Evaluating the synergistic use of advanced liver models and AI for the prediction of drug-induced liver injury.

Journal: Expert opinion on drug metabolism & toxicology

PMID: 39893552

Abstract

INTRODUCTION: Drug-induced liver injury (DILI) is a leading cause of acute liver failure. Hepatotoxicity typically occurs only in a subset of individuals after prolonged exposure and constitutes a major risk factor for the termination of drug development projects.

Authors

Yitian Zhou

Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden.
Yi Zhong

Department of Chinese Medicine Science & Engineering,Zhejiang University Hangzhou 310058,China.
Volker M Lauschke

Unit of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.

Keywords

Animals Chemical and Drug Induced Liver Injury Drug Development Drug Evaluation, Preclinical Humans Liver Liver Failure, Acute Machine Learning Models, Biological Risk Assessment Risk Factors

External Resources

View on PubMed Access via DOI PubMed (39893552)

Evaluating the synergistic use of advanced liver models and AI for the prediction of drug-induced liver injury.

Abstract

Authors

Keywords

External Resources

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