Skin Sensitization Potency Prediction Based on Read-Across (RAx) Incorporating RhE-Based Testing Strategy (RTSv1)-Defined Approach: RTSv1-Based RAx.

In recent years, nonanimal approaches for skin sensitization have been developed in response to political, regulatory, and ethical demands. The reconstructed human epidermis (RhE)-based testing strategy (RTS)v1-defined approach (DA) is used to categorize skin sensitization potency. However, the RTSv1 DA alone cannot be used to predict potency based on EC3 values [the estimated concentration that produces a stimulation index of 3 in the local lymph node assay (LLNA)], and underpredictions have been reported. Read-across (RAx) can complement DA data and improve prediction confidence. Although case studies combining new approach methodology/DA data with RAx have been reported, they focus on a single target chemical and lack a comprehensive and robust strategy with well-examined reliability. This study developed a strategy incorporating the RTSv1 DA into RAx (RTSv1-based RAx) to predict skin sensitization potency, applying it to 43 chemicals. The predictive performance of RTSv1-based RAx was evaluated by comparing its predicted potency category and EC3 outcomes with those of RTSv1 DA and the LLNA. RTSv1-based RAx accurately predicted the Globally Harmonized System of Classification (GHS) subcategorization for 38 chemicals and determined the predicted EC3 values for 17 sensitizers within a fourfold range of LLNA-derived EC3 values. This study demonstrates that RTSv1-based RAx offers robust predictivity for both GHS subcategorization and predicted EC3 values, making it useful for quantitative risk assessment.