Produced by C&EN Webinars

LLM Agents for Liver Injury Risk Prediction and Medicinal Chemistry Decision Support

DATE

Previous Date: July 14, 2026

New Postponed Date: October 13, 2026

TIME

9:00 a.m. PT | 12:00 p.m. ET | 5:00 p.m. UK

Overview

Liver safety remains one of the most difficult risks to anticipate in drug discovery. Many liabilities emerge only after substantial investment, when standard preclinical assays have not fully captured the human biology, exposure context, or mechanisms that drive clinical liver injury. For discovery teams, the challenge is not simply detecting toxicity earlier, but understanding whether a signal is relevant, what mechanism may be responsible, and how that insight should influence compound design and progression decisions.

Axiom helps drug discovery teams address this challenge by generating human-relevant hepatic safety profiles before molecules enter the clinic. Using 2D+ multicellular hepatic systems profiled by high-content imaging, transcriptomics, proteomics, and standard ADME assays, Axiom builds an integrated data package for each compound. Axi, Axiom’s reasoning agent, then combines these data with partner-generated assays, chemical series context, exposure estimates, and clinical evidence to produce mechanism-aware predictions of human liver safety risk.

Rather than relying on a single cytotoxicity score, Axiom evaluates biological signatures across mechanisms. This enables medicinal chemistry and DMPK teams to generate interpretable, series-specific structure-toxicity hypotheses, compare analogs, prioritize compounds with improved predicted therapeutic index, and identify follow-up assays or structural modifications most likely to reduce risk.

In this webinar, we will introduce the Axiom hepatic profiling platform and show how integrated phenotypic, omics, ADME, and exposure-aware interpretation can support safer compound design. We will review performance against established DILI reference compounds and newer chemical matter, then walk through case examples showing how Axi synthesizes multimodal evidence to guide mechanistic interpretation, risk ranking, and medicinal chemistry decision-making.

Key Learning Objectives:

How Axiom has constructed an industry leading clinical toxicity prediction package from in vitro assays
How agents (Axi) can help drug discovery teams interpret multimodal data across medchem, exposure, and tox to prioritize compounds and reduce residual tox liabilities
Specific case studies on toxicity of modern clinical molecules

Who Should Attend:

Medicinal chemists, toxicologists, DMPK scientists, pharma program directors
Business development and tech scouts from biotech and pharma

Sponsored by:

Speakers

Will Van Treuren
Computational Scientist,
Axiom

Chengpeng Wang
Computational Scientist,
Axiom

Melissa O’Meara
Forensic Science Consultant,
ACS Media Group

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