Real world-like simulations show efficient predictive power of in vitro skin corrosion tests used as stand-alone and in combination and how can toxicologists take advantage of them

Evaluating the QileX-RhE skin corrosion test for chemical subcategorization in accordance with OECD TG 431

Skin corrosion testing is integral to evaluating the potential harm posed by chemicals, impacting regulatory decisions on safety, transportation, and labeling. Traditional animal testing methods are giving way to in vitro alternatives, such as reconstructed human epidermis (RhE) models, aligning with evolving ethical standards. This study evaluates the QileX-RhE test system's performance for chemical subcategorization within the OECD TG 431 framework. Results demonstrate its ability to differentiate subcategories, accurately predicting 83% of UN GHS Category 1A and 73% of UN GHS Category 1B/1C chemicals with 100% sensitivity in corrosive prediction. Additionally, this study provides a comprehensive assessment of the test method's performance by employing nuanced parameters such as positive predictive value (PPV), negative predictive value (NPV), post-test odds and likelihood rations, offering valuable insights into the applicability and effectiveness of the QileX-RhE test method.

Expansion of the Cosmetics Europe skin sensitisation database with new substances and PPRA data

The assessment of skin sensitisation is a key requirement in all regulated sectors, with the European Union's regulation of cosmetic ingredients being most challenging, since it requires quantitative skin sensitisation assessment based on new approach methodologies (NAMs). To address this challenge, an in-depth and harmonised understanding of NAMs is fundamental to inform the assessment. Therefore, we compiled a database of NAMs, and in vivo (human and local lymph node assay) reference data. Here, we expanded this database with 41 substances highly relevant for cosmetic industry. These structurally different substances were tested in six NAMs (Direct Peptide Reactivity Assay, KeratinoSens™, human Cell Line Activation Test, U-SENS™, SENS-IS, Peroxidase Peptide Reactivity Assay). Our analysis revealed that the substances could be tested without technical limitations, but were generally overpredicted when compared to reference results. Reasons for this reduced predictivity were explored through pairwise NAM comparisons and association of overprediction with hydrophobicity. We conclude that more detailed understanding of how NAMs apply to a wider range of substances is needed. This would support a flexible and informed choice of NAMs to be optimally applied in the context of a next generation risk assessment framework, ultimately contributing to the characterisation and reduction of uncertainty.