Olink Flex with Katarina Hornaeus

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, 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 Sarantis. Thank you for joining Proteomics in proximity. I'm your host, Dale Yuzuki, with my co host. Good morning. Good morning, Katerina. Good morning, Dale. And today we have as a guest with us Katarina Hornaeus. She is currently a product manager with Olink Proteomics. And Katarina, if you can tell us a little bit about your background first. I've found that you're really interesting in terms of you've been with Olink for many years, but... maybe we start with sort of your education and then take it from there. Yeah, so I moved to Uppsala, uh, early 2000, and started studying molecular biology actually, uh, at the Swedish uh, agricultural university, uh, because I was so into veterinary, um, medicine and animals, but soon realized that, ah, I was more into the tiny molecules rather than the actual, ah, animal. And you grew up in Sweden and so did you grow up on a farm with animals? No, I didn't. I grew up in Stockholm. Uh, okay. City girl. That's my four first years in city center of Stockholm. Um, I see. But nonetheless interested in animals. I mean, Sweden certainly is an agrarian place. And how many of my colleagues at Olink really like horses, for example? And of course, I don't have much exposure to horse culture. I don't know, Sarantis, in Greece, it's not something usual. I mean, there are people that are taking care, but uh, I like horses. But you have to dedicate a lot. Of time and effort, of course. Katarina, then, so you were at an agriculture university and you discovered that you were more interested in molecules. So then what did you study there? Um, what I studied at so, they had actually this bachelor, program in biotechnology. Um, so I started, studying that. And then the agricultural university is very close to Uppsala University, where you have all other education. So they had some nice collaborations. So I did some courses at Uppsala University, some courses at the agricultural university. so, yeah, they gave me my degree in molecular biology. Um, and then I did a few years in a genetics laboratory, as a research engineer. Really? What kind of genetics did you work on in that laboratory? Then? I was back to animals. ...so we were DNA typing horses. There you go. That's great because in Sweden you have to DNA type your horse to get a passport for them to make sure you have the correct father and mother in the passport. They work with that. And we also, did some, genetic tests for diseases that they can have. ...so you understand then, a lot of molecular biology techniques on the genetic side. And then where did you go? then I did something completely new, so I went, uh, to the newly formed Science for Life Laboratory in Sweden, m, there was, um, um, a woman at Uppsala University, who was going to start up a core facility for Mass Spec analysis, proteomics analysis with Mass Spec. Uh, so, yeah, together we started building this core facility for Mass Spec analysis. Um, so then I was into proteins. How do you see this transition from genes to proteins? How do you feel (about) this transition? Actually, I, uh, was really excited because of course, you get some background to everything when you study, but when you start really working with it yourself, you start to see completely different pictures of everything. And, um, I was so excited about proteins because that's actually what's going on in your body, right. So you can really look at different, uh, phenotypes, based on the proteins, which you can't really do, on the genetic side. As far as the Science for Life laboratory, if I understand correctly, this is a government effort right, for research. And they set up basically a couple of institutes around the country. Was the one in Uppsala established the same time as the one at the Karolinska? Is it the KTH in Stockholm? Yeah. So I think, at least those Mass Spec facilities were set up around the same time, but they had slightly different angle. Uh, since we are so close to agricultural university, we did a lot of studies, from the veterinary side of things, and a lot of bacteria, a lot of plants. So, I would say more those kind of projects rather than the bigger Human Project. I see. So the bigger human project at KTH, this is with Mathias Uhlen, right? Exactly. And Johan Schwenk. Oh, Johan Schwenk. And this is the Human Proteome Atlas. Right. That they had started around that time. Exactly. And then I see. And then the group up in Uppsala that you were working on was still using proteomics, but looking at as a part of Science for Life laboratories, looking at other organisms. Yeah, but we did Human Project as well, mainly from Uppsals University. Um, but I thought the ones that were non human organisms were much more ah, interesting. Wow. So here it is. You go back to the non human world, right? Yeah, exactly. But it was mainly because all the projects coming in were so different. And you work with bacteria and then you were working with horses, and then you were working with a plant and. Then, yeah, so you went from genotyping horses to look at parentage and lineage to looking at horses from their MasSpec proteomes, then being an expert in Mass Spec, actually, for sure, you have seen some limitations. And then how do you see this transition with Olink technology? How do you see this transition from Mass Spec to Olink? What is your experience on that? Being like a Mass Spec expert? I mean, the main reason for me quitting my Mass Spec career was because I was so sick of all the maintenance that you have to do with a Mass Spectrometer. I can't count the hours I was sitting there in front of that huge machine with this liquid chromatography system trying to get this column in the exact correct position, get the pressure at the exact correct level to not get any leakage. And then after 2 hours you were like, yes, I finally nailed it. And you walk up to the office and then 1 hour later you go down just to check that everything is fine and then it's a leakage and you have to start over. There it is, it's like a part time plumber, right? You have to make sure the plumbing is correct. Now that's the first time I've ever heard of that. Right? This is the first time we get to that level of detail where somebody is routinely doing this. I don't have mass spec experience, direct experience, but here we're talking to somebody. You did this, you were at, Uppsala, uh, there at the Science for Life Laboratories for a couple of years, is that correct? Yeah, I was there for three years approximately. And then, ...was that at that point you joined Olink? Yeah, I was at Uppsala University. I heard about Olink and the whole time in different (conversations). And looked up Olink, found out that the company is just across the street from where I'm working. This company seems super cool. And then I was looking for a job that was not in the lab because I felt that I've been in lab for so many years, I wanted to try something else. And then there was this position for, a technical support position, at Olink. Um oh, how cool. And this was very early in Olink's sort of commercial history. What year was that? That was 2016. 2016. So this was at the very beginning. Exactly. So you were one of the first technical support people, is that right? Yeah, I basically was the technical support at the time. So we had one technical support, we had one data scientist. I think ah support role is a great role. I think all of us who have passed all these things because you learn the good and the bad things of your product, the good bad things from your customer. Do you have some anecdote from a customer at this time that you can share with us just to hear how people, they start to describe? No names. Thank you Dale. We have so many great stories from these early days, but I remember one, customer from I think she was on Ireland, it was a really small project and it wasn't like, cell lysates, nothing that we promote that we were doing at the time. But anyway, they came back to us and said that, we've run your technology now, where we got the results from analysis service. We find nice, separation of our groups, but then we wanted to validate this with another technology. So they had validated or tried to validate the results using an ELISA And, the results were like, all over the place. So they were like, oh, it is crap. We don't trust you. Your technology sucks. They were like, super upset. No, I know what that's like, because there's so much investment. Right, exactly. It was fee for service then. Right. They sent samples from Ireland to Sweden. Yeah. So a lot of work went into it. Understood. So we tried to solve it, but then in the end, we just gave up. And we bought those ELISA kits that they had used. We brought them in house to R & D. And since we had our samples, that analysis service, we used our samples and some additional, samples that we had. We ran recombinant antigens in buffer. We made a pretty big experiment out of this. And what we found out in our experiment was that the ELISA kits were actually or one of the ELISA kits was actually not measuring, but it said it should be measuring. Um oh, that's great. Here it is. You actually had the exact antigen. And this was when we had, what, just like a single Or... I think we had around five of them at the time. The customer was running several target one particular protein. Right. They find something interesting. They're looking at an ELISA, nothing's matching up. So you're looking at one protein out of several hundred. But you went ahead and tried to reproduce the customer's problem, and then you find out that their orthogonal validation method was incorrect. Yes. So what did the customer say after that? I think they were actually still a bit grumpy. They were a bit disappointed, I think, that it wasn't the way they thought it was, but... it generated some additional Olink studies from that specific place. That's great. That's a nice story. Yeah, that is a great resolution. Right. Where actually there was a problem with the other method. Yeah. Were there other situations right. Where, there were just things that were mystifying to Olink, but then resolved. Yeah, I have two other stories on. One is, um, where we ran, like, our first huge, big study. So, 1000 samples. That was like, enormous for us at the time. It was this important KOL (key opinion leader) from the UK. We were like, all right, we finally get to run a project for this important customer, and we really want to give them like, the best results ever For clarity. KOL means key opinion leader. So we're talking about prominent scientist, who's senior author on papers, et cetera. Go ahead. Exactly. Ah, so they sent us 1000 samples. We used, um, I think our Target 96 Inflammation panels, sent back the data. We were like, okay, so this is going to be great. Finally they're going to see how great our technology is. Um, so what they did and they had some previous ELISA data on this sample set and, they had run IL-6. And then a couple of weeks later they came back to us saying that we have no correlation for IL-6. And we were like, even at the time, we were like, but we know that IL-6 is working. We have done correlations, we know it's working. So we were, me and the data science person. Um, at the time, we were doing some really thorough troubleshooting, trying to understand how they mixed up their samples in any way, or the sample manifest. We tried so many different, combinations and we used like, algorithms to try to find matching, uh, data points with patients. And we were doing this for so long. Uh, but yeah, the only explanation we would have is that they have done a mix up somewhere. and then but yeah, we didn't manage to solve it at the time. But then, one or two years later, one of the PI's and that sent those samples contacted us and were like, actually, we sent you the, the wrong sample manifest. Or the biobank had sent you the, the wrong sample manifest. So once that was solved, the correlation looked perfect again. Uh, that's great, that's nice. It only took one or two years. It only took one or two years. They figured it out, right, that it wasn't the IL-6 signal and they're able to use that data. Wow. And you said you had two more stories. What's the last one? Yeah, I have another one, which was, from the same region in the world. Actually. There seems to be pretty grumpy over there. That's really funny. No joking. We won't be making a joke on that. It's fine. Just correlation. Just a correlation. This is just anecdotal, it just happened to happen. But anyway. Uh, this was like one or two years later. And we had a customer, who we had also like, convinced to like, can you please try out Olink? We think it would be great for you to try it out. So they put together some samples. They were working on this, ah, rare disease. So they didn't have that many samples, but anyway, they sent it to us and we ran it and we sent results back. And they came back and they were so upset again because they didn't have correlation this time around. I think it was, for MSD (MesoScale Discovery) and OLink, um, for our audience. To be clear, MSD stands for MesoScale, um, Discovery. So MesoScale Discovery is another multiplex, ah, sort of protein analysis platform, say, data from a different sort of orthogonal technology. So go right ahead. Yeah. Right. So we were again investigating, have we done anything wrong in the lab? What's going on here? And then we had, um, a couple of meetings where we tried to ask them, so, did you actually run the exact same samples using the both technologies? Did you run the same sample matrix? Um, and first time around, they said, yeah, we run the same sample matrix. We're like, okay, so we did some further investigations. Couldn't really understand what's going on, so we schedule another meeting. And then I really asked, I was like, So what samples did you send to MSD? Was it serum or was it plasma? He was like, It was serum. I was like, okay, but, uh, what you sent to Olink was plasma, right? And he was like, yeah, but they say it doesn't matter. I was like, no, it doesn't matter if you like, for the technology, but when you look at correlations, there's different matrices. Uh, and he was like, oh, yeah, okay. Right. So after that meeting, he became our best friend and our best advocate. Yeah. You turn the negative into the positive, and that is remarkable. And so what about a year, year and a half ago, you made a transition from technical support, right. You became a Director of Technical support, growing the team. Oh, by the way, how you went started from the first technical support person, and when you moved positions, within Olink, how large was the technical support group? so my group was around ten people at a time. Um, when I started tech support, I was doing tech support and Field Application scientist role in the same role. And then, like, I think in roles so that I was doing only tech support, and we had other people taking over the FAS responsibilities. So we had I mean, the tech support group was about ten people, but then we had the FAS team that were, I guess, around 20 people at the time. Wow. So you went from a technical support field application scientist role as one person to now 30 people. That is so cool. And then you were involved then in the hiring of all these 30 people, is that correct? Because you had yeah, not all of them. I mean, I hired a couple of them, and then they, uh, kept on hiring new people. Yeah. Ah, wow. Illustrating the growth, right? Yeah, but it's been a great experience. I mean, I've trained many of our labs that are still running Olink. Great. Yeah. That's nice. Katarina, you mentioned about 96 and Target, and I'm guessing that this is part of our, let's say midplex. And this, uh, is Midplex product. Would you like to give a little bit of overview what we have now in our portfolio, like, for Midplex. Yeah. So for Midplex, we have our working horses. The target it seems. So we have 15 of them. Um, where, um, we have 14 human and one from mouse. And then we have a, lower plex panel. The Target 48 cytokine, which, gives um, data in ABS quant. So in picogram per mL. And, with this panel? We have put a lot of effort in pulling in the right proteins, um, to this panel. And it's been really appreciated on the field because people really the goal that we had was like, get the best targets into this panel. And what we hear from customers is that you've actually managed to put them in the same panel. So if I run other technologies, I have to run multiple kits or multiple panels from them. But you have them in the same panel. Um, that's great. And now your current role is product manager for two other products. Yes. Right. So now we're getting to the heart of sort of your day to day. Exactly. Now actually, starting from this year, I'm product manager for Flex and Focus. Whereas last year I had the whole Mid Plex, portfolio. But since we have now launched Flex, um, I'm going to focus on these two products which belong to our customized offering. Sure. So if you can first talk about Focus, because a lot of people may not be aware of Olink Focus. Yes, Focus is our, like, really premium product. So this is a product that we develop, like, from scratch for our customers. So, like, from having the antibody and the oligo and putting them together to produce the probe, um, and... we work really closely with our customers for whom we develop these panels. Um, we have you can select different levels of validation so you can have the basic validation offering, but then we have several other layers that you can put on to really tailor it to the needs that you have. And you can, select assays from our whole and put them in to your smaller 21-plex... panel. And we can also, like, build a panel for if you're interested in CSF or Urine or like, supernatants. So, yeah, we can tailor-make this panel for you. Meaning you're actually adjusting the panel for the type of sample the customer plans to run. So if they wanted just to analyze urine, that Focus panel of 21 out of remarkable, right, we have 3000 antigen / assay pairs. Right. And then you then shrink it down to any sample type, but you're saying, okay, customer wants to test or routinely examine urine and to optimize it for urine. Is that correct? Yes, correct. Just like that. That's amazing. That's amazing. What you tell me then, uh, about Olink Flex? This is our newest offering, right? Yeah, it's our newest offering. So, this is, somewhere in between our fixed panels and the Focus panel. So what we've done for Flex is that we wanted to offer a quick way for customers to pick and choose, proteins that they're interested in, and get them in a kit, like, within weeks, instead of this long validation development work that we have with Focus. Um, so what we've done for Flex is that we have, built a library of approximately 200 proteins, with high, inflammation, uh, content, basically. the way it works is that we have prevalidated all of these, assays in house using the same level of validation as we have for our fixed panels. Then we have to give a picture of it. We have Olink, and, um, then, our customer says, well, I want these, tubes, pull them into another tube, and send it to the customer. That's great. Ah, is it already available, Katarina? This product? Perfect. Yes. And where can I see the list of 200 proteins? So, ah, you can, of course, go to Olink.com/flex where you will find the list of proteins and all the validation data and the validation data package, describing exactly, how we have validated the product. But what we have also developed for this product, which is, I think, like, super cool and very unique, is that we have this panel design builder within our digital, platform Olink Insight. So you, as a customer, can log into Olink Insight, go to the Flex section, and there you will have your own, like, workstation, for building customized panels. So, two things, right? Olink Insight can be found at https://insight.olink.com insight.olink.com And I think the other observation is you've used "Cool" Now twice in this conversation. First, when you joined Olink in Really cool company. So, is Olek still a really cool kind of company. Right? Things are happening all the time. New things are happening. We're like, we're really on the front line of things. It's exciting. We, have Leading Edge, right? Yeah. I just went, like, this panel designer and Insight. We have competitors, right, that have similar products. I, went to one of those panel designers just to have a look at what it looks like, and I was just so confused. They were like, you had to choose species, you had to choose the number of plates. And then I was like, so am I going to decide which plate to put, which assay on, and how many can I put on each plate, and where should I put them? If I click this, then that disappears. But I want that protein. But it disappears if I click on this protein, what does that mean? And so we call it combine-ability. Right. In terms of the percentage of proteins that you can get. And what you're saying is with other technologies, they just don't play nicely together, is that right? No, exactly. But Olink Insight is a great tool. I played with it with myself, and I really find it really easy to do it and very straightforward. And I think people that would really enjoy and eager to start customize their projects in a way right. And um, be the PI of their projects. That's really great. That's really great. So while alternative platform, I mean, namely it's like what Luminex can do, maybe like you can choose from, but really you can't combine anything, is that right? Of course you can combine, but to a much lower degree, than for Flex. So we have a 99% combinability of our library, which means that you can basically freely mix and match what we have in the library. We made an like, estimate of competitors and they are at about lots of limitation. If you keep iterating 80%, 80%, stuck. Right? Yes. Wow, this is great. Yeah. Their problem is that they have these "matrix effects", which we circumvent with our technology. Yeah. And you mentioned absolute quantitation. Is that what people get with Flex as well? They can get picogram. Yes. They get pico-gram per mL. Um, but you can also export the NPX values, which I think is really beautiful, because then you can integrate your data from your Flex project with the other, Olink products. And for those that may not be familiar with Olink data, NPX is normalized protein expression. It's a log2 sort of relative numerical scale is sort of, sort of what that data refers to. So we have a relative quantitation via NPX values, as well as absolute for the Oling Flex. Uh, Katarina, any final of things you want to say about Olink or Olink Flex? Um Olink flex. Yes, I want to say that one great ah, thing with Flex is also that we do um, a ah, quality control of each produced Flex kit, which is pretty unique on the market, actually. So many other companies that offer these customized products, they just pull them together and ship it to the customer. Whereas we actually put together the kit, we run it in house at Olink to make sure that it's working as it should, that we get out the data that we should get from it, before we ship it to the customer. And what does this QC sheet look like? Meaning it'll actually give you sort of we put in this amount and this is what we measured kind of thing. So, what you will get as a customer is that with each kit or each order, you will get a certificate of analysis. A C of A! Um, wow. Yeah, exactly. All the reagents indicates, um, it shows you the, um, LLOQ and Upper Limit of Quantitation for each protein in your panel. And it also gives you, like, a statement that this has been quality control according to Olinks' guidance and so on. That's great. Well, thank you for sharing these things with us, uh, today. Kurt, it's great to meet you. Thank you again. Have a nice day and safe travels, everybody. Hello, M. Thank you for listening to the Proteomics in Proximity podcast brought to you by Olink Proteomics. To contact the hosts or for further information, simply email info@olink.com.