To develop a testing strategy incorporating the human cell line activation test (h-CLAT), direct peptide reactivity assay (DPRA) and DEREK, we created an expanded data set of 139 chemicals (102 sensitizers and 37 non-sensitizers) by combining the existing data set of 101 chemicals through the collaborative projects of Japan Cosmetic Industry Association. Of the additional 38 chemicals, 15 chemicals with relatively low water solubility (log Kow > 3.5) were selected to clarify the limitation of testing strategies regarding the lipophilic chemicals. Predictivities of the h-CLAT, DPRA and DEREK, and the combinations thereof were evaluated by comparison to results of the local lymph node assay. When evaluating 139 chemicals using combinations of three methods based on integrated testing strategy (ITS) concept (ITS-based test battery) and a sequential testing strategy (STS) weighing the predictive performance of the h-CLAT and DPRA, overall similar predictivities were found as before on the 101 chemical data set. An analysis of false negative chemicals suggested a major limitation of our strategies was the testing of low water-soluble chemicals. When excluded the negative results for chemicals with log Kow > 3.5, the sensitivity and accuracy of ITS improved to 97% (91 of 94 chemicals) and 89% (114 of 128). Likewise, the sensitivity and accuracy of STS to 98% (92 of 94) and 85% (111 of 129). Moreover, the ITS and STS also showed good correlation with local lymph node assay on three potency classifications, yielding accuracies of 74% (ITS) and 73% (STS). Thus, the inclusion of log Kow in analysis could give both strategies a higher predictive performance.

The skin sensitization potential of chemicals has been determined with the use of the murine local lymph node assay (LLNA). However, in recent years public concern about animal welfare has led to a requirement for non-animal risk assessment systems for the prediction of skin sensitization potential, to replace LLNA. Selection of an appropriate in vitro test or in silico model descriptors is critical to obtain good predictive performance. Here, we investigated the utility of artificial neural network (ANN) prediction models using various combinations of descriptors from several in vitro sensitization tests. The dataset, collected from published data and from experiments carried out in collaboration with the Japan Cosmetic Industry Association (JCIA), consisted of values from the human cell line activation test (h-CLAT), direct peptide reactivity assay (DPRA), SH test and antioxidant response element (ARE) assay for chemicals whose LLNA thresholds have been reported. After confirming the relationship between individual in vitro test descriptors and the LLNA threshold (e.g. EC3 value), we used the subsets of chemicals for which the requisite test values were available to evaluate the predictive performance of ANN models using combinations of h-CLAT/DPRA (N = 139 chemicals), the DPRA/ARE assay (N = 69), the SH test/ARE assay (N = 73), the h-CLAT/DPRA/ARE assay (N = 69) and the h-CLAT/SH test/ARE assay (N = 73). The h-CLAT/DPRA, h-CLAT/DPRA/ARE assay and h-CLAT/SH test/ARE assay combinations showed a better predictive performance than the DPRA/ARE assay and the SH test/ARE assay. Our data indicates that the descriptors evaluated in this study were all useful for predicting human skin sensitization potential, although combinations containing h-CLAT (reflecting dendritic cell-activating ability) were most effective for ANN-based prediction.

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The Organisation for Economic Cooperation and Development (OECD) Test Guideline (TG) 439 is an in vitro test method of reconstructed human epidermis (RhE), which was developed for hazard identification of irritating chemicals in accordance with a primary skin irritation test using rabbits with 4-hr exposure. A regulation for quasi-drugs in Japan requires data from primary skin irritation tests using rabbits to undergo 24-hr exposure, and this is used as an evidence for 24-hr closed patch tests in humans. In this study with the same chemicals, primary skin irritation test data using rabbits undergoing 24-hr exposure and a 24-hr occlusive human patch test data were analyzed by comparing the results obtained with four test methods adopted in OECD TG 439. The performances of in vitro test methods showed a positive predictive value of 72.7-85.7% to predict the results of 24-hr primary rabbit skin irritation test knowing that its positive predictive value was 57.1% against humans only. The prediction factors of in vitro test methods were higher for the human patch test data with a sensitivity reaching 60 to 80%. Three surfactants gave false negatives in some of the RhE methods evaluated with the human patch test, but in each case, they were correctly classified as positive when evaluated at double concentration. Therefore, the approach of setting the margin to 2 was effective in eliminating false negatives. This suggests that in vitro test methods are useful for assessing skin irritation potential without animal testing for the application of quasi-drugs in Japan.