GARDskin dose-response assay and its application in conducting Quantitative Risk Assessment (QRA) for fragrance materials using a Next Generation Risk Assessment (NGRA) framework.

Development of New Approach Methodologies (NAMs) capable of providing a No Expected Sensitization Induction Level (NESIL) value remains a high priority for the fragrance industry for conducting a Quantitative Risk Assesment (QRA) to evaluate dermal sensitization. The in vitro GARDskin assay was recently adopted by the OECD (TG 442E) for the hazard identification of skin sensitizers. Continuous potency predictions are derived using a modified protocol that incorporates dose-response measurements. Linear regression models have been developed to predict human NESIL values. The aim of the study was to evaluate the precision and reproducibility of the continuous potency predictions from the GARDskin Dose-Response (DR) assay and its application in conducting QRA for fragrance materials using a Next Generation Risk Assessment (NGRA) framework. Results indicated that the GARDskin Dose-Response model predicted human NESIL values with a good degree of concordance with published NESIL values, which were also reproducible in 3 separate experiments. Using Isocyclocitral as an example, a QRA was conducted to determine its safe use levels in different consumer product types using a NGRA framework. This study represents a major step towards the establishment of the assay to derive NESIL values for conducting QRA evaluations for fragrance materials using a NGRA framework.

Quantitative assessment of sensitizing potency using a dose-response adaptation of GARDskin.

Hundreds of chemicals have been identified as skin sensitizers. These are chemicals that possess the ability to induce hypersensitivity reactions in humans, giving rise to a condition termed allergic contact dermatitis. The capacity to limit hazardous exposure to such chemicals depends upon the ability to accurately identify and characterize their skin sensitizing potency. This has traditionally been accomplished using animal models, but their widespread use offers challenges from both an ethical and a scientific perspective. Comprehensive efforts have been made by the scientific community to develop new approach methodologies (NAMs) capable of replacing in vivo assays, which have successfully yielded several methods that can identify skin sensitizers. However, there is still a lack of new approaches that can effectively measure skin sensitizing potency. We present a novel methodology for quantitative assessment of skin sensitizing potency, which is founded on the already established protocols of the GARDskin assay. This approach analyses dose-response relationships in the GARDskin assay to identify chemical-specific concentrations that are sufficient to induce a positive response in the assay. We here compare results for 22 skin sensitizers analyzed using this method with both human and LLNA potency reference data and show that the results correlate strongly and significantly with both metrics (rLLNA = 0.81, p = 9.1 × 10-5; rHuman = 0.74, p = 1.5 × 10-3). In conclusion, the results suggest that the proposed GARDskin dose-response methodology provides a novel non-animal approach for quantitative potency assessment, which could represent an important step towards reducing the need for in vivo experiments.

Validation of the GARD™skin Assay for Assessment of Chemical Skin Sensitizers: Ring Trial Results of Predictive Performance and Reproducibility.

Proactive identification of chemicals with skin sensitizing properties is a key toxicological endpoint within chemical safety assessment, as required by legislation for registration of chemicals. In order to meet demands of increased animal welfare and facilitate increased testing efficiency also in nonregulatory settings, considerable efforts have been made to develop nonanimal approaches to replace current animal testing. Genomic Allergen Rapid Detection (GARD™) is a state-of-the-art technology platform, the most advanced application of which is the assay for assessment of skin sensitizing chemicals, GARD™skin. The methodology is based on a dendritic cell (DC)-like cell line, thus mimicking the mechanistic events leading to initiation and modulation of downstream immunological responses. Induced transcriptional changes are measured following exposure to test chemicals, providing a detailed evaluation of cell activation. These changes are associated with the immunological decision-making role of DCs in vivo and include among other phenotypic modifications, up-regulation of co-stimulatory molecules, induction of cellular and oxidative stress pathways and xenobiotic responses, and provide a holistic readout of substance-induced DC activation. Here, results from an inter-laboratory ring trial of GARD™skin, conducted in compliance with OECD guidance documents and comprising a blinded chemical test set of 28 chemicals, are summarized. The assay was found to be transferable to naïve laboratories, with an inter-laboratory reproducibility of 92.0%. The within-laboratory reproducibility ranged between 82.1% and 88.9%, whereas the cumulative predictive accuracy across the 3 laboratories was 93.8%. It was concluded that GARD™skin is a robust and reliable method for the identification of skin sensitizing chemicals and suitable for stand-alone use or as a constituent of integrated testing. These data form the basis for the regulatory validation of GARD™skin.

The GARD platform for potency assessment of skin sensitizing chemicals.

Contact allergy induced by certain chemicals is a common health concern, and several alternative methods have been developed to fulfill the requirements of European legislation with regard to hazard assessment of potential skin sensitizers. However, validated methods, which provide information about the potency of skin sensitizers, are still lacking. The cell-based assay Genomic Allergen Rapid Detection (GARD), targeting key event 3, dendritic cell activation, of the skin sensitization AOP, uses gene expression profiling and a machine learning approach for the prediction of chemicals as sensitizers or non-sensitizers. Based on the GARD platform, we here expanded the assay to predict three sensitizer potency classes according to the European Classification, Labelling and Packaging (CLP) Regulation, targeting categories 1A (strong), 1B (weak) and no cat (non-sensitizer). Using a random forest approach and 70 training samples, a potential biomarker signature of 52 transcripts was identified. The resulting model could predict an independent test set consisting of 18 chemicals, six from each CLP category and all previously unseen to the model, with an overall accuracy of 78%. Importantly, the model was shown to be conservative and only underestimated the class label of one chemical. Furthermore, an association of defined chemical protein reactivity with distinct biological pathways illustrates that our transcriptional approach can reveal information contributing to the understanding of underlying mechanisms in sensitization.