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Comments (80)

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  pinkmuffinere
  > But let’s think about that 91% failure rate for a moment. When I bring this up in presentations, I invite the audience to consider what the auto industry would look like of 91% of new car designs proved unable to roll out of the factory, or if 91% of new airliner models were unable to leave the ground - and if you only found that out after spending all the R&D money to build them at full size and trying to fly them. No cutting-edge restaurant could survive if 91% of its innovative dishes proved inedible or outright poisonous. What other industries operate under these bizarre conditions?This is bizarre, bordering on stupid. Frist of all, there likely is ~90% failure rate of prototypes; I feel that roughly matches my experience in engineering. Of course the design that makes it through the process, testing, refinement, and into mass production is not going to have a 90% failure rate, but that's a _finished product_, whereas clinical tests are just that -- tests. Finished cars are more analogous to individual pills coming out of the factory. And I'm not even sure the analogy would be very meaningful anyways, because we have different requirements for things of different impact and importance. A 10% manufacturing defect rate is fine in forks, but not for fire extinguishers.
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  mbnielsen
  Many comments so far seem to try to handwave away the 90 % failure as somehow "optimal" in the system, which seems absurd to me. It is clearly not advantageous for individual companies to keep a drug candidate alive long enough for it to fail in stage III or IV. One obvious question is why they don't and it is very, very tempting to speculate that it's because the problems are getting harder, we are targeting novel mechanisms etc. Again, I think this misses a simpler explanation:As with many cases where companies make seemingly bad decisions, I think a lot of the explanation lies in system dynamics. Think about the incentive structure inside large pharma companies - it is generally not a career advancement move for a project manager to kill the drug candidate they oversee. It is career advancing to get it approved for the next stage. What could possibly go wrong in this world?
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  arjie
  Can’t agree with the premise. It seems that through changing regulatory regimes and technology a 1 in 10 chance is the economic optimum for this. Interesting stability, certainly, but I’d expect that as technology improves success rate, funding increases until the marginal project is unprofitable.The better we get at doing things, the more ambitious we get. As an example, we can keep babies alive much earlier in gestation, so we try harder if they’re earlier than we would before. We should expect a homeostatic equilibrium between our skill and our ambition.
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  levocardia
  I'm actually surprised it isn't going up over time. That is naively what you would expect as the low-hanging fruit is plucked. So the fact that it's been stable is probably a sign that scientific advances are roughly keeping pace with the (presumably) increasing challenge of finding ever more targets for drugs.
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  jcims
  Roughly equivalent to the percentage of startups that fail.Lower numbers don’t mean we’re doing better, it means we’re trying less.
• AbsurdCensor
  As someone who works in research, this isn’t surprising at all. It’s hard to find something that treats (well most often reduces symptoms) of a particular disease. It’s even more difficult to find something that is also safe at the dose level it takes to treat said disease. Are there faster ways to do this? Probably not. AI is only going to help out so much, just like automated drug screening only helped so much since its introduction in the 90s.
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  qsera
  >So when we do get something to work and something that people are willing to pay money for, we try to squeeze every dollar out of it because we never know when the next one will come along.Would make a small correction. It does not have to be people. It can be also be "doctors" or "governments". It is easier to convince or coerce/fool a lesser number of humans (doctors) or a single government regulatory body than to fool/convince every one who use the product, because the people can directly evaluate the product.And when a single doctor is coerced, then the product is forced on hundreds of their patients. When a government is coerced, then the product is forced on tens of millions of people..
• Plasmoid
  The author, Derek Lowe, also writes the hilarious Things I won't work with series (https://www.science.org/content/blog-post/things-i-won-t-wor...)
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  contubernio
  Without doing any serious thought, it is concerning that the statistic doesn't vary more temporally. It seems too consistent, and raises the suspicion that it reflects regulatory agenda more than anything intrinsic
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  perpetuallunch
  This is completely unsurprising, and this:But let’s think about that 91% failure rate for a moment. When I bring this up in presentations, I invite the audience to consider what the auto industry would look like of 91% of new car designs proved unable to roll out of the factory, or if 91% of new airliner models were unable to leave the groundIs an utterly irrelevant comparison. For physical thing we have engineering, and the practical application of the trades and craft, trial and error.For modern medicine, we're only just starting to come out of the wild west era. Or perhaps slightly further along than that.
• asdff
  You want high failure rates. If failure rates were low, that tells you that you are probably being far too conservative in funding new clinical trials.
• L-four
  If failure rates went down wouldn't that increase the number of clinical trials until the failure rates go back up.
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  roenxi
  > I’m fond of saying that the most important single statistic about the drug industry is the clinical failure rate, which is (by any reasonable standard) appallingly high.He starts off on the wrong note, there is nothing at all wrong with a high rate of clinical failures. If anything, the reasonable argument standard might be that this rate is too low. It implies researchers are trying things that they expect to have a 10% chance of working out. That means we're missing out on all the cures and techniques that have a 1% chance of working out but but nonetheless do work.Failed attempts cost society nearly nothing and successes will have compounding benifits for, y'know, lets optimistically say the human race survives for centuries. 1% or 0.1% success rates sound completely reasonable with that sort of lopsided risk profile. There isn't much of a reason not to try anything and everything that has the faintest chance of helping and see what happens.
• Fomite
  Doing hard things is hard.
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  refurb
  As someone who used to work in pharmaceutical R&D, the important thing to remember is the hurdle to get over hasn’t remained constant.The FDA has gotten significantly more strict in its review than it was in the 1960s.A good example is hERG inhibition as an off-target effect. It’s a receptor on heart muscles and will result in QT prolongation and potential arrhythmias.It wasn’t discovered until the 1990s. Now every molecule is screened and many are dumped. The impact can vary but there are tons of drugs on the market now that are hERG inhibitors (many discovered after the fact).It’s a good example of the increased rigor that the FDA applies to everything they review that past trials never had to face.
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  debo_
  There's an alternative that is slowly emerging. Many clinical trials "fail" but the drug candidate in question works really well for identifiable subsets of the participants. Right now pharma companies won't bother pursuing those drugs because they can't market it broadly. But it's still possible these drugs could help people in the future.
• _3u10
  Umm restaurants ARE like that, why do you think there’s so many burger and pizza joints?
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  tchalla
  I’ve been hearing for 10 years now on how “AI” will change this clinical rate. It’s now like the “This is the year of Linux” prediction meme. And like Derek has mentioned multiple times you can’t statiscialise biology. I don’t think many people get it so we have tech bros like us throw AI at data.
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  calf
  Why does he conclude there is no alternative? He already argued this would be strange in other disciplines. So reform it.