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Medicine Science

Algorithm Finds Thousands of Unknown Drug Interaction Side Effects 121

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."
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Algorithm Finds Thousands of Unknown Drug Interaction Side Effects

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  • by zero.kalvin ( 1231372 ) on Thursday March 15, 2012 @05:46AM (#39362091)
    What kind of statistical analysis methods they use in these studies? For example we use a lot of Likelihood functions, BDT, and neural networks to get the maximum number of information out of our data. Do they use these kind of methods in there analysis ? ps, my field is astrophysics and astroparticles.
    • by whydavid ( 2593831 ) on Thursday March 15, 2012 @06:36AM (#39362257)
      In Biomedicine you tend to see a heavy reliance on T-Tests, Chi-Square variants, Fisher's Exact, regression, McNemar's and Cox Proportional Hazards when temporally rich data is being tested. I don't have access to this article yet, but I would be surprised if they weren't performing a paired T-test in situations where outcome variables were measured on a ratio scale, McNemar's for binary outcomes where temporal data is not provided (maybe rare or nonexistent in this study), and Cox Proportional Hazards if there are any cases where we have a long temporal history of the data. Based on the sheer number of hypotheses tested we would expect to see some sort of correction for multiple testing here, too.
      • From the fine (real article) []

        Our new method (i) accomplishes the goals of stratification, dampening or removing the effect of covariates, without the need to divide drug-exposed reports into strata; (ii) is both adaptive (it removes different covariates for different drugs) and appropriate for systematic application and routine analysis; and (iii) is designed to complement modern signal detection approaches and thus extends the applicability and power of existing methods. Our model is inspired by the case-control approach to cohort selection in observational clinical studies. Each drug-exposed patient is matched to one (or more) nonexposed patients (controls). The nonexposed patients are selected on the basis of how well they match an exposed patient on a set of predefined covariates. Propensity score matching (PSM)—a statistical method designed to yield an unbiased estimate of treatment effects—has emerged as the preferred method of matching exposed and nonexposed patients in observational cohort studies and has yielded similar estimates of effects when compared to the results of randomized control trials (9–11). However, like other confounder controlling methods, PSM requires the covariates to be both known and measured; neither parameter is guaranteed to be present in spontaneous reporting systems. Instead, to match patients, we adapted PSM to use only the co-reported drugs and co-reported indications. We hypothesize that many confounders correlate with these key variables and do not need to be modeled.

        As usual with these sorts of studies, my head asplode.

    • by buchner.johannes ( 1139593 ) on Thursday March 15, 2012 @07:21AM (#39362391) Homepage Journal

      As usual, Science&Nature only provide high-level info, so you'll have to dig deeper than the article ( [] )
      On the authors website, [] there is a paper that describes the machine-learning algorithms used:
      Tatonetti, N.P., Fernald, G.H. & Altman, R.B. A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports. J Am Med Inform Assoc (2011) DOI:10.1136/amiajnl-2011-000214 []

    • This article on pharmacovigilance [] probably has what you're looking for.
  • Does this mean those commercials on TV for prescription drugs will now take up an entire commercial break just reading the side effects? With some of the potential side effects being far worse than the condition that the drug intends to treat, it's going to be pretty intimidating for anyone who might have been interested in trying the newest drugs. It may help if the risk were quantified, but with frivolous lawsuits running rampant these days, the drug company legal team probably can't let them skip over
  • Say! (Score:5, Funny)

    by sixtyeight ( 844265 ) on Thursday March 15, 2012 @06:15AM (#39362181)

    Say! Are there any new prescription drugs out there that I'm not taking, but should be? Those seem pretty safe.

    Perhaps they'll soon come out with glossy color catalogs for the new ones each season. They'll be full of loads of bikini-clad women draped over cars, popping pills.

  • by FhnuZoag ( 875558 ) on Thursday March 15, 2012 @06:23AM (#39362201)

    I am a statistician.

    I've only done a light skim of the paper, but it seems to me that the OP (but not the paper itself) is being way too positive here. Their methodology seems to be very vulnerable to false positives - with a massive database of drugs and potential adverse effects, you'd expect a *lot* of apparent side effects occuring solely by chance. For example:

    "We constructed a database of 438,801 off-label side effects for 1332 drugs and 10,097 adverse events."

    Supposing you are doing a hypothesis test at the standard 0.05 significance level, for each of the 1332*10097 drug-side effect combinations. Then, with naive assumptions, on a null hypothesis, you'd be picking up an average of 666k+ 'side effects' anyway, purely by chance. With the drug interactions case, this multiple testing problem gets even worse.

    Now, there are ways to correct for multiple testing, but for things as large and complicated as this problem, I'm not sure the standard methods are going to cut it. At best, this study should be considered more a *filter* on the set of potential side effects, than really an enumeration of effects that are actually there. This is ignoring other issues like the placebo effect.

    • Re: (Score:3, Informative)

      by whydavid ( 2593831 )
      I don't know why standard methods wouldn't cut it. Testing half a million SNPs and several combinations of those SNPs in a GWAS study is far more convoluted and controlling FDR through permutation is still relatively straightforward (though maybe computationally expensive...thought I doubt that is a huge problem for Stanford researchers). And your numbers are inflated by probably an order of magnitude even if no correction was done. They would not be testing all drug/ADE combinations because the vast maj
      • GWAS done in the traditional hypothesis testing way have a *massive* multiple testing problem, which is only partially solved by imposing *extremely* stringent requirements on significance. That's why things like the Group Lasso and so on are being devised to work on them. It's definitely a non-trivial problem.

        I agree that my calculations are very naive. But in my reading of the paper, I'm not really satisfied that they've done enough to deal with the multiple testing issue. (There is a mention of correctio

    • >> vulnerable to false positives

      I don't know crap about the two tailed t-test, but I do know that if I ask for side effects in my drugs I better damn well get them!

    • Re: (Score:3, Insightful)

      by Veetox ( 931340 )

      "Their methodology seems to be very vulnerable to false positives..."

      I would agree, and go on to suggest that this is intentional. Even after applying "corrective" measures, one has to pick a preference: false negative or false positive, and then show your work (just like in math class). When it comes to drugs, the control methods are never *really* enough. If you're doing an in silico screen, depending on the algorithms used, you may want false positives, because you're just going to throw everything into a high-throughput screen and let the robots do the rest of the work.


    • by Anonymous Coward


      Is your computation of 1332*10097 correct? I think it's wrong.

      Isn't the combinatorial function without repetition ((n+1)!) / (r!(n-r)! )?

      • No, that would be the right calculation for arbitary combinations of a certain length. We're looking for the number of pairs (drug, side effect), of which there are #drugs*#sideeffects total.

  • by Attila Dimedici ( 1036002 ) on Thursday March 15, 2012 @06:26AM (#39362207)
    I definitely see this type of data mining as a useful tool, but to what degree of surety are they that the adverse effects are caused by the drugs in question? What percentage of people taking the drugs in question have to exhibit the effect before they consider it a product of drug interaction? It appears that they consider even one occurrence of the effect that does not appear in someone with the same condition not taking the drug to be an effect of the drug. If that is true, that would reduce the usability of this analysis. However, even with that flaw, this is a very valuable study. My stepfather struggled with a respiratory problem this winter that was caused by one of the medications he was on. His doctor never admitted that the medication was the problem, but it only started to clear up after he was taken off of it and that only happened when my mom insisted. She had found information that said the drug sometimes resulted in the respiratory problem he was experiencing.
    • Good points. I wish I had a moderator point left to give you. While this study's results should be taken with a grain of salt it's an innovative idea of how to better quantify side effects and better information for consumers.
    • by dgatwood ( 11270 )

      What percentage of people taking the drugs in question have to exhibit the effect before they consider it a product of drug interaction?


      Just kidding. There is no single percentage. You need to know what percentage of people with the same disorders would exhibit that particular symptom while taking one or zero of those drugs, and compare the various percentages using a T-test or similar.

      The minimum statistically significant difference in those percentages further depends on the sample size, and w

  • by Shazback ( 1842686 ) on Thursday March 15, 2012 @06:31AM (#39362233)
    They're going to need bigger boxes.
  • Simple (Score:1, Interesting)

    by ledow ( 319597 )

    All drugs have side-effects. In some those side-effects can be serious and even deadly, but it's pretty unpredictable what the side-effects will be and/or their severity in a particular patient, let alone one that takes other drugs. In others, the side-effects will never appear.

    For instance, I'm one of those annoying people who doesn't take drugs unless absolutely necessary - not because I distrust the medical establishment (because I don't) but because if I don't need a drug, I won't take it - and even t

    • Re:Simple (Score:4, Insightful)

      by Anonymous Coward on Thursday March 15, 2012 @06:58AM (#39362319)

      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.

      • by ledow ( 319597 )

        Migraines are a different matter that I covered separately in that same post BECAUSE they are nothing to do with headaches and because they have unique drugs that can combat them quite effectively if taken at the onset.

        Anybody that confuses or merges migraine and headaches is lacking in understanding themselves. My current and previous partners both suffer severe migraine (up to and including visual effects such as not being able to cross a road because they see cars on the road and/or "seeing" people as h

        • by mutube ( 981006 )

          Migraines are a different matter that I covered separately in that same post BECAUSE they are nothing to do with headaches and because they have unique drugs that can combat them quite effectively if taken at the onset.

          I understand what you're getting at - I myself won't take painkillers for mild headaches (drinking water usually does the trick - whether it's dehydration or placebo). However, in my early 20s I suffered from quite bad migraines (blindness aura, skin crawling insect feeling, crushing pain, an

        • by mcmonkey ( 96054 )

          If you have a headache that a headache tablet gets rid of, or helps, you don't have a need for the tablet, it's just convenience.

          WTF does that mean? If a drug helps, then you didn't really need the drug? Yeah, and if you don't feel hungry after eating, then you don't really need food. And if you can see after turning on a light, then it wasn't really dark.

          As for "it's just convenience," are there any recorded cases of terminal migraines or headaches? Anything anyone does to alleviate headache pain is a convenience.

          If you have a headache that *isn't* affected enough by paracetamol, you need to get your doctor to give you something stronger.

          Well doctor, I get headaches that paracetamol has no effect on, but will go away if I take ibuprofen early enough. T

        • Migraines are a different matter that I covered separately in that same post BECAUSE they are nothing to do with headaches and because they have unique drugs that can combat them quite effectively if taken at the onset.

          "Headache" is a vague symptom. Migraine is one of many conditions which produces a (very distinct kind of) headache as a symptom.Yes, it has distinct drugs which are effective at treating the condition or mitigating the symptom.

          Fevers also cause headaches (which are very different than those

      • Have the people you're close to tried the other over-the counters, Aspirin or ibuprofen, etc?

        I've personally found paracetamol to be pretty ineffective in just about any dosage, for pretty much every type of pain I've ever had (however, I've known people who found it effective for their own pain). This sucked growing up when I used to get terrible headaches and my parents were afraid of reye's syndrome and assumed all NSAIDS were aspirin for some reason (tylenol marketing dept, I assume...), so that's all

        • by Anonymous Coward

          Have the people you're close to tried the other over-the counters, Aspirin or ibuprofen, etc? I've personally found paracetamol to be pretty ineffective in just about any dosage

          Paracetamol (aka acetaminophen, aka Tylenol) is a troubling drug. It's therapeutic dose and toxic dose are very close. In some individuals, there's no safe effective does. There are times it's called for, but ibuprofen and aspirin are safer. That said, the anti-over-the-counter drug rant was just crazy. Those things are amazing when use correctly, sadly, most people take the wrong drugs and never read the labels.

          • My personal experience is that they're pretty variable in pain relief. I assume that different causes of pain are more susceptible to different drugs, and sometimes I happen to pick the right one, but I'm not aware of any way to tell which kind of pain I'm having or how it matches with which kind of OTC pain reliever. Is there such a resource for determining it? I don't think the labels are very helpful in this regard.

    • by Fwipp ( 1473271 )

      But, literally ANYTHING I pop into my mouth that I haven't had before could kill me the instant it touches my stomach. You have no way to know.

      You've convinced me. I am switching to a zero-food diet.

  • So there is a short list of drugs a person is taking, medium list of person's medical conditions, and a long list of drug interaction side effects. All a person needs to do is to prioritize that interaction list according to severity: from "will kill you" at the top down to "skin reddening" or "facial swelling" at the bottom, and pick the least damaging drugs. This calls for a smartphone app.
  • by iliketrash ( 624051 ) on Thursday March 15, 2012 @07:00AM (#39362325)

    OMG. I really do hope medicine outgrows its infancy during my lifetime.

    • Doctors and nurses are still resisting checklists! SIMPLE CHECKLISTS!!? a proven method to drastically cut down errors to which there is no decent counter argument but here we are STILL - no checklists.

      You think the human ego will not drastically hold back progress more than the other humans contribute towards progress? I don't.

      Health for profit is not ultimately beneficial; it could be removed and replaced with something better but the culture is so brainwashed we'll continue down in the wrong direction --

  • A nice song from Consumers Union about drug side effects to enrich your day. []

  • by jonpublic ( 676412 ) on Thursday March 15, 2012 @07:52AM (#39362509)

    Ive had some pretty nasty side effects from a drug that weren't on the label. It really sucked. I'm still dealing with them.

    Let me tell you that if you goto a doctor and say that you think that side effects are related to the drug he put you on and those side effects aren't yet on the label they will treat you like you are crazy. It was really eye openning to see how doctors can talk down to patients. The drug I was taking for example can cause tendons to snap. That was known. The doctor flat out didn't believe that incrediblely painful tendinitis could be related to taking the drug.

    It really sucks. I got lucky though because a month later the FDA released a new list of side effects that for this drug that included my ones. Then I got a doctor to pay attention and help me out.

    I knew the side effects were related to the drug thanks to a quick google search that showed thousands of other people had experienced the same things that I had. There were literally 100,000 posts in a forum discussing what I had experienced in the previous weeks.

    I can't even imagine the complexity when combining two drugs and what havoc that could cause.

  • That doctors will now have to consult a computer program before giving an Rx.... ABOUT DARN TIME.
  • I'd like to have a go at the database myself. Is it included in the article (which I don't have access to)? (It should be, IMHO, because how do you otherwise replicate their results?) Can it be found elsewhere?

  • To be more precise it's directed at the interaction between drugs. So by itself, this study doesn't have any impact on a singular drug
  • But it's not science yet. The more important findings need to be verified in controlled experiments.

  • I think it goes without saying that we should all live as clean and natural as possible. I'm not saying we shouldn't use drugs to improve our health, to fight disease or to manage pain and discomfort. We should. It's very useful to do so. But I am saying we should actively seek to AVOID using drugs and to seek out the most healthy foods and to live the most healthy lifestyles available to us.

    But you know what? I'm fat. I'm definitely overweight. I have been better than I am today but I ate too much o

  • Yes, let's bury the signal under even more noise.
  • a *lot* longer. Maybe, we can just turn them into the whole darn show. I see sitcoms developing around viagra. (Stay tuned for "What's up, Doc?!)

  • Time to invest in stocks that manufacture pill bottle labels.
  • "May result in increased desire for gambling or sexual activity."

    I almost swore it was a joke the first time I saw the commercial, especially given that it was to treat restless leg syndrome.

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