Login / Signup

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

Anca Maria JuncanLuca-Liviu RusClaudiu MorgovanFelicia Loghin
Published in: Toxics (2024)
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.
Keyphrases
  • molecular docking
  • risk assessment
  • drug delivery
  • healthcare
  • soft tissue
  • quality control
  • oxidative stress
  • palliative care
  • chronic pain
  • artificial intelligence
  • data analysis
  • deep learning
  • big data
  • gestational age