Beauty Giants Jointly Uncover Skin Absorption of Some 50 Compounds


Toxicology in Vitro will publish a study in December 2020 elucidating the partition and diffusion coefficients of some 50 compounds in intact skin and isolated skin layers and lipids.

According to the article, available online, the 7th Amendment to the Cosmetic Directive and REACH have mandated that in vitro methods be developed to assess the risk of chemicals for their potential toxicity. As such, Cosmetics Europe's Absorption, Distribution, Metabolism and Elimination (ADME) Task Force is leading projects to help predict the local and systemic bioavailability of topically exposed compounds.

The present work, co-authored by researchers from The Procter & Gamble Company (Cincinnati), Procter and Gamble (Darmstadt), Pierre Fabre Dermo-Cosmétique, Beiersdorf AG and L'Oréal Research & Innovation, determined the partition and diffusion coefficients of 50 compounds in intact and isolated human skin layers. The compounds were selected for their relevance to cosmetics and included positive and negative reference chemicals.

A standard protocol was used to determine partition (K) and diffusion (D) coefficients. K values were measured in dermatomed skin, isolated dermis, whole epidermis, intact stratum corneum (SC), delipidized SC and SC lipids by measurements of radioactivity in the tissue layers/lipid component vs. buffer samples. D determinations were made in dermatomed skin, isolated dermis, whole epidermis and intact SC based on the cumulation of radiolabeleld compounds in receptor fluid and Fick's second law.

Detailed results for all 50 compounds, including triclosan, benzophenone, propylparaben, methylparaben, hydroquinone, benzoic acid, etc., are provided in the article. This is reportedly one of the largest in vitro skin penetration datasets yet; no other studies have generated such a comprehensive database of K and D values for intact and isolated skin layers from standardized assays for such a large number of chemicals. The authors note this data should improve the understanding of skin penetration of chemicals with varying physicochemical properties, as well as improve the prediction capacity of in silico skin penetration models.

See related: Pathways for Skin Penetration

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