May 22, 2025 • 49 mins
“AI is going to be super transformative... we’ve all moved too slowly and need to speed up our integration.” says Houman Ashrafian, Head of R&D at Sanofi. In this episode, Ashrafian joins Bloomberg Intelligence analyst Sam Fazeli to unpack how AI-powered portfolio construction, franchise-based innovation and a long-term mindset are reshaping the pharma giant’s R&D strategy. They explore Sanofi’s ambition to become a premier immunology powerhouse, how the company is applying venture-style rigor to pipeline decisions, and why cultural transformation -- not quarterly earnings -- is the key to staying relevant through 2040.
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Speaker 1 (00:10):
Welcome to another episode of Bloomberg Intelligence Vanguards of Healthcare podcast,
where we speak with the leaders at the forefront of
change in the healthcare industry. My name is Sam Fazelli
and I'm a pharmaceuticals analyst and head of Global industry
Research at Bloomberg Intelligence, the in house research arm of
Bloomberg with five hundred analysts covering two thousand companies and
(00:31):
one hundred industries. I'm thrilled to welcome human Ashrafion, the
head of R and D at santo of It, to
the program today. Who man joined sano of You almost
two years ago after about seven years a short adventure
life sciences where we met a couple of times. Welcome
to the podcast, woman, Thanks.
Speaker 2 (00:50):
Having me Samon. It's exciting to be with an industry
vanguard legend himself.
Speaker 1 (00:55):
Thank you, You're too kind. So you obviously have a
very unique back ground relative to some other R and
D chiefs in pharmaceutical industry, especially as a VC. What
could farmer learn from a healthcare growth equity model, especially
when it comes to portfolio prioritization. How are you approaching
(01:15):
this at ten of you? So I'm really curious to
get your feel on that and your thoughts on that.
Speaker 2 (01:20):
Well, let's talk about the here and now and the future.
And Sam I started the conversation by calling out, you're
provenent in this space. I did it thoughtfully. Your own
journey has been through NIMURA and HSBC and ultimately to
where you are now in the vaunted role that you're in.
And I think your journey reflects sort of where farm
(01:42):
R and the organizations need to go. So I think
there's three chapters to this story. Number one is the
advent of AIML based technologies. Number two really importance of
portfolio construction analytics, and three is about the future. So
historically you and I would have done our models on
(02:03):
an Excel spreadsheet. We would have probabilized, we would have
had a simple discounting, and going beyond that would have
been difficult. Right, So portfolio strategy was very straightforward. I
think the discipline a venture capitalist or a private equity
guy brings to the table has changed that completely. We've
got a more sort of MARKOWITZI and much more profound
(02:28):
sense of portfolio manager, which is something that I bought
to Sanafy. So if you want to think simplistically, you
might think you know you've got three buckets of risk low, medium, high,
and how you attribute value across those. But I think
in twenty twenty five, the application of more sophisticated probabilization,
(02:49):
more accurate AI based costing, milestone analysis, Monte Carlo analysis,
et cetera, allows you to provide a much clearer sense
of the extant portfolio as it is. Perhaps the most
important thing I'll say, though, is how that AI and
portfolio management strategy, which by the way, my group's run
(03:11):
by Helen Mary Arnos, is going is to try and
take that perspective that Warren Buffett and Charlie Munger brought
to the table. You know, it's Warren's ninety fourth year
and he's just stepping down a CEO of Bulkshaway, and
their comment was looking for the future is important. It's
better to be approximately right than absolutely wrong. And I
(03:35):
think that's the job of an R and D chief nowadays,
which is to try and figure out where the apple
is going to fall, to be approximately right and move
your portfolio not only to the hero and now to
deliver what the market expects on a quarter by quarter
earning spaces, but actually moved to figuring out where the
breakthroughs are going to be. So punchline is AI and
(03:57):
portfolio analytics allows you to make a much more informed
sense of where to exercise scientific judgment.
Speaker 1 (04:04):
Great, that's we have a lot of conversation, hopefully if
time allows, on the AI side of things. Now, we
have a common friend Drew Pardoll, who, as one of
his lectures to immunology students, ask them what diseases aren't
impacted by immunology or by the immune system, and his
(04:25):
favorite thing is that most of them start to try
and find one, and he says none. Everything is impacted
by the immune system. So some of he has used
the phrase becoming a premier immunology powerhouse or being a
premier immunology powerhouse. So how are you and some of
you thinking about immunology as a whole. You've talked about
(04:46):
it more broadly than traditional I and I, So how
is this shaping your pipeline approach?
Speaker 2 (04:54):
Yes, so when people do, and I think Drew is
probably mostly right on this topic. He's kind enough to
say that I am an honorary member of the Immunology Club,
which is probably as good as it gets. The answer
is pretty straightforward, and people when you talk about imnology,
particularly to the markets. They think about gut skinning, lung joints, right,
(05:16):
And I think that's perfectly legitimate. If you look at
the bubbles of Tagger related growth in terms of farmer
as it's seen from a snapshot today, those are the
growth markets IBD, atopic dermatitis, ariasis, rhematoid arthritis of the
current darlings. But Drew rightly calls out imminology for reasons
(05:36):
we can talk about related to tissue hemeostasis and remodeling
is the basis of much more than classical iminology. That's
not to say the classical imunology is not interesting and
it's not a high Kagger growth area. It is, but
we need to move to where the apple is going
to fall. We need to go to where the pucks
going to be. We need to skate to where the
puck's going to be. And I think imnology is increasingly
(05:57):
recognized to obviously underpin oncology you've referred to Drew already
one of the founders of that field, but also increasingly
in terms of ophtalmology. Even Obasti ten years ago, if
you went to a conference instead Obesti was driven by
a minology. Apart from a few luminaries like go Counter
Nashcalil at Harvard Med School, you'd be laughed out at
(06:20):
the conference. And now most people are arguing that GLIP
one resistance or recrudescence of altered satiety subsequent to glip
or increte in cessation is rated to the persistent low
level inflammation that you see. So I think the punchline
to your question, but I think Drew Bride and as
(06:41):
an imminology powerhouse, we have insights, asymmetric insights that allow
us to go into adjacencies.
Speaker 1 (06:49):
Right now, we will get to the pipeline a little
bit more. But if you wanted to just list your
top priorities over the next five years, as you consider
what you've just been saying to us, where do we
want to be in five years time in general? And
we'll get to the nitty grity in a minute.
Speaker 2 (07:06):
Yeah, I think that maybe to give you a short
answer to that, I think the history of the pharmaceutical
industry has been characterized by individual assets. We've all got
pretty good at building a depiction or a kid truder
or on a tourist statin or on a metprosole or
ascimetidin and I think the and I've missed out a
(07:26):
bunch and apologies to the very great many drug developers
you've developed single assets. It's been awesome. I think what
we need to do and Santa Fe's moving moving to
as I've come to Sanathe is a franchise based thinking
right to be able to capture again asymmetrical contrarian insights
one scientifically two to give payers and providers, healthcare providers
(07:53):
an HCP's confidence and to give patients confidence and to
benefit from from that confidence and trust. I think we
need to start working in franchises. And what you're going
to see from sama Fie is that rather than talk
about individual assets, and I try and avoid talking landividual assets,
we're going to be supporting patients in asthma for their
whole life, irrespective strata they sit in. We're going to
be supporting patients with type two skin and other inflammation
(08:16):
for their whole lives, irrespective of where they sit, whether
it's an oral, whether it's a biologic, whether it's a
multi biologic, whether it's because they're there a responsive or
whether they're in combo. We're here for them at least
to the end of my career, and I suspect much longer.
Speaker 1 (08:30):
I mean, one value that you get out of that
immediately is that once you come within new product for
a subgroup of those patients or a later stage of disease,
is that you don't have to go and reinvent the
wheel in terms of marketing and selling it and finding
the patients and finding the physicians, et cetera. How much
is that part of this equation?
Speaker 2 (08:50):
Yeah, I mean, I think there are really thoughtful commercial
opportunities that play out if you're already an incumbent and
a space, and those are really well established. I won't
go into pricing and switching and various other things which
definitely help. But actually I think size of field, force,
(09:11):
core points, etc. But I think that's missing the point.
And actually in Sana Fee we don't talk that way.
It may beggar belief for listeners, but actually our focus
is as a tiebreaker. The patient's always the focus on
what we do, and for me, it's more about the
insights you learn from your clinical trials, the biomarket strategies,
(09:31):
and the genetics you develop, which allows you to understand
the patient better. And one thing we never talk about
is sam no one will talk about in any of
the interviews you do, is the important and medical affairs,
that iterative cycle between what you learn from the healthcare
provider and patient at the could face, often not in
tertiary centers, but also in community practices about the needs
(09:53):
of the patient, which is now in the way we've
built R and D fed back into research, is what's
going to be transformative. So yes, of course advantages, but
much more the insight to get from patients are valuable.
Speaker 1 (10:04):
Now. Part of building a pipeline and a portfolio is
that you can't do everything organically. Some of that come
from business development. So what does what dynamics play into
the decision of in licensing versus trying to go in house?
How do you judge that?
Speaker 2 (10:20):
Well, two comments. I VC and a biotech founder, and
I have the highest respect for people outside the company.
We shouldn't be complacent. We recognize that we know some stuff,
but there's a lot of stuff we don't know. Let
me give a single SoundBite for people to go away
and think about. I grew up watching mars Ink, mass Infectionery, etc.
(10:44):
Buy companies and they were of course they were a
private company. But they were butchered initially because they were
paying thirty five XP ratios and people were say, how
are they going to make money off? This makes no
financial sense? Well it wasn't true. Mars had an asymmetric
insight into those marketplaces that allow them to thoughtfully underwrite deals. Now, Salafy,
we're extremely financially disciplined. It's a core pillar of our
(11:10):
history of acquiring three hundred companies and being a conglomerate.
But I think that the principle holds, which is, as
you focus on franchises and we have a limited number
of thas that we're in, it allows us to have
an asymmetric insight based on our own data. Remember, the
concept of data is going to come up more frequently.
(11:30):
That allows us to underwrite a different not only quantum
but shape of deal structure. And I hear more and
more from people the excitement of working with semotheis and
the capital alone, but is the insights we bring.
Speaker 1 (11:43):
So would you say that you're or not that you're
more interested in asset level deals or platform level deals.
Speaker 2 (11:50):
I think it's a misnomer. I think this is a
we spent you and I've spent twenty years, made twenty
five years talking about this. I think it's a misnomer.
It depicts in the function of an asset or a
platform relationship with Regeneral, it's both. So we're not ecumenical.
We're non ecumenical. Will will will go to the mat
for whatever fits with the broader portfolio strategy. And I
(12:13):
want to keep saying and it will come back. It's
our job, as I hope one day we will be
in every way the premier pharmaceutical company in the world.
The European company has some legitimacy to aspire to that,
building the right shape of portfolio construction and ensuring that
(12:34):
we're at the bottom of every tree so that when
an apple falls, whether it we catch it on its
way down or that we're the first people to pick
it up. That's what buys us legitimacy. So the answer
to your question is whether we do it internally, whether
we do it externally, whether we do it in partnership,
whether we do it through equity, or whether we do
it through media, M and A. We need to be
(12:56):
able to look in that crystal ball and make enough
thoughtful bets.
Speaker 1 (13:00):
As an XVC, are you the type to go after
when a new technology idea appears, micro, an A, r ANAI,
whatever it is. I mean, those are not new anymore.
Are you the type to go after them right at
the beginning or would you rather wait and see a
couple of inevitably failures. Yeah.
Speaker 2 (13:18):
I think once you've got a water tight portfolio construction,
have a really well mapped out risk strategy, which we
do now. By the way, it took me a bit
of time to put it in place, but actually the
discipline is not putting it in place. It was about
people adhering to it. We have the right to take
some low bet likely blockbusters, but also some potentially transformative bets,
(13:41):
which well, I'm sorry, I don't like the verbs parier
in French. The notion of betting is not something that
I'm prone to. It's we are. I'm an investor, and
we're making thoughtful investments to ensure the portfolio gives you
those extremely low odds. But transformative alpha versus something that
(14:04):
gives you, you know, less alpha than it allows you
to continue operating.
Speaker 1 (14:09):
When you're in a VC. You know, Short Adventures was
your last post. I think you have a small group
of people who work with the money is committed, you
make a decision, you do it. Vast organization at Sanafi.
How much culture shift was needed to get to this point,
if any? And have you got to that point already
(14:32):
in terms of being nimble, identifying ideas and getting everybody
behind it.
Speaker 2 (14:38):
So three quick comments on that. Firstly, complacencies are enemy.
And I think that the notion that wherever perfect is ludicrous.
So we're always a work in motion. I should call
out Paul Hudson my erstwhile partner CEO in this project.
And actually the work started when Paul in twenty nineteen
became CEO and implemented a cultural mindset where we played
(15:04):
a win. And neither did that mean playing in its
conventional sense, nor did it mean winning in a narrow sense.
But Paul had started the journey on the cultural change.
And I think he that, you know, because of a
focus on all sorts of other parameters, Paul's genius in
making the cultural transformation has been vastly underestimated. He is
(15:27):
a brilliant man of visionary not a scientist, you know,
not a not a classically trained person in these arts.
But his intuition and his perfection and making the culture
change have been really, really, really robust, and I hope
someone writes the book, maybe me one day about it,
so that that was the start of the journey. And
I hope that since ide come in bringing in some
(15:50):
of that portfolio and financial discipline, but also the culture
of recognizing the ones. We've got a portfolio in place,
you can take, you know, some lower risk investments and
some higher risk investments, because that's what a portfolio looks like.
It is important. One comments the problem is that I
think most companies today shackled by their quarterly earnings in
(16:15):
year to year growth, and of course everything's top line
and pipeline. But I think the real trick is to
take the twenty forty perspective, and I think that's a discipline.
We brought some of it.
Speaker 1 (16:28):
Yeah, that's a tough thing to do, given that you
still have to do quarterly reports. But as analysts, we
all wish that the quarters could stop and the very
most get a half half yearly. But anyway, now, China
is an interesting area. There's you know, I've just been
at AACR, at the pre meeting at ACR. Lots of
China details, et cetera. One of the sessions I went to,
(16:50):
which was a d c's and cell therapies or immuno therapies,
four out of the eight were China assets or originated
from China. So it's clear, and I think most people
agree on this that there's been a lot and an
amazing hockey stick evolution in Chinese science. Now I'm worried
(17:11):
that my vision is tainted by the fact that I
am quite a lot highly focused on oncology at the minute.
And do you feel the same when you come at
it from a broader perspective? Are you seeing the same?
I mean, I'm looking at the number of deals you
guys have done in China versus other farmer companies. It's
not at the highest end, it's more of the at
(17:33):
the lower end. And in fact, couple of them were
tech and AI related deals, which sedgeways straight to the
next topic. What do you see there?
Speaker 2 (17:42):
Yeah, So let me start with perhaps the most important point,
which is, you know, my perspective is the innovation arises everywhere. Again,
I think we have such a short term perspective on
the world. John von Neuman, the innovator of AI and mL,
was Hungarian mass infectionery came out of the Midwest. Morris
(18:05):
Chang's t SMC came out of Taiwan, which went fabulous
on chips when there was no nothing else of that
sort in Taiwan that we're making substantially plastic. You know,
my job as a head of R and D, as
an executive committey member of sanafe's to look for innovation
wherever it is. So let's just jump to China. So
I you know, my only piece of advices. We all
(18:26):
we all swing between fads, and we just need to
we need to take that. You know, I think it's
calming to the human spirit to take the twenty forty perspective.
And remember the notion that by the way, Sam a
countrymen of ours got inscribed on a ring. This two
short pass. We need, we need a bit of stability.
(18:47):
Sanity will be seeking innovation anywhere in the world for Rauther.
So let's talk about China. China is hugely important, right.
The US is our principal market today and I think
for the foreseeable future will remain the principal market for
for and actually a major source for innovation. There's nothing
that's going to change out. We've got large offices in
r and the offices in Boston, and I'm excited to
(19:07):
do that as well as in Europe. But China is
the you know, the second largest and will continue to
become the second largest pharma pharmaceupermarket in the world. President
she two five year blocks in a row is supported
that healthcare is a major national strategic opportunity. You know,
forty two percent of the deals this year innovative pipeline
(19:28):
deals were done in China. You know, although they lag
behind in terms of clinical trials and they're doing three
point two percent of clinical trials, they continue to produce
the greatest number of engineers and scientists anywhere in the world,
and funding has been there to support it. Those facts
are important because I think it's important to recognize a
(19:49):
that China's overinvested in salan gene therapy, and I think
that at ADC's the certain technologies it's overinvested in. I
think there will be a rec libration of that, especially
as access to capital is diminished in China. But there's
no doubt that today China is producing fast followers, and
there's no doubt that speed and scale of the market
(20:12):
that China provides particularly with engineering and STEM graduate means
it's going to move very quickly in the next five
years to first investing class drugs. My view about Santafe's
position is that the market should be very careful how
it interprets our movement in China. We've been very quiet.
It's not our way, it's not the written way to
shout from the rooftops about what deals we do. You
(20:35):
saw we did a couple of deals with helips On recently.
We will do more in China. I've got a fairly
large footprint in China. It will continue to grow. We're
excited about rebalancing R and D investments. And one thing
I should say to you is again, people forget this.
We've been in China for four decades. I've visited China
(20:55):
three times a year. Since I've been at Santa Fe,
I visited the US equal or more. The message you
should take away from me is we're going to do
our work in the US. We're going to do our
work in China. The opportunity for a company like Salavi
is to genuinely benefit without borders for any innovation from
wherever it comes.
Speaker 1 (21:15):
Right, So let's talk about AI and technology. Of course,
it's a buzzword if you want to say that. Every
company I talk to they say, look, we've been doing
machine learning this kind of work for a long time.
You know. I attended an AI session at ACR again
where a gentleman who had been developing protein folding back
in twenty late two thousand's early to twenty tens was
(21:39):
talking about his model. Of course, alpha folder has become
the one that everybody talks about. So accepting that that
this is not necessarily new, there are elements of AI
that are new large language models, gen AI agent ki
so AI from what I understand, at every level is
changing direct development from the chemistry, from a biology, from
(22:01):
the clinical trial organization, patient finding it, et cetera. How
is it disrupting the R and D model from your perspective, disrupting,
not necessarily obviously in a positive way, I hope, right,
and as relative not just to Fharma but generally. And
how do you think this will continue to evolve? I'm
really interested in this part in the next five and
(22:22):
ten years.
Speaker 2 (22:23):
Okay, so let me start by saying, I'm an AI groupie.
I when I was a kid, as I told, as
I said to you, John von Neuman and Emmy at
were at the top of my mind. You know that
who defined the architecture of the current computer. I was
super excited. I was in my early teens. I was
(22:44):
excited about people talk about Turing. I was interested in
Gordon Welschman's decryption using the Amigant machine. I'm a group
and I think AI is going to be super transformative.
I'm on record saying that I think that all of
us have moved too slowly on AI, and we need
to speed up our integration about what we do. But
I want to provide one caveat before we get into
(23:07):
the you know, the hype phase of AI. And I
think we should be in hype phase. I think, remember,
I want to go where the apple is going to fall.
I think it's a complete error. It's a contempt for
us to wait and depart in. We need to go in.
We need to go in hard, will make mistakes, It's okay.
But my qualification, and this is an important qualification. I
(23:27):
think if you talk to the open AI, if you
talk to the ilias, if you talk to the people
who were there early on, in attention is the key
they will tell you. And you know, that whether it's
R and n's or a whatever network.
Speaker 3 (23:46):
Structure you build, most of these technologies were built for inference.
They were built for correlation, right, And that's okay if
you want to figure out which movie is going to
take over the world, or which toothpaste is going to win,
or which hamburger is going to emerge, which flight is
(24:08):
going to be the most popular.
Speaker 2 (24:10):
And I use those examples because Jason Wang of Nvidia
use those examples when he was talking about the importance
of inference. Correlation often doesn't play in our favor in
our world in terms of true innovation, because it is
that causative leap that's critically important. So that the disclaimer
is that where AI is going to make its greatest
(24:32):
contribution in biopharma is where correlation is adequate and is
less likely to be productive, where causation is the problem,
and that arrow of causation is going to continue to
daunt us. So let me let me just be clear
for the SoundBite. It's important. It's AI is going to
transform where we do correlation. It's going to be less potent,
(24:56):
I think, where we do causations. So your question was
what's it doing today and I'm going to give you
the punchlines and then we can get into some detail
and where is it going to go in five to
ten years. Where it's going today is the bits where
correlation helps, right. It unequivocally can do huge things in
terms of designing, copiloting, trial design, in terms of ensuring
(25:20):
that we recruit in the right sites, ensuring that we
can transition between sites, maximizing rates of recruitment, document writing,
medical writing submissions, etc. And that will transform drug development costs.
It will dramatically reduce costs, streamline or reduce time, particularly
in the back end. It will help with personalized medicine
(25:42):
because of course those correlations are what personalized medicine is
predicated on in terms of which patients will develop which drugs.
And unequivocally, even a complex healthcare system like the US
will be helped in terms of health inequalities. And we
are moving to ipowered solutions across all these things, including
our commercial bits. I think that bar to going to
the next level in terms of its impact on discovery
(26:09):
is going to be harder. It will contribute to reduce
some cycle times in discovery, there's no doubt, but in
terms of that inductive creatively, I think it's going to
be harder.
Speaker 1 (26:21):
So that's great. There's so much in what you've just
said to unpack. We could do a separate podcast on it,
but let me just get to this point. So, in
terms of the elements that you said, patient trial design,
patient recruitment, et cetera, document writing, I fully get that
when it comes to biology, target identification, faster drug design.
(26:42):
I think I heard you say that at the very least,
it helps to speed things up, but not necessarily be
the originator of the idea at the moment. One of
the things that seems to be especially at that that
point a bottle neck and I want your yes or
no on it, if you like, is that the world
(27:02):
data that's available out there is pretty much driven by
positive trial outcomes positive experiments. The negative experiments that who
man may have done in the lab, as Ellie may
have done in the lab, et cetera, don't get published.
You hear about them when you go to a conference
and sit next to you somebody, or you have it
at the dinner or whatever. So the negative outcomes now
(27:25):
generating hypotheses using AI based on the common knowledge that's
been published. Therefore, has a risk. Do you see that
as a risk or do you think that within the company,
given the data that you have access to, you can
fix that.
Speaker 2 (27:40):
Yeah, So three comments. Firstly, your listeners won't know that
you did your first degree in Cardiff and that's where
you first did your experiments. A big call out shout
out to Cardiff University for its most famous alumnis. Moving
to the answer to your question. I don't think there's
a monotonic answer to your question. I think there are
certain discipl in which we have adequate data or approaching
(28:02):
adequate data to answer the question. No one's doing autonomous
trial design at the moment, and I think it's somewhere away,
but there's vast amounts of data to help copilot some
of those designs. Right. I wouldn't recommend you do it,
but you could download all of clinicaltrials dot org and
have some version of a thoughtful clinical trial designer. There
(28:23):
are real challenges without approach, by the way, So there
you may have data in terms of trial design. But
for example, as you said, let me give you two extremes,
can you optimize child design? Probably and that people are
trying today. Can you predict the outcome of phase two trials.
In the phase three that's where your problem becomes real, right,
(28:43):
because there's an ascertainment bias, the selection bias where the
negative trials and the trial data is substantially less well represented.
So there are some areas And the last thing is
and sam This is a subtlety that probably doesn't come
out in podcasts Normally, there is an uncertainty and no
one's captured this. How much data do you need to
(29:06):
answer a certain version of complex question? Right? And we
don't know the shape of surface of data quantity you
need to match to a particular set of problem, right,
That epidemiological uncertainty is going to dog the application of
a I'll give you a simple example when we think
about digital twins, how much data do you need to
(29:28):
contend with a complexity of cellular biology? While that's a
holy grail for all of us, no one knows do
you need all the data that's in the universe You'll
never get there, or do you need data from a
million ipss of each cell type? And that level you'll
only know when you know.
Speaker 1 (29:46):
That's a problem. It's the unknown in terms of just challenges.
Before we move onto a pipeline specifically in the AI space,
coming really up to the helicopter view from it, there's
two issues that I want to and maybe there's others
that you would like if at an organization you're not
I'm assuming just full of lots of humans who have
(30:07):
as a child, we're interested in technology like that, right,
there's normal people, if you want to call it that,
who have other interests who maybe find it tougher to
switch to using CHGPT in their systems. So how much
of a culture shift where are you on that? Continue?
Number two is if you're using a lot of in
(30:28):
house data for some of the work that you're doing,
how much of it is actually available and how much
effort do you have to spend on making it available
to systems to understand the US And lastly, we come
back to the final question that I ask you about
the three areas that I'm hoping to you'd be able
to give me a feel for impact.
Speaker 2 (30:46):
Yeah, So the number one is, thank god, there is
you know, I think some days or maybe every day,
and it's trying to feel laments, there's a whoman in
the organization, and thankfully then there's much more reasonable people
throughout the world organization. You know, it's a journey. It's
a journey for everybody. It's a journey. You know. I
walk in and see my son who's eleven, who, by
(31:08):
the way, wants to be an investor, and he on
a Saturday morning has four Yeah, he has four lms
open and he's co prompting from the lams. You know,
it's we're all on a different stage of our journey.
We've started that cultural translation. I've already referenced Paul's importance
and I don't I'm not a person who believes in
(31:29):
the culture of the CEO. It's not shouting out Paul
because he's the CEO. I'm notoriously independent in my thinking.
But he has started that cultural journey, which I think
is important. So we're on a journey. People adopt things
at different rates. We have many people in the organization,
tens of thousands on their smartphone have an AI app
(31:52):
which allows us to look end to end in the organization.
You know, I have people at two o'clock in the morning,
you know, asking me what about sales of a particular
drug in Australa. You know, what's the basis of changes
in those sales? So there is a democratization of some
AI that's a sort of snackable AI, whereas we have
some much more complex, sophisticated expert AI where an individual
(32:12):
in the organization will or five individuals in the organize,
you know, the cry o m AI structural piece, and
then everything in between. You know, we've got we've got
our relationship with open a formation bio for bringing together
stuff for clinical development. We you know, we've got stuff
in Germany with a biomedex relationship. There's vast amounts of
(32:33):
we've got a relationship with okin. We you know, I
think it's a mistake to consider it in the same
way that if I said to you, do people use apps?
It's a mistake. You know, my my mother or my
father who's in his nineties now will use what's app
but sidely it's not on TikTok or Instagram. I think
what I think the only important thing is to start
(32:54):
everyone on that journey and ensure that you're incentivizing people
both through the technology but also through more conventional incentivization
techniques to embrace this technology. It's about workforce planning and
skill development. But we've started that journey. We we we've
made mistakes. We'll make more mistakes, thank god, and we're
learning from those mistakes.
Speaker 1 (33:15):
That we move forward another data front, Well.
Speaker 2 (33:17):
We use the lab books now, the physical lab books.
We're gone even before I king, thank god, we use it.
One is no one is good. I think we're all
early on in that process. But certainly we use a
combination of proprietary data and data in the public domain.
There is literally a whole podcast and we probably shouldn't
go into it now about how you know tag data,
(33:39):
graphing nodes, how you optimize the use of data and
data architecture, and perhaps most importantly, following the raise policy.
You know, our AI se to ensure that the data
is used responsibly thoughtfully. This data governance you'll have seen that.
And I never talk about competitors, but I don't think
(34:02):
this is a competition issue of JANJ announced to three
weeks ago that they were curtailing vast numbers of the
AI projects because they had, you know, there was a
conflagration of AI projects and both cost and time and
compute and cloud were a real issue. I think what
you're going to see when you talk about data is
there can be better than the governance.
Speaker 1 (34:23):
In terms of three areas probability of success, time to market,
speed to reach peak. Those seem to be the three
areas where if you could make an impact, you would
increase the NPV of a product. Added fourth one if
you like. I couldn't think of another one, of course,
size of the market. But if you wanted to put
(34:46):
an impact factor on each odd of ten, probablyative success,
time to market, speed to reach peak, all the ai
that you know, which one of those, how would you
rank those out of ten? For PROBERTI of success impact.
Speaker 2 (35:01):
That we have three problems in our industry, really only three,
and they map onto your comments, right. We have industries
take a long time to get from idea to peak sales.
We have a high attrition rate, and we're highly regulated,
which isn't reflected in your comment. That's that there are
only two other industries that I can think of that
face our problems. One is oil and gas. That's use
(35:23):
the same words that we do to describe, you know,
independence versus large players. Pipeline, They use discovery them be
in drigging, digging holes, development which they mean is the
door riggs, and defense. And if you talk to those guys,
they really do believe that AI is going to impact
(35:45):
on all three of those. So I think that we're
going to see the next generation of farmer company, which
is AI powered to contend with all those three parameters.
And what you'll see if they do, you'll see top
line growth brether than twenty Your CPS growth go bananas
because of the efficiency, and you'll see the free cash
(36:08):
will increase because the investments required per molecule will diminish.
I think they will translate into the three parameters you've
got also regulary success, but they'll translate into better financial parameters, and.
Speaker 1 (36:21):
The efficiency comes across the board manufacturing supply chain hr ALL.
Speaker 2 (36:27):
I mean, they're already coming, it's not the Only question
is whether big organizations can adapt quickly or whether the
nimbleness of smaller organizations will mean that either we have
to buy in technology or will be disrupted.
Speaker 1 (36:39):
Let's talk about pipeline. What I'm not going to do
is what we do on a cell side call is
dig into every single molecule or at a conference where
you can go wild on the details of trial outcomest.
There is a question in my mind. I'd like your view,
and then we'll talk about where you fit on that.
So we've had of the past twenty thirty years, we've
(37:02):
had drug classes that become massive. Let's go back to
the antascits. Then we had the lipid lowers. Then we
had the TNFS. I might miss something along the way here.
Then we had the the TNFS. So with the roarthritis,
et cetera, orb CIT is now currently the way that
we're thinking, what's the next one?
Speaker 2 (37:23):
Yes, the first that you did miss io by the way.
Oh sorry, of course, but it's hard to predict what
the next one is going to be. But I think
the obvious if you think about the evolution that you've described,
you went from the symptom modification to disease modification, and
acid to disease modification. If you think about the latter,
(37:44):
whether it's statins for secondary and then primary prevention. If
you think about inn oncology, if you think about even
some of the larger anti inflammatory drugs, they went from
symptom modification to fundamental alterations in the course of disease.
Speaker 1 (38:02):
We did go from old old style drugs to immunology.
I think we did right.
Speaker 2 (38:07):
We did. We went from we went from drugs that
were identified in phenitipic screens. You know, at my first
year at med school, we're still looking at intestinal organ
baths where we threw stuff on and worked out through
radiation competition experiments activation and inhibition properties the receptors. Right
even though we you could do that experiment without even knowing,
(38:28):
you know, what the nature of those receptors were. And
now we're going into disease modification. So I think that
with all due humility, I think that what you're going
to see is the greatest scourges of our society against
and I'm not talking about climate health or any of
the man made stuff is. It's going to be mental health,
neural the generation and consequences of chronic disease, and those three.
(38:51):
And if we don't solve those problems, we will be
you know, the society will will collapse. Right if we
can't deal with a scourgeon your generation, or mental health
and or chronic disease, that's going to be a problem.
And Sam, before we lest we forget you know the
fact that mankind has been able to impact on cystic
(39:12):
fibrosis or I understand THH two inflammation and impact on it,
or create a three enemy that chip makes me hugely
optimistic that we can deal with those problems.
Speaker 1 (39:23):
And of course respiratory I thought is one of those.
Speaker 2 (39:26):
Yeah, I think we're already just.
Speaker 1 (39:27):
Starting to treat the underlying causes that it's been symptomology, symptoptology.
Speaker 2 (39:32):
Yeah, I think that's completely true. I think that when
you look at, for example, I try and avoid being
self serving, when you look at our molecule and malytilla map,
which please don't forget, I'm the biggest fan of depictions.
It's the reason that many of us in part are
here today, and it's the molecule that validated the THH
(39:54):
two inflammatory intervention. We will, we will grow and commit
to depiction until it's very long, stand far beyond. But actually,
when you begin to semolgules like a little map that
come into the space which have post drug cessation, way
after months, many months, after five half lives have disappeared,
you know, durability of disease responds a massive association between
(40:17):
PK and PD. It gives you optimism that actually you
can interfere in the march your early disease modification of allergy.
Speaker 1 (40:27):
Of course, with spiritually fitsy chronic disease issues right, because
that's what it is. Yeah, So if we look at
some of this pipeline, where do you think the market
this is one of the favorites of some seal side analysts,
which I actually enjoy listening to. Where do you think
the market underestimates and this underestimate the potential of your pipeline?
Which which area if you want to call it a
(40:49):
drug or a pipeline drug, or a disease area or
or as you were saying, it's not that it's about
treating a patient through the entire Yeah, I.
Speaker 2 (41:00):
Think there's been a systematic discount. And I say this
with humility because I have the highest respect for the
cell side analysts and for our byside in general. But
I think there's been a and we've got to earn
the right. I'm all good with I told you I'm
taking a twenty thirty, twenty forty perspective, will prove I'm
okay with people saying prove yourself. I'd never step back
(41:22):
from proving myself. And I feel incredibly committed to Sanafie.
But I think we have a systematic discount. You can
see that in our pe ratio. We have a systematic
discount compared to our level of innovation. So I think
that if you ask me to call out one space,
I think that we've built very substantial capability in pipelining
(41:46):
products and the sels. I don't really know how to
valuate those assets, right. They predominantly value things in our
models on the lead indication and how they discount lcs
is problematic. Now, I remember in depiction, we're on indication
seven and we're going to keep going, and then each
(42:07):
indication is a multi billion dollar indication. So I think
I think, rather than talking about in each individual space,
the two things that I think the cell side currently
discount and it's down to us to work with them
for them to understand us is one they discount individual
molecules do They think very much about product indication, But
they also discount franchise based thinking, right, and the halo
(42:28):
you get the intangible which you can't put into your
model on physician trust and therefore use within a franchise.
Speaker 1 (42:37):
In our last couple of minutes here, human personally, I'm
happy to talk about politics, but in general, what we're
interested in policies, things that impact and things that you
can measure against saying okay, there's a new policy. What
are you seeing that worries you? And what are you
seeing that you think is an opportunity? You can take
that in the US, Europe, anywhere you like. In terms of.
Speaker 2 (43:01):
Nothing worries me. Actually, I was lucky enough to be
an immigrant to the UK and I'm always inspired by
the global innovation community. So you know, I think again,
this too shure past. We spend our time worrying. I
think all of this stuff is an opportunity. You just
got to find the opportunity and leverage it. You know, Honestly,
(43:23):
when I go to bed at night, my I don't
spend my time sweating. You know, we're as a company
not supportive of tariffs. We think the tarif's create attacks
for everybody. They generate complexity and innovation for people. But
the truth is that the world is always changing. You know.
My background is an immigrant reminds me that nothing stays
(43:44):
the same. And I, with a due humility, believe that
we've created such a strong pipeline, such a massive group
of talent, and every day I thank myself, I thank
the world and thank the team that we've got the
talent that we have. We continue doubling down on talent.
Think our job is to make Sanafe resilient and actually
(44:04):
go to where the skate to where the punt so
punchline is. I'm not worried. I think all of this
represents an opportunity for us and as a Sanity leadership team,
and every member of the company is up for that challenge.
Speaker 1 (44:16):
I hope folks realize that you've actually said in between
the lines, you've said a lot more than than perhaps
is obvious. But in these last comments with regards to
the price differential, healthcare provision differential, innovation differential, they're all
related between the US and Europe. Now we know there
(44:37):
are things going on in the US which one worries
might impact the future of innovation there in the longer term,
in terms of grants being cut, budgets being reduced, et cetera.
How do you what is the solution there? One side
is saying we need to bring US drug prices down
to perceived US drug prices, right because I know, we
(44:59):
all know there's a issue between the list price and
net price, et cetera, down to what's what the Europeans
are paying for instance. On the other hand, some executives
have been saying no, no, no. The problem is is
Europe they need to raise their prices. So I'm not
going to ask you to take your position on this,
but what do you think the solution is?
Speaker 2 (45:17):
Yeah, So three comments. Number one is you said the
most important comment that you made is perceived and it's
not just gross and net prices when people If people
took time to understand the shape of pricing in Europe
versus the US, the gap is much smaller than has
been publicized. And indeed, in some sectors the US gets
(45:40):
access to drug on a cheaper basis than Europe or
other places. So number one is, I think it's a
bit of a misnomer to talk about prices in a
simple sense, and I think one of our jobs as
and industry is to educate the world is to where
pricing differs. But the US that's get access to drugs
(46:00):
in some courses at very similar prices or with very
many with very minded difference. Number two is I do
think that as a europe we need to step up
and pay for innovation or the natural consequences that Europe
won't get access to innovation. And I think there's definitely
that message, not all parts of the Europe. Not all
(46:22):
parts of Europe are the same. Right, we have to
recognize that Europe is a common union with and to
be celebrated variation. And then finally, remember we're here forever.
Santafie's aim is not here to solve problems today and tomorrow.
We're here to solve problems over the next twenty years,
and our only motivation that is to generate value for patients.
(46:45):
And I'm particularly confident that with the management team that
we have today, we are resilient enough to be able
to flex and strain to ensure that whatever the regimes
turned out to be, that we will do our very
best work with governments in all the world, whether they're
developed truands and developed to generate drugs that will transform
(47:06):
a lot of mankind. That's why I went into medicine,
and my goal hasn't changed.
Speaker 1 (47:10):
Well, man, you know that I could sit here for
hours talking to I know for sure that you have
much better things to do. So I appreciate your time
and really nice to catch up with you again, and
I look forward to seeing you at some point.
Speaker 2 (47:23):
It is increasingly rare when you look at the industry
that people who've come from the analyst side have the
experience you have. There are a number of other people
in the industry with the same kind of experience that
are being exited or exiting now. It's an incredible privilege
for the industry to have siting on the analyst side.
(47:44):
And I know that's not exactly where you said anymore,
but to have thoughtful commentators that can tease out the
key question. I think your listeners should know that that's
a privilege that might not be here forever.
Speaker 1 (47:55):
That is very kind of you. I know a whole
host of other people who I believe qualify for execus
the same commentary. But I appreciate that, and I think
on that note, given you've made me feel a million dollars,
we can we can end the podcast, and I want
to thank you again for your time and look forward
to repeating maybe in a year or two, to see
where we've got to like you. Thank you. M m.
Speaker 2 (48:27):
M m.
Speaker 1 (48:31):
M m
Speaker 3 (48:41):
M m
Welcome to another episode of Bloomberg Intelligence Vanguards of Healthcare podcast,
where we speak with the leaders at the forefront of
change in the healthcare industry. My name is Sam Fazelli
and I'm a pharmaceuticals analyst and head of Global industry
Research at Bloomberg Intelligence, the in house research arm of
Bloomberg with five hundred analysts covering two thousand companies and
(00:31):
one hundred industries. I'm thrilled to welcome human Ashrafion, the
head of R and D at santo of It, to
the program today. Who man joined sano of You almost
two years ago after about seven years a short adventure
life sciences where we met a couple of times. Welcome
to the podcast, woman, Thanks.
Speaker 2 (00:50):
Having me Samon. It's exciting to be with an industry
vanguard legend himself.
Speaker 1 (00:55):
Thank you, You're too kind. So you obviously have a
very unique back ground relative to some other R and
D chiefs in pharmaceutical industry, especially as a VC. What
could farmer learn from a healthcare growth equity model, especially
when it comes to portfolio prioritization. How are you approaching
(01:15):
this at ten of you? So I'm really curious to
get your feel on that and your thoughts on that.
Speaker 2 (01:20):
Well, let's talk about the here and now and the future.
And Sam I started the conversation by calling out, you're
provenent in this space. I did it thoughtfully. Your own
journey has been through NIMURA and HSBC and ultimately to
where you are now in the vaunted role that you're in.
And I think your journey reflects sort of where farm
(01:42):
R and the organizations need to go. So I think
there's three chapters to this story. Number one is the
advent of AIML based technologies. Number two really importance of
portfolio construction analytics, and three is about the future. So
historically you and I would have done our models on
(02:03):
an Excel spreadsheet. We would have probabilized, we would have
had a simple discounting, and going beyond that would have
been difficult. Right, So portfolio strategy was very straightforward. I
think the discipline a venture capitalist or a private equity
guy brings to the table has changed that completely. We've
got a more sort of MARKOWITZI and much more profound
(02:28):
sense of portfolio manager, which is something that I bought
to Sanafy. So if you want to think simplistically, you
might think you know you've got three buckets of risk low, medium, high,
and how you attribute value across those. But I think
in twenty twenty five, the application of more sophisticated probabilization,
(02:49):
more accurate AI based costing, milestone analysis, Monte Carlo analysis,
et cetera, allows you to provide a much clearer sense
of the extant portfolio as it is. Perhaps the most
important thing I'll say, though, is how that AI and
portfolio management strategy, which by the way, my group's run
(03:11):
by Helen Mary Arnos, is going is to try and
take that perspective that Warren Buffett and Charlie Munger brought
to the table. You know, it's Warren's ninety fourth year
and he's just stepping down a CEO of Bulkshaway, and
their comment was looking for the future is important. It's
better to be approximately right than absolutely wrong. And I
(03:35):
think that's the job of an R and D chief nowadays,
which is to try and figure out where the apple
is going to fall, to be approximately right and move
your portfolio not only to the hero and now to
deliver what the market expects on a quarter by quarter
earning spaces, but actually moved to figuring out where the
breakthroughs are going to be. So punchline is AI and
(03:57):
portfolio analytics allows you to make a much more informed
sense of where to exercise scientific judgment.
Speaker 1 (04:04):
Great, that's we have a lot of conversation, hopefully if
time allows, on the AI side of things. Now, we
have a common friend Drew Pardoll, who, as one of
his lectures to immunology students, ask them what diseases aren't
impacted by immunology or by the immune system, and his
(04:25):
favorite thing is that most of them start to try
and find one, and he says none. Everything is impacted
by the immune system. So some of he has used
the phrase becoming a premier immunology powerhouse or being a
premier immunology powerhouse. So how are you and some of
you thinking about immunology as a whole. You've talked about
(04:46):
it more broadly than traditional I and I, So how
is this shaping your pipeline approach?
Speaker 2 (04:54):
Yes, so when people do, and I think Drew is
probably mostly right on this topic. He's kind enough to
say that I am an honorary member of the Immunology Club,
which is probably as good as it gets. The answer
is pretty straightforward, and people when you talk about imnology,
particularly to the markets. They think about gut skinning, lung joints, right,
(05:16):
And I think that's perfectly legitimate. If you look at
the bubbles of Tagger related growth in terms of farmer
as it's seen from a snapshot today, those are the
growth markets IBD, atopic dermatitis, ariasis, rhematoid arthritis of the
current darlings. But Drew rightly calls out imminology for reasons
(05:36):
we can talk about related to tissue hemeostasis and remodeling
is the basis of much more than classical iminology. That's
not to say the classical imunology is not interesting and
it's not a high Kagger growth area. It is, but
we need to move to where the apple is going
to fall. We need to go to where the pucks
going to be. We need to skate to where the
puck's going to be. And I think imnology is increasingly
(05:57):
recognized to obviously underpin oncology you've referred to Drew already
one of the founders of that field, but also increasingly
in terms of ophtalmology. Even Obasti ten years ago, if
you went to a conference instead Obesti was driven by
a minology. Apart from a few luminaries like go Counter
Nashcalil at Harvard Med School, you'd be laughed out at
(06:20):
the conference. And now most people are arguing that GLIP
one resistance or recrudescence of altered satiety subsequent to glip
or increte in cessation is rated to the persistent low
level inflammation that you see. So I think the punchline
to your question, but I think Drew Bride and as
(06:41):
an imminology powerhouse, we have insights, asymmetric insights that allow
us to go into adjacencies.
Speaker 1 (06:49):
Right now, we will get to the pipeline a little
bit more. But if you wanted to just list your
top priorities over the next five years, as you consider
what you've just been saying to us, where do we
want to be in five years time in general? And
we'll get to the nitty grity in a minute.
Speaker 2 (07:06):
Yeah, I think that maybe to give you a short
answer to that, I think the history of the pharmaceutical
industry has been characterized by individual assets. We've all got
pretty good at building a depiction or a kid truder
or on a tourist statin or on a metprosole or
ascimetidin and I think the and I've missed out a
(07:26):
bunch and apologies to the very great many drug developers
you've developed single assets. It's been awesome. I think what
we need to do and Santa Fe's moving moving to
as I've come to Sanathe is a franchise based thinking
right to be able to capture again asymmetrical contrarian insights
one scientifically two to give payers and providers, healthcare providers
(07:53):
an HCP's confidence and to give patients confidence and to
benefit from from that confidence and trust. I think we
need to start working in franchises. And what you're going
to see from sama Fie is that rather than talk
about individual assets, and I try and avoid talking landividual assets,
we're going to be supporting patients in asthma for their
whole life, irrespective strata they sit in. We're going to
be supporting patients with type two skin and other inflammation
(08:16):
for their whole lives, irrespective of where they sit, whether
it's an oral, whether it's a biologic, whether it's a
multi biologic, whether it's because they're there a responsive or
whether they're in combo. We're here for them at least
to the end of my career, and I suspect much longer.
Speaker 1 (08:30):
I mean, one value that you get out of that
immediately is that once you come within new product for
a subgroup of those patients or a later stage of disease,
is that you don't have to go and reinvent the
wheel in terms of marketing and selling it and finding
the patients and finding the physicians, et cetera. How much
is that part of this equation?
Speaker 2 (08:50):
Yeah, I mean, I think there are really thoughtful commercial
opportunities that play out if you're already an incumbent and
a space, and those are really well established. I won't
go into pricing and switching and various other things which
definitely help. But actually I think size of field, force,
(09:11):
core points, etc. But I think that's missing the point.
And actually in Sana Fee we don't talk that way.
It may beggar belief for listeners, but actually our focus
is as a tiebreaker. The patient's always the focus on
what we do, and for me, it's more about the
insights you learn from your clinical trials, the biomarket strategies,
(09:31):
and the genetics you develop, which allows you to understand
the patient better. And one thing we never talk about
is sam no one will talk about in any of
the interviews you do, is the important and medical affairs,
that iterative cycle between what you learn from the healthcare
provider and patient at the could face, often not in
tertiary centers, but also in community practices about the needs
(09:53):
of the patient, which is now in the way we've
built R and D fed back into research, is what's
going to be transformative. So yes, of course advantages, but
much more the insight to get from patients are valuable.
Speaker 1 (10:04):
Now. Part of building a pipeline and a portfolio is
that you can't do everything organically. Some of that come
from business development. So what does what dynamics play into
the decision of in licensing versus trying to go in house?
How do you judge that?
Speaker 2 (10:20):
Well, two comments. I VC and a biotech founder, and
I have the highest respect for people outside the company.
We shouldn't be complacent. We recognize that we know some stuff,
but there's a lot of stuff we don't know. Let
me give a single SoundBite for people to go away
and think about. I grew up watching mars Ink, mass Infectionery, etc.
(10:44):
Buy companies and they were of course they were a
private company. But they were butchered initially because they were
paying thirty five XP ratios and people were say, how
are they going to make money off? This makes no
financial sense? Well it wasn't true. Mars had an asymmetric
insight into those marketplaces that allow them to thoughtfully underwrite deals. Now, Salafy,
we're extremely financially disciplined. It's a core pillar of our
(11:10):
history of acquiring three hundred companies and being a conglomerate.
But I think that the principle holds, which is, as
you focus on franchises and we have a limited number
of thas that we're in, it allows us to have
an asymmetric insight based on our own data. Remember, the
concept of data is going to come up more frequently.
(11:30):
That allows us to underwrite a different not only quantum
but shape of deal structure. And I hear more and
more from people the excitement of working with semotheis and
the capital alone, but is the insights we bring.
Speaker 1 (11:43):
So would you say that you're or not that you're
more interested in asset level deals or platform level deals.
Speaker 2 (11:50):
I think it's a misnomer. I think this is a
we spent you and I've spent twenty years, made twenty
five years talking about this. I think it's a misnomer.
It depicts in the function of an asset or a
platform relationship with Regeneral, it's both. So we're not ecumenical.
We're non ecumenical. Will will will go to the mat
for whatever fits with the broader portfolio strategy. And I
(12:13):
want to keep saying and it will come back. It's
our job, as I hope one day we will be
in every way the premier pharmaceutical company in the world.
The European company has some legitimacy to aspire to that,
building the right shape of portfolio construction and ensuring that
(12:34):
we're at the bottom of every tree so that when
an apple falls, whether it we catch it on its
way down or that we're the first people to pick
it up. That's what buys us legitimacy. So the answer
to your question is whether we do it internally, whether
we do it externally, whether we do it in partnership,
whether we do it through equity, or whether we do
it through media, M and A. We need to be
(12:56):
able to look in that crystal ball and make enough
thoughtful bets.
Speaker 1 (13:00):
As an XVC, are you the type to go after
when a new technology idea appears, micro, an A, r ANAI,
whatever it is. I mean, those are not new anymore.
Are you the type to go after them right at
the beginning or would you rather wait and see a
couple of inevitably failures. Yeah.
Speaker 2 (13:18):
I think once you've got a water tight portfolio construction,
have a really well mapped out risk strategy, which we
do now. By the way, it took me a bit
of time to put it in place, but actually the
discipline is not putting it in place. It was about
people adhering to it. We have the right to take
some low bet likely blockbusters, but also some potentially transformative bets,
(13:41):
which well, I'm sorry, I don't like the verbs parier
in French. The notion of betting is not something that
I'm prone to. It's we are. I'm an investor, and
we're making thoughtful investments to ensure the portfolio gives you
those extremely low odds. But transformative alpha versus something that
(14:04):
gives you, you know, less alpha than it allows you
to continue operating.
Speaker 1 (14:09):
When you're in a VC. You know, Short Adventures was
your last post. I think you have a small group
of people who work with the money is committed, you
make a decision, you do it. Vast organization at Sanafi.
How much culture shift was needed to get to this point,
if any? And have you got to that point already
(14:32):
in terms of being nimble, identifying ideas and getting everybody
behind it.
Speaker 2 (14:38):
So three quick comments on that. Firstly, complacencies are enemy.
And I think that the notion that wherever perfect is ludicrous.
So we're always a work in motion. I should call
out Paul Hudson my erstwhile partner CEO in this project.
And actually the work started when Paul in twenty nineteen
became CEO and implemented a cultural mindset where we played
(15:04):
a win. And neither did that mean playing in its
conventional sense, nor did it mean winning in a narrow sense.
But Paul had started the journey on the cultural change.
And I think he that, you know, because of a
focus on all sorts of other parameters, Paul's genius in
making the cultural transformation has been vastly underestimated. He is
(15:27):
a brilliant man of visionary not a scientist, you know,
not a not a classically trained person in these arts.
But his intuition and his perfection and making the culture
change have been really, really, really robust, and I hope
someone writes the book, maybe me one day about it,
so that that was the start of the journey. And
I hope that since ide come in bringing in some
(15:50):
of that portfolio and financial discipline, but also the culture
of recognizing the ones. We've got a portfolio in place,
you can take, you know, some lower risk investments and
some higher risk investments, because that's what a portfolio looks like.
It is important. One comments the problem is that I
think most companies today shackled by their quarterly earnings in
(16:15):
year to year growth, and of course everything's top line
and pipeline. But I think the real trick is to
take the twenty forty perspective, and I think that's a discipline.
We brought some of it.
Speaker 1 (16:28):
Yeah, that's a tough thing to do, given that you
still have to do quarterly reports. But as analysts, we
all wish that the quarters could stop and the very
most get a half half yearly. But anyway, now, China
is an interesting area. There's you know, I've just been
at AACR, at the pre meeting at ACR. Lots of
China details, et cetera. One of the sessions I went to,
(16:50):
which was a d c's and cell therapies or immuno therapies,
four out of the eight were China assets or originated
from China. So it's clear, and I think most people
agree on this that there's been a lot and an
amazing hockey stick evolution in Chinese science. Now I'm worried
(17:11):
that my vision is tainted by the fact that I
am quite a lot highly focused on oncology at the minute.
And do you feel the same when you come at
it from a broader perspective? Are you seeing the same?
I mean, I'm looking at the number of deals you
guys have done in China versus other farmer companies. It's
not at the highest end, it's more of the at
(17:33):
the lower end. And in fact, couple of them were
tech and AI related deals, which sedgeways straight to the
next topic. What do you see there?
Speaker 2 (17:42):
Yeah, So let me start with perhaps the most important point,
which is, you know, my perspective is the innovation arises everywhere. Again,
I think we have such a short term perspective on
the world. John von Neuman, the innovator of AI and mL,
was Hungarian mass infectionery came out of the Midwest. Morris
(18:05):
Chang's t SMC came out of Taiwan, which went fabulous
on chips when there was no nothing else of that
sort in Taiwan that we're making substantially plastic. You know,
my job as a head of R and D, as
an executive committey member of sanafe's to look for innovation
wherever it is. So let's just jump to China. So
I you know, my only piece of advices. We all
(18:26):
we all swing between fads, and we just need to
we need to take that. You know, I think it's
calming to the human spirit to take the twenty forty perspective.
And remember the notion that by the way, Sam a
countrymen of ours got inscribed on a ring. This two
short pass. We need, we need a bit of stability.
(18:47):
Sanity will be seeking innovation anywhere in the world for Rauther.
So let's talk about China. China is hugely important, right.
The US is our principal market today and I think
for the foreseeable future will remain the principal market for
for and actually a major source for innovation. There's nothing
that's going to change out. We've got large offices in
r and the offices in Boston, and I'm excited to
(19:07):
do that as well as in Europe. But China is
the you know, the second largest and will continue to
become the second largest pharma pharmaceupermarket in the world. President
she two five year blocks in a row is supported
that healthcare is a major national strategic opportunity. You know,
forty two percent of the deals this year innovative pipeline
(19:28):
deals were done in China. You know, although they lag
behind in terms of clinical trials and they're doing three
point two percent of clinical trials, they continue to produce
the greatest number of engineers and scientists anywhere in the world,
and funding has been there to support it. Those facts
are important because I think it's important to recognize a
(19:49):
that China's overinvested in salan gene therapy, and I think
that at ADC's the certain technologies it's overinvested in. I
think there will be a rec libration of that, especially
as access to capital is diminished in China. But there's
no doubt that today China is producing fast followers, and
there's no doubt that speed and scale of the market
(20:12):
that China provides particularly with engineering and STEM graduate means
it's going to move very quickly in the next five
years to first investing class drugs. My view about Santafe's
position is that the market should be very careful how
it interprets our movement in China. We've been very quiet.
It's not our way, it's not the written way to
shout from the rooftops about what deals we do. You
(20:35):
saw we did a couple of deals with helips On recently.
We will do more in China. I've got a fairly
large footprint in China. It will continue to grow. We're
excited about rebalancing R and D investments. And one thing
I should say to you is again, people forget this.
We've been in China for four decades. I've visited China
(20:55):
three times a year. Since I've been at Santa Fe,
I visited the US equal or more. The message you
should take away from me is we're going to do
our work in the US. We're going to do our
work in China. The opportunity for a company like Salavi
is to genuinely benefit without borders for any innovation from
wherever it comes.
Speaker 1 (21:15):
Right, So let's talk about AI and technology. Of course,
it's a buzzword if you want to say that. Every
company I talk to they say, look, we've been doing
machine learning this kind of work for a long time.
You know. I attended an AI session at ACR again
where a gentleman who had been developing protein folding back
in twenty late two thousand's early to twenty tens was
(21:39):
talking about his model. Of course, alpha folder has become
the one that everybody talks about. So accepting that that
this is not necessarily new, there are elements of AI
that are new large language models, gen AI agent ki
so AI from what I understand, at every level is
changing direct development from the chemistry, from a biology, from
(22:01):
the clinical trial organization, patient finding it, et cetera. How
is it disrupting the R and D model from your perspective, disrupting,
not necessarily obviously in a positive way, I hope, right,
and as relative not just to Fharma but generally. And
how do you think this will continue to evolve? I'm
really interested in this part in the next five and
(22:22):
ten years.
Speaker 2 (22:23):
Okay, so let me start by saying, I'm an AI groupie.
I when I was a kid, as I told, as
I said to you, John von Neuman and Emmy at
were at the top of my mind. You know that
who defined the architecture of the current computer. I was
super excited. I was in my early teens. I was
(22:44):
excited about people talk about Turing. I was interested in
Gordon Welschman's decryption using the Amigant machine. I'm a group
and I think AI is going to be super transformative.
I'm on record saying that I think that all of
us have moved too slowly on AI, and we need
to speed up our integration about what we do. But
I want to provide one caveat before we get into
(23:07):
the you know, the hype phase of AI. And I
think we should be in hype phase. I think, remember,
I want to go where the apple is going to fall.
I think it's a complete error. It's a contempt for
us to wait and depart in. We need to go in.
We need to go in hard, will make mistakes, It's okay.
But my qualification, and this is an important qualification. I
(23:27):
think if you talk to the open AI, if you
talk to the ilias, if you talk to the people
who were there early on, in attention is the key
they will tell you. And you know, that whether it's
R and n's or a whatever network.
Speaker 3 (23:46):
Structure you build, most of these technologies were built for inference.
They were built for correlation, right, And that's okay if
you want to figure out which movie is going to
take over the world, or which toothpaste is going to win,
or which hamburger is going to emerge, which flight is
(24:08):
going to be the most popular.
Speaker 2 (24:10):
And I use those examples because Jason Wang of Nvidia
use those examples when he was talking about the importance
of inference. Correlation often doesn't play in our favor in
our world in terms of true innovation, because it is
that causative leap that's critically important. So that the disclaimer
is that where AI is going to make its greatest
(24:32):
contribution in biopharma is where correlation is adequate and is
less likely to be productive, where causation is the problem,
and that arrow of causation is going to continue to
daunt us. So let me let me just be clear
for the SoundBite. It's important. It's AI is going to
transform where we do correlation. It's going to be less potent,
(24:56):
I think, where we do causations. So your question was
what's it doing today and I'm going to give you
the punchlines and then we can get into some detail
and where is it going to go in five to
ten years. Where it's going today is the bits where
correlation helps, right. It unequivocally can do huge things in
terms of designing, copiloting, trial design, in terms of ensuring
(25:20):
that we recruit in the right sites, ensuring that we
can transition between sites, maximizing rates of recruitment, document writing,
medical writing submissions, etc. And that will transform drug development costs.
It will dramatically reduce costs, streamline or reduce time, particularly
in the back end. It will help with personalized medicine
(25:42):
because of course those correlations are what personalized medicine is
predicated on in terms of which patients will develop which drugs.
And unequivocally, even a complex healthcare system like the US
will be helped in terms of health inequalities. And we
are moving to ipowered solutions across all these things, including
our commercial bits. I think that bar to going to
the next level in terms of its impact on discovery
(26:09):
is going to be harder. It will contribute to reduce
some cycle times in discovery, there's no doubt, but in
terms of that inductive creatively, I think it's going to
be harder.
Speaker 1 (26:21):
So that's great. There's so much in what you've just
said to unpack. We could do a separate podcast on it,
but let me just get to this point. So, in
terms of the elements that you said, patient trial design,
patient recruitment, et cetera, document writing, I fully get that
when it comes to biology, target identification, faster drug design.
(26:42):
I think I heard you say that at the very least,
it helps to speed things up, but not necessarily be
the originator of the idea at the moment. One of
the things that seems to be especially at that that
point a bottle neck and I want your yes or
no on it, if you like, is that the world
(27:02):
data that's available out there is pretty much driven by
positive trial outcomes positive experiments. The negative experiments that who
man may have done in the lab, as Ellie may
have done in the lab, et cetera, don't get published.
You hear about them when you go to a conference
and sit next to you somebody, or you have it
at the dinner or whatever. So the negative outcomes now
(27:25):
generating hypotheses using AI based on the common knowledge that's
been published. Therefore, has a risk. Do you see that
as a risk or do you think that within the company,
given the data that you have access to, you can
fix that.
Speaker 2 (27:40):
Yeah, So three comments. Firstly, your listeners won't know that
you did your first degree in Cardiff and that's where
you first did your experiments. A big call out shout
out to Cardiff University for its most famous alumnis. Moving
to the answer to your question. I don't think there's
a monotonic answer to your question. I think there are
certain discipl in which we have adequate data or approaching
(28:02):
adequate data to answer the question. No one's doing autonomous
trial design at the moment, and I think it's somewhere away,
but there's vast amounts of data to help copilot some
of those designs. Right. I wouldn't recommend you do it,
but you could download all of clinicaltrials dot org and
have some version of a thoughtful clinical trial designer. There
(28:23):
are real challenges without approach, by the way, So there
you may have data in terms of trial design. But
for example, as you said, let me give you two extremes,
can you optimize child design? Probably and that people are
trying today. Can you predict the outcome of phase two trials.
In the phase three that's where your problem becomes real, right,
(28:43):
because there's an ascertainment bias, the selection bias where the
negative trials and the trial data is substantially less well represented.
So there are some areas And the last thing is
and sam This is a subtlety that probably doesn't come
out in podcasts Normally, there is an uncertainty and no
one's captured this. How much data do you need to
(29:06):
answer a certain version of complex question? Right? And we
don't know the shape of surface of data quantity you
need to match to a particular set of problem, right,
That epidemiological uncertainty is going to dog the application of
a I'll give you a simple example when we think
about digital twins, how much data do you need to
(29:28):
contend with a complexity of cellular biology? While that's a
holy grail for all of us, no one knows do
you need all the data that's in the universe You'll
never get there, or do you need data from a
million ipss of each cell type? And that level you'll
only know when you know.
Speaker 1 (29:46):
That's a problem. It's the unknown in terms of just challenges.
Before we move onto a pipeline specifically in the AI space,
coming really up to the helicopter view from it, there's
two issues that I want to and maybe there's others
that you would like if at an organization you're not
I'm assuming just full of lots of humans who have
(30:07):
as a child, we're interested in technology like that, right,
there's normal people, if you want to call it that,
who have other interests who maybe find it tougher to
switch to using CHGPT in their systems. So how much
of a culture shift where are you on that? Continue?
Number two is if you're using a lot of in
(30:28):
house data for some of the work that you're doing,
how much of it is actually available and how much
effort do you have to spend on making it available
to systems to understand the US And lastly, we come
back to the final question that I ask you about
the three areas that I'm hoping to you'd be able
to give me a feel for impact.
Speaker 2 (30:46):
Yeah, So the number one is, thank god, there is
you know, I think some days or maybe every day,
and it's trying to feel laments, there's a whoman in
the organization, and thankfully then there's much more reasonable people
throughout the world organization. You know, it's a journey. It's
a journey for everybody. It's a journey. You know. I
walk in and see my son who's eleven, who, by
(31:08):
the way, wants to be an investor, and he on
a Saturday morning has four Yeah, he has four lms
open and he's co prompting from the lams. You know,
it's we're all on a different stage of our journey.
We've started that cultural translation. I've already referenced Paul's importance
and I don't I'm not a person who believes in
(31:29):
the culture of the CEO. It's not shouting out Paul
because he's the CEO. I'm notoriously independent in my thinking.
But he has started that cultural journey, which I think
is important. So we're on a journey. People adopt things
at different rates. We have many people in the organization,
tens of thousands on their smartphone have an AI app
(31:52):
which allows us to look end to end in the organization.
You know, I have people at two o'clock in the morning,
you know, asking me what about sales of a particular
drug in Australa. You know, what's the basis of changes
in those sales? So there is a democratization of some
AI that's a sort of snackable AI, whereas we have
some much more complex, sophisticated expert AI where an individual
(32:12):
in the organization will or five individuals in the organize,
you know, the cry o m AI structural piece, and
then everything in between. You know, we've got we've got
our relationship with open a formation bio for bringing together
stuff for clinical development. We you know, we've got stuff
in Germany with a biomedex relationship. There's vast amounts of
(32:33):
we've got a relationship with okin. We you know, I
think it's a mistake to consider it in the same
way that if I said to you, do people use apps?
It's a mistake. You know, my my mother or my
father who's in his nineties now will use what's app
but sidely it's not on TikTok or Instagram. I think
what I think the only important thing is to start
(32:54):
everyone on that journey and ensure that you're incentivizing people
both through the technology but also through more conventional incentivization
techniques to embrace this technology. It's about workforce planning and
skill development. But we've started that journey. We we we've
made mistakes. We'll make more mistakes, thank god, and we're
learning from those mistakes.
Speaker 1 (33:15):
That we move forward another data front, Well.
Speaker 2 (33:17):
We use the lab books now, the physical lab books.
We're gone even before I king, thank god, we use it.
One is no one is good. I think we're all
early on in that process. But certainly we use a
combination of proprietary data and data in the public domain.
There is literally a whole podcast and we probably shouldn't
go into it now about how you know tag data,
(33:39):
graphing nodes, how you optimize the use of data and
data architecture, and perhaps most importantly, following the raise policy.
You know, our AI se to ensure that the data
is used responsibly thoughtfully. This data governance you'll have seen that.
And I never talk about competitors, but I don't think
(34:02):
this is a competition issue of JANJ announced to three
weeks ago that they were curtailing vast numbers of the
AI projects because they had, you know, there was a
conflagration of AI projects and both cost and time and
compute and cloud were a real issue. I think what
you're going to see when you talk about data is
there can be better than the governance.
Speaker 1 (34:23):
In terms of three areas probability of success, time to market,
speed to reach peak. Those seem to be the three
areas where if you could make an impact, you would
increase the NPV of a product. Added fourth one if
you like. I couldn't think of another one, of course,
size of the market. But if you wanted to put
(34:46):
an impact factor on each odd of ten, probablyative success,
time to market, speed to reach peak, all the ai
that you know, which one of those, how would you
rank those out of ten? For PROBERTI of success impact.
Speaker 2 (35:01):
That we have three problems in our industry, really only three,
and they map onto your comments, right. We have industries
take a long time to get from idea to peak sales.
We have a high attrition rate, and we're highly regulated,
which isn't reflected in your comment. That's that there are
only two other industries that I can think of that
face our problems. One is oil and gas. That's use
(35:23):
the same words that we do to describe, you know,
independence versus large players. Pipeline, They use discovery them be
in drigging, digging holes, development which they mean is the
door riggs, and defense. And if you talk to those guys,
they really do believe that AI is going to impact
(35:45):
on all three of those. So I think that we're
going to see the next generation of farmer company, which
is AI powered to contend with all those three parameters.
And what you'll see if they do, you'll see top
line growth brether than twenty Your CPS growth go bananas
because of the efficiency, and you'll see the free cash
(36:08):
will increase because the investments required per molecule will diminish.
I think they will translate into the three parameters you've
got also regulary success, but they'll translate into better financial parameters, and.
Speaker 1 (36:21):
The efficiency comes across the board manufacturing supply chain hr ALL.
Speaker 2 (36:27):
I mean, they're already coming, it's not the Only question
is whether big organizations can adapt quickly or whether the
nimbleness of smaller organizations will mean that either we have
to buy in technology or will be disrupted.
Speaker 1 (36:39):
Let's talk about pipeline. What I'm not going to do
is what we do on a cell side call is
dig into every single molecule or at a conference where
you can go wild on the details of trial outcomest.
There is a question in my mind. I'd like your view,
and then we'll talk about where you fit on that.
So we've had of the past twenty thirty years, we've
(37:02):
had drug classes that become massive. Let's go back to
the antascits. Then we had the lipid lowers. Then we
had the TNFS. I might miss something along the way here.
Then we had the the TNFS. So with the roarthritis,
et cetera, orb CIT is now currently the way that
we're thinking, what's the next one?
Speaker 2 (37:23):
Yes, the first that you did miss io by the way.
Oh sorry, of course, but it's hard to predict what
the next one is going to be. But I think
the obvious if you think about the evolution that you've described,
you went from the symptom modification to disease modification, and
acid to disease modification. If you think about the latter,
(37:44):
whether it's statins for secondary and then primary prevention. If
you think about inn oncology, if you think about even
some of the larger anti inflammatory drugs, they went from
symptom modification to fundamental alterations in the course of disease.
Speaker 1 (38:02):
We did go from old old style drugs to immunology.
I think we did right.
Speaker 2 (38:07):
We did. We went from we went from drugs that
were identified in phenitipic screens. You know, at my first
year at med school, we're still looking at intestinal organ
baths where we threw stuff on and worked out through
radiation competition experiments activation and inhibition properties the receptors. Right
even though we you could do that experiment without even knowing,
(38:28):
you know, what the nature of those receptors were. And
now we're going into disease modification. So I think that
with all due humility, I think that what you're going
to see is the greatest scourges of our society against
and I'm not talking about climate health or any of
the man made stuff is. It's going to be mental health,
neural the generation and consequences of chronic disease, and those three.
(38:51):
And if we don't solve those problems, we will be
you know, the society will will collapse. Right if we
can't deal with a scourgeon your generation, or mental health
and or chronic disease, that's going to be a problem.
And Sam, before we lest we forget you know the
fact that mankind has been able to impact on cystic
(39:12):
fibrosis or I understand THH two inflammation and impact on it,
or create a three enemy that chip makes me hugely
optimistic that we can deal with those problems.
Speaker 1 (39:23):
And of course respiratory I thought is one of those.
Speaker 2 (39:26):
Yeah, I think we're already just.
Speaker 1 (39:27):
Starting to treat the underlying causes that it's been symptomology, symptoptology.
Speaker 2 (39:32):
Yeah, I think that's completely true. I think that when
you look at, for example, I try and avoid being
self serving, when you look at our molecule and malytilla map,
which please don't forget, I'm the biggest fan of depictions.
It's the reason that many of us in part are
here today, and it's the molecule that validated the THH
(39:54):
two inflammatory intervention. We will, we will grow and commit
to depiction until it's very long, stand far beyond. But actually,
when you begin to semolgules like a little map that
come into the space which have post drug cessation, way
after months, many months, after five half lives have disappeared,
you know, durability of disease responds a massive association between
(40:17):
PK and PD. It gives you optimism that actually you
can interfere in the march your early disease modification of allergy.
Speaker 1 (40:27):
Of course, with spiritually fitsy chronic disease issues right, because
that's what it is. Yeah, So if we look at
some of this pipeline, where do you think the market
this is one of the favorites of some seal side analysts,
which I actually enjoy listening to. Where do you think
the market underestimates and this underestimate the potential of your pipeline?
Which which area if you want to call it a
(40:49):
drug or a pipeline drug, or a disease area or
or as you were saying, it's not that it's about
treating a patient through the entire Yeah, I.
Speaker 2 (41:00):
Think there's been a systematic discount. And I say this
with humility because I have the highest respect for the
cell side analysts and for our byside in general. But
I think there's been a and we've got to earn
the right. I'm all good with I told you I'm
taking a twenty thirty, twenty forty perspective, will prove I'm
okay with people saying prove yourself. I'd never step back
(41:22):
from proving myself. And I feel incredibly committed to Sanafie.
But I think we have a systematic discount. You can
see that in our pe ratio. We have a systematic
discount compared to our level of innovation. So I think
that if you ask me to call out one space,
I think that we've built very substantial capability in pipelining
(41:46):
products and the sels. I don't really know how to
valuate those assets, right. They predominantly value things in our
models on the lead indication and how they discount lcs
is problematic. Now, I remember in depiction, we're on indication
seven and we're going to keep going, and then each
(42:07):
indication is a multi billion dollar indication. So I think
I think, rather than talking about in each individual space,
the two things that I think the cell side currently
discount and it's down to us to work with them
for them to understand us is one they discount individual
molecules do They think very much about product indication, But
they also discount franchise based thinking, right, and the halo
(42:28):
you get the intangible which you can't put into your
model on physician trust and therefore use within a franchise.
Speaker 1 (42:37):
In our last couple of minutes here, human personally, I'm
happy to talk about politics, but in general, what we're
interested in policies, things that impact and things that you
can measure against saying okay, there's a new policy. What
are you seeing that worries you? And what are you
seeing that you think is an opportunity? You can take
that in the US, Europe, anywhere you like. In terms of.
Speaker 2 (43:01):
Nothing worries me. Actually, I was lucky enough to be
an immigrant to the UK and I'm always inspired by
the global innovation community. So you know, I think again,
this too shure past. We spend our time worrying. I
think all of this stuff is an opportunity. You just
got to find the opportunity and leverage it. You know, Honestly,
(43:23):
when I go to bed at night, my I don't
spend my time sweating. You know, we're as a company
not supportive of tariffs. We think the tarif's create attacks
for everybody. They generate complexity and innovation for people. But
the truth is that the world is always changing. You know.
My background is an immigrant reminds me that nothing stays
(43:44):
the same. And I, with a due humility, believe that
we've created such a strong pipeline, such a massive group
of talent, and every day I thank myself, I thank
the world and thank the team that we've got the
talent that we have. We continue doubling down on talent.
Think our job is to make Sanafe resilient and actually
(44:04):
go to where the skate to where the punt so
punchline is. I'm not worried. I think all of this
represents an opportunity for us and as a Sanity leadership team,
and every member of the company is up for that challenge.
Speaker 1 (44:16):
I hope folks realize that you've actually said in between
the lines, you've said a lot more than than perhaps
is obvious. But in these last comments with regards to
the price differential, healthcare provision differential, innovation differential, they're all
related between the US and Europe. Now we know there
(44:37):
are things going on in the US which one worries
might impact the future of innovation there in the longer term,
in terms of grants being cut, budgets being reduced, et cetera.
How do you what is the solution there? One side
is saying we need to bring US drug prices down
to perceived US drug prices, right because I know, we
(44:59):
all know there's a issue between the list price and
net price, et cetera, down to what's what the Europeans
are paying for instance. On the other hand, some executives
have been saying no, no, no. The problem is is
Europe they need to raise their prices. So I'm not
going to ask you to take your position on this,
but what do you think the solution is?
Speaker 2 (45:17):
Yeah, So three comments. Number one is you said the
most important comment that you made is perceived and it's
not just gross and net prices when people If people
took time to understand the shape of pricing in Europe
versus the US, the gap is much smaller than has
been publicized. And indeed, in some sectors the US gets
(45:40):
access to drug on a cheaper basis than Europe or
other places. So number one is, I think it's a
bit of a misnomer to talk about prices in a
simple sense, and I think one of our jobs as
and industry is to educate the world is to where
pricing differs. But the US that's get access to drugs
(46:00):
in some courses at very similar prices or with very
many with very minded difference. Number two is I do
think that as a europe we need to step up
and pay for innovation or the natural consequences that Europe
won't get access to innovation. And I think there's definitely
that message, not all parts of the Europe. Not all
(46:22):
parts of Europe are the same. Right, we have to
recognize that Europe is a common union with and to
be celebrated variation. And then finally, remember we're here forever.
Santafie's aim is not here to solve problems today and tomorrow.
We're here to solve problems over the next twenty years,
and our only motivation that is to generate value for patients.
(46:45):
And I'm particularly confident that with the management team that
we have today, we are resilient enough to be able
to flex and strain to ensure that whatever the regimes
turned out to be, that we will do our very
best work with governments in all the world, whether they're
developed truands and developed to generate drugs that will transform
(47:06):
a lot of mankind. That's why I went into medicine,
and my goal hasn't changed.
Speaker 1 (47:10):
Well, man, you know that I could sit here for
hours talking to I know for sure that you have
much better things to do. So I appreciate your time
and really nice to catch up with you again, and
I look forward to seeing you at some point.
Speaker 2 (47:23):
It is increasingly rare when you look at the industry
that people who've come from the analyst side have the
experience you have. There are a number of other people
in the industry with the same kind of experience that
are being exited or exiting now. It's an incredible privilege
for the industry to have siting on the analyst side.
(47:44):
And I know that's not exactly where you said anymore,
but to have thoughtful commentators that can tease out the
key question. I think your listeners should know that that's
a privilege that might not be here forever.
Speaker 1 (47:55):
That is very kind of you. I know a whole
host of other people who I believe qualify for execus
the same commentary. But I appreciate that, and I think
on that note, given you've made me feel a million dollars,
we can we can end the podcast, and I want
to thank you again for your time and look forward
to repeating maybe in a year or two, to see
where we've got to like you. Thank you. M m.
Speaker 2 (48:27):
M m.
Speaker 1 (48:31):
M m
Speaker 3 (48:41):
M m
Host
Jonathan Palmer
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