on September 27th, 2013 No Comments
My colleague Bruce Goldman has written elegantly here before about how large biological databases (a phenomenon commonly known as “big data”) are a treasure trove of information – for those who know where to look for it. Bruce has referred to the computerized technique, which pairs existing drugs with human diseases (sometimes vastly different from the conditions for which the drugs were originally developed) as a molecular Match.com. And although the hook-ups are sometimes apples-and-oranges odd, they’re showing lots of promise.
Last night, Stanford researchers Atul Butte, MD, PhD, and Julien Sage, PhD, published a study in Cancer Discovery (subscription required) describing how they’ve used this algorithm developed in the Butte lab to identify a possible new treatment for small cell lung cancer, which is particularly deadly. And because the drug, an antidepressant called imipramine, is already approved by the Food and Drug Administration for use in humans, they’ve been able to quickly and (relatively) inexpensively move into human trials.
We are cutting down the decade or more and the $1 billion it can typically take to translate a laboratory finding into a successful drug treatment to about one to two years and spending about $100,000.
How exactly does it work? More from our release:
The pipeline works by scanning the hundreds of thousands of gene-expression profiles (gathered by multiple researchers and stored in large databases) across many different cell types and tissues — some normal and some diseased, some treated with medications and some not. Alone, these profiles may not mean much to any one investigator or group, but when viewed together, researchers can pick out previously unsuspected patterns and trends.
For example, if a particular molecular pathway is routinely activated (as indicated by an increase in the expression levels of the genes involved) in a cancer cell, and a drug is shown to block or suppress that same pathway (by decreasing the expression of genes in the pathway), it’s possible the drug could be used to treat that type of cancer — regardless of the disease for which it was originally approved.