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April 24, 2026Molecular Informatics0 citations

Current Insights on Skin Permeability Data and Quantitative Structure‐Property Relationship Modeling

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FAFarah AsgarkhanovaSBShamkhal BaybekovGMGilles Marcou

Key Points

  • Evaluate skin permeability through computational modeling to enhance product safety and efficacy.
  • Developed a QSPR model using the SkinPiX dataset and HuskinDB database.
  • Utilized 209 curated compounds with associated skin permeability coefficients (Kp).
  • Assessed model performance on three new experimental data points.
  • The QSPR model provided accurate predictions of skin permeability.
  • Datasets and models are freely accessible, aiding future research.
  • Supporting safer and more effective product development.

Abstract

Skin permeability is a critical factor in pharmaceuticals, cosmetics, and occupational safety. Experimental determination of skin permeability coefficients (Kp) is time-intensive and resource-intensive, highlighting the importance of computational predictions. This study presents a quantitative structure-property relationship (QSPR) model developed using the recently published SkinPiX dataset and the HuskinDB skin permeability database, comprising 209 curated compounds with associated Kp values and metadata. The model performance was assessed on three new experimental data points. The datasets and models are freely available, providing a valuable tool to enhance decision-making and support the development of safer and more effective products.

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Cite This Study

Asgarkhanova et al. (2026) studied this question.

synapsesocial.com/papers/69eb09c9553a5433e34b41dahttps://doi.org/10.1002/minf.70030
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