drug safety tools under an ARPA-H program, combining in silico models, mechanistic assays, and higher-order biological systems to catch toxicity earlier in drug discovery and help safer drugs reach clinical trials.

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