@inproceedings{591c26ac985e4c6a9e6f6695a94e652f,
title = "The application of Gaussian processes in the predictions of permeability across mammalian membranes",
abstract = "The problem of 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. The aim of the current study was to explore whether including another species skin data in a training set can improve predictions of the human skin permeability coefficient. Permeability data for absorption across rodent skin was collected from the literature. The Gaussian process model was applied to the data, and this was compared to two QSPR methods. The results demonstrate that data from non-human skin can provide useful information in the prediction of the permeability of human skin.",
author = "Yi Sun and Brown, {Marc B.} and Maria Prapopoulou and Rod Adams and Neil Davey and Moss, {Gary P.}",
year = "2012",
doi = "10.1007/978-3-642-33266-1_63",
language = "English",
isbn = "9783642332654",
volume = "7553 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 2",
pages = "507--514",
booktitle = "Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings",
edition = "PART 2",
note = "22nd International Conference on Artificial Neural Networks, ICANN 2012 ; Conference date: 11-09-2012 Through 14-09-2012",
}