I'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.
Derek 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.
there 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).
For 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.
if 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.
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.
nerd-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 ◊.
> "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.
Drug 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.
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.
I think that was originally linked but got changed to the £30 to Elsevier version for some reason.
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.
Wheres my follicles dammit?
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
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.
Only for values of 'all' that exclude well-connected members of the billionaire class and their select associates.
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.
Ketamin should have huge impacts on neuro/brain plasticity when used properly (i.e. in therapy)
In therapy as well.
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.
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.
No? Well fancy that! :)