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Novartis Puts Biology Before Modality in Its Next R&D Chapter · Vanguards of Healthcare by Bloomberg Intelligence

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  Speaker 1: Welcome to another episode of Bloomberg Intelligence's Van Guards of
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  Speaker 1: Healthcare podcast, where we speak with the leaders at the
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  Speaker 1: forefront of change in the healthcare and pharmaceutical industries. My
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  Speaker 1: name is San Frazelli and I'm a farmer analyst at
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  Speaker 1: Bloomberg Intelligence, the in house research arm of Bloomberg. I'm
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  Speaker 1: thrilled to welcome Funa Marshall today, president of biomedical Research
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  Speaker 1: at nov Artists, to talk to us about a whole
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  Speaker 1: host of topics that I'm sure a lot of folks
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  Speaker 1: are now used to having listened to our podcast. So
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  Speaker 1: welcome FIORDA. Very nice to have you here, and thank
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  Speaker 1: you for joining us.
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  Speaker 2: No, thank you, Sam, I delighted to join you and
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  Speaker 2: your audience.
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  Speaker 1: That's brilliant. So I was gonna, as I usually do,
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  Speaker 1: ask you to give a little introduction to yourself, the
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  Speaker 1: way that you want to describe your role and your past,
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  Speaker 1: your career. You know, I think we have a tiny
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  Speaker 1: thing in common, and that's love of neuroscience. I did
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  Speaker 1: neuroscience many years ago, and unfortunately my PhD supervisor, whom
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  Speaker 1: I had a humongous regard for, Professor and Net Dolphin,
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  Speaker 1: recently passed away. So I want to give a shout
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  Speaker 1: out to her for trusting me with in her lab
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  Speaker 1: in the eighties. If you could believe that Funa over.
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  Speaker 2: To you, I can Sam, because we have another thing
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  Speaker 2: in common, which is our British connection. I trained in
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  Speaker 2: the UK and of course knew a Nett very well
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  Speaker 2: trained in neuropharmacology at Cambridge for my PhD. I joined
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  Speaker 2: Big Farmer pretty quickly into what was Glaxo later became
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  Speaker 2: GSK SO. Ten years in Big Farmer moved to a
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  Speaker 2: millennium into the sort of new wave of technology. It's
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  Speaker 2: a theme in my career that I like to use
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  Speaker 2: whatever is the best possible technology available to do what
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  Speaker 2: we do, which is very difficult discovering drugs. And then
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  Speaker 2: subsequently set up a biotech company which was a spin
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  Speaker 2: out from the MRC Laboratory of Molecular Biology around protein
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  Speaker 2: crystallography SO and elect cryoelectron microscopials called Heptari's SO. Again
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  Speaker 2: then another new technology development step. We did a lot
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  Speaker 2: of different collaborations again with many Big Farmer companies. As
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  Speaker 2: a biotech SO got to see it from that side
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  Speaker 2: of the table that ultimately felt that in order to
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  Speaker 2: be you know most productive and have the biggest impact
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  Speaker 2: was better actually within Big Farmer. So actually went to
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  Speaker 2: Murk to start with initially in the UK and then
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  Speaker 2: over into the US became head of their discovery research,
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  Speaker 2: and then finally about four years ago, moved to nev
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  Speaker 2: Artists to head biomedical research. And biomedical research includes all
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  Speaker 2: of the early discovery of nev Artists through to translational medicine.
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  Speaker 2: We have translational clinical oncology and translational medicine that takes
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  Speaker 2: the programs through to around about phase two when we
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  Speaker 2: transition to development.
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  Speaker 1: Right, so fe that background really is quite an amazing
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  Speaker 1: setup to go into research. And what I'm interested in
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  Speaker 1: is when you look at the platforms that novartist has
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  Speaker 1: in terms of the variety of areas that you've been
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  Speaker 1: particularly successful in radiolygen therapies, ANTISENSRNA, etc. Do you want
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  Speaker 1: to talk through maybe what you're looking at in the
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  Speaker 1: longer term for other modalities that you might be looking
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  Speaker 1: at in any of the therapeutic areas that relate to you. Yeah.
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  Speaker 2: So, I mean, I think the first point is we
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  Speaker 2: don't just do technology for technology's sake. We really sort
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  Speaker 2: of ground ourselves in what are the disease areas that
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  Speaker 2: we want to focus on, where are the highest done
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  Speaker 2: that needs and where can we really bring sort of
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  Speaker 2: meaningful differentiation. And usually we're looking for what the underlying
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  Speaker 2: drivers are of the disease, particularly for example, if we
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  Speaker 2: have genetic contribution to those diseases, so that we get
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  Speaker 2: higher validation. And then we think about what is the
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  Speaker 2: right technology in order to address those targets and pathways
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  Speaker 2: and where can we be differentiated because you know, one
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  Speaker 2: of the features of Nevaltis is we don't want to
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  Speaker 2: follow the crowd. We want to you know, steer our
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  Speaker 2: own path into what we think the most exciting opportunities
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  Speaker 2: for patients and what are the technologies that can be
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  Speaker 2: really you know differentiated, So you know, rather than looking
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  Speaker 2: at new ones, I mean, I thought it would be
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  Speaker 2: maybe more interesting to say how we're really extending both
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  Speaker 2: r LT and s I, R and A into the
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  Speaker 2: future and really you know, building on the expertise that
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  Speaker 2: we have in these technologies. So if you take radioligands therapy,
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  Speaker 2: I mean, I feel like this is a technology really
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  Speaker 2: just starting. If you think, really there's Plevicto, which is
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  Speaker 2: the prostate cancer RLT, but you know, not so many
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  Speaker 2: are are approved, and certainly we're ahead in this field.
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  Speaker 2: But what we're really trying to do is building on
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  Speaker 2: that knowledge with Previcto C whether you can get you
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  Speaker 2: an RLT for pretty much every tumor. So we're mapping
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  Speaker 2: the surface of tumors and really you know, going with
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  Speaker 2: targets that we know on certain tumor types and converting
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  Speaker 2: those to rlts. And what you have to do then
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  Speaker 2: is optimize, you know, whatever the protein is on the tumor.
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  Speaker 2: Decide on what ligand do you want to have, So
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  Speaker 2: we characterize multiple different ligands. We find that peptides are
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  Speaker 2: particularly helpful as ligands for rlts. You don't want know
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  Speaker 2: long half life. You want to be delivering that radiation
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  Speaker 2: dose and then have that cleared away, you know, so
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  Speaker 2: you know, just a reminder to those listening. RLT is
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  Speaker 2: essentially targeted radiation to the tumor with a radio isotope.
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  Speaker 2: We use two types of isotope. One is lutitium, which
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  Speaker 2: delivers a beta emitted of radiation and that can actually
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  Speaker 2: cover not just the tumor it's downd to, but it
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  Speaker 2: has some crossfire as well. And then tinium as another
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  Speaker 2: radio isotopes, so we're looking at different isotopes. That's what's
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  Speaker 2: called an alpha emitter, and it delivers really high energy radiation,
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  Speaker 2: producing you know, really catastrophic double stranded DNA breaks within
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  Speaker 2: the tumor. And so we're looking at we've now recently
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  Speaker 2: got some data with the psma victo is with lutitium.
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  Speaker 2: Now we've got actinium, and we've seen that tumors that
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  Speaker 2: can become resistant to lutitium, you know, can still be
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  Speaker 2: sensitive to actinium. So you know, the next thing is
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  Speaker 2: how we take these forward. And we've set up a
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  Speaker 2: radio isotope lab in Barzel actually where we do a
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  Speaker 2: lot of screening in mouse models of different tumor types
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  Speaker 2: and really characterizing many different rlts. And what's really interesting
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  Speaker 2: about the RLT field is that you can do what's
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  Speaker 2: called a phase zero study, so this is in humans,
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  Speaker 2: in clinical studies, in in patients, and you use different
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  Speaker 2: types of isotopes in this case where you do either
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  Speaker 2: a pet study or a spect study, and that allows
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  Speaker 2: you to characterize whether the RLT is binding to the tumor.
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  Speaker 2: You can calculate what's called dosymmetry, which the delivery of
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  Speaker 2: the radiation to the tumor. We all say, look, is
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  Speaker 2: it binding to normal to shoot? That would obviously be
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  Speaker 2: a bad thing and that might cause you to not
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  Speaker 2: move forward with that RLT. And you can get an
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  Speaker 2: understanding of pkpd and all of these sorts of things.
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  Speaker 2: So it allows you to actually take multiple experimental rlts
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  Speaker 2: forward and then make decisions at that early clinical stage
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  Speaker 2: whether it's worth further investment going forward. So we actually
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  Speaker 2: have a really extensive portfolio of more than twenty rlts
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  Speaker 2: that we move forward in this way, and we complement
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  Speaker 2: our internal work as always with collaborations or biotech partnerships
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  Speaker 2: or acquisitions. So we recently bought a company, Marianna, which
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  Speaker 2: was a Cambridge, US based company that specialized in actinium
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  Speaker 2: and these phase zero studies. So we've continued to invest
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  Speaker 2: in that site and we're finding that's very helpful for
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  Speaker 2: decision making. So, you know, all in on rlts and
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  Speaker 2: we think there's a lot of opportunity, but you know,
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  Speaker 2: there may be tumor types where at RLT isn't the
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  Speaker 2: best modality. So very recently actually we have acquired a
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  Speaker 2: UK company, Mirics, and they're an ADC company, and so
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  Speaker 2: we find that we think ADCs are going to be
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  Speaker 2: complementary to RLT, but we wanted to really look for,
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  Speaker 2: you know, where is a new space, what is the
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  Speaker 2: next horizon, the next generation of antibody drug conjugates, And
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  Speaker 2: we thought that you know, a lot of the current
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  Speaker 2: ones are essentially taking known chemotherapy sort of the idea
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  Speaker 2: is targeted chemotherapy in this In this case, you're attaching
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  Speaker 2: the chemotherapy ligand to the antibody and it's usually like
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  Speaker 2: a topo isomerase inhibitor. Those still have retained quite significant
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  Speaker 2: tox and you know, really trying to get away from
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  Speaker 2: that tox and just deliver to the tumor. And so
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  Speaker 2: we really like this new payload that Miris has. It's
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  Speaker 2: called an NT inhibitor, which really has it affects the
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  Speaker 2: lipid modification of proteins, but particularly ones involved in rapid
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  Speaker 2: cell growth. So tumor cells are much more sensitive to
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  Speaker 2: it than normal tissue. So this is a very new
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  Speaker 2: deal that we've just done and we'll be building out
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  Speaker 2: that platform and you know, looking at where it's complementary
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  Speaker 2: to RLT.
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  Speaker 1: I'm looking forward to doing a podcast with the Jonathan
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  Speaker 1: Tobin who is the one of the inventors on that.
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  Speaker 1: I've known him for a while. Obviously he's London based,
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  Speaker 1: so yeah, you know, it's not an enormous universe in London.
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  Speaker 1: And so you know, if I could take you back
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  Speaker 1: to alpha versus beta, yes, there's a lot of discussion
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  Speaker 1: there obviously is there a role for both Once you've
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  Speaker 1: got everything with an alpha emitter on it, do you
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  Speaker 1: still do you still see a future for beta emitters?
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  Speaker 2: Yeah? Oh definitely. I mean alpha is very powerful emitter.
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  Speaker 2: One of the things we want, and it will depend
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  Speaker 2: on the antigen. P SMA, which is the one for
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  Speaker 2: prostate is actually quite unusual and it's so specific to
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  Speaker 2: the tumor. You don't find PSM, you know, widely expressed
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  Speaker 2: on other cells, where if you were to take her
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  Speaker 2: too as an example, which obviously very important antigen on
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  Speaker 2: breast cancer cells, you do have her to expression on
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  Speaker 2: normal cells. And so this is why the to ADCs
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  Speaker 2: do cause some off target toxicity. So what we're we
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  Speaker 2: actually are bringing forward to her to rilt both with
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  Speaker 2: actinium and lutitium, and we're going to compare this, but
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  Speaker 2: it's going to depend on the expression of the antigen
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  Speaker 2: on the tumor cells, and if the expression is very high,
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  Speaker 2: you probably don't need or maybe not even want actinium.
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  Speaker 2: You might actually prefer luttium because the therapeutic index between
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  Speaker 2: normal cells and the tumor cells, that's what you're really
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  Speaker 2: interested in. And there may be settings where you would,
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  Speaker 2: you know, bring a lutitium first, and then you might
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  Speaker 2: bring actinium later on. So this is something that we're
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  Speaker 2: really you know.
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  Speaker 1: Do you mean in a sequence within the same.
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  Speaker 2: Page that could be in a sequence that makes sense?
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  Speaker 1: That's interesting, right, And then thinking about peptide versus antibody,
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  Speaker 1: you very elegantly said that you're looking for half life
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  Speaker 1: angle here because you've got to really like it, obviously.
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  Speaker 1: But on the other hand, how hard is it to
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  Speaker 1: tune the specificity of a peptide these days, which, of
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  Speaker 1: course I'm sure you're doing it. I'm sure there's the
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  Speaker 1: word AI will come up soon, but I don't know
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  Speaker 1: if it will in this case. But the question then
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  Speaker 1: ends up being do peptides give you a better opportunity
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  Speaker 1: because you're kind of agnostic to what exactly they bind
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  Speaker 1: to As long as they bind to your tumor and
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  Speaker 1: not anywhere else. Help me understand what No, No, that's
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  Speaker 1: absolutely right.
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  Speaker 2: I mean you want you want to membrane protein. It
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  Speaker 2: doesn't need to be internalized, and it can as long
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  Speaker 2: as it's specific for the tumor. That's really what you're
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  Speaker 2: looking for. And then you want to binder so you
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  Speaker 2: don't actually need it or want it to affect the
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  Speaker 2: function of that protein. And pep tides are they're actually
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  Speaker 2: one of my favorite modalities. I mean, they're incredibly flexible
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  Speaker 2: and then you can constrain them if you want to
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  Speaker 2: bind to different binding sites on proteins. And we have
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  Speaker 2: very excellent ways of screening libraries of peptides and then
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  Speaker 2: engineering them to have really remarkable potency. You can get
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  Speaker 2: down to p comola potency with a peptide and they're
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  Speaker 2: actually very easy to make, and you know then they're
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  Speaker 2: very suitable for attaching the radioligrant i as well. But
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  Speaker 2: they have that the optimal type of p K. They
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  Speaker 2: also can penetrate into tumors probably better than an antibody could,
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  Speaker 2: being smaller, so that there's a lot of advantages of them.
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  Speaker 1: What about internalizing if you were not to put a
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  Speaker 1: radio ligand on it and rather putting a one of
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  Speaker 1: the si RNA's or something else on it to bring
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  Speaker 1: those to the tumor. Is there merit there?
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  Speaker 2: I mean you can you could, You could pick an
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  Speaker 2: internalizing protein and if at you know, another modality which
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  Speaker 2: I'm sure come to talk about is s I r
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  Speaker 2: n A. And here we look at both peptides as
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  Speaker 2: well as antibodies to deliver si rna to cells. And
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  Speaker 2: you know, here there are some advantages and disadvantages. Usually
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  Speaker 2: here you you want to deliver a large amount of
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  Speaker 2: the s irna in an efficient way. Maybe an antibody
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  Speaker 2: will could do that better. But it's also it needs
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  Speaker 2: you know, the s I r and A then needs
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  Speaker 2: to be taken up into the risk complex. So it's
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  Speaker 2: also what happens to that ligand when it's internalized is
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  Speaker 2: an important consideration.
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  Speaker 1: And is there any value to the thinking that if
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  Speaker 1: you had an antibody approach, you could also use the
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  Speaker 1: blocking aspect of the antibody in terms of if it's
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  Speaker 1: her too, you get that benefit as well as the
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  Speaker 1: delivery of a radio like And is there any well
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  Speaker 1: does that make sense?
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  Speaker 2: No, it doesn't really because the p K of the
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  Speaker 2: radio ligand needs to be quite short, whereas when you're
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  Speaker 2: blocked trying to block the function of the protein, then
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  Speaker 2: you want a longer acting agent. If you wanted her
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  Speaker 2: to antibody block her, you'd want to have that around
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  Speaker 2: for a long time.
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  Speaker 1: I was pushing my lug there a little bit. And
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  Speaker 1: then so let's talk to about s I rn A.
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  Speaker 1: There's been some recent conversation. In fact, I've had a
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  Speaker 1: similar podcast with John Maraganoro, who obviously everybody knows from
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  Speaker 1: Alila Days, and he's a big fan of interfering RNA
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  Speaker 1: or that that that pathway as opposed to antisense. And
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  Speaker 1: I think the latest news where an antisen strug didn't
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  Speaker 1: do as well as one would have expected to obviously
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  Speaker 1: gets all the s I rn A type people all
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  Speaker 1: riled up and happy. So what do you what do
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  Speaker 1: you think of the whole thing being I'm assuming quite
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  Speaker 1: diagnostic to this because, as you rightly said right at
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  Speaker 1: the beginning, you want to take the best product forward
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  Speaker 1: irrespective of what the technology is.
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  Speaker 2: Yeah, I mean, it depends on what you want to
• 14:31
  Speaker 2: do with the oligonucleotide as to whether it's better to
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  Speaker 2: have an anti sense or an s i RNA anti
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  Speaker 2: sense has got some advantages, but one of the problems
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  Speaker 2: is that it can have some react you know, you
• 14:42
  Speaker 2: often can get some reaction to the anti sense because
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  Speaker 2: it's it's a sort of raw oligonucleotide. It can stimulate
• 14:48
  Speaker 2: innate immune and you can get inflammation, so you know,
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  Speaker 2: sometimes that can counter the effect you're trying to achieve
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  Speaker 2: with the s.
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  Speaker 1: I r n A.
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  Speaker 2: And also it's not it's just about you know, the
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  Speaker 2: oligonucleotide itself, it's how it's being delivered. And in some
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  Speaker 2: cases the raw oligonucleotide can be good enough, particularly for example,
• 15:08
  Speaker 2: if you're giving in intrathecal administration, we have a Tao
• 15:12
  Speaker 2: antisense oligon nucleotide for example, whereas with the s IRNA,
• 15:16
  Speaker 2: you know, you need to deliver it specifically. And of
• 15:19
  Speaker 2: course the al Nylon technology was to deliver it to
• 15:21
  Speaker 2: hapatastes and so a livered delivery, and that's an incredibly
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  Speaker 2: that really moved on the technology, and we have improved
• 15:30
  Speaker 2: drug which is lect Bo, which is an siRNA in
• 15:33
  Speaker 2: partnership with al Nylon that lowers PCSK nine and we've
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  Speaker 2: built on that to have a whole portfolio of s
• 15:39
  Speaker 2: irnas that are targeted to the liver to reduce a
• 15:44
  Speaker 2: number of different cardiovascular you know, risk factors. And the
• 15:47
  Speaker 2: technology here is really advanced because as well as you know,
• 15:51
  Speaker 2: there used to be about every three months, then they
• 15:53
  Speaker 2: went to every six months. Now the chemistry on the
• 15:55
  Speaker 2: oliger nucleotide background, first of all, has reduced any of
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  Speaker 2: the sort of reactive and stimulation of the immune system,
• 16:02
  Speaker 2: so we've been able to get away from that. But
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  Speaker 2: we can also get really very long acting s irnas
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  Speaker 2: potentially now once a year delivery, which you know, if
• 16:09
  Speaker 2: you were just trying to control cardiovascular risk factors, that
• 16:13
  Speaker 2: could be very favorable that you're just having a once
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  Speaker 2: a year injection. The other thing new technology is now
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  Speaker 2: you can make dual sRNAs, so you can target two
• 16:21
  Speaker 2: things together, or you can combine two together. So again
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  Speaker 2: this idea that you could have multiple risk factors controlled
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  Speaker 2: with a sort of multi factorial sRNA is very beneficial.
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  Speaker 2: And then you know what we're really excited about now
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  Speaker 2: is ability to deliver siRNA to other tissues apart from
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  Speaker 2: the liver, and this is what partly led us into
• 16:44
  Speaker 2: the Avidity acquisition, which I'm sure you'll want to say
• 16:47
  Speaker 2: something about but here Avidity had optimized the transferrent receptor
• 16:52
  Speaker 2: antibody to deliver s irna specifically to muscle skeletal muscle
• 16:57
  Speaker 2: for neuromuscular diseases. So we'll come back Vividity. But what
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  Speaker 2: we're trying to do now is to find targets that
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  Speaker 2: allow us to deliver s irna to all the cells
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  Speaker 2: that were interested in, whether that's cardiomyocytes or renal cells
• 17:11
  Speaker 2: or across the blood brain barrier.
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  Speaker 1: So when do we think about sirony versus aentesis? When
• 17:16
  Speaker 1: I look at Pella Carson, it's lp LITTLEA. Obviously it's
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  Speaker 1: a CB risk. So you're targeting pcskenine is n si rna,
• 17:24
  Speaker 1: whereas this one is an anti sense. Do you want
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  Speaker 1: to took us through what led to those two decisions,
• 17:30
  Speaker 1: going down the different parts of mechanisms.
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  Speaker 2: I mean it was partly, you know, we wanted to
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  Speaker 2: in both of those cases really move forward and bring
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  Speaker 2: the first molecule to patients that was effective and you
• 17:45
  Speaker 2: know what would be the best molecule available, And in
• 17:49
  Speaker 2: the case of PCSK nine, it was lec vo, and
• 17:52
  Speaker 2: that partnership led us to take that forward it could
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  Speaker 2: have been an anti sensuligo, but you know that am
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  Speaker 2: to be an s irna same in the case if
• 18:00
  Speaker 2: peller Cassin was actually faster to get an antisen solig nucleotide.
• 18:04
  Speaker 2: We think there's a big first mover advantage of really
• 18:07
  Speaker 2: proving the hypothesis that LP little A lowering will be
• 18:10
  Speaker 2: really important for cardiovascular risk reduction. We will actually know
• 18:15
  Speaker 2: that data quite soon, and we've been able to show
• 18:17
  Speaker 2: in that case that Pello Carson does produce, you know,
• 18:19
  Speaker 2: really very long acting reduction in LP little a that
• 18:24
  Speaker 2: we think will allow us to test the hypothesis and
• 18:27
  Speaker 2: be a meaningful drug. But you know, behind that, we're
• 18:29
  Speaker 2: also developing an sir and A for LP little a
• 18:32
  Speaker 2: so and that will potentially have higher knockdown.
• 18:37
  Speaker 1: So there are a few companies out there. One we
• 18:39
  Speaker 1: recently approved oral PCSKN nine inhibitor from merk with an
• 18:43
  Speaker 1: all standard oral drug, if you want to call it that.
• 18:45
  Speaker 1: I don't know if there's anything standard about anything these
• 18:47
  Speaker 1: days anymore. You have the possibility of fixed those combinations
• 18:52
  Speaker 1: potentially or some sort of if you can avoid drug
• 18:56
  Speaker 1: drug interactions. Could this work here? Could you have an
• 18:58
  Speaker 1: anti SyncE for little A given the dosing schedule, and
• 19:03
  Speaker 1: have also added mechanism either same drug or bispecifics, if
• 19:09
  Speaker 1: that's the right phrase to use, but double acting could
• 19:12
  Speaker 1: that work with plus well.
• 19:14
  Speaker 2: Each of these modalities, whether it's the small molecule or
• 19:18
  Speaker 2: s I R and A I mean, they produce sufficient
• 19:20
  Speaker 2: knockdown of the target in their own right, and so
• 19:23
  Speaker 2: it wouldn't really make sense to give both at the
• 19:26
  Speaker 2: same time, I think in the in these cases. So,
• 19:29
  Speaker 2: but most of this comes from the liver. So these
• 19:32
  Speaker 2: molecules that are targeted to the liver in the case
• 19:35
  Speaker 2: of the oligon nucleotides, do produce very profound inhibition of
• 19:39
  Speaker 2: either pcskn I or LP little eight. So it's more
• 19:42
  Speaker 2: about patient choices. And you know, we're talking about millions
• 19:46
  Speaker 2: of patients here who would be who have cardiovascular risk
• 19:50
  Speaker 2: around the world, even in the US. So of course,
• 19:53
  Speaker 2: as we've even seen with the g l P one situation,
• 19:56
  Speaker 2: some people would rather just have an injection and forget
• 19:59
  Speaker 2: about it, especially if that is you know every other
• 20:02
  Speaker 2: you know, every six months, you can just go to
• 20:04
  Speaker 2: your physician, you have your injection, that's it. You don't
• 20:07
  Speaker 2: need to worry about your medicine. And what we've seen
• 20:10
  Speaker 2: with the statins, for example, is even though people get
• 20:13
  Speaker 2: given their oral statins, I mean a huge number, I
• 20:16
  Speaker 2: think it's something like sixty percent, don't actually take their
• 20:18
  Speaker 2: statins every day as they should do, so they still
• 20:21
  Speaker 2: retain significant risks. So the benefit of these long acting
• 20:25
  Speaker 2: agents is that you know, you don't have that worry
• 20:28
  Speaker 2: about forgetting If you come on vacation, then you've forgotten
• 20:31
  Speaker 2: your medicine. This sort of thing. You just go to
• 20:33
  Speaker 2: the doctor, you get your annual check up for every
• 20:35
  Speaker 2: six months when you get your injection. But other people,
• 20:38
  Speaker 2: you know, they might not like having an injection, they
• 20:40
  Speaker 2: might prefer an oral in in which case you know,
• 20:43
  Speaker 2: they will take one of these oral agents that are
• 20:45
  Speaker 2: coming through. And I think you know, our viewer is
• 20:48
  Speaker 2: that there's plenty of room in the market for both
• 20:50
  Speaker 2: types of modalities.
• 20:52
  Speaker 1: Right now, just talking about the Avidity deal, not specifically
• 20:57
  Speaker 1: the deal, but the science that you required transferring receptors
• 21:02
  Speaker 1: as a as a trojan horse. If that's a fair use,
• 21:06
  Speaker 1: very timely analogy. Yes, I haven't seen it yet, maybe
• 21:10
  Speaker 1: tomorrow night. I think it's just for the sake of
• 21:13
  Speaker 1: those who may be listening where Odyssey is not released,
• 21:16
  Speaker 1: we're talking about that movie. So, but it's been around
• 21:20
  Speaker 1: a long long time as a concept at least, and
• 21:23
  Speaker 1: people have tried to use it. So what's been happening
• 21:25
  Speaker 1: to make it? I mean, because there's a lot of
• 21:27
  Speaker 1: folks who are still using it as particularly for penetrating
• 21:30
  Speaker 1: the brain barrier. Here it's interesting because they're going to
• 21:33
  Speaker 1: have to muscle. I didn't think muscle needed a particular
• 21:38
  Speaker 1: delivery system, but so took us through that. And what
• 21:41
  Speaker 1: your current understanding of the transferring receptor or other ways
• 21:44
  Speaker 1: of trying to get into the brain is, so, I.
• 21:47
  Speaker 2: Mean, you're quite right. Transferring has been known as a
• 21:50
  Speaker 2: transporter and as a delivery system to get into the
• 21:53
  Speaker 2: brain for quite some time. Transferring is expressed on multiple
• 21:56
  Speaker 2: different cell types, but actually lowics quite low expression on
• 22:00
  Speaker 2: the liver compared to muscle, for example. But what's important
• 22:04
  Speaker 2: with the Avidity platform is that all transferring antibodies and
• 22:10
  Speaker 2: ligands are not all the same and they can be
• 22:12
  Speaker 2: tuned to have differential delivery depending on the level of expression.
• 22:17
  Speaker 2: And Avidity was able to optimize the delivery of si
• 22:23
  Speaker 2: R and A to the muscle with their transfer and
• 22:26
  Speaker 2: receptor molecules. So all the transferring molecules are not are
• 22:30
  Speaker 2: not at all the same, and they have different formats
• 22:32
  Speaker 2: of antibodies, different binding affinities, this sort of thing. So
• 22:37
  Speaker 2: you know that that was really what was unique about
• 22:39
  Speaker 2: their platform technology and is.
• 22:41
  Speaker 1: That the same does the same applied to let's use
• 22:45
  Speaker 1: the phrase shuttle brain shuttles.
• 22:47
  Speaker 2: Yeah, all the brain shuttles. I mean that each of
• 22:50
  Speaker 2: them actually has to be optimized for the purpose that
• 22:54
  Speaker 2: you want them for, and in some cases you have
• 22:56
  Speaker 2: to optimize them for the target as well. We actually
• 22:59
  Speaker 2: have I've really put a lot of time and effort
• 23:01
  Speaker 2: into brain shuttles over the last year, and we've done
• 23:04
  Speaker 2: multiple deals with different companies. With a company called Bioarctic
• 23:09
  Speaker 2: signeuro we actually did a transferring amyloid beta that was
• 23:13
  Speaker 2: a brain shuttle. We also have a collaboration with Arrowhead
• 23:16
  Speaker 2: and some of these are different shuttles, not just transferring,
• 23:19
  Speaker 2: different brain shuttles. So this is a huge exploding area
• 23:24
  Speaker 2: of interest in how you can actually deliver shuttle you know,
• 23:28
  Speaker 2: deliver molecules to the brain biologics, and you do need
• 23:31
  Speaker 2: different shuttles, whether it's an antibody you want to deliver
• 23:34
  Speaker 2: or if it's an s irna for example, and also
• 23:37
  Speaker 2: whether you want to get ce ans delivery or muscle.
• 23:41
  Speaker 2: If you do muscle, do you want to get skeletal
• 23:43
  Speaker 2: muscle as well as cardiac muscle. So there's lots of
• 23:47
  Speaker 2: opportunity for optimization here and continued improvement.
• 23:51
  Speaker 1: Can these also work with small molecules, not just RNAs.
• 23:55
  Speaker 2: Not so well. Peptides yes, not so much a small molecule.
• 24:00
  Speaker 1: Interesting, So, if we think about the brain, one of
• 24:04
  Speaker 1: the questions I've always had in my mind is if
• 24:06
  Speaker 1: there's any way that you could modulate the distribution within
• 24:10
  Speaker 1: the brain, because these things get in and then you
• 24:13
  Speaker 1: kind of rely on diffusion. I suppose to try and
• 24:16
  Speaker 1: get the drug to deeper parts of the brain, et cetera.
• 24:20
  Speaker 1: Talk to us about that, because there are some parts
• 24:22
  Speaker 1: where you want to impact.
• 24:24
  Speaker 2: That's immediately a very interesting You're completely right, Sam, and
• 24:27
  Speaker 2: this is a very interesting area. And you know, either
• 24:31
  Speaker 2: you can actually use small molecules to deliver s irna
• 24:36
  Speaker 2: into specific brain areas. So in this case you're thinking
• 24:40
  Speaker 2: about you know, neurotransmitter receptors for example, you can actually
• 24:44
  Speaker 2: have maybe a peptide or a small molecule attached to
• 24:47
  Speaker 2: an s irna that would then allow take up into
• 24:51
  Speaker 2: particular neuronal subpopulations. So that's one possibility for what you're suggesting.
• 24:57
  Speaker 2: Another very interesting technology is actually gene therapy, and this
• 25:02
  Speaker 2: is something we continue to really invest in. We acquired
• 25:04
  Speaker 2: a company called Kate Therapeutics and they have optimized a
• 25:09
  Speaker 2: capsid a you know, aave capsids for muscle delivery for
• 25:13
  Speaker 2: neuromuscular disease. So we're actually doing you know, the same
• 25:17
  Speaker 2: diseases with avidity, but you know, behind that the next
• 25:19
  Speaker 2: wave could potentially be gene therapy. But those once you
• 25:23
  Speaker 2: do the gene delivery, then you can deliver something that
• 25:27
  Speaker 2: includes a promoter that can be specific to specific neurons,
• 25:32
  Speaker 2: so you can all specific cells. So it's it's what
• 25:35
  Speaker 2: you're delivering is then only expressed in certain cells, and
• 25:39
  Speaker 2: you can actually incorporate ways of turning it off in
• 25:42
  Speaker 2: the cells where you don't want that gene to be expressed.
• 25:44
  Speaker 2: So that's a pretty exciting future technology, I think for
• 25:47
  Speaker 2: the neuroscience area.
• 25:49
  Speaker 1: So I want to keep going on about neuroscience obviously
• 25:52
  Speaker 1: that's for a little while anyway, And where do you
• 25:56
  Speaker 1: when do you think these are going to be visible
• 25:59
  Speaker 1: to the list world, which I belong to, because we
• 26:02
  Speaker 1: start getting excited by stuff and be able to assess
• 26:05
  Speaker 1: them and analyze them when they get into the clinic.
• 26:08
  Speaker 1: What's the time frame here in.
• 26:10
  Speaker 2: Well, I mean, first of all, of course, the avidity
• 26:12
  Speaker 2: portfolio is now visible and we've got data coming out
• 26:16
  Speaker 2: there which is validating the ability. When we had the
• 26:19
  Speaker 2: recent data with the f SHD molecule which showed that
• 26:23
  Speaker 2: we could get delivery to muscle and we could use
• 26:26
  Speaker 2: that to knock down the aberrant protein called Ducks four,
• 26:29
  Speaker 2: which is a transcription factor, we showed reduction in the
• 26:32
  Speaker 2: downstream genes and we actually short saw benefits or muscle
• 26:36
  Speaker 2: biology through c K which so you know that technology
• 26:42
  Speaker 2: is coming through. And then the gene therapy, you know,
• 26:44
  Speaker 2: we're advancing into the clinic, you know within a year
• 26:48
  Speaker 2: where we'll be starting to see that. Another technology that
• 26:52
  Speaker 2: you know I haven't mentioned here is one that's also
• 26:54
  Speaker 2: in the clinic where we have a lipid modified sir
• 26:57
  Speaker 2: and A. This came from a collaboration at Aquis of
• 27:00
  Speaker 2: a company called DTX and this is a molecule for
• 27:03
  Speaker 2: charco married tooth disease, So it's another neuromuscular disease. And
• 27:07
  Speaker 2: this is a muscle again, muscle delivery and an SR
• 27:11
  Speaker 2: and a knockdown. But here a lipid has been optimized
• 27:14
  Speaker 2: to be taken up into muscle or one of the
• 27:17
  Speaker 2: most common neuromuscular diseases. So this is also it's in
• 27:21
  Speaker 2: patience right now in ascending DOSA sending. So as we
• 27:25
  Speaker 2: start to get clinical data coming out, of course we'll
• 27:27
  Speaker 2: be reporting this at various congresses.
• 27:30
  Speaker 1: And these all fit really well with the current portfolio
• 27:34
  Speaker 1: that in the muscle worlds all genes more clearly a
• 27:38
  Speaker 1: world changing therapy for the patients who benefit from it
• 27:42
  Speaker 1: they can access it. But thinking about the CNS side
• 27:44
  Speaker 1: of things, and let's let's try and draw a line
• 27:47
  Speaker 1: between neurology and neuropsychiatry. Thinking about neurology, we've talked about
• 27:52
  Speaker 1: al Zhemer's already. Do you think we're going to be
• 27:54
  Speaker 1: able to get close One of the issues that I
• 27:57
  Speaker 1: think we all know and the community faces is that
• 28:01
  Speaker 1: you often can't get enough into the brain to get
• 28:05
  Speaker 1: the impact that you need. You know, if it was
• 28:07
  Speaker 1: with naked antibodies to start with, now we're trying to
• 28:10
  Speaker 1: get the brain shuttles. Do you think we're going to
• 28:12
  Speaker 1: get to a point where two or three percent of
• 28:14
  Speaker 1: the antibody as opposed too point two percent or whatever
• 28:16
  Speaker 1: the number is, it can get of a naked anybody,
• 28:19
  Speaker 1: It can get into the brain and do what it
• 28:20
  Speaker 1: needs to do, or whatever other mechanism it is.
• 28:23
  Speaker 2: Yeah, yes, I think so. I think we're approaching that
• 28:25
  Speaker 2: with some of these new shuttles to get certainly. And
• 28:28
  Speaker 2: you know, you're also trying to make the antibody itself
• 28:31
  Speaker 2: more potent so that you know, you need less anyway,
• 28:34
  Speaker 2: And we have got a very exciting antibody coming forwards
• 28:38
  Speaker 2: in the clinic already for ALS, also for AD. This
• 28:42
  Speaker 2: is what's called a TREMD two agonist antibody, and this
• 28:46
  Speaker 2: is on microglia. So it's another one of the really
• 28:49
  Speaker 2: strong genetically linked targets to Alzheimer's disease. And these microglear cells,
• 28:55
  Speaker 2: if you like, they're the brain's immune system and they
• 28:59
  Speaker 2: can be in a p detective mode where they reduce
• 29:01
  Speaker 2: your chances of getting the disease, but they can also
• 29:04
  Speaker 2: switch over into a pro inflammatory mode. And what trem
• 29:07
  Speaker 2: too does is to stabilize them in the neuroprotective mode,
• 29:10
  Speaker 2: and so you know that one we you know, we've
• 29:13
  Speaker 2: actually shown that that doesn't have a shuttle, but it's
• 29:16
  Speaker 2: been optimized to get into the CNS. We've been able
• 29:19
  Speaker 2: to show good evidence of target engagement by taking CSF
• 29:23
  Speaker 2: samples and sharing bymarkers consistent with this switch to the
• 29:28
  Speaker 2: neuroprotective phenotype. So yeah, I think there's a lot of
• 29:32
  Speaker 2: interest and excitement about these new targets coming forward. For Alzheimer's, that's.
• 29:38
  Speaker 1: So trim two targeting, that's not for ALS, that's yeah, yeah,
• 29:42
  Speaker 1: it is fair.
• 29:43
  Speaker 2: As as well, both of them. The genetics was from Alzheimer's,
• 29:46
  Speaker 2: but it pointed to microglear, but there's growing understanding of
• 29:49
  Speaker 2: the very important role of microglear in contributing to ALS
• 29:53
  Speaker 2: as well.
• 29:54
  Speaker 1: Unfortunately, like Alzheimer's, I've had very close contact with or
• 30:00
  Speaker 1: contacts and friends who have been impacted by ALS. What
• 30:03
  Speaker 1: the x CEO of Bloomberg actually is suffering from motain
• 30:07
  Speaker 1: neuron disease. But the question then comes to particularly for
• 30:11
  Speaker 1: all of these diseases, you know, the brain's capacity to
• 30:13
  Speaker 1: adapt and this plasticity enables us to continue to function
• 30:17
  Speaker 1: without obviously showing signs of disease for quite a while,
• 30:22
  Speaker 1: and when it does start showing signs of disease is
• 30:24
  Speaker 1: quite not too late, because you can also try and
• 30:27
  Speaker 1: hold reversing. I think is a tough expectation because if
• 30:31
  Speaker 1: you've lost neurons you anyway, how do you think that
• 30:35
  Speaker 1: will actually pan out as a clinical use for als
• 30:39
  Speaker 1: and Alzheimer's or Parkinson's, pick your disease.
• 30:42
  Speaker 2: Now, you're absolutely right there, Sam, and I think it
• 30:46
  Speaker 2: is very difficult to What we're trying to do is
• 30:49
  Speaker 2: slow the progression of the disease, and that you know,
• 30:51
  Speaker 2: the more advanced you go in the disease, the more difficult,
• 30:54
  Speaker 2: the more function that you've lost. And so you really,
• 30:58
  Speaker 2: you know, the answers you want to get in very
• 30:59
  Speaker 2: early and move to you know, as early as you
• 31:03
  Speaker 2: can to intervene in the disease, ideally either when symptoms
• 31:07
  Speaker 2: are only just starting or if possible, even before that.
• 31:11
  Speaker 2: And what's very good is that you know, we're getting
• 31:13
  Speaker 2: much better buyo markers to diagnose and these can even
• 31:16
  Speaker 2: be plasma bio markers, and we found this in Alzheimer's.
• 31:19
  Speaker 2: There are now circulating plasma biomarkers of phosphorlated tau for example,
• 31:24
  Speaker 2: that can you know, to diagnose Alzheimer's much earlier. You know,
• 31:30
  Speaker 2: there's also some biomarkers that you can use for other
• 31:34
  Speaker 2: diseases like Parkinson's disease and als that are being developed
• 31:37
  Speaker 2: and monitored. And of course once you have a therapy,
• 31:39
  Speaker 2: that drives the biology to search because finding things earlier,
• 31:43
  Speaker 2: if there's no therapy, you know that that be actually
• 31:46
  Speaker 2: quite devastating, frustrating, and there's no real drive and motivation.
• 31:49
  Speaker 2: But once you have a therapy, you know this could
• 31:51
  Speaker 2: be really good if you could give it earlier. That
• 31:53
  Speaker 2: then really drives the field to want to be better
• 31:56
  Speaker 2: at diagnosing and intervening earlier. So that's certainly our strat
• 32:00
  Speaker 2: g for all of these neurodegenerative diseases to try and
• 32:02
  Speaker 2: go as early as possible and to produce the maximum benefit.
• 32:07
  Speaker 2: Saying for the muscular dystrophees by the way, because again
• 32:10
  Speaker 2: these are progressive diseases, and you know, we start in
• 32:14
  Speaker 2: the sort of you know, in our clinical trials are
• 32:16
  Speaker 2: in adults and teenagers, but as quickly as possible we
• 32:19
  Speaker 2: will go into younger patients so that we can you know,
• 32:22
  Speaker 2: really try and intero dealing before they've had significant loss
• 32:26
  Speaker 2: of function.
• 32:26
  Speaker 1: So let's let's talk about this Alzheimer's. You've mentioned air lists,
• 32:30
  Speaker 1: you've mentioned what other neurological diseases are you no artists
• 32:34
  Speaker 1: looking at?
• 32:34
  Speaker 2: I mean, yeah, well we pretty much cover all of them,
• 32:38
  Speaker 2: so Parkinson's disease as well. I mean nothing I can
• 32:41
  Speaker 2: specifically talk about except that we do have. We do
• 32:45
  Speaker 2: think inflammation is a major contributor across the neurodegenerative diseases,
• 32:49
  Speaker 2: as I mentioned with microglia, but other other neuroinflammation. So
• 32:54
  Speaker 2: I'm very interested in pathways that actually could be you know,
• 32:57
  Speaker 2: a pan neurodegenerative therapy. So we have a number of
• 33:01
  Speaker 2: areas there that we're looking at. The other area is
• 33:04
  Speaker 2: Huntington's disease. So we do actually have a molecule called
• 33:08
  Speaker 2: Wotter plan which is in phase two three for Huntington's disease.
• 33:12
  Speaker 2: And that's a small molecule that lowers Huntington And you
• 33:16
  Speaker 2: know that one's reading out as well. So neurge generative
• 33:20
  Speaker 2: diseases across the board are within our area of interest
• 33:24
  Speaker 2: for sure.
• 33:25
  Speaker 1: I'm going to push you somewhere where I don't think
• 33:28
  Speaker 1: it's fair, but as we can talk about it hypothetically.
• 33:30
  Speaker 1: One of the problems. We've just done a research project
• 33:32
  Speaker 1: here looking at what Europe, for example, which is a
• 33:36
  Speaker 1: you know, four hundred odd million people, needs to spend
• 33:38
  Speaker 1: on defense, industrial base, it's technology base to just be
• 33:44
  Speaker 1: able to be to have a meaningful amount of sovereignty
• 33:48
  Speaker 1: in those areas, and we came up with a fourteen
• 33:50
  Speaker 1: trillion euro number by twenty thirty five. The problem I
• 33:54
  Speaker 1: worry about there is that somewhere, somehow along the way,
• 33:57
  Speaker 1: people have to balance what they pay for different things,
• 34:00
  Speaker 1: and healthcare seems to always be at these pharmaceuticals, where
• 34:04
  Speaker 1: as we can see in Germany which seems to be
• 34:06
  Speaker 1: never ending in terms of the pressure they're putting on
• 34:08
  Speaker 1: drugs and drug pricing. Do you hope that if we
• 34:12
  Speaker 1: got the right drugs and what sort of assuming we
• 34:15
  Speaker 1: had meaningful clinical benefit, that countries will want to pay
• 34:19
  Speaker 1: for it, given that, I mean to a degree, the
• 34:21
  Speaker 1: saving comes in about twenty years time, avoiding these people
• 34:25
  Speaker 1: like possibly myself, from developing diseases and being a burden.
• 34:29
  Speaker 1: Do you see or when you speak to people that
• 34:33
  Speaker 1: are in those kind of jobs, and roads that there's
• 34:36
  Speaker 1: willingness to think about this as a genuine Well, yeah,
• 34:39
  Speaker 1: this is a.
• 34:39
  Speaker 2: Very very hot hot topic and it actually, Sam's very
• 34:42
  Speaker 2: interesting you mentioned this because the Alzheimer's Society just literally
• 34:46
  Speaker 2: published a report and this is in the UK specifically,
• 34:49
  Speaker 2: but about twenty five percent of hospital beds are actually
• 34:53
  Speaker 2: occupied long term by patients with dementia, and of course
• 34:57
  Speaker 2: those beds that really should be taken up with people
• 35:00
  Speaker 2: who have other diseases that need acute hospital care. And
• 35:04
  Speaker 2: so this is a huge burden on the NHS in
• 35:07
  Speaker 2: the case of the UK, on healthcare providers, huge burden
• 35:11
  Speaker 2: on cares. How many carers actually are out of employment
• 35:15
  Speaker 2: because they have to look after people who have neurodegenerative diseases.
• 35:19
  Speaker 2: So if you take all those things into account, Actually
• 35:22
  Speaker 2: the Alzheimer's Society has commented that, you know, drugs that
• 35:25
  Speaker 2: would be effective for these diseases would actually be very
• 35:28
  Speaker 2: a cost benefit if you do the calculations correctly in
• 35:31
  Speaker 2: terms of saving on healthcare systems, allowing people to stay
• 35:36
  Speaker 2: out of care, to not need full time care. So
• 35:38
  Speaker 2: I think this is all all a case of how
• 35:40
  Speaker 2: you do your healthcare economics, and I certainly hope that
• 35:44
  Speaker 2: we can bring drugs that are you know, really having
• 35:47
  Speaker 2: a meaningful benefit, that you know, these calculations should result
• 35:51
  Speaker 2: in society really believing that these are worth paying for.
• 35:55
  Speaker 1: I mean, of artists did actually become quite pioneering in
• 35:58
  Speaker 1: some of these health economic calculations and the ways to
• 36:01
  Speaker 1: pay for it, and with particularly with the UK. I
• 36:04
  Speaker 1: have to say I haven't followed to see how that
• 36:06
  Speaker 1: all panned out in the end, because it all sounds fantastic.
• 36:09
  Speaker 1: Well let's not let's not go there now. Now. I
• 36:12
  Speaker 1: want to say a phrase, we are entering a new
• 36:15
  Speaker 1: era in neuro or neurological diseases, yes or no?
• 36:20
  Speaker 2: Oh, yes, for sure. I mean all these things we're doing,
• 36:22
  Speaker 2: I mean, we couldn't have done these even five years ago,
• 36:25
  Speaker 2: let alone ten years ago. And but I think the
• 36:27
  Speaker 2: other thing that we haven't talked about. These are all technologies,
• 36:30
  Speaker 2: but I think the more important thing is actually the
• 36:32
  Speaker 2: real understanding of what is the driver and cause of
• 36:35
  Speaker 2: these diseases, which we didn't know before, and the first
• 36:39
  Speaker 2: waves of treatments for very much around the symptoms of
• 36:41
  Speaker 2: the disease the consequences, rather than trying to intervene on
• 36:46
  Speaker 2: the underlying causes of the disease. So I think that's
• 36:49
  Speaker 2: what's very different as well.
• 36:50
  Speaker 1: Okay, great, This actually one of the things as we spoke,
• 36:55
  Speaker 1: you mentioned quite a few acquisitions by novartists. So I
• 37:00
  Speaker 1: want to talk about two things. One is, obviously all
• 37:03
  Speaker 1: companies say the same thing. We are agnostic if the
• 37:06
  Speaker 1: science is great ext elsewhere, we are not just about
• 37:10
  Speaker 1: everything has to be done inside and no artists something
• 37:12
  Speaker 1: has been very open about it. All former companies are.
• 37:16
  Speaker 1: I'm assuming there's no target. You just look at idea.
• 37:19
  Speaker 1: You know, if something comes along that makes sense, you're acquired.
• 37:22
  Speaker 1: You don't have a thirty percent target, forty percent target
• 37:25
  Speaker 1: of projects have to be sourced externally. I'm assuming you
• 37:28
  Speaker 1: can correct me if I'm wrong, But then you also
• 37:31
  Speaker 1: have I want to also take this into the next
• 37:33
  Speaker 1: stage of discussing the pressure on science in general, particularly
• 37:38
  Speaker 1: in the US. Now, I have to base this on
• 37:42
  Speaker 1: the small n that I have. I sit with some
• 37:45
  Speaker 1: I go particularly to oncology conferences, sit with some of
• 37:48
  Speaker 1: the most amazing oncology scientists, immunologists, and this particular AACR
• 37:55
  Speaker 1: conference I went to, there was a lot of worry,
• 37:59
  Speaker 1: a lot of pressure and worry about whether they can
• 38:02
  Speaker 1: keep getting their funding, whether they can continue to find
• 38:04
  Speaker 1: Now that science translates to bio biotech companies translates to
• 38:09
  Speaker 1: acquisition potential and knowledge, what is your feeling about this
• 38:13
  Speaker 1: and understanding of how this is panning out, because there
• 38:15
  Speaker 1: is it's palpable that that pressure on science, at least
• 38:18
  Speaker 1: in the US. I mean, Europe has had issues trying
• 38:21
  Speaker 1: to trying to fund the stuff, but I think we're
• 38:24
  Speaker 1: still managing.
• 38:26
  Speaker 3: Yeah.
• 38:26
  Speaker 2: I mean, you know, I think academic science, publicly funded
• 38:30
  Speaker 2: science is really essential for scientific innovation. I mean, there
• 38:35
  Speaker 2: is innovation within companies and within Farmer certainly we do
• 38:39
  Speaker 2: a lot, but if you look across you know, drug
• 38:42
  Speaker 2: drugs on the market, a lot of those foundational the
• 38:46
  Speaker 2: foundational work behind those understanding of diseases has come from
• 38:50
  Speaker 2: publicly funded research. And so you know, also we've got
• 38:55
  Speaker 2: to remember that the training of scientists that then later
• 38:59
  Speaker 2: go into industry, you come through those universities, and then
• 39:02
  Speaker 2: you know, we want scientists that have done PhDs, post ops,
• 39:06
  Speaker 2: that are active in research. So it's a talent pool
• 39:09
  Speaker 2: as well. So there's many reasons why, you know, it
• 39:12
  Speaker 2: is really important for countries to maintain their academic investment.
• 39:17
  Speaker 2: There's economic, no question, economic benefit to the countries in
• 39:21
  Speaker 2: doing that. You know, In since I've joined the Artists,
• 39:24
  Speaker 2: We've had something like two hundred different academic collaborations around
• 39:29
  Speaker 2: the world, many of them of course in the US,
• 39:31
  Speaker 2: actually many in Europe as well. And these are you know,
• 39:34
  Speaker 2: great partnerships that we have, and you know, they you
• 39:37
  Speaker 2: know really sort of you know, we can combine capabilities
• 39:40
  Speaker 2: of new emerging science that we can then translate into medicine.
• 39:44
  Speaker 2: So you know, as an industry, I'm part of the
• 39:49
  Speaker 2: Farmer Foundation, which many many pharmaceutical companies are, and we
• 39:53
  Speaker 2: do we do put direct funding into you know, post
• 39:57
  Speaker 2: docs and PhD students and new US researchers. But this
• 40:01
  Speaker 2: is you know, really a drop in the ocean compared
• 40:03
  Speaker 2: to the whole sort of government funding that is needed.
• 40:06
  Speaker 2: So you know, certainly, you know, I'm a strong advocate
• 40:09
  Speaker 2: if I ever get to speak to government in the
• 40:12
  Speaker 2: US or the UK for that matter as well, about
• 40:14
  Speaker 2: the importance of funding academic science and also not to
• 40:18
  Speaker 2: have too much control by government. I mean, I certainly
• 40:22
  Speaker 2: see the rationale for aligning economic benefit with academic funding
• 40:28
  Speaker 2: that the question is who makes that judgment, And a
• 40:30
  Speaker 2: lot of what would be considered blue sky research actually
• 40:33
  Speaker 2: does translate into really important, meaningful therapies. And if I
• 40:38
  Speaker 2: go back to the company that I spun out of
• 40:40
  Speaker 2: the Laboratory of Molecular Biology, Heptaris, you know that that
• 40:44
  Speaker 2: was elect cryo electron microscopy. You know, might have been
• 40:48
  Speaker 2: seen as a very sort of academic type of approach
• 40:52
  Speaker 2: of trying to look at protein crystals under an electron microscope,
• 40:55
  Speaker 2: but you know that then funding took over many, many
• 40:59
  Speaker 2: decades of research. Richard Henderson got the Nobel price for it,
• 41:03
  Speaker 2: but that allowed us to then really design drugs using
• 41:06
  Speaker 2: cryoelectron microscopy, you know that are now in the late
• 41:08
  Speaker 2: stage clinical trials, so that there can be a disconnect
• 41:12
  Speaker 2: in the time exactly as you've said, where you make
• 41:14
  Speaker 2: that investment and then later on where you get the
• 41:17
  Speaker 2: economic benefit. But it's certainly very important to maintain this funding.
• 41:21
  Speaker 1: So on a scale of zero to ten, how worried
• 41:25
  Speaker 1: are you about the current state of science funding in
• 41:28
  Speaker 1: the United States, which is one of the biggest funders
• 41:31
  Speaker 1: of well.
• 41:32
  Speaker 2: I am one of life's eternal optimists, and I have
• 41:36
  Speaker 2: seen funding go up and down over time, so I
• 41:39
  Speaker 2: like to think that there are mechanisms in place to
• 41:43
  Speaker 2: reset to where things should be over time. So, you know,
• 41:47
  Speaker 2: I have got some concerns at the moment, but understand
• 41:50
  Speaker 2: that there are obviously a lot of different pressures on
• 41:53
  Speaker 2: governments around the world in terms of where they're spending
• 41:56
  Speaker 2: their money, and you know, I just hope that money
• 42:00
  Speaker 2: will continue to be found for research.
• 42:03
  Speaker 1: Well, we have about fifteen minutes left and I'm going
• 42:06
  Speaker 1: to go to AI now, artificial intelligence in drug discovery.
• 42:11
  Speaker 1: So Britson is saying that it's not about new technology
• 42:16
  Speaker 1: example AI, but the people that harness it internally has
• 42:19
  Speaker 1: no artists, got the right people to harness it. I mean,
• 42:21
  Speaker 1: this is every company is dealing with this. We are
• 42:24
  Speaker 1: dealing with this, trying to get our colleagues to use
• 42:27
  Speaker 1: AI cleverly, right, So what's going on at novartis on
• 42:33
  Speaker 1: this front.
• 42:34
  Speaker 2: Yeah, So, I mean I have some agreement with Brent.
• 42:37
  Speaker 2: I mean, it's not just about the tools, but it
• 42:39
  Speaker 2: is always who is using them and how you are
• 42:41
  Speaker 2: using them, no question about that. So I really wanted
• 42:46
  Speaker 2: to make sure that it might just talk about biomedical research.
• 42:50
  Speaker 2: But this is happening across nev artists to make sure
• 42:52
  Speaker 2: that we do have the right organizational structure to enable
• 42:55
  Speaker 2: AI to deliver the potential that it has. So one
• 42:59
  Speaker 2: of the things that I I'd done quite recently is
• 43:01
  Speaker 2: to put a head of Data and Digital on my
• 43:04
  Speaker 2: leadership team that wasn't there before, so all discussions now
• 43:08
  Speaker 2: have ahead of Data and Digital who thinks in that way.
• 43:10
  Speaker 2: Then also asked for every single one of my leadership team,
• 43:14
  Speaker 2: whether they're head of boncology, head of codibascular, each of
• 43:17
  Speaker 2: them must have a data scientist on their leadership team,
• 43:20
  Speaker 2: so that any meeting around the table you have somebody
• 43:23
  Speaker 2: that really sort of understands the technology and how it
• 43:26
  Speaker 2: can be applied and is thinking in that way. And
• 43:29
  Speaker 2: then you know, what used to be the case is
• 43:32
  Speaker 2: that the data scientists tended to be lowered down in
• 43:35
  Speaker 2: the organization. You'd have wet lab scientists running things, doing
• 43:39
  Speaker 2: experiments and then sort of asking the data scientists almost
• 43:41
  Speaker 2: as a service, to do the analysis. And what I've
• 43:44
  Speaker 2: tried to do is actually turn that upside down so
• 43:46
  Speaker 2: that quite often now it's the data scientists that are
• 43:48
  Speaker 2: designing the experiments that the experiments are fit for AI
• 43:52
  Speaker 2: analysis and enablement. So we have, for example, our head
• 43:55
  Speaker 2: of computational chemistry now runs a new department called you know,
• 44:00
  Speaker 2: Digital Design, and that has both wet lab as well
• 44:03
  Speaker 2: as dry lab chemists within the mix. And the other
• 44:07
  Speaker 2: thing is to think about where is AI going to
• 44:09
  Speaker 2: have the most impact. One of the areas I'm most
• 44:11
  Speaker 2: excited about is really discovering sort of new biology and
• 44:15
  Speaker 2: doing things that we didn't find before without AI. So
• 44:19
  Speaker 2: set up a new department called Target Identification that is
• 44:23
  Speaker 2: again led by a data scientist and using AI to
• 44:27
  Speaker 2: really go across different disease areas, work with the disease
• 44:30
  Speaker 2: area groups and bring AI to those disease area groups
• 44:34
  Speaker 2: and use AI to discover new targets. So it's really
• 44:38
  Speaker 2: important to have the right organizational structures and the right
• 44:41
  Speaker 2: people in place. And all of my other colleagues across
• 44:46
  Speaker 2: nev Artists, including Vas himself, you know, the CEO has
• 44:51
  Speaker 2: an AI digital person reporting to him. Everybody is now
• 44:54
  Speaker 2: thinking in that same way about having those people around
• 44:57
  Speaker 2: the table. And the other thing is like really training everybody,
• 45:01
  Speaker 2: bringing them all up you know what we call AI fluency.
• 45:04
  Speaker 2: So make sure everybody has access to the right types
• 45:08
  Speaker 2: of AI. They know how to use them, when to
• 45:10
  Speaker 2: use them, when not to use them, but also understand
• 45:13
  Speaker 2: what the risks are, what's appropriate and you know, also
• 45:17
  Speaker 2: governed by sort of legal have the right governance in
• 45:19
  Speaker 2: place in the way that we use AI.
• 45:22
  Speaker 1: Putting aside target identification, which which brings if it's new
• 45:26
  Speaker 1: biology or new target, et cetera. And where do you
• 45:29
  Speaker 1: see can you already quantify within your realm productivity gains?
• 45:35
  Speaker 2: Can you already yeah, well yes, I mean we can
• 45:38
  Speaker 2: see I think molecule design, whether that's small molecules or biologics, antibodies,
• 45:44
  Speaker 2: which are enabled by AI, and we very strongly have
• 45:48
  Speaker 2: this sort of AI is augmenting the human human in
• 45:51
  Speaker 2: the loop way of working. And we are already seeing
• 45:56
  Speaker 2: first of all, molecules that were targets that were particularly
• 45:59
  Speaker 2: difficult that we tried many times before to find molecules
• 46:04
  Speaker 2: and we were not able to do so. With the
• 46:06
  Speaker 2: help of AI, you know, we are now finding molecules
• 46:09
  Speaker 2: to what we thought were sort of undruggable target So
• 46:12
  Speaker 2: that's something again getting AI to do something that we
• 46:15
  Speaker 2: couldn't do before. But the other interesting one is just
• 46:19
  Speaker 2: the time obviously productivity time, which I think you're trying
• 46:22
  Speaker 2: to get to and you know, what we're assessing is
• 46:25
  Speaker 2: that you can get about a thirty percent reduction in
• 46:28
  Speaker 2: cycle time. This is within the early discovery stages, from
• 46:33
  Speaker 2: when you start a target to when you're getting to
• 46:35
  Speaker 2: a candidate. We think the average can go from sort
• 46:39
  Speaker 2: of three three to four years down to you know,
• 46:42
  Speaker 2: eighteen months to two years, and we're starting to see
• 46:45
  Speaker 2: examples of where that's the case. Doesn't happen in every project,
• 46:48
  Speaker 2: of course, but the ones where it can really speed
• 46:51
  Speaker 2: up is where you already have information. And then the
• 46:56
  Speaker 2: other areas where it can really speed things up is
• 46:58
  Speaker 2: in clinical trial design in an optimization and very meaningful.
• 47:03
  Speaker 2: We've even got examples of where we've used modeling and
• 47:06
  Speaker 2: modeling is enabled by AI. But I mean there's a
• 47:09
  Speaker 2: sort of gray area to what's AI and what sort
• 47:11
  Speaker 2: of advanced computational modeling to use clinical data to really
• 47:16
  Speaker 2: accelerate maybe even go straight from phase one to phase three,
• 47:19
  Speaker 2: which of course is hugely beneficial from a productivity.
• 47:23
  Speaker 1: I think the regulators are are not that we really
• 47:26
  Speaker 1: foramples where I regulate.
• 47:27
  Speaker 2: Yes, Actually, the regulators and the US are very interested
• 47:31
  Speaker 2: in these types of approaches.
• 47:33
  Speaker 1: I mean, this is great for patients. What makes me
• 47:35
  Speaker 1: a little sad is that however fast you get a
• 47:38
  Speaker 1: product to market. Of course, it gives you longer pattern life,
• 47:41
  Speaker 1: but then you still have things like the Inflation Reduction
• 47:43
  Speaker 1: Act they get in and impact the pricing and the
• 47:47
  Speaker 1: profit that you can you can gain from that. But
• 47:50
  Speaker 1: that's okay. I mean, it's part of the part of
• 47:52
  Speaker 1: the process. And in terms of so, I've heard the
• 47:55
  Speaker 1: number thirty percent quite often from various leaders in your
• 47:59
  Speaker 1: type of position, and that seems to be unless you've
• 48:02
  Speaker 1: all agreed in the background, let's talk about thirty percent.
• 48:04
  Speaker 1: This seems to be quite a quite a common number.
• 48:08
  Speaker 2: It is a real number.
• 48:09
  Speaker 1: Yeah, now so, but the reason the only issue with
• 48:11
  Speaker 1: that is, if I think about this, a lot of
• 48:14
  Speaker 1: that reward comes in about six seven years time. You've
• 48:19
  Speaker 1: got an undruggable target that you've drugged, You've got it
• 48:22
  Speaker 1: a faster preclinical, you've got a faster clinical to get
• 48:26
  Speaker 1: the profit back that's in or revenue back for it
• 48:30
  Speaker 1: is in six is there is this productivity gain going
• 48:35
  Speaker 1: to also mean a potential near term increase in R
• 48:39
  Speaker 1: and D. I mean, are you. Let's talk about the
• 48:42
  Speaker 1: the R part of it. You're doing the R part
• 48:44
  Speaker 1: of it right, the D we can do. You have
• 48:47
  Speaker 1: a sense that, oh, in the next year or two,
• 48:50
  Speaker 1: I need to watch my research budget because my token
• 48:53
  Speaker 1: use has gone through the roof. How does this work?
• 48:56
  Speaker 1: I'm trying to understand that.
• 48:58
  Speaker 2: Yeah, I mean we have a sort of research budget
• 49:00
  Speaker 2: which is around twenty percent of our sales, so that
• 49:04
  Speaker 2: that is the research budget, and what we're trying to
• 49:06
  Speaker 2: do is make sure we're even more productive with AI,
• 49:09
  Speaker 2: with using those tools so that we get more out
• 49:12
  Speaker 2: of what we're putting into it. So we have enterprise
• 49:15
  Speaker 2: wide token budget of course, but that's that's run across
• 49:19
  Speaker 2: nev artists. We try not to have our scientists worry
• 49:22
  Speaker 2: about that. You know that they we want them to
• 49:25
  Speaker 2: use AI as much as possible and if somebody goes
• 49:28
  Speaker 2: over their sort of allocation, then they can ask for
• 49:31
  Speaker 2: some more. So at the moment, we actually think it's
• 49:34
  Speaker 2: a it's a small and worthwhile spend.
• 49:36
  Speaker 1: Right, Okay. So one of the other things that I've
• 49:39
  Speaker 1: always wondered about is that as no artists and the
• 49:41
  Speaker 1: many many years you've been in the world of drug development,
• 49:45
  Speaker 1: you have an enormous amount of data in house. So
• 49:49
  Speaker 1: there's two questions I want to target here. One is
• 49:52
  Speaker 1: a lot of these tools or models that are trained
• 49:55
  Speaker 1: on publicly available information. I tend to be a little
• 49:59
  Speaker 1: bit biased by nature of the fact that people don't
• 50:01
  Speaker 1: publish negative data or data that's ambiguous, whereas no artists
• 50:06
  Speaker 1: in house and other farmer companies do have that data.
• 50:09
  Speaker 1: Does that give you a competitive age in specific disease
• 50:13
  Speaker 1: areas that you've been active in more than others? And
• 50:16
  Speaker 1: then does it give you a competitive edge over biotech
• 50:19
  Speaker 1: companies because they don't have that information? And can you
• 50:23
  Speaker 1: access all the data that you've got in little lab
• 50:26
  Speaker 1: books going back handwritten, going back to twenty I don't
• 50:30
  Speaker 1: know when I was a scientist in nineteen ninety eight
• 50:33
  Speaker 1: and ninety nine and two thousand and et cetera. How
• 50:36
  Speaker 1: does that allget This.
• 50:38
  Speaker 2: Is a really interesting, very important point. Sam. Of course,
• 50:40
  Speaker 2: it's essential to have the right data to train the
• 50:44
  Speaker 2: AI models. And again I think nev artists must have
• 50:47
  Speaker 2: had good full sight because I think one of the
• 50:49
  Speaker 2: few companies that really set up a big data lake,
• 50:53
  Speaker 2: we call it Data forty two. It's on a Palenteer
• 50:56
  Speaker 2: Foundry database that contains all clinical trials going back sort
• 51:00
  Speaker 2: of thirty years, which of course it does include, you know,
• 51:03
  Speaker 2: even down to individual patient information data results. And I
• 51:09
  Speaker 2: were super enthusiastic about using data forty two and actually
• 51:13
  Speaker 2: moved it with it in biomedical research, established a whole
• 51:16
  Speaker 2: group around it. And what we're now doing is adding
• 51:19
  Speaker 2: in a lot of the pre clinical data as well,
• 51:21
  Speaker 2: so first of all pre clinical safety data so that
• 51:23
  Speaker 2: we can then search across from pre clinical intoclinical what
• 51:27
  Speaker 2: actually happened. So if we've seen this particular tox event
• 51:30
  Speaker 2: pre clinically, what happened if we took that molecule forward,
• 51:33
  Speaker 2: did we actually see it in the clinic and vice versa.
• 51:37
  Speaker 2: And now we're adding in additional data and continuing to
• 51:41
  Speaker 2: sort of feed data forty two, and we can incorporate
• 51:44
  Speaker 2: data sets that we bring in as well through additional
• 51:47
  Speaker 2: partnerships for example. So I think not many other companies
• 51:51
  Speaker 2: are fortunate enough to have this type of searchable AI
• 51:55
  Speaker 2: searchable database. So we do think this does give us
• 51:58
  Speaker 2: an advantage, and we're using it extends and even how
• 52:01
  Speaker 2: it has real world evidence is in there as well,
• 52:03
  Speaker 2: so you know, we can use it to design clinical studies,
• 52:07
  Speaker 2: make sure the studies are powered correctly. Look whether we
• 52:10
  Speaker 2: get an adverse event, whether we've seen it before, all
• 52:13
  Speaker 2: of this sort of thing.
• 52:14
  Speaker 1: But let me just theoretically say, historically you've not been
• 52:17
  Speaker 1: in anti infectives. I don't even know if that's actually
• 52:19
  Speaker 1: true if I look back there.
• 52:21
  Speaker 2: Yeah, y, in fact, we are in the global health area.
• 52:23
  Speaker 2: But yes, let's just say harder if you're not in
• 52:26
  Speaker 2: an area. Yes, totally agreed.
• 52:29
  Speaker 1: So some companies, I don't know a glaxosmith Klein will
• 52:32
  Speaker 1: be particularly well placed in respiratory. I mean, I don't
• 52:36
  Speaker 1: ask you to comment on that specifically, but so that's
• 52:39
  Speaker 1: not exactly the wrong thing. And then do you end
• 52:41
  Speaker 1: up using all the are you currently using, particularly mostly
• 52:45
  Speaker 1: the frontier type models that are out there? Do you
• 52:49
  Speaker 1: do you have any intention or thought about using any
• 52:51
  Speaker 1: of the other models of an Europe's got a model
• 52:53
  Speaker 1: called Mistral. The Chinese models have become very very competitive
• 52:58
  Speaker 1: and much lower cost. How do you see that.
• 53:02
  Speaker 2: We lead with the models that we trust best, and
• 53:06
  Speaker 2: the well known US sort of commercially available models are
• 53:09
  Speaker 2: the ones that we're using. But we do use hugging
• 53:12
  Speaker 2: face to access open open AI type of models that
• 53:16
  Speaker 2: are out there. We evaluate those, make decisions on you know,
• 53:20
  Speaker 2: whether they're useful or not.
• 53:22
  Speaker 1: So yeah, it's a mixture. Cool now conscious of the time,
• 53:26
  Speaker 1: we've lost quite a bit along the way. So it's
• 53:29
  Speaker 1: San Diego one of my favorite cities. Beautiful visit despite
• 53:34
  Speaker 1: this jet lag. So I'm always excited when there's a
• 53:37
  Speaker 1: medical conference there. Tell us please about the research hub
• 53:40
  Speaker 1: in San Diego and the what the theory, philosophy, idea
• 53:44
  Speaker 1: of this research jobbism it sounds really interesting.
• 53:47
  Speaker 2: Well, you know, we've had what was called GNF. It
• 53:50
  Speaker 2: was the artist you know, Genetics Foundation, Gene Research Area
• 53:54
  Speaker 2: was there has been there for more than twenty years
• 53:57
  Speaker 2: in the La Joya area and you know, near this
• 54:00
  Speaker 2: scrips and some of the leading sort of institutions, and
• 54:03
  Speaker 2: you know, we've done some great work there. But we've
• 54:06
  Speaker 2: also you know, increasingly done business development in the San
• 54:10
  Speaker 2: Diego area. So obviously Avidity being one, but before that
• 54:14
  Speaker 2: Cake Therapeutic that I mentioned DTX, and we also have
• 54:17
  Speaker 2: a site in San Francisco. So you know, when I joined,
• 54:21
  Speaker 2: I looked and we had a lot of different sites
• 54:23
  Speaker 2: scattered around California. The sort of more than twenty year
• 54:27
  Speaker 2: old building GNF needed really updating. So you know, the
• 54:30
  Speaker 2: first plan was to update that and extend it, but
• 54:33
  Speaker 2: when you really look at what a new facility needs
• 54:36
  Speaker 2: to look like, especially in times of AI, it made
• 54:39
  Speaker 2: more sense to start all over again and that there's
• 54:42
  Speaker 2: a great new sort of super campus for biomedical research
• 54:46
  Speaker 2: in that area of San Diego. So we made the
• 54:48
  Speaker 2: decision to move to a new building breed down the
• 54:51
  Speaker 2: people from Emeryville just outside San Francisco, and it also
• 54:57
  Speaker 2: incorporate the biotech companies that we've required over time into
• 55:01
  Speaker 2: one new facility. So very excited about that ability to
• 55:05
  Speaker 2: do that.
• 55:05
  Speaker 1: Will you have a lab there that's entirely driven by AI,
• 55:09
  Speaker 1: robots inside doing the aliquotte and the test.
• 55:12
  Speaker 2: Are certainly going to have. Is this certainly top of
• 55:15
  Speaker 2: our mind as to obviously having this opportunity to design
• 55:18
  Speaker 2: labs from the get go. Now how you incorporate automation
• 55:22
  Speaker 2: into those labs? And you know, I'm not sure I'm
• 55:25
  Speaker 2: that keen on the self driving, fully automated lab. You know,
• 55:30
  Speaker 2: I still strongly believe that you do need humans to
• 55:33
  Speaker 2: be there involved sort of hands on to a certain extent,
• 55:36
  Speaker 2: even though it's hands on, you know, running an automated system.
• 55:40
  Speaker 2: Certain parts of research are more amenable to automation. Of course,
• 55:44
  Speaker 2: the sort of screening type aspects, but a lot of
• 55:47
  Speaker 2: that we do virtually now. Anyway, the real creativity and
• 55:51
  Speaker 2: the real benefit of having people in the lab doing experiments,
• 55:54
  Speaker 2: to me, you know, maybe old fashioned, but I still
• 55:56
  Speaker 2: think that's really important. It's where a lot of the
• 55:58
  Speaker 2: ideas come from. So you know, we're thinking about what's
• 56:01
  Speaker 2: fit for purpose and what processes makes sense to automate.
• 56:05
  Speaker 2: Which one's less so, but that will certainly be part
• 56:08
  Speaker 2: of the designed features. And we have we have got
• 56:11
  Speaker 2: very good automation people in California as well, and I
• 56:15
  Speaker 2: think California is leading in terms of things like AI
• 56:19
  Speaker 2: applied to lab automation and other areas. So another reason
• 56:24
  Speaker 2: for us to want to really have a facility in California.
• 56:27
  Speaker 1: Well, so I've dropped a couple of hints there for you.
• 56:29
  Speaker 1: I'm passionate about science and I love San Diego. So
• 56:33
  Speaker 1: if you ever have a visit to your lab organized
• 56:36
  Speaker 1: to the building, remember me sadly when we do.
• 56:40
  Speaker 2: When we do the opening of the building, Sam make
• 56:43
  Speaker 2: a note on this then when we have the opening ceremony,
• 56:46
  Speaker 2: be lovely to have it covered by Bloomberg.
• 56:48
  Speaker 1: So let's let's finish off with the artist's scientific philosophy.
• 56:53
  Speaker 1: If you wanted to put that in one phrase.
• 56:56
  Speaker 2: What is that focus on patients where that are met
• 56:59
  Speaker 2: need is and really try and understand the fundamental basics
• 57:04
  Speaker 2: of the disease and address those fundamentals with the right modality.
• 57:09
  Speaker 1: Brilliant. Well that's Fiona Marshall. Thank you very much, President
• 57:13
  Speaker 1: of Biomedical Researcher and of Artists. Thanks so much for
• 57:16
  Speaker 1: joining me today on our latest episode. Please don't forget
• 57:19
  Speaker 1: to give us a review and make sure to click
• 57:21
  Speaker 1: the follow button on your favorite podcast app or site
• 57:24
  Speaker 1: so you never missed a discussion with the leaders in
• 57:27
  Speaker 1: healthcare innovation and this has certainly been a fantastic conversation.
• 57:31
  Speaker 1: I again want to thank Fiona for spending the time
• 57:33
  Speaker 1: and Kevin Ettal the team who helps us put this together.
• 57:37
  Speaker 1: I'm Sam Fazelli and you've been listening to the Vanguards
• 57:40
  Speaker 1: of Healthcare podcast by Bloomberg Intelligence, the in house research
• 57:44
  Speaker 1: arm of Bloomberg. Until next time, take care.
• 58:16
  Speaker 3: Must uses as pass us and Mussons and cosmos and
• 58:30
  Speaker 3: bases