OK, let's get into this. We're taking a deep
dive today into some, well, some really cutting
edge areas that are fundamentally changing how
we think about health and medicine. Absolutely.
We're pulling insights from some fascinating
conversations Eric Tupel hosted recently. That's
right. First up, we'll be digging into the latest
science on sleep with Professor Matthew Walker.
And we're talking updates that go... quite a
bit beyond just counting hours. Then we'll switch
gears a bit, look at the bigger picture, the
future landscape of life science. Things like
genomics, AI, and our understanding of the immune
system, which is evolving so rapidly. And for
that, we're drawing on insights from Sir John
Bell, who's a real visionary in those fields.
Exactly. So the mission for this deep dive, really,
is to pull out the most impactful bits of knowledge
from what these experts are saying. Yeah, translating
some quite complex research into to hopefully
surprising facts and insights that are actually
relevant, especially for professionals, working
in industries touched by all these changes. Because
understanding this stuff isn't just academic
curiosity anymore, is it? It feels key to navigating,
well, both our personal health futures and the
professional world in the next few years. Couldn't
agree more. It really is. Right then. Let's jump
straight in. We'll start with the science of
sleep, which is often, I think, underappreciated,
and maybe begin with something quite unexpected
at social side. Yes. It's become increasingly
clear that sleep's influence goes way beyond
just us as individuals. Recent work has really
shown a light on its crucial role in how we interact
socially. Which is surprising, isn't it? Because
you tend to think of sleep deprivation effects
as your mood, your concentration, maybe physical
health. That's the traditional view, yes. But
it's about more than just how you feel when you
haven't slept. It's actually about how that lack
of sleep affects the people around you. Okay,
tell me more about that social dimension. What's
the new thinking? Well, there's some really compelling
research, particularly from Dr. Eddie Ben Simon
over at Berkeley. Her work demonstrates pretty
clearly that sleep deprivation makes people measurably
more asocial. Asocial. Yes. Essentially, not
getting enough sleep seems to make you, well,
she used the term, socially repellent. Socially
repellent? That sounds quite harsh. It is a strong
term, yes. But the data suggests that people
who are under -stumped tend to withdraw socially.
They report feeling lonelier. And crucially,
they seem to project something that makes other
people less inclined to want to engage with them.
So people can actually sense it, even if they
don't know you pulled an all -nighter. It seems
that way, yes. The research showed that even
when observers didn't know the person was sleep
-deprived, they rated them as less socially appealing,
less attractive to interact with. And here's
where it gets, well, frankly, a bit alarming.
The studies also found that after interacting
with someone who was sleep deprived, a person
who was actually well -rested walked away feeling
more lonely themselves. No way. So a kind of
social loneliness contagion. Your bad night's
sleep can actually make someone else feel lonely
just by talking to them. Exactly. It's like a
ripple effect. A sort of viral transmission of
that feeling. And the work also uncovered another
really significant social impact, a reduction
in what they call helping behavior. Meaning?
Meaning, when you're insufficiently slept, you're
simply less likely to offer help to others, even
strangers. Your sort of default setting shifts
towards being less altruistic, less pro -social.
And I remember reading there was population level
data on this too, something about daylight savings.
That's right, yes. The daylight sevens time study
is a really striking example. They looked at
charitable donations across the U .S. And in
the days immediately after the clocks go forward
in spring, when everyone loses that hour of sleep
opportunity, there was a statistically significant
drop. A drop in donations. A big dent, as Professor
Walker described it, in national charitable giving.
Just from losing one hour of potential sleep
across the population, it shows this reduced
helping behavior playing out on a massive scale.
That's incredible. It really speaks volumes,
doesn't it, about how fundamental sleep is for
just Well, basic human cooperation and empathy.
It does. And you can immediately see the professional
implications. Teamwork, collaboration, effective
leadership. They all rely so heavily on positive
social interaction, on that willingness to help
each other out. Absolutely. If your team or even
just key people in it are chronically under -slept,
it's bound to have a tangible, negative effect
on how everyone functions together. It's not
just about individual performance, it's about
the collective. It really reframes sleep health,
doesn't it? Not just a personal wellness thing,
but almost a social or organizational imperative.
I think that's exactly right. A social imperative.
OK, so that's the surprising social angle. What
about the underlying biology? There's been a
lot of talk about genetic short sleepers. Is
that a real thing? Are some people genuinely
OK on much less sleep? Yes, it is real. But,
and this is a huge, but it's incredibly exceedingly
rare, for the vast, vast majority of us, that
need for seven to nine hours is biologically
baked in. The evidence for impairment below that
is just overwhelming. But there are some people.
There are. Science has identified this tiny,
tiny subset of individuals who seem to genuinely
thrive on significantly less sleep. Maybe five
hours. Maybe even a bit less. And Critically,
they show no apparent signs of impairment. No
impairment at all. That sounds like a superpower.
It almost defies everything else we know about
sleep debt. It certainly seems that way, and
researchers have actually pinpointed specific
genes linked to this. The first one identified
was called the DEC2 gene. A specific mutation
in that gene seems strongly connected to this
natural short sleep ability. But you stressed
how rare it is. How rare are we talking? Professor
Walker put it very starkly. He said, you are
statistically more likely to be struck by lightning
in your lifetime than to have this specific genetic
makeup that allows you to genuinely function
perfectly well on very little sleep. Struck by
lightning. OK. It puts it in perspective. So
most people who think they're fine on five hours
probably aren't. That's the overwhelming likelihood,
yes. They might feel okay, or they've adapted
subjectively, but objectively they're likely
accumulating significant sleep debt with all
the downstream negative consequences for their
health and cognitive function, even if they don't
realize it. Right. So why is this tiny group
so interesting to science, then, if it's that
uncommon? Because it poses this fundamental biological
puzzle. How has Mother Nature, through just random
genetic mutation, found a way in these few individuals
to essentially, well, ZIP file sleep? ZIP file
sleep? I like that analogy. They somehow compress
all the necessary functions that normally take
seven to nine hours into maybe five or six and
still seem to get all the benefits. The huge
question is, how? What are the molecular tricks?
What are the mechanisms that let them do that?
And if we could figure that out? If we could
figure that out. It could unlock profound secrets
about what sleep is actually for at a fundamental
level, and potentially lead to new ways to help
people with sleep problems, or maybe even enhance
sleep efficiency for everyone else. Which I suppose
immediately raises thoughts about future applications,
maybe even trying to replicate it artificially.
Exactly. And that's where it gets complicated,
ethically and societally. While the main scientific
goal is understanding, the knowledge could lead
down paths like developing drugs or even genome
editing to try and induce this short sleep ability.
And Professor Walker raised concerns about that.
He did. He talked about the risk of an arms race
of de -escalation and sleep. A scenario where
society, chasing productivity gains, pushes people
towards less and less sleep, potentially overriding
other vital functions of sleep that we don't
even fully understand yet. It highlights why
we need to really grasp the why and how before
we start thinking about artificial manipulation.
Which is a perfect segue to another critical
biological mechanism, the glymphatic system.
This is the brain's cleaning crew, right? That's
a great way to put it, yes. It's basically the
brain's equivalent of the lymphatic system that
cleans waste from the rest of the body. The glymphatic
system's job is to flush out metabolic byproducts
that accumulate in the brain while we're awake.
Including things like the proteins linked to
Alzheimer's. Precisely. Things like beta amyloid
and tau proteins. They're essentially the molecular
garbage that the brain produces through its normal
activity. And it needs to be cleared out regularly,
otherwise it builds up and causes problems. And
the established view, the overwhelming evidence,
has pointed to sleep being absolutely crucial
for this process. Yes, that's been the prevailing
understanding for some time now, based on a huge
amount of evidence from many different research
groups across different animal species and increasingly
in humans too. The idea being that deep sleep
is the prime time for this brainwashing. Exactly.
The data strongly suggested that sleep, particularly
that deep, non -REM sleep, stage 3 sleep, provides
the optimal window for this glymphatic system
to really kick into high gear. Why then? Why
not when we're awake? Well, the thinking is that
when we're awake, the brain is just too busy
processing information. There's less space between
the brain cells, and the fluid flow needed for
cleansing seems to be significantly reduced.
Some researchers even describe wakefulness as
a state of sort of low -level biochemical damage,
and sleep provides the essential sanitary salvation.
But wasn't there a study recently that caused
a bit of a stir, suggesting maybe clearance was
higher when we were awake? That's correct. A
study published I think around 2022 or 2023 used
some specific imaging techniques in humans and
reported findings suggesting higher fluid flow
and potentially higher clearance during wakefulness
compared to sleep, which naturally seemed to
contradict quite a lot of the previous work.
And what was the reaction from other scientists?
Were there criticisms of that study? Yes, researchers
who'd been proponents of the sleep -dependent
model raised several points about the methodology.
They noted the use of imaging methods that weren't
standard, or at least different from those used
in many of the animal studies. There were also
questions about an artificial method used to
perfuse fluid through the brain, rather than
observing the natural flow. And importantly,
concerns about the sampling rate, whether it
was fast enough to capture the crucial slow brainwave
oscillations that happen during deep sleep. These
slow waves being important for driving the fluid
flow. That's the hypothesis, yes, that these
very slow, large amplitude brain waves physically
help to pump the cerebral spinal fluid through
the brain tissue, facilitating that waste removal.
So if the measurement technique missed those,
it could skew the results. So weighing everything
up, what's the current sort of nuanced understanding?
Is it all about sleep or is it more complicated?
I think the picture is becoming a bit more nuanced
than just saying it only happens during sleep.
The glymphatic system is clearly dynamic. It's
possible there's a kind of low battery mode clearance
that can happen during quiet wakefulness. But
sleep is still king. But the overwhelming weight
of evidence, when you look across all the different
studies, different species, different methods,
still points very strongly towards sleep, especially
deep and REM sleep. providing the optimal opportunity
for a really thorough cleanse. A full biochemical
reboot. Like the difference between putting your
phone on low power mode versus actually switching
it off for a proper update and refresh. That's
a great analogy, yes. You might get some background
tidying in low power mode, but the deep clean,
the system overhaul, really happens when it's
properly off. The bulk of evidence still firmly
supports sleep as the preferential most effective
state for this vital brain maintenance. It just
makes intuitive sense, doesn't it, that such
a complex, active organ needs dedicated downtime
for housekeeping? And you mentioned a link between
this glymphatic system and other parts of the
body, like the heart. Yes, that was fascinating.
A paper in a cardiology journal reported that
patients with atrial fibrillation, or AFib, a
common heart rhythm problem, actually showed
less active glymphatic clearance during their
sleep. Really? How does that connect? It highlights
this idea of cardiorespiratory neurophysiological
coupling. It suggests it's not just the brain's
electrical activity driving this fluid flow.
The heart and the lungs, their rhythms during
sleep, seem to synchronize with the brain's slow
waves to help drive the pulsations needed for
efficient clearance. So it's the whole system
working together heart, lungs, brain to wash
the brain during sleep. Exactly. It's a beautiful
illustration of how sleep benefits the entire
embodied organism, as Professor Walker put it.
Your body and your brain are deeply interconnected
in this process. good cardiovascular and respiratory
health might actually contribute to better brain
cleansing overnight. That link is quite profound.
A heart condition potentially impacting brain
maintenance. Wow. And speaking of things that
impact sleep and potentially this glymphatic
function, what about sleep medications? Ah, yes.
A critical area. And the research here has thrown
up some quite surprising and frankly concerning
findings, especially regarding the older, more
established classes of sleeping pills. You mean
things like Ambien, the Z drugs, benzodiazepines?
Exactly. Those drugs, the ones often called sedative
notics, zolpidem, ezolpaclone, zeleplon, and
the older benzodiazepines like diazepam or temezepam,
they primarily work by, well... broadly sedating
the brain's cortex. They essentially just dampen
down overall brain activity. And they do help
people sleep or at least feel like they're sleeping
more. They certainly make you fall asleep faster
and they can increase the total time spent apparently
asleep. On a standard sleep study, they might
even show an increase in deep sleep minutes.
However, and this is crucial, they seem to significantly
alter the electrical quality or the signature
of that deep sleep. Alter the signature. What
does that mean in practice? It means they seem
to create a substantial dent, as Professor Walker
termed it, in those very large, very slow brain
waves that are the hallmark of truly restorative
deep NREM sleep. They suppress those critical
slow oscillations. The same oscillations thought
to drive the glymphatic system. Precisely. So
by suppressing those key brain waves, even if
the sleep looks like deep sleep on a superficial
level, the underlying functional machinery needed
for optimal brain cleansing seems to be impaired.
So even if your sleep tracker says you got more
deep sleep after taking an older sleeping pill,
you might not actually be getting the brain cleaning
benefits. That's exactly what the evidence suggests.
Pioneering work, particularly from making Natagard's
lab using animal models, found that despite increasing
sleep time and apparent deep sleep time, the
actual brain glymphatic cleansing was reduced
perhaps by 30 % to 40 % when these older sedative
hypnotics were used. Reduced? That's incredibly
counterintuitive. You take something to help
you sleep better. And it hinders one of sleep's
key functions. It is profoundly counterintuitive,
yes. But it strongly suggests these drugs might
be generating what's been called junk sleep,
sleep that ticks the boxes on basic duration
measures but lacks some of the crucial functional
properties, like efficient waste clearance. That's
a really significant finding, given how widely
prescribed these medications are and have been
for decades. Is there a newer approach, a different
class of drug that might avoid this problem?
Yes, thankfully there is. There's a newer class
of medications called DORAZ. That stands for
dualorexin receptor antagonists. DORAZ? Okay.
How do they work differently? They represent
a much more... well, elegant and targeted way
to promote sleep. Instead of just blanketing
the cortex with sedation, they target a very
specific chemical system in the brain, the orexin
system. Orexin. Orexin, sometimes called hypocretin,
is a key neurotransmitter that acts like a wakefulness
switch or volume control. Keeps us alert. Doors
work by blocking the receptors that erect and
binds to, so they essentially just turn down
the volume on wakefulness. So less forcing sedation,
more allowing sleep to happen naturally. Exactly.
It doesn't push the brain into an artificial
state, but rather removes the wakeup signal,
allowing the natural process of sleep onset and
maintenance to emerge more easily when conditions
are right. It's a much more subtle mechanism.
And have these newer Dora drugs been tested for
their effects on glymphatic activity or brain
cleansing? Yes. And there's a very exciting and
promising study that Professor Walker highlighted.
It involved older adults, age 65 and up, using
a Dora drug called SuverXant brand name Balsamra.
What did that study involve? It was a proper,
rigorous, randomized placebo -controlled trial.
They gave the participants either SuverXant or
a placebo. They measured not only how much sleep
they got and how much deep NREM sleep, but crucially,
they also measured the levels of those Alzheimer's
biomarkers, beta amyloid and tau in the bloodstream
before and after the night of sleep. Okay, and
what did they find regarding those biomarkers?
Did the Dora help clear them? They found that
on the night the participants took the Dora drug,
Suvarexan, there was significantly greater clearance
of both beta amyloid and tau protein from the
brain into the bloodstream compared to when they
took the placebo. The opposite effect to the
older drugs. Exactly the opposite. It wasn't
just increasing sleep duration or deep sleep
minutes, it seemed to be generating genuinely
functional sleep. sleep that was actually facilitating
the removal of these potentially harmful proteins
linked to Alzheimer's disease. That's a massive
development. It really is. Professor Walker framed
it as potentially the first evidence we have
of a sleep medication that not only helps you
sleep in a more naturalistic way, but also seems
to enhance the brain's own restorative cleansing
processes. That could have huge implications
for brain health, especially as we age. It really
drives home that not all sleep is created equal,
especially when medication is involved. So quantity
is important, obviously, but it sounds like we
absolutely have to focus just as much, if not
more, on sleep quality and also sleep regularity.
Absolutely. For years, the public health message,
the whole conversation, was heavily skewed towards
just getting enough hours The quantity. And don't
get me wrong, sufficient quantity is non -negotiable.
You need that foundation. But it's not the whole
story. Not by a long shot. Research, especially
over the last decade or so, has made it increasingly
clear that sleep quality and sleep regularity
are equally, and in some cases more, predictive
of critical health outcomes. Like what kind of
outcomes? Things like all -cause mortality, your
overall risk of dying from any cause, also cardiovascular
disease risk, metabolic health, think diabetes
risk, and potentially even cancer mortality as
well. Quality and regularity are powerful predictors
across the board. OK, let's unpack quality first.
How is that usually defined or measured? A common
and useful metric for sleep quality is sleep
efficiency. It's actually quite simple. It's
the percentage of time you spend actually asleep
while you're in bed trying to sleep. Right. So
if you're in bed for eight hours, but tossing
and turning for two, your efficiency isn't great.
Exactly. Generally, a sleep efficiency of 85
% or higher is considered good, indicating solid,
consolidated sleep. When efficiency drops much
below that, usually because your sleep is fragmented
with lots of awakenings, that's when you start
seeing problems. And what kind of problems are
linked specifically to poor quality fragmented
sleep? Pretty much system -wide impairments,
increased risk of those metabolic and cardiovascular
issues we mentioned, hormonal imbalances. But
perhaps most strikingly, the effects on mood
and mental health are profound. How so? It's
a remarkable finding, but sleep is abnormal in
every single psychiatric condition that's ever
been studied. Depression, anxiety, PTSD, bipolar
disorder, schizophrenia, you name it, sleep is
disrupted. And very often, the key feature isn't
necessarily just short sleep duration, but severely
fragmented poor quality sleep. Poor sleep efficiency
is a major red flag for mental health issues.
That really highlights how fundamental good quality
sleep is for just, well, keeping everything running
smoothly mentally and physically. Okay, what
about regularity then? You said that's also vital,
maybe even underappreciated. Hugely underappreciated,
I think. but absolutely vital. There was a really
stunning study using data from the UK Biobank,
this massive data set with hundreds of thousands
of people. What did they look at in that study?
They tracked not just how much sleep people were
getting on average, but also how regular their
sleep schedules were over many years. So how
consistent were their bedtimes and wake times
from day to day, including weekends? And what
did they find about regularity versus quantity?
The results were quite remarkable. People who
maintained high sleep regularity, basically going
to bed and waking up around the same time every
day, had a significantly lower risk of dying
from any cause, from cancer and from cardiovascular
disease, compared to those with very irregular
schedules. Even accounting for how much sleep
they got overall. Yes. And here's the kicker.
When they statistically compared the predictive
power of regularity versus quantity for all -cause
mortality, regularity almost beat quantity. Really?
Almost more important than total hours slept.
That feels counterintuitive if we've always been
told to get your eight hours. It does, doesn't
it? But it highlights something crucial. While
you absolutely need sufficient quantity, being
perfectly regular but only sleeping four hours
a night isn't going to work. Regularity acts
as a powerful anchor for your entire internal
biological clock, your 24 -hour circadian rhythm.
So keeping a consistent schedule helps keep your
body clock stable. Exactly. It sends strong,
reliable timing signals to your brain and body
every day. And having a well -aligned, robust
circadian rhythm doesn't just directly benefit
health. It also feeds back to improve both your
sleep quantity and your sleep quality. They all
reinforce each other quantity quality and regularity
They're the three pillars of healthy sleep and
we need to pay attention to all of them Okay,
so with all this detail stages quality efficiency
regularity It's no surprise people are turning
to technology sleep trackers rings watches even
smart mattresses now Are these things genuinely
helpful or can they sometimes make things worse?
It's a great question and the answer is Well,
it depends For the average person, someone who
doesn't already have clinical insomnia or a lot
of anxiety around sleep, tracking can generally
be pretty useful. Why is that? Because sleep
is notoriously difficult for us to judge subjectively.
We're often quite bad at estimating how long
it took us to fall asleep, how many times we
woke up, how much deep sleep we got. Unlike,
say, counting steps or tracking calories, which
are more concrete. So the old adage, what gets
measured gets managed, can definitely apply.
Can you give an example of how seeing the data
might help someone change their behavior? A classic
one is alcohol. Many people are quite surprised,
maybe even shocked, when they see the objective
data from their tracker showing just how consistently
even moderate alcohol consumption close to bedtime
absolutely tanks their sleep quality. How does
it show up in the data? Typically you'll see
reduced REM sleep. Increased heart rate throughout
the night, more awakenings, poor sleep efficiency.
Seeing that pattern night after night can be
a really powerful motivator to, say, cut back
on evening drinking or stop drinking earlier.
Right, makes sense. If someone is thinking about
getting a tracker, any tips on what to look for?
I think the key things are low friction and reasonable
accuracy. Low friction just means it needs to
be easy and comfortable enough that you'll actually
wear it or use it every single night without
it being a hassle. So something like a ring might
be lower friction than a watch for some people.
Potentially, yes. Or a smart mattress is perhaps
the ultimate in low friction. It's just there.
You don't wear anything. In terms of accuracy,
especially for sleep staging, the technology
is getting better all the time. Data generally
suggests devices like the Aura Ring are currently
among the more accurate wearables compared to
gold standard sleep lab polysomnography. But
others like Fitbit, Apple Watch, Whoop are also
pretty good and constantly improving. Full disclosure,
I should mention I have previously done some
advisory work for Aura in the past. Okay, useful
context. But you mentioned a potential downside,
particularly for some people. Yes, and this is
really important. For individuals who are already
prone to anxiety, especially anxiety about sleep
or maybe have perfectionistic tendencies, these
trackers can sometimes backfire. There's a recognized
phenomenon now called orthosomia. Orthosomnia?
What's that? It's basically where someone becomes
so fixated, so obsessed with achieving the perfect
sleep score or hitting ideal numbers on their
sleep tracker app. That the anxiety about it
actually makes their sleep worse. Exactly. The
pressure to perform to get that perfect data
creates stress. And stress is the absolute enemy
of sleep. It becomes this vicious cycle. You
worry about the score. That makes you sleep poorly.
You get a bad score. You worry more. So what
should someone do if they suspect they might
be falling into that trap? Well, the first thing
might be to simply take a break from tracking
altogether for a while. See if that reduces the
anxiety. If the sleep problems persist, especially
if it's chronic insomnia, the gold standard treatment
is cognitive behavioral therapy for insomnia,
or CBTI. That directly addresses the unhelpful
thoughts and behaviors around sleep. Another
strategy could be to just check the data much
less frequently. maybe only once a week, looking
for broad trends rather than getting caught up
in the nightly numbers. It's a really valuable
reminder, isn't it, that the tracker data is
just a tool. It's information. It's not the ultimate
judge of your sleep health. How you feel is still
paramount. Precisely. You always need to integrate
the objective data with your subjective experience.
How rested do you actually feel during the day?
How's your energy, your mood? Does it align with
what the tracker says? Sometimes the data might
look bad, but you feel fine or vice versa. Your
subjective feeling of restfulness is incredibly
important. And just finally, on tech, you mentioned
smart mattresses. How are they different? What's
the promise there? This is where the technology
starts to move beyond just tracking sleep to
actively augmenting or improving it. Devices
like the eight -sleep mattress, for example,
they don't just measure your sleep stages, heart
rate, breathing rate. They actually do something
with that data. Yes. They use it to intelligently
adjust the temperature of the mattress surface,
zone by zone, throughout the night. Temperature.
Why is that important? Because our body temperature
regulation is incredibly tightly linked to our
sleep cycle. To fall asleep easily, your core
body temperature needs to drop slightly. To maintain
deep sleep, you generally need to stay slightly
cool. and then your temperature needs to rise
again towards morning to help you wake up naturally.
And the mattress can manage that automatically
based on your individual sleep. That's the idea.
It learns your patterns, senses your current
sleep stage and physiology minute by minute,
and then subtly adjusts the heating or cooling
of the mattress surface to keep you in your optimal
thermal zone for each stage of sleep. It's a
really elegant use of technology, creating this
constant personalized thermal feedback loop to
improve sleep quality and maybe even quantity.
That sounds quite sophisticated. It is. And they're
adding other features, too, like detecting snoring
and then maybe subtly adjusting the head elevation
to help open the airway. Yeah. These kinds of
smart beds, I think, represent a really promising
new direction for actually enhancing sleep, not
just measuring it. OK. That brings us to the
end of our deep dive into sleep science. Some
truly surprising stuff there. The social impacts,
the genetic quirks, the brain's cleaning system,
how meds affect it, the importance of quality
and regularity, and how technology fits in. It
certainly shows how much more we're learning
about this fundamental biological need and just
how fast the science is moving on so many different
fronts at once. Right. So... Let's shift gears
now. We're staying with cutting edge science,
but broadening the view to the whole future of
life science, drawing on that conversation with
Sir John Bell. Yes, a really influential figure,
long distinguished career in genetics, immunology,
formerly the Regis Professor of Medicine at Oxford.
And now he's heading up this significant new
venture called the Ellison Institute of Technology,
the EIT, based over here in the UK. OK, tell
us about the EIT. What's its mission? What makes
it different? Well, it's incredibly ambitious.
It's funded by Larry Ellison, the tech entrepreneur.
And his mission is really broad, using state
-of -the -art science and technology, especially
AI and machine learning, to tackle some of the
world's biggest problems. Not just health? Not
just health, no. Health care and disease are
major focuses, obviously, but also critical areas
like food security, climate change, even things
like global governance. It's a very wide scope.
And you mentioned a unique approach or model.
Yes, that's a key difference. The vision is that,
where possible, the solutions they develop should
actually be commercially viable and sustainable.
It's structured more like a company than a traditional
academic foundation. The aim is to create tangible
products, platforms, services that have real
-world impact and can sustain themselves, rather
than relying solely on grants or donations. It's
a more entrepreneurial take on Philanthropic
science, perhaps. And the scale sounds pretty
huge. Oh, absolutely massive. They're building
this enormous campus, potentially millions of
square feet eventually, and planning to recruit
around 5 ,000 people. Really top talent from
across the globe. 5 ,000 people, wow. Yeah. The
focus is on getting the absolute best minds,
the top 1 % in their fields, and giving them
the resources and freedom to take risks on really
novel, potentially disruptive ideas that might
struggle to get funding through more traditional
channels. And it works closely with Oxford University.
How does that relationship function? Yes, there's
a very strong synergistic link. Oxford's been
very supportive. The idea is that the EIT complements
Oxford's strengths and the wider UK life science
ecosystem. One specific gap Sir John mentioned
EIT aims to fill is helping promising UK science
scale up. Historically the UK has been great
at discovery but less good at growing those discoveries
into large impactful companies. EI key structure
and funding are designed to allow them to build
full stack solutions taking things right through
development. That makes sense. And speaking of
the UK's life science landscape, Sir John Bell
himself was hugely influential in establishing
the UK as a world leader in human genomics, wasn't
he? Absolutely pivotal. His influence was immense.
There were really three massive, successive initiatives
that built that leadership in large -scale human
genomics data. Which were? The UK Biobank, then
Genomes England, and the newest one, our Future
Health. He was kind of built on the last tackling
different aspects of using genomic information.
Let's start with UK Biobank. That's become this
incredible global resource for researchers. How
did that come about? Well, it really grew out
of Oxford's traditional strength in large -scale
epidemiology, studying disease patterns in big
populations. The key insight was realizing you
needed enormous numbers of people, huge cohorts,
to reliably detect the often small effects of
individual genetic variations on common diseases.
So the idea was born to recruit a massive group.
Exactly. The incredibly ambitious plan was to
recruit half a million people across the UK,
collect loads of health data questionnaires,
physical measures but critically, also collect
biological samples, like DNA, and get consent
to link all that to their ongoing NHS health
records. Half a million people linked to health
records. That sounds like a logistical nightmare
to set up. Was it difficult? Extremely difficult.
Sir John talked about facing massive resistance
initially from peer reviewers. People doubted
it was even feasible. Could you recruit that
many? Get reliable data, manage the NHS linkage,
even do the genetics on that scale back then.
But they persevered, got crucial funding from
the MRC and Wellcome Trust, and built this resource
that is now genuinely used by tens of thousands
of researchers around the world every single
day. It completely changed the game for genetic
epidemiology. Amazing achievement. And then came
Genomes England. That shifted the focus more
towards using genomics in actual clinical care.
Yes, exactly. As the cost of sequencing a whole
genome just plummeted thanks to new technology,
the idea emerged. Could we use this powerful
tool right now within the NHS to help diagnose
rare diseases? Because many rare diseases have
a genetic cause, but finding it is hard. Precisely.
It can be like finding a needle in a genetic
haystack. Whole genome sequencing gives you the
whole code. This project got really important
backing from the then Prime Minister, David Cameron,
partly driven apparently by his own family's
experience with a rare condition. And did that
face resistance, too? Oh, yes. So John mentioned
massive resistance, again, this time from parts
of the medical establishment, perhaps understandably
wary of the complexity, the cost, the interpretation
challenges. But again, they pushed through, sequenced
100 ,000 genomes from patients with rare diseases
and their families, made huge numbers of diagnoses.
And it continues today with things like a program
for sequencing newborns to spot treatable conditions
incredibly early. And the third and most recent
big initiative is our future health. What's the
ambition there? Our future health really represents
another shift in focus, moving towards prevention
and early diagnosis. It came out of the UK's
life science strategy back in 2017. A key push
came from the pharmaceutical industry, who basically
said the UK needs to focus on the future of health
care, stopping people getting sick in the first
place or catching diseases much, much earlier.
Moving away from just treating established disease.
Exactly. Moving decisively towards identifying
people at high risk before symptoms appear or
diagnosing conditions at stage zero or stage
one when treatments are often far more effective.
The scale here is just enormous. The goal is
to recruit five million adults in the UK. Five
million. That's about 10 % of the adult population.
It is. It's staggering. The idea is to track
their health over many years, combine genetic
data with lots of other health information, lifestyle
data, maybe even data from wearables. To do what,
exactly? Primarily to build incredibly detailed
models of who is likely to develop which diseases,
enabling much earlier identification of risk.
And secondly, to create a massive platform for
efficiently testing new preventative therapies
or early diagnostic tools on a huge scale. And
has recruitment going for that. Despite delays
due to the pandemic, it's been incredibly fast.
Millions have already registered and large numbers
have provided samples and data. It's going to
generate this unbelievably rich multiomics data
set. Multiomics. So beyond just the genome sequence.
Yes. much beyond. Looking at proteins, proteomics,
metabolites, metabolomics, maybe epigenetic markers,
even things like organ clocks, biological markers,
trying to estimate the functional age of different
organs. It's about building a much more holistic,
dynamic picture of health and disease risk over
time. That sounds like it could truly revolutionize
preventative medicine. But it must require new
ways of thinking, clinically and regulatory -wise.
Absolutely. You need new types of clinical trials
designed for prevention in healthy populations.
You need regulators to think about approving
diagnostics based on predicting future risk,
not just confirming present disease. It's a huge
shift. And driving a lot of this potential, you
mentioned AI is absolutely central to the Ellison
Institute's vision. Yes. AI is seen as a core
enabling platform, underpinning pretty much everything
they do, whether it's health, climate, food,
whatever. And they have a massive advantage here
because of the huge compute power funded by Larry
Ellison. Access to that level of computing being
essential for modern AI. Absolutely critical.
Training these incredibly complex machine learning
models on the vast data sets we're talking about
requires enormous computational resources. Few
universities or traditional institutes can compete
on that scale. And they're bringing in the talent
to use it? Yes, actively recruiting top AI and
machine learning talent from around the world,
including people from places like Google DeepMind.
So you have this potent combination, world -class
talent, massive compute, and access to the UK's
unique rich healthcare, and genomic data assets.
Those are the three essential pillars. Talent,
compute, data. Makes sense. Eric Topol's review
for the NHS actually highlighted the UK's potential
to lead in AI for health, didn't it? Building
on that genomic strength. It did, yes. The potential
is clearly there. And you mentioned a second
key technology platform at EIT working alongside
AI. That's right. Generative biology or synthetic
biology, as it's often called. That's the other
core platform. They've recruited a real leader
in the field, Professor Jason Chin from Cambridge,
to head that up. Generative or synthetic biology,
what does that involve? It's essentially about
designing and building new biological parts,
devices and systems, or redesigning existing
ones for useful purposes. So engineering life,
basically. What kind of applications are we talking
about? Things like being able to synthesize huge
stretches of DNA from scratch to encode new functions,
engineering cells or microbes to act as diagnostics
or therapeutics, or to produce valuable chemicals,
even potentially transforming plants to make
them more nutritious or resilient to climate
change. It's about using engineering principles
to manipulate biology in predictable ways. And
how does that connect with AI? They work synergistically.
AI can analyze vast amounts of biological data
to help design these new biological systems,
predict how they'll behave, and then generative
biology provides the tools to actually build
and test those designs in the real world. This
capability can then feed into all of EIT's main
focus areas, creating new health solutions, new
food production methods, new environmental technologies.
It's moving from just reading biology to actively
writing and editing it. Okay, let's move to another
area where Sir John has deep expertise and where
EIT is making a big push. Understanding the immune
system. You called it the next great frontier.
I think it really is. If you think about it,
our clinical tools for assessing someone's immune
status are still surprisingly crude. Often it
boils down to just counting different types of
white blood cells. Which doesn't tell you much
about how well they're actually functioning.
Exactly. The immune system is this incredibly
complex network of different cell types, T cells,
B cells, innate immune cells interacting through
countless molecular signals, antibodies, including
autoantibodies that can cause disease. It's vastly
complex. And without a really deep molecular
understanding of an individual's immune state,
making big breakthroughs in immune -related diseases
is really hard. Which covers a huge range. Infections,
cancer, autoimmune diseases. A massive range.
Sir John described our current approach in this
area as sometimes feeling like pinning the tail
on the donkey. A bit of guesswork in the dark.
We need a much more detailed map. So what's EIT
doing specifically to try and build that map
to get beyond the guesswork? They're establishing
a very significant long -term project focused
on deep immunophenotyping, basically characterizing
immune cells and responses at a really detailed
molecular level. And how are they going about
that? What's the methodology? A key part involves
using human challenge models in a very careful
and controlled way. Human challenge models? What
does that mean, exposing people to diseases?
Yes, essentially. It involves carefully selecting
healthy volunteers and exposing them to controlled,
safe doses of specific pathogens like common
cold viruses or bacteria, or giving them vaccines.
And the purpose is to watch the immune system
react in real time. Precisely. It allows researchers
to observe the entire immune response right from
the beginning in a controlled setting. They can
track exactly how different parts of the immune
system, different cell types, different molecules
respond over time at a very fine -grained molecular
level. It gives you much richer, more dynamic
information than just taking a snapshot blood
sample from someone who's already sick or even
someone healthy. And I'm guessing AI is absolutely
essential for making sense of all the data that
generates. Utterly essential. The sheer volume
and complexity of the data from these kinds of
studies is immense. You're looking at changes
in gene expression across thousands of genes
in different immune cells, sequencing the receptors
on T cells and B cells to understand their diversity,
measuring hundreds of thousands of different
proteins and metabolites in the blood. It sounds
overwhelming. It would be, without powerful computational
tools. AI and machine learning are critical for
finding the patterns in that complexity. Understanding
how all the different components, T cells, B
cells, innate immunity, antibodies interact.
Figuring out which interactions actually lead
to a protective immune response versus those
that might lead to disease or side effects. So
the ultimate goal is to build a kind of predictive
model of the immune system. Yes, to build a really
solid scientific foundation for predicting and
anticipating what kind of immune response you
need to generate for effective protection against
a specific infection or for effective therapy
against cancer or to calm down an autoimmune
attack. And if you can predict it, you can potentially
design interventions to achieve it. That's the
hope. If we understand exactly what a good immune
response looks like at the molecular level for,
say, flu, We can design much better vaccines
to elicit exactly that response. If we know how
cancer evades the immune system, we can design
immunotherapies to overcome those evasion tactics.
Or for autoimmune diseases, if we can pinpoint
the specific rogue immune cells or pathways,
we can develop much more targeted therapies.
Like the recent breakthroughs in treating diseases
like lupus you mentioned. Exactly. Treatments
targeting specific types of B cells, like those
expressing CD19, have shown remarkable results
in some severe autoimmune diseases, illustrating
the power of this kind of molecular process.
precision. It's about moving beyond broad immunosuppression
to highly targeted interventions. And Sir John
mentioned this major immunology project at EIT
is starting soon. Yes. He said they expect data
collection using these challenge models and deep
phenotyping to begin within the next six months
or so. It's a major undertaking, but the potential
payoff for understanding health and disease is
enormous. It really is exciting work. All right,
just finally, the conversation ended with a brief
reflection on the broader state of global science,
didn't it? Potential challenges ahead. Yes, there
was a brief, quite poignant exchange near the
end, alluding to potential headwinds facing science
globally, maybe political disruption, challenges
to international collaboration. Sir John shared
his perspective on that. And what was his take?
Was he pessimistic? Not entirely pessimistic,
but realistic perhaps. He strongly emphasized
the inherently global nature of science. That
despite national borders or politics, scientists
everywhere are fundamentally part of a shared
community working on common problems. He stressed
America's indispensable role as a scientific
powerhouse given its scale and impact. And his
hope for the future. His view was that the global
scientific community needs to stick together
to lean in collectively to support the scientific
enterprise, hoping that any political disruptions
are temporary. He made the point that the complex
structure supporting international science collaborations
take a long time to build but can be damaged
quite quickly, underlining the need for continued
vigilance and support from society and governments
everywhere. A thoughtful note to end on. Well,
this has been quite the journey from the unexpected
ways sleep affects our social lives and the intricate
mechanics of brain cleaning right through to
the future being forged by genomics, AI, synthetic
biology, and a deeper understanding of our own
immune systems at places like the EIT. It really
covers a vast landscape, doesn't it? And it makes
it clear these aren't just abstract topics for
scientists. They are fundamentally reshaping
our understanding of health. of aging and they
have profound implications for how we might live
and work in the future. The pace of change is
just incredible. It certainly gives you, the
listener, a lot to think about. Given these rapid
advances, this power to understand health at
such a deep level, how might our personal responsibility
for managing health change in the coming years?
And what does all this mean for you professionally,
especially if you're in an industry touched by
biology, data, and technology? The ripple effects
are going to be immense. over the next decade.
They really are. The future of health is being
written right now in labs and data centers across
the world. Absolutely. And if you found this
deep dive insightful and valuable, please do
consider taking a moment to rate and share the
show. It really helps others find it.