dc.contributor.author | Shah, Alpa | |
dc.contributor.author | Sun, Yi | |
dc.contributor.author | Adams, Roderick | |
dc.contributor.author | Davey, Neil | |
dc.contributor.author | Wilkinson, Simon Charles | |
dc.contributor.author | Moss, Gary Patrick Joseph | |
dc.date.accessioned | 2017-09-04T17:03:24Z | |
dc.date.available | 2017-09-04T17:03:24Z | |
dc.date.issued | 2016-02-16 | |
dc.identifier.citation | Shah , A , Sun , Y , Adams , R , Davey , N , Wilkinson , S C & Moss , G P J 2016 , ' Support vector regression to estimate the permeability enhancement of potential transdermal enhancers ' , Journal of Pharmacy and Pharmacology , vol. 68 , no. 2 , pp. 170-184 . https://doi.org/10.1111/jphp.12508 | |
dc.identifier.issn | 0022-3573 | |
dc.identifier.uri | http://hdl.handle.net/2299/19318 | |
dc.description | This is the peer reviewed version of the following article: Shah, A., Sun, Y., Adams, R. G., Davey, N., Wilkinson, S. C. and Moss, G. P. (2016), Support vector regression to estimate the permeability enhancement of potential transdermal enhancers', Journal of Pharmacy and Pharmacology, Vol. 68 (2): 170–184, which has been published in final form at doi:10.1111/jphp.12508. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. © 2016 Royal Pharmaceutical Society. | |
dc.description.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. | en |
dc.format.extent | 15 | |
dc.format.extent | 1501438 | |
dc.language.iso | eng | |
dc.relation.ispartof | Journal of Pharmacy and Pharmacology | |
dc.subject | Gaussian processes | |
dc.subject | hydrocortisone | |
dc.subject | support vector machine | |
dc.subject | support vector regression | |
dc.subject | transdermal enhancer | |
dc.title | Support vector regression to estimate the permeability enhancement of potential transdermal enhancers | en |
dc.contributor.institution | School of Computer Science | |
dc.contributor.institution | Centre for Computer Science and Informatics Research | |
dc.contributor.institution | Biocomputation Research Group | |
dc.description.status | Peer reviewed | |
dc.date.embargoedUntil | 2017-01-11 | |
rioxxterms.versionofrecord | 10.1111/jphp.12508 | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |