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An evaluation of the potential of linear and nonlinear skin permeation models for the prediction of experimentally measured percutaneous drug absorption
(2012-04)
Objectives: The developments in combinatorial chemistry have led to a rapid increase in drug design and discovery and, ultimately, the production of many potential molecules that require evaluation. Hence, there has been ...
The application and limitations of mathematical modelling in the prediction of permeability across mammalian skin and polydimethylsiloxane membranes
(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 stochastic machine learning methods in the prediction of skin penetration
(2011-03)
Improving predictions of skin permeability is a significant problem for which mathematical solutions have been sought for around twenty years. However, the current approaches are limited by the nature of the models chosen ...
Predicting drug absorption rates through human skin
(Institute of Electrical and Electronics Engineers (IEEE), 2010)
Predicting the rate at which a substance will pass through human skin and into the bloodstream is a problem of current interest. We use Gaussian Process modeling to train a set of predictors using every combination of six ...
The application of feature selection to the development of Gaussian process models for percutaneous absorption.
(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 ...