The animal tests have been recently banned for cosmetic ingredients in 2013 by the European Union. The assay measures the proliferation of lymphocytes during the induction phase of skin sensitization and provides EC3 values (effective concentration for a stimulation index of threefold in lymphocyte proliferation compared to vehicle controls) to make comparisons of the relative potency of different chemical sensitizers. The murine local lymph node assay (LLNA) has been established as an alternative animal model to traditional guinea pig methods to provide important animal welfare benefits and has been successfully validated and incorporated into a regulatory guideline described as Organization for Economic Cooperation and Development (OECD) Test Guideline Number 429. Nevertheless, these protocols are relatively long and complex with some limitations.

Traditionally, guinea pig maximization test (GPMT) and Buehler assay (BA) are utilized as predictive animal models for the identification of skin sensitizers and are widely accepted by regulatory authorities due to their reliable detection of potential human contact allergens. These chemically modified proteins may trigger T cell-mediated immune reactions and lead to ACD. Chemical sensitizers, which may be detergents, preservatives, or fragrances in household and personal care products or active ingredients, impurities from synthetic process and industrial materials in the pharmaceutical products, act as haptens binding to protein molecules. Skin sensitization is thereby an important toxicological endpoint in chemical safety assessment and a focus in regulatory decision making. The disease not only impairs the quality of life for the patients but also results in high costs in healthcare systems and economy. Skin sensitization associated with allergic contact dermatitis (ACD) is the second most common occupational illness accounting for 10–15% of all occupational disease worldwide. In addition to providing datasets for developing computational models, SkinSensDB is equipped with browsing and search tools which enable the assessment of new compounds for their skin sensitization potentials based on data from structurally similar compounds. To facilitate the development of AOP-based prediction models, a skin sensitization database named SkinSensDB has been constructed by curating data from published AOP-related assays. However, there are few freely available databases integrating both the in vivo and the in vitro skin sensitization assays for development of AOP-based skin sensitization prediction models.

Current computational models to predict skin sensitization mainly based on in vivo assays without incorporating alternative in vitro assays. The integration of multiple assays as key events in the AOP has been shown to have improved prediction performance. The development of the adverse outcome pathway (AOP) and associated alternative in vitro assays have reshaped the assessment of skin sensitizers.

Prediction of chemical skin sensitizer had traditionally relied on data from rodent models. Skin sensitization is an important toxicological endpoint for chemical hazard determination and safety assessment.

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