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Updated: Mar 27, 2026

Evaluating Vascular Hyperpermeability-inducing Agents in the Skin with the Miles Assay
Published on: June 19, 2018
Support vector regression to estimate the permeability enhancement of potential transdermal enhancers
Alpa Shah1, Yi Sun2, Rod G Adams2
1Department of Software Engineering and IT, Ecole de Technologie Superieure, Montreal, QC, Canada.
Objectives:
Searching for chemicals that will safely enhance transdermal drug delivery is a significant challenge. This study applies support vector regression (SVR) for the first time to estimating the optimal formulation design of transdermal hydrocortisone formulations.
Methods:
The aim of this study was to apply SVR methods with two different kernels in order to estimate the enhancement ratio of chemical enhancers of permeability.
Key Findings:
A statistically significant regression SVR model was developed. It was found that SVR with a nonlinear kernel provided the best estimate of the enhancement ratio for a chemical enhancer.
Conclusions:
Support vector regression is a viable method to develop predictive models of biological processes, demonstrating improvements over other methods. In addition, the results of this study suggest that a global approach to modelling a biological process may not necessarily be the best method and that a 'mixed-methods' approach may be best in optimising predictive models.
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