-: How can artificial intelligence
and generative AI accelerate drug discovery?
Iya, let's start with you.
What are some of the biggest challenges
in drug discovery today?
-: There's different levels of complexity
that manifest their way all the way from the beginning
to how we figure out what the right biology is
to how we test the drug first in humans, right?
The question is how can we tackle that complexity?
What's gonna enable us to learn what we need to do
fast enough to really identify the right treatment
for the right patient at the right time?
-: What are some of the ways you believe generative AI
and AI can help tackle some of that complexity?
-: Well, here's where we are
with biology and drug development.
Twenty years ago,
we were just able to start sequencing the genome, right?
And where we could actually measure every single base pair
in the human genome
and we did it for one person on the planet.
Well, fast forward 20 years later,
we're able to do that now for every single individual.
So we can finally start to collect the data that we need
to learn about our biology
and not just biology in one person
from biology across populations.
And couple that with clinical data,
and couple that with other kinds of measurements,
like our ability to have a cell express
what those genes are doing at different times
under different conditions.
Measure RNA, measure protein, measure metabolomics.
And so the opportunity is
can we now take these advances in AI
but now apply those technologies to this mountains of data
to learn biology and learn what drives biology
so that we can get to better treatments?
-: I think Iya, you nailed it, basically.
Machine learning was already a way to extract information
out of huge data sets.
I think GenAI has been the next step
where it's not just information that you're extracting
but it's knowledge.
And we were sitting on tons of data
and now conversion from data to knowledge is super fast.
But one thing which is super important for me,
and that's why it's good that Iya is here,
because she's a scientist. It's not just about technology.
Science is not dead.
We need scientists who understand biology, microbiology,
using those technologies to get to more powerful drug,
faster, shorter time to the market.
-: So Iya, as a firm,
BCG is very excited about our research collaboration.
What are you excited about with the collaboration
that we're about to embark on?
-: I'm super excited as well.
It's about the convergence, right?
The convergence of science and deep science
and we're talking biological science, clinical science,
with technology, AI, and machine learning,
and even the hardware that goes with it.
Bringing all of this together
and then working in collaboration
to solve hard research problems, right?
-: And Sylvain, how about for you,
what are we excited about as a firm about this?
-: We are super excited because we do projects for clients,
many industries, many things in the world,
many types of projects. But for us,
it's really groundbreaking to start working on a hardcore
R&D project, super hard, as Iya said,
which have a massive impact on the world.
And we have a team, a group,
which is our advanced AI research group,
which is super eager to partner with clients,
not to do projects, but to do research together
on topics that matter. We believe in diverse teams.
So, joining forces between
I would say the top league research team in R&D pharma
and our data science team is a fantastic opportunity for us.