145
Views
9
CrossRef citations to date
0
Altmetric
Reviews

Quantitative knowledge-based analysis in compound safety assessment

&
Pages 287-298 | Published online: 22 Jan 2011
 

Abstract

Introduction: Despite rapid progress in OMICs and computational technologies in compound safety assessment, drug failure rate due to toxicity is still unacceptably high. One reason for this is an inadequate interpretation of high-throughput preclinical data. Another reason is the poor mechanistic understanding of drug side effects as currently just a few compound targets are linked to specific adverse reactions.

Areas covered: Current performance issues with statistical analysis of OMICs data or gene/protein/compound lists are discussed, illustrating potential advantages of knowledge-based approaches in prediction of human toxicity. The authors show several examples of quantitative functional analysis, including cross-tissue toxicity predictions and integrated analysis of different types of OMICs data. They also describe novel approaches linking compound targets and associated pathways to side effects. The reader will gain an update on the recent developments in knowledge-based analysis in toxicogenomics and computational methods correlating protein targets with adverse reactions.

Expert opinion: Quantitative pathway analysis is a useful approach for deriving multi-variant predictive biomarkers for drug safety. However, more comprehensive studies are needed for direct comparison of performance between pathway- and gene-centric methods.

Notes

This box summarizes key points contained in the article.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 99.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 727.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.