Looking-up DCTN1 on genecards, a popular site that collates known gene-function relationships, shows that it is already known to be associated with Parkinson's-like conditions [0]. Similarly on Uniprot [2].
I am surprised they end on a gene mutation already known to be involved in a rare disease and a vague hypothesis about the mechanism. Among the many things DCTN1 does... it also directs autophagosomes toward lysosomes for waste degradation. Hm, disruptions in waste degradation.. build up of unwanted proteins and waste in cells... yeah that seems like it would cause neurodegeneration as well! Point being, there are dozens of things, maybe hundreds. Is cholesterol particularly compelling here? Not really. PhD students come up with similar hypotheses every hour. Hypotheses are cheap. I'm sure it can and will do better, but for now... I feel they might be underprepared for curing all disease in 10 years.
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a_sewer_rat
This is combinatorial chemistry of the 1990s, except more stupid and more venture dollars.
shearerp
Notice how it goes from "we proved Fields-medal level stuff" to "promising leads" when we go to the world of biology. Still awesome, but speaks to the limitations of pure thinking in a more applied subject. No automatic cancer cures today.
SimianSci
Ai labs look to be desperate to try and stave off the cooling hype that looks to be snowballing in the industry right now. These next few months are going to be crucial to their potential survival and future.
Its not surprising to me that this press release looks half-baked.
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anthuswilliams
This is one of the laziest and nonsensical press releases I have ever seen attached to a scientific paper. Everything in the press release is either misrepresenting what is in the linked paper or is completely obvious and uninteresting.
Evidently if you fan-out data analysis work across 1946 agents instead of just one, the analysis is faster and more thorough than if you instructed a single agent to go through all of the 1946 genes sequentially. And that, in turn, is faster than if you did it yourself. Like, duh.
The linked paper is not exactly transformative, but the impression it leaves is quite a bit better than the nonsense press release.
jostmey
The problem was never generating leads. The bottleneck is validated results. It’s performing clinical trials proving efficacy. And this is where I think AI will have the biggest impact—-helping scientist, navigate study complexity and regulatory burden
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RomanPushkin
I hope OpenAI will prove its usefulness in stealing joy from mathematicians, engineers, and biologists this time. It feels like there's a chance of warmer feedback this time from everyone out there keeping an eye on what they do.
Personally I would forgive all of the joy being stolen by AI if they discover something fundamental and outstanding that would help all of us.
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mdevere
This is very, very weak.
Clinical science is inundated with well-reasoned "potential leads". Ideas for targets, and even designing drugs to interact with those targets in the desired way, is not the bottleneck. Hasn't been for decades. The bottleneck is in clinical development i.e. human trials.
There are many many AI drug discovery companies out there, many of them very well funded, and ALL of them with no shortage of "potential leads".
These companies usually start out with the idea that their potential leads are better than the alternatives (generally because they cast a much bigger net/ considered more screening criteria than a human could, thanks to AI) and that big pharma will pay them license fees.
And yet, all of those companies, pretty much without exception, have turned into drug development companies themselves. They are forced to develop their own "potential leads" into actual approved drugs. And they are subject to the same timelines, same costs and - so far - the same probabilities of success as any other drug developer.
PerturbAI & OpenAI's "potential leads" might be better or worse than the next AI company. I would guess worse, given there is zero proprietary data involved and no clarity about why the underlying models are going to generate insightful findings. Either way, not useful.
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Metacelsus
So they did a perturb-seq experiment and then launched one agent per gene in the library?
Seems quite inefficient to me. Unless the goal is to spend millions in API credits.
dude250711
OpenAI in sciences: "We have bitten off a bit of each of these apples - you guys finish eating them, because that is what you are best at - finishing half-eaten food. May we have a $2T valuation, please?"
crmd
The valuation bubble pops if the market comes to believe frontier AI will not disrupt other industries at the rate that it did software engineering.
suddenlybananas
Why waste so much space on a chart on whether "human experts preferred distributed-agent reports over single-agent reports"? I thought we were supposed to be curing alzheimer's and cancer!
londons_explore
And here is me just trying to keep ~10 agents busy....
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vatsachak
"new leads"
I use LLMs every day but damn... can we please market them and value them as a coding tool and not the savior/destroyer of the world. "new leads" comes off flat after the previous tone
anfogoat
More PR bs from unscrupulous people. Until you've cured an actual disease for actual people, please shut up.
Noaidi
I am sorry, but if you still have stupid humans these leads will end up going the same place all the leads go. Nowhere.
So what if DCTN1 is linked to Alzheimer's? All they will do is invent a drug to mess with the enzyme and it might only still help a small percentage of people and no one will be able to afford it.
It is well know that diet plays a large role in Alzheimer's[1] and is largely an issue of personal genetics and environment.
Looking-up DCTN1 on genecards, a popular site that collates known gene-function relationships, shows that it is already known to be associated with Parkinson's-like conditions [0]. Similarly on Uniprot [2].
[0] https://www.genecards.org/card/DCTN1#Phenotypes
[1] https://www.uniprot.org/uniprotkb/Q14203/entry#disease_varia...
I am surprised they end on a gene mutation already known to be involved in a rare disease and a vague hypothesis about the mechanism. Among the many things DCTN1 does... it also directs autophagosomes toward lysosomes for waste degradation. Hm, disruptions in waste degradation.. build up of unwanted proteins and waste in cells... yeah that seems like it would cause neurodegeneration as well! Point being, there are dozens of things, maybe hundreds. Is cholesterol particularly compelling here? Not really. PhD students come up with similar hypotheses every hour. Hypotheses are cheap. I'm sure it can and will do better, but for now... I feel they might be underprepared for curing all disease in 10 years.
This is combinatorial chemistry of the 1990s, except more stupid and more venture dollars.
Notice how it goes from "we proved Fields-medal level stuff" to "promising leads" when we go to the world of biology. Still awesome, but speaks to the limitations of pure thinking in a more applied subject. No automatic cancer cures today.
Ai labs look to be desperate to try and stave off the cooling hype that looks to be snowballing in the industry right now. These next few months are going to be crucial to their potential survival and future.
Its not surprising to me that this press release looks half-baked.
This is one of the laziest and nonsensical press releases I have ever seen attached to a scientific paper. Everything in the press release is either misrepresenting what is in the linked paper or is completely obvious and uninteresting.
Evidently if you fan-out data analysis work across 1946 agents instead of just one, the analysis is faster and more thorough than if you instructed a single agent to go through all of the 1946 genes sequentially. And that, in turn, is faster than if you did it yourself. Like, duh.
The linked paper is not exactly transformative, but the impression it leaves is quite a bit better than the nonsense press release.
The problem was never generating leads. The bottleneck is validated results. It’s performing clinical trials proving efficacy. And this is where I think AI will have the biggest impact—-helping scientist, navigate study complexity and regulatory burden
I hope OpenAI will prove its usefulness in stealing joy from mathematicians, engineers, and biologists this time. It feels like there's a chance of warmer feedback this time from everyone out there keeping an eye on what they do.
Personally I would forgive all of the joy being stolen by AI if they discover something fundamental and outstanding that would help all of us.
This is very, very weak.
Clinical science is inundated with well-reasoned "potential leads". Ideas for targets, and even designing drugs to interact with those targets in the desired way, is not the bottleneck. Hasn't been for decades. The bottleneck is in clinical development i.e. human trials.
There are many many AI drug discovery companies out there, many of them very well funded, and ALL of them with no shortage of "potential leads".
These companies usually start out with the idea that their potential leads are better than the alternatives (generally because they cast a much bigger net/ considered more screening criteria than a human could, thanks to AI) and that big pharma will pay them license fees.
And yet, all of those companies, pretty much without exception, have turned into drug development companies themselves. They are forced to develop their own "potential leads" into actual approved drugs. And they are subject to the same timelines, same costs and - so far - the same probabilities of success as any other drug developer.
PerturbAI & OpenAI's "potential leads" might be better or worse than the next AI company. I would guess worse, given there is zero proprietary data involved and no clarity about why the underlying models are going to generate insightful findings. Either way, not useful.
So they did a perturb-seq experiment and then launched one agent per gene in the library?
Seems quite inefficient to me. Unless the goal is to spend millions in API credits.
OpenAI in sciences: "We have bitten off a bit of each of these apples - you guys finish eating them, because that is what you are best at - finishing half-eaten food. May we have a $2T valuation, please?"
The valuation bubble pops if the market comes to believe frontier AI will not disrupt other industries at the rate that it did software engineering.
Why waste so much space on a chart on whether "human experts preferred distributed-agent reports over single-agent reports"? I thought we were supposed to be curing alzheimer's and cancer!
And here is me just trying to keep ~10 agents busy....
"new leads"
I use LLMs every day but damn... can we please market them and value them as a coding tool and not the savior/destroyer of the world. "new leads" comes off flat after the previous tone
More PR bs from unscrupulous people. Until you've cured an actual disease for actual people, please shut up.
I am sorry, but if you still have stupid humans these leads will end up going the same place all the leads go. Nowhere.
So what if DCTN1 is linked to Alzheimer's? All they will do is invent a drug to mess with the enzyme and it might only still help a small percentage of people and no one will be able to afford it.
It is well know that diet plays a large role in Alzheimer's[1] and is largely an issue of personal genetics and environment.
[1] https://news.harvard.edu/gazette/story/2024/07/alzheimers-st...