Inductive Bio Wins 3rd Consecutive AI Drug Discovery Benchmark

NEW YORK, July 14, 2026 — Inductive Bio, an AI drug discovery partner developing virtual chemistry labs, placed first in OpenADMET's PXR Blind Challenge, beating more than 350 researchers across large pharma, biotech, academic, and AI organizations. Inductive’s third consecutive win in the industry's leading AI small molecule competitions, with top honors in the ASAP-Polaris-OpenADMET Antiviral Challenge and ExpansionRx-OpenADMET blind challenge, establishes a track record unmatched by any other AI drug discovery company.

The PXR Blind Challenge tasked participants with predicting activation of pregnane X receptor (PXR), a protein that detects foreign compounds and triggers the body to metabolize and flush them out. PXR induction is a common liability that often goes undetected until mid- to late-stage
lead optimization, often years after initiating discovery efforts. The blind challenge format, in which participants predict properties of previously unseen compounds, offers a rare opportunity to benchmark ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) modeling under real-world conditions.

“PXR induction is one of those problems that kills programs late, after teams have already devoted significant resources to a compound series," said Ben Birnbaum, Inductive's Co-Founder and CTO. “Predicting it means picking up on subtle signals in chemical structure. This first-place finish tells us that our Beacon models are catching those signals, showing how far these models can go on the toughest drug discovery problems.”

Across the three blind challenges, there were over 750 competitors who made nearly 10,000 submissions across a total of 17 critical assay endpoints for drug discovery. Inductive placed first in all three challenges, even against entrants from companies many times its size, including Merck (with NVIDIA), Novo Nordisk, EMD Serono, and more.

Inductive’s work on PXR is part of a broader drug safety focus for the company, which was selected to lead an up to $21M ARPA-H CATALYST award, with Amgen and academic partners, to build AI models of drug-induced liver injury and cardiotoxicity - two of the largest drivers of clinical drug safety failures.

“We built Inductive to give every drug hunter a virtual chemistry lab, so teams can predict how a molecule will behave before spending months testing it in a wet lab and focus their effort on only the highest-quality ideas," said Josh Haimson, Inductive's co-founder and CEO. "Three consecutive wins in independent blind challenges against teams 1000x our size tell us that the Beacon models powering that lab are the state of the art for AI drug discovery tasks like ADMET prediction.”

The Beacon models are trained on one of the industry’s largest and most diverse datasets, drawn from Inductive’s pre-competitive data consortium, and fine-tuned to each partner’s chemical space. Inductive’s virtual lab currently powers the discovery programs of dozens of biopharma partners and has delivered multiple development candidates in significantly shorter timelines than the industry standard.

About Inductive Bio

Inductive builds virtual chemistry labs that help drug hunters design higher quality molecules, faster. Inductive's virtual labs are designed to scale proven scientific best practices across medicinal chemistry, computational chemistry, DMPK, and safety, enabling teams to make higher-quality decisions consistently throughout discovery. Inside these virtual labs, AI chemistry assistants work with predictive ADMET and PK models to help scientists evaluate more hypotheses in silico and surface key risks earlier. The most promising molecules move from the virtual lab to the wet lab in a tight feedback loop that accelerates the advancement of high-quality molecules. For more information, please visit www.inductive.bio.

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