Alternative Methods for Skin-Sensitization Assessment

The dimer effect: A refinement approach towards skin sensitization assessment in-chemico using Amino acid Derivative Reactivity Assay

Skin sensitization is a key endpoint for safety assessment, especially for cosmetics and personal care products. The adverse outcome pathway for skin sensitization and the chemical and biological events driving the induction of human skin sensitization are now well understood. Several non-animal test methods have been developed to predict sensitizer potential by measuring the impact of chemical sensitizers on these key events. In this work, we have focused on Key Event 1 (the molecular initiating step), which is based on formation of a covalent adduct between skin sensitizers and endogenous proteins and/or peptides in the skin. There exists three in-chemico assays approved by the Organization for Economic Co-operation and Development-(1) Direct Peptide Reactivity Assay (DPRA), (2) Amino Acid Derivative Reactivity Assay (ADRA), and (3) Kinetic Direct Peptide Reactivity Assay (kDPRA) to quantify peptide/amino acid derivative depletion after incubation with test chemicals. However, overestimated depletion of the cysteine-based peptide/amino acid derivatives is known in such assays because of the dimerization of the thiol group. In this present work, we report the synthesis and structural confirmation of the dimer of N-(2-[1-naphthyl]acetyl)-L-cysteine (NAC) from the ADRA assay to allow simultaneous determination of (a) peptide depletion by quantifying NAC monomer and (b) peptide dimerization by quantifying NAC dimer thereby eliminating the overestimation. We present a case study with three chemicals to demonstrate the importance of this approach. Thus, this simultaneous assay gives a more informed view of the peptide reactivity of chemicals to better identify skin sensitizers.

The evaluation of skin sensitization potential of the UVCB substance diisopentyl phthalate by in silico and in vitro methods

Diisopentyl phthalate (DiPeP) is primarily used as a plasticizer or additive within the production of polyvinyl chloride (PVC), and has many additional industrial applications. Its metabolites were recently found in urinary samples of pregnant women; thus, this substance is of concern as relates to human exposure. Depending upon the nature of the alcohol used in its synthesis, DiPeP may exist either as a mixture consisting of several branched positional isomers, or as a single defined structure. This article investigates the skin sensitization potential and immunomodulatory effects of DiPeP CAS No. 84777-06-0, which is currently marketed and classified as a UVCB substance, by in silico and in vitro methods. Our findings showed an immunomodulatory effect for DiPeP in LPS-induced THP-1 activation assay (increased CD54 expression). In silico predictions using QSAR TOOLBOX 4.5, ToxTree, and VEGA did not identify DiPeP, in the form of a discrete compound, as a skin sensitizer. The keratinocyte activation (Key Event 2 (KE2) of the adverse outcome pathway (AOP) for skin sensitization) was evaluated by two different test methods (HaCaT assay and RHE assay), and results were discordant. While the HaCaT assay showed that DiPeP can activate keratinocytes (increased levels of IL-6, IL-8, IL-1α, and ILA gene expression), in the RHE assay, DiPeP slightly increased IL-6 release. Although inconclusive for KE2, the role of DiPeP in KE3 (dendritic cell activation) was demonstrated by the increased levels of CD54 and IL-8 and TNF-α in THP-1 cells (THP-1 activation assay). Altogether, findings were inconclusive regarding the skin sensitization potential of the UVCB DiPeP-disagreeing with the results of DiPeP in the form of discrete compound (skin sensitizer by the LLNA assay). Additional studies are needed to elucidate the differences between DiPeP isomer forms, and to better understand the applicability domains of non-animal methods in identifying skin sensitization hazards of UVCB substances.

Low-cost quantum mechanical descriptors for data efficient skin sensitization QSAR models

Quantitative Structure Activity Relationship modelling methodologies need to incorporate relevant mechanistic information to have high predictive performance and validity. Electrophilic reactivity is a common mechanistic feature of skin sensitization endpoints which could be concisely characterized with electronic descriptors which is key to enabling the modelling of small datasets in this domain. However, quantum mechanical methodologies have previously featured high computational costs which would exclude the use of large datasets. Consequently, we investigate the use of electronic descriptors calculated using the Hartree Fock with 3 corrections (Hf-3c) method, a low-cost ab initio methodology that has higher chemical accuracy than previous semiempirical methodologies for modelling in vitro skin sensitization assay outcomes. We also model the Ames assay as a surrogate for determining skin sensitization outcomes. The quantum chemical descriptors calculated using the Hf-3c method with conductor-like polarizable continuum model (CPCM) implicit solvation found improved QSAR model performance for the in vitro Ames (n = 6049, 0.770 AUC), KeratinoSens (n = 164, 0.763 AUC), and Direct Peptide Reactivity Assay (n = 122, 0.750 AUC) datasets, with their combination producing high predictive performance for unseen in vivo Local Lymph Node Assay (n = 86, 0.789 AUC) and Human Repeated Insult Patch Test (n = 86, 0.791 AUC) assay toxicant outcomes.

Guidelines for Manufacturing and Application of Organoids: Skin

To address the limitations of animal testing, scientific research is increasingly focused on developing alternative testing methods. These alternative tests utilize cells or tissues derived from animals or humans for in vitro testing, as well as artificial tissues and organoids. In western countries, animal testing for cosmetics has been banned, leading to the adoption of artificial skin for toxicity evaluation, such as skin corrosion and irritation assessments. Standard guidelines for skin organoid technology becomes necessary to ensure consistent data and evaluation in replacing animal testing with in vitro methods. These guidelines encompass aspects such as cell sourcing, culture techniques, quality requirements and assessment, storage and preservation, and organoid-based assays.

Circular economyeast: Saccharomyces cerevisiae as a sustainable source of glucans and its safety for skincare application

Glucans, a polysaccharide naturally present in the yeast cell wall that can be obtained from side streams generated during the fermentation process, have gained increasing attention for their potential as a skin ingredient. Therefore, this study focused on the extraction method to isolate and purify water-insoluble glucans from two different Saccharomyces cerevisiae strains: an engineered strain obtained from spent yeast in an industrial fermentation process and a wild strain produced through lab-scale fermentation. Two water-insoluble extracts with a high glucose content (> 90 %) were achieved and further subjected to a chemical modification using carboxymethylation to improve their water solubility. All the glucans' extracts, water-insoluble and carboxymethylated, were structurally and chemically characterized, showing almost no differences between both yeast-type strains. To ensure their safety for skin application, a broad safety assessment was undertaken, and no cytotoxic effect, immunomodulatory capacity (IL-6 and IL-8 regulation), genotoxicity, skin sensitization, and impact on the skin microbiota were observed. These findings highlight the potential of glucans derived from spent yeast as a sustainable and safe ingredient for cosmetic and skincare formulations, contributing to the sustainability and circular economy.

The BMDC model, a performant cell-based test to assess the sensitizing potential and potency of chemicals including pre/pro-haptens

BACKGROUND

Chemical-induced allergies at workplace represent a significant occupational health issue. These substances must be properly identified as sensitizers. In previous studies, an original model using mouse bone marrow-derived dendritic cells (BMDC) was developed for this purpose.

OBJECTIVES

The aim of this study was to evaluate the predictive capacity of the BMDC model with a large panel of sensitizers (including pre- and pro-haptens) and non-sensitizers.

METHODS

The readout from the BMDC model is based on expression levels of six phenotypic markers measured by flow cytometry.

RESULTS

The results indicate that 29 of the 37 non-sensitizers, and 81 of the 86 sensitizers were correctly classified compared to the Local Lymph Node Assay (LLNA). Statistical analysis revealed the BMDC model to have a sensitivity of 94%, a specificity of 78%, and an accuracy of 89%. The EC2 (Effective Concentration) values calculated with this model allow sensitizers to be categorized into four classes: extreme, strong, moderate and weak.

CONCLUSIONS

These excellent predictive performances show that the BMDC model discriminates between sensitizers and non-sensitizers with outstanding precision equal to or better than existing validated alternative models. Moreover, this model allows to predict sensitization potency of chemicals. The BMDC test could therefore be proposed as an additional tool to assess the sensitizing potential and potency of chemicals.

The 3Ranker: An AI-based Algorithm for Finding Non-animal Alternative Methods

The search for existing non-animal alternative methods for use in experiments is currently challenging because of the lack of both comprehensive structured databases and balanced keyword-based search strategies to mine unstructured textual databases. In this paper we describe 3Ranker, which is a fast, keyword-independent algorithm for finding non-animal alternative methods for use in biomedical research. The 3Ranker algorithm was created by using a machine learning approach, consisting of a Random Forest model built on a dataset of 35 million abstracts and constructed with weak supervision, followed by iterative model improvement with expert curated data. We found a satisfactory trade-off between sensitivity and specificity, with Area Under the Curve (AUC) values ranging from 0.85-0.95. Trials showed that the AI-based classifier was able to identify articles that describe potential alternatives to animal use, among the thousands of articles returned by generic PubMed queries on dermatitis and Parkinson's disease. Application of the classification models on time series data showed the earlier implementation and acceptance of Three Rs principles in the area of cosmetics and skin research, as compared to the area of neurodegenerative disease research. The 3Ranker algorithm is freely available at www.open3r.org; the future goal is to expand this framework to cover multiple research domains and to enable its broad use by researchers, policymakers, funders and ethical review boards, in order to promote the replacement of animal use in research wherever possible.

Read-across-based intelligent learning: development of a global q-RASAR model for the efficient quantitative predictions of skin sensitization potential of diverse organic chemicals

Environmental chemicals and contaminants cause a wide array of harmful implications to terrestrial and aquatic life which ranges from skin sensitization to acute oral toxicity. The current study aims to assess the quantitative skin sensitization potential of a large set of industrial and environmental chemicals acting through different mechanisms using the novel quantitative Read-Across Structure-Activity Relationship (q-RASAR) approach. Based on the identified important set of structural and physicochemical features, Read-Across-based hyperparameters were optimized using the training set compounds followed by the calculation of similarity and error-based RASAR descriptors. Data fusion, further feature selection, and removal of prediction confidence outliers were performed to generate a partial least squares (PLS) q-RASAR model, followed by the application of various Machine Learning (ML) tools to check the quality of predictions. The PLS model was found to be the best among different models. A simple user-friendly Java-based software tool was developed based on the PLS model, which efficiently predicts the toxicity value(s) of query compound(s) along with their status of Applicability Domain (AD) in terms of leverage values. This model has been developed using structurally diverse compounds and is expected to predict efficiently and quantitatively the skin sensitization potential of environmental chemicals to estimate their occupational and health hazards.

Bioactive limonoids from Carapa guianensis seeds oil and the sustainable use of its by-products

Carapa guianensis (Andiroba, Meliaceae) is considered a multipurpose tree. In Brazil, Indigenous people have used it as insect repellent and in the treatment of various diseases. Most biological activities and popular uses are attributed to limonoids, which are highly oxygenated tetranortriterpenoids. More than 300 limonoids have been described in Meliaceae family. Limonoids from Andiroba oil have shown high anti-inflammatory and anti-allergic activities in vivo, by inhibiting platelet activating factors and many inflammatory mediators such as IL-5, IL-1β and TNF-α. It also reduced T lymphocytes, eosinophils and mast cells. In corroboration with the wide popular use of Andiroba oil, no significant cytotoxicity or genotoxicity in vivo was reported. This oil promotes apoptosis in a gastric cancer cell line (ACP02) at high concentrations, without showing mutagenic effects, and is suggested to increase the body's nonspecific resistance and adaptive capacity to stressors, exhibit some antioxidant activity, and protect against oxidative DNA damages. Recently, new methodologies of toxicological assays have been applied. They include in chemico, in vitro, in silico and ex vivo procedures, and take place to substitute the use of laboratory animals. Andiroba by-products have been used in sustainable oil production processes and as fertilizers and soil conditioners, raw material for soap production, biodegradable surfactants and an alternative natural source of biodegradable polymer in order to reduce environmental impacts. This review reinforces the relevance of Andiroba and highlights its ability to add value to its by-products and to minimize possible risks to the health of the Amazonian population.