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Cosmetic regulations prohibit animal testing for the purpose of safety assessment and recent registration, evaluation and authorization of chemicals guidance states that the local lymph node assay (LLNA) in mice shall only be conducted if in vitro data cannot give sufficient information for classification and labeling. However, Quantitative Risk Assessment for fragrance ingredients requires an NESIL (no expected sensitization induction level), a dose not expected to cause induction of skin sensitization in humans. In absence of human data, this is derived from the LLNA and it remains a key challenge for risk assessors to derive this value from nonanimal data. Here we present a workflow using structural information, reactivity data and KeratinoSens results to predict an LLNA result as a point of departure. Specific additional tests (metabolic activation, complementary reactivity tests) are applied in selected cases depending on the chemical domain of a molecule. Finally, in vitro and in vivo data on close analogues are used to estimate uncertainty of the prediction in the specific chemical domain. This approach was applied to three molecules which were subsequently tested in the LLNA and 22 molecules with available and sometimes discordant human and LLNA data. Four additional case studies illustrate how this approach is being applied to recently developed molecules in the absence of animal data. Estimation of uncertainty and how this can be applied to determine a final NESIL for risk assessment is discussed. We conclude that, in the data-rich domain of fragrance ingredients, sensitization risk assessment without animal testing is possible in most cases by this integrated approach.

Sensitization, the prerequisite event in the development of allergic contact dermatitis, is a key parameter in both hazard and risk assessments. The pathways involved have recently been formally described in the OECD adverse outcome pathway (AOP) for skin sensitization. One single non-animal test method will not be sufficient to fully address this AOP and in many cases the use of a battery of tests will be necessary. A number of methods are now fully developed and validated. In order to facilitate acceptance of these methods by both the regulatory and scientific communities, results of the single test methods (DPRA, KeratinoSens, LuSens, h-CLAT, (m)MUSST) as well for a the simple '2 out of 3' ITS for 213 substances have been compiled and qualitatively compared to both animal and human data. The dataset was also used to define different mechanistic domains by probable protein-binding mechanisms. In general, the non-animal test methods exhibited good predictivities when compared to local lymph node assay (LLNA) data and even better predictivities when compared to human data. The '2 out of 3' prediction model achieved accuracies of 90% or 79% when compared to human or LLNA data, respectively and thereby even slightly exceeded that of the LLNA., (Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.)

The currently available animal-free methods for the detection of skin sensitizing potential of chemicals seem promising. However, no single method is able to comprehensively represent the complexity of the processes involved in skin sensitization. To ensure a mechanistic basis and cover the complexity, multiple methods should be integrated into a testing strategy, in accordance with the adverse outcome pathway that describes all key events in skin sensitization. Although current majority voting testing strategies have proven effective, the performance of individual methods is not taken into account. To that end, we designed a tiered strategy based on complementary characteristics of the included methods, and compared it to a majority voting approach. This tiered testing strategy was able to correctly identify all 41 chemicals tested. In terms of total number of experiments required, the tiered testing strategy requires less experiments compared to the majority voting approach. On the other hand, this tiered strategy is more complex due the number of different alternative methods required, and predicted costs are similar for both strategies. Both the tiered and majority voting strategies provide a mechanistic basis for skin sensitization testing, but the strategy most suitable for regulatory decision-making remains to be determined., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Skin sensitization is a key endpoint for cosmetic ingredients, with a forthcoming ban for animal testing in Europe. Four alternative tests have so far been submitted to ECVAM prevalidation: (i) MUSST and (ii) h-Clat assess surface markers on dendritic cell lines, (iii) the direct peptide reactivity assay (DPRA) measures reactivity with model peptides and (iv) the KeratinoSens(TM) assay which is based on detection of Nrf2-induced luciferase. It is anticipated that only an integrated testing strategy (ITS) based on a battery of tests might give a full replacement providing also a sensitization potency assessment, but this concept should be tested with a data-driven analysis. Here we report a database on 145 chemicals reporting the quantitative endpoints measured in a U937- test, the DPRA and KeratinoSens(TM) . It can serve to develop data-driven ITS approaches as we show in a parallel paper and provides a view as to the current ability to predict with in vitro tests as we are entering 2013. It may also serve as reference database when benchmarking new molecules with in vitro based read-across and find use as a reference database when evaluating new tests. The tests and combinations thereof were evaluated for predictivity, and overall a similar predictivity was found as before on three-fold smaller datasets. Analysis of the dose-response parameters of the individual tests indicates a correlation to sensitization potency. Detailed analysis of chemicals false-negative and false-positive in two tests helped to define limitations in the tests but also in the database derived from animal studies., (Copyright © 2013 John Wiley & Sons, Ltd.)

Tests for skin sensitization are required prior to the market launch of new cosmetic ingredients. Significant efforts are made to replace the current animal tests. It is widely recognized that this cannot be accomplished with a single in vitro test, but that rather the integration of results from different in vitro and in silico assays will be needed for the prediction of the skin sensitization potential of chemicals. This has been proposed as a theoretical scheme so far, but no attempts have been made to use experimental data to prove the validity of this concept. Here we thus try for the first time to fill this widely cited concept with data. To this aim, we integrate and report both novel and literature data on 116 chemicals of known skin sensitization potential on the following parameters: (1) peptide reactivity as a surrogate for protein binding, (2) induction of antioxidant/electrophile responsive element dependent luciferase activity as a cell-based assay; (3) Tissue Metabolism Simulator skin sensitization model in silico prediction; and (4) calculated octanol-water partition coefficient. The results of the in vitro assays were scaled into five classes from 0 to 4 to give an in vitro score and compared to the local lymph node assay (LLNA) data, which were also scaled from 0 to 4 (nonsensitizer/weak/moderate/strong/extreme). Different ways of evaluating these data have been assessed to rate the hazard of chemicals (Cooper statistics) and to also scale their potency. With the optimized model an overall accuracy for predicting sensitizers of 87.9% was obtained. There is a linear correlation between the LLNA score and the in vitro score. However, the correlation needs further improvement as there is still a relatively high variation in the in vitro score between chemicals belonging to the same sensitization potency class.