Google DeepMind CEO: We Want To Build A Virtual Cell

Channel: Alex Kantrowitz

Published at: 2025-02-10

YouTube video id: CEOOMYxMvY4

Source: https://www.youtube.com/watch?v=CEOOMYxMvY4

you worked on basically uh decoding all
protein folding with Alpha fold you won
the Nobel Prize for that not to skip
over the thing that you won the Nobel
Prize for but I want to talk about
what's on the road map sure which is
that you have um an interest in mapping
a virtual cell yes uh what is that and
what does it get us yeah well so if you
think about what we did with Alpha fold
was essentially solve the problem of the
the the the finding the structure of a
protein um proteins everything in life
depends on proteins right in your body
um so that's the kind of static picture
of a protein but the thing about biology
is really it's you only understand
what's going on in biology if you
understand the Dynamics and the
interactions between the different
things in in a cell and so a virtual
cell project is about building a
simulation an AI simulation of a full
working cell I probably start with
something like a yeast cell because of
the Simplicity of of the yeast organism
and um and you have to build up there so
the next step is with Alpha three for
example we started doing pairwise
interactions between proteins and lians
and proteins and DNA proteins and RNA
and then the next step would be modeling
a whole pathway maybe a cancer pathway
or something like that that be helpful
for solving a disease and then finally a
whole cell and the reason that's
important is you would be able to hypoth
make hypotheses and test those
hypotheses about making some change some
nutrient change or injecting a drug into
the cell and then seeing what happens to
the how the cell responds um and at the
moment of course you have to do that
painstakingly in a wet lab but imagine
if you could do it a thousand a million
times faster in silico first and only at
the last step do you do a validation in
the wet lab so instead of doing the
search in in in the wet lab which is
millions of times more expensive and
timec consuming than the validation step
you just do the search part um in silico
so it's again it's sort of translating
again what we did in the games
environments uh but here in the sciences
and the biology so you you build a model
and then you use that to do the
reasoning and the search over and then
the predictions are you know at least
better than not maybe they're not
perfect but they're useful enough to um
to be useful for experimentalist to to
validate against and the wet lab is
within people yeah so the wet lab uh you
you'd still need a final step with the
with the wet lab to prove that uh what
the predictions were actually valid so
you know you you wouldn't have to do all
of the work to get to that prediction in
in in the wet lab so you just get here's
the prediction if you put this chemical
in this should be the change right and
then you just do that one experiment so
and then after that of course you still
have to have clinical trials if you're
talking about a drug you would still
need to test that properly through the
clinical trials and so on and test it on
humans for efficacy and so on that I
also think could be improved with AI
that whole clinical CH that's also takes
many many years but this that would be a
different technology from the virtual
cell virtual cell would be would be
helping the discovery phase for drug
Discovery just like I have an idea for a
drug throw it in the virtual cell see
what it does yeah and maybe eventually
it's a liver cell or or a brain cell or
something like that so you have
different cell models and then you know
at least 90% of the time it g is giving
you back what would really happen that'
be incredible how how long do you think
that's going to take to figure out um I
think that would be like um maybe 5
years from now okay yeah yeah so I have
a kind of five-year project and a lot of
the alpha fold the old Alpha fold team
are working on that yeah asking your
team here so you figured out yeah
speaking with him I was like you figured
out uh protein folding what's next and
this is like it's just very cool to hear
about these new challenges because yeah
the H developing drugs is a mess yeah
right now we have so many promising
ideas they never get out the door
because just the process is absurd it's
process too slow and Discovery phase too
slow I mean look how long we've been
working on Alzheimer's and and I mean in
this tragic way to for someone to go and
for the families and and and you know we
should be further it's 40 years of work
on that yeah yeah I've seen it a couple
times in my family and if we can ensure
that doesn't happen it's just one of the
best things we could use ai4 in my
opinion yeah yeah it's ter terrible way
to see somebody uh decline so yeah it's
important work um in addition to that
there's the genome yes and so the Human
Genome Project sort of I was like okay
so they decoded the whole genome there's
no more work to do there like just same
way that you decoded proteins with fold
but it turns out that actually we just
have like a bunch of letters when it's
decoded and so now you're working to use
AI to translate what those letters mean
yes so yeah we have lots of cool work uh
on on genomics and um uh uh uh trying to
figure out if mutations are going to be
harmful or or benign right most
mutations to your DNA are are are
harmless U but of course some are
pathogenic and you want to know which
ones there are so our first uh systems
um are have are the best in the world at
predicting that um
and then um uh uh the next step is to
look at uh sit situations where the
disease isn't caused just by one genetic
mutation but maybe a series of them in
concert and obviously that's a lot
harder like and a lot of more complex
diseases that we haven't made progress
with they probably not due to a single
mutation right that's more like rare
childhood diseases things like that um
so there you know we need to I think AI
is the Perfect Tool uh to to to sort of
um uh uh uh uh uh try and figure out
what these weak interactions uh are like
right how they may be um uh uh uh kind
of compound on top of each other um and
so maybe the statistics are not very
obvious but an AI system that's able to
kind of spot patterns would be able to
figure out there's some connection here
and so we talk about this a lot in terms
of disease but also I wonder what
happens in terms of uh making people
superhuman I mean if you're really able
to Tinker with the genetic code right
the possibilities seem
so what do you think about that is that
something that we're going to be able to
do through AI I think one day I mean
we're focusing much more on on the on
the disease profile and fixing yeah
that's the first step and and I've
always felt that that's the most
important if you ask me what's the
number one thing I wanted to use ai4 and
the most important thing we use A4 is
for helping human health um but then of
course beyond that one could imagine uh
aging things like that you know is of
course there's a whole field in itself
is aging a disease is it a combination
of diseases can we extend um our healthy
lifespan um these are all important
questions and I think very interesting
and I'm I'm pretty sure AI will be
extremely useful in helping us find
answers to those questions too you know
I see Memes come across my Twitter feed
and maybe I need to change the stuff I'm
recommended but it's often like if you
will live to 2050 you're not going to
die yeah uh what do you think the
potential Max lifespan is for a person
well look I know those a lot of those
folks in aging research very well I
think it's very interesting the
pioneering work they they do I think
there's nothing good about getting old
and your body decaying I think it's you
know if anyone who's seen that up close
with their relatives it's a pretty hard
thing to go through right as a family or
or the or the person of course and um
and and so I think anything we can
alleviate human suffering and and extend
healthy lifespan is a good thing um you
know the natural limit seems to be about
120 years old but um from what we know
you know if you look at the oldest
people that that that are lucky enough
to to to live to that age so there's you
know it's it's it's a it's a it's an
area I follow quite closely uh I don't
have any I I guess new insights that are
not already known in that um but I do I
I would be surprised if there if that's
if that's the limit right because
there's a sort of two steps to this one
is curing all diseases one day which I
think we're going to do with isomorphic
and the work we're doing there our spin
out our drug Discovery spin out um but
then that's not enough to probably get
you past 20 because there's some sort of
then there's the question of just
natural systemic Decay right Aging in
other words so not specific disease
right uh often those people that live to
120 they don't seem to die from a
specific disease it's just sort of just
general atrophy um so then you're going
to need something more like Rejuvenation
where you you you rejuvenate your cells
or you you know maybe stem cell research
you know companies like Altos are are
are working on these things resetting
the the cell clocks um seems like that
could be possible but again I feel like
it's so complex because biology is such
a complicated emerging system you need a
in my view you need AI to help to to be
able to crack anything anything close to
that