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pubmed-article:20375448pubmed:abstractTextDrug development is expensive and prone to failure. It is potentially much less risky and expensive to reuse a drug developed for one condition for treating a second disease, than it is to develop an entirely new compound. Systematic approaches to drug repositioning are needed to increase throughput and find candidates more reliably. Here we address this need with an integrated systems biology dataset, developed using the Ondex data integration platform, for the in silico discovery of new drug repositioning candidates. We demonstrate that the information in this dataset allows known repositioning examples to be discovered. We also propose a means of automating the search for new treatment indications of existing compounds.lld:pubmed
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pubmed-article:20375448pubmed:year2010lld:pubmed
pubmed-article:20375448pubmed:articleTitleAn integrated dataset for in silico drug discovery.lld:pubmed
pubmed-article:20375448pubmed:affiliationBioinformatics Support Unit, Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle-upon-Tyne NE1 7RH, UKlld:pubmed
pubmed-article:20375448pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:20375448pubmed:publicationTypeResearch Support, Non-U.S. Gov'tlld:pubmed