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Machine Learning Models for Predicting Liver Toxicity

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In Silico Methods for Predicting Drug Toxicity

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2425))

Abstract

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.

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Acknowledgments

The authors thank Gwenn Merry in the Office of Research at the National Center for Toxicological Research for her review and outstanding editing of the manuscript. This work was supported in part by an appointment to the Research Participation Program at the National Center for Toxicological Research (Zuowei Ji) administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the US Department of Energy and the US Food and Drug Administration.

Disclaimer: This chapter reflects the views of the authors and does not necessarily reflect those of the US Food and Drug Administration.

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  1. National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA

    Jie Liu, Wenjing Guo, Sugunadevi Sakkiah, Zuowei Ji, Gokhan Yavas, Wen Zou, Minjun Chen, Weida Tong, Tucker A. Patterson & Huixiao Hong

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  1. Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy

    Emilio Benfenati

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Liu, J. et al. (2022). Machine Learning Models for Predicting Liver Toxicity. In: Benfenati, E. (eds) In Silico Methods for Predicting Drug Toxicity. Methods in Molecular Biology, vol 2425. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1960-5_15

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  • DOI: https://doi.org/10.1007/978-1-0716-1960-5_15

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