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A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates
Published on: February 23, 2018
Modelling the effect of mixture components on permeation through skin
T Ghafourian1, E G Samaras, J D Brooks
1Medway School of Pharmacy, Universities of Kent and Greenwich, Chatham, Kent ME4 4TB, UK. t.ghafourian@kent.ac.uk
International Journal of Pharmaceutics
|July 21, 2010
Summary
This study developed a quantitative structure-activity relationship (QSAR) model to predict skin penetration. The model uses molecular properties and solvent characteristics to estimate chemical transport through skin, improving formulation design.
Area of Science:
- Dermal pharmacokinetics
- Computational chemistry
- Formulation science
Background:
- Estimating skin penetration of chemicals from formulations is challenging.
- Understanding vehicle effects on penetrant diffusivity and transport is crucial.
- Quantitative structure-activity relationship (QSAR) models can predict skin permeation.
Purpose of the Study:
- To develop a QSAR model for predicting skin permeation.
- To correlate skin permeability with chemical and solvent properties.
- To identify key descriptors influencing skin transport.
Main Methods:
- Utilized a dataset of 12 penetrants in 24 solvent mixtures.
- Employed finite-dose diffusion cell studies with porcine skin.
- Performed stepwise regression analysis to build the QSAR model.
Main Results:
- Developed a QSAR model using logP, molecular connectivity index, and boiling-melting point difference.
- Observed a negative correlation between skin permeability and logP for lipophilic compounds.
- Found that vehicles with small boiling-melting point gaps enhance skin permeation.
Conclusions:
- The developed QSAR model effectively predicts skin permeation.
- Vehicle properties, specifically boiling-melting point difference, significantly impact skin transport.
- Identified gaps in chemical space for future skin permeability studies.
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