Scientists use ML to find an antibiotic able to kill superbugs in mice • Hacker News Board

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

#71

Post by xzel » Fri, Feb 21, 2020, 3:40 PM UTC

mattmanser wrote: post #57

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…

I don't understand, they didn't find ONE they found NINE. That doesn't sound like luck.

That is sort of the thing about receptors, it is really had to know what will actually work. When you run these types of programs you'll get a number of possibilities that the simulator will spit out, that be from an AI or more traditional stat generated model. There were a few articles very similar to this with Coronavirus cures. They then have to go work in a well designed clinical trial, against a placebo, and then in humans, which is way more unlikely. It's most likely that all 9 don't work, unfortunately. I'm not saying the fact they found them was luck, the luck is if they actually work.

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

#72

Post by whatshisface » Fri, Feb 21, 2020, 3:41 PM UTC

pacman128 wrote: post #67

m3kw9 wrote: post #64

Earlier quoted context omitted.

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.

Are humans more complex than mice or just different? I've always assumed the latter, but I'm in no way an expert.

The mouse genome is about 14% shorter than the human genome, although that could mean a lot or a little depending on certain other factors.

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

#73

Post by asdfman123 » Fri, Feb 21, 2020, 3:43 PM UTC

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…

Yeah, I used linear regression through Excel in my 5th grade science fair to draw a nice line over my data points that showed how plants grew with different fertilizers.

Linear regression is everywhere in science and that can be classified as machine learning artificial intelligence.

Still, it's cool that science is using more data and more intricate algorithms to produce fits.

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

#74

Post by xzel » Fri, Feb 21, 2020, 3:45 PM UTC

entee wrote: post #21

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…

I share some of your skepticism, but I think this particular paper is worth a little less cynicism. It’s true that statistical analysis has always helped inform medicinal chemistry efforts. They used to be called QSAR ;) What’s different here is the scale of information that was processed. As you point out the computational power and therefore the algorithms we can apply has enabled different experiments which I very…

I totally agree, and I think my comment could be summarized as such from another angle. I think the recent Coronavirus + AI = cure spam has me a little jaded. I'll add this, this paper is really well done and like I said I really hope this works in humans!

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

#75

Post by whatshisface » Fri, Feb 21, 2020, 3:48 PM UTC

kirrent wrote: post #7

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…

At least one disincentive is that if you do find an amazing new antibiotic effective against certain strains of antibiotic resistant bacteria, antibiotic stewardship means the medical community will try and use it only where necessary to slow any adaptation to the new drug. That makes your potential patient population much smaller.

Here's an interesting thought. Let's say that the number of possible antibiotics that can be discovered is so high that bacteria cannot simultaneously be resistant to all of them (plant immune systems, which involve a lot of small moleculea, indicate that this may be possible). Then, this game theory trap where stewards are guarding what we have so that pharma doesn't want to make anything new is both pointless and self-perpeuating, because we will never reach the point where we realize we've beaten resistance.

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

#76

Post by Psyladine » Fri, Feb 21, 2020, 3:48 PM UTC

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…

It's a bummer, from the headline you'd think the ML designed a molecule and tests with it showed results, instead it compared known drug interactions against available compounds, sort of a rainbow table matrix. You know, what researchers already do for a living.

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

#77

Post by xzel » Fri, Feb 21, 2020, 3:49 PM UTC

redsymbol wrote: post #69

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…

> 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 guess I'm not sure where the dismissiveness is coming from here. Are claiming this could have been trivially done before? If so, why didn't you or someone else do it already? Or are you claiming it's an uninteresting result that is not worthy of publicat…

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.

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

#78

Post by tjchear » Fri, Feb 21, 2020, 3:57 PM UTC

Rochus wrote: post #68

antirez wrote: post #66

Earlier quoted context omitted.

True but it's interesting that once you have an oracle that given a molecule provides you with an antibiotic score, you can show it directly molecules that are easy to produce and or likely safe for humans. This should help significantly.

It will not go without replication, trials and production, regardless what oracle you have. And keep in mind that the oracle has a quite significant error rate. You won't get an immediate solution, just proposals. And whether or how a drug works is also dependent on the environment and there are dynamic aspects and complex processes within a cell extending over space and time. It's much more complex than speech recog…

We speak in hypotheticals of course, but barring any physics defying barriers here, one can imagine a future where those issues you raised have been addressed (e.g improved simulation/ML techniques, less red tape, faster trials, greater accessibility to treatment). Even now, I think mankind's immune defense is no longer confined to itself, but must be thought of as a bigger system that extends to the pharmaceutical industrial complex. Any sufficiently ambitious bacteria is basically taking on not just us, but also the collective work of all researchers diligently working on the next super bug killer.

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

#79

Post by redsymbol » Fri, Feb 21, 2020, 3:59 PM UTC

xzel wrote: post #77

redsymbol wrote: post #69

Earlier quoted context omitted.

> 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 guess I'm not sure where the dismissiveness is coming from here. Are claiming this could have been trivially done before? If so, why didn't you or someone else do it already? Or are you claiming it's an uninteresting result that is not worthy of publicat…

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 have been published already?

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

#80

Post by Rochus » Fri, Feb 21, 2020, 4:26 PM UTC

tjchear wrote: post #78

Rochus wrote: post #68

Earlier quoted context omitted.

It will not go without replication, trials and production, regardless what oracle you have. And keep in mind that the oracle has a quite significant error rate. You won't get an immediate solution, just proposals. And whether or how a drug works is also dependent on the environment and there are dynamic aspects and complex processes within a cell extending over space and time. It's much more complex than speech recog…

We speak in hypotheticals of course, but barring any physics defying barriers here, one can imagine a future where those issues you raised have been addressed (e.g improved simulation/ML techniques, less red tape, faster trials, greater accessibility to treatment). Even now, I think mankind's immune defense is no longer confined to itself, but must be thought of as a bigger system that extends to the pharmaceutical i…

You are invited to try it. You will not be able to avoid the laws of nature, and there will also be many legal hurdles. But if you make a big step forward, you will undoubtedly be a Nobel Prize candidate.