Prediction of the skin permeability of topical drugs using in silico and in vitro models
Related Experiment Video
Updated: Jan 23, 2026

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Cristina Alonso1, Víctor Carrer1, Sonia Espinosa2
1Institute of Advanced Chemistry of Catalonia -Spanish National Research Council (IQAC-CSIC) 18-26 Jordi Girona st 08034 Barcelona, Spain.
Abstract:
The main challenge of topically applied drugs is to overcome the skin barrier to reach the site of action at the concentration needed for efficacy. In the research of new topical drugs, design of molecules with optimized properties for skin penetration is a key factor and assays for its characterization are needed. A group of 20 representative topical molecules of clinical use were studied in two in silico models (Potts & Guy and Barratt), and an in vitro assay with artificial membrane (Skin-PAMPA). A subset of 9 drugs were also evaluated in the Franz cells assay, formulated in a solvent and in a marketed formulation. Each assay allowed us to grade compounds according to their permeability value. Globally good alignments were found for the studied compounds when comparing models, although discrepancies for some compounds such as tazarotene, tacrolimus, ketoconazole and metronidazole were observed. Overall, the studied in silico and the in vitro models are useful tools to support selection and characterization of research compounds in terms of skin permeability.
Related Concept Videos
Factors Affecting Drug Distribution: Tissue Permeability
Small molecules with a molecular weight below 500 to 600 Daltons can easily pass through the capillary membrane, gaining access to different tissues. Larger...
Bioavailability Enhancement: Drug Permeability Enhancement
Factors Affecting Dissolution: Drug Permeability, Stability and Stereochemistry
In Vitro Drug Dissolution: Compendial Testing Models I
In Vitro Drug Dissolution: Compendial Testing Models II
Predicting Molecular Geometry

