Literature DB >> 25615431

Contribution of new technologies to characterization and prediction of adverse effects.

David Rouquié1, Marjoke Heneweer, Jane Botham, Hans Ketelslegers, Lauren Markell, Thomas Pfister, Winfried Steiling, Volker Strauss, Christa Hennes.   

Abstract

Identification of the potential hazards of chemicals has traditionally relied on studies in laboratory animals where changes in clinical pathology and histopathology compared to untreated controls defined an adverse effect. In the past decades, increased consistency in the definition of adversity with chemically-induced effects in laboratory animals, as well as in the assessment of human relevance has been reached. More recently, a paradigm shift in toxicity testing has been proposed, mainly driven by concerns over animal welfare but also thanks to the development of new methods. Currently, in vitro approaches, toxicogenomic technologies and computational tools, are available to provide mechanistic insight in toxicological Mode of Action (MOA) of the adverse effects observed in laboratory animals. The vision described as Tox21c (Toxicity Testing in the 21st century) aims at predicting in vivo toxicity using a bottom-up-approach, starting with understanding of MOA based on in vitro data to ultimately predict adverse effects in humans. At present, a practical application of the Tox21c vision is still far away. While moving towards toxicity prediction based on in vitro data, a stepwise reduction of in vivo testing is foreseen by combining in vitro with in vivo tests. Furthermore, newly developed methods will also be increasingly applied, in conjunction with established methods in order to gain trust in these new methods. This confidence is based on a critical scientific prerequisite: the establishment of a causal link between data obtained with new technologies and adverse effects manifested in repeated-dose in vivo toxicity studies. It is proposed to apply the principles described in the WHO/IPCS framework of MOA to obtain this link. Finally, an international database of known MOAs obtained in laboratory animals using data-rich chemicals will facilitate regulatory acceptance and could further help in the validation of the toxicity pathway and adverse outcome pathway concepts.

Entities:  

Keywords:  adverse effect; in vitro testing; mode of action; omics; predictive toxicology

Mesh:

Year:  2015        PMID: 25615431     DOI: 10.3109/10408444.2014.986054

Source DB:  PubMed          Journal:  Crit Rev Toxicol        ISSN: 1040-8444            Impact factor:   5.635


  5 in total

1.  Transcriptome profiling of HepG2 cells exposed to the flame retardant 9,10-dihydro-9-oxa-10-phosphaphenanthrene 10-oxide (DOPO).

Authors:  Boris V Krivoshiev; Gerrit T S Beemster; Katrien Sprangers; Bart Cuypers; Kris Laukens; Ronny Blust; Steven J Husson
Journal:  Toxicol Res (Camb)       Date:  2018-03-12       Impact factor: 3.524

2.  Effects of chlorpyrifos and trichloropyridinol on HEK 293 human embryonic kidney cells.

Authors:  Jeanette M Van Emon; Peipei Pan; Frank van Breukelen
Journal:  Chemosphere       Date:  2017-10-07       Impact factor: 7.086

3.  Pesticide toxicogenomics across scales: in vitro transcriptome predicts mechanisms and outcomes of exposure in vivo.

Authors:  Immacolata Porreca; Fulvio D'Angelo; Lucia De Franceschi; Alessandro Mattè; Michele Ceccarelli; Achille Iolascon; Alberto Zamò; Filomena Russo; Maria Ravo; Roberta Tarallo; Marzia Scarfò; Alessandro Weisz; Mario De Felice; Massimo Mallardo; Concetta Ambrosino
Journal:  Sci Rep       Date:  2016-12-01       Impact factor: 4.379

4.  Shedding New Lights with the Breakthrough Ideas to Understand Current Trends in Modern Toxicology.

Authors:  Ok-Nam Bae; Joo Young Lee
Journal:  Toxicol Res       Date:  2016-01-31

5.  Transcriptomic Profiles in Zebrafish Liver Permit the Discrimination of Surface Water with Pollution Gradient and Different Discharges.

Authors:  Zhou Zhang; Wei Liu; Yuanyuan Qu; Xie Quan; Ping Zeng; Mengchang He; Yanmei Zhou; Ruixia Liu
Journal:  Int J Environ Res Public Health       Date:  2018-08-03       Impact factor: 3.390

  5 in total

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