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Reproductive Health & DAOs with Dr. Jennifer Garrison
Recorded: Sept. 21, 2022 Duration: 1:14:29Space Recording
Full Transcription
Hi, Maria.
I sent you an invitation
as a co-host.
Let me know
if you got it.
Okay.
Hi, Jennifer.
So, Maria, can you test your mic, please?
We sent, um, you are a speaker now.
Jennifer, can you hear us?
Yes.
Is it working?
Yes, it's working.
Can you hear me?
Yes, we can.
Hooray!
Awesome.
Awesome.
Awesome.
Everybody is early.
Oh, are we early?
I felt like I was running very late, but that's because I, um, I mistakenly thought there was
a video component.
It's so I'm futzing around with my camera.
No worries.
We are recording this session and I just started it a bit earlier just to make sure that, um,
we got everybody here.
And just to give you, thank you for being here.
I am just going to quickly tweet that we are live with you.
And, um, as soon as, um, 3 p.m., um, hits the clock, we'll just start the conversation.
Are you in San Francisco?
Oh, we lost Jennifer.
I think she's back now.
Hi, can you hear me?
Yeah, we lost you.
Yeah, it's weird.
It, um, it sort of rewound and I was listening to a recording of us, um, and it kicked me out
of co-hosts.
I'm not sure why.
Um, yeah, I was asking you if you were in San Francisco and all of a sudden you were
not there anymore.
Yeah.
And then I started listening to a recording of us.
Um, anyway, yes, I'm in San, well, I'm in the, I'm at the box, so I'm in Novato, but
yes, I'm in the Bay area.
Okay.
Um, can you hear me okay?
Is my mic good for this purpose?
Yeah, we can hear you.
And thank you, thank you, everybody who is here so far.
We are going to get going right at 3 p.m.
Um, I know that a lot of people RSVP'd, but the good things is that we also are going to
be recording.
So, uh, we'll make sure to share this with, um, anybody who was not able to tell the live
session.
Just as a quickly, um, format.
This is a 16 minute conversation.
And, uh, for 45 minutes, we are going to be doing, um, a Q and a with Dr. Jennifer Garrison
and the other 15, we would love for people to come and ask questions.
But, um, if people don't have questions, we have plenty of them.
So, that's okay.
I'm just going to tweet a couple of things.
Maria, I'll leave this with you while I share this on a couple of places and then we'll get
going.
Okay, it's 3 p.m.
So, we are going to get going with the official welcome and, um, with the actual, uh, event
today.
Thank you so much, Jennifer, for being here, for being here with us today.
Um, we are going to be talking about your work in reproductive longevity and how you think
DAOs and decentralized science can help support this important research.
Uh, my name is Ramin Kini.
I am the core lead for Athena DAO.
We are a decentralized collective looking to fund reproductive health research and drug
discovery.
And, uh, with me, I have my co-host, Maria Marinova, who is our science lead.
She's going to tell you more about herself in a second.
After that, uh, Dr. Jennifer Garrison is going to tell you about her work as well.
This conversation is 60 minutes, 45 minutes Q and A.
If you come up for a question for the Q and A part, which is 15 minutes, just know that
we are potentially going to be using this recording and your image is there.
If you're comfortable with it, please come up.
If not, um, just, um, obviously you're welcome as a listener.
Uh, without much ado, I'm going to pass the mic to Maria to speak about herself and her
work and then to Dr. Jennifer Garrison.
Thank you, Laura.
Um, so just a brief intro, um, I have been interested in aging and longevity for a very
long time.
Um, so I pursued a, um, bachelor's in molecular and cell biology, and then, uh, went on to do
my PhD between two labs, uh, biology of aging and female reproduction, um, which is how I
found myself in this fascinating field.
Um, and I was surprised to find out how under research it is.
Um, so it's been, um, a great project, uh, and I want to learn, uh, in Athenadale, um, I'm
leading the scientific group, um, and our purpose would be to find, um, relative projects for us
to fund.
Um, so if you would like to contribute and work with us, please get in touch with me.
My DMs are open.
Um, so to kick off this session, uh, just a bit of housekeeping, um, the session will be
recorded, uh, as Laura mentioned.
Uh, so if you do speak later on, uh, and ask questions, um, you need to know that it'll
be recorded, um, and we'll have 45 minutes, um, of the panel and then we'll open for
questions afterwards.
Jennifer, if you want to, um, I'm going to let you do the introduction of yourself.
Please go ahead.
Um, sure.
Thanks for inviting me.
I, I really appreciate the opportunity to have this, this discussion.
Um, it's one I think that, that a lot of, um, scientists aren't aware of.
And so I, and, and I think, I think there's a lot of conversation that needs to happen
on both sides.
So I'm super excited about this topic.
Um, I am, uh, also a scientist.
I run a research lab.
So I got my PhD in chemistry and chemical biology from UCSF.
Then I went on to do my postdoc in neuroscience at the Rockefeller University.
Um, and I run a research lab at the Buck Institute.
I also have appointments at UCSF and USC.
And my lab really focuses on trying to understand how changes in homeostatic circuits in the
brain with age contribute to systemic aging.
And we work on a class of signaling molecules called neuropeptides, which essentially act
like the brain's wifi.
Um, I'm not going to talk about that today.
Uh, you can go and look at my lab website if you're interested.
And of course my DMs are open if anyone wants to talk about anything that we cover today.
Um, the reason I'm here is because, uh, I co-founded and I direct a global consortium.
So this is a nonprofit that's separate from, uh, the work that I do in my lab.
And the nonprofit is called the Global Consortium for Reproductive Longevity and Equality, which
is a mouthful.
Um, but what we're trying to do is to accelerate, uh, translating basic scientific discoveries
that happen in the lab into useful products and therapies that will positively impact women's
lives.
And we want to do that as fast as possible.
So the way that we do that is we're focused right now around grant funding to, uh, scientists
all over the world who are working on ovarian aging.
Um, so I'll stop there and, and let you, uh, direct the discussion, Laura.
Thank you, Jennifer, for that introduction.
I just want to point out that, um, this global consortium that Jennifer founded only came to
be in 2018, which when I interviewed.
Actually 2020, it was in 2020.
Oh, 2020.
I mean, I was, when I interviewed you the first time, I found it quite shocking because
I would have thought I, I wasn't aware that as I am aware, as I am aware now, how little
research we've done and how this was not even something that was, uh, important in scientific
research.
Can you tell us about the historical context or what was for you, obviously as a researcher
and a scientist yourself, what is it that made you think this is, I mean, I know what
you thought that it was so uncrucial, but why hadn't it happened before?
Yeah, I mean, I felt the same thing when I started looking into it, which was in 2018.
So in 2018, um, with a really generous donation from Nicole Shanahan, we started a center at
the Buck Institute, right?
The Buck Institute is an independent research institute that's wholly devoted to understanding
mechanisms of aging.
So we're trying to understand what are the underlying causes of aging so that we can potentially
intervene to extend healthspan.
And, um, you know, we hadn't before 2018, we hadn't really thought too much about reproductive
aging, partly because when you step back and think about it from the perspective of an aging
researcher, you know, human aging, this is something that we think about in a person's
forties, fifties, sixties, and beyond.
And ovaries are aging at like two and a half times the rate of the other tissues.
It's essentially an accelerated model for human aging.
And so a woman who's in her late twenties, early thirties doesn't like on the surface
strike you as, as, as a potential topic of research for aging biology.
But, um, it turns out that ovaries are, are really, you know, they really fall off the
curve in terms of aging.
So anyway, we started this center at the Buck Institute to focus scientists around answering
these questions.
Like really fundamental questions that honestly, like you said, I think we should have had the
answer to a long time ago.
Things like what is the causal cue or the factor or the constellation of cues and factors that
essentially really reproducibly tell a female human's ovaries to start to decay when she's,
um, you know, in her late twenties.
And when we started looking into, you know, start hiring faculty into the center, it was
actually really tricky to identify researchers who were working at that interface between
reproductive biology and aging science.
Um, and the reason for that, after, you know, looking into it quite a bit, I think there's,
there's three things that really contributed to the fact that we're woefully behind in this.
Number one is that just in general, women's health has been underfunded, right?
Forget about just reproductive aging, women's health as a whole has been woefully underfunded
for decades.
Um, and women's health is often treated as like a niche subcategory of medicine.
Um, it was getting something like 1%, barely 1% of the research dollars and biopharma investment.
But we're talking about something that impacts, you know, over half the population.
So this kind of neglect has led to, um, uh, a huge dearth of, of, of discovery in this space.
Um, and you couple that with systemic sex bias and biomedical research, right?
For the last hundred years, the male body has been biology's baseline.
Um, it was considered more, more predictable than the female counterpart, right?
Less messy, less noisy, um, the ovulatory cycles that characterize female physiology were considered
like confounding variables in the data.
And it's true.
It does make the data more complex, but that complexity is actually really important to
understand.
And I think both of those things are changing the, the lack of funding and the, the sex bias
and biomedical research, it's all changing in a positive direction.
But, you know, these changes have only started to happen in the last few years.
And so we're just really far behind with basic discovery.
The last thing that I think has contributed to this is that there's, you know, there's,
there are persistent societal taboos around female health and female physiology, um, talking
about periods, talking about sex, talking about menopause.
These are things that at least for the generations that are older than us, um, have historically
been off, you know, kind of topics that were, were not really broached.
So I, I think those are the, that's, that's the, the universe of things that have really
limited progress in this space.
Before Maria asked the question on research and we move to that, I just want to, um, contextualize
things also that reproductive longevity is crucial to women's, uh, health and wellbeing.
I know that you've talked about menopause as being a debilitated, um, state.
Can you talk about that a bit?
Because, uh, for me, one of the biggest drivers that made me get into more interested in reproductive
health was the fact that I found that during menopause, women's cellular aging accelerates
by something like six or 7%.
And that's the reason women are more propense for Alzheimer's, cardiovascular disease, post
menopausal osteoporosis, and a series of chronic health issues.
That means that we live longer, but we live longer with low quality of life and health
problems.
Um, that's all true.
So I think, um, most, most people are familiar with, like, we're really familiar with the downstream
consequences of ovarian aging, right?
And I think a lot of people are more familiar with the consequences as they relate to fertility,
right?
So ovarian aging definitely causes miscarriages and a decline in, uh, oocyte quality, which
then leads to, um, potentially infertility, um, and, uh, birth defects and things like that.
I think that is, um, those are things that most people are familiar with.
I think what's less obvious to many people is that ovaries are making, um, a lot of endocrine
hormones that are really essential for general health.
And so when ovaries stop functioning, um, at menopause, this dramatically increases a
woman's risk of a whole host of diseases.
Um, and I, you know, reproductive aging is going to impact every single female on the
planet who's lucky enough to make it to midlife.
And, you know, I, I think those hormones that are essential for general health really do dramatically
impact not just health risks for disease, but also the vasomotor symptoms associated with
the reduction in those hormones around perimenopause and menopause dramatically impact a woman's quality
of life. Um, hot flashes, uh, cognitive fog, um, brain fog, um, things like that really,
really do impact every aspect of a woman's life when she's going through it. So, you know,
one of the reasons that the, the GCRLE has the E in it, that the E stands for equality.
And we really think about solving ovarian aging, or at least understanding it, um, as an issue
of equality. Absolutely. Thank you. Um, you already mentioned, um, the issue of insufficient
funding, and I know the global consortium is, um, working in that space, um, and you funded
a number of fascinating projects in the first round of grant allocations. Um, so what do you
think is the most exciting thing being worked on right now, um, in that space? Do you have
personal favorites? That's like asking, uh, so I don't have children, but I imagine that's
what, what, uh, it would be like to ask about your favorite child. Um, I think because we're
just at the beginning and we really don't know where to look, right? That's important
to acknowledge like what we don't know. We don't know where to look. We don't know where
those causal cues are coming from, whether it's during development or during early adulthood
or during, you know, um, puberty, we have absolutely no idea. And so it's really important
that I thought it was really important that we not limit the kinds of projects that we
were going to fund. Um, so we, we broadly funded, you know, everything that our scientific advisory
committee thought was exciting. Um, and that, you know, it's diagnostics, biomarkers, looking
for, uh, clocks that would help define reproductive span, right? So me right now, um, I'm staring
down perimenopause in a few years and I genuinely have no idea where I am in my reproductive span
trajectory. I don't know if I'm two years away from menopause or 10 years away from menopause
and that's ridiculous, right? I mean, with all of the tools we have available to us today,
I should be able to get a, a better resolution picture of where I am. Um, then things like, um,
new target discovery, new cellular targets for interventions, um, looking at the interplay between
like the environment and ovarian function is really cool. Um, finding new models to study
menopause because we don't have great animal models right now, um, which is a problem. If you want to
study something in biology, you really need a good model, um, to, to do that. And then on the clinical
side, I think I'm really excited about the longitudinal data sets that are being collected
on women in perimenopause and menopause. It's really shocking to, to realize that, that a lot of the
questions that we have, a lot of the open, big questions in the field, they're open questions
because we simply haven't looked. It's not even a question of developing new technology or, or
overcoming some technical hurdle. It is genuinely that we haven't done the experiments. So we haven't
collected the data. So there are a lot of, uh, efforts underway to collect large scale data sets,
um, longitudinally on women that will be so valuable for discovery.
I love that you mentioned that Jennifer, because, um, today earlier on another call where, um,
we're part of this, the new bio X, Y, C, um, Dow builder by molecule. And we're one of the four,
uh, other Dow's in the first cohort. And when we've talked about Athena Dow, I said, well, you guys are
talking about IP innovation and that's very exciting. But when it comes to women's reproductive health,
uh, we're at the point where we actually need to get to that, where there's so much research that
hasn't happened. And that's where we need to start when it comes to this area. Um, I think Maria,
you had another question on the research.
Um, so in terms of, um, research fields and things that haven't been explored just because
there have been no, um, funding available, uh, what do you think are the lowest hanging fruits,
um, that can easily be addressed? What do you want people to be working on right now?
Um, yeah. And I, I made a whole webinar about this, so we don't have to spend a lot of time on it.
People can go look it up if they want to, but I really think that right at this moment,
that the lowest hanging fruit, the things that are the most tractable to solve, um, is to redefine
diagnostics, uh, and biomarkers. I think if we, we need to rethink and change the narrative in terms
of the tools that we're using to, um, to tell a woman, not just where she is in her reproductive
span trajectory, but to tell her in general, how her body as a whole is functioning as a unit,
right? Like, um, we often try to like isolate the reproductive system and look at it without
considering, um, the rest of the body and, and truth eggs, you know, women's eggs are,
they do change over time. They decline in quality, but for the most part, they're sitting there kind
of quiescent and it's the environments around the eggs that's changing, right? The micro environment
inside the ovary and inside the follicles is changing, but then, you know, the macro environment,
the woman, if you think about her body as a, as a, as a system, right? There's a lot,
I think that could be done without any therapeutic intervention with diet, with exercise to optimize
all the different parts of the system. And those kinds of lifestyle interventions can sometimes have
a dramatic impact on fertility, um, and reproductive health. So I, you know, I, what I said in this
webinar is that if you're an entrepreneur, I think there's a huge opportunity to put together,
to take tools that we already have. So tools for measuring a lot of different things through, um,
blood tests and urine tests, um, that would give you like a holistic picture of a woman's body and how
how it's functioning. But then to combine that with something that would require a little bit of
technical innovation, and that is a way to monitor reproductive hormones at a much higher, um,
resolution than we do now. So right now, the tools we have are rudimentary. We take a woman's
temperature, we do a few blood tests, and then we take the static snapshot of hormones, um, which is
ridiculous because, you know, the way that hormones fluctuate, it's a dynamic system and you need to capture,
you know, the entirety of those fluctuations over a whole cycle. And so, um, right now there are, um,
there are a few, uh, private companies that offer things like urine spot tests where you could
potentially imagine sampling every day or every other day, which is really what you need. Um, and
you can't do that by taking blood, right? That's, you can't bleed a woman every day to over 30 days.
That's not going to work. Um, but I think there's a little bit of innovation that needs to be done to be
able to measure those hormones in a dynamic way. But then there's a second piece of innovation,
which I think is very tractable. And that is to take all of these, these numbers and all of this
information and feed it into some kind of a high level algorithm that's based on science and medicine
and, and give women, you know, a real snapshot of where they are. And so this also requires that
longitudinal data that I was talking about, but, but everything I'm describing, you know, these are
simple, simple, simple, simple fixes. And I think having, I think every woman should be able to go
to her doctor for her annual pap smear. And when she gets those, those tests that she should also
be able to have like a women's health reproductive diagnostic panel that, that you can look at year
to year. Um, I think that's those, that's where I think that the most innovation is likely to happen
quickly. The other place where innovation can happen quickly is on the product side,
right? Everything we're doing right now is kind of a bandaid until we understand more about,
you know, until we do that discovery piece to understand those causal mechanisms.
But while we're waiting for that discovery piece to happen, there's a lot that can be done to improve
the tools we already have, and to maybe think up new products that will help women, um, you know,
as they're, as they're aging. So things like, um, improving the way that we administer hormone
replacement therapy, right? There's a lot of room for innovation there. Um, and I could talk about
this for a while, so I'm going to stop. Great. Thank you. Um, if anyone wants to take this on,
our, um, applications for funding will be opening soon, just to mention, um, and for the next question,
um, I think that is basically here to support innovation in reproductive health. Um, so can you
tell us about the biggest challenges and drawbacks in the field, um, both for academic research,
startups, um, or in terms of public perception?
Sure. I'll start with that last one. Um, I think public perception is something where
we can make a real impact now. And I do spend a lot of time giving talks and, um, talking to
non-scientists, um, as a, as a way to really broaden, um, the collective knowledge that's out
there in the world about what's happening. Um, and there's a piece to it that I think is really
essential for women in general, and that is just to educate them about their physiology. Most women
don't know that they're born with all the eggs they're ever going to have. A lot of women don't
realize that, you know, the number and quality of their eggs is declining precipitously when they
enter their twenties. And they often only find out that that's happening when they go to use their
ovaries and they have, they encounter fertility issues. And, and there's no reason that needs to be
the case, right? We should, we don't have something in adulthood where we get educated about fertility
and, um, female reproductive biology, but we should. And I think, um, you know, giving,
giving this information to the world and translating, um, the science is something that it, you know,
we took on as one of the mandates for the JCRLE. Um, I spent a lot of time building out the network.
And my goal is, you know, if we want to, to really accelerate things, my goal is to
build this thing differently than other scientific fields. I really think that if we're going to make
progress, that bringing in both academia and industry partners is important and that we can
take advantage of, you know, the unique expertise of both and that that will help accelerate things.
So, um, yeah, talking to the public is, is something that I think is really important.
And that's one of the reasons that I, I, I come on things like Twitter spaces.
Um, in terms of, uh, challenges, I think we've probably already really covered most of them
for academic research. It really is a question of, um, funding, uh, and, and, uh, you know,
re refocusing attention on collecting data in both sexes. And like I said, that's changing.
The rules have changed for NIH. Um, people really now appreciate that sex specific differences in
biology is it's a, a feature, not a bug and that we can really learn about a lot about biology by
studying, um, females as well for startups. Um, in this space, I think one of the challenges that I
see is that there's a, you know, and this is a good thing. There's a huge amount of interest right
now, um, from funders, uh, and from industry in this area. And I think one of the challenges
is trying to communicate what Laura said earlier. And that is that we really haven't done the R and D
yet. We don't have the discovery piece. The IP doesn't exist to make therapeutics or to make
interventions. So for companies that are interested in developing products and diagnostics,
I think that there's a, you know, there's a huge opportunity. I worry that there's gonna,
that there's such a rush to invest in this space that funders are gonna, you know, invest in things
that are not sound and that there'll be, you know, a lot of companies that don't succeed and that might
sour investors on the space before we have a chance to really, you know, have the IP that will lead to
something that's a game changer. So that's my worry. Um, thank you for mentioning that, Jennifer,
because I know we've had a lot of conversations where one of your main missions is also to make
sure that we're looking at, um, sound science. You also already have the, uh, have been developing
a platform, a communication platform with a consortium, the knowledge hub, which is very
important that, uh, in this day and age where people don't trust science, that we actually communicate
the correct, um, like scientific research, because there's a lot of hype and there's a lot of things
that look like great startups and are actually, I know we had a conversation where you pointed a couple
of things to me that were like, no, that's not right. And this is going to be crucial for, um,
Athena Dow moving forward and collaborating with, um, so, I mean, the consortium and taking guidance
from you. That brings me to my next question. Athena Dow being, uh, obviously something that
exists within, not within academia, not within a venture fund, not as a community, just a patient
community, but something in between. I know that you are very curious about this space and you've
been, you've joined, you have a discord, you've joined, you look through the DAOs. Um, I know that
we've had conversations about Vita Dow and you were first a guest there, uh, on a panel discussion
earlier this year. So I am very curious about, first of all, how do you, why do you like the idea of, uh,
DAOs and decentralized science? And the second part is how can we build things in a way that supports
your work as it is already? That's a lot of questions. Um, but I would, yeah, I really do
want to, um, focus this conversation around, um, DSI and how it might help. Um, and I think,
you know, I read Sarah Hamburg's letter to nature last year, calling on scientists to get involved
here. And I, I think it's that, that, um, it was largely not ignored, but I think that for now,
at least, um, the DSI movement and DAOs are mostly under the radar for, for scientists at large. I think
that the exception to that is that among young people, so among the trainees, um, you know,
the people who are just coming into the science, I think they're aware of it, but people at my level
and above and in general don't understand it, don't know what it is. Um, and, and don't really,
you know, don't really have any interest in getting involved. And I, I really do think that there has to
be a conversation in both ways because, you know, what I've seen is that there's a lot of, um,
I don't want to say disorganization, but it was really hard for me to actually understand what,
you know, and I have a strong interest in trying to understand what's happening.
And even then it was hard for me to understand, you know, what was, what was going on. So it seems
to me like there's a lot of, um, there's a lot of noise and, and maybe a little bit of, um, I guess
it's because it's a real, a really new area, um, that, that there's a lot of, um, parts that are still
in flux. Um, so it's new and untested, but I think, you know, I, I, I'm a fan of, um, of supporting
anything that's going to move the needle. And I think we've talked a lot about a lack of funding
in the space. I, I, you know, and you and I have had this conversation many times, Laura, I think that
there are, DSI has a lot of things. If you read what the goals are, they're, they're basically
saying they're going to change the entire world of science, which I think is kind of naive and, um,
and, you know, maybe they're overthinking and maybe trying to go after too many things at once.
Um, so I'll tell you what I think, where I think there can, they could really make a difference.
Um, I think in terms of, um, thinking about how research is funded, I love that, that, that DSI
is opening up that dialogue. I don't think that anyone, none of the DAOs that I've seen have hit on
the right way to do this. And I think that that's because if you want to change how research is funded,
you first have to understand how science funding works and nearly a hundred percent of the people
I've spoken to on the VC side and in the DSI space fundamentally don't understand how science funding
works. And so I, I want to like, and you know, I'm always going to tell you what I think. So, um,
you should take all of this with a grain of salt. These are my opinions. Um, and I'm happy to change
my mind, but I really think that, you know, if you don't understand how science funding
works to begin with, just throwing money at the problem is not going to help anything.
Um, just becoming another funder, just becoming another place where someone can go and get
a different kind of grant is not going to move the needle even a little bit. Um, when we think
about what's wrong with science funding, aside from the volume problem, of course, we need more
money in the space. That's, that's a given, but just putting more money into the space is really not
going to, it's not going to have the kind of effect or enact the kind of change that, that you want it
to have. Um, I think there's a lot of different ways I could imagine, um, it, it having more of an
impact. One way is to think about, you know, one of the limitations, I think the biggest limitation for
science funding is that the incentives are misaligned, right? So as a science, like I run a lab,
I run a research lab and it is my job as the head of the lab to bring in all of the funding for my
lab. Um, I have to, you know, pay all of my employees. I have to pay for all the equipment.
I have to pay for all of the supplies. And so I'm kind of like a small business. And the way that I
fund my business is that I apply for grants. And I, right before this call, I actually counted up,
how many grants do I have right now? I have eight grants. Um, some of them are big. Most of them are very
small and they're for all different projects. Um, some of them fund specific people in my lab.
Some of them fund specific projects. Um, they're all different and they're all for different lengths
of time and they are partially overlapping. And so I have this kind of patchwork of funding
that I use to, to keep my lab going. And I'm constantly looking at that patchwork and spotting
where the holes are and then applying for new grants to plug those holes. Um, and so, you know,
people, I think when I read about DSI on the web, what I find is there's, uh, often a very loud voice
that says, well, writing grants is a waste of scientist time. And that's true. Um, many scientists
spend way too much of their time writing grants, no question. Um, but grant writing, you know, as an
exercise is actually really beneficial. It's just the amount of time that we have to devote to it.
So if I could spend say 10% of my time writing grants, I think that would be ideal because
writing a grant actually forces you to focus your thoughts. It forces you to focus, um, your attention
on, you know, what are the new technologies that you could apply? It forces you to focus on thinking
through logically what, what experiments you could do, you know, and, and sitting down and having that
sort of internal conversation and, and doing, you know, reading and places you wouldn't normally do
reading, that's, that's really helpful for thinking. Um, but having to spend 80% of my time doing that
is really, you know, that's detrimental to progress. Um, the other thing I would say is that
when I thought about, you know, we give away grants to the consortium, we gave away the first ones in 2020
and we're about to gear up to give the second round and then going forward, we'll do this every year.
And I spent an inordinate amount of time thinking about how I wanted to structure those grants,
because as a scientist, I know where all the problems are. I know all the things that are
limiting for me. And one of the biggest problems that I see is that there's no, like what, what we
need if we want to really stimulate discovery and creativity and all the things that everyone who
support science wants to see, we need sustainable funding. We need to make pots of money that are
available to a researcher, which of course you have to show progress, right? You can't just take money
and, and forever and not show any progress, but, but there needs to be a timeline that's more in,
in sync with how long it takes to do biomedical research, right? Most grants are one year, two
year, three years. If you're lucky, you get a five year grant from the NIH and five years is barely
enough time to get started. And the problem is that once you get a grant, um, you, you know,
you do the initial experiments, you start to get some momentum, then the money runs out,
and you have to look for the money somewhere else. And sometimes that means you can continue
the same project, but most of the time it means you have to pivot slightly what you're working on
to fit whatever the funders have, have decreed is the most important thing that they care about.
And so I'm constantly making these pivots in my research program to try to fit the calls for funding.
And that is so, it's just such, it's so misaligned with what we're trying to do. So when I, you know,
when we put together the consortium, one of the visions is to have two pots of money. One would
be for new grantees, right? For, because we want to bring as many people, as many creative scientists
into the space as we can. But the other pot of money is for, for sustainable funding so that current
grantees can apply for money. They say like, look, we made this progress. We've got this really cool
idea going forward. Like we want to keep working on this and to have a pot of money that they can
apply for, which would be a much shorter, you know, it would essentially be a much different
kind of application. But as a way for, for them to know that if they're doing good work,
they're going to be able to get the funding and continue working on the things that they want to work
on. The other thing that's broken is this, this idea that funders can decide what the most important
thing is. As a scientist, you know, I mean, and I'm not even, I'm barely a mid-career scientist,
but I have, you know, 20 plus years of education and experience. And I can tell you that nobody knows
better than me what I should be working on. And the idea that someone else is going to come in and
tell me like what they think the most important thing I can do is, um, is just, it's insulting.
And it's so dumb. Like, it's just, it's really, um, it's really, it's really frustrating. Anyway,
sorry. I feel like I just went on a rant. No, thank you. That was an amazing, I mean,
I, I've loved our conversations and I know, um, I've also loved your honesty. I think the biggest part
is, um, not just trying to say we're going to change the world, but how can we actually effectively,
um, move the needle and not just the grander vision, but the very granular step-by-step.
And I think, um, I mean, just for context for everybody, it is an honor to have Jennifer here
because she's actually the biggest advocate in, um, trying to move this field forward. I know you're
here on our Twitter space, but you also, um, do appear on CNN talking about this and go around
the world, trying to get more people involved. And I think one of the biggest things, uh, my next
question would be, I think that you've alluded to the fact that we don't have enough people working
on this problem and we're going to be collaborating with DAOs. We're going to be collaborating with, uh,
all our friends on web three. How can we, you're an expert at this. Um, you've been doing it for
three, four years more, um, in terms of being a public face for reproductive longevity. How can
we galvanize more people to get into this area of research, uh, from Vita DAO, from lab DAO, from all
the other, um, bio DAOs? Because I think you did say that we're not even getting enough, um, things
through. There's already, where do we, you know, where do you get those scientists to want to move
into the field or how do we get them on board? Yeah. Um, I, you know, and I've thought a lot
about this because again, um, I, I think, uh, I, like, I want to be welcoming of people who are
interested in helping, right? I mean, even if they're misguided or even if they don't, they're
a little bit naive in the beginning, like that's fine. You can, you can educate people and explain
to them like how science funding works. And you can also talk to them about what their strengths are and,
and help them think about where they might fit in a way that really pushes us forward. Um, so for
DSI, I mean, the idea that you could contribute tools for data sharing, I think is really powerful,
right? Um, there are, I would say there are several initiatives out there. Um, uh,
let's see, um, CZI comes to mind. Um, the Allen Institute comes to mind, but there are several
initiatives out there that are really about open science, um, big science, big science and open
science and, um, taking a close look at those initiatives and asking how and, and where you
can support them, whether it is with gen, with expertise or with funding. I think I would, I would
strongly recommend that you do that because we don't need to, the thing is, you know, scientists
are well aware of what's broken. Like we all, we all can tell you what we think is the most
broken thing about how science works, but we are also all constantly working on solutions.
And so I'd say over the last 10 years, there are a couple of really wonderful examples of large
scale efforts to make big data and open data a thing. Um, and so seeing how you can collaborate
with them or support them or, um, you know, work with them, I would encourage you to do that.
Um, the other thing I would say is, you know, look at the models that actually work for science
funding. There aren't that many of them to be perfectly frank. Um, one is HHMI. I think HHMI is
probably the best model we have for funding. And, uh, the problem is of course that they have
limited budget. And so they, there's a limited number of people they can fund, but you know,
the way HHMI works is that they fund the scientist, they fund the researcher and the lab, not a project.
They acknowledge that they don't know, they're not experts, um, the way that the people they fund are,
and that they acknowledge that, you know, if you're the expert, you should decide,
you know, you should be free to do experiments, get negative results or get results that you don't
expect and pivot your whole, your research questions in a different direction based on
the data you get. Um, and so HHMI funds a limited number of people, but they do it in a way that makes
sense. They fund the whole lab, you know, they fund, if you have HHMI funding, you don't need to apply
for other grants. You can, if you want to, but you don't need to. Um, and they also fund scientists
for seven years before they do a review. And, you know, the review process is intense, but if you're
doing good work, most people can be pretty sure that they're going to get renewed. And if they end
the funding after seven years, they give the researchers a two year, um, ramp down time. So,
so, so at a minimum, they're funding someone for nine years. Now that is enough time and they fund
them at a level that they can sustain an entire lab. And now that is a model for doing really
innovative science. And if you look at the, the work that comes out of labs that are HHMI funded,
it is in general, the most cutting edge, you know, it, it, it tops, you know, the, the innovation
spectrum. It really, that that's a lot of the science that moves things forward. And, and so
looking at models that work and, and taking cues from them, I think is really important.
I would say, since you are just starting out, there's some really granular things that I think
you could do that would be really impactful. I think just funding one-off grants to academic
scientists, honestly, is not going to help that much. Um, what I would say, and partly that's because
most of the DAOs that I've talked to and the DCI people haven't even thought about how to handle,
overhead costs. Um, they haven't really thought about how to handle IP. They haven't, you know,
in, and these things are really important. Um, for now, at least most scientists are working at
institutions that are not going to give away IP and they're working at institutions that charge
overhead. And, you know, a lot of private foundation grants don't allow overhead on the grants.
And that sounds noble, but you know, my lab wouldn't function if we didn't have electricity
and a space and a facilities team to fix things when they break and clean the floors and a grants
team to submit our grants and a finance team to pay my people and an HR team to take care of my
employees. You know, there's a lot of things that, that, that overhead goes towards. And the truth is,
if I get an, uh, if I, if I get a grant from a foundation that doesn't pay overhead,
my institution, and this is true across the board, will get that money from me one way or another.
So it'll be behind the scenes, but that money is coming out of my budget somehow. And so it's really
short sighted. And I think pretty naive, um, to not think about that. Anyway, I would suggest strongly
that the DAOs look at funding PhD and postdoctoral fellowships because training the next generation
of researchers is really in line with, with your vision. And we don't have nearly enough
fellowships for PhD students and postdocs. Like there's always there's, you know, these are things
that are good for their CVs, um, whether they go into industry or academia, it's always a really
good thing to show that you've been able to get independent funding. And so there are PhD fellowships,
there are postdoctoral fellowships, but they're really competitive. I mean, five percent of the
people who apply to some of these fellowships actually get awarded the money. And that's ridiculous,
right? There are so many talented trainees. The beautiful thing about funding fellowships
is that, um, you don't have to pay overhead on those, right? The institution doesn't take any
overhead on, on fellowships and, um, and it would just be a wonderful way to, to really
push the field forward. Um, because that would also, you know, that also that money goes directly
to the labs, obviously too. Um, I would also point towards grants for funding large and expensive
equipment, right? If I want a piece of equipment that costs, you know, hundreds of thousands of dollars,
really difficult to come by. Um, there are a few grants through the NIH that are for equipment,
but, um, you know, they take a long time to get, um, there aren't that many of them. And in this day
and age, I think, you know, sometimes the technology can really help with the science.
The last thing I would suggest is, um, scientific conferences, right? I just organized,
um, Maria, you were there. I just organized the first ever international conference on reproductive
aging. And I spent a ridiculous amount of time raising the money for that. Um, and that's because,
you know, we get sponsors, companies will sponsor us, um, journals will sponsor us, scientific, um,
professional societies will sponsor us, but you know, they give like $2,000 or $3,000 or something.
And so, you know, we ended up with 20 or 30 sponsors and it took a, you know, an amazing
amount of time and manpower to get that money when really, if we could have a source, you know,
it'd be great to have larger grants for scientific conferences. The biggest grant that we got was from
the NIH. Um, but the second biggest grant we got was from impetus, which is obviously a DSI initiative.
So, um, those are the three places I would say, if you wanted to make a difference tomorrow,
um, while you're investigating all these other things that I'm talking about, that those would
be really impactful. Um, thank you so much for that, Jennifer. It's really helpful. And I really
also love your honesty about, um, how you see decentralized science and DAOs and how we have to do
a lot of work. I was very happy also that Paul, um, Koolhaas, who is the founder of Molecule,
who is here for most of the conversation. He couldn't, um, join as a speaker, but it's good
that they also get to hear, um, the perspective of somebody that is building, um, a strong pipeline
for research with the grants that you're doing at the consortium. Um, I think that we are 15
minutes away from the top of the hour. I don't think we are to 15 minutes away from the top of the
hours. So I want to please invite, um, people to raise their hands if they have questions.
I also wanted to just, um, give, give a shout out to Rita Dow because I know that they've developed a
strong, um, fellowship program and it was also, it also happened because of, uh, decentralized science.
And it was also, I think that fellowship was completely funded by crypto. I'm, and I don't
think I'm know that it is from the Gitcoin round. And, um, I know that Maria has, and is a fellow
and a lot of the postdocs, PhDs that are part of Vita Dow. It did provide opportunities, as you said,
to attend conferences. I love the notion of the equipment. That is a big thing that I had, uh,
we haven't even discussed. So, um, I think those are very important points and anybody that listens
to the recording, um, I think you provided a lot of guidelines in terms of how we can move things
forward. Oh yeah. One more note. Um, the reason I mentioned large equipment is because, uh, anything
over $5,000 institutions don't take overhead on. And so large equipment, you know, you don't have to
worry about those things that I mentioned. Um, and it is really also a place where it can be very
difficult. If you're not, you know, a core facility, it can be really difficult to, to get
expensive equipment. Um, I think the other thing that I love that you always say is, um,
it's not just about throwing money at the problem and indeed we do need the capital, but it's also how
to actually do it efficiently and in a way that makes impact. And sometimes very little capital can
go a long way and a lot of capital can do not much. So balancing that out is super crucial.
I just wanted to see if anybody had any questions. If not, in the meantime, I'm let Maria go to the
next question. Maria, did you want to ask the one, like we still had it? Yeah. Yeah, sure. I can jump in.
Um, and then, um, and then if anybody comes up with a question, I will continue with that. Um,
I was just wondering if you've talked to any of your colleagues, um, and what would they think of the
design space? Um, because for the general public, um, group to might not have the best reputation. Um,
some people are a bit skeptical that it is a scam and so on. Um, so what do you think, um,
we can do to make this more credible and lower the barrier for entry for researchers?
Yeah. I mean, honestly, I think, um, many of my colleagues don't understand it and I have tried
to explain and I do try to explain and, um, there are some nice, you know, blog posts and articles that
I can point to on the web that give kind of an, uh, an overview of what, what DSI is, um,
what it hopes to be. Um, I think at this moment, it's so new and untested that there, you know,
there's not much to point to in terms of what's happening, what's already happened, but that's
good. I mean, that, that means there's a huge opportunity and, and I think the future is really,
there's a lot of possibility here. Um, I will say, I think it's important to acknowledge what
you don't know. It's also important to acknowledge that, that, um, you know, applying the same tools
and principles that worked for crypto and finance to the scientific enterprise probably isn't going to
work here. Um, and, and so, you know, I think, I think acknowledging that and, and trying to engage
with the, with the scientists is maybe the most important thing, right? I, I don't think that,
I, I, I think that there's a lot of skepticism because, you know, there's this kind of feeling,
like, I think among scientists who know what DSI is, that it's just a bunch of kids who, who don't
know anything about science, who think they can fix everything. And, and there is a little bit of
naivety on one side, you know, like if I were to come to one of the people who developed Ethereum
and say, Hey, you know, I, I think this is super cool what you're doing. And, um, I know a little
bit of like Python and I do some stuff to analyze my large data sets for computational neuroscience.
And, uh, I want to take a look at your code and tell you what you're doing wrong and try to fix it
for you. Like, that's just, it's just silly, right? It's painfully naive. It's nonsensical.
It's a waste of time. So I think it's really important that the people who are, who are crafting
the, the direction and the way that things are going in DSI, that they really have these conversations
with, with senior scientists, with people who understand the space, who understand where the holes
are, where the pain points are, um, you know, what's going to make a difference, what's not
going to make a difference and, and make it an open dialogue. Um, because right now I think there's a
lot of noise and, um, and I, I, I would just, uh, you know, I'm one person and I have a lot of strong
opinions, but, uh, many of my colleagues will have similarly strong opinions and, and probably have a lot
of other ideas that, that I haven't thought of. Thank you so much for that, Jennifer. Um, as,
as usual, very, um, honest and, um, it's, this is important for all of us to hear, especially as we
build this. And as you said, it's very new. It's almost like this massive experiment and it'll be
great if we actually make it work out in ways that benefit all the different causes that we're working
for. Um, Ariella and Max, thanks for being here. I'm going to let Ariella speak and thank you for
being here, Ariella, and for being such a big supporter again, and who is going to be working
with us on the CICOM for the reproductive health report that we're going to be, uh, doing.
Ariella, go ahead. Hi, thanks. Yeah. Hi, Laura, Maria, and Jennifer. Thank you so much for having this
space. I've been following it and just appreciating everything, um, you know, that you all have been
saying. And so I had a question for, um, for Dr. Garrison. I, uh, I really appreciate,
like Laura was saying, I really appreciate your, uh, very refreshing honesty about your
perspectives on DSI. Um, for context, I'm an MD, PhD student at Washington University studying the
genetics of aging. And so I'm definitely seeing this from the perspective of a trainee in traditional
academia. And, you know, part of that journey of exploring my options for the future, like
academia industry, what is this new blockchain world? Let's see what happens. Um, when I was
interacting with this space, I noticed there were not a lot of, um, you know, not a lot of women
in positions of leadership and authority and not a lot of, um, funding and resources going to women's
issues. And I thought that even though I share a lot of your views about, you know, some flaws and
challenges and even trends were cringeworthy moments in DSI, I thought it might be a good idea
to go ahead and secure women's place in this space anyway, even if it, even if, you know, it isn't
perfect yet. And I just wanted to know what your views are on that, you know, like, do you think
that, let me try to phrase this question better? Um, do you, do you share my view that it is
important to secure women's place in this space? Or do you think, you know, while it's still in its
infancy and like, like a little, a little wonky, it's not that important yet? Um, first call me
Jennifer, please. Um, second, I totally agree with you. Um, I mean, I think that women should
secure their space in every arena of public life and professional life. Um, it's ridiculous that
we're still having this conversation, um, right. Women make up 50% of the population,
so they should be represented at, at least 50%, um, in every, especially in positions of leadership
and authority in every space. So yes, I completely agree with you. And, and yeah, the reason I'm here,
the reason I I'm, I'm here because I think there's a lot of promise. And again, like rising tides lift
all boats is, is a kind of a silly, ridiculous, um, thing to say, but it's true. And, um, I think
having new perspectives and having new ideas and having people challenge, you know, the way that things
have, have historically been, I think that's really valuable. Um, I, and I'm here to, you know, to,
to help as much as I can. Um, I think, you know, at least as far as funding goes, like I said, we,
we spent a lot of time and a lot, a lot of effort putting together a really careful process for a
granting. We made it easy for everyone, but we also made it rigorous and we made it so that, um,
you know, we have a scientific advisory committee made up of experts and these, you know, these
processes are not easy to replicate. Um, and I think one of the things I would caution and, and
encourage everybody who's thinking about giving away money to scientists is, is to really scrutinize
the process and, and think hard about whether or not, you know, a DAO is the right way to do that. Um,
and again, like, like you, Ariella, I don't know, you didn't say, I think you said you were a PhD
student. You probably applied for, for fellowships and did you apply for fellowships? Yeah, I have a
T32 right now. You have a T32. So that's a fellowship from the NIH and the funding levels, um,
are different across different institutes of the NIH, but they're generally very low. Um, and that means
that a lot of really, um, amazing, talented, smart, totally worthy candidates are not being funded.
So making a postdoctoral fellowship or a PhD fellowship or both, um, you know, generally
speaking, it takes about a hundred K a year to fund, not just the, um, uh, a person's salary and
benefits, but also to give them a little bit of extra money for supplies and travel to conferences and
things like that, you know, a hundred K a year makes a huge difference in a trainee's life.
And that's a way that you could both fund the science because those are the people doing the
research. Um, but it also gives the trainee, you know, a really wonderful thing to put on their
resume. It gives, um, the lab that they're in some financial security without having to worry about
all those things we just talked about, like overhead and IP. Um, and it, it actually, you know,
these are things that, um, you're, you're, you know, the Dow name would then be the name of the
fellowship and it would be on CVs that everyone's looking at. It would be a way to get your name out
there. Anyway. Um, yeah, I totally agree with you, Ariella. And if you're going to be at the
Cold Spring Harbor aging meeting, I'll be there. Yes, I am going to be there. Great. So we can meet in
person. Yeah, that would be great. Just for everyone listening, we make like $30,000 a year,
not a hundred thousand. So I wish. Oh, but so that's, that's an important point. Um, but the
cost to your lab, right? Like most postdoctoral fellowships, like the NIH is paying probably
somewhere around 80 or $90,000 to your institution to support you because there's tuition, you know,
there are costs that you don't see. Um, but then, no, I just, for the other people not listening
are like, Oh man, the PhD students make a hundred. I just want to say, no, definitely we do not.
Yeah. Well, in our program, I'm the, I'm the associate director for the biology of aging PhD
program here that we share with USC. Um, our students make, I think 42,000 a year, but it's
still, it's not a lot, but then they also get free tuition and we're paying them to learn. So it's
kind of a trade-off. It's different from medical school where they would be paying 40 or $50,000 a
year in tuition. Um, but again, it's a place where a good fellowship gives, you know, pays for the
salary, the benefits and all that stuff, and then gives a few, you know, 10 or $15,000 on top of that
to pay for the student to have control over ordering some supplies and also maybe like a laptop
and maybe travel to a meeting or two. And so that usually tallies somewhere around 75 or a hundred K
per year. Just as a comment, I've always been so shocked how scientists don't have a much higher
salaries considering that they are, thanks to the research that they do and the work that they do,
we're able to have things like iPhones and vaccines and anything that moves humanity forward. Um, but,
um, Max, thank you so much for being here. I know you're a big supporter and, um, I'm going to let
you introduce yourself and, um, ask your question. Uh, yeah. Hi, Laura. Uh, great, uh, to be here.
Hi, Maria. Hi, Jennifer. And hi, Ariella and the rest, uh, of people. Um, yeah, I'm Max. I'm also
like involved with VitaDAO. I'm currently doing a PhD in Singapore on, uh, aging. Um, my question to you,
Jennifer Whitby is like the longest lived person has been like 122 years. Um, the oldest person I think
ever gave birth to children was I think around 66, 67. Um, what do you think would it take to,
to increase fertility, like for like a lot of women or like for a lot of, yeah, for a lot of women to
still be able to have babies with 70, like as a signal that, um, rejuvenation and, um, delaying
of aging is really possible? Yeah, that's a great question. I mean, honestly, if I could answer that
question, we wouldn't need the consortium. Um, like that's the money question. That's the,
that's the bazillion dollar question is what, uh, what, uh, what, what is the thing that we can,
what is the thing that we can intervene with to, um, to extend reproductive span, to change,
you know, to change the number and the quality of eggs that a woman has when she's 40 essentially.
Right. So, um, by the time a woman's 40, she's left with somewhere between one and 2% of the, the,
the starting number of eggs that she had at the beginning. And so if we could change that number,
like, we don't need to, we don't need to do just to change that number by, you know, increase it to
3% from 2% or to increase it to 2% from 1%, um, would be incredible. And I can think of lots of
different ways that that might work. So, um, but, but I don't know, like, I really don't know where
we're going to find that, that, that thing. And that's why we're, that's why we're, we're like
frantically trying to get as much money out to scientists as we can. And that's why,
you know, we started the center of the buck. And as soon as, as soon as I realized, like,
the work I'm doing, I think is very important. I think that the signal for menopause originates
in the brain, but that's my personal bias. And, and, you know, I'm doing the research to,
to test that, that hypothesis, but there's like 50 other possible hypotheses for how it might work
that I can think up. And, and so, you know, the, the idea is to put as much money as fast as possible
into scientists' hands so that they can test all these ideas. Um, yeah. So I, yeah, I don't know.
I wish I knew. Thank you for the question.
Yeah, Max, um, it's very involved in the, obviously longevity space. And I know that he's a big
supportive or reproductive longevity. And, um, I know he's been thinking of these things a lot.
So thanks for coming, Max. I, we do have one more, we're at the top of the hour. We have just
one more question that somebody asked on a tweet. Jennifer, is that okay? It's, um, maybe just a
couple more minutes. Absolutely. So what about more translational models rather than more clinical
data in order to be able to isolate effects of physiological mediators, depending on the
estros faces? What are the challenges in that area? Um, the challenges in finding, uh, models that
are not just, uh, uh, just collecting data in women. Yeah. Just making it for the translational.
Yeah. The translational pieces is tricky because, um, you know, we're unique. Humans, um, are unique
in that there aren't very many other species of animal that go through a true menopause. And so
you know, there are limitations as with any sort of animal model, there are lots of limitations,
but particularly for looking at, uh, menopause, you know, there are aspects of menopause that you
can recapitulate in a rodent or in a monkey model. Um, but none of them are perfect. Um, there are
aspects of reproductive aging that you can recapitulate in a fly or a mouse, um, or a worm.
And so, you know, depending on your research question, um, some models might be perfectly adequate.
I think that the biggest innovations we're going to see are in trying to either make genetically
modified rodent models that will basically endow mice or rats with, um, the aspects of human
menopause that they don't naturally have. Um, and I think that there's a lot of promise,
although it's, it's going to take, I think that we're pretty early stages. I think there's promise
in thinking about, um, human ovary sort of ex vivo models. I don't want to say, um, organoids
because honestly making an ovarian organoid will be almost as difficult as making a true
brain organoid, right? We have brain organoids that are amazing for research, but they aren't
brains. They aren't many brains. They are, you know, they recapitulate some aspect of brain
function or they recapitulate some aspect of some, some piece of, you know, some piece
of the brain that in that they have like certain layers or tissues or cell types, but nobody
is growing. No one's anywhere near growing an actual brain in a dish with ovaries. You
know, they're so complex. I think a lot of people don't realize how complex they are, but
they have so many different cell types and sub compartments. And when you think about what
happens over the course of a cycle, they go through this dynamic, like dramatic macroscopic
remodeling that happens over, you know, 26 or 28 days. And, um, there's no other tissue
in the body that does that and tried to recapitulate that in a dish is going to be challenging. But
again, just like every other model, I think that there will be aspects of, of the system
that you can recapitulate that will be super useful for, for research. The last thing I'll
say is that, um, human material is very hard to come by. Um, you know, when women freeze
their eggs or their embryos, um, they typically have something in mind for them and they don't,
they don't want to just give them away. But, um, fertility clinics will often just throw away
eggs. Um, once the, once a woman decides she doesn't want to maintain them anymore, they
just throw them away. And so we just started through the consortium, a biobank to take those
discarded eggs and make them available to researchers. Um, so just having access to
human tissue will be super valuable.
Thank you for that, Jennifer. Um, it's speaking, I mean, you mentioned this thing that it's
important. I, we're at the top of the hour. I would love to hear, um, a parting thought
in some calls to action from anybody who's listening as to what are like immediate things
that people can do to support your work and to get involved also with Athena Dow so we
can build something that really does help researchers and that it really helps, uh, get
more funding into all of these things that you mentioned on this conversation today.
Yeah, absolutely. Um, we need ambassadors. So, um, you know, I want this space to include
anyone who has an interest. So that means clinicians and scientists for sure, but it also means
funders. It means, uh, people in biotech and pharma. Um, and it means you, I, and so be an
ambassador for us. We have a white paper on our website. Um, it's gcrle.org. Uh, it's written
at the top, Jennifer. Oh, thank you. Yeah. Yeah. Jennifer's white, um, the gcrle white papers
at the top. If you haven't looked at the tweets, please do. It's written for, yeah, it's written
for non-scientists. Um, if you're an investor interested in funding either basic science or
entrepreneurs in the space, get in touch with me. Um, I often connect founders with funders,
but more than that, if you know anyone who's interested in philanthropic funding, um, as
much money as I can raise for these grants, that's how much money I can give away. Um, we
also are, you know, I've started petitioning direct to consumer companies in the fertility
menopause space to add a small donation line in their checkout workflows. Something like, would
you like to donate $5 to research aimed at making menopause optional? Um, so anyone who's
listening, who wants to collaborate in that sense, I would love to talk to you. Um, but
mostly we want to incentivize this collaboration and conversation between the stakeholders who
don't normally interact. So please join our network. Um, we have a knowledge hub that we're
building on the site, but we also have a little discussion space and it's kind of in beta form
and it's been pretty quiet there, but we would love for people to join. Um, we really want
everyone, um, to help us, you know, start these conversations and nurture the field. Um, so, and
thank you for listening.
Thank you so much for coming, Jennifer, and I'm, um, deeply honored that you are a supporter of
Athena Dow and that you're going to help us build this. Um, as I say, you're the trail, but, oh, I can't
say the word. Uh, my English as a second language is coming out, but, um, you are the leader in
reproductive longevity advocacy, and we have so much to learn from you. So I just wanted
to say to everybody, we did pin a lot of the, um, relevant information that was discussed
here at the top. And, um, just as a call to action, there are a couple of things you can
join, um, or discord or linked, uh, or link tree on our Twitter has all the information of
different, um, things. So you can, um, either contact us or join our discord. And, uh, we
look to be collaborating and being good ambassadors in the web three space for everything that, uh,
Jennifer is working on. Um, Maria, if you wanted to say something before we actually, um,
close the room and again, again, for being here, um, Jennifer, uh, thanks again for being
here, Jennifer. Yeah. Thanks for hosting me. Thank you so much. It was a fantastic talk.
We look forward to having more, especially as we, uh, build out Athena Dow and when we
publish our reproductive health report that Jennifer is also, um, advising us on. So thank
you so much for everybody for being here and taking this time. And, um, we are going to have
another guest next month. We'll be announcing the speaker soon. Jennifer, for the, just as a
side note, we had a meeting with you since Sue today, and, um, she was just mentioning how
she's working on a lot of the grants and they take a lot of time. So all scientists, even
research scientists, every senior scientists like yourselves have spent a lot of time on
that. Thank you so much, everybody for being here again and, um, have a great afternoon.
