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Related Experiment Video

Updated: Apr 23, 2026

Visualizing and Quantifying Pharmaceutical Compounds within Skin using Coherent Raman Scattering Imaging

Visualizing and Quantifying Pharmaceutical Compounds within Skin using Coherent Raman Scattering Imaging

Published on: November 24, 2021

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

Farah Asgarkhanova¹, Shamkhal Baybekov¹, Gilles Marcou¹

¹Laboratory of Chemoinformatics, UMR 7140 University of Strasbourg, Strasbourg, France.

Molecular Informatics

|April 22, 2026

Summary

This summary is machine-generated.

This study developed a computational model to predict skin permeability (K_p) using QSPR. This approach offers a faster, cost-effective alternative to experimental methods for pharmaceuticals and cosmetics.

Keywords:

HuskinDB SkinPiX in silico modeling quantitative structure‐property relationship modeling skin permeability

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Last Updated: Apr 23, 2026

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Area of Science:

Pharmacokinetics and Drug Delivery
Computational Chemistry and Cheminformatics
Toxicology and Occupational Safety

Background:

Skin permeability is crucial for product development and safety assessments.
Experimental measurement of skin permeability coefficients (K_p) is laborious and costly.
Computational prediction models are needed to streamline research and development.

Purpose of the Study:

To develop and validate a quantitative structure-property relationship (QSPR) model for predicting skin permeability.
To utilize the SkinPiX dataset and HuskinDB database for model development.
To provide a freely accessible tool for researchers and industry professionals.

Main Methods:

Development of a QSPR model using curated compound data from SkinPiX and HuskinDB.
Inclusion of 209 compounds with experimentally determined K_p values and metadata.
Validation of the model against three new experimental data points.

Main Results:

A robust QSPR model was successfully developed for predicting skin permeability coefficients.
The model demonstrates reliable performance on new experimental data.
The developed datasets and predictive models are made publicly available.

Conclusions:

The QSPR model offers an efficient and cost-effective method for estimating skin permeability.
This tool can significantly aid in the development of safer pharmaceuticals, cosmetics, and in occupational safety evaluations.
The free availability of datasets and models promotes wider adoption and accelerates innovation.