Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Scientists use ML to find an antibiotic able to kill superbugs in mice

statnews.com

Post reply on HN
Print view View original

81–90 of 93 posts

Re: Scientists use ML to find an antibiotic able to kill superbugs in mice

#81

Post by sp332 »

redsymbol wrote: post #79
xzel wrote: post #77

Earlier quoted context omitted.

I'm saying I'm tired of the puff piece articles and reddit style headlines. I was saying NN's and other "AI" style models has been used in this way for decades for these types of things. 0 disrespect to the actual science; the paper is great and I truly hope it works in humans. We need more drugs against the inevitable fight against drug resistance.

Okay, fine... what do you want to be different about the situation, then? Do you not want any non-technical summary articles like this to be written? So that only those with the training to understand a Cell journal article would be able to learn anything about the result? Or do you prefer that no journal articles be published that rely on 2020-era NN models, because older articles based on less state-of-the-art NNs…

The story could be about perseverance paying off, instead of a breakthrough portending big changes in near-future drug development.

Re: Scientists use ML to find an antibiotic able to kill superbugs in mice

#82

Post by Dumblydorr »

xzel wrote: post #18
entee wrote: post #2

This paper shows what can be done when you carefully run an ML program alongside a wet lab experimental program tailored to feed back into the ML program. The results end up far more interesting than some recent "ML aided drug discovery" papers in that they actually discovered a drug that functions very differently than known antibiotics (AB). Even though the structures that came out look AB-like, they work different…

People have been doing this exact thing for two decades at least but obviously with less computing power. There's literally nothing new about the idea. The real trick is being incredibly lucky and finding something that actually works in humans after multiple trials. I'm sure you know this based on your comment and this isn't really directed at you (truly wish you best of luck, I really hope the computing power and s…

There are differences over time, though. This drug repurposing, for instance, allows us to take drug candidates for other diseases and apply them to new areas. That is a fairly new approach when combined with ML in drug development, as in the past one would see brute force computation without repurposing. Repurposing gets better and better over time, as well, since there are more and more drugs on the lists that we've already run through a gamut of testing.

Re: Scientists use ML to find an antibiotic able to kill superbugs in mice

#83

Post by Dumblydorr »

koolba wrote: post #3

> That is an especially pressing challenge in the development of new antibiotics, because a lack of economic incentives has caused pharmaceutical companies to pull back from the search for badly needed treatments. Each year in the U.S., drug-resistant bacteria and fungi cause more than 2.8 million infections and 35,000 deaths, with more than a third of fatalities attributable to C. diff, according to the the Centers…

The issue is that no pharma company wants to make drugs that will be carefully stewarded as last lines of defense vs super bugs. You won't see 3M patients per year because every hospital system worth its salt has antimicrobial stewardship programs which will interrogate every case of antibiotic use. Doctors are trained and pushed into using these drugs as infrequently as possible because they all know Darwinian selective pressure will render antibiotics less useful the more they're used.

But it's a different story in developing nations with lower standards, where they will steal your IP and bombard the microbial population with every antibiotic they can.

Furthermore, agriculture will surely love to grab new compounds to blanket their herds with. They will not give pharma great profits either, and they'll increase resistance to your fancy new drug that you spent billions developing.

So overall, it's a grim financial picture for pharma and antibiotics. They would prefer to make cancer drugs, chronic disease drugs, biologics, and not these carefully stewarded and easily ripped off antibiotics. IMO, antibiotics will come from altruistic scientists working on their own, and not from the CFOs and bottom lines of pharma.

Re: Scientists use ML to find an antibiotic able to kill superbugs in mice

#84

Post by xzel »

redsymbol wrote: post #79
xzel wrote: post #77

Earlier quoted context omitted.

I'm saying I'm tired of the puff piece articles and reddit style headlines. I was saying NN's and other "AI" style models has been used in this way for decades for these types of things. 0 disrespect to the actual science; the paper is great and I truly hope it works in humans. We need more drugs against the inevitable fight against drug resistance.

Okay, fine... what do you want to be different about the situation, then? Do you not want any non-technical summary articles like this to be written? So that only those with the training to understand a Cell journal article would be able to learn anything about the result? Or do you prefer that no journal articles be published that rely on 2020-era NN models, because older articles based on less state-of-the-art NNs…

I'd much prefer there be more detail in the article about AI research in drug discovery, how it still needs clinical trials in humans. I agree with the sub-comment as well. I think your last question doesn't make sense to me though as I haven't said anything similar to that.

But I think you raise an interesting point about non-technical summary articles: what do they do and who are they for? Does the non-technical public need to know about this research? Do they gain anything vs. reading the study's actual summary? I'm not sure. I do think there isn't much for non-technical people to get from this article that would be useful. I think the best reason would be for younger people to pique their interest in the field. Though, I honestly don't know the answer.

Re: Scientists use ML to find an antibiotic able to kill superbugs in mice

#85

Post by redsymbol »

xzel wrote: post #84
redsymbol wrote: post #79

Earlier quoted context omitted.

Okay, fine... what do you want to be different about the situation, then? Do you not want any non-technical summary articles like this to be written? So that only those with the training to understand a Cell journal article would be able to learn anything about the result? Or do you prefer that no journal articles be published that rely on 2020-era NN models, because older articles based on less state-of-the-art NNs…

I'd much prefer there be more detail in the article about AI research in drug discovery, how it still needs clinical trials in humans. I agree with the sub-comment as well. I think your last question doesn't make sense to me though as I haven't said anything similar to that. But I think you raise an interesting point about non-technical summary articles: what do they do and who are they for? Does the non-technical pu…

Yeah, good points. I guess such non-tech articles serve several purposes.

I do think this one gives non-technical people get something useful, though. More broadly, it'll increase science understanding among the non-scientist/non-technical public, at least on this topic, and good does tend to come out of that.

Re: Scientists use ML to find an antibiotic able to kill superbugs in mice

#86

Post by conjectures »

xzel wrote: post #18
entee wrote: post #2

This paper shows what can be done when you carefully run an ML program alongside a wet lab experimental program tailored to feed back into the ML program. The results end up far more interesting than some recent "ML aided drug discovery" papers in that they actually discovered a drug that functions very differently than known antibiotics (AB). Even though the structures that came out look AB-like, they work different…

People have been doing this exact thing for two decades at least but obviously with less computing power. There's literally nothing new about the idea. The real trick is being incredibly lucky and finding something that actually works in humans after multiple trials. I'm sure you know this based on your comment and this isn't really directed at you (truly wish you best of luck, I really hope the computing power and s…

> People have been doing this exact thing for two decades at least but obviously with less computing power.

Here's an analogy which shows how the cynicism here isn't actually useful wisdom:

Lee Sedol lost at go.

Kasparov lost at chess two decades before.

The Kasparov loss was 'exactly the same thing albeit with less computing power'

Re: Scientists use ML to find an antibiotic able to kill superbugs in mice

#87

Post by SQueeeeeL »

conjectures wrote: post #86
xzel wrote: post #18

Earlier quoted context omitted.

People have been doing this exact thing for two decades at least but obviously with less computing power. There's literally nothing new about the idea. The real trick is being incredibly lucky and finding something that actually works in humans after multiple trials. I'm sure you know this based on your comment and this isn't really directed at you (truly wish you best of luck, I really hope the computing power and s…

> People have been doing this exact thing for two decades at least but obviously with less computing power. Here's an analogy which shows how the cynicism here isn't actually useful wisdom: Lee Sedol lost at go. Kasparov lost at chess two decades before. The Kasparov loss was 'exactly the same thing albeit with less computing power'

Correct. I don't understand why this contradicts the argument.

"Computers can learn complicated games with more computing power"

"Compute power goes up"

"Computer learns more complicated game"

I mean, if you really think of AlphaGo on an extremely high level, it's just a really elaborate way to create and learn a dictionary of moves to take under different circumstances. Of course that's going to be completely dependent on amount of memory and CPU power.

Re: Scientists use ML to find an antibiotic able to kill superbugs in mice

#88

Post by mikorym »

ranDOMscripts wrote: post #30
mikorym wrote: post #23

Earlier quoted context omitted.

I come from a country with serious sewage issues. Most of it is government operated sewage works that are just not maintained and were due for upgrade 10-20 years ago. The issue is also an order of magnitude worse in some areas than in others. The Gates Foundation is not relevant here, in that problem field, in any meaningful way. It is an issue about operational structure and unit cost structure. Tax money gets spen…

It is my (albeit limited) understanding that the Gates grants are focused on providing toilets to areas where there previously were none and not on replacing crumbling infrastructure. They're trying to get facilities to the millions of people who have to poop in the bushes because that's all there is.

That's not the issue. The issue is that there are sewage systems that dump raw sewage into rivers. Toilets are more of a nod to human decency than environmental issues.

But if Bill would like to phone me, then I would explain to him that while decency does score high in my books, you can have perfect golden toilets that dump sewage into rivers. In that case I would rather take a veldtie in the bushes.

Re: Scientists use ML to find an antibiotic able to kill superbugs in mice

#90

Post by sjg007 »

m3kw9 wrote: post #64
headmelted wrote: post #39

Earlier quoted context omitted.

I’m usually also skeptical of getting excited about successful animal trials for new medications, but with this I’m actually leaning more on the side of optimism. With cancer treatments and antivirals in mice, we’re not so much targeting the pathogen as targeting the host immune system in the hopes it ends up nerfing the intended target (tumor/virus/whatever). Given that the compound seems effective against C. Diffic…

Problem with many of these molecules that are found to work in mice, when put in human which is considerably more complex, say it goes thru the liver, the liver may break down most of it when circulating the blood stream. So now the drug needs to also resist that type of break down. Now multiply that by 10 to 100 of other types of reactions your body can generate from this.

Well c diff is in the gut so it’ll work there probably.
Post reply on HN