Brian, thanks for speaking at the university conference.
Balji, it's my pleasure. I love being here.
Awesome. All right so last year you came
by at the opening of network school on the very first day.
Thank you for coming to the ribbon cutting and grand
opening. This year we've moved very far.
We've built a lot of stuff. We've had, you know, more than
1000 people have come and really on our way towards building
network school and startup societies.
And you've also come a long way. Blueprint has has come very far.
It's become a global movement. Don't die in Blueprint.
We actually have Blueprint bars, as you know, at NS and all the
blueprint kind of stuff. What is the what's the summary
of the last year few years? Give give the give Brian
O'Brien. And then I want to talk about
the longevity network scene. It was initially an intrigue.
When this went viral a couple years ago, it was kind of like
what is happening. There was the tsunami of hate
and then it went into this quasi curiosity mode of what is this?
Is this real? Is this sketch?
And then there's been this gradual acceptance, like
actually it's legitimate and it's interesting.
The hate has tapered off substantially and now it's
really gone into a movement. I'd say then the Netflix
documentary was out in January that had a a deep global impact.
And so now over the past, I'd say maybe 5 to 6 months, I'm now
with some of the most powerful and influential people in the
entire world. It's just been this, this really
remarkable trajectory towards credibility where I mean,
yesterday I was with, well, I wouldn't say, I won't say who I
was with, but like some of those powerful people in the world
working on health and Wellness protocols and whatnot.
So it's just been interesting to go from what is this to now like
deeply engaged in in the world order.
So that's been, it's a fun, been a fun trajectory, very
unexpected. That's amazing.
So you know what I would say, and I will propose this to you
and maybe maybe you'd agree, maybe you won't, but let's
discuss. I actually think the Don't Die
network state is actually the key to both.
And the reason I say that is I think the primary barrier to
longevity and more generally transformative biomedicine is
the American regulatory state and more generally the American
healthcare apparatus and how it only treats people when sick.
And it acknowledges that death is or thinks death is notable.
And also we get almost no news about the incredible
developments that have happened in academic biomedicine in terms
of reversing aging in mice or even in humans.
And there's some amazing phenotypes like, you know, I can
put this one on screen which shows two mice of the same age,
and the first one is balding and older and the second one is
clearly younger. Or here is like a side effect I
can put on screen of a couple of men who had a cancer drug and it
caused as a good side effect their hair to reverse color and
to go from Gray to less Gray. And you've probably seen
actually, are there other examples you've seen that are
like that, that have these amazing visual undeniable
effects within humans or animals?
Yeah, I mean, many, there was a study out in June from a bunch
of Chinese researchers who put over the over expression of FOXO
3 and they packaged it up in a messing common stem cell that
people are doing interesting experiments that have measurable
impacts. You could read them out or you
can visually see them. And I agree with your framework
that when you seeing is believing that a lot of people,
I mean apology. I think your point is correct
that when I started doing this years ago, I tried to achieve
the best biomarkers of anywhere in the world.
Like that was like a way to say there's a healthiest person in
the world, there's a richest, fastest, can there be the
healthiest? And what I learned is nobody
cares about biomarkers. They just wanted to look at skin
and face. And, you know, and so I had been
on this deeply caloric restriction diet, and I'd lost
so much fat in my face. I hadn't really paid attention
to aesthetics. And people could not see the
project when my face was gaunt. And so it's remarkable that I
agreed that people understand longevity basically through the
face. And So what they see, they can
believe. Or hair, But that really is, I
think, the entry point for most people in understanding what is
aging. Do therapies work?
If you can't see it there, they don't believe it.
That's right. And I think there is some sort
of meta logic to that because for many people, longevity is
about aesthetics and you know, people wanting to look younger
and you know, if they had the trade off between looking
younger and actually in a sense biologically being younger, some
fraction, but actually even take the first over the second or
what have you, right? But I think it's almost like the
entry point. It's a little bit like, you
know, with with cryptocurrency, people seeing was believing
because it generated transformative wealth and then
they paid attention to the theory underneath.
And so if with longevity we can generate transformative health,
then we'll get people to pay attention to the theory
underneath. So what are the top three or
five? You mentioned the fox O
overexpression, Fox O3 overexpression, right?
Was it Fox O or Fox P? Fox O3.
OK, give me like 3-4 five other. What are what are your top ones
that have like a visual phenotype that you think is
really impressive? Yeah, I mean, sadly, I would say
there's probably, honestly, there's skin therapies, I'd say
hyperbaric oxygen therapy and then just the cumulative effects
of good sleep, exercise and nutrition.
Those are the ones that aesthetically work the best.
Of course you can. Go ahead, go ahead.
That's on humans. So what about on mice?
What about on animals, where we can do a lot more in terms of
genetic manipulation? Yeah, I mean on mice, I, I guess
I've seen enough of these studies where it seems like you
can generate really compelling effects on mice in many
different ways. And this is seen with caloric
restriction, it's seen with rapamycin, it's seen with
metformin. So I in some regards that the
the bar is lower on mice visual outcomes because there's plenty,
there's a, there's a lot of them with humans, I think it's much
harder. Interesting.
So why do you think that is? Do you think that the effect is
there in humans but it's not as visible?
Or do you think it doesn't translate from muscle musculus
to Homo sapiens? Yeah, it's a good question.
It reminds me of anyone, anyone who's selling the skin cream
basically shows the same, you know, 4812 week transformation
of a light wrinkle line to a, you know, a smooth wrinkle line
or something like that. It's kind of the same with, with
my studies. If you, if you see enough of
these, you kind of like have a general pattern of like roughly
what you show in the mice, whether it's a, a biopsy or
whether it's hair growth or something like that.
So I mean, I guess I I do, there's credibility to it, but I
also take with a grid of a grain of assault of, you know, there's
translation issues from from mice to humans.
But yeah, really, I mean, I think mice, mice are compelling.
Humans ultimately respond most strongly to other human faces.
Interesting. Yeah.
So I mean some of the large effect size things that have
been done in mice, obviously there's the GFP mouse where you
can make a mouse glow in the dark by taking green fluorescent
protein. You can, you have like a
myostatinol mouse where you can make them like incredibly
muscular and there's various treatments that can do that.
And there are all kinds of knockout mice and gently altered
mice that do, you know, crazy things.
And the, you know, my view is it should be possible.
There's also like the Doogie mouse, I don't know if you know
this, by Joe Shen more than 20 years ago, where they made the
mice smarter and they seem to be able to run mazes faster, right?
So my view is that we are finally, after more than 80
years exiting the FDA era where the focus was on minimizing side
effect size and finally re entering the era of large effect
sized drugs that may actually have more side effects but also
have larger effects like Ozempic, which you don't need
to. I mean, of course they need to
do studies to determine whether Ozempic work, but people don't
need to see whether Ozempic works like they don't need to
like squint and be like, you know, did it work or not?
It's a it's just such a visible effect that it's like caffeine
does it, does it wake you up? You can take it and it's like
end of 1. You know, it works, right?
So all the GLP ones, that's the new era.
We're back to the era of the wonder drugs potentially.
So why don't we have Ozempic for cognition?
Why don't we have Ozempic for longevity, Ozempic for muscle
mass? We should, we will, we could
maybe right, if we take all of these things that we think work
in humans or like mice or human adjacent mammals or perhaps like
for example Alzheimer's drugs have a neuroprotective effect,
but they also have a neuro enhancing effect, many of them,
right, like drug repurposing. And so my thought is A, we have
all of these interventions on this side which have these
amazing visual phenotypes, and then B, we have all these
jurisdictions on this side. And So what I want to do is
offer $1,000,000 longevity prize for the people who take these
visual interventions and carry it all the way through to
actually have them legal in these jurisdictions.
And when I say legal and functional, they should have a
paper at least on archive, the documents, everything, all data,
open source, open state. And they should have a law there
that allows them to do it. Ideally, there's some government
official who's even welcoming it in in the area and there's 190
countries and a lot of them are doing interesting things in
crypto and now they can do interesting things in bio.
Let me know your thoughts. I, I agree with you entirely.
The, the thing that we get people most excited is when they
see visual effects by far. And when you do a comparison and
contrast to when we talk about machine intelligence, we talk
about orders of magnitude of scaling of efficiency.
When you talk about human effects, you're saying 10%,
fifty percent, 20%. It's such a disparity between
the caabilities we have in improving our machines and
intelligence and what we can do with human lifespan, healthspan,
ability. And so the question is, and I
think what you're getting at the heart of it is what is the
system to create larger effect sizes?
And so we see, for example, like what's with the GLP ones that is
potentially the first mainstream longevity drug where now it's,
it's well, it's characterized well enough where you're seeing
cognition benefits, you're seeing, I mean, you're seeing
all sorts of benefits out, I mean, in addition to weight
loss. And you know, most people, I
mean, I, I am micro dosing that now myself, even though I have
no need to lose weight, I can basically try to achieve a dose
where I can achieve some of the health benefits.
But that that has very compelling, it's a very
compelling offering. You know, it's a very simple
drug. And so I think you're right is
if we can train people's attention to jurisdictions where
you can actually move this thing forward, because it's very, very
hard to innovate in the United States.
It's burdensome, it's complicated.
And and of course it's not without, it's without reason,
right? Like they, they are trying to
make things safe, but just over time, the bureaucracy owns the
situation. It just becomes a paralysis
state. So it's the same situation we
have with China, where China is racing forward on energy and AI
and a bunch of other things, and the US is having a difficult
time because we have this large regulatory state that slows
things down. So I think it's on point.
Awesome. So you know, I might, I want to
discuss the whether they make people safe or not.
But let's say we do $1,000,000 longevity prize will and let's
say we get to work. Will you come with me and talk
to the the people there and, and maybe try it out if it's real?
Yes, absolutely. I mean, we are looking for safe
efficacious therapies that have large effect sizes and that's
just it's really limiting right now in the field.
Amazing. And The thing is Type 1 meaning
just testing safety is actually very inexpensive.
It's Type 2, which is testing quote efficacy that's much more
expensive. And just determining whether
something is safe, you could have a totally different drug
regime that just tested for safety.
And there's a lot of things you can do by the way, with like
potentially patient derived organoids where you've got like
a proxy for the human that you're testing the drug on
beforehand. You could do much more with
pharmacogenomics, you know, pharm GKB and various kinds of
resources. If everybody had a genome
sequence, you could at least see whether you know, for example,
your warfarin dose is dependent on VKRC one and C by two A9.
And so you could see what your dose was before taking the drug.
You could look at relatives and what their dosage was.
You could look at people who are distant familiar relatives if
you had genomic databases and what their response was.
So much we can do with technology in terms of just
quickly checking whether something is safe and then
willing, willing buyer, willing seller, right?
Like a like a minimal necessary regulation, right?
And you know, this brings me, you know, when you said whether
or not they care about safety, it's a little bit like saying
the TSA cares about safety. Do they really, you know,
because it's, I mean, that's, that's the benign way of looking
at it, right? And the other way of looking at
it, they just care about optics. And so they're not optimizing,
for example, type one versus type 2 errors and the
sensitivity and specificity, the false positive, false negative.
Alex Tabrock and others that you know, marginal revolution have
written about drug lag, which is if you have a drug that was
approved but it was delayed by lit six years by the FDA, then
all of the incremental, you know, morbidity and mortality
over that window is directly attributable to FDA.
Because the bio medicine was the same at the time that that new
drug application that NDA was submitted, right.
It's not the dry medicine change that the approval time was so
long that it slowed it down. It was literally just pure
information in a sense that they were getting over that time
period. And so that is the unseen.
You know, one of the things I thought about is running a
Google ad campaign at some point to find somebody who's who had a
sibling or a, or a relative or, you know, parent that had passed
away of some condition during this period.
And, and say, well, did you know that six years later a drug was
approved that would have saved them and then talk to them.
And that's a way that you could actually make drug lag visible,
you know, on the screen, right. That's like one example of how
quote safety often is actually unsafe because it's so risk
averse that it's reward averse. Let me know your thoughts.
Yeah, I mean, yes. And that statement, if you think
about the, the way we do things, and I actually globally, I was
going to say the US, but people, we allow people to experiment
with fast food and a lot of sugar.
And right, like you, you are, you have the freedom to kill
yourself and to experiment. Does fried food cause me to age
and potentially develop disease and lead to my lifetime?
So you have the freedom to do that.
But if you want to try to experiment, to do something good
for yourself, you can't, it's against the law.
And so it's really backwards in that if you try to step on
anyone's ability to sell anything that causes someone to
die, you know, people are are are upset, but yet we can't get
the system to move so that we can self experiment on things
that could help us. Now, clearly there's going to be
complicated outcomes. It's not the case that people
are going to make good decisions, but that's just
humans. So it really is backwards that
and I think it's really a stifling factor on our ability
to make any progress. Whereas like when you look at
computation, it's just like anything that produces better
compute or intelligence go like very little guardrails.
So it's really a constraining thing for us humans.
That's right. I mean, The thing is, as I said
before, and you probably also observed, you can go bungee
jumping, you can go skydiving. Euthanasia is even legal in many
states, right? Like you could join the
military. There's many different contexts
in which you're allowed to take a very serious risk of dying,
right? And with essentially no upside
when it's bungee up or skydiving, it's just pure
thrills. I mean, fine, right?
So why can't you take a risk of taking a new new drug or device
or something like that that could improve your life, right?
Why is why is human self improvement of all things, the
thing which is stopped, right? And it's always framed as
protecting you from yourself. But what if you had better
information? You know, for, for example, the
FDA doesn't really like it's a circle phase 4, you know, like
post market surveillance. It doesn't include real time
reviews from hundreds of countries or like, you know,
hundreds of jurisdictions. Like, whereas even like Reddit
reviews do the upvotes on Reddit or whatever are drawn from
around the world. So you can, like, Crowdsource
all of this data from around the world because biology remains
the same. And that kind of, you know,
because it's locked at the low estate rather than the level of
network, you know, like, like an Uber rider, their rating, the
sourcing information from New York City and when they take a
ride in London and so and so forth.
But drug responses aren't for people of similar biology around
the world. They're not centrally pulled
together. And they could be.
Yeah. Yeah, I mean that the some of
the risks like the GLP ones for example like blindness, I think
there's like 3000 plus lawsuits against the GLP one manufacturer
right now. But you can, you can take
precautions by getting your genome sequenced and see if you
are at risk for those kinds of conditions.
So like you're saying, you can do really basic inexpensive
tests to see if you are a responder, non responder or a
higher risk for these outcomes. And now that our testing is
getting so cheap, is this a really great path where if, if,
if the, if the regulatory structure says, hey, this is too
complicated and too high risk. I mean, you could even offset
that and say you, you, you can characterize yourself much
better to lower that risk. So, I mean, it really is.
It's very hard to justify the argument that that we should be
as limited as we are. That's right.
And now, so let's say there's three treatments which assume
you had a friendly regulator, OK, somebody who, and crucially
by the way, people would sign something that's similar to like
being a test pilot because no plane crashes, no planes, no
train crashes, no trains, right? If there were people who are
willing to take the risk of a plane crash, you never have
transatlantic flight, you never have flight at all in the 1st
place, right? And there were a lot of plane
crashes early on because people are figuring it out, right?
And we could think of those people as heroes.
So let's assume there was some jurisdiction where it had a
crypto like attitude like you know where if it's willing by or
you're signing all your stuff away, you recognize you're
taking a risk, you're an adult and blah, blah, you're being
appropriately informed, compensated, whatever.
The thing is, what are the three most promising treatments that
we should look at that will have large visual effect size?
I mean, if you look at the evidence on what has worked,
it's been gene therapy, cell therapy, you know, at the very
top and then yeah, lifestyles thing.
So probably gene therapy, cell therapy.
What about? Parabiosis, for example.
I'm not sure it's going to have the effect size that was big
enough. Because I've seen varying
studies on that. You've probably looked at it
more closely. Yeah, I mean, so I did this with
my father. I also did several of the
treatments. Now you can do the pheresis
without a donor and just replacing all of your plasma
with with albumin. People are now generating the
synthetic plasma for the replacement.
So I think it has some promise, but I don't think it's ever
going to have the effect size that a cell therapy or gene
therapy would have. OK, I we'll see what we'll see
the data comes out, but my guess is that gene therapy, self
therapies will will be the biggest ones and also and also
the OS case stuff. OK, All right, so gene therapy,
cell therapy, OS K All right, so let's go in order gene therapy,
which genes? What looks interesting?
I mean, the ones that people been playing with like
Telomerase or Klotho, Fox O3, full of statin, I mean those are
the ones that mostly have been top of charts, but people are
working on several others. I mean, now that it's really a
fascinating field where it is emergent in that we're looking
at much more underappreciated genes that we have been before.
So yeah, this is like probably like endless and it's just the
case. We haven't been able to
characterize these things very well to line them up and say I
mean like for example, when you look at what the new limit, so
Brian Armstrong and Blake Byers built stood up new limit.
When you look at what they've done with the transcription
factors, like basically saying like what, what changes things
inside the body, they turned it into a computational problem.
Whereas before when you're screening like what are the
combinations? It's a very hard problem because
the combinatorial set is so large.
And so now that they they, they took a, a tech approach to a, a
biological problem and they laid.
Transcription factor binding sites.
Exactly. And they'd be doing so much
progress in in making it a computational problem versus
what people are doing before a much slower academic cloud
approach. So I think.
Yeah, I think, I think, I think some combination can work.
The problem is that what you do in silico and to be clear, I
like new limit and it's great, but some compliment of those
because the in silico approach will also have often false
positives and false it depends on how specific that situation
factor binding site kind of thing is.
But I think I think there's definitely promise to to
combining both. Go ahead.
I'm imagining that it's probably just an intuition building
process that even if there is some false positives in your,
you have some degree of accuracy where you can entirely get there
still. It's just this like, how do you
how do you take this insanely large problem, make a somewhat
approachable and have a more sophisticated like iteration
speed? So I think if you look at their,
their progress for the past couple years, that's what I
think is probably the potential for gene therapy.
You know, people are looking at things like can we do the four
hour sleep gene, for example, right?
Which is like very appealing. You get more time in life.
So I think there's a pretty long list of things people start
trying to knock off. So let's let's go through.
So let's just talk about that for a second.
Less sleep, right? Less fat, you know, or less
weight, OK, like Ozempic, but gene therapy, Ozempic, more
muscle, right? Maybe faster healing perhaps for
a lot of things that's, that's helpful.
Perhaps, you know, like reversing graying of hair.
I mean, I, I actually, I actually think it looks a little
distinguished, but that's fine. You know, a lot of the skin
stuff like wrinkles and and so on and so forth.
What are the other upgrades that you think are interesting?
Go ahead. Cognition, Right Intelligence.
Cognition, of course. Right.
Yeah. And and actually that.
Could take several forms because there's like spatial rotation,
this musical ability, right? Also, I think sight hearing, you
know? Yeah, yeah.
I mean, I, I recently discovered, I mean, over the
past couple years, I've got mild to moderate hearing loss from
listening to loud music too loud as a kid and also shooting guns.
And that leads to dementia. A gun guy, I would never have
thought. That honestly, yeah, yeah.
I mean, we grew up with guns. Like it was like an omnipresent
thing in our lives. We just everyone had guns and we
were. We're all shooting them all the
time. But yeah, so we.
Yeah, I basically, I have. I discovered this.
I didn't realize I had any deficiencies until I got the
test. And so now I'm going to get a
hearing aid because there's evidence that it can lead to
dementia. I'm guessing most Americans,
most people in the world probably have hearing loss.
Our modern day world was not built for our ears.
Like concerts, like 120 decibels damage starts happening over
about 90. So we just, we have way too many
loud noises, ambulances, etcetera.
So but yeah, hearing and gene therapy, we've been wanting to
find a gene therapy because I would love to be able to fix my
hearing. There's a few groups who've
tried it, who've been playing around, but there's nothing even
close. So that's what I'm saying.
This is so promising is once you if we actually can figure out
how to efficiently do gene therapies and do them in a state
that allows rapid iteration and we can try these things and we
can pass some safety threshold, then I think it really could be
this like this new era of how we think about ourselves entirely.
That's right. Because I think gene therapy,
what's interesting about it is it blurs the difference between,
I mean, biochemistry and genetics are very closely
related, as you know, you know, because you'll have a compound
and then there's like, like some small molecule and it will
trigger like a protein will bind to it and that protein will then
bind to the genome and unlock mRNA that'll do other things.
So biochemistry and jigs are, are, are tightly related.
And one of the things I've observed is that many of these
things people are fine with solving them at the biochemical
level. Like for example, caffeine does
make you smarter, right? Or, you know, people are OK with
chemistry to dye their hair blonde, for example.
They're like, Oh my God, you can't solve at the genetic
level. Or actually, another example is
they're OK with solving at the surgical level.
So for example, height, it's OK to take HGH, which is a
biochemical solution, and it's OK people do a very painful
thing of limb lengthening, which is a surgical solution.
But the genetic solution, Oh my God, right.
And because they just have this weird, you know, hang ups, they
don't actually understand the distinction or the relationship
between biochemistry and genetics and how close they are.
And you can do that for all kinds of traits.
Surgical and biochemical are OK and genetic is Oh my God, right.
But gene therapy is actually something that's more like
biochemistry because it's an injection or whether it's an
injection or something similar to that depends on the mentality
of it. But it has, it's like it feels
to people like a drug because on somebody who's already living,
but it changes them in an upgraded way, right?
And it's actually been starting to work for people who had
sickle cell and other things. You can put that on the screen,
right? So, OK, so there's gene therapy,
right? And then let's talk about cell
therapy. What should we?
Look at, I mean, there's a, we've been trying to get access
to cell therapies for years and it's never been possible because
they're just too high risk. So we're, there's some attempts
at doing this with mesenchymal stem cell therapies, you know,
stem cell therapies. We have not yet seen a lot of
success with these. We don't see a lot of good
evidence, you know, as as one approach, whether it's from your
body or someone else's body. But there's some of the more
advanced things to, to change more sophisticated by pathways
in the body that just don't have good pathways.
Like it's just a very hard drug to get approved and there hasn't
been good, good ones to like. It's a very hard development
path. You know, an interesting
question that occurs to me is depending on what age these
treatments would be effective. For example, let's say you've
got a car and you, you hit the brakes and you hit them hard
enough and it doesn't crash into the wall, right?
There's a, there's a point of no return by which if you hit the
brakes, it doesn't matter. You're still smashing into the
wall, right? But that's just a thought
experiment. You might actually from the
ranks of older people or people who for a reason are pursuing
euthanasia, especially the people who are pursuing
euthanasia in places like Canada or whatever, right?
You might say to them, why not try one of these treatments?
Because if you're if, you're going to die, right?
Like like can't like can't like hard teeth therapies for cancer.
Exactly. That's right.
Just like, you know, for example, with this a novel
argument that strikes me that similar to the ACT UP argument
that was made in the late 80s, early 90s that finally
liberalized the FDA after many decades.
Basically a lot of people who had HIV said we're going to die,
so why don't you approve AZT and these other things so at least
we've got a fighting shot. You know, Dallas Buyers Club
documented that, right? So it strikes me that a
potential extension of that would be, given that there's
millions and millions of senior citizens out there, right?
Those who were like, you know what, might as well give it a
shot towards the end. Now, the tricky part about that
is in that car analogy, they might be close enough to the
wall that even if the treatment worked, it couldn't reverse it,
but maybe it could, I don't know, it's case by case kind of
thing to figure out, you know, maybe it's a powerful enough
thing that just rewinds it. One of the things I know you
know this, but like that's always struck me and and many
others who have written about this is a relatively older
couple can have a child that is a newborn that, you know,
clearly there's something of regenerative in our in our
bodies that can birth again, right?
Like and so maybe that can be triggered even much later in
life than we think. Yeah, this is like Yamanaka
factors. Take an adult stem cell, you go
back to a pluripotent. So you make a 7 year old liver
young again. And of course, like now, people
are go ahead. Yeah, so, so with your biomarker
thing, you could gauge someone's life expectancy and if they've
got only five years to live, give them what you know.
Obviously they have to opt in, sign up all the stuff they've
only got a few years to live. Try it.
What's the loss exactly? I mean, that's The thing is the
the exciting thing is the technology is here.
Like we actually know we can turn an adult stem adult cell
into a pluripotent cell. Like legit age reversal.
Of course, now there's complications with, you know,
can you avoid it being cancerous?
Cancerous. Yes, of course.
Right. Can you avoid, you know, the
other off target outcomes? So like there's things we need
to sort through, but they the cool thing is in 2025, we now
know we can legitimately reverse age in a stunning way.
And This is why I think your sentiment is correct.
Apology where we're too damn slow.
I like, I, I don't, I don't know why we are not pursuing
longevity like we're pursuing artificial general intelligence.
You know, when I look at 2025 and I try to zoom out to the
perspective of the year 2500, either you're, you're working on
AGI or you're building don't die like everything ultimately build
up to like your existence or your shared existence with the
with AGI. And so I just don't know why it
doesn't have a similar level of fever pitch build around it.
I think, I think a big part of it is the stuff that I think
about a lot, which is the governance part, because you
need risk tolerant jurisdictions since and that's that's the
whole change in your way of thinking.
It's like, you know, as we've talked before, like you know,
the traditional financial system assumes you have some degree of
inflation every year and you lose some of your health.
One 2% inflation, lose some of your health every year.
The social medical system assumes you lose some of your
health every year, So you lose some of your wealth and you lose
some of your health. And so it's a paradigmatic
change. Even if crypto has bar charts
and, and, and graphs that look like the traditional financial
system, it's moral premises are fundamentally different.
Even if you or I will publish graphs that look like
traditional biomedical papers, the moral premises are totally
different because it says maybe we don't have to die.
Right. Yeah, that was that was our
first phone call. Like I think you called me.
Hey, Brian, I think we have the same philosophy.
I reject inflation and you reject death.
Yes, it's been gradual. That's like we we're after the
same concepts. That's right, because actually
it's and The thing is that wealth in a sense is accumulated
life force, right, because you're spending hours of your
conscious, highly productive time on accumulating wealth.
And so it's diluted from you. It's like you're spending
they're taking away your life. You know, there's this movie
called in Time by by Andrew Nichols that actually makes that
metaphor. It's like, you know, sci-fi
drama, but the concept is like, the currency is ours, right?
Like hours of your life were there, right?
Yeah, yeah, on I guess there's a side tangent on this biology.
I just finished his book Passion the Western Mind by Richard
Tarnas. And he he tries to go through
the major epochs of ideology and he starts with Plato and
Aristotle going through the Renaissance or going through
Christianity, medieval times, Renaissance, Enlightenment,
modern day, scientific era. And if you look at it from that
perspective of like a Ray Dalio principles perspective where you
zoom out, you say, hey, there's these like these big economic
cycles, reserve currency that they go through the same stuff
every time. It's we're really due for a
major ideological shift right now.
And I think you're on this, I'm on this, that it's not some
slight tweaks to the, to the continuum slightly.
It is like a wholesale change on scale with other major
ideological shifts. And I think what we're talking
about today is basically a part of that that is like this
unleashed want for health, right?
We don't. This is not about living
forever. It's not about transhumanism.
It's about we all appreciate waking up in the morning feeling
good. We don't like aches and pains.
We don't want to be diseased. We don't want to see our loved
ones die. It's about feeling great and
being great. And that that ideology is not
part of our zeitgeist. Like we just accept this slow
decay, death and decline. And it's like almost something
where you celebrate. It's like I'm living life by
slowly killing myself. Yeah.
Well, human self improvement is, I think the way that I think
about it, where that's a continuum from simply eating
right and doing better to hitting your genetic limits and
then surpassing them, right. And, you know, towards that end,
by the way, I think the influence of, let's call it
Dharmic and cynic thought on the world.
So, you know, for centuries, India and China, like Marco Polo
sought out India, That's Marco Polo sought out China.
And Columbus saw that India, that's actually how the Americas
discovered why Native Americans are called Indians, because
India was a large enough economic power, it wasn't
unified, but as it was worth sailing to and, and for Columbus
to do it. And so for, for the last few 100
years, India and China have basically been through their
equivalent of the dark ages. And now they're coming back.
And those two schools of thought have a different view on the
human body and they're they're they're less in the Abrahamic
school of thought is as kind of weird hang ups in certain ways
that the Chinese and Indian schools of thought are more
generally the Synic and Dharmic schools of thought don't.
And so like, for example, something I've thought a lot
about, I may have mentioned this to you, the concept of genomic
resurrection or reincarnation. Did we talk about that?
We did. Yeah, yeah, yeah.
So but explain it. You could get your DNA sequenced
and stored on on desk and we already can do chromosome
synthesis for eukaryotes like, you know, we could do it for
actually you could synthesize an entire prokaryotic chromosome
from disk and actually have that thing swim around in a test
tube. And as our abilities of
chromosome synthesis get better, you could have imagine just
projecting out to be able to do it for full complex human
chromosomes. And it's just, it's like a
technological direction. It's kind of like if sequencing
got better, synthesis will probably get better.
And it might take, you know, a few decades, but it'll get
there. Which means that if you have a
file, you could, if somebody was well behaved, you could write
their genome to a blockchain or something like that.
And if they had good karma, then the community would reincarnate
them 50 or 100 years hence or whenever chromosome synthesis
becomes feasible because they have the data there.
And you know, people argue the genome isn't everything, but
it's a lot. It'll get you a lot.
And then you could replay all their past life experiences for
them if you recorded it, and they would just be born with all
this amazing knowledge of everything that happened, you
know, And that's something where if someone was going in on one
of these missions where they're trying out this experimental
drug, you could sequence their genome and say, if it doesn't
work out, you'll be reincarnated with the knowledge that you had
in life and so on and so forth. And we'll kind of we'll look
after you in the next in the next life, right?
And so that's like a Dharmic inspired way of thinking about
it. And then the psych inspiration,
among other things, is just extreme pragmatism and just
experimenting with things. This is actually, you know, the,
the the western mindset used to also be like this Banting and
best. Do you know that story?
I don't. So Banting and best this
important story for you. You know like 19 if I get the
dates right. I think 1921 they started
experimentation on insulin supplementation.
Said hypothesis could treat diabetes and they tested it on
1st like dogs then and it worked and then they treated, you know,
they tried self experimentation and they went for patient
volunteers and those patients just like stood up in bed like
this. It was like the canonical bench
to bedside concept like a bubbling beaker.
You know, it's brought there and they iterated on formulation and
so on and I think you know right now it's so hard to go from like
pill to oral to an injection to a patch.
There's a whole process and whereas in some ways it's kind
of like going from web to a mobile client to like a command
line client, it's kind of the same drug but in different
formats or whatever. So they just did all that.
It wasn't case control studies. It wasn't, it was just
iteration, quick iteration and seeing it.
And it was a large. And by 1923 they had Eli Lilly
doing scale production of insulin for the entire North
American continent. They'd won the Nobel Prize.
And that was a time when pharma moved at the speed of software
where you went from my dear to execution and via iteration in
like 2 years. And one of the issues I think a
lot about is there's no case control studies on case control
studies. There's no regulatory science on
the regulator themselves. Why don't we have a jurisdiction
where you can just iterate your way to, you know, to something
we're, we're crucially, by the way, the patients aren't simply
patients are participants in their own health.
They're not like a row in a table like a very 20th century
study like Framingham or something like that.
That's just like a row in a table, right?
Whereas if it's a human being there and they've got a mobile
app and they can send you back what their experience of the
treatment is and they're an active participant in their own
health, it's totally different paradigm.
It's bi directional. And the very simplest version of
that is adaptive clinical trials, which show you can like
converge on an endpoint faster if you know you're not simply
doing in like a like a really dumb open loop, you know, trial
right where you're not. You're basically taking
information from the trial as it's going to to adjust things
so very shortly. But an adaptive clinical trials.
But I think you can do much better than that.
No, no software is designed with case control studies.
SpaceX wasn't designed with case control studies.
You know, I'm saying that there isn't some utility to them, but
they're really for teasing apart small effect sizes rather than
large effect sizes that are so manifest that they just jump out
at you. Yeah, this probably goes back to
the beginning of our conversation where if you have a
large visual effect size that gets everyone involved and if
you can, if you can do so in a jurisdiction to be like, hey,
you can go from idea, you know, in gene therapy, cell therapy or
something else. And I mean, I guess that's why
people are so interested in peptides is peptides are drugs,
right? Peptides give you a drug like
effect sizes. The problem is they're poor,
poorly characterized. There's questions about how
they're manufactured and did the quality of those things.
And then also you have a lot of off target effects.
So I mean, peptides are inherently A risky path when
you're not doing a well characterized path.
But yeah, I mean, this is if we could demonstrate some like one
or two wins of a process from a talented drug developer to a
actual thing that works that has a low safety profile, large
effect. Now, I guess like TBD, whether
we can see that because I mean, biology is complicated.
Maybe that's too big of an asking.
Maybe, you know, the GLP ones, they kind of hit that sweet spot
where it's the immediate visual effect of fat loss.
And it has all these follow on health benefits where even if
you're not obese or if you're not having an an eating problem,
they it. Gives you discipline.
Yeah, exactly. Yeah, yeah.
That reminds me of like in the future, like we talk about like
you and I have imagined what gene therapies we say hair,
skin, you know, muscles, etcetera.
But it might be fun to have a thought experiment of like what
would gene therapy be like in 30 years?
Like what kind of nuanced, expansive concepts would what do
we think about now? We we think about like designer
babies of like we're going to choose height and eye color, but
let's how are you doing some human experience?
Mini circle is interesting because they have the concept of
a plasmid that's reversible. You can turn it on and turn it
off, right? So almost like, you know, I have
some caffeine and I don't, right?
You could or you change your, you know, put on your contact
lenses or not. You know, biology is
complicated. There's all kinds of off target
stuff. It's not true.
You'll get it right. People's biology is different
and old. It's true.
But there's something cool that you're of a very specific target
that can flip on and off a protein that can add or delete a
function, right? And Patrick Friedman, I think,
had that therapy and he showed his, this is a mini circle, you
know, which is doing the plasmid.
So Patrick Friedman and Farb Navy both had the therapy and
Patrick said that he was just crushing it with his VO2 Max.
Farb also said the same thing, right?
And that's something where it's end of one, but they know their
own body better than anybody else.
It's end of one, but it's over. It's it's a lot of variables.
Which end of 1. You know, Mike Snyder's thing on
this from many years ago. The we're talking about Mike
Snyder's prophet Stanford. And he, yeah, the intergrome,
right? He just took every possible
thing from expression to the rest and just ran on himself.
And he's able to, for example, see himself getting sick in the
gene expression data like a few days before he actually got
sick. Right, exactly.
And so we could with better metrics.
That's another piece of this actually, diagnostics are non
invasive, right? So if you had constant like
whole, you know, like like all 30,000 odd or 22,500 whatever,
you know, a human gene expression panel and you track
that and maybe you know, metabolomics and so on.
You did something like the Mike Snyder intergrome while you're
giving people this gene therapy or self, but you just got a much
richer readout, you know, from them right now.
You're not just relying on self report.
You know, it is it's like your biomarker stuff, obviously, but
it's just like, you know, we're getting 10s of thousands of
them. That seems like, you know,
something that is very feasible because costs are coming down of
all that sequencing and so on. That'd be a very good thing to
do. Like an inch groan like thing
that's like a time series inch groan.
First you get whatever data points on them to determine
healthy, then you impose A stimulus, and then you look in
state space and you see is it actually changing anything or
not and what's a change? Yeah, that's exactly what I'm
doing at Blueprint. So we are going to try to do for
five, we guess we've done that for myself.
Like when you build an ASIC, you know, if you ever haven't, if
you have not built an ASIC, it's really cool that if you like get
a picture and zoom in, zoom in, zoom in, zoom in, zoom in, you
find that it's like down to the nano level of like granularity.
It's beautiful. It's amazing we can design these
structures. It's crazy, yes.
It's crazy. And The thing is you can
characterize this at every level, every circuit design you
can characterize. You can say what happens then I
do this and and it's like we can characterize our machines and
our intelligent machines so well from the circuit all the way up
to the application layer. We can characterize the entire
stack, the servers they run on the energy.
Whereas in human biology we can't characterize.
You can get like a really high level of like, what does my
blood draw say, right, Like my cholesterol or my my liver
enzymes. But you can't get down and
characterize these, these these smaller molecular interactions,
which like you're saying, they read out really important data.
Am I getting sick? Am I showing signs of disease?
Am I responsive to this drug or not?
In what ways? It's like if we can pair the
characterization with these jurisdictions with good drug
developers, like that's your path.
I mean, and then we could open up and once people get like a a
few successes, we'll say, huh, like this is a thing.
We can, we can actually do it. I was talking to Jason Kelly the
other day. He's founder of Ginkgo Bioworks.
Yeah, I was, I was first. Yeah, exactly.
I was first money in. And they, they really led the
charge for biotech in industrial, industrial
applications. It was a really great moment.
They've run into some roadblocks and doing it, which like, you
know, breaks my heart because there's nothing I want to see
more than biotech in the industrial world, like really
smart biotech designs. And we are saying today like we
we're talking about doing something together and we both
just like, why can't we build human with the same fever pitch?
We build tech like why, Like why can't we chase this thing?
They're just, it's so frustrating.
That it boils down to risk tolerance.
And the reason is with tech we can have crashes because when
crashes and the computer crashes and crashes all the time, it's
like acceptable to fail, right? With humans, people get really
mad if there's a failure, right? They are, you know, but but they
didn't used to with Bantic and best in that era, people were
more reward seeking and less risk averse, right.
And I think we're kind of coming back to that era gradually where
risk tolerance has radically increased over society over the
last few decades. I think.
And you know, one thing on this is an intermediate between
though, maybe we can just go to the full thing.
I think just the diagnostic zone, right, where you can just
get get genome sequence without a prescription from your doctor.
It's so stupid. The entire FDA, you know, CDRH
thing where it's like requiring a prescription to look at the
mirror. Like why should you need a why?
Why should that be bottleneck through the medical system to
get to get your genome sequence? When when the AI models are
smarter than my doctor like why do I have to go ask them?
Exactly. That's right.
So I think there is definitely room for something where you get
your GM sequenced by, for example, Nucleus or some at home
kind of device, you know, like as Oxford Nanopore or something
like that gets smaller and smaller eventually get there.
Or you just do in the lab and you just get the file back and
you have it interpreted by something like an open source
version of Prometheus. And then but but it's an AI
enabled thing and it's all done locally.
And so I've got some companies that I'm looking at that do some
combination of these things. But you know, I think the second
generation of truly personal genomics could be another big
thing that we do. And maybe that's the
intermediate step, that then people have enough data and
enough time series on themselves that then that opens up.
Basically, the reason that's interesting is now you're not
flying blind every you have a sense of your own dashboard and
your own metrics. Like you're one of the very
first on this. Actually, there's that guy, the
measured man. There's the article in the
Atlantic many years ago on this guy.
He's a prophet. Forget his name.
You should maybe meet him if you haven't.
It's back with the Atlantic was good.
But the so the this guy also is measuring all kinds of time
points on himself and he and he found he was like an early
quantified self kind of person, right.
So if you have that dashboard now you have a sense of kind of
what's the speed bump? What's a real major thing?
And then you're kind of better able to process what an
intervention is doing. Is it messing you up?
It's just moving these genes, that kind of thing like these
expression levels etcetera. Do you actually in your all your
bio maker stuff, have you done gene expression time series on
yourself? By the way, his name is Larry
Smarr. That's him.
Yeah, that's the guy. I've never met him.
When was this done? Do you know him?
I don't know if I just know him from the I think Larry Smarr,
Mike Snyder and you should do if you want, we should all do a
podcast together or something because you know, but.
That's a good idea. Those those two people are very
aligned with our way of thinking.
Yeah, So he's a founder of the National Center for
Supercomputing Applications at NASA, born in 1948.
So he's a. Yeah, so he's 80 or something
now, maybe. I'm not sure what health he's
in, but him and Mike Snyder are both pioneers in this space.
Mike Snyder with the intergrome, Larry Smarr, Right.
And I think it's worth, I bet, by the way, if you put that into
AIAI is very good at expanding suggestion lists.
So if you put both of those there and say who else is like
that, you'll come up, but maybe others will come up too.
Yeah, he found early Crohn's disease in himself before his
clinically diagnosed. I mean, this is like, so I have
kernel on my desk here. This is this is the brain
interface I built. I measure my brain every day
now. I'll show you.
Yeah. So this is like characterization
the brain like you can start. You can see the inside here
maybe. Yeah.
So he said like we did. We we spent seven years building
this technology. It's basically wearable fMRI
using light, using light. And this is the problem is we've
never had the ability to characterize our brains.
Like if you want a brain scan, if you do FM RI or you can MRI,
FM RI is a functional side, MRI is a structural side, but just a
go to facility sitting there in an environment that's
claustrophobic. But now I can basically
characterize my brain every day looking at the functional
networks. You know, I have a I my
intuition, by the way, does that need to be, can you walk around
with that or is it have to be plugged into the wall?
Yeah, yeah, it, it's a stationary.
It's stationary. You know, a fun test would be
what does it look like when someone is just scrolling versus
what does it look like when they're on the treadmill?
Yes, exactly. And like I didn't do this but my
my colleague did. He drank alcohol for science and
he saw an immediate aging of his brain.
I think it was two to three years.
The following day. We it's been cool to just see
basic correlations. What happens when you're sleep
deprived? What happens when you exercise?
What happens you eat? Well, like you can run all these
experiments now or I couldn't before, but this is like the
characterization thing. This, the characterization thing
is what we've been missing is people run to do therapies and
even when they do therapies, it's poor care, poorly
characterized. It's.
Very, let it be characterized. Let alone before, like having
something like you're saying some time series longitudinal
data looking at these things, which is I've, you know, I've
become the most characterized person human in history.
There's no human that has, it's more characterized than myself.
And so we have, it's enabled us to find so many insights that we
just haven't been able to find in the literature or through
other observations through doctors.
It's just like it's it's all about measurement.
And what is what is the cost per day of your characterization by
the way, like what, what acids are you running?
Honestly, it's not that expensive.
These are like, I mean blood draws, saliva, stool,
mitochondria, fitness tests, imaging, methylation,
proteomics. You're like, I don't know.
She's like not honestly, probably I'm guessing without
thinking about this more robustly, but something like
50,100 thousand a year. Like not, it's not that much.
It's like 1000 a day and so if we could bring that down to 10
bucks a day. Or.
Even 1000 a month? Yes, exactly right.
Actually it's less than 1000 a day.
If you're saying 100, if you're saying 100 KA year, right, then
it's somewhere between 2:00. It's like 203 hundred a day,
right? It's already not too bad for
what it is, right? So it's like, you know, the
$1000 genome. There's, there's, I mean, I've
run a clinical lab. There's definitely returns on
scale with clinical lab for all kinds of stuff with
instrumentation to reagents to everything.
So I've thought about a residential clinical lab where
we just build it into network school and because it's a pain
to go and you know, you want is a phlebotomist to come to you,
right? You want mobile phlebotomy, you
want saliva, you want ideally even in in your apartment or
something like that. You can just leave your
toothbrush or something like that.
And then it can just, you know, you spend in a cup or something.
And then there's various ways of probably streamlining, if not
fully automating something, make it easier to get samples.
I. Have a sensor in my toilet.
Yeah, exactly that. Kind of automatically, yeah.
Bill Gates was interested in this 20 years ago and you could,
you know, like you're in color imagery and so on and so forth.
There's a lot you can, you can do with that and you just have
it there and, and might maybe, you know, you just image it and
so on and so forth. I think the Chinese could do a
lot here because they they can innovate on hardware and, and
there's something to be done here because they're building a
lot of cities. So they could actually install
these smart toilets. Some kind of Chinese, Japanese
companies. The Japanese also do a lot of
toilets. Yeah, I just watched that South
Park episode where they got the Japanese toilet.
Anyways, yeah, this is it's also the the characterization thing
is really cool because, you know, I when I started
Blueprint, I was trying to solve my own problem.
Like, how do I actually find nutritious food that's third
party tested and low on toxins? And then friends and family are
like, hey, can I have access? I'm like, sure, here we go.
And it just like accidentally became a business.
But the problem with that is like, even though I'm trying to
solve a real problem in life, people have such a negative
connotation towards therapies, like towards things you actually
like. It's complicated.
The characterization is much more friendly, right?
If you're helping someone measure themselves, there's much
less blowback. And so I'm moving very hard in
that direction where I'm going to help people characterize
themselves. Yeah, just characterize yourself
like me. Like, let's just like, get this
based on measurement. It's a much safer path to build
because then people somehow they don't have suspicions like
they're doing me now, but like really I'm like, I don't like, I
don't want to be doing this like like I there's so many like if I
were to out to make money, there's like 1000 other ways I
want to do to make money. So anyway, yeah, so.
The thing is actually, you know, years ago.
That's why, you know, my first company was in diagnostics,
because also diagnostics has a lot of advantages.
First is it's half computer science because after you do the
assay, then you can analyze everything on the computer and
you can make all the dashboards and so on.
So it's like at least half within our bailiwick.
It can't hurt the person usually.
So the risk is way, way, way lower.
So you can move much faster. You know, the worst thing you
can do is you can give them a wrong result, but you can move
close to speed of computer science.
And then most interestingly, it means that the intervention is
informed. So arguably diagnostics creates
a room for therapeutics. So perhaps, yeah, we start with
the quote, you know, the universal longitudinal
diagnostic network state, first longitudinal longitudinal
network state, then longevity network state.
Cool. I like this.
So basically we get a cohort of people together, we say we are
going to invest the capital to do high fidelity
characterization. I love this.
We don't, we don't know why, right?
We don't know to what end. My standard integral for 100 or
1000 people. Yeah.
Now it, and it may not be useful to be this characterized for
five years, 10 years, like we don't know.
But like we want this longitudinal characterization so
that when we find things to to trial, we have this time series
longitudinal data that we can, yeah, that gives us a better
shot identifying what therapies are going to what we'll be
responsive to, what we won't be and then see the off target
effects. And so probably a much better
way. Whereas right now evenly when
you look at the clinical trials, they are so poorly
characterized. It's clearly like I read this
one. Scalar variable on a very
complicated human. I read these studies.
I'm just like, this is not reliable data.
Like when you're telling me it does blank and blank and it has
these side effects like sure, like nothing close to what I
would think could be. So even this way.
That's why like the GLP ones are a good one because like they
have them good characterization better than than like, you know,
a, a non characterized peptide. But that said, like we don't
know a lot, which is why like all this stuff is coming out
like blindness and stuff like that.
So yeah, we really, I guess like this conversations land just on
characterization as a key input. But then we need to go to these
jurisdictions to figure out with that how we leverage fast track,
safe, high effect size therapies because we need a like we need a
moment in for longevity. We need something, yeah.
What you saying? Like it could be the case that
it's like, you know, the history book says, you know, from like
2025 to the 2035, these new therapies came out and I had
this like started this cubit of effect or there's like a moment
where something happens, maybe the GLP ones that story of like
people are familiar with doing these.
They're important. They are but but but but we
could have the azempic for aging would be that moment.
Yeah, like something something pretty, but that the effect size
is big enough where everybody turns their head and they're
like, I understand reality differently now because of that.
Yes, that's right. And I think I do think that's
possible simply because we're seeing it in mice and so on.
We just got to figure out what buttons to press within humans.
But I really like the idea of the longitudinal network state
and then the longevity network state or the longitudinal
special economic zone, longitudinal diagnostics.
And then and we can cost that out and we can do something with
it as a Desi thing, you know? Desi.
Yeah. Yeah.
We could or we could do a nutritional raise, but it's just
a very, very scoped thing, which is these end people for this
period of time. And frankly, they could even pay
for it where it's something where it's not that expensive.
It's just expensive enough to be within like a, you know, sort of
pro zoomer budget, like a crypto person, right?
And and they could maybe live in their school and be part of the
study and. You know right?
I like this. So you have the list of all the
instruments that you do for your measurements.
Do you have that in a public spreadsheet or do you have that
internally? I need to put it together.
Yeah, basically, yeah. What what would like, what would
a high fidelity characterization look like?
What, what tests would you need? What machines would you need?
What labs would you need? Because some of the some of the
assays we want done are just not available, the off the shelf
labs. So even if we had some people
who could spit up some nice so so it could accommodate some of
the unique things we want to measure, that'd be great.
Yeah, I think and we we do it in participation with NUS or
somebody like a, you know, some, some sort of local diversity or
hospital and I think we could do something here.
I think it's something very, very cool.
So if anything, it's like a new model of even it's a new model
of healthcare really like. The key is, you know, like at
Stanford, there was this concept called back again when Sanford,
back when Sanford was good residential education.
And the idea was that the education didn't stop when you
were, it wasn't one hour in class.
You were 23 hours outside of class.
And so education after the dorm rooms and sort of so it was
like, you know, immersive in that sense.
So this is. Residential health, Yeah, Yeah.
I mean, this is kind of like we, we've, you and I have been
spinning around this idea, I mean, since our, since we first
met of like how we bridge the worlds of ideology, health,
governance, nation state, like what is this moment?
And I I like this as a path because it does.
It bridges, it brings together the things people care about.
Yeah, and there won't be that much resistances because we
could start with the launch tool measurements.
No one gets hurt, right? Exactly.
You have enough data to show what normal looks like, what
interventions look like, what fitness looks like, what bad
foods look like. You've got all their
nutrigenomics. You got their pharmacogenomics.
It's a whole thing. There's a whole stack of
actually open source software that you develop in doing this.
Yeah, I like this a lot. And then we can also, if we, OK,
this is probably too much, but then we we add some organelles,
right. So now you start doing try
therapy trials against the organelles instead of.
So then you've got organoids. Exactly.
Yeah, exactly. So now you start doing the the
experimentation, high throughput experimentation on your
organelles and then proxies. Exactly.
Yeah, that'd be bad. I mean, that'd be amazing if we
actually set this up. All right.
Yeah, OK, good outcome. All right.
So we've got a plan for the longevity network state towards
the longevity network state making progress.
OK. Well, thank you very much,
Brian. Thanks for having me, really
enjoyed this. Awesome talk soon, OK?
Bye.