Welcome to the

Proteomics in Proximity podcast, where

your co hosts Dale Yuzuki, Cindy

Lawley and Sarantis Chlamydis from OLink

Proteomics talk about the intersection of

Proteomics with genomics for drug target

discovery to the application of

proteomics to reveal disease

biomarkers and current trends in using

proteomics to unlock

biological mechanisms. Here we have

your hosts, Dale, Cindy, and

Saranits hello everybody.

Uh, I'm happy to welcome you in another

episode from Proteomics in Proximity,

together with um, my cohost Dale and Cindy.

We are really happy  

  today to have with us

Ida Grunberg, the Chief Scientific Officer

of Olink. Really happy to discuss with

her about her career and uh,

 ongoing projects and

ongoing outcomes in uh,

Olink.   Welcome Ida.

Uh, thank you very much. Thanks for

having me. Great to meet you can join

us.      

Thank you very much Ida, for joining.

Actually, I will start the question by 

 I would like to know a little bit more

about your background and 

 what was your status and

how do you see your transition from

academic to the industry? Can

you share a little bit more of your

experience? It would be really nice to hear.

Of course, I don't know how much time we

have, but I try to keep it

short.   So I'm a

molecular biologist by training. 

 And then I joined

     professor of

Landergren's group to start my

PhD. And at the time I

joined, he had actually just founded

Olink. So they were just the floor

     above us. Uh,

  so I was very

early introduced to OLink,

but uh, it was a great

group to spend a PhD

in. Very uh,  inspiring and

creative. We were developing

all different molecular tools

targeting   DNA,

RNA and protein, depending on the

research question. So I think that thanks to

my time there, I got    

a great foundation, 

 um, and a very open

mind to the importance

of   all the

omics.       Ida,

I'm curious what years

roughly, I mean, not to date yourself,

but   was it the early 2000s,

late 1990s? It was the


I joined Ulf's (Ulf Landegren's)

Lab in January 2006,

and they had founded Olink

in late


on board, I think in


was there between 2006 and


And then I focused actually more,

sorry to say, not on proteins, but on the

transcriptomic side. So I was working

more with Professor Mats Nilsson's group,

developing uh, technology for

transcript detection, more for point

mutation and genotyping

applications for colorectal

cancer and lung cancer

applications. So it was

actually      I'm

sorry, was this using sequencing? No,

it was an in-situ-based application. Uh,   

so we were using padlock probe

that had been invented in

Ulf's and Mat's group. So there

was a microscope,

... readout.   So really

like padlock probes

  similar to molecular

inversion. Exactly. Halo Genomics,

yeah, they were all in the family. So

again, we were almost


fantastic group to be very

privileged to have done my PhD

there.   So it was during my

last year where actually the

technology I have been working on

developing that we licensed that together

with Olink. So that was my door

into the company.  

So uh, just after I finished my

PhD, I continued at R&D,

at Olink and first focused on

continue commercializing that

technology that was later

sold off to another

company and I continued that

R&D, working more on the

technologies that...

we are focusing on now, more on the

proximity extension assay. 

   That was also around

the time when we first

launched the first panel.

So that a lot of

things were happening

  and still keep in mind

that that was the early days. So I don't

know, maybe we're 25 people,  

more than half of the company were at

R&D.     But then of

course we had

commercialization      going.

 so then   I

was recruited to the small

commercial team at the

time, um,     

    first

I had been in academia, so

for me it was like, wow, uh,

transition, should I go into

sales? But at that time

we had zero customers, 

one product coming

out. So it was really, from the

beginning, a very scientific sell

working with our

collaborators,

close     

friends, in

Uppsala. So I think we were three

people at the commercial team at the

time.    So I didn't see

it as   a scary

transition actually. But I

always think... Help me with. The date,

help me with the dates. Now is this


    So still

very early days.  

So the first

now we call it Target 96 oncology was

launched in


years uh, covering the

Nordic and European and then  

 2015 we

had decided that the biggest market is in

the US. We need to have someone

being based there.   So I

was asked if I could go over

and start off our US

market. So that's when I did the move

to Boston.   

   That must have

been such an interesting transition

for you to      

start something in the US.

Where... no

recognition of the technology, no friends,

no colleagues, maybe a few colleagues.

Yeah. How was that?  

   How was that?

No,   you're

right,   it was extremely

exciting, but also extremely scary,

  but a...

very valuable experience.  

 But as you said,  

  I had zero colleagues

in the US. I moved to Boston by myself.

I had been there once before

for like a day,   so I

knew basically no one.

And since we didn't

have anything in place, really,

we had to start from

scratch. But took day by day

and first settling in at an

incubator in Cambridge and

started connecting with the amazing

few customers we had at the time

and went from there. 

   What was one of the

most influential customers at

that time?   Is there

someone you can point to or a couple of them

that really opened your eyes

to   how the technology could

change things? Yeah. No, but for sure, I

mean, we were very lucky to, for

example, working with The Broad from really

the beginning. So the

incubator, that I was working

from was basically in the same block as

The Broad. So definitely there I spent some

time and trying to get in and set up some

seminars and so on.  

...We had some there and

also at the MGH (Massachusetts General Hospital), we had some

early adopters there as well. So I tried to

stick very close to them. 

so that was really the beginning. And

also why we decided to

set up in Boston,

Cambridge. That is the Mecca of

life science, but also where we

have    the early

adopters. Yeah, not a

bad neighborhood to hang out

in. Right next door to The Broad,

just down the street from MGH, actually. I

remember like, walking down Broadway and I

felt my IQ was just raising. 

    That was a

good spot.      Would you

remember any of the first projects that you

have been involved?   

   Let's say the first favorite

one. You mean

from the US market? Yes,

from the US market. One of the first that

you had close to your heart, actually.

For sure. Since we

basically no one knew about us, uh, we

had to have some strategies on

how are we going to actually  

generate some evidence and

content. Because already back then, we

believed in    

it's. Not enough just us showing what was the

power, the power of the technology, but

generating real data. So we

hooked up with,  

some researchers at

Stanford then in San Diego. So with

Stanford,  ah, we had

more of a wellness study where we

were comparing different

diets that, 

the different   group of

peoples were on. So we could

track the effect of inflammation

if you're on a high

fat or low carb diet. So that

was one of these    

 case studies that we early

did. Another one was done in San Diego

with Professor Doug Galasko where

he had a study on the

effect of antioxidants on

  Alzheimer's disease.

So there we also did a study together with

him so we could generate   great, data

that we could go out and have

joint road shows with.  

I mean, from your work

in the in situ transcript-

omics now to

Alzheimer's and wellness. Right. What

a shift. A huge shift, right? What early

days to be looking at wellness, right? This

is such a hot topic. Right?

Isn't that amazing? Yeah, exactly. I don't

know if it was just luck, but those

early studies have still been

shown to be very modern and

been very   

  active in the spaces as well

now. So   luck

maybe Doug    and

Doug is. Still leading the way.   Or the

Alzheimer's...

arena, for sure. Yeah, exactly. So

remarkable. But we have also, I think

all of you have heard about us. That could

be a nice story as well. So again,

since   coming to the US. And

basically no one knew about

Olink and this little

small Swedish company. 

  but,

... for being such a

small country, there's a lot of

great researchers and

scientists in the States. So

we try to also work very closely with

them. We formed what we called the Swedish

Mafia   so we could

all     yeah.

...we didn't say it...     To be

clear, this is not the "Swedish House

Mafia." That's a music

thing.       

 No, but seriously, so it was

great. So we have that at

Stanford, then in

Rockefeller, and teamed up with them. And

then they were also happy to

support and really put Sweden on the map

there. And... we have for sure, a

good reputation,    

especially in protein history.

So we try to also leverage on that and

not just saying with this

unknown Swedish company, but we're

proud and we're here for a

reason, because we know this.  

And as far as in the early

days, people were sending samples.

Right. You were getting customers sending

samples to Uppsala. But

then shortly after right. Didn't

you start actually building a laboratory

here? No, exactly. So I moved in 2015. Then,

just a few months

after, we started to have these

studies coming in. And some of them were

critical to have them run in the States.

So then, of course, we wanted an

office in Boston, but

we realized we also need a lab.   So

that's when we started to look for

different places. So my role was very

broad, going around, looking at

different spaces. And

then we found this beautiful old

garage in Watertown, 

    literally a

garage.   Show you a

picture.      

   It was going to

be rebuilt   into

a small lab space.    

So that's where we started. And... the

rest is history. And we always thought this

garage story was great and used to say that,

well, Apple started in the garage

too.      

   Wow.  

This particular garage. Then you

installed a BioMark. Right? And

I understand an employee,

Dan Frederick of ours, who's an

application scientist, he told me a

little bit about that first

installation.    What can you tell me about

it? I don't know any

details.    It was two

or one.    Uh,

we did, but the space was so

tight, so   

it was funny. We grew

out of that mobile garage

in no time, and

especially when we were going to

have two BioMarKs. And I can't

remember I think we even had three there.

And   these are big

pieces. Very big. In the end, we

were having meetings in the

cars outside  

because we couldn't fit in there.

   The cars

 "...meet me in my

car!"      

  We're doing a podcast.

Right.      

That's an interesting.   

    Dan told

the story of how it grew

so quickly. And then, of course,

when the opportunity came for him

to work for Olink, it was a very

easy decision for him to make,

  just witnessing

firsthand that kind of growth.

   And, these customers

then you had to hire, I guess you then

hired people to  

  run the laboratory assays,

that kind of thing you were central to that. Yeah,

for sure. So one of the first employees was

Jen, who is still working with us.

She's great. So she's been there from the

beginning and many others as well. So 

 many times we get

nostalgic and remembers the

garage.       

Yeah. And I think also, together with

all that growth, the

need of people to use proteomics, right.

You see this change of people of thinking

from one publication to thousand

publications, right? How do you see

this? How do you see this, actually? How was

your feeling for the first publication when

it came out? Can you describe? It

     was that

huge. We used to have like a

bell, so we're walking in the corridors

like, wow,    

  it was big. It was

big. And especially, I

mean, looking back, the first paper

that was in Nature Communications,

our close collaborator, Professor Ulf

Gyllensten,  it was a

great paper. I mean,

looking back, it was

only    one panel of 92

proteins, but a big study.   

So fascinating outcome

that really paved the way

to where we are today.

So, yeah.   

    For those who may

not be familiar, right, this paper

did    over a thousand

Swedish individuals. So they had

genotyping data and then they looked at


to protein. Then they had health

outcome data and then they had all the

clinical data. So they can talk about

the influence of genetics upon 

 the biomarkers,

genetics upon the outcomes,

and then the other

lifestyle and clinical factors. I

mean, reading it now, I mean, it was

a 2014 paper and it was like,

wow. Exactly    

     the

fascinating chord of it. So it's

a population study from the very

far north of Sweden,

Karesuando, where it's like

freezing year round.  

 And they had been following these

thousand individuals for a long time

and as you said, had all the information

on their lifestyle and

diets, but they wanted to add

proteomics to it. And then,

I mean, still less than hundred proteins,

but uh, they could gain so

much data and insight from,

uh, these results  

quickly. Their conclusion, or

the take home from the study was that they

could really see the effect of

non-disease factors. So this was

a healthy population, but

still see that. I think more than


varying.     All the variance

were actually coming from these

genetic and lifestyle factors.

So like age and blood pressure

and weight and smoking

habits, all of that had an enormous

effect... on proteins.

  And they mapped all of

that.   It was just

demonstrating that value of

capturing real time biology in

the context of the genetics.

It's a phenomenal paper. Yeah,

for sure. And

also    it was a very

broad paper that they could also follow

up. They called it like a publication

generator, the data that they get out

because then they could also follow up and

see. So what should we do

with all this information? Is there any way

that we can   associate these

results to more actionable,

diagnostical, clinical,  

biomarkers? In the

follow up paper, they proposed...  a

model to adjust for

these... variables

and   that

algorithm that they proposed back then

is very relevant

today. That they  

  find really select

the most robust biomarkers that

are not  

varying because of these non-disease

factors. So a great start

of the thousand papers.

It sort of reminds me a little bit

of I'm sorry to make the

parallel to the sequencing space but that's

sort of sequence once query

often, right? You have such a broad

look at proteins that you can deep dive

into those data for

multiple different purposes across that

population. Just at that time that was very

high-plex, we call that midplex now.

   But  

that's a   beautiful

...  point... about

the data set.   

And what was also really interesting

for me was this idea of clinical cut off.

Exactly. In that you have sort

of individuals, right, with

certain levels of certain

biomarkers and if you have a certain

one or a handful that

spike up or drop

off, that means something is

happening, right, health wise for that

individual. So here we're talking about

personalized medicine based

upon the individual's

protein profile at a given time

and their genetic background and of

course their lifestyle and the different

things that they do. I was

thinking "this is personalized medicine, this

is the future", right? It's in

reference to the

population that you're able to compare it

to. And today we're

seeing such diverse populations

being characterized with proteomics.

So it's an exciting time

there as well, right? But we

started somewhere and   that ability to

be personalized and translate to

the impact genetics is

having on something that we might actually

take to the clinic.   

Maybe not Olink, but

those customers is  

    exciting.

 Mhm, this particular

population in the far north of Sweden is

still being followed then today? I

don't think they have additional

samples taken  

as far as I know. But they

continued studying that and then

also since that was the first

more epidemiology study we did, they

also were part of a 

    European

network with other concerned populations

that followed.  So that was really the

start uh, of it. And

also with all these lifestyle factors

they had many more papers

coming where they were looking into

the    

specific factors affecting like the

Swedish tobacco with the snuff

for example. That they saw

association to some biomarkers

and they got some media

attention for also using that to

look at aging and biological versus

chronological aging and

how    diets

like fish and coffee can

affect or reduce your

aging and so on. So...  

it was fascinating.   

that's great    

news for us. Coffee drinkers for

sure. Yeah, exactly.

Well I think on the reference to snuff for

those not familiar with it. It's

really popular in Sweden, I guess most

of Europe, but I think it hasn't hit

the US yet. Is it popular in

Greece?      

 It's kind of a thing you put in your

gum. And is it nicotine? Yes,

for sure.    

  No, it's actually 

 not even all of Nordic, but

some of the Nordic countries, but yes,

that's why also this type of research

was supported. I would say it's very

popular in some areas of the US as well.

For sure.    Okay,

so you've seen it here.

Absolutely.   This cohort is like

it was really well conserved. An isolated

cohort. Right. They've seen the real

effects and the real association with the

biomarkers without any so much external air

pollution or other factor they may

influence with that. That was a beautiful

place, actually. It was a beautiful, amazing

yes,    exactly.  

It's hard to capture those

environmental variables right. But that

the protein levels could

exceed the challenges with

capturing some environmental

variables. I think that's a

message that I find we have to

convey to a lot of geneticists who are

used to the signals being weaker and harder

to see,  

... and having the power to detect

some of these polygenic

signals... to disease

can be more challenging in genetic

studies that are solely

genetics and disease. But I think bringing

in proteins can allow for

  magnification of that

ability to see that

association. Mhm yeah. So then

back to that. This was the first

publication, I don't think we could have

asked for a better    start

because it really first, I mean,

demonstrated the robustness of the

technology that was very important being new

into the market, but also the

power, as Cindy said,

combining high quality

proteomics with genetics and this

epidemiological information. 

And now 1000

publications later, I

understand the same group had a very

interesting recent Olink

publication as well. What can you

share about that? Yeah, I mean they

have since the beginning. So they started

more with population, 

health studies and

then   part of one of the

course they did, they saw some

interesting signatures for gynecological

cancers. So then they

continued

drilling down that path

and then saw early an

interesting signature,  

for patient statification of

ovarian cancer. So

we worked with them around that

and      together

with this group that we also

begin our journey with

our focus panel with

custom development. So 

       we

helped out with developing that protocol

with the input from FDA and that

whole story.   

I was just going to say I also love

that Stefan Enroth, who was the

first author on that early paper,

is now the PI (principal investigator), the last

author in this most recent

paper.      

 We all evolve. Yeah.

No exactly. So they have continued I

mean, we developed

a focused signature

panel for ovarian cancer where they could

see that they were superior to what

is actually used today in

diagnostics, in the US.

But they have continued trying to

polish on that and hoping to

get it to something

clinically,useful. And also looked

into other matrices. So

this was first based on

  plasma, but also looking

into alternative

matrices that can be, sampled

in a home environment with

filter papers. And

now, using our (Olink) Explore, the

broadest    

.ibrary.    So that was a

paper that came out, just was it last week

or two weeks ago, where they now

have continued to

really polish on this

signature. So great

work. And for background,

ovarian cancer,

third major   fatality

 rate,   not

very good biomarkers at all. CA


ages, it's just not that

great.   You mentioned

patient stratification. So this  

particular Focus and what you're

talking about is a custom product of


they applied a handful

of markers. Was that to stratify

patients for treatment? So 

    the first question

was more for patient stratification

because   many

women are having surgery

without needing it, basically. So that

was the first where they wanted to

stratify    women

with benign cysts from ovarian

cancer,   Like a

blood test to stratify those. So

that's where they started, but now

going into more diagnostic

applications for basically early

diagnostic of to  

identify those early

stages.      Yes.

So is this also for recurrence monitoring?

Yes.       

So that's a huge application

right. Where women will

have  a   cyst

removed, like you mentioned, but they don't

know when   they need

to go ahead. And there's really

no real good way to measure

when it's coming back. And so

it's like living underneath this constant

fear   of

recurring, right, ovarian cancer,

which is a huge medical

burden, for sure. And especially if we can

come to the point where we could have for

more careful monitoring of

those   in high risk.

      Yeah,

I love that it's in women's health as

well, which we talk about being

an area that   could

use some more funding. Right?

     Yeah.

     And

you mentioned then about Explorer and

perhaps alternative matrices, that kind of

thing. Right. I mean that has must

been... from

that start with the early

work with 92 Plex,

  assays now to


time. I'm curious, you mentioned

alternative matrices. What were some

of the more unusual things you've

seen in terms of in all these

years ways people are measuring proteins?

Yeah,      I think

we have covered the whole

human body, really.  

  So never

stop being surprised with like and why

do you want to run ground

teas? Okay, so that's one

example that was surprising to

hear, but teeth. Yes,

exactly.  Ah, but of course,

tears, saliva, urine, those

are quite common CSF, of

course, but then   

different types of biopsies

also extremely important, of course. fine-needle

biopsies,    

interstitial fluids, 

 synovial fluids,

blister fluids from

... burn

victims.    Wow.

Interesting.    

Yeah,     we have

covered, I think, everything.

  Intestinal juice was

interesting when we got  

there was some device that

collected intestinal juice. So

we ran it, and it worked. 

 How interesting. So, I think

a lot of these samples, right,

where you don't even bother to

quantitate how much protein is in the

sample because you consume a lot of it.

Right.   And people

don't know beforehand if it'll

work. However,    we

have assurance that we use

very small volumes. We were

able to be very sensitive to pick up

very low sort of

amounts of protein available.  

Right? People just say,

well, we don't know, therefore, we just

need to go ahead and try it. And many times

it works. Right. I mean, we have had

applications where they said, we collected

these very precious samples years

ago, but we couldn't use it for anything.

And now we have the opportunity and we could

deliver   extremely

valuable data. So all of these fine

needle biopsies or micro

vesicles, tape

strips, exosomes, 

cells. Yeah, exactly.  

So, huge

impact. Yeah. These antibody

hooks, right. They're hooking it out

of   this solution in such a

low volume, it's, ah, pretty

exciting.      And then

we haven't talked about the different

species that we have done as

well. That's the whole

'zoo' that we have done as well. 

   So tell

us.       

    Interesting. 

     Just to be

clear, our protein

targets are

optimized or developed in R & D

to, human with

all but our mouse mouse panel. Right?

We certainly have a mouse panel. And so when

someone comes in and wants to understand

what's going on with a cow, for example,

    what do you tell them

and what are the most

extreme examples that you've seen?

Yeah, I mean, what we tell them, of course, 

 exactly what you said, that we

don't have any cow

specific panels,

but it's quite close

homology for many of these

species to humans, and they don't have

any other better options, 

  so   we give

them more data than they could get

from anywhere else.

So,   of course,  

rodents, ...

nonhuman primates, dogs,

cows,   

 fish,  

horse. Wow.   

   So actually, they're able to

measure proteins out of fish, even

though we know that our

antibodies are generated against

antigens from humans, but

still we're able to actually 

 conclusively identify

that    the

proteins measured. In a fish sample,

I think the detectability

in fish was low. 

 So   it's

not anything we recommend 

 normally. Yeah. 

    With some

underlying information that you can get from

for specific proteins, you can get

some interesting results out

of it. It reminds me,

again, bringing back into the genetics,

is we worked on a whale

project, and there are no

SNP chips for whales. Right.

So    I think we use

the same HapMap


from Enroth et al. in 2014,  

to see how many SNPs we could find

homology... across species.

And it was actually pretty

useful. So, yeah,

interesting.      

  It's coming back a

little bit populational like the generation

of big data.   I

know now that there are some  

  projects running at

Olink in regards of

visualizing and integrating

data with Olink Insight. Could you

give us a little bit of

feedback on that? Would you give us some

comments on that just to get to know the

more details?      

Do you refer to the big

publication?       

Yes. Olink Insight is a very,

very exciting new initiative that

we have. So it's a 

digital knowledge platform

for proteomics that we have built

for our customers and

community.    And there is when

looking at in the digital

space, there's nothing of this kind on the

market today.    

How we started that, we thought that

since   we see us as the

leaders in proteomic assays, so we also

want to be pioneers in the digital

space and drive the development

for more modern innovative

tools to help.   

  The proteome is very

complex. The data analysis can be

extremely challenging. If we

can, with our insights and

experience, try to

support the community   to

faster come to

conclusions and actionable

results. By

developing tools and 

 connect different  

  public databases

and different annotation tools,

we can help to support

them throughout basically the

journey. So I'm very, very

excited about Olink Insight. So

the difference we're going to have or we

have different   apps to

support the analytics

side as well as open

data sets that you can use for

validation or confirmation of a

disease signature or

compare with a

healthy proteome, and

also share data

stories where it's like best

practice analytics, 

 ah, for different

applications. So it's a

fantastic platform.  

Yeah. One of the best features within

that, that I've struggled with since I

joined Olink is that conversion

from gene name, where you

have   many different gene

names for a single gene,

converting that to the

protein that is coded for by that

gene. Right. Because in the genetics

base, so many people work with genes, so

there can be   a dash

in there or no dash in there, or there

can be something that looks like a date. So

you throw that into Excel and it's a real

pain to look up DEC1. Right?

But to be able to pull that out of

Insight, it's such a simple thing,

but      it's got

a nice functionality, 

that I think  

is just a microcosm

of the bringing together of the genetics,

and the proteomics. Just a nice

example of how thought out it was in

the needs.    

And for those interested in trying

it out, it's free to

use it's at 

insight.olink.com,  

One of the other interesting features

that relates to the 1000

publications is the ability to

search publications by

Biomarker, is that correct Ida?

Correct.     

   So this is basically,

why wouldn't I use

PubMed versus

this particular feature within Insight?

No, exactly. And I think that's one

of the features at Insight that you can go

to PubMed, but of course, if

you want to see the thousand publications in

different categories, that's  

the place to go. But also in.

general, it has very smart, smart search

tools,  but it's public information.

But we have tried to make

it in an even more user

friendly   interface,

the same as with the

Pathway Explorer that we call it,

that is based on the amazing Reactome

database. But it also

has some additional layers to it

where you can    

insert a list of your top

markers and really see the underlying

biological pathways and

mechanisms. So it's a,

fantastic tool to go there.

     You can download

the images as well. Right. Once you got

that publication set

up.    When I was playing with

it, I was shocked when

I clicked on a single

node and the amount of

information that I can find

about that node in

really well written prose with

references and everything I wanted to

know almost in like three

or four paragraphs. It

was remarkable work.   

A lot of work, obviously, has gone

into it, and remarkable

resource.        

  Well, thank you, Ida, for

joining us today. I really

enjoyed this conversation. Are

there any last words you like to share with

our audience? No, I think this is just

the beginning. I think still 1000

is an   amazing

milestone, but, I think

already this year it's been


I can be invited again when we reach


be there you go. Absolutely.

    You are

always welcome. Always.

  A big shout out to

all of our both the early adopters

that's been with us since the

beginning and supported us.

... we wouldn't be anywhere without

them. So those are the most important

players here.   Absolutely.  

For sure. All right, until

next time. Thank you for

joining us. Thank you. That's great.

Bye. All right. 

 Thank you for listening to the

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