Algorithm Finds Thousands of Unknown Drug Interaction Side Effects

ananyo writes "An algorithm designed by U.S. scientists to trawl through a plethora of drug interactions has yielded thousands of previously unknown side effects caused by taking drugs in combination (abstract). The work provides a way to sort through the hundreds of thousands of 'adverse events' reported to the U.S. Food and Drug Administration each year. The researchers developed an algorithm that would match data from each drug-exposed patient to a nonexposed control patient with the same condition. The approach automatically corrected for several known sources of bias, including those linked to gender, age and disease. The team then used this method to compile a database of 1,332 drugs and possible side effects that were not listed on the labels for those drugs. The algorithm came up with an average of 329 previously unknown adverse events for each drug — far surpassing the average of 69 side effects listed on most drug labels."

Comments

Re:not surprising

[whydavid]

Not to plug my profession or anything, but this is exactly why the entire field of biomedical informatics exists. If you think this is bad, consider the fact that there are currently over 20 million abstracts in PubMed....do you think even 10% of that has actually been properly synthesized into operational knowledge and applied to patient care? And we won't even go into genomic data, or even the amount of records that one patient might accumulate in their EMR over the span of a lifetime, or the fact that a 320 slice CT generates so many layers of images that they can't all be carefully reviewed (and an abnormality may be so small it only appears in a couple of them), or the overwhelming breadth and depth of surveillance data collected from ERs/pharmacies/drugstores/monitoring stations/schools/etc... by public health practitioners. There is a critical challenge in biomedicine to distill useful knowledge from all of this data...and it's akin to drinking from a firehose. No one is going to read the 329 warnings for the drug, but in an ideal world we'll be able to identify genetic indicators that make you more or less susceptible to certain side effects (pharmacogenomics) and present this information to you/your doctor (and no one has to read the booklet that comes with the prescription).