AIMC Topic: Skin Absorption

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The influence of diffusion cell type and experimental temperature on machine learning models of skin permeability.

The Journal of pharmacy and pharmacology
OBJECTIVES: The aim of this study was to use Gaussian process regression (GPR) methods to quantify the effect of experimental temperature (T ) and choice of diffusion cell on model quality and performance.

Support vector regression to estimate the permeability enhancement of potential transdermal enhancers.

The Journal of pharmacy and pharmacology
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 hydro...

Artificial neural network analysis for predicting human percutaneous absorption taking account of vehicle properties.

The Journal of toxicological sciences
An in silico method for predicting percutaneous absorption of cosmetic ingredients was developed by using artificial neural network (ANN) analysis to predict the human skin permeability coefficient (log Kp), taking account of the physicochemical prop...

The application of machine learning to the modelling of percutaneous absorption: an overview and guide.

SAR and QSAR in environmental research
Machine learning (ML) methods have been applied to the analysis of a range of biological systems. This paper reviews the application of these methods to the problem domain of skin permeability and addresses critically some of the key issues. Specific...