Literature DB >> 29267930

Green Toxicology-Know Early About and Avoid Toxic Product Liabilities.

Alexandra Maertens1, Thomas Hartung1,2.   

Abstract

Toxicology uniquely among the life sciences relies largely on methods which are more than 40-years old. Over the last 3 decades with more or less success some additions to and few replacements in this toolbox took place, mainly as alternatives to animal testing. The acceptance of such new approaches faces the needs of formal validation and the conservative attitude toward change in safety assessments. Only recently, there is growing awareness that the same alternative methods, especially in silico and in vitro tools can also much earlier and before validation inform decision-taking in the product life cycle. As similar thoughts developed in the context of Green Chemistry, the term of Green Toxicology was coined to describe this change in approach. Here, the current developments in the alternative field, especially computational and more organo-typic cell cultures are reviewed, as they lend themselves to front-loaded chemical safety assessments. The initiatives of the Center for Alternatives to Animal Testing Green Toxicology Collaboration are presented. They aim first of all for forming a community to promote this concept and then for a cultural change in companies with the necessary training of chemists, product stewards and later regulators.
© The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Keywords:  big data; cell culture quality assurance; computational toxicology; nonanimal methods; read-across; safety testing

Mesh:

Year:  2018        PMID: 29267930     DOI: 10.1093/toxsci/kfx243

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  7 in total

Review 1.  Big-data and machine learning to revamp computational toxicology and its use in risk assessment.

Authors:  Thomas Luechtefeld; Craig Rowlands; Thomas Hartung
Journal:  Toxicol Res (Camb)       Date:  2018-05-01       Impact factor: 3.524

2.  A Farewell to Harms: The Audacity to Design Safer Products.

Authors:  Nicholas Anastas; Gary W Miller
Journal:  Toxicol Sci       Date:  2018-02-01       Impact factor: 4.849

3.  Avoiding Regrettable Substitutions: Green Toxicology for Sustainable Chemistry.

Authors:  Alexandra Maertens; Emily Golden; Thomas Hartung
Journal:  ACS Sustain Chem Eng       Date:  2021-06-01       Impact factor: 9.224

4.  Internationalization of read-across as a validated new approach method (NAM) for regulatory toxicology.

Authors:  Costanza Rovida; Tara Barton-Maclaren; Emilio Benfenati; Francesca Caloni; P. Charukeshi Chandrasekera; Christophe Chesné; Mark T D Cronin; Joop De Knecht; Daniel R Dietrich; Sylvia E Escher; Suzanne Fitzpatrick; Brenna Flannery; Matthias Herzler; Susanne Hougaard Bennekou; Bruno Hubesch; Hennicke Kamp; Jaffar Kisitu; Nicole Kleinstreuer; Simona Kovarich; Marcel Leist; Alexandra Maertens; Kerry Nugent; Giorgia Pallocca; Manuel Pastor; Grace Patlewicz; Manuela Pavan; Octavio Presgrave; Lena Smirnova; Michael Schwarz; Takashi Yamada; Thomas Hartung
Journal:  ALTEX       Date:  2020-04-30       Impact factor: 6.250

Review 5.  On the Utility of ToxCast-Based Predictive Models to Evaluate Potential Metabolic Disruption by Environmental Chemicals.

Authors:  Dayne L Filer; Kate Hoffman; Robert M Sargis; Leonardo Trasande; Christopher D Kassotis
Journal:  Environ Health Perspect       Date:  2022-05-09       Impact factor: 11.035

6.  Weighted Gene Correlation Network Analysis (WGCNA) Reveals Novel Transcription Factors Associated With Bisphenol A Dose-Response.

Authors:  Alexandra Maertens; Vy Tran; Andre Kleensang; Thomas Hartung
Journal:  Front Genet       Date:  2018-11-12       Impact factor: 4.599

7.  Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility.

Authors:  Thomas Luechtefeld; Dan Marsh; Craig Rowlands; Thomas Hartung
Journal:  Toxicol Sci       Date:  2018-09-01       Impact factor: 4.849

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.