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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."
Presumably so doctors can better select functionally similar drugs to minimise these interactions...
For example, TFA says that the high-blood-pressure medication class thiazides and SSRIs can interact. Neither of these is available without prescription therefore a doctor could use such data to make better treatment decisions...
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).
People keep telling me to take headache tablets, cold/flu "remedies", painkillers, etc. etc. etc. and I avoid them like the plague. The people who use them use them CONSTANTLY and still get headaches, flu and pain worse than I ever have. If you have a pack of pills in your bag "just in case" of headache, cold, etc. then you should be made to throw them away - they are purely placebo.
Look, somebody should hit your head with a hammer to make sure you know what you're talking about.
You ignore the fact that we are all different from each other. Headaches are a good example: I practically never get headaches.Other people I'm close to get absolutely terrible headaches from time to time that are so bad that they keep them awake and only the strongest Paracetamol can give some remedy for a short time. You either lack empathy (working in management?) or have really no idea how bad headaches or migraine can be.
A better solution would be to just ban the placement of ads for prescription drugs anywhere other than medical literature.
Sphinx of black quartz, judge my vow.
>> Medical doctors are going to read that, it's their job.
I think you mean "Medical doctors SHOULD read that...", or under the best cases "Medical doctors are going to TRY to read that..."
Realistically? They won't have the time to do it properly. Doctors are massively overworked, trying to see far too many patients and dealing with a field that is too broad and grows way too rapidly to keep up with even if they *didn't* have the inconvenience of actually applying their knowledge. I mean, this study alone claims to have discovered 438,228 new drug interactions and side effects. (329 side effects per drug x 1332 drugs) You try to do a thorough read-through and analysis of that kind of data without taking any time off from work; and work quick, you probably only have a week at most until something new you need to learn comes along....