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

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

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 molecula...

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Bibliographic Details
Main Authors: Taeyeub Lee, Joram M. Posma
Format: Article
Language:English
Published: BMC 2025-08-01
Series:Journal of Cheminformatics
Subjects:
Drug induced liver injury
Feature engineering
Graph neural networks
Molecular optimisation
Online Access:https://doi.org/10.1186/s13321-025-01068-3
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https://doi.org/10.1186/s13321-025-01068-3

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