Skin sensitization leading to allergic contact dermatitis (ACD) is one of the most significant environmental health issues resulting from exposure to chemicals in commercial products. ACD accounts for ca. 90% of occupational skin diseases (10% of all occupational diseases), posing significant public health burden. According to the European Commission, skin sensitization testing represents over 5% of all toxicity testing.Currently, the local lymph node assay (LLNA, OECD 429) is the preferred test method; however, in April 2015 anin chimico method (direct peptide reactivity assay, DPRA) and two in vitro methods (ARE-Nrf2 Luciferase test, OECD 442D, and Human Cell Line Activation Test, h-CLAT) were validated at ECVAM (the European Centre for the Validation of Alternative Methods) to alleviate animal testing where permissible. These non-animal tests cover specific events within the skin sensitization AOP, and should only be considered in combinations and/or supported by in silico methods.In contrast to in vitro and in chimico tests, a single in silico model can address all key initiation events within the skin sensitization AOP (skin permeation, activation by auto-oxidation or by enzymes and haptenation with skin proteins/peptides), and provide assessments at lower cost and shorter timeframes. However, existing models are hindered by over-reliance on structural features of chemicals, statistics that obscure mechanistic relationships and by a relatively small, publicly available training set of chemicals with reliable LLNA data. Consequently, existing in silico models have often performed inadequately in external tests, particularly within the pharmaceutical chemical space, which is dominated by large and functionally diverse chemicals.
CADRE's skin sensitization model (CADRE-SS) was co-developed with Sustainability A to Z and Redshift Technologies, and was validated in collaboration with Bristol Myers Squibb and BASF to encompass commodity and pharmaceutical chemical space. It is a computational tool that blends expert rules, quantum-mechanical modeling, molecular simulations and multivariate statistics to predict skin sensitization potential and relative potency of chemicals and formulations. Developed as a tiered system, our model evaluates skin sensitization comprehensively as a function of skin permeability, metabolism and reactivity with skin proteins and peptides. In contrast to competing in silico technologies that rely on structure-based descriptors, CADRE-SS uses descriptors derived from modeling of molecular interactions. Each technical component of CADRE-SS represents cutting-edge research in its field: molecular interactions are studied using Monte-Carlo simulations in conjunction with quantum and classical mechanics calculations; covalent protein-binding is assessed with tailored hybrid density-functional (DFT) methods; and statistical models rely on advanced genetic algorithms. Consequently, CADRE-SS consistently achieves above 90% concordance with experimental human and animal tests. As all models within CADRE, our skin model was constructed in accordance with OECD Validation Principles for (Q)SARs(2) and guidelines for QSARs published by Tropsha and Gramatica (3).
External validaiton reports are available upon request from our Contact us page.