Deep Learning Prediction of Drug-Induced Liver Toxicity by Manifold Embedding of Quantum Information of Drug Molecules.

Journal: Pharmaceutical research
PMID: 39663331

Abstract

PURPOSE: Drug-induced liver injury, or DILI, affects numerous patients and also presents significant challenges in drug development. It has been attempted to predict DILI of a chemical by in silico approaches, including data-driven machine learning models. Herein, we report a recent DILI deep-learning effort that utilized our molecular representation concept by manifold embedding electronic attributes on a molecular surface.

Authors

  • Tonglei Li
    Department of Industrial & Molecular Pharmaceutics, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana, 47907, USA. tonglei@purdue.edu.
  • Jiaqing Li
    School of Electrical Engineering, Yanshan University, Qinhuangdao, China.
  • Hongyi Jiang
    Department of Industrial & Molecular Pharmaceutics, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana, 47907, USA.
  • David B Skiles
    Department of Industrial & Molecular Pharmaceutics, Purdue University, 575 Stadium Mall Drive, West Lafayette, Indiana, 47907, USA.

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