This training will provide a roadmap for the use of outputs from the DILIsym® module in ADMET Predictor® to derive an early assessment of rank-ordered hepatotoxic risk within the DILIsym Quantitative Systems Toxicology (QST) software. The DILIsym module permits liver safety assessment during early drug discovery efforts with minimal data required. Learn how to utilize the DILIsym module qualitative yes/no outputs with the quantitative outputs to parameterize toxicity mechanisms in DILIsym for rank order toxicity assessments. Discover a workflow permissive for early discovery applications! We’ll show you a workflow that leverages ADMET Predictor structure-based machine learning models constructed from a library of DILI/clean compounds. Explore the option to use constant liver exposure based on molar concentrations or use ADMET Predictor High-Throughput PK (HTPK) results. Then, we’ll integrate all of the above in the DILIsym in vivo context for early insights into liver liabilities.

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Instructors: Lisl Shoda, James Beaudoin, Christina Battista