Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2: Look, we've got to talk about the impact of generative
Speaker 2: AI in real life across industries, Biofarmer being one of them,
Speaker 2: and I'm priessed to welcome with the show Paul Hudson,
Speaker 2: CEO of Sanofi, discuss how your enormous French her Farmer
Speaker 2: company has been leveraging the new technology in its operations.
Speaker 2: And yes, there's drug discovery, but also what's so interesting, Paul,
Speaker 2: is you're integrating it within the functionality of your business
Speaker 2: on a day to day basis.
Speaker 1: Yeah, thank you, and it's a pleasure to be here.
Speaker 1: We're really trying.
Speaker 3: To do incredible things for patients and discovering new medicines
Speaker 3: and you know, with AI being the great disruptor and
Speaker 3: all of the excitement last year, the wow of large
Speaker 3: anguige models, and this year for us, it's all about
Speaker 3: the how and how we can get our you know,
Speaker 3: the large amounts of our organization focused whether you're in
Speaker 3: a lab doing expert AI, whether using generative AI in
Speaker 3: regulatory or text driven of our business and importantly snackable
Speaker 3: AI when we're looking at really trying to give better
Speaker 3: decision intelligence for almost everybody in the organization with the
Speaker 3: sole intent of becoming much more efficient effective in delivering
Speaker 3: new meds.
Speaker 1: And it's amazing.
Speaker 2: Really, I love this snackable AI you're using play it's
Speaker 2: a proprietary app. But I've got to ask sort of,
Speaker 2: how have you thought about which underlying large language model
Speaker 2: you should look to. How you integrate this do you
Speaker 2: go to outsourced do you build it from within.
Speaker 3: Pol Well, we're drug discoverers and developers, we're not coders
Speaker 3: at our heart. So we have this first of its
Speaker 3: kind relationship now with open AI, partnership with Formation bio
Speaker 3: translating that for is to make sure that we can
Speaker 3: be customizing large language models to look at drug discovery,
Speaker 3: to try and drug undruggable diseases. To this point, and
Speaker 3: we're doing things that have really never been done before.
Speaker 3: It's early days, but it's extremely promising. And remember there's
Speaker 3: such a large amount of diseases that don't have medsons
Speaker 3: available for them because we simply have not had the
Speaker 3: computing pairer of the opportunity to deploy ourselves. And now
Speaker 3: just now we're at this next great revolution in science.
Speaker 3: It's such a privilege actually to lead a company at
Speaker 3: this point. As for play, our sort of snackable approach,
Speaker 3: we partnered with a small startup out of Germany, a Ley.
Speaker 3: They've been working withthers, They've grown weathers and that's, by
Speaker 3: the way, open for everybody.
Speaker 1: We don't own it, were having to share it.
Speaker 3: We want all boats to rise win healthcare after all,
Speaker 3: and so the more users, the more fun, the more accuracy,
Speaker 3: the more chance to discovering new medicines.
Speaker 2: So have your talent reacted because there's so much do
Speaker 2: mongering that AI is going to take all our jobs.
Speaker 3: Well, I think our approach has been how to weaponize
Speaker 3: our people to do better.
Speaker 1: Like you know, I don't know whether you're familiar with.
Speaker 3: Ways, the driving app, but I see it very much
Speaker 3: like that. I got to get in the car. I'm
Speaker 3: going to start the engine and drive to the end
Speaker 3: of the street. And if Ways says I'm statistically more
Speaker 3: likely to have an easier journey turning left rather than
Speaker 3: turning right, I want that advice as crowdsource large data,
Speaker 3: real time. I want our people to feel they are
Speaker 3: amplified or multiplied in that event.
Speaker 1: In that event too, The goal is not about less people.
Speaker 3: The goal is about putting our people to be more
Speaker 3: effective and to make and to have better decision intelligence
Speaker 3: that in itself gives us a great opportunity to do
Speaker 3: something incredible. And we've only seen huge Appetite's why on
Speaker 3: any given day we have eighteen thousand people in our
Speaker 3: organization using the EI we make available and I think
Speaker 3: that's pretty fantastic.
Speaker 2: Let's talk about doing the amazing the incredible, because we
Speaker 2: have just seen a push up in your share price
Speaker 2: on the day and you've been reorientating this business of
Speaker 2: Sonofye and thinking about more R and D, about drug
Speaker 2: discovery and applicate and look some costly cases in the
Speaker 2: way that you have to experiment do clinical trials, but
Speaker 2: they've paid off today and we think about the drug
Speaker 2: discovery when it comes to a key lung chronic lung disorder.
Speaker 2: Can you just tell us about what that means to
Speaker 2: the business.
Speaker 3: Well, in Europe, just yesterday today we got approval for
Speaker 3: chronic constructive coon me disease. COPD picks a huge number
Speaker 3: of people third biggest killer. We're ready to go now
Speaker 3: in Europe to be able to provide an advanced therapy
Speaker 3: that will reduce their chance to go to hospital by
Speaker 3: a third, and that's a breakthrough.
Speaker 1: And there's been so little innovation.
Speaker 3: We aspire to be the world's leading immnology company, and
Speaker 3: that's partly driven by moments like that that we live
Speaker 3: for in our industry to do things that transform or
Speaker 3: protect patients lives, will prevent disease.
Speaker 1: You know.
Speaker 3: The reality is we're a very proud, huge, big company,
Speaker 3: but we wanted to be at the forefront of science
Speaker 3: again and we've made some big bets, but appropriately so
Speaker 3: to try and make sure our science is some of
Speaker 3: the most exciting and it's first in class or best
Speaker 3: in class. And to couple it with our conversation of earlier,
Speaker 3: the more we add AI, the more we improve our
Speaker 3: decision intelligence, the more opportunity we have to do more
Speaker 3: in that space. And I think that's what's catching the
Speaker 3: excitement in our organization, and we believe we're quite far ahead.
Speaker 3: I mean, of course, we're very responsible about how we
Speaker 3: use AI, but others are still hesitating.
Speaker 1: We're taking our moment, but sometimes you need.
Speaker 2: Good data to feed in to these large language models. Paul,
Speaker 2: what about the data on viruses such as well bird
Speaker 2: flu At the moment here in the UK and the US. Indeed, Look,
Speaker 2: there is a worry that the data hasn't been good
Speaker 2: enough in the United States. Is that something that worries
Speaker 2: you and you need to be developing a new vaccine
Speaker 2: for that.
Speaker 3: Look, I mean we've been through one pandemic. I think
Speaker 3: we've learned a great deal about trying to have the
Speaker 3: best data, and I think we position ourselves to take
Speaker 3: advantage of those opportunities on behalf of society. Frankly, we
Speaker 3: played a part small part in COVID, but we stand
Speaker 3: ready should we be asked the data and it's legitimacy,
Speaker 3: you know. We often that data comes in through government channels,
Speaker 3: through health systems, you know, and we work at real
Speaker 3: time speed to make sure that we have the very
Speaker 3: best data available in terms of large language models and
Speaker 3: the rest of the data sets.
Speaker 1: You know, we collaborate far and wide.
Speaker 3: We have punishes with oak in with ADOM, wise with excyensia.
Speaker 3: We really are trying to make sure that we have
Speaker 3: at our fingertips huge data sets.
Speaker 1: To mean, our accuracy.
Speaker 3: And our predictive capability is far ahead of the competition.
Speaker 3: We won't get it right everywhere, but the data integrity
Speaker 3: of the absolute fundamental start in place. Our relationship with
Speaker 3: open AI and with Formation by It, we're putting our
Speaker 3: own data at play to make sure that they can
Speaker 3: learn from it too.
Speaker 1: Again, all boats your rights. We're in healthcare to do good.
Speaker 2: You're also selling off bits of healthcare because you're focusing
Speaker 2: in on the R and D, the drug side, and
Speaker 2: maybe the consumer business goes for a hefty price tag.
Speaker 2: You've been thinking about IPO and you've been thinking about sale.
Speaker 2: How is that process going poor?
Speaker 3: Well, we announced that October that we were going to
Speaker 3: become a pure play by a Farmer. You know, we
Speaker 3: want to double down on the things we just talked about,
Speaker 3: and we have an incredibly successful and energize consumer business.
Speaker 3: We feel that they feel in fact that they can
Speaker 3: stand better on their own two feet and be independent,
Speaker 3: raise their own capital, take on their own projects, and
Speaker 3: we want to support them in that it's the right
Speaker 3: thing to do. Our capital should be allocated towards discovering
Speaker 3: new medicines, and there should be about growing their business
Speaker 3: fast in the market, which by the way, they're doing
Speaker 3: very successfully. We've declared that buy as early as Q
Speaker 3: four twenty four will be ready to go to separate
Speaker 3: that business. We haven't shared how we will do it,
Speaker 3: but I think it's quite.
Speaker 1: Well known that.
Speaker 3: You know, we're talking to interesting parties, certainly Pe, and
Speaker 3: we have the capital markets vehicles available to us too,
Speaker 3: So no, we're excited for them. There's a huge amount
Speaker 3: of interest. It's a great business and we hope to
Speaker 3: create value for patients, for stakeholders, and indeed for the
Speaker 3: people in the business.
Speaker 2: Q four twenty four is pretty notable given that we're
Speaker 2: in quite a politically uncertain time. Look, we two brips
Speaker 2: sit here looking that there's going to be an election
Speaker 2: and people voting in the UK tomorrow and then of
Speaker 2: course this weekend is all important for France. How as
Speaker 2: a leader of such a French giant, are you feeling
Speaker 2: about the political risk of doing a deal in this market?
Speaker 3: Well, look, you know, in terms of healthcare and being
Speaker 3: a leader of an incredibly important French company, you know,
Speaker 3: our first priority is to ensure that whoever governs, they
Speaker 3: provide a predictable, stable environment. Because research is a ten
Speaker 3: to fifteen year process, so you know, we need to
Speaker 3: think long term. We hope that whoever leads the country
Speaker 3: will think long term. We know the current government has
Speaker 3: been incredibly supportive of innovation and creating that ecosystem. We
Speaker 3: hope that that would continue.
Speaker 1: Of course.
Speaker 3: You know, there are people trying to understand what it
Speaker 3: means for the economy, much like for the change in
Speaker 3: government if it's to come about in the UK, and
Speaker 3: people want that predictability in the markets too. You know,
Speaker 3: we're long term player, trying to do the right things
Speaker 3: for patients, trying to drug the undruggable, and we hope
Speaker 3: to partner with whoever's in power, of course, because we
Speaker 3: have to be ready to do our part for society
Speaker 3: and and you know, so far we believe that can continue.
Speaker 2: Paul, it's been great talking to you the intersection of
Speaker 2: drug discovery of artificial intelligence slackable AI as you call it.
Speaker 2: Paul Hudson, great to have some time. CEO of Sanofie
Speaker 2: say well,