A team led by Atul J. Butte at Stanford University, in a National Institutes of Health-funded computational study, analyzed genomic and drug data to predict new uses for medicines that are already on the market.
The scientists drew their data from the Gene Expression Omnibus, a publicly available database containing the results of thousands of genomic studies submitted by researchers across the globe, an NIH release said Wednesday.
The study focused on 100 diseases and 164 drugs and analyzed the thousands of possible drug-disease combinations to find drugs and diseases whose gene expression patterns essentially canceled each other out.
For example, if a disease increased the activity of certain genes, the computer program attempted to match it with one or more drugs that decreased the activity of those same genes.
The study has already found two possible drug-disease combinations.
An anti-ulcer medicine (cimetidine) was found to match with lung cancer, and an anti-convulsant (topiramate) was matched with inflammatory bowel disease, which includes Crohn's disease.
"Bringing a new drug to market typically takes about $1 billion, and many years of research and development," said Rochelle M. Long, director of the NIH Pharmacogenomics Research Network.
"If we can find ways to re-purpose drugs that are already approved, we could improve treatments and save both time and money."
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