Literature DB >> 28927750

The challenge of the application of 'omics technologies in chemicals risk assessment: Background and outlook.

Ursula G Sauer1, Lize Deferme2, Laura Gribaldo3, Jörg Hackermüller4, Tewes Tralau5, Ben van Ravenzwaay6, Carole Yauk7, Alan Poole8, Weida Tong9, Timothy W Gant10.   

Abstract

This survey by the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) highlights that 'omics technologies are generally not yet applied to meet standard information requirements during regulatory hazard assessment. While they are used within weight-of-evidence approaches to investigate substances' modes-of-action, consistent approaches for the generation, processing and interpretation of 'omics data are not applied. To date, no 'omics technology has been standardised or validated. Best practices for performing 'omics studies for regulatory purposes (e.g., microarrays for transcriptome profiling) remain to be established. Therefore, three frameworks for (i) establishing a Good-Laboratory Practice-like context for collecting, storing and curating 'omics data; (ii) 'omics data processing; and (iii) quantitative WoE approaches to interpret 'omics data have been developed, that are presented in this journal supplement. Application of the frameworks will enable between-study comparison of results, which will facilitate the regulatory applicability of 'omics data. The frameworks do not constitute prescriptive protocols precluding any other data analysis method, but provide a baseline for analysis that can be applied to all data allowing ready cross-comparison. Data analysis that does not follow the frameworks can be justified and the resulting data can be compared with the Framework-based common analysis output. Crown
Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Keywords:  Hazard assessment; Omics; Plant protection products; Registration, Evaluation, Authorisation, and Restriction (REACH); Regulatory toxicology; Test method standardisation; Test method validation; Transcriptomics; Weight-of-evidence

Mesh:

Year:  2017        PMID: 28927750     DOI: 10.1016/j.yrtph.2017.09.020

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


  21 in total

1.  Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases.

Authors:  Marissa B Kosnik; David M Reif
Journal:  Toxicol Appl Pharmacol       Date:  2019-07-16       Impact factor: 4.219

2.  Perspective: Advancing Understanding of Population Nutrient-Health Relations via Metabolomics and Precision Phenotypes.

Authors:  Stephanie Andraos; Melissa Wake; Richard Saffery; David Burgner; Martin Kussmann; Justin O'Sullivan
Journal:  Adv Nutr       Date:  2019-11-01       Impact factor: 8.701

Review 3.  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

Review 4.  Prospects and challenges of multi-omics data integration in toxicology.

Authors:  Sebastian Canzler; Jana Schor; Wibke Busch; Kristin Schubert; Ulrike E Rolle-Kampczyk; Hervé Seitz; Hennicke Kamp; Martin von Bergen; Roland Buesen; Jörg Hackermüller
Journal:  Arch Toxicol       Date:  2020-02-08       Impact factor: 5.153

Review 5.  Mode of action-based risk assessment of genotoxic carcinogens.

Authors:  Andrea Hartwig; Michael Arand; Bernd Epe; Sabine Guth; Gunnar Jahnke; Alfonso Lampen; Hans-Jörg Martus; Bernhard Monien; Ivonne M C M Rietjens; Simone Schmitz-Spanke; Gerlinde Schriever-Schwemmer; Pablo Steinberg; Gerhard Eisenbrand
Journal:  Arch Toxicol       Date:  2020-06-15       Impact factor: 5.153

6.  Population-based dose-response analysis of liver transcriptional response to trichloroethylene in mouse.

Authors:  Abhishek Venkatratnam; John S House; Kranti Konganti; Connor McKenney; David W Threadgill; Weihsueh A Chiu; David L Aylor; Fred A Wright; Ivan Rusyn
Journal:  Mamm Genome       Date:  2018-01-20       Impact factor: 2.957

Review 7.  Applying 'omics technologies in chemicals risk assessment: Report of an ECETOC workshop.

Authors:  Roland Buesen; Brian N Chorley; Beatriz da Silva Lima; George Daston; Lize Deferme; Timothy Ebbels; Timothy W Gant; Amber Goetz; John Greally; Laura Gribaldo; Jörg Hackermüller; Bruno Hubesch; Danyel Jennen; Kamin Johnson; Jun Kanno; Hans-Martin Kauffmann; Madeleine Laffont; Patrick McMullen; Richard Meehan; Mark Pemberton; Stefania Perdichizzi; Aldert H Piersma; Ursula G Sauer; Kerstin Schmidt; Hervé Seitz; Kayo Sumida; Knut E Tollefsen; Weida Tong; Tewes Tralau; Ben van Ravenzwaay; Ralf J M Weber; Andrew Worth; Carole Yauk; Alan Poole
Journal:  Regul Toxicol Pharmacol       Date:  2017-09-25       Impact factor: 3.271

8.  Next generation sequencing data for use in risk assessment.

Authors:  B Alex Merrick
Journal:  Curr Opin Toxicol       Date:  2019-03-08

Review 9.  A generic Transcriptomics Reporting Framework (TRF) for 'omics data processing and analysis.

Authors:  Timothy W Gant; Ursula G Sauer; Shu-Dong Zhang; Brian N Chorley; Jörg Hackermüller; Stefania Perdichizzi; Knut E Tollefsen; Ben van Ravenzwaay; Carole Yauk; Weida Tong; Alan Poole
Journal:  Regul Toxicol Pharmacol       Date:  2017-11-04       Impact factor: 3.271

10.  Considerations for Strategic Use of High-Throughput Transcriptomics Chemical Screening Data in Regulatory Decisions.

Authors:  Joshua Harrill; Imran Shah; R Woodrow Setzer; Derik Haggard; Scott Auerbach; Richard Judson; Russell S Thomas
Journal:  Curr Opin Toxicol       Date:  2019
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