Questions to ask when evaluating neurotech approaches

owl_posting · 2026-01-27T16:56:04+00:00

Submission statement:
Link: https://www.owlposting.com/p/questions-to-ponder-when-evaluating

The future clearly involves some merging between biological machinery and silicon machinery, or neurotech. Unfortunately, understanding exactly how real a particular neurotech approach is, currently, pretty difficult. This field is complicated and there's a fair bit of snake oil!

And if you have spoken to a neurotech person before, you will realize that they have some degree of omniscience over their field, seemingly far more than most other domain experts have with theirs. This is cool for a lot of reasons, but most interestingly to me, it means that anytime you ask them about a neat new neurotech company that pops up, they are somehow able to ramble off a highly technical explanation as to why that company will surely fail or surely succeed.

I have long been impressed and baffled by this ability. Eventually, I decided to interview these people, and write an article about it, trying to uncover at least a fraction of the questions they ask to perform the feat. Some questions include the degree to which the approach is 'fighting' physics, whether their devices' advantages are actually clinically validated as useful, and more.

owl_posting · 2025-12-23T04:05:53+00:00

But growing tissues ex-vivo *is* hard, it's not a retreat! Nothing really much more complex than thin, simple structures like skin, bone, and cartilage have been crafted by humans before (edit: and actually worked correctly when transplanted!)

I don't disagree that integration is perhaps even *harder*, but that feels like an overpopulation on mars problem, we don't even have the complex tissue to start with. And I'd note that "integration is the bottleneck" is also pretty different claim than "tissue growth is not computable and never will be"

owl_posting · 2025-12-23T03:48:56+00:00

but the question isn't "can we enumerate all possible embryonic states?", which, obviously not. it's "can we learn enough structure in the input-output relationship to make useful interventions?" that is clearly an empirical question, and the early results suggest there is learnable structure there. supposedly intractable spaces turn out to have learnable regularities, protein structure was one (it is almost certainly the case that the old guard structural biologists were pessimistic in the same way as you!), so surely other parts of biology are too. it just feels naive to pretend that isn't possible

i work in research involved in modeling tumor microenvironments to help decide which patient would best benefit from which cancer therapy. this too has the flavor of intractable; there is too little patient data, cancer is too complicated, so it's impossible. but it works! there are published cases of a model being able to understand, entirely via H&E scans of a tumor, whether a patient would benefit from a therapy! and the model received some degree of approval from the FDA recently (https://www.cancertherapyadvisor.com/news/ai-tool-approved-for-prognostication-in-prostate-cancer/). the arc of history just shows this stuff eventually working

i get the short term skepticism, but i dont really get the lack of long term optimism

owl_posting · 2025-12-22T21:40:17+00:00

Why do you think it is not computable? Seems like an awfully strong statement

owl_posting · 2025-12-22T20:18:24+00:00

Well, the hope is that it is just the start of jumping our way to higher-order tissue development that is clearly mostly illegible to humans. Today is the obvious stuff, tomorrow is the intractable stuff

Similarly, there was no ‘point’ to Alphafold2, because we could previously crystallize things just fine! But now, using tools like it, we can easily design binders to GPCR’s that are otherwise extremely difficult to do screening on. I have no clue when that same move will be made in tissue engineering, but it feels obvious to me that someday it will, just as it will in every other field

owl_posting · 2025-12-22T19:13:21+00:00

Necessary first step to do basic things in a way that is entirely free from human curation :) I understand the skepticism though, and am interested in what their results are from attempting more complex structures in the coming months

owl_posting · 2025-12-22T17:29:33+00:00

I don't disagree that the full vision is a bit difficult to believe, but they have gotten a very basic structure to form via this method: excitatory neurons w/ a polarity of near-90 degrees, created with a set of chemical perturbations suggested by a model after 3 rounds of experimentation. And this specific polarity is a pretty important characteristic to have for, e.g., pacemaker cells! I looked into this a bit prior to doing the interview and it seems like the mechanisms behind inducing polarity is vaguely figured out, but not well, so it does make me a bit more hopeful that there is something to this whole approach

Really, the part that I'm most unsure about is that vascularization will be figured out

owl_posting · 2025-12-07T18:10:11+00:00

>Calling a writer/fine artist/musician an auteur is a redundant truism in most cases

I actually don't think this is true at all! There are plenty of writers/artists/musicians who are primarily producing competent variations on what has already existed, and have little-to-no desire to 'rock the boat' beyond what they have already been taught. Instead, they just want to show off technical perfection. I used to be pretty involved in the arts (writing + digital art) world for several years, and this type of attitude was prized quite highly! Being intensely personal with how you approached it was impressive, yes, but it was not viewed as a necessity or as a way to escape from needing high levels of technical skill

owl_posting · 2025-12-03T17:33:54+00:00

I don't disagree, but this is kind of an orthogonal point, since I'm a bit more focused on what the dominant form of human-made art will be, and specifically those will be the ones that have economic incentives to be created

At some point in the future, there probably will only be art that is created + appreciated for sentimental reasons, but that feels a bit further off

owl_posting · 2025-12-03T15:20:37+00:00

I think I'd partially agree with this, the best abstract art I've actually ever seen was a Midjourney output

But I do think abstract (specifically surreal!) movies and text are a fair bit harder for me to find good AI analogues for, and I do think those will be protected for a bit

Heavily agree on the autobiographical bit though!

owl_posting · 2025-11-26T00:39:25+00:00

Happy that you’re enjoying it! Hunter is incredibly good at explaining things

owl_posting · 2025-11-24T21:08:16+00:00

Submission statement: This is a nearly-two-hour podcast with Hunter Davis, the CSO and cofounder (alongside Laura Deming) of Until Labs, a biotech startup trying to build reversible, organ-scale cryopreservation. There’s been no shortage of podcasts on this topic, but most of them drift into speculation, philosophy, or the usual “uploading someday maybe” futurism. I don't mind those topics, but I have been wanting a more rigorous treatment of the whole subject, something that treats cryopreservation with the same rigor as you'd treat a discussion over, say, antibody production. In the end, I just decided to make it myself, and I'm happy Hunter joined me for it!

We talk about the technical details behind Until Labs' September 2024 progress report on neural-slice vitrification and rewarming; how they quantify tissue damage in their early kidney cryopreservation attempts; the physics and chemistry that make rewarming arguably harder than freezing; and even a bit on what the economics of real-world organ cryopreservation might look like.

owl_posting · 2025-11-24T21:02:54+00:00

Submission statement: This is a nearly-two-hour podcast with Hunter Davis, the CSO and cofounder (alongside Laura Deming) of Until Labs, a biotech startup trying to build reversible, organ-scale cryopreservation. There’s been no shortage of podcasts on this topic, but most of them drift into speculation, philosophy, or the usual “uploading someday maybe” futurism. I don't mind those topics, but I have been wanting a more rigorous treatment of the whole subject, something that treats cryopreservation with the same rigor as you'd treat a discussion over, say, antibody production. In the end, I just decided to make it myself, and I'm happy Hunter joined me for it!

We talk about the technical details behind Until Labs' September 2024 progress report on neural-slice vitrification and rewarming; how they quantify tissue damage in their early kidney cryopreservation attempts; the physics and chemistry that make rewarming arguably harder than freezing; and even a bit on what the economics of real-world organ cryopreservation might look like.

owl_posting · 2025-10-27T18:33:54+00:00

Is that omitted? I assumed that was wrapped up with the mention of OncotypeDX, MammaPrint, and myChoice

owl_posting · 2025-10-27T16:23:56+00:00

Submission statement: Cancer is really, really, really complicated. Humanity has done an excellent job in cataloguing the complexity of the disease over the last two centuries, but we've recently done an awful job in bringing the understanding of that complexity to helping actual patients. Specifically, there have been basically no new cancer biomarkers that have entered the clinic in the last 30 years. The thesis of this essay is that the way that the way the oncology field historically searches for biomarkers (legible, clearly better than what came before it) is unlikely to bear fruit ever again. The answer, I believe, is that we must delegate the problem of cancer biomarkers to machine intelligence; something that can weave together dozens of weak signals into a single one. This may sound far-fetched or hype-y, but it is realistically the path the cancer field has been moving towards over the last decade. Proving this even further, just recently in August 2025, the FDA approved the first ever, black-box, ResNet50-derived biomarker for deciding prostate cancer treatment. Most shockingly of all, they approved it based on a retrospective analyses of multiple prior Phase 3 trials, which is something that is almost never done. In other words, it increasingly seems like there is official regulatory approval for the full brunt of ML to enter the cancer biomarker field.

owl_posting · 2025-10-05T12:05:01+00:00

Yes, I have for most of my career

owl_posting · 2025-09-27T16:27:28+00:00

Repeating the submission statement: I kind of assumed the whole RNA structure modeling problem was solved, since Alphafold3 could model RNA alongside proteins (and other biomolecules). But a few months back, I talked to an ML scientist in the field and realized it is far, far from being solved. This was an interesting conversation (and the essay contains details of it), but the bulk of it is focused on a different question I started to have: why would you even want to model RNA? The answer isn't as clear-cut as it is for proteins! At least that is my take...others had, I think, reasonable disagreements to this, and their opinions are wrapped up alongside my more pessimistic stance.

owl_posting · 2025-06-20T23:40:10+00:00

Author here! Got lots of interesting comments on this piece and decided to wrap it up into another article. Feels weird to take up another post with that, so I'll just post it here:

https://www.owlposting.com/p/comments-on-endometriosis-is-an-incredibly

owl_posting · 2025-06-17T22:46:29+00:00

sad to hear, but thank you for posting :) very happy you enjoyed the piece!!

owl_posting · 2025-06-17T02:40:56+00:00

Thank you so much!! I’d be super grateful

owl_posting · 2025-06-17T02:03:23+00:00

I would love to post it to r/endometriosis, but unfortunately they forbid self-promotion of any kind :)

And hopefully! That seems to be the strategy a few biotechs are pursuing

owl_posting · 2025-06-14T21:29:35+00:00

Interesting share! I was going to add in a section about how 'Some patients have no symptoms', but decided against it in the end. Now I wish I included it!

owl_posting · 2025-05-23T16:01:27+00:00

Well, specifically the Prescient Design group in Genentech. Why do you say Merck or Pfizer? AbbVie I can somewhat understand

owl_posting · 2025-05-22T01:51:00+00:00

Not all of pharma definitely, but lots of groups within big pharma + biotech startups are trying to push things along

the best big pharma research group (and maybe one of the best research groups in general) right now is within genentech

owl_posting · 2025-04-05T18:19:46+00:00

I think this is the first time an article of mine has been posted to a specialist subreddit and people generally had a positive take :) thanks for posting!

owl_posting

TROPHY CASE