LAUSR

Safety assessment is an essential component of the regulatory acceptance of industrial chemicals. Previously we have developed a model to predict skin sensitization potential of chemicals for two assays, human patch test and murine local lymph node assay, and implemented this model in a web portal. Here, we report on the substantially revised and expanded freely available web tool, Pred-Skin version 3.0. This up-to-date version of Pred-Skin incorporates multiple Quantitative Structure-Activity Relationship (QSAR) models developed with in vitro, animal in vivo, and human ex vivo data, integrated into a consensus Naïve Bayes model that predicts human effects. Individual QSAR models were generated using skin sensitization data derived from human repeat insult patch tests (HRIPTs), human maximization tests (HMTs), as well as mouse Local Lymph Node Assay (LLNA). In addition, data for three validated alternative methods, Direct Peptide Reactivity Assay (DPRA), KeratinoSens, and the human Cell Line Activation Test (h-CLAT) were employed as well. Models were developed using open-source tools and rigorously validated according to the best practices of QSAR modeling. Predictions obtained from these models were then used to build a Naïve Bayes model for predicting human skin sensitization with the following external prediction accuracy: correct classification rate (89%), sensitivity (94%), positive predicted value (91%), specificity (84%), and negative predicted value (89%). As an additional assessment of model performance, we identified eleven cosmetic ingredients known to cause skin sensitization but not included in our training set, and nine of them were accurately predicted as sensitizers by our models. All models are freely accessible through the Pred-Skin v. 3.0 portal at http://predskin.labmol.com.br/. Pred-Skin can be used as a reliable alternative to animal tests for predicting human skin sensitization.