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A Critical Review of Adverse Effects to the Kidney: Mechanisms, Data Sources and In Silico Tools to Assist Prediction

Pletz, J, Enoch, SJ, Jais, DM, Mellor, CL, Pawar, G, Madden, JC, Webb, SD, Tagliati, C and Cronin, MTD (2018) A Critical Review of Adverse Effects to the Kidney: Mechanisms, Data Sources and In Silico Tools to Assist Prediction. Expert Opinion on Drug Metabolism and Toxicology. ISSN 1744-7607

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Abstract

Introduction: The kidney is a major target for toxicity elicited by pharmaceuticals and environmental pollutants. Standard testing which often does not investigate underlying mechanisms has proven not to be an adequate hazard assessment approach. As such, there is an opportunity for the application of computational approaches that utilise multi-scale data based on the Adverse Outcome Pathway (AOP) paradigm, coupled with an understanding of the chemistry underpinning the molecular initiating event (MIE) to provide a deep understanding of how structural fragments of molecules relate to specific mechanisms of nephrotoxicity.
Aims covered: The aim of this investigation was to review the current scientific landscape related to computational methods, including mechanistic data, AOPs, publicly available knowledge bases and current in silico models, for the assessment of pharmaceuticals and other chemicals with regard to their potential to elicit nephrotoxicity. A list of over 250 nephrotoxicants enriched with, where possible, mechanistic and AOP-derived understanding was compiled.
Expert opinion: Whilst little mechanistic evidence has been translated into AOPs, this review identified a number of data sources of in vitro, in vivo and human data that may assist in the development of in silico models which in turn may shed light on the inter-relationships between nephrotoxicity mechanisms.

Item Type: Article
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in Expert Opinion on Drug Metabolism and Toxicology on 22/10/18, available online: http://www.tandfonline.com/10.1080/17425255.2018.1539076
Uncontrolled Keywords: 1115 Pharmacology And Pharmaceutical Sciences
Subjects: H Social Sciences > HA Statistics
R Medicine > R Medicine (General)
R Medicine > RM Therapeutics. Pharmacology
Divisions: Applied Mathematics (merged with Comp Sci 10 Aug 20)
Pharmacy & Biomolecular Sciences
Publisher: Taylor & Francis
Date Deposited: 24 Oct 2018 09:28
Last Modified: 04 Sep 2021 09:59
DOI or ID number: 10.1080/17425255.2018.1539076
URI: https://researchonline.ljmu.ac.uk/id/eprint/9535
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