We’re all familiar with the litany of disclaimers and warnings that accompany pharmaceutical ads: the hurried voice-over of possible side effects that inevitably follows a scene of a smiling woman breathing deeply in an allergen-filled meadow or a couple running hand in hand on a tropical beach toward a distant romantic hideaway. Often the list seems almost comically long and dire.

But what do you do if you’re on the medication and experiencing a symptom that is inexplicably not included in the droning monologue? How do you know if it’s a true side effect? According to our release on the topic today:

Unfortunately, there’s no easy answer. Clinical trials are designed to show that a drug is safe and effective. But even the largest trials can’t identify irksome or even dangerous side effects experienced by only a tiny proportion of those people taking the drug. They also aren’t designed to study how drugs interact with one another in the human body – a consideration that becomes increasingly important as people age and their medicine cabinets begin to overflow.

Now Stanford bioengineer and geneticist Russ Altman, MD, PhD, and graduate student Nicholas Tatonetti have devised a way to sift through the mountains of data collected by the Food and Drug Administration after a drug is approved to identify never-before-suspected side-effects and drug interactions. The research is published today in Science Translational Medicine:

Although the FDA has its Adverse Event Reporting System for doctors, patients and drug manufacturers to use after the agency has approved a drug, many of the more than 4 million reports in the database are little more than anecdotal – there’s no way to tell whether the fever, rash, dizziness, seizure or other unwanted reaction was a true side effect of the drug, a result of a combination of medications or even a simple fluke of circumstance (maybe the patient had a cold or other undiagnosed medical condition at the time of the event).

Tatonetti found that he could identify true side effects and adverse drug interactions by carefully matching groups of patients in the FDA database. Patients on similar medications are likely to share medical and environmental traits that make them good controls for one another. The researchers have created two publicly available databases of their work, named OFFSIDES and TWOSIDES, respectively:

So far the OFFSIDES database includes an average of 329 new adverse events for each of the 1,332 drugs included in the system. (The average number of adverse events listed on a drug’s package insert is 69.) The TWOSIDES database identifies 1,301 adverse events, resulting from an analysis of 59,220 pairs of drugs that cannot be clearly assigned to either drug alone.

“This is a testament to the value of huge data sets,” said Altman. “They allow us to throw out a lot of cases. When you start with millions of pieces of information, you can be pretty rigorous about weeding out those that don’t match. And if you can arrive at even just a few hundred well-matched cases, that can give a good statistical comparison.”

One interesting (and alarming) bit of information to come out of the study is that patients taking both a class of antidepressant called an SSRI and a common class of high blood pressure drug called thiazides are significantly more likely to experience a worrisome cardiac side effect called prolonged QT intervals than those taking either drug alone.

Previously: Unexpected drug interactions identified by Stanford data mining
Photo by trekkyandy