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Machine Learning Models for Predicting Liver Toxicity. 2022

Jie Liu, and Wenjing Guo, and Sugunadevi Sakkiah, and Zuowei Ji, and Gokhan Yavas, and Wen Zou, and Minjun Chen, and Weida Tong, and Tucker A Patterson, and Huixiao Hong
National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA.

Liver toxicity is a major adverse drug reaction that accounts for drug failure in clinical trials and withdrawal from the market. Therefore, predicting potential liver toxicity at an early stage in drug discovery is crucial to reduce costs and the potential for drug failure. However, current in vivo animal toxicity testing is very expensive and time consuming. As an alternative approach, various machine learning models have been developed to predict potential liver toxicity in humans. This chapter reviews current advances in the development and application of machine learning models for prediction of potential liver toxicity in humans and discusses possible improvements to liver toxicity prediction.

UI MeSH Term Description Entries
D006505 Hepatitis INFLAMMATION of the LIVER. Hepatitides
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000069550 Machine Learning A type of ARTIFICIAL INTELLIGENCE that enable COMPUTERS to independently initiate and execute LEARNING when exposed to new data. Transfer Learning,Learning, Machine,Learning, Transfer
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia
D055808 Drug Discovery The process of finding chemicals for potential therapeutic use. Drug Prospecting,Discovery, Drug,Prospecting, Drug
D064420 Drug-Related Side Effects and Adverse Reactions Disorders that result from the intended use of PHARMACEUTICAL PREPARATIONS. Included in this heading are a broad variety of chemically-induced adverse conditions due to toxicity, DRUG INTERACTIONS, and metabolic effects of pharmaceuticals. Drug-Related Side Effects and Adverse Reaction,Adverse Drug Event,Adverse Drug Reaction,Drug Side Effects,Drug Toxicity,Side Effects of Drugs,Toxicity, Drug,Adverse Drug Events,Adverse Drug Reactions,Drug Event, Adverse,Drug Events, Adverse,Drug Reaction, Adverse,Drug Reactions, Adverse,Drug Related Side Effects and Adverse Reaction,Drug Related Side Effects and Adverse Reactions,Drug Side Effect,Drug Toxicities,Effects, Drug Side,Reactions, Adverse Drug,Side Effect, Drug,Side Effects, Drug,Toxicities, Drug

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