Literature DB >> 29037774

Framework for the quantitative weight-of-evidence analysis of 'omics data for regulatory purposes.

Jim Bridges1, Ursula G Sauer2, Roland Buesen3, Lize Deferme4, Knut E Tollefsen5, Tewes Tralau6, Ben van Ravenzwaay3, Alan Poole7, Mark Pemberton8.   

Abstract

A framework for the quantitative weight-of-evidence (QWoE) analysis of 'omics data for regulatory purposes is presented. The QWoE framework encompasses seven steps to evaluate 'omics data (also together with non-'omics data): (1) Hypothesis formulation, identification and weighting of lines of evidence (LoEs). LoEs conjoin different (types of) studies that are used to critically test the hypothesis. As an essential component of the QWoE framework, step 1 includes the development of templates for scoring sheets that predefine scoring criteria with scores of 0-4 to enable a quantitative determination of study quality and data relevance; (2) literature searches and categorisation of studies into the pre-defined LoEs; (3) and (4) quantitative assessment of study quality and data relevance using the respective pre-defined scoring sheets for each study; (5) evaluation of LoE-specific strength of evidence based upon the study quality and study relevance scores of the studies conjoined in the respective LoE; (6) integration of the strength of evidence from the individual LoEs to determine the overall strength of evidence; (7) characterisation of uncertainties and conclusion on the QWoE. To put the QWoE framework in practice, case studies are recommended to confirm the relevance of its different steps, or to adapt them as necessary.
Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Keywords:  Data relevance; Hazard assessment; Mode-of-action; Regulatory toxicology; Strength of evidence; Study quality (reliability); Weight-of-evidence

Mesh:

Year:  2017        PMID: 29037774     DOI: 10.1016/j.yrtph.2017.10.010

Source DB:  PubMed          Journal:  Regul Toxicol Pharmacol        ISSN: 0273-2300            Impact factor:   3.271


  1 in total

Review 1.  Framework for the quality assurance of 'omics technologies considering GLP requirements.

Authors:  Hans-Martin Kauffmann; Hennicke Kamp; Regine Fuchs; Brian N Chorley; Lize Deferme; Timothy Ebbels; Jörg Hackermüller; Stefania Perdichizzi; Alan Poole; Ursula G Sauer; Knut E Tollefsen; Tewes Tralau; Carole Yauk; Ben van Ravenzwaay
Journal:  Regul Toxicol Pharmacol       Date:  2017-10-05       Impact factor: 3.271

  1 in total

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