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Role of in silico genotoxicity tools in the regulatory assessment of pharmaceutical impurities

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The toxicological assessment of genotoxic impurities is an important consideration in the regulatory framework for pharmaceuticals. In this context, the application of promising computational methods (e.g. Quantitative Structure-Activity Relationships (QSARs), Structure-Activity Relationships (SARs) and/or expert systems) for the evaluation of genotoxicity is needed, especially when very limited information on impurities is available, both for practical reasons and to respect the principle of the 3Rs (Replacement, Reduction and Refinement) of animal use. To gain an overview of how computational methods are used internationally in the regulatory assessment of pharmaceutical impurities, the current regulatory documents were reviewed. The software recommended in the guidelines (e.g. MCASE, MC4PC, Derek for Windows) or, practically used by various regulatory agencies (e.g. U.S. Food and Drug Administration, U.S. and Danish Environmental Protection Agencies), as well as the other existing programs were analysed, highlighting their benefits and limitations. Both statistically-based and knowledge-based (expert system) tools were analysed. Information on the models’ training sets as well as their applicability domains was retrieved. The overall conclusions on the available in silico tools for genotoxicity and carcinogenicity prediction are quite optimistic and the regulatory application of QSAR methods is constantly growing. For regulatory purposes, it is recommended that the predictions of genotoxicity/carcinogenicity should be based on a battery of models, combining high sensitivity models (low rate of false negatives) with high specificity ones (low rate of false positives), and in vitro assays in an integrated manner.
2012-11-09
TAYLOR & FRANCIS LTD
JRC66474
1062-936X,   
http://www.tandfonline.com/doi/pdf/10.1080/1062936X.2012.657236,    https://publications.jrc.ec.europa.eu/repository/handle/JRC66474,   
10.1080/1062936X.2012.657236,   
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