A valuable application not mentioned here is streamlining synthesis and manufacturing to lower the costs of current drugs. That would positively impact millions more people than a new treatment for advanced pancreatic cancer. But there's not as much potential profit so....
The cost of manufacturing drugs is not where pharma makes it’s profits. Look at the margins for competitive generic drugs and over the counter medicine. Margins are tight.
Pharma makes bank on drugs that are patent protected. Squeezing the manufacturing cost is a small gain on top of that.
Yip, drugs are similar to software in this regard. Expensive to develop, very cheap to replicate. It'd make vastly more sense as a nationalized industry, because I think a profit motive is not only unnecessary, but actively harmful because the drugs that help society the most, and the drugs that make the most money, have little overlap.
If a big pharma had the choice between an expensive treatment that could help treat any cancer, or an extremely cheap treatment that could prevent any cancer - which would they pick? The answer when you're motivated by profit is unfortunately different than the one when you're motivated by social benefit. And this is more than just a thought experiment because this issue is going to drive which type of treatments are pursued.
Problem with those expensive treatments is that there are not that many cases. So profit from each is big but overall they add up to less. Getting everyone who can afford it on planet on some relatively cheap drug would be lot more profitable overall.
Get million out of thousand people or ten out of billion people... Later would be preferable.
Well there's also the third option of get a million out of a billion people. And that's only one side of the perverse equation. The other is rent-seeking. A treatment that needs to be redone or repeatedly boosted is far more profitable than a treatment that simply solves something once and for all, especially if that 'solving' treatment can be done cheaply.
Hard disagree on the oversimplification. Drugs with R&D, certification and production belong to the most complex and hard product classes.. they are nothing like software.
Picking the right drug is a lottery game in itself that involves portfolio strategy, biologic modeling of your product efficacy and safety, optimization of yields, and "field testing". Then you still have to build the right distribution channels to the patient and find someone to pay for your product. Even reproducing drugs is not a trivial thing, as you need to re-certify production plants. In the case of biologics it is even more complicated.
Unless we burn enormous amounts of cash or set up specific incentives, there is not way we can bring primary socially motivated drugs to the market with the current risk structure of the industry.
Pharma is one of the most complex playing fields there is. The sad thing is that we might strongly overstimate the ability to significantly improve the development of new drugs through AI in the next 10 years.
What does flight have to do with anything else in that list? And what about it? Make it cheaper? Greener? Just odd to put such a specific mode of transportation in an otherwise broad list.
Mostly that planes already have good autopilot but still most crashes are due to human error. There is also a reasonably high barrier to entry to piloting. One that can majorly be removed by current autopilot + purpose built AI and anyone should be able to fly without much overhead.
> There is also a reasonably high barrier to entry to piloting. One that can majorly be removed by current autopilot + purpose built AI and anyone should be able to fly without much overhead.
Being a doctor in America has a high barrier to entry.
It’s not because medical science is difficult.
It’s because the American Medical Association (aka, doctor’s union) limits the number of new doctors and medical students each year.
If you 2x the number of medical students, resulting in 1.5x number of qualified doctors, resulting in perhaps 20-30% lower salaries, and maybe 5-10% lower cost to patients.
But no, preserving a doctor’s middle-class salary is more important than lowering patients’ costs.
Ah yes the doctor’s union which has a ~15% membership rate to said union. What a powerful union, when is the last time they had a strike?
Google “number medical students over time”
Then google “number residency slots over time”
Then notice how both of them have been increasing significantly over time.
Then compare the income percentile for doctors in US vs say Canada, Australia etc. all are top 1-3%. Doctors are paid well relative to median salary in every first world country.
Then google “physician percent healthcare costs” and learn that physician pay is about 8-10% of total healthcare spending. Then realize about 40% of that $ immediately goes back to the government via various taxes, so even if you paid physicians nothing you’d only save about 5% of healthcare spending.
Do you not try to verify any information you read before confidently regurgitating it at a later point? You really should…
When students sued the residency system for anti-trust congress passed legislation specifically exempting them from anti-trust completely. They don't need to strike to get their way.
Do unions often work to lower wages paid to their members? Maybe now you’re understanding why so few physicians are members of the AMA? They do not care about (and quite literally do not represent) physicians.
We have clinical trials for that. I’d also suggest that the first step in offering fixes for a complex problem should be educating yourself about the nature of that problem.
We are talking about future research directions, not what's possible today. Given the success AI has had in virtually every domain its been deployed in, there's no reason to think it won't do well simulating physiological processes.
How many of these "we sandboxed it and said not to do Y, but then it went and did it!" stories would you consider necessary to disprove that?
It may be good at following rules 99.99% of the time but if someone launches a million times more parallel agents than they would hire humans, it might still be much worse in practice...
"We've been told we must find an effective drug candidate here, and to follow this process for evaluating the quality of the candidate, but actually we could subtly change the analysis like this to make this candidate look favorable enough..."
(And then compare that to deterministic algorithms...)
We are not perfect as human beings, and we can’t expect AI, which is modeled after us to be perfect too. This fear of AI is irrational.
The argument here is that AI can run permutations faster than any human can. And, feeding it a company’s proprietary data about what worked, what did not, how it worked and so on can be invaluable at accelerating the discovery process of new drugs.
Because human trials are so expensive that will be all the more reason to pre-screen with AI, like we already do with traditional simulations and things like proteome-wide off-target profiling.
There's no regulation on not doing a trial because your oracle machine told you it was an expensive dead end.
