Drug data reveal sneaky side effects

An algorithm designed by US scientists to trawl through a plethora of drug interactions has yielded thousands of previously unknown side effects caused by taking drugs in combination.

The work, published today in Science Translational Medicine1, provides a way to sort through the hundreds of thousands of 'adverse events' reported to the US Food and Drug Administration (FDA) each year. Its a step in the direction of a complete catalogue of drugdrug interactions, says the study's lead author, Russ Altman, a bioengineer at Stanford University in California.

A program predicts the potential side-effects of mixing different pills.

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Although clinical trials are often designed to assess the safety of a drug in addition to how well it works, the size of the trials needed to detect the full range of drug interactions would surpass even the large, late-stage clinical trials sometimes required for drug approval. Furthermore, clinical trials are often done in controlled settings, using carefully defined criteria to determine which patients are eligible for enrolment including other conditions they might have and which medicines they can take alongside the trial drug.

Once a drug hits the market, however, things can get messy as unknown side-effects pop up. And thats where Altmans algorithm comes in.

Even if you show a drug is safe in a clinical trial, that doesnt mean its going to be safe in the real world, says Paul Watkins, director of the HamnerUniversity of North Carolina Institute for Drug Safety Sciences in Research Triangle Park, North Carolina, who was not involved in the work. This approach is addressing a better way to rapidly assess a drugs safety in the real world once it is approved.

Altman and his colleagues have been studying drugdrug interactions as a way to understand how a persons genes influence their response to pharmaceuticals. To do that, he says, you must first have a good picture of the molecular mechanisms that underlie drug responses.

Adverse events are incredibly valuable clues to what these drugs are doing in the body, Altman says. They can tell you the other pathways in the cell that are being tickled by these drugs.

But reports of adverse drug events are notoriously prone to bias. For example, cholesterol-lowering treatments are more often taken by older patients, and so conditions associated with ageing, such as heart attack, could be wrongly linked to a drug as a side effect.

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Drug data reveal sneaky side effects