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Paper Abstract and Keywords
Presentation 2008-06-26 14:30
Prediction of Drug Clearance Pathway with Machine Learning
Kouta Toshimoto (Tokyo Inst. of Tech.), Makiko Kusama, Kazuya Maeda, Yuichi Sugiyama (Univ. of Tokyo), Yutaka Akiyama (Tokyo Inst. of Tech.) NLP2008-4 NC2008-14
Abstract (in Japanese) (See Japanese page) 
(in English) The clearance pathway is one of the important factors to consider the pharmacokinetics of drugs.
We have developed a machine learning system of drug clearance pathway for a given drug compound from its physicochemical descriptors.
The system is composed of five support vector machines (SVMs), each corresponding to one of five major candidate clearance pathways,
and prediction is given by choosing a pathway with largest SVM output. We prepared pathway data for 157 drugs,
and 1089 physicochemical descriptors for each of them. However, if we use all the descriptors,
we will have over-learning problem and less explainable model.
Thus we performed exhaustive feature selection procedure, by a modified greedy algorithm or a correlation coefficient-based method, and our system showed more than 85\%
prediction accuracy when using 12 selected descriptors.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine learning / Pharmacokinetics / Support vector machine(SVM) / Feature selection / / / /  
Reference Info. IEICE Tech. Rep., vol. 108, no. 101, NC2008-14, pp. 19-24, June 2008.
Paper # NC2008-14 
Date of Issue 2008-06-19 (NLP, NC) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NLP2008-4 NC2008-14

Conference Information
Committee NC NLP  
Conference Date 2008-06-26 - 2008-06-27 
Place (in Japanese) (See Japanese page) 
Place (in English) University of the Ryukyus 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Machine Learning Approach to Biodata Mining and Nonlinearity in Biological Phenomena, and General 
Paper Information
Registration To NC 
Conference Code 2008-06-NC-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Prediction of Drug Clearance Pathway with Machine Learning 
Sub Title (in English)  
Keyword(1) Machine learning  
Keyword(2) Pharmacokinetics  
Keyword(3) Support vector machine(SVM)  
Keyword(4) Feature selection  
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1st Author's Name Kouta Toshimoto  
1st Author's Affiliation Tokyo Institute of Technology (Tokyo Inst. of Tech.)
2nd Author's Name Makiko Kusama  
2nd Author's Affiliation The University of Tokyo (Univ. of Tokyo)
3rd Author's Name Kazuya Maeda  
3rd Author's Affiliation The University of Tokyo (Univ. of Tokyo)
4th Author's Name Yuichi Sugiyama  
4th Author's Affiliation The University of Tokyo (Univ. of Tokyo)
5th Author's Name Yutaka Akiyama  
5th Author's Affiliation Tokyo Institute of Technology (Tokyo Inst. of Tech.)
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Speaker Author-1 
Date Time 2008-06-26 14:30:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NLP2008-4, NC2008-14 
Volume (vol) vol.108 
Number (no) no.102(NLP), no.101(NC) 
Page pp.19-24 
#Pages 6 
Date of Issue 2008-06-19 (NLP, NC) 

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