A critical review of adverse effects to the kidney: mechanisms, data sources, and in silico tools to assist prediction

Julia Pletz, Steve J Enoch , Diviya M Jais , Claire L Mellor, Gopal Pawar, James W Firman (Contributor), Judith C Madden (Contributor), Steven D Webb, Carlos A Tagliati, Mark.T.D Cronin

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)
206 Downloads (Pure)

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 utilize multiscale 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 interrelationships between nephrotoxicity mechanisms.
Original languageEnglish
Pages (from-to)1225-1253
Number of pages29
JournalExpert Opinion on Drug Metabolism and Toxicology
Volume14
Issue number12
Early online date22 Oct 2018
DOIs
Publication statusPublished - 25 Nov 2018

Keywords

  • kidney
  • nephrotoxicity
  • in silico
  • computational models
  • (Q)SAR
  • mechanisms

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