- The power of artificial intelligence
is it helps us understand very complex systems
that the human brain struggles to do by itself-
and the cell is just such a system.
We've learned a lot over the past decades
about the mysteries of the molecules that make up cells,
entire genomes sequenced, protein structures solved.
But, we put aside for quite a while
the role of physiology of cells, how cells work,
and how they interact with each other,
how they create organ systems.
And now, we have powerful tools to revisit those questions.
We're making a new initiative to build one
of the world's biggest GPU supercomputers
for basic nonprofit research.
And it's gonna reveal a lot about how we develop
as organisms, what goes wrong in diseases
like cancer, neurodegeneration, diabetes.
And we're making a really substantial effort
to understand this in much more detail
and discover, hopefully, new ways to treat disease.
I'm Steve Quake, I'm a biophysicist and bioengineer.
I'm the Head of Science at the Chan Zuckerberg Initiative,
and a professor at Stanford University.
Science kind of goes in waves, and we're just emerging
from the genome and molecular biology age.
We made enormous progress characterizing
what individual genes do,
and how they work together in genomes,
but we have no way to predict from the genome
what makes all the cell types of the human body,
and how the molecules that make them up
achieve their functions.
There's many interesting mysteries still to solve.
One incredibly important one is the immune system:
how we respond to a vaccine,
what goes wrong in autoimmune disease and allergies,
and how the immune system may detect
incipient disease, such as early cancers.
But at the moment, we're benefiting
from an enormous technical revolution in science:
novel imaging techniques, novel sequencing techniques,
the advent of artificial intelligence,
large language models.
These AI models will provide very detailed insight
into how to do cellular therapy,
which is using engineered cells to cure disease.
At CZI, we're investing in novel approaches
to do genome engineering of cells
to do much more sophisticated things
than current cellular therapies allow,
and also to detect disease as it's just beginning to happen.
A large part of my research of the last decade has been
the development of cell atlases.
The cell atlas is a molecular characterization
of all the cell types in the body,
and provides unprecedented detail
in how one cell differs from another,
and how they're changing with age,
development, health and disease.
We got into the making of the cell atlases
by first focusing on individual tissues,
and trying to understand the cellular complexity
of those tissues, particularly in cancer.
And that led us to understand that it would be very useful
to do this across the entire body.
The Tabula Sapiens represent the culmination
of our efforts making cell atlases.
We were able to analyze organs from individual human donors
and do a full molecular characterization of them.
An absolutely crucial tool in making all the cell atlases
is the software CELLxGENE, which was developed at CZI.
It provides a very easy interface
to investigate and analyze complex data.
We're continuing to grow the Tabula Sapiens.
At the same time, CZI has been funding
the creation of individual tissue atlases around the world.
And those are now all being combined
along the Tabula Sapiens into one usable database
that we're making available to the scientific community,
and that's giving us the power to ask deeper questions
about the atlas and the cell types within it.
We're very excited about the promise
of large language models and other approaches
to machine learning and artificial intelligence
to help us understand the mysteries of the cell.
And one thing those models need
is very well curated data sets,
and large data sets to learn on.
And that's what we've been able to assemble at CZI.
We're making one of the world's biggest GPU supercomputers
for basic nonprofit research, and we pulled together
a collection of more than 30 million cells,
each of which has 20,000 genes characterized,
and they've been very carefully expert annotated.
It's great learning material for artificial intelligence,
and we can't wait to see what comes out
of that from the scientific community.
Over the next 20 years, we're gonna see profound changes
in how we do science.
Many of the things that are expensive
and difficult experiments to do now, will be done in silico
by computers using the insights we're gaining
from artificial intelligence and machine learning.
These AI tools will predict what a single mutation does
to cells across the body,
what diseases you're potentially gonna get,
and what will happen as we start expressing different genes
in an artificial way in cells to try
to reprogram them for new functions.
You can imagine many applications
of engineered cells in medicine:
cells that explore the body,
discover tumors in their earliest stages
before they can be detected by conventional radiology,
cells that might explore across the blood-brain barrier,
and discover the plaques
that cause neurodegenerative disease,
and also start to digest those.
The applications of these insights
will lead to earlier interventions, earlier therapies,
and it's gonna be a revolution in medicine.