Prediction of human skin permeability of drugs in vivo with artificial neural network.
- Author:
Xu-chuen FU
1
Author Information
- Publication Type:Journal Article
- MeSH: Humans; Hydrogen Bonding; Neural Networks (Computer); Permeability; Skin Absorption; Solubility
- From: Journal of Zhejiang University. Medical sciences 2003;32(2):152-158
- CountryChina
- Language:Chinese
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Abstract:
OBJECTIVETo predict in vivo human skin permeability of drugs.
METHODSAppropriate BP(Back-propagation) neural network to predict human skin permeation ratios of drugs (R, absorbed/unabsorbed) was established. The octanol water partition coefficients (logP), molecular volumes (V), hydrogen bond acidities (sigma alpha 2(H)) and hydrogen bond basidities (sigma beta 2(H)) were selected as the neural units of input layer, and logR values were selected as the neural units of output layer.
RESULTSThe calculated logR values of 17 drugs were in good accordance with their observed values.
CONCLUSIONBP neural network can be used to predict in vivo human skin permeability of drugs.
