The Bone-Marrow derived Dendritic Cell (BMDC) test is a promising assay for identifying sensitizing chemicals based on the 3Rs (Replace, Reduce, Refine) principle. This study expanded the BMDC benchmarking to various in vitro, in chemico, and in silico assays targeting different key events (KE) in the skin sensitization pathway, using common substances datasets. Additionally, a Quantitative Structure-Activity Relationship (QSAR) model was developed to predict the BMDC test outcomes for sensitizing or non-sensitizing chemicals. The modeling workflow involved ISIDA (In Silico Design and Data Analysis) molecular fragment descriptors and the SVM (Support Vector Machine) machine-learning method. The BMDC model's performance was at least comparable to that of all ECVAM-validated models regardless of the KE considered. Compared with other tests targeting KE3, related to dendritic cell activation, BMDC assay was shown to have higher balanced accuracy and sensitivity concerning both the Local Lymph Node Assay (LLNA) and human labels, providing additional evidence for its reliability. The consensus QSAR model exhibits promising results, correlating well with observed sensitization potential. Integrated into a publicly available web service, the BMDC-based QSAR model may serve as a cost-effective and rapid alternative to lab experiments, providing preliminary screening for sensitization potential, compound prioritization, optimization and risk assessment.
Keywords: 3Rs principle; BMDC; Benchmark; LLNA; QSAR model; Sensitizing chemicals.
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