Comparison of the predictive nature of the Genomic Allergen Rapid Detection (GARD) assay with mammalian assays in determining the skin sensitisation potential of agrochemical active ingredients

GARD™skin and GARD™potency: A proof-of-concept study investigating applicability domain for agrochemical formulations

Several New Approach Methodologies (NAMs) for hazard assessment of skin sensitisers have been formally validated. However, data regarding their applicability on certain product classes are limited. The purpose of this project was to provide initial evidence on the applicability domain of GARD™skin and GARD™potency for the product class of agrochemical formulations. For this proof of concept, 30 liquid and 12 solid agrochemical formulations were tested in GARDskin for hazard predictions. Formulations predicted as sensitisers were further evaluated in the GARDpotency assay to determine GHS skin sensitisation category. The selected formulations were of product types, efficacy groups and sensitisation hazard classes representative of the industry's products. The performance of GARDskin was estimated by comparing results to existing in vivo animal data. The overall accuracy, sensitivity, and specificity were 76.2% (32/42), 85.0% (17/20), and 68.2% (15/22), respectively, with the predictivity for liquid formulations being slightly higher compared to the solid formulations. GARDpotency correctly subcategorized 14 out of the 17 correctly predicted sensitisers. Lack of concordance was justifiable by compositional or borderline response analysis. In conclusion, GARDskin and GARDpotency showed satisfactory performance in this initial proof-of-concept study, which supports consideration of agrochemical formulations being within the applicability domain of the test methods.

The correlation of haptenation of gold nanoparticles and cysteine modified screen printed carbon electrode by impedance technique with local lymph node assay data

Skin sensitization occurs when a skin sensitizer binds covalently to skin proteins through the haptenation process. The objective of this study was to correlate the electrochemical impedance spectroscopy (EIS) data of a screen printed carbon electrode (SPCE) modified with cysteine and gold nanoparticles (AuNPs) with local lymph node assay (LLNA) data as a potential skin sensitizer biosensor. The EIS was used to quantify variations in charge transfer resistance of skin sensitizers (ΔR_CT^{skin sensitizer}) due to different binding rates of skin sensitizers to cysteine. SPCE was modified through electrodeposition of AuNPs/thiourea/self-assembly of AuNPs/cysteine (assigned as ETSC) for the detection of skin sensitizers. Surface analysis of modified SPCEs using FESEM and EDX revealed a smooth surface with an uneven distribution of cysteine with AuNPs molecules. The ETSC modified SPCE showed a significant skin sensitizer biosensor since the ΔR_CT^{skin sensitizer} readings were increased proportionally to the strength of the skin sensitizers, with strong/extreme skin sensitizers displaying higher ΔR_CT^{skin sensitizer} readings compared to moderate and weak/non-skin sensitizers. The skin sensitization analysis from this work was compared to LLNA (animal study), human cell line activation (h-CLAT), direct peptide reactivity assay (DPRA), and KeratinoSens™, surface plasmon resonance (SPR) matched the categorization of LLNA in the following descending order: 96%, 92%, 82%, 70%, 70%, and 12%. With just an 8% mismatch with LLNA data, the EIS approach used in this study could be used as a screening tool for skin sensitizers.

Skin Sensitization Testing: The Ascendancy of Non-Animal Methods

A century ago, toxicology was an empirical science identifying substance hazards in surrogate mammalian models. Over several decades, these models improved, evolved to reduce animal usage, and recently have begun the process of dispensing with animals entirely. However, despite good hazard identification, the translation of hazards into adequately assessed risks to human health often has presented challenges. Unfortunately, many skin sensitizers known to produce contact allergy in humans, despite being readily identified as such in the predictive assays, continue to cause this adverse health effect. Increasing the rigour of hazard identification is inappropriate. Regulatory action has only proven effective via complete bans of individual substances. Since the problem applies to a broad range of substances and industry categories, and since generic banning of skin sensitizers would be an economic catastrophe, the solution is surprisingly simple—they should be subject to rigorous safety assessment, with the risks thereby managed accordingly. The ascendancy of non-animal methods in skin sensitization is giving unparalleled opportunities in which toxicologists, risk assessors, and regulators can work in concert to achieve a better outcome for the protection of human health than has been delivered by the in vivo methods and associated regulations that they are replacing.

In silico Prediction of Skin Sensitization: Quo vadis?

Skin direct contact with chemical or physical substances is predisposed to allergic contact dermatitis (ACD), producing various allergic reactions, namely rash, blister, or itchy, in the contacted skin area. ACD can be triggered by various extremely complicated adverse outcome pathways (AOPs) remains to be causal for biosafety warrant. As such, commercial products such as ointments or cosmetics can fulfill the topically safe requirements in animal and non-animal models including allergy. Europe, nevertheless, has banned animal tests for the safety evaluations of cosmetic ingredients since 2013, followed by other countries. A variety of non-animal in vitro tests addressing different key events of the AOP, the direct peptide reactivity assay (DPRA), KeratinoSens™, LuSens and human cell line activation test h-CLAT and U-SENS™ have been developed and were adopted in OECD test guideline to identify the skin sensitizers. Other methods, such as the SENS-IS are not yet fully validated and regulatorily accepted. A broad spectrum of in silico models, alternatively, to predict skin sensitization have emerged based on various animal and non-animal data using assorted modeling schemes. In this article, we extensively summarize a number of skin sensitization predictive models that can be used in the biopharmaceutics and cosmeceuticals industries as well as their future perspectives, and the underlined challenges are also discussed.