Integrated in silico modeling for the prediction of chronic toxicity

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RICHARZ, Andrea-Nicole, Michael R. BERTHOLD, Elena FIORAVANZO, Daniel NEAGU, Chihae YANG, José-Manuel ZALDÍVAR-COMENGES, Mark T. D. CRONIN, 2013. Integrated in silico modeling for the prediction of chronic toxicity. In: International Journal of Toxicology. 32(1), pp. 72-73. ISSN 1091-5818. eISSN 1092-874X. Available under: doi: 10.1177/1091581812471490

@article{Richarz2013-02-05Integ-37368, title={Integrated in silico modeling for the prediction of chronic toxicity}, year={2013}, doi={10.1177/1091581812471490}, number={1}, volume={32}, issn={1091-5818}, journal={International Journal of Toxicology}, pages={72--73}, author={Richarz, Andrea-Nicole and Berthold, Michael R. and Fioravanzo, Elena and Neagu, Daniel and Yang, Chihae and Zaldívar-Comenges, José-Manuel and Cronin, Mark T. D.} }

2013-02-05 Cronin, Mark T. D. Richarz, Andrea-Nicole Neagu, Daniel Yang, Chihae Zaldívar-Comenges, José-Manuel Fioravanzo, Elena eng Neagu, Daniel Berthold, Michael R. 2017-02-13T14:31:47Z 2017-02-13T14:31:47Z Zaldívar-Comenges, José-Manuel The COSMOS (Integrated In Silico Models for the Prediction of Human Repeated Dose Toxicity of COSMetics to Optimise Safety) Project addresses the safety assessment needs of the cosmetics industry, without the use of animals. The main aim of the COSMOS Project ( is to develop freely available tools and workflows to predict safety to humans following the use of cosmetic ingredients. The integrated suite of computational workflows being developed includes models based on the threshold of toxicological concern (TTC) approach, innovative chemistry such as chemical categories, read-across and quantitative structure-activity relationships (QSARs) related to key events in adverse outcome pathways (AOP), and multiscale modeling based on physiologically-based pharmacokinetics (PBPK). Initial results include the development of the COSMOS database for curated repeat dose toxicity data as well as information on skin permeability, development of a robust inventory of materials used in cosmetics products and their associated chemical structures, datasets for better TTC analysis and the extension of the current TTC approach to cosmetics, as well as a KNIME platform including workflows to identify structural rules, fragments and properties associated with particular mechanisms of toxicity. In addition, a multi-scale modeling approach to predict target organ concentrations and extrapolate from in vitro to in vivo exposure scenarios has been established. The research leading to these results has received funding from the European Community’s Seventh Framework Program (FP7/2007-2013) under grant agreement n<sup>o</sup> 266835 and from Cosmetics Europe. Berthold, Michael R. Yang, Chihae Richarz, Andrea-Nicole Cronin, Mark T. D. Integrated in silico modeling for the prediction of chronic toxicity Fioravanzo, Elena

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