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- Hacker News
- >It’s a nerve-wracking way to live, but there’s no alternative in sight.
There's always AI simulation on the way. Deepmind's Isomorphic labs is working on it https://www.isomorphiclabs.com/articles/the-isomorphic-labs-...
And an AI designed drug for idiopathic pulmonary fibrosis from Insilico Medicine is going to clinical trials https://www.artificialintelligence-news.com/news/insilico-me...
by tim333 - In addition to many others commenting that a great defense is to reject a lot of things.
But also it strikes me, perhaps we're also approaching the limits of "drugs" as in compounds delivered by topical, oral ingestion, injectable etc? Perhaps the human creature needs upgrades that go beyond "just add chemicals systemically"?
I'm thinking of things like targetted delivery by nanobots, gene editing, replacing body parts with engineered/mechanical versions...
For example maybe we can obviate statins for those who have genetically high cholesterol by editing their genes, or maybe just replace the failing biological pump (heart) with a mechanical one?
(Cue all the folks with the "One does not simply" memes :) )
by maerF0x0 - 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 ground
Is 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.
- If someone said, 91% of software projects fail, i would beieve them.by bawolff
- > Is 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.
I don't think its irrelevant, but a better comparison would be to what vacuum tube development looked like before we understood electrons. There were some very whacky designs and most of them didn't work for crap.
And, yeah, I would argue that PCR shifted us from the alchemy phase of biology to the science phase and now mRNA has shifted us from the science phase of biology to t he engineering phase of biology. We're just getting started.
by bsder - > For modern medicine, we're only just starting to come out of the wild west era. Or perhaps slightly further along than that.
Why do you say that? What's the evidence? We continue to have virtually no clue how to make drugs, per TFA.
by estearum - > 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.
You could say the same about deep learning. Yet we see improvements every day.
by amelius - And, moreover, the human body is much, much more complex than any plane or car. We know how cars work and how planes work. For many parts of the human body, we don't know exactly how they work. We have multiple hypothesis, maybe, but we can't say "oh yes this is how serotonin works in the brain". We might know the small scale interactions, but why do SSRIs work in terms of the entire brain? We don't know. Why and how does anesthesia work? We also don't know.by preg_match
- Also, highly related, in the previous paragraph, they say: "We know a lot more about the biology of disease - although God knows, not nearly enough".
Anyone smarter than a 10 year old would not we actually know almost everything about car design. How it works is not at all hidden. We have iterated on pretty much the same thing for 100 years. The current state is about efficiency, materials and manufacturing.
When you have deep knowledge and experience in a field you will get near 100%.
by mianos - Indeed, I suspect the failure rate of, say, new jet engine designs is rather high as well -- those failures just never get reported in a federal repository, unlike RCTs, since they never make it out of the simulator or the prototyping lab. And we have, comparatively, much better computational models of how airplanes fly than how cancer cells mutate. FWIW this clinical stat is far better than Edison's supposed lightbulb-idea failure rate!by levocardia
- 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...)by Plasmoid
- 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.
by refurb - It's interesting that you frame it as the FDA increasing regulation and not that science has increased its foreknowledge of problems.by mmooss
- I had to look what "clinical failure rate" means and I think I got the answer in this paper [1] and... I'm not going to say that it is worrisome. Unlike other industries, we can't accurately model in the pre-prototype phase how something will behave in living beings. And to use the author examples, cars and airliners are big and way simpler to model than the complex pathways that you find in biology.
We are chipping away at that problem but it's not like we have it mostly solved as other engineering areas of knowledge. I would argue that due that phase I successes isn't the benchmark, but phase II success should be the actual measure. I'm sure that if someone charts the accumulative success rate for each phase of clinical trials, you will see that phase I is the most brutal one.
by braiamp - > I had to look what "clinical failure rate" means
That should have been the end if the comment; the follow-up by demonstrating such expertise just has me laughing.
- Roughly equivalent to the percentage of startups that fail.
Lower numbers don’t mean we’re doing better, it means we’re trying less.
by jcims - lower numbers might be play to not lose, instead of play to win. On the other hand, do no harm.
ugh, I don't know
by m463 - I’m not entirely sure other startups necessarily want to succeed…
Their goal often seems not to be toward a successful, sustainable product. They just market their vision in the hopes of being acquired.
A few fewer failures might not be entirely a bad thing.
by BobbyTables2 - 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.by AbsurdCensor
- 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?
by mbnielsen - The human body is an extremely complex system. Simulating it completely accuracy would require a computer many orders of magnitude more powerful than anything currently existing, so the only way to know if a treatment doesn't produce any unexpected side effect is years of empirical testing, because such things can take years to manifest. Fundamentally the problem space contains inescapable complexity; it's not the fault of pharma firms.by logicchains
- Sure, but Pharma A is full of career managers who never kill drugs under development and Upstart B relentlessly culls drugs that don't work early on. Upstart B's failure rate at the final stages is under 50% so they develop 5 times as many drugs, beating the existing company, and indeed all other drug companies.
Since this isn't happening, it seems this might not be the explanation.
by rwmj - > it is generally not a career advancement move for a project manager to kill the drug candidate they oversee.
You're grossly oversimplifying the process. The decision to "kill" a drug is huge, especially if it's already in the clinic (per the article). That decision will be taken by a large group of people, not an individual - and certainly not a "project manager".
by mft_ - 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.by levocardia
- I suspect there's a ceiling on failure rates people are willing to operate under. A diversified investor might still be willing to take high risk/reward bets. But workers can go their whole career producing nothing of value. It becomes hard to tell the difference between smart, hard working people who were unlucky and lazy grifters. I've done 2 series-A startups and I don't think I can do another one.by bwhiting2356
- He points out that it basically has gone up, since the 80s and 90s brought some new therapeutic targets and approaches that by now have been mined out.by CamperBob2
- I actually do this for a living within pharma now! There's a TON of work that goes into drug discovery before we even call it a program. The odds of success are low, so we put in months of work evaluating a candidate before even have a hunch of a program.
Yes, the science advances, previously high-hanging fruits become low-hanging become high-hanging again [1], but the tooling also advances: we now have databases like OpenTargets which let us more easily evaluate potential drug targets. Failure is so much more than that, though: a program can fail after you've shown efficacy in animals, sometimes it just doesn't happen in the human subjects. Or you fail to find the right measurement (endpoint). A million ways to die.
[1] Gene editing is an example: impossible, then very possible, but now the blocker is public perception which in turn blocks investment.
by a_bonobo - 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.
by arjie - But technology isn't improving the success rate. And the marginal project is already expected to be unprofitable. Pharma is a hits driven business and the hits are getting simultaneously more expensive to produce, harder to find, and enter into a much more competitive market environment.by estearum
- The economic calculus is ambivalent between a clinical trial with a 10% chance of a drug discovery worth a billion dollars, a 100% chance of a drug discovery worth a hundred million dollars, and a 1% chance of a drug discovery worth ten billion dollars. I'm not sure the economically marginal project is less likely to fail as much as it would simply target more niche markets.