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

Abstract

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.