Millions of Americans take more than one prescription drug, and often times doctors don't know which drugs, when combined, can cause serious illness or death. Sadly, such warnings come only after the damage is done, when enough clear reports of adverse reactions begin to emerge.
Now, scientists at Columbia University in New York have harnessed the power of data science to identify two common prescription drugs that, if mixed, can have deadly consequences.
The drugs — an antibiotic called ceftriaxone, sold under the brand name Rocephin, and the heartburn medication lansoprazole, sold as Prevacid — each carry no known heart risk when used alone, but together they may increase the risk of an irregular heart rhythm and even death. [10 Amazing Facts About Your Heart]
The scientists said they hope that their data-science approach could be used to identify many other similarly harmful drug interactions long before anyone gets hurt. They describe their method today (Oct. 10) in a paper in the Journal of the American College of Cardiology.
The percentage of Americans taking prescription medicines has risen steadily for decades. A study published last year in the Journal of the American Medical Association reported that nearly 60 percent of Americans are taking prescription drugs, and upward of 20 percent are taking two or more drugs at the same time. This adds up to billions of prescriptions being filled each year, according to data from the National Association of Chain Drug Stores.
Many of these drugs have known side effects, and may cause thousands of deaths each year, according to the U.S. Food and Drug Administration, which collects reports about adverse drug reactions from both doctors and the public. The precise number of deaths is not known and may be underreported, the FDA states on its website.
Far less is known about what happens when prescription drugs mix. One known potentially lethal mix is the antibiotic Bactrim and with the blood-thinner warfarin, which together can cause internal bleeding. Other prescription drugs can be harmful when mixed with natural or dietary supplements, such as heart medications with St. John's wort. [7 Bizarre Drug Side Effects]
Yet with so many prescription drugs on the market, it can be hard for doctors to know which drugs don't work together well. And sometimes, reports of adverse effects to the FDA cannot be verified. So, researchers at Columbia University decided to approach the problem from the back end, to start with a common and potentially deadly symptom from drug interactions and then see which drugs, when mixed, could trigger it.
The researchers, led by Nicholas Tatonetti, assistant professor of biomedical informatics at Columbia University Medical Center, searched through nearly 2 million reports of adverse drug reactions in an FDA database, looking for reports of long QT syndrome, an episode of abnormal heart rhythms that can cause long-term heart damage or death. They combined this with an additional 1.6 million electrocardiogram (ECG) results from 380,000 patients in a Columbia University database.
Using a computer algorithm to fish through this ocean of data, the team found eight drug pairs associated with long QT syndrome. Among these, the ceftriaxone–lansoprazole combination stood out. Patients taking ceftriaxone and lansoprazole together were 1.4 times more likely to have long QT syndrome as revealed on the ECG than people who were taking either of these drugs alone.
The researchers then tested the ceftriaxone–lansoprazole combination in the lab in samples of human cells. They found that the combination blocked the proteins that control the heart's electrical activity and rhythm, called the hERG channel.
"What's most surprising is that you can go from a database of billions of data points to making a prediction that two molecules together can change the functions of a protein in a single heart cell," Tatonetti said.
Although the method narrows in on only one kind of deadly side effect, long QT syndrome, the researchers hope to expand the method to make predictions of other types of adverse reactions before a new drug hits the market.
"One of the key motivations for this work is that it's prohibitively expensive and time-consuming to prospectively evaluate every possible combination of drugs," said Tal Lorberbaum, a graduate student at Columbia and lead author on the paper. "We are very interested in and actively developing methods to computationally predict drug-drug interactions using only pre-clinically available data," he told Live Science.
Such future work also could include preventing internal hemorrhaging, another common problem arising from certain drug interactions, Tatonetti said.
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