The Skin Sensitisation of Cosmetic Ingredients: Review of Actual Regulatory Status

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.

Development of cream bases suitable for personalized cosmetic products

Background and aims

The individualization of cosmetic products or personalized dermatology preparations are in great demand at the present time.

Methods

24 emulsifying cream bases were proposed which were prepared by the classical, automatic and semi-automatic methods, respectively, and the physical stability resulted from the three types of homogenization was taken into account. Texture parameters were also studied for the most stable cream bases in the preformulation stage and the t - statistical test was applied. In order to choose the most optimal preservative, the effectiveness of the NipaEster solution 0.1%, Cosgard and Euxyl® PE 9010 was tested on the strains of Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans.

Results

9 cream bases were stable through all the preparation methods used, and preservation was achieved with Euxyl® PE 9010. Following the texture parameters, significant differences were observed for the same formula in the case of choosing a different preparation method.

Conclusions

Formulas F1, with methyl glucose sesquistearate as emulsifier, F8, with cetearyl glucosite as emulsifier, and F14, with Ceteareth-20 can be used as cream bases for customized products.

Evaluation of the Safety of Cosmetic Ingredients and Their Skin Compatibility through In Silico and In Vivo Assessments of a Newly Developed Eye Serum

The term "risk assessment" is often substituted with "safety assessment", to demonstrate the safe properties of cosmetic ingredients and formulations. With respect to the actual legislative framework, the proper use of in silico evaluation could offer a representative non-animal substitute for the toxicity evaluation of cosmetic ingredients. The in silico assessment needs to be integrated with other lines of proof (in vitro and/or in vivo data) in the form of a complex methodology in order to demonstrate the safety evaluation of cosmetic ingredients/products. The present study aimed to develop and characterize a new cosmetic formulation, designed for the skin care of the periorbital area. Quality control comprising stability, physicochemical, and microbiological evaluation was performed. Another objective of this study was to present a screening model for the safety evaluation of the cosmetic formulation by identifying individual ingredients, and to confirm the skin compatibility based on in vivo evaluation. The results demonstrated the in silico and in vivo safety profile of the cosmetic ingredients used in the present formulation. In silico evaluation, using a novel, specific software applicable for the risk evaluation of ingredients and formulations, showed that the incorporated ingredients were non-mutagenic and non-sensitizing, and considering the margin of safety (MoS), the cosmetic raw materials could be considered safe. Skin compatibility was confirmed by the patch test performed under dermatological control, evidencing the "non-irritating" potential of the developed cosmetic formulation.

The use of essential oils in atopic dermatitis: a review

Atopic dermatitis (AD) has become a common childhood disease that affects a large number of children worldwide and has become a chronic skin disease that causes huge economical and psychological damage to the whole family. Despite the use of steroids, immunosuppressants, and various topical preparation, the prognosis is still poor. Hence, this review aimed to explore the potential of using essential oils (EO) as an active ingredient in managing AD. The review was completed by using Pubmed, Scopus, and Medline to search for relevant articles that study the pathophysiology of AD, the properties of EO, the use of EO in managing AD, and the suitable advanced formulation to incorporate EO. From the review conducted, it was concluded that EO have huge potential in managing AD and can be used as complimentary therapeutic agents in AD treatment. Scientists and industries should venture into commercializing more topical products with EO to help manage AD more effectively.

Integration of the Natural Language Processing of Structural Information Simplified Molecular-Input Line-Entry System Can Improve the In Vitro Prediction of Human Skin Sensitizers

Natural language processing (NLP) technology has recently used to predict substance properties based on their Simplified Molecular-Input Line-Entry System (SMILES). We aimed to develop a model predicting human skin sensitizers by integrating text features derived from SMILES with in vitro test outcomes. The dataset on SMILES, physicochemical properties, in vitro tests (DPRA, KeratinoSensTM, h-CLAT, and SENS-IS assays), and human potency categories for 122 substances sourced from the Cosmetics Europe database. The ChemBERTa model was employed to analyze the SMILES of substances. The last hidden layer embedding of ChemBERTa was tested with other features. Given the modest dataset size, we trained five XGBoost models using subsets of the training data, and subsequently employed bagging to create the final model. Notably, the features computed from SMILES played a pivotal role in the model for distinguishing sensitizers and non-sensitizers. The final model demonstrated a classification accuracy of 80% and an AUC-ROC of 0.82, effectively discriminating sensitizers from non-sensitizers. Furthermore, the model exhibited an accuracy of 82% and an AUC-ROC of 0.82 in classifying strong and weak sensitizers. In summary, we demonstrated that the integration of NLP of SMILES with in vitro test results can enhance the prediction of health hazard associated with chemicals.