On the use of in silico tools for prioritising toxicity testing of the low-volume industrial chemicals in REACH
| Autor: | Patrik L. Andersson, Aleksandra Rybacka, Christina Rudén |
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| Rok vydání: | 2013 |
| Předmět: |
Pharmacology
Quantitative structure–activity relationship business.industry Computer science In silico Reproducibility of Results General Medicine Chemical industry Toxicology Models Biological Risk Assessment Toolbox Hazardous Substances Low volume Rat liver Toxicity Tests Carcinogens Animals Humans Computer Simulation Biochemical engineering Risk assessment business Reproductive toxicity |
| Zdroj: | Basicclinical pharmacologytoxicology. 115(1) |
| ISSN: | 1742-7843 |
| Popis: | This study was conducted to evaluate the utility of a selection of commercially and freely available non-testing tools and to analyse how REACH registrants can apply these as prioritisation tool for low-volume chemicals. The analysis was performed on a set of organic industrial chemicals and pesticides with extensive peer-reviewed risk assessment data. Analysed in silico model systems included Derek Nexus, Toxtree, QSAR Toolbox, LAZAR, TEST and VEGA, and results from these were compared with expert-judged risk classification according to the classifying, labelling and packaging (CLP) regulation. The most reliable results were obtained for carcinogenicity; however, less reliable predictions were derived for mutagenicity and reproductive toxicity. A group of compounds frequently predicted as false negatives was identified. These were relatively small molecules with low structural complexity, for example benzene derivatives with hydroxyl-, amino- or aniline-substituents. A rat liver S9 metabolite simulator was applied to illustrate the importance of considering metabolism in the risk assessment procedure. We also discuss outcome of combining predictions from multiple model systems and advise how to apply in silico tools. These models are proposed to be used to prioritise low-volume chemicals for testing within the REACH legislation, and we conclude that further guidance is needed so that industry can select and apply models in a reliable, systematic and transparent way. |
| Databáze: | OpenAIRE |
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