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Proteomics in Proximity discusses the intersection of proteomics with genomics for drug target discovery, the application of proteomics to reveal disease biomarkers, and current trends in using proteomics to unlock biological mechanisms. Co-hosted by Olink's Dale Yuzuki, Cindy Lawley and Sarantis Chlamydas.
Welcome to the
Proteomics in Proximity podcast,
where your co-host
Cindy Lawley and Sarantis Chlamydas
from Olink Proteomics
talk about the intersection of proteomics
with genomics for drug target discovery,
the application of proteomics
to reveal disease biomarkers,
and current trends in using proteomics
to unlock biological mechanisms.
Here we have your host,
Cindy and Sarantis.
– Hello there.
Welcome back to Proteomics in Proximity.
I'm your host, Cindy Lawley,
with my co-host Sarantis Chlamydas.
We have a very special episode for you
today.
We have a few guests
coming to us from our new home,
our new family, our new neighborhood,
Thermo Fisher Scientific.
Some of you might recall that last summer
we completed
the joining of Olink and Thermo
Fisher Scientific.
I'm excited to report that we've got
Gianluca and, Karen to join us
to talk about why and what that means
for all of us and all of you.
Sarantis, do you want to tell us
a little bit more about our guests?
– Thank you.
I’m really pleased to welcome our guests
today.
Truly honored to have Gianluca.
And he's the Executive Vice
President of Thermo Fisher Scientific.
Karen Nelson is Chief Scientific Officer.
And, we are looking forward to discuss
about integration
of all in proteomics
to the Thermo Fisher Scientific family
and not only as a strategic alliance and,
movement, but also the next step opening
and promoting actually a world
that is healthier, that is safer
and actually,
makes our life easier for everybody.
I would like to pass the words to Gianluca
if you don't mind.
I would like to know you
a little bit more better.
And to I get to know your journey
and your career path that you had
in Thermo Fisher and I am looking forward
to hearing from both of you.
Thank you very much.
– Sarantis, thank you very much.
And, Cindy,
thanks for having both myself, and Karen,
we were incredibly excited
to have the opportunity to join you.
As you might remember, many months back,
when we first talk, I knew about you.
Not because of Olink but because
of this podcast that really helped me
as a non-scientist over the years
to get acquainted
with the magic world of proteomics.
And having been 20 years in the industry,
I always thought
that proteomics that the certain point
would be very transformative.
And, indeed it is the case.
And that's why ultimately we decided,
about a year ago to acquire Olink
and now Olink being part of the Thermo
Fisher Scientific family.
It is, truly being transformative
to the world of science.
So I'm incredibly excited to be here.
A little bit about me...
– Can I just pop in and say that Gianluca
and I met at the castle in Uppsala
at a dinner, and,
And he knew about the podcast,
which was just so flattering to us.
We were very excited to hear that. Sorry.
Go ahead, Gianluca.
– I knew about the pod.
I was a fan. And, I'm continuing to be.
– You even had it on your phone.
You even showed me. I said, oh, please.
He had it up.
It was right at the end of the episode.
I was gobsmacked.
– I had the proof.
The proof is in the pudding.
You see, it wasn’t only marketing.
– Frist step towards
trust between us, Gianluca.
– Absolutely.
Well, so.
And this was a little bit about me.
I've been at Thermo Fisher Scientific
for the best part of the last 20 years.
I was in Europe at first.
Then I spent a few years in South America.
In Brazil,
I moved, then in 2012, to China.
Actually one of the biggest achievement
while I was in South America
when I was running, what at that
time was Life Technologies in South
America is meeting my wife,
and we together moved in China in 2012.
When we moved in China,
we announced that Thermo Fisher
was acquiring Life Technologies.
We ended up spending five years
running, Thermo Fisher
in China had two kids
that were born in Shanghai.
So I think technically made in China
and then imported in the US
when tariffs were not a thing
back in 2018,
we moved to California
and then here in Boston,
I now run our product
and technology businesses at the company
and as said, I'm
incredibly excited about proteomics.
We have ample time to talk about that,
over the course of this podcast.
And so, without further ado,
maybe I'll hand it over to Karen
to tell us a little bit about herself.
– Absolutely. Looking forward.
Looking forward.
Actually, I would like to know,
I think as well
that Karen has a tremendous career
and academic career.
And it was she was leading
Craig Venter Institute, almost a decade.
How was the transition from
I mean, it's a common question right,
the transition from academy to a big
a technology industry institution?
How did you find this?
How was your vision? When do you change?
– Well, Sarantis and Cindy,
thanks for having us today.
It's such a pleasure to be
with you guys,
and Cindy, I'm just getting
caught up on your podcast,
but they really are great.
So thanks for doing that.
– Aw thanks.
– You know, so I joined four years ago
and, Sarantis, to your question,
probably one of the best career moves of
my probably is well,
I'm by now, I'm sure it has been the best
career decision of my life.
I spent close to 23 years
in a non-for-profit research world
with the Venter team, and they're,
you know, they were part of the team
that did the human genome,
my biggest claim to fame was doing
the first human microbiome.
So a lot of time spent in genomics
technologies and then my coming over
to Thermo Fisher and seeing the breadth
and possibilities of what we have
all the way from instruments
through consumables in the life sciences
through clinical trials
that has been such an amazing,
experience for me, both in terms of people
and learning and the willingness
of everybody wanting to partner.
And then,
you know, when I heard that you guys
were joining the family, it was like,
you know, Gainluca, and I were like,
yes, this is perfect
because it was such a nice complement
to what we had already in-house
and had the potential to really accelerate
what we're doing to make the world
healthier and safer.
So thanks for having us here
today.
– Yeah, thanks, Karen.
Because we do. We feel very welcome.
– Wonderful.
– I just want to highlight
and put on records that you said
that was the best
move of your life and career.
– She moved from Craig Venter to me.
And so I don't know
if I have the same scientific pedigree,
I have to say, but I think that there's
a compliment coming.
– Well, it's
been such a pleasure to be here.
– He’s throwing down
the gantlet, Karen, to Craig.
– I know, I know.
– Now I'm thinking
maybe we'll hear from Craig.
– But, you know.
But just the magnitude
and the impact of Thermo Fisher.
You know, I am one of those,
who grew up on Thermo Fisher
reagents and instruments and supplies.
You know, it was Gibco
in every aspect of your lab,
for example, and different pieces
of equipment and thermal cyclers.
So it's actually,
you know, my opportunity to be back,
at home, just like you guys are here now.
– And I'll say it's not an easy thing
to make a transition that that layers
on what Craig Venter accomplished
and what you accomplished with him.
I mean, just
the whole history is just phenomenal.
– Well Cindy, you're part of that too.
You made the jump.
So you know what it's like.
– Yeah.
So that's why I'm
complimenting us both
for having such a good...
– Good mentors and great guidance.
– That's right.
It's all about having a cool technology,
having wonderful people around
you and those wonderful people
then create a good culture.
And I think with that in place,
changing the world, feeling
like we've got a purpose, I mean, that's
just icing on the cake, right?
So, Gianluca, we've got mass spectrometry,
an amazing capability
here at Thermo Fisher.
And I will say, I as Karen says,
I come from the genetics world.
So, so proteins
have always been really scary to me.
I felt like Olink gives me a little bit
of a,
an easing into proteomics.
But why Olink in the context
of the enormous capabilities
at Thermo Fisher
using mass spectrometry and the advances
that we're seeing in that space?
– Yes.
Obviously starts from the
understanding
of the importance of proteins
and the importance of proteins,
to obviously our,
incredibly complex
and fascinating biological systems.
And as a leader in proteomics,
through our mass spectrometry franchise,
we had the opportunity
to have great insights
on what was happening in the market
and also the understanding that,
not only having solutions
that are helping you to go incredibly deep
and, in a way, in an untargeted fashion
to study
proteins was not enough to be able
to provide to our customers
the full breadth of what they truly need,
which to us is also a high affinity
method.
A throughput like, Olink provides
that truly is being transformational.
When you look at the result of the UK
Biobank
in terms of both
the amount of information that,
the UK
Biobank cohort has been able to create
and the one that is ahead of us,
but more importantly,
the number of publications
and the understanding of correlation
between the presence of protein,
their level disease,
this has been truly transformational.
And the pivotal moment thinking science.
And we'll discover more and more.
And so, we felt that was very natural
to actually combine,
the all the technology
with the incredible leadership
that we already had in mass spectrometry.
And indeed, we are now seeing how engaging
with customers,
the two technology
can be incredibly complementary
to have a more comprehensive
understanding of the human proteome.
And I can't wait to see
what's going to happen
in the next few years,
because I do believe
there's going to be transformational
in the way that ultimately
we actually prevent
then detect and treat diseases
that today are not, treated
as well as they should.
– To monitor, right? Who's really at risk?
And I, I joke about the Goldilocks,
too hot to cold and just right.
And I don't want to dismiss
your microbiome
metabolites,
but they are so hot, they move so quickly.
Right?
DNA moves at the pace of generations.
That's really slow.
It's hard to nudge, but proteins,
it's just, it's the baby bear bowl.
It's just fabulous.
– So, Cindy,
I wanted to pick up on something
you said about proteomics being scary.
I don't know if it was scary
as much as we didn't have the right tools.
Right.
And now, finally, we do have to. And,
if you think about Astral and Astral Zoom
and how deep you can go on a sample now,
I mean, it's unbelievable
what's changed over
the past 15, 20 years
in terms of technology development.
So we're now in a better comfort, space.
And to Gianluca’s point about integrating
the Olink data with, proteomics data.
I mean, it's such a tremendous advance
for science.
And from where I sit, yeah, for sure.
– And I guess I think of it more as scary
from a geneticist point of view,
where we had this,
you know, certainly in 2007
when we advanced to the
to the massively parallel sequencing
and being able to analyze those data,
right, that we just shifted the burden
from the collection of the data
to the reconstituting the data
and comparing it to reference genomes
and handling
those data or even transcriptomic data
just feels a little more,
you know, it's A C T and G
right there isn't the conformational
or the, conformational complexity
or the protein protein
interaction complexity, but I think,
geneticists are really getting comfortable
with full length proteins.
And then mass Spec is going to be
the only way, today to dig
into proteome forms, to dig into
what are the post-translational
modified aspects of those proteins
that are actually,
providing the bulk of those signals?
And, of course, we're seeing from the UK
Biobank data
amazing signatures of 5 to 20 proteins
that are predicting disease
better than anything
a doctor has available today.
Like this is, you know, just echoing
on what you're saying.
Gian, it's a very exciting time now.
– I mean, I want to follow up
in on Gianluca’s comment about UK Biobank.
We see recently also that pharma
investing from these data sets,
right, of generating real world
evidence, real world data.
And we see that they invest in cultural
on platforms like Olink.
How will you see both of you
the role that can play in this platform
kind of way of working pharma
together with governmental institutions,
with academic institutions
to enable precision medicine?
How do you see Thermo Fisher plays a role
that are and having all of this
weight and breadth of
multi-omics approache?
– It’s a great question.
And, you know, maybe because, the probably
only non-scientist
of the crew here in the pod,
– I disagree.
– You disagree?
– Honorary member.
– No, you’re scientist.
– Honorary member.
– You are absolutely a scientist.
– I learned in street fighting,
spending a lot of time with customers.
But, you know, I've been thinking a lot
and being, at heart,
a lover of technology and innovation.
I've been, obviously
very impressed
what is happening in the world of,
automotive technologies
and, transportation?
We now have self-driving cars.
I wake up in the morning and my Tesla
doesn't even need me
to tell where I'm going,
because the Tesla knows that
more probably I’m going to the office.
So I sit on my Tesla and there's already,
a predefined destination in the morning.
And then I put self driving
and the car drives itself to the office.
Intervention is very limited.
And my hope is that
at a certain point,
health becomes the same.
We are on autopilot.
And to be able to do that
you actually need,
devices and detectors and signals.
And I think proteins are providing
just that.
We actually don't understand everything
to the same extent
that, digital technologies
are able to understand,
visual signs
and help a car driving itself yet.
But I think that's going to be obviously,
a big transformation.
And that is why I think to your question,
pharma
companies are so interested
now in getting a head start in proteomics.
Because, we've seen again,
through some of the result of the UK
Biobank protein
signatures and this, poly protein,
you can call it race course.
My opinion, but I'll leave it
to the scientists on the part to confirm
is more than rescore,
I think very different to look at poly
protein signatures and polygenic
risk scores as an example.
That's why I think pharma so interested
in this poly protein signature
as an indicator
of either an early onset of disease
or perhaps an indication of,
response to therapy.
So again, over time, I think the,
utility of protein
signature
is going to be quite broad in nature,
whether he's prevention, early detection,
whether he's response to treatment.
And I
think more things that can be done
through, those signatures.
So it's quite exciting.
Does the interest in the space,
the key to me is still
generating millions and millions
of data points so that ultimately
we can apply artificial intelligence
and truly get to it to cells.
Do I can I call self-driving human
or is a bit to, provocative?
I don't know.
– I think self,
so why do we want to call that?
I mean, it's a really good question.
We should come up with a phrase, Gian,
I don't know that self-driving human,
but it’s self, I mean, we're certainly
putting power in the hands
of the individual, right? Yes.
We the community, the scientific community
by building such tools.
And I think this point about self-driving,
I love the comparison.
You know, I love a good analogy, but,
you know, I was talking to one of the
I live in the Bay area, this, you know,
you can't swing a dead cat without hitting
somebody who's been involved
in some aspect of collecting self-driving.
I would never swing a cat, by the way.
Is involved in some aspect
of this technological advance.
And even where I used to live
in the agricultural belt of California,
they used an old air force base
to do some of the practicing out of that.
But but what turned out to be
the most important thing is that the right
data were used
the minute you have incorrect data.
And here I'm calling back to specificity.
Right.
And the importance of knowing exactly
what protein you're measuring.
If the minute you have wrong data,
the algorithm
can't discern the difference.
And so I think that was the turning point
based upon the conversations
I've had with a few of these folks of,
of being able to, to really make that work
because it's phenomenal
to see those cars drive themselves.
They can come pick you up at the curb
with not a driver in the seat.
It's impressive.
– Actually.
You're not far away from the concept of
digital twins, right in pharma convention
that they have the digital twins
where actually can project things in AI.
Right.
And predict things in AI, I think that's
we are really close on this,
really close on this on this era.
– And the virtual cell. Right.
We could navigate through it.
– So Cindy, just pick up on what
one of the points Gianluca was making
is that,
you know, some of the preliminary data
coming out of UK
Biobank in terms of stratifying
patients is really amazing.
Right.
And so to Gianluca's, point be,
you know, the early diagnosis,
like the protein signature that's coming
really early on, we're going to be
at a point where we can use that to change
the trajectory of health or treatment.
And I think we're just at the beginning
here.
And, you know, you know, I just think
it's going to change how we think
about human health could go all the way
to animal health, environmental health.
But it's just such an amazing opportunity
for the field.
When you start to look at
the initial implications of the data
that's coming out.
And I, I think, Gianluca, we have multiple
collaborations now, right?
It's not just the UK Biobank.
I think it's we're processing...
– Topmed, FinnGen, yeah. – Yeah.
– We're involved in our future health
where, yeah, there's
there's so many places
where there's opportunities.
And I think it just for context on UK
Biobank, what a sweet data
set that is just to remind listeners
that, you know,
those collections were made
for individuals between 40 and 67 years
of age, and it's been almost 20 years
for them to develop diseases.
And so to Karen's
point to Gian, to your point,
this is a beautiful set to be able
to look at those baseline blood samples
and see the signatures for the same
diseases in different individuals.
And that has, you know, certainly
coming out of, Ruth Travis's group,
they've been able to do that in cancer
that hit the UK news last year around
how they could see a median of 12 years
before diagnosis of cancer.
12 years. That's phenomenal. Right?
A minimum of seven years.
That was what hit the news.
And then, and then of course,
the Carrasco Zanini paper
coming out of Claudia Langenberg's lab,
where 67 out of the 200 diseases
in just the pilot of the
UK Biobank Pharma Proteomics Project.
They were able to see these 5 to 20
protein signatures that outperform
anything a doctor has available today.
So just for some context, that
some of that exciting stuff coming out of
that study, that pilot and those pilot
data are available
for application to use them,
and they're free for many, many,
many academic institutions
So it's, it's an exciting time.
– One of the thing I want to add,
one thing that is,
maybe the elephant in the room
or the human in the room,
call it, the way we want.
– The self-driving human.
– The self-driving human.
But, in serious terms.
One of the things that I’ve been,
fascinated with
is ultimately human psychology.
And I think I'm not misquoting this, but,
in a study that was run a few years back,
they highlighted
how 50% of the individuals
that should take medicines
that are critical due
to the chronic condition
and in many cases, a life
saving, medicines,
they're in noncompliance.
50% of them die in noncompliance,
which tells you,
the fact that, for some reason,
humans are not very,
self caring, if you wish.
And so one thing that
I think is going to be very important
to your point on the amount of available
information, is
how do we disseminate this information?
How do we make sure there's
enough, learning,
opportunities both for doctors
but also for individuals
to become more self-aware
on how they actually can stop the car
before the car crashes.
With the analogy of self-driving cars, a
self-driving car normally doesn't crash.
And I think from a health standpoint,
we should make sure
that we prevent disease more effectively
going forward.
With all of this insight and information
that we have available.
Then one of the concerns I have,
I don't know your perspective, is
how do we influence culture
and who is going to be, actually
helping consumers to do a better job
in taking good care of themselves?
That, to me, is still an unresolved issue.
If we don't resolve it as a society, then
it would be very difficult
to take full advantage of, these tools.
But maybe these alternative solutions,
that will, be implemented
over time as a result of,
now much better tools to help,
consumers and patients.
– Karen, do you have ideas about that
from the genetics space?
Right.
This feels like a parallel,
of education needed, right.
That what what was what was what helped
us there from your perspective?
– Well there’s
I mean, to Gianluca's point it
probably it has to happen in parallel,
right, to get absorption
into the general population.
I think back then we had set aside
funds for like ethical,
legal and social implications.
Remember all of that good stuff,
Cindy?
– Yeah. Oh Yeah.
– And, it was a percentage of all funding
going into genomic research was,
used for like education and legal work
and getting,
because there were a lot of questions.
A lot of concerns.
And not everybody is trained in science.
And so they don't understand.
And, you know,
we tend to be positive and can only,
just try to discuss
the positive implications.
But there are concerns
about some of these, research areas
that people don't quite understand.
And I think, the education and the value
and highlighting, you know, like the car
analogy.
Gianluca, you're saying
that when the light comes on, on the car,
take it in and don't wait till like,
the engine shuts down right.
And we're getting to the point
where we can
have that light come on really early
when there's a problem in the car.
Not on an Italian car though, right?
I'm talking about
in other parts of the world. So.
But I think, as a society, Cindy,
we probably need to start
having those conversations
about getting the information out,
getting the positive findings out.
You know, it's right now, it's
so positive, like, how do we get that out
in words
that the general community can understand?
And I think it's up to us
to try and accelerate that.
– And isn't it easier
because proteins aren't
tied to our personal genetic information,
right.
– Right, it should be.
– That might be because, yeah, it's
not an identifier of us as individuals.
Our protein signature.
– Right. But it's hard to understand, right.
Because you talk about proteins
and proteoforms and splicing
and all this good stuff.
And so it's about how to translate
that in words that, the average person
can understand the benefit of the research
that's ongoing right now.
– I think to your point,
I mean, it's also really important
not only to generate the data, right,
but having the tools to interpret
the data and make sense out of this data.
And I think that's also really important.
We'll come to the future and it'll come
really important to the future as well.
Interpret the data, make them easy
for the people to understand
and make the right use on that. Yeah,
that's an excellent point, Karen.
I actually would like to follow up
on this, Karen, if you have this NGS
background and experience, what excites
you more in this NGS proteomics nowadays?
And do you see this like a game changer
for clinical trials for example?
Do you see that will make clinical trials
smarter having NGS
proteomics integrated
to the omics pipelines, for example.
– Quick answer is yes.
You know, you think about NGS.
It's like a static point
in time that you're understanding
what's going on in the cell.
Now, we can actually
understand over a time period
how a cell is behaving, how it's reacting,
what it what it's doing.
You can do it with a human.
You can do it with a bacterial cell.
You can do it with a plant.
I mean, you can understand
what the DNA has resulted
in terms of activity at the cell level.
And I think it's so exciting.
I mean, genomics was exciting.
We built massive informatics resources,
software resources, massive tools, AI.
We were using all these tools back then,
but now we have a chance
to actually understand
what are the messages coming out
and what are they turning into.
And how can not that we want to stop it,
but how can we use that information
to influence the outcomes
and our health in the long term?
And I think it's gonna,
over time, become a critical part of,
you know,
a companion, part of clinical trials?
I would think so.
I don't do that on a daily basis,
but I would absolutely believe that
they're going to you can take a plasma
sample on a daily basis
and look at how certain
protein markers are fluctuating.
Imagine a time like that. Right.
– Well, Chris Whelan talked about this
in depression where they had
three endotypes based on proteins
after the clinical trial.
Right. So this is an in that trial.
But they responded differently
to the therapy.
Each of those three.
Yeah sorry.
Go ahead Karen.
– No I was just saying that
I think you guys had a partnership where
initial outputs from Olink data turned
actually into, diagnostic in the clinic.
Right.
And it took a couple of years,
but I believe that that's going
to become at scale
that we can have these early biomarkers
being detected as a result of
the technologies that we're,
fostering in-house.
I really believe that.
– Yeah, yeah, those diseases
and there's application
and disease specific signatures
that our customers are building.
I think that is one of the most exciting
things I was excited about in joining
the Thermo Fisher family is that we can
we can accelerate those.
Right.
– And Sarantis, my last happy,
happy point.
Imagine being able to live
through the genomics revolution
and landing where I can live
through the proteomics revolution.
– That’s amazing.
– I mean,
not a lot of people
get that opportunity, right, Cindy?
– That's right, that's right.
It's pretty special, it really is.
– What do you think also
this will open the door to let's say FDA
and to other and let's say institutions
that can be biomarkers
that are approved will make probably
all of these procedures much easier.
Having all of these nice data sets.
What is your opinion
there, Gianluca, on that?
– I think regulators, have their hands full,
to stay up to speed
with the technology for sure.
And it's actually,
refreshing to see that
I think we had recently one of the first,
AI driven biomarkers
approved, in the pathology space.
If I'm not mistaken.
And so it tells you that,
they're starting to move at pace.
And that's a very good news.
By the way, I Chatgpted
the data point
that I quoted on Nonadherence,
and, in fact,
there was a study from the W.H.O.
that says that, Nonadherence can account
for up to 50% of treatment failure.
And just to put this in context,
in the US,
around 125,000 deaths
and out to 25% hospitalization each year,
that are driven from nonadherence,
with medication.
So, it's indeed highlighting
how the need of,
you know, information and education
of the patient population
is, super critical.
But also,
I think technology plays a big role.
Why we're seeing...
– Sentry Mode, right, Gianluca?
I mean.
– Sentry Mode. Yes.
– Get a pop up.
– Get a pop up, but, you know, in that
case, you obviously have the car that,
allows you to do that in a patient ward.
Actually, you need technology to be able
to detect, as Karen was highlighting.
What about detecting this biomarker
on a continuous basis?
And I feel we're still
in the era of mainframe,
in the life science space.
You have this big instrument...
– Or it’s the Volkswagen Bub from 1966.
– Yes.
That's a good analogy.
– Beautiful car, but.
– We use Fiat.
You know,
I know that you now you're in the US.
So you say Fiat means fix it again, Tony.
But I
as an Italian,
I could take offense for that.
But actually...
– Yeah, you’ll get in trouble.
– It was my first car and
I truly enjoyed my Fiat.
But I think technology
will need to play a big role.
And I could envision over time
we already have much smaller
and compact sequencers
and the we know the detection technology
for Olink case sequencing.
But over time, we're going to have smaller
and smaller technologies
that can be ultimately integrated in,
our houses and will probably benefit from,
an availability of biomarkers
at the level.
And to certain extent,
you know, even with a WHOOP
today,
you can have these digital biomarkers
that are augmenting
your insights on your health.
And I think this will happen over time
for things like protein for sure,
which are challenging to measure
as you know, with the current technology,
but they're becoming easier and easier
to measure with modern technologies.
– And then you think to that, let's say
one of the barriers you have to go with like
finding new ways of sequencing
or more easy ways of sequencing,
or more handy ways of sequencing, right,
that there will be the future,
how you envision it.
– Totally, totally.
That's why, we're investing,
a billion three,
a billion four every year in R&D.
That's Karen’s
ward, she’s very tightly managing,
the priority around,
everything that we spend in innovation.
But, certainly that's the direction
we're driving towards.
And I'm sure Karen
has some perspective on that.
– No, I agree, I was laughing to myself
because I remember
in the early days of the microbiome,
they wanted to put a digital detector
in the toilet and so people could know
if they were sick.
But but think about it, right, Cindy?
I mean, imagine being able
to look at inflammation in a urine sample.
It could become our future that, you know,
you have some way to check at home
and this becomes a part of your lifestyle.
So I, I do agree with that 100%.
But in terms of our investment
in R&D and pushing the envelope
and integrating cost company,
these are these opportunities.
Again, you know, it's
the things that wake you up in the morning
excited to go to work.
We think about these opportunities.
And I will tell you honestly that Gianluca
and I think the proteomics space is
one of the especially bringing Olink in,
is one of the biggest,
most exciting areas for us.
So we don't advertise it all the time.
But we are very,
proud of the acquisition
and what it means for the company.
– I love to hear it.
– You are very welcome.
Welcome on board.
Very happy to have you on board.
– Thank you.
– It's been a year now, Sarantis,
and it's like, I've known you forever.
– Yeah.
– Yeah, we get under your skin. We get there.
– Yeah. We are, we are looking forward to.
– It's very exciting.
– It's very exciting.
It's very exciting to see that
the matching right with the omics pipeline
that you’re having.
And it's really clear, nice fit on that
because now it's a complete
now it's a complete toolbox right
end to end for the customer
from data generation
also to data interpretation.
That's the beauty.
That's the beauty.
– Yes. Correct.
– Can I add one thing?
I want to add one thing
which is super important
because obviously,
the Olink technology
as well as largely Mass Spec
for untargeted protein, detection
and quantification,
has been used in
the translational and research space,
but one of the big unlock
will be when those technologies
are getting to the clinics. And
I think we have an interesting parallel
with what we did with Ion Torrent.
We acquired the company back in 2011,
I believe,
and now we are basically the enabler of,
vast majority of clinical testing,
that are next generation sequencing based,
thanks to the fact that the team
has worked to streamline that technology.
Now we have a fully integrated
and automated NGS,
that is used for therapy selection,
with, you know, great products.
We just announced that we got FDA approval
for, our Genexus system. And,
you know,
a set of, panel and markers used for therapy selection.
So it's incredibly exciting.
It's been a long journey.
But it's a journey that, we learned
how to, go through and execute.
And I do envision
the same journey on a shorter timeline
because we learned a lot
over the last decade, 15 years.
And I'm super excited thinking
at when we're going
to see, proteomics,
into the clinics at scale.
It will require obviously
content, technology, etc.
but, it's, exciting to think about
when is going to happen.
– And I think the what's critical
and we do this today with our focus panels
is being able to turn over
those custom subsets
of proteins that we already understand
exactly how they cross react together.
We already understand how they play.
And those, you know, authentication
steps of, you know, two antibodies and
and one hybridization,
those that three factor authentication
is really enabling this to happen quickly.
And so I would encourage
folks to keep an eye on this space
because we're already seeing, you know,
there's over 700 references to the UK
Biobank.
You know, foundation paper
that came from the pharma partners.
That was in October of 2023.
So lots of references by using those data,
some of them just mining the data
for new insights.
It's a rich source.
– And if you don't trust a one factor
authentication
for your digital needs,
why should you trust it for your health?
– That’s true.
– Exactly.
– So use Olink.
That's the only two factor authentication
at scale out there.
– And antibodies are what we use
in therapies.
Right.
So I'm also excited
although much of it's behind closed doors.
But when pharma are able to publish
on mechanistic insights
from the, the therapeutic targets
that they're identifying, right.
This is a big push for why
14 pharma partners are paying
for 600,000 samples
to be run, the entire cohort in the UK
Biobank.
And I think that the mapping
of those causal pathways across different
diseases is going to be a reference
that we will come back to for many years.
It feels very good, Karen.
It f feels like the GWAS revolution
over again.
Right.
It's like you say, it's just such a privilege
to have a front row seat and a tiny,
impact
on where
this goes and where it will go next.
– Well to be part of the team,
Cindy, we're all part of the team, right?
– It's awesome. It's awesome.
So I'm having the time of my life.
I am having the time of my life.
How about you, Sarantis?
– Oh it's so great I mean, I'm
coming from the omics perspective, right.
And being in a big family,
with the omics family coming together,
which for me is the most exciting thing
ever.
You know, looking forward to break into
clinics, looking for biomarkers and push and beat
and convince FDA to have biomarkers
for clinical diagnostics.
That's I think is the next step
I have to go through.
– And, Cindy, one more plug.
One more little comment to Miller
who is on our team sent me a list of about
ten microbiome papers where they're using
Olink to look at inflammation.
And doing that correlation.
– Thanks for the reminder.
– But it's just amazing how it's spanning
multiple different,
areas of science, right.
That you probably wouldn't have thought
about the connection originally.
– That's right.
And we can put those in the show notes.
So if folks are interested in that.
I had just had a customer,
ask me specifically about that as well.
Another person
who came from that microbiome.
It’s still happening, this microbiome
– Still trying.
– revolution
where we're learning so much. Yeah.
It's like they.
I always think of them paying
the biome is paying currency
like it's paying rent to live in our body.
Right?
By giving us these metabolites
like serotonin and things like this.
Again, Gianluca and I,
I think both really love a good analogy.
So, so final thoughts,
we're just going to kind of,
wind down here.
It's a pretty great place to end on.
Gianluca, do you have some final thoughts
you'd like to leave our listeners with?
– Absolutely.
The future is bright and is bright,
thanks to the
for us, 120 plus thousand colleagues
at the company showing up every day
trying to create
those incredible innovation that,
equally talented and incredibly important
customers and partners
are using to actually transform
the way that,
we identify early
or fully, then ultimately identify
treatment and treat diseases that,
today are either
not well treated or untreatable.
And that's why
it is incredibly exciting.
To do that well,
you actually need the right technology.
Back to the analogy
of the self-driving car.
You need the right sensors.
You need the right orchestration,
information,
and you want to rely on something
for your life.
When you drive on a self-driving car or
when you actually drive through your life
and you make medical decision,
you actually want to rely,
on the best of the technologies
and our two factor
authentication at Olink,
is something very special.
And I think it has been,
proven, testified by the adoption
that we've seen from the UK Biobank study
as an example and the many partners
in the pharma space
that now are working with us to create
the next generation
of medicine and diagnostic.
So it is incredibly exciting.
It has been a great journey thus far,
and I can't wait for the next decade
to play out
so that, together as an industry,
we actually can truly transform
the way that, medicine works.
– Beautiful.
Karen?
– Cindy,
I can't add anything more to that.
I'm good.
That was perfect.
That was really good.
So thank you again for having us.
It's been really a lot of fun.
– I’m so looking forward to it.
So in the show notes,
I'll add some of the genetic corroboration
of the Olink specificity
and also some mass spec
corroboration of the Olink specificity
as well as Elisa.
Right.
There's lots of ways to corroborate.
You just have to be able to see
the protein in whatever matrix you're
looking at.
Any final words from you,
Sarantis – Oh, I mean, it's exciting.
It's exciting times.
And I mean looking forward
to break the barrier.
Right.
To make our world healthier, safer.
Right. And, the best place to live.
Thank you very much for your time.
And it was great
honor to have you, both of you here.
– Thank you, both.
– Awesome.
Well, just as a reminder,
if you want to reach out to us,
we're at pip@olink.com
that stands for Proteomics in Proximity.
We love to hear from you.
We love to get feedback and questions
that you'd like to hear answered here.
Thank you very much for tuning in.
Well, that wraps up this episode
of Proteomics in Proximity.
Huge thanks to our guests and authors
of such impactful publications.
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