Title :
Neural System for in silico Drug-Drug Interaction Screening
Author :
Polak, Sebastian ; Brandys, Jerzy ; Mendyk, Aleksander
Author_Institution :
Dept. of Pharmacoepidemiology & Pharmacoeconomics, Jagiellonian Univ., Cracow
Abstract :
Drug usage is always associated with risk drugs interactions are considered to be one of the potential sources of undesirable action of drugs. Such a situation enforced U.S. Food and Drug Administration (FDA) as well as European Medicines Agency (EMEA) to issue a guidance for industry and researchers for in vivo and in vitro drug interactions studies. The authors proposed neural networks based in silico system for potential drug-drug interactions screening with use of simple physico-chemical data describing each chemical substance particle. Initial results where 77% of classification rate in generalization test was found suggest that computational intelligence based systems could be effective in this area
Keywords :
drugs; learning (artificial intelligence); neural chips; pharmaceutical industry; EMEA; European Medicines Agency; FDA; U.S. Food and Drug Administration; computational intelligence based system; drug usage; neural network; physico-chemical data; silico drug-drug interaction screening; Artificial neural networks; Biological system modeling; Computational intelligence; Drugs; Educational institutions; Food industry; In vitro; In vivo; Neurons; Pharmaceutical technology;
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7695-2504-0
DOI :
10.1109/CIMCA.2005.1631448