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  • Title: Support vector regression to estimate the permeability enhancement of potential transdermal enhancers.
    Author: Shah A, Sun Y, Adams RG, Davey N, Wilkinson SC, Moss GP.
    Journal: J Pharm Pharmacol; 2016 Feb; 68(2):170-84. PubMed ID: 26751826.
    Abstract:
    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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