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|Title:||Computer models versus reality: How well do in silico models currently predict the sensitization potential of a substance|
|Authors:||TEUBNER Wera; MEHLING Annette; XAVER SCHUSTER Paul; GUTH Katharina; WORTH Andrew; BURTON JULIEN; VAN RAVENZWAAY Bennard; LANDSIEDEL Robert|
|Citation:||REGULATORY TOXICOLOGY AND PHARMACOLOGY vol. 67 no. 3 p. 468-485|
|Publisher:||ACADEMIC PRESS INC ELSEVIER SCIENCE|
|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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