Sivanesan Dakshanamurthy and colleagues explain that drug companies must limit efforts to market new drugs because the current approach is so expensive, time-consuming and prone to failure. Scientists long have known that drugs already approved for one disease might be effective for others.
However, existing methods to identify new uses for old drugs lack accuracy and have other disadvantages. So Dakshanamurthy's team developed a comprehensive new computer method called "Train-Match-Fit-Streamline" (TMFS) that uses 11 factors to quickly pair likely drugs and diseases.
They describe using TMFS to discover evidence that Celebrex, the popular prescription medicine for pain and inflammation, has a chemical signature and architecture suggesting that it may work against a difficult-to-treat form of cancer. Likewise, they found that a medicine for hookworm might be repurposed to cut off the blood supply that enables many forms of cancer to grow and spread. "We anticipate that expanding our TMFS method to the more than 27,000 clinically active agents available worldwide across all targets will be most useful in the repositioning of existing drugs for new therapeutic targets," they said.
The authors acknowledge funding from the National Institutes of Health and the Department of Defense.
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Michael Bernstein | EurekAlert!
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