The skin allergy risk assessment-integrated chemical environment (SARA-ICE) defined approach to derive points of departure for skin sensitization.

Mechanistically based non-animal methods for assessing skin sensitization hazard have been developed, but are not considered sufficient, individually, to conclusively define the skin sensitization potential or potency of a chemical. This resulted in the development of defined approaches (DAs), as documented in OECD TG 497, for combining information sources in a prescriptive manner to provide a determination of risk or potency. However, there are currently no DAs within OECD TG 497 that can derive a point of departure (POD) for risk assessment. The Skin Allergy Risk Assessment - Integrated Chemical Environment (SARA-ICE) DA for skin sensitization is a Bayesian statistical model that estimates a human-relevant metric of sensitizer potency, the ED₀₁, an estimate of the human predictive patch test dermal dose at which there is 1% chance of inducing sensitization, which can be used in a risk assessment paradigm. The model accounts for variability of input data and explicitly quantifies uncertainty. SARA-ICE derives the ED₀₁ from a variety of in vitro and in vivo test method data and is built upon historical human, murine, and in vitro test data for 434 chemicals. In addition to the ED₀₁ POD SARA-ICE DA also provides a Globally Harmonized System of Classification and Labelling of Chemicals (GHS) classification probability for GHS subcategories 1A, 1B and not classified (NC). Here we describe the SARA-ICE model and its evaluation, including performance versus benchmark PODs. In addition, via a case study with isothiazolinones (ITs), we demonstrate the utility of SARA-ICE for integrating different data inputs and compare the ED₀₁ for six ITs to existing historical data.