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