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Browsing by Author "Moss, Gary"
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The application and limitations of mathematical modelling in the prediction of permeability across mammalian skin and polydimethylsiloxane membranes
Moss, Gary; Sun, Yi; Wilkinson, Simon C.; Davey, N.; Adams, Roderick; Martin, Gary P.; Prapopopolou, M.; Brown, Marc (2011-11)Objectives: Predicting the rate of percutaneous absorption of a drug is an important issue with the increasing use of the skin as a means of moderating and controlling drug delivery. One key feature of this problem domain ... -
The application of discriminant analysis and Machine Learning methods as tools to identify and classify compounds with potential as transdermal enhancers
Moss, Gary; Shah, A.J.; Adams, R.G.; Davey, N.; Sun, Y.; Wilkinson, S.C.; Pugh, W.J. (2012-01-23)Discriminant analysis (DA) has previously been shown to allow the proposal of simple guidelines for the classification of 73 chemical enhancers of percutaneous absorption. Pugh et al. employed DA to classify such enhancers ... -
The application of feature selection to the development of Gaussian process models for percutaneous absorption.
Lam, L.T.; Sun, Yi; Davey, N.; Adams, Roderick; Prapopoulou, M.; Brown, Marc; Moss, Gary (2010)Objectives: The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical ... -
Development of a Gaussian Process – Feature Selection Model to Characterise (poly)dimethylsiloxane (Silastic®) Membrane Permeation
Sun, Yi; Hewitt, Mark; Wilkinson, Simon C; Davey, Neil; Adams, Roderick; Gullick, Darren; Moss, Gary (2020-07)Objectives The current study aims to determine the effect of physicochemical descriptor selection on models of polydimethylsiloxane permeation. Methods 2,942 descriptors were calculated for a dataset of 77 chemicals. Data ... -
The importance of hyperparameters selection within small datasets
Ashrafi, Parivash; Sun, Yi; Davey, Neil; Adams, Roderick; Brown, Marc; Prapopoulou, Maria; Moss, Gary (Institute of Electrical and Electronics Engineers (IEEE), 2015-10-01)Gaussian Process is a Machine Learning technique that has been applied to the analysis of percutaneous absorption of chemicals through human skin. The normal, automatic method of setting the hyperparameters associated with ... -
The influence of diffusion cell type and experimental temperature on machine learning models of skin permeability
Ashrafi, Parivash; Sun, Yi; Davey, Neil; Wilkinson, Simon Charles; Moss, Gary (2019-11-14)Objectives The aim of this study was to use Gaussian process regression (GPR) methods to quantify the effect of experimental temperature (Texp) and choice of diffusion cell on model quality and performance. Methods Data ... -
Prediction of skin penetration using machine learning methods
Sun, Yi; Moss, Gary; Prapopoulou, M.; Adams, Roderick; Brown, Marc; Davey, N. (Institute of Electrical and Electronics Engineers (IEEE), 2008)Improving predictions of the skin permeability coefficient is a difficult problem. It is also an important issue with the increasing use of skin patches as a means of drug delivery. In this work, we applyK-nearest-neighbour ... -
Transiently supersaturated solutions from the dissolution of amorphous powders for topical drug delivery
Palmer, I. A.; Jones, S. A.; Murnane, D.; Traynor, M.J.; Moss, Gary; Brown, Marc (2010-06)The aim of this study was to prepare amorphous forms of clotrimazole to determine whether increasing the rate and extent of dissolution of clotrimazole would result in supersaturated solutions capable of increasing the ...