The article (and what I can access of the paper it is based on) doesn't really give any details as to what this class is, how it works etc. All the interesting parts about this aren't mentioned.
this post was submitted on 20 Dec 2023
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It sounds like they trained a classification model using 39,000 molecules with known reactivity to MRSA. The molecules are vectorized text representations of the structures. Once trained, they can run arbitrary molecules through the model and see which ones are predicted to have antibiotic properties, or at least MRSA reactivity.
They likely fed in molecules from families of structures that seem likely to contain an antibiotic but are too numerous to manually test them all. They get a prediction of which ones are likely to have the properties they want, and then start the slow process of creating and testing the molecules in the lab.
I get what they did (its been something a lot of groups have been wanting to do for years) but I am curious what molecule specifically they found that worked especially well. i.e What does this thing look like? What is the new antibiotic's mechanism of action? None of those latter details are discussed. Its something we can only guess at.
It sounds like they are moving forward with clinical testing in partnership with a bio company, so I'm sure they withheld the information anticipating a patent. The results of this paper was the validation of the explainable AI model which identified candidate classes of compounds.
Wow I love science. I love that someone owns the exclusive rights to sell new drugs at whatever price they want
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ai is finding antibiotics for diseases ai hasn't even created yet (I kid, I kid)
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Finally a good use of AI, instead of using it to replace artists.
Yeah but think of all the bacteria it's putting out of work.
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Quick to the beef depository!
First Check if it doesn't make our fingers merge into a stub
Ooo, a new allergy!
My dad was allergic to practically every antibiotic. He only developed the allergy in his senior years. It was a big problem for him. Even if the antibiotic seemed to be working okay, he had to take a lot of Benadryl just in case and keep an epi pen around.
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Can't wait for anti-antibiotics movements! 😅
Anti-antibiotics... Isn't that just biotics? Like from Mass Effect? IDK, could be cool 👀
Yeah, just like anti-antifa.. 😅
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This AI thing would be excellent at hide and seek.
Does this AI use the same process for piecing together things as LLMs do for art and writing? Is this a drug we have known about but not yet applied as an antibiotic or a whole new compound?
It doesn't sound like it but they don't have enough detail in the article to say.
It sounds likey they are using a classification model that takes a vectorized text representation of molecules and classifies or scores them by their expected properties/reactivity. They took 39,000 molecules with known reactivity to MRSA to train the model, I assume to classify the structures. Once trained they can feed in arbitrary molecules into the trained model and see which ones are predicted to have antibiotic properties, which they can verify with bench work.
They likely fed in molecules from classes of likely candidate structures, and the model helped focus and direct the wet work.
I'm not up on the latest, but years ago I helped a similar project using FPGAs running statistical models to direct lab work.
I'd be interested to know why FPGAs were selected for this application. I'm not especially familiar with their use cases.
This was years ago before GPU processing really took off, and we wanted the performance, but also, wanted to see if we could develop an affordable discrete lab device that could be placed in labs to aid in computationally directed bench work. So effectively, testing the efficacy of the models and designing ASICs to perform lab tests.
With a CPU or even a GPU, there is a bunch of inefficiencies for every task as they're designed to be able to do pretty much anything - your H265 media decoder isn't going to be doing much when you're keeping a running sum of the number of a certain type of bond in a list of chemicals
With ASICs and a lesser extent FPGAs, you can make it so every single transistor is being used at every moment which makes them wildly efficient for doing a single repetitive task, such as running statistical analysis on a huge dataset. This is because rather than being limited by the multiprocessing ability of the CPU or GPU, you can design the "program" to run with as much multiprocessing ability as is possible based on the program, meaning if you stream one input per clock cycle, after a delay you will get one input per clock cycle out, including your update function so long as it's simple enough (eg moving average, running sum or even just writing to memory)
This is one specific application of FPGAs (static streaming) but it's the one that's relevant here
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llms have progressed beyond cut and paste way more than a year ago. they have shown understanding of what items are and how they behave and interact. I know it's popular here to call it a parrot or whatever but most people don't have access to the high level stuff and most seem afraid/snobby/parroting things themselves.
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