Predicting toxicity through computers: a changing world
Open Access
- 18 December 2007
- journal article
- Published by Springer Science and Business Media LLC in Chemistry Central Journal
- Vol. 1 (1), 32
- https://doi.org/10.1186/1752-153x-1-32
Abstract
The computational approaches used to predict toxicity are evolving rapidly, a process hastened on by the emergence of new ways of describing chemical information. Although this trend offers many opportunities, new regulations, such as the European Community's 'Registration, Evaluation, Authorization and Restriction of Chemicals' (REACH), demand that models be ever more robust. In this commentary, we outline the numerous factors involved in the evolution of quantitative structure-regulatory activity relationship (QSAR) models. Such models not only require powerful tools, but must also be adapted for their intended application, such as in using suitable input values and having an output that complies with legal requirements. In addition, transparency and model reproducibility are important factors. As more models become available, it is vital that new theoretical possibilities are embraced, and efforts are combined in order to promote new flexible, modular tools.Keywords
This publication has 11 references indexed in Scilit:
- In silico-aided prediction of biological properties of chemicals: oestrogen receptor-mediated effectsChemical Society Reviews, 2008
- Regulatory Perspectives in the Use and Validation of QSAR. A Case Study: DEMETRA Model for Daphnia ToxicityEnvironmental Science & Technology, 2007
- Predicting Toxicological and Ecotoxicological EndpointsPublished by Springer Science and Business Media LLC ,2007
- Validation of the modelsPublished by Elsevier BV ,2007
- Computational ToxicologyPublished by Wiley ,2006
- Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.Environmental Health Perspectives, 2003
- Beware of q2!Journal of Molecular Graphics and Modelling, 2002
- Factors Influencing Predictive Models for ToxicologySAR and QSAR in Environmental Research, 2001
- Handbook of Molecular DescriptorsMethods and Principles in Medicinal Chemistry, 2000
- The Correlation of Biological Activity of Plant Growth Regulators and Chloromycetin Derivatives with Hammett Constants and Partition CoefficientsJournal of the American Chemical Society, 1963