2013
DOI: 10.1016/j.yrtph.2013.09.007
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Computer models versus reality: How well do in silico models currently predict the sensitization potential of a substance

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Cited by 53 publications
(60 citation statements)
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“…Some of these available (Q)SARs have been encoded into expert, knowledge-based systems that are available for the prediction of skin sensitization (e.g., Derek for Windows (DfW)), statistical systems (e.g., TOPKAT, MCASE) and hybrid systems (e.g., Tissue Metabolism Simulator (TIMES)). Comprehensive reviews and evaluation of expert systems, SARs and QSARs are available from ECETOC and in the form of publications from Patlewicz et al and Teubner et al (ECETOC, 2003;Patlewicz et al, 2008;Teubner et al, 2013).…”
Section: Resultsmentioning
confidence: 99%
“…Some of these available (Q)SARs have been encoded into expert, knowledge-based systems that are available for the prediction of skin sensitization (e.g., Derek for Windows (DfW)), statistical systems (e.g., TOPKAT, MCASE) and hybrid systems (e.g., Tissue Metabolism Simulator (TIMES)). Comprehensive reviews and evaluation of expert systems, SARs and QSARs are available from ECETOC and in the form of publications from Patlewicz et al and Teubner et al (ECETOC, 2003;Patlewicz et al, 2008;Teubner et al, 2013).…”
Section: Resultsmentioning
confidence: 99%
“…Two such profilers are the protein-binding profilers based on OECD and OASIS algorithms (''Protein binding by OECD'', ''Protein binding by OASIS v1.2''). In order to also identify substances, which require abiotic or metabolic activation, the ''auto-oxidation profiler'' and the ''skin metabolism profiler'' were used Teubner et al, 2013.…”
Section: Oecd Qsar Toolboxmentioning
confidence: 99%
“…In an independent evaluation of three different QSAR models developed for assessment of chemical sensitizers, estimated predictive accuracies ranged between 59-74% [41]. A more recent evaluation revealed that QSARs indeed are able to perform accurate predictions, with examples of models performing perfectly in limited chemical domains [42]. Thus, the authors conclude that while mechanistic models can be used to a certain degree under well-defined conditions, in silico models for sensitizers are currently not sufficient for accurate predictions in a broad chemical space.…”
Section: In Vitro Assaysmentioning
confidence: 99%