Literature DB >> 21404310

Computational chemistry, systems biology and toxicology. Harnessing the chemistry of life: revolutionizing toxicology. a commentary.

Ian Kimber1, Colin Humphris, Carl Westmoreland, Nathalie Alepee, Gianni Dal Negro, Irene Manou.   

Abstract

There is a continuing interest in, and increasing imperatives for, the development of alternative methods for toxicological evaluations that do not require the use of animals. Although a significant investment has resulted in some achievements, progress has been patchy and there remain many challenges. Among the most significant hurdles is developing non-animal methods that would permit assessment of the potential for a chemical or drug to cause adverse health effects following repeated systemic exposure. Developing approaches to address this challenge has been one of the objectives of the European Partnership for Alternative Approaches to Animal Testing (EPAA). The EPAA is a unique partnership between the European Commission and industry that has interests in all aspects of reducing, refining and replacing the use of animals (the '3Rs'). One possible strategy that emerged from a broad scientific debate sponsored by the EPAA was the opportunity for developing entirely new paradigms for toxicity testing based upon harnessing the increasing power of computational chemistry in combination with advanced systems biology. This brief commentary summarizes a workshop organized by the EPAA in 2010, that had the ambitious title of 'Harnessing the Chemistry of Life: Revolutionizing Toxicology'. At that workshop international experts in chemistry, systems biology and toxicology sought to map out how best developments in these sciences could be exploited to design new strategies for toxicity testing using adverse effects in the liver as an initial focus of attention. Here we describe the workshop design and outputs, the primary purpose being to stimulate debate about the need to align different areas of science with toxicology if new and truly innovative approaches to toxicity testing are to be developed.
Copyright © 2011 John Wiley & Sons, Ltd.

Entities:  

Mesh:

Year:  2011        PMID: 21404310     DOI: 10.1002/jat.1666

Source DB:  PubMed          Journal:  J Appl Toxicol        ISSN: 0260-437X            Impact factor:   3.446


  4 in total

1.  Prediction of drug-induced eosinophilia adverse effect by using SVM and naïve Bayesian approaches.

Authors:  Hui Zhang; Peng Yu; Ming-Li Xiang; Xi-Bo Li; Wei-Bao Kong; Jun-Yi Ma; Jun-Long Wang; Jin-Ping Zhang; Ji Zhang
Journal:  Med Biol Eng Comput       Date:  2015-06-05       Impact factor: 2.602

2.  In silico prediction of drug-induced myelotoxicity by using Naïve Bayes method.

Authors:  Hui Zhang; Peng Yu; Teng-Guo Zhang; Yan-Li Kang; Xiao Zhao; Yuan-Yuan Li; Jia-Hui He; Ji Zhang
Journal:  Mol Divers       Date:  2015-07-11       Impact factor: 2.943

3.  Thermodynamics study of biokerosene from coconut and palm kernel oils and JP-8 aircraft fuels in the gas phase by the DFT method.

Authors:  Edimilson S Moraes; Gustavo F Reis; Jorddy Cruz; Klaus Cozzolino; Abel F G Neto; Tarciso Andrade-Filho; Antonio M J C Neto
Journal:  J Mol Model       Date:  2020-03-16       Impact factor: 1.810

Review 4.  Novel in vitro and mathematical models for the prediction of chemical toxicity.

Authors:  Dominic P Williams; Rebecca Shipley; Marianne J Ellis; Steve Webb; John Ward; Iain Gardner; Stuart Creton
Journal:  Toxicol Res (Camb)       Date:  2012-09-05       Impact factor: 3.524

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.