Improving drug-induced liver injury prediction using graph neural networks with augmented graph features from molecular optimisation.

Journal: Journal of cheminformatics
Published Date: Aug 18, 2025

Abstract

PURPOSE: Drug-induced liver injury (DILI) is a significant concern in drug development, often leading to the discontinuation of clinical trials and the withdrawal of drugs from the market. This study explores the application of graph neural networks (GNNs) for DILI prediction, using molecular graph representations as the primary input.

Authors

  • Taeyeub Lee
    Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, W12 0NN, UK. t.lee23@imperial.ac.uk.
  • Joram M Posma
    Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, U.K.

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