In silico approaches in organ toxicity hazard assessment: Current status and future needs in predicting liver toxicity

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Bassan, Arianna, Alves, Vinicius M, Amberg, Alexander, Anger, Lennart T, Auerbach, Scott, Beilke, Lisa, Bender, Andreas, Cronin, Mark TD, Cross, Kevin P, Hsieh, Jui-Hua et al (show 17 more authors) , Greene, Nigel, Kemper, Raymond, Kim, Marlene T, Mumtaz, Moiz, Noeske, Tobias, Pavan, Manuela, Pletz, Julia, Russo, Daniel P, Sabnis, Yogesh, Schaefer, Markus, Szabo, David T, Valentin, Jean-Pierre, Wichard, Joerg, Williams, Dominic ORCID: 0000-0002-0758-3152, Woolley, David, Zwickl, Craig and Myatt, Glenn J (2021) In silico approaches in organ toxicity hazard assessment: Current status and future needs in predicting liver toxicity. Computational Toxicology, 20. p. 100187.

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Abstract

Hepatotoxicity is one of the most frequently observed adverse effects resulting from exposure to a xenobiotic. For example, in pharmaceutical research and development it is one of the major reasons for drug withdrawals, clinical failures, and discontinuation of drug candidates. The development of faster and cheaper methods to assess hepatotoxicity that are both more sustainable and more informative is critically needed. The biological mechanisms and processes underpinning hepatotoxicity are summarized and experimental approaches to support the prediction of hepatotoxicity are described, including toxicokinetic considerations. The paper describes the increasingly important role of <i>in silico</i> approaches and highlights challenges to the adoption of these methods including the lack of a commonly agreed upon protocol for performing such an assessment and the need for <i>in silico</i> solutions that take dose into consideration. A proposed framework for the integration of <i>in silico</i> and experimental information is provided along with a case study describing how computational methods have been used to successfully respond to a regulatory question concerning non-genotoxic impurities in chemically synthesized pharmaceuticals.

Item Type:	Article
Uncontrolled Keywords:	Computational Toxicology, Expert Alerts, Hazard Identification, Hepatotoxicity, In Silico, In Silico Toxicology Protocols, Liver toxicity, Organ toxicity, QSAR, Read-across, Risk Assessment
Divisions:	Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User:	Symplectic Admin
Date Deposited:	27 May 2022 08:33
Last Modified:	18 Jan 2023 21:00
DOI:	10.1016/j.comtox.2021.100187
Open Access URL:	https://researchonline.ljmu.ac.uk/id/eprint/15480/
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3155595