“A major cost driver for our health care system is the price of drugs, and the biggest driver of those costs is the expense of clinical trials,” says Atul Butte, M.D., Ph.D., who led the research teams at Stanford. Based on their findings, Dr. Butte explains that applying big-data tools to publicly available records is already cutting down the time and money needed to translate a laboratory finding into a successful drug treatment from “a decade or more and $1 billion, to roughly one to two years and about $100,000.” However, researchers need access to more data to continue this success.
Scientists there have identified potential new uses for these old drugs by scanning thousands of gene profiles stored in publicly available databases.Pooling and analyzing vast amounts of information can reveal previously unseen patterns and trends that aren’t apparent in smaller studies. By systematically using a number-crunching algorithm that grouped illnesses by how they changed gene activity, and then matching them with medications that blocked these pathways, researchers came up with these seemingly quirky pairings of diseases and drugs — which they are now testing on humans.
Read more about this in an article in The Atlantic which can be found at http://www.theatlantic.com/sponsored/cvs-innovation-care/2013/12/health-cares-big-data-mandate/78/
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