[Prediction of human skin permeability of drugs in vivo with artificial neural network].
To predict in vivo human skin permeability of drugs.



Appropriate 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.



The calculated logR values of 17 drugs were in good accordance with their observed values.



BP neural network can be used to predict in vivo human skin permeability of drugs.
Fu
Xu-chuen
XC
Department of Pharmacy, Zhejiang University City College, Hangzhou 310015, China.
D006801:Humans; D006860:Hydrogen Bonding; D016571:Neural Networks, Computer; D010539:Permeability; D012869:Skin Absorption; D012995:Solubility