Title: Computer models versus reality: How well do in silico models currently predict the sensitization potential of a substance
Authors: TEUBNER WeraMEHLING AnnetteXAVER SCHUSTER PaulGUTH KatharinaWORTH AndrewBURTON JULIENVAN RAVENZWAAY BennardLANDSIEDEL Robert
Citation: REGULATORY TOXICOLOGY AND PHARMACOLOGY vol. 67 no. 3 p. 468-485
Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE
Publication Year: 2013
JRC N°: JRC81554
ISSN: 0273-2300
URI: http://www.sciencedirect.com/science/article/pii/S0273230013001529
http://publications.jrc.ec.europa.eu/repository/handle/JRC81554
DOI: 10.1016/j.yrtph.2013.09.007
Type: Articles in periodicals and books
Abstract: Industrial chemicals need to be assessed for their potential to cause skin sensitization. The European chemical and cosmetic legislations have generated increased availability of reliable experimental data on skin sensitization potentials but also a greater demand for non-animal testing methods. In this study, animal data on 55 non-sensitizing and 45 sensitizing chemicals was reviewed and used to test the performance of computer (in silico) models for the prediction of skin sensitization. Statistical models (Vega, Case Ultra, TOPKAT), mechanistic models (Toxtree, OECD (Q)SAR toolbox v3.1, DEREK) and a hybrid model (TIMES-SS) were evaluated. Substances were selected which were not expected to be found in the model training sets. This study also explored other aspects, such as ease of use and data interpretation, and applicability for regulatory purposes.
JRC Directorate:Institute for Health and Consumer Protection Historical Collection

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