5 ms·
AI in drug discovery – what it is, where we stand and the path forward
https://www.nature.com/articles/s41573-026-01496-2 https://www.nature.com/articles/s41573-026-01496-2
- EA-3167 2mo ago> "The paper goes on to make recommendations for AI companies and investigators, and these are well worth reading. The common theme is that people need to think more about why they’re doing certain techniques or using certain technologies, rather than just using them because they’re newly available." Please. Please let some people with power and influence understand this lesson sooner rather than later. I understand the reasons that's unlikely to occur, but usually the impact isn't quite so drastic and expensive as this is. Just because something is new and shiny doesn't mean that it'll produce the outcomes you need at the other end, and until it's shown that capability your approach to it should be MODERATE.
- bbondo 2mo agoDrug discovery scientists think about what they're doing and why ALL THE TIME. AI stuff is just another tool. It's also worth mentioning that drug development timelines typically exceed the interval in which these technologies have been available (or at least effective). Measuring impact will take a long time.
- Xenoamorphous 2mo agoNeed one for hair loss ASAP.
- asxndu 2mo agoAlready exists (finasteride), only problem is that it castrates you chemicallym
- pstuart 2mo agoYep. Not everybody but enough to warrant vigilant monitoring and titration.
- gradus_ad 2mo agoFor everyone struggling with hair loss but concerned about side effects of Fin. Look into topical fin. It produces higher concentrations of the medication in the scalp and lower systemic concentration. Not perfect, but better.
- skepticATX 2mo agoAbout 2% of finasteride users experience these side effects, and they are reversible after discontinuation.
- pton_xd 2mo agoApparently some users report persistent side effects even years after stopping the medication (post-finasteride syndrome).
- xX_Hacker_Xx 2mo agoyep that would be me
- Vacyyyy 2mo agoAre you familiar with Dr. Powers, there's hope
- xX_Hacker_Xx 2mo agonot familiar tbh, i will check it out sometime. thanks
- debugnik 2mo agoHow many of them can be accounted for by the natural rate of sexual dysfunction? I've been taking it without significant side effects for ~15 years, so I'm not worried, although at this point it's losing its main effect as well.
- deleted 2mo ago[deleted]
- rubicon33 2mo ago[flagged]
- newsomix9xl 2mo agoIndeed. My plans for a youthful Mohawk are being stymied by the lack of AI promised medical breakthroughs. Wheres my follicles dammit?
- alpineidyll3 2mo agoAbsci has a good asset coming out pretty soon that you could try to get on the trial.
- codemax98 2mo agoAbsci is bullshit
- xX_Hacker_Xx 2mo agothere is a AI designed drug for hair loss that i know of. its slow-release oral minoxidil formulation called MINX. AI helped with the formulation [1]. its in in similar category as VDPHL01. Hundreds of millions if not a billion dollars has been invested into Veradermics, and their main product is VDPHL01 (also an extended-release oral formulation). [1] https://x.com/anagenxyz/status/2071601868841595082 https://x.com/anagenxyz/status/2071601868841595082
- kridsdale1 2mo agoI’m on 0.5 to 1mg oral minoxidil daily for a few years now and it’s working great. Blood pressure benefits too.
- rubicon33 2mo agoAny other side effects? I’ve never even heard of this.
- mjmj 2mo agoI’ve taken low dose oral min for a few years and it’s systemic, meaning it’ll make all your hair grow. I now have body hair where before it was never noticeable. “I’m hairy like monkey” as my kids say.
- kridsdale1 1mo agoCan confirm. My torso and upper arms be sprouting like Robin Williams. Wasn’t like this before. Thankfully that’s easy to buzz off, and worth it to keep my head.
- Scoundreller 2mo ago> Blood pressure benefits too. Speak for yourself, if mine goes any lower I’m going to pass out
- SoftTalker 2mo agoA good set of clippers.
- piskov 2mo agoTrack KX-826, clascoterone, and VDPHL01
- Z_I_F_F 2mo agoPP-405 too
- deleted 2mo ago[deleted]
- p-o 2mo agoWe're all about to come face to face with this reality. This dance can only last so long.
- alpineidyll3 2mo agoif you think the state of the art in this area is something you'll hear about from a guy that looks like santa in an academic journal, your investments deserve what's about to happen to them.
- GolfPopper 2mo ago>We're all about to come face to face with this reality. This dance can only last so long. Only for values of 'all' that exclude well-connected members of the billionaire class and their select associates.
- esseba-dev 2mo ago[flagged]
- WarOnPrivacy 2mo agonerd-fanboi proposal: Articles by national treasures (like Derek Lowe, Raymond Chen) should be highlighted with specific identifiers on HN - like a distinctive title font or an ascii diamond ◊.
- snapetom 2mo agoNo thanks. Social media needs less hero worship. Just RSS whoever you like.
- WarOnPrivacy 2mo agoI agree. I won't do heroes. Ever. A National Treasure, on the other hand - they enrich life without being a vector for tribalism (eg:Michael Kramer/Kate Reading).
- snapetom 2mo agoStop calling them "National Treasures." That's hero worshipping. That's just sad.
- jayd16 2mo agoMake the feature a per user list of flagged sources.
- gedy 2mo agoI would have agreed in past, but the new random "blog" at whatever.etc being written by LLMs is making me skip clicking most links here now.
- Oarch 2mo ago[AI drug discovery] was never the hard part.
- techpression 2mo agoThis made me laugh, more than expected, but I did visit LinkedIn just before so that could explain it. Thanks!
- bharatsuthar 2mo agoYeah it's [x was never the hard part] all the way down. It's a very human thing and I bet we'd keep saying that even after we've solved the hardest mysteries including consciousness, the origin of life or the true nature of reality.
- xtracto 2mo agoSomehow reminded me of: THERE IS INSUFFICIENT DATA TO ANSWER THE QUESTION.
- cryptographical 2mo agoneed one for brain plasicity. it would be nice to be able to easily learn a foreign language or musical instrument naturally.
- KellyCriterion 2mo agoThere is one! Ketamin should have huge impacts on neuro/brain plasticity when used properly (i.e. in therapy)
- immmmmm 2mo agoPsychedelics are several orders of magnitude stronger on the plasticity front. In therapy as well.
- bharatsuthar 2mo agoSo is ketamine but we haven't explored it more for other brain functions where it can act as a psychoplastogen eg reopening critical periods of visual learning.
- deleted 2mo ago[deleted]
- consensus1 2mo agoPsilocybin has this effect. Source: I can't remember where I read it, so low confidence.
- bharatsuthar 2mo agoSure, but what kind of protocol are you going to use to actually reap the benefits of these transient neuroplasticity effects, especially for learning something new like math or piano as an adult? Same with ketamine. It's not like you can take it a couple of times and open some magic window where everything suddenly becomes easier to learn. From my personal experience and surface-level understanding of the current research, psychedelics(including ketamine) seem to temporarily relax hardened beliefs/priors and rigid neural pathways, which can help you see things from a fresh perspective. But learning something substantial like math or a new language after you've passed the most plastic stages of development is still going to take much longer than what these drugs can realistically help with. They might make you see something differently or even get you extremely interested in it, but sustaining that interest and consolidating the knowledge or skill is still slow compared with childhood/adolescence. Of course, it depends a lot on what you're learning. For example, crystallized intelligence and sufficient motivation can make some things much easier to learn as an adult, but many useful things are also just boring to learn when you no longer have a childlike plastic brain or an environment built around constant learning. Edit: Theoretically, you could accelerate learning by taking psychedelics/ketamine at a set frequency but it's a huge gamble because of their risk profile. eg. HPPD/trauma risk with classic psychedelics and bladder/neurotoxicity risk with ketamine if you get addicted or take it too frequently.
- chrisjj 2mo agoHas this yet produced a treatment for AI psychosis? No? Well fancy that! :)
- tim333 2mo agoDerek Lowe discusion of the paper https://www.science.org/content/blog-post/so-how-ai-drug-discovery-doing-really https://www.science.org/content/blog-post/so-how-ai-drug-dis... I think that was originally linked but got changed to the £30 to Elsevier version for some reason.
- murphyslab 2mo agoDerek Lowe as a science communicator, and others like him, is sorely needed to understand the real meaning and significance of the study and others. I say that as someone with a PhD in chemistry who's been to plenty of presentations on drug discovery topics. It's difficult to calibrate statements made by other scientists unless you're well embedded within a field: Is this someone whose opinions matter? Are they the subject matter expert they make themselves out to be? Is this research itself truly impactful? Is it really 5 years until it will be realized outside of academic labs? Etc... It's difficult to decipher questions around credibility because they rely on real-world interactions and associations that extend beyond the physical tokens of paper counts, publication venues, citations, and author lists that typically lag behind the front of human knowledge which is generated from real-world interactions. It can be simple things, like the insightful question a grad student, with minimal publication history, asks in a seminar. Of course, the paywall is also unhelpful too, but a good, brief commentary by an appropriate commentator is a better link for 99% of prospective readers compared to most "peer reviewed" (scare quotes because that's a real question nowadays) articles.
- joe_the_user 2mo agoNot that I'm a Derek Lowe fanboy or anything but the entirety of your comment is like "that guy needs to check himself" without, like, any specific context, any specific argument he's wrong on this specific question or like anything. It's like "deciphering questions around credibility" is hard ... all the way down. Where's yours? What are you saying?
- bogzz 2mo agoIsn't the comment in fact praising Derek Lowe as a science communicator? In the second paragraph OP is just posing the questions that one might have when reading about a field not your own, that highlight the importance of reliable science communicators.
- colingauvin 2mo agoI'm a structural biologist at a mid-sized biotech. I use AI tools daily. They make accomplishing the same things I was able to accomplish before quite a lot faster and easier. They don't help me magically accomplish new things that I couldn't previously. For example, it helps me install academic software, debug things. It helps me take a large dataset and write scripts to ask questions. It helps me go through experiment drafts to see if I'm missing things. It helps me remember obscure formulas I use every 6 months. It has not, at least in my experience, come up with anything truly novel. A concrete example: AlphaFold is great...to come up with a starting model for a chimeric fusion or something. What would have taken me 1-2 hours fumbling around in PDB or CIF files is now a quick prompt.
- iririririr 2mo agodo you feel this is the same trade off of UI builders like android studio (or msvb6). you do in minutes what you previously did in 2, 3 hours. is it all the work? no, but it's a part that's early on and have high perceived impact. then, as you progress, that tool actually gets in the way and a new feature that would take 2 hours, now is around 2 days.
- colingauvin 2mo agoIn some ways, but it's tough to say if that's my ADHD or not. It's far too easy to leave one branch of reasoning now and jump to another whenever progress gets difficult. Though in some areas where I can sustain interest, AI is helping me go deeper. For instance, I've been putting myself to sleep at night by just asking it questions about expectation maximization and Bayesian statistics. This has seriously boosted my understanding of cryo-EM alignment algorithms in a way I couldn't do in grad school because there was no professor that understood enough to help me when I got stuck reading literature. So it's a double edged sword for sure.
- calvinmorrison 2mo ago> In some ways, but it's tough to say if that's my ADHD or not. It's far too easy to leave one branch of reasoning now and jump to another whenever progress gets difficult. I have a co-worker who doesnt feel like ADHD helps him because he sits down and just starts... doing work and typing. Assign him a complex task, he will just start on it. Mind blowing he does this day in and day out. an absolute machine.
- largbae 2mo agoHow refreshing was this article vs. all the slop? The lack of comparable data and testability really does seem to be a challenge. I wonder if people would be more willing to collect and share lots of health data if the collecting company was a non-profit dedicated to anonymizing it.
- arionhardison 2mo agoI think the real win here is for idiots like me: A) no education B) no resources C) not smart enough to be a self-taught bio-hacker Everyone hears "AI is going to cure disease" and pictures some cure-all pill from a bio lab which is what I feel this paper is hinting at is missingb but that's the top of the funnel; I'm at the bottom where patients live and that is where AI is already quietly working. Its just not being benchmarked. I built https://crohns.ai https://crohns.ai. I set out to make an AI-native clinical-trial manager with a feedback loop (DDP) and ended up somewhere completely different: instead of chasing a new "drug" which is totally out of my grasp; financially, intellectually etc... I used it to codify a care protocol that helped me avoid a flare after I got laid off, lost my insurance, and lost access to Skyrizi.
- dmix 2mo ago> Skyrizi How are those biologics? Did you have to visit the doctor to get injections frequently?
- arionhardison 2mo agoHands down the best drug I have been on EVER; but its 11k a month with no insurance. The 1st 2 injections where done by a nurse that came to my home, the others were done as self injections using their njection kits.
- arionhardison 2mo agoIronically, now I have several people that are on it tracking their infusions etc... Intent: https://wiki.crohns.ai/agent/posts/ibd-biologic-switch-decision https://wiki.crohns.ai/agent/posts/ibd-biologic-switch-decis... Program: https://crohns.ai/program/71168-biologic-therapy-initiation https://crohns.ai/program/71168-biologic-therapy-initiation Protocol: https://crohns.ai/protocol/71168 https://crohns.ai/protocol/71168 If given the chance, I might go back on it because my protocol can be a little strict at times but either way I do see a significant shift to tools like this given the state of the US Healthcare system.
- 2mo ago
- scripthound841 2mo ago[dead]
- plaidfuji 2mo ago> “…the focus of AI in drug discovery must shift from doing what can be done - such as modelling data that is readily available, but that is unlikely to move the needle - to doing what should be done, even if this requires, for example, substantial data generation…” It’s a worthy goal, but I think that many involved in this work might be thinking, even unconsciously, “You first”. This is the problem with AI for all of science - not just drug discovery. Applied ML has spread like wildfire through academia over the past decade - this started well before the LLM hype. It’s the perfect honey trap: research is painstaking and slow, ML offered a shortcut, and best of all, it just needs data. Research produces lots and lots of data! Surely this will be a match made in heaven. I’ve watched the same pattern play out at least four or five times now in various roles. (1) Propose an ML-guided approach to material/chemistry discovery/optimization. (2) Gather existing data (real, experimental data). (3) Realize there’s less than about 50 true rows of data on the outputs of interest. At this point, you either: (4a) revert to traditional methods but keep the veneer of using ML to save face, or (4b) pivot to computational/simulation work or a high-throughput system that’s very far removed from your original problem, but allows you to keep playing with ML toys It’s really bad. I left the industry. I don’t know how long it will take for people doing real science to take back the reins (and the funding).
- eru 2mo ago(3) seems like a problem in its own right? Basing science, traditional or newfangled ML, on such small amounts of data looks pretty weak.
- plaidfuji 2mo agoIn chemicals and materials, 50 rows of good data is a really solid study. That’s e.g. a 3x4x4 experimental design (assuming replicates for each condition get averaged into a single row). If you managed to prep that many samples correctly and obtain consistent characterization data across all properties of interest, you’ve easily got a paper. It’s also kind of malpractice to jam this type of data (few samples, wide rows) into modern ML models. There are plenty of simpler statistical methods that will tell you what’s going on, and even then a well-made plot might be good enough. The difficulty is not in drawing insight from the final numbers, it’s almost always in how those numbers came to be in the first place. Thus the reticence of science-oriented companies to invest heavily in these mass data-gathering exercises to feed ML. It’s damn expensive, and almost always leads you back to raw data issues, not breakthrough discovery. Doing it without a set purpose in mind is even more likely to yield garbage.
- scripthound841 2mo ago[dead]
- redox99 2mo agoObviously the missing part (which we already have for software and math) is that we need agents to be able to run automated loops in the real world. That basically requires robots. I think we'll be there in less than 5 years.
- tim333 2mo agoAs to >clinically relevant impact is, so far, disappointingly limited it could be that the AI tools have to get to some threshold before they are very useful? Like with the Economist talking to Hassabis: >AlphaFold itself took six years of work to predict its first protein structure, and then one year to follow up with what he describes as the structures of “all 200m proteins known to science”. He hopes a similar speedup will happen inside Isomorphic.
- rimbo789 2mo agoI hope to be lucky enough to never take a drug that ai had any impact on the discovery or study
- Marciplan 2mo agothe comments in this thread is what makes me love hn
- tclarke142 2mo agoWhat I increasingly see at my Biotech is more and more AI assisted drug candidates but no corresponding improvement in the capacity or ability to manufacture and scale them. I think it's a problem that groups like Anthropic will encounter in a few months/years and one that will annoye them a lot because it's not as simple as throwing more compute, people or money at it.