0:24
Thank you very much, Chairman.
0:32
I guess we can start.
0:33
So thank you again to the organising to give us the opportunity to come and give a talk.
0:38
So primarily from my standpoint, what I'm going to do is maybe introduce Olink proteomics a little bit, introduce the technologies, just touch on the product portfolio and hopefully timing allow.
0:47
I've got a short summary of a particular use case in a clinical trial that actually uses one of our products.
1:32
So really just to give you a little introduction Olink Proteomics was actually started off from the University of Uppsala in Sweden in 2016.
1:41
And over recent times, we've actually seen some really nice engagement and traction from the market in terms of the products.
1:47
But certainly in recent years, we're seeing that kind of interest from the market grow exponentially.
1:54
We're very humbled by that reaction from the researchers.
1:58
So now we're actually a global organisation and we're supporting over 1000 institutes in biopharma and in research across the globe.
2:07
We also are actually supporting the top 20 pharma companies by revenue.
2:11
And so far we've actually got over 2400 publications, peer reviewed publications, which is a bit of a testament in terms of the quality and the proof of our products.
2:24
And I'm actually hoping by the end of this week that's that number is going to be 2500.
2:28
We're almost there.
2:30
And to date, so far we've analysed with the help of researchers over 4 million of those samples on our platform.
2:39
I should also state, you're probably aware that we were acquired by Thermo Fisher Scientific as well.
2:44
So basically we're hoping that there will be further progression into this space.
2:50
I guess what's really been driving that interest in terms of Olink Proteomics and it really comes down to the fundamental aspect is primarily our technology, which we call proximity extension assay.
3:02
And if I can take you just a few minutes on how it works, if you have your target protein, then you actually have two antibodies that bound to that particular protein and each of those antibodies actually have a unique DNA oligo.
3:17
And once those antibodies bind successfully to the target protein, they bind together and hopefully being in close proximity, those oligos actually combine, hence the proximity extension assay.
3:32
And then it's that unique DNA barcode that is being used to basically detect on a qPCR format or also based on next generation sequencing.
3:43
So overall is that dual recognition coupled with the antibodies that give us the accuracy with this technology, you can actually analyse from as little as 5 proteins all the way up to 5400.
3:58
So that gives that scalability approach on a platform and being able to utilise existing workflows in research labs has actually generated some efficiency gains as well.
4:08
So that has really been the overall support in the product being or the technology being utilised.
4:17
But with that accuracy as well, it actually overcomes some of those traditional challenges using Multiplex technologies such as sensitivity, specificity, basically kind of incorrect leads as well.
4:31
But in addition to that, this primarily is the portfolio that we have.
4:36
So our researchers are actually using this for a wide variety of use cases, anything from broad discovery to targeted research, from all the way down to validation and clinical translation as well.
4:50
And just very quickly, if you look at you know the diagram here on the far left is our flagship product, Olink Explore HD.
5:00
So this is primarily where you can measure up to 5000 proteins from a single platform, basically from an NGS readout.
5:08
And one of our newest and latest products called Olink Reveal that we just launched a couple of months ago.
5:14
This is primarily covering the entire proteome with around 1000, a little bit more than that, biomarkers.
5:20
And a couple of key advantages around that is that it actually provides deep coverage in certain regions around inflammation.
5:27
The hands on time is manual.
5:29
It's only 2 1/2 hours and to make it accessible, you don't actually need any automation.
5:36
They come with lyophilized reagents and any scientist that's pretty deadly with pipettes can actually run the experiments.
5:44
So we've tried to make our products easier and accessible in various different labs as well.
5:49
And then as you kind of move down this side, we have more targeted solutions.
5:54
Target 96 primarily looking at certain diseases or processes.
6:00
Target 48 is primarily 45 proteins that are looking at cytokines or inflammatory responses.
6:06
We also have a mouse panel and if you really want to be adventurous, if you want to do more custom offerings, then we have the Olink Flex where you can actually select a library of 200 and design the panel of interest from those 200, anything from 5 to 30 or you've got the final option here.
6:23
If you really want to develop a bespoke solution and we can support that as well.
6:29
And some of these solutions actually give picograms per ml readout as well.
6:34
But not only that, out of those 2400 publications, we actually have a significant amount or publications that actually illustrate the technology pretty robust in different sample matrices.
6:48
50% of those publications, they're primarily around serum and plasma, which are validated on our technology.
6:57
But scientists are clearly obviously adventurous and they're even utilising technology on other matrices such as CSF, tissue cell lysates, extracellular vesicle, dried blood spots, etcetera.
7:11
And just on the right hand side, we have Doctor Afshari from the Department of Dermatology, UMASS.
7:16
He was even using the technology from skin interstitial fluid where they were able to actually profile different inflammatory skin conditions as well.
7:26
So and he's hoping to publish this data actually in not too distant future.
7:34
Some other aspects about how we're helping in order to allow scientists to gain access to the technology, we're actually offering a variety of different options.
7:45
The first option you see on the left is if you want to acquire the technology in house.
7:50
So that's our signature Q100 instrument.
7:52
So that's a partial image of that.
7:54
It's almost like a qPCR system.
7:56
You can just run it very seamlessly.
7:59
In the middle, we actually have a dedicated global network of certified service providers.
8:04
These institutes have been highly trained and we have day training and they offer consistent solutions to the customers and high-quality results as well.
8:16
And the third option, if you really don't want to get your hands dirty too much, you can actually send the samples to us and we can actually run almost like a white glove support mechanism where you send the samples to us, we can store them, we can run the experiments, we can analyse the data and also give it back to you as well.
8:33
So we have these different options depending really on what your needs are, what the scientists needs are.
8:42
Something that I also wanted to mention, it might not be fairly common known earlier this year the UK Biobank actually sent out a press release by choosing Olink as the choice of platform for the world's largest human proteomic study.
8:59
So this was this is one of their statements actually coming from their website.
9:03
So basically the UKB including their pharmaceutical partners as part of this project, actually then wanted to launch the world's most comprehensive study looking at proteins and ultimately to transform the study of disease and treatments as well.
9:21
And for us, this was obviously a bit of a hard gift, but this is obviously an amazing achievement for us and we're very humbled by it.
9:30
I'm clearly a marketing guy and I don't think I could have asked anything better than this to come out.
9:35
And what they're actually going to be doing is using our Explore HT, the 5400 proteins and running that over 600,000 samples.
9:43
So they're actually hoping to generate more discoveries, more insights into certain diseases.
9:48
And this actually comes two years after we did what they're calling a pilot project of 54,000 samples and the data is now publicly available.
10:00
And we've already seen over 100 publications come out based on the data that they proposed as well.
10:05
So we're pretty excited about this and we're hoping that you're on this will provide more insights into disease and research for everyone.
10:14
This is just for us to kind of illustrate in terms of what we're looking to do over the foreseeable future as well.
10:19
So we've been investing in our portfolio based on the requests and even demands of customers.
10:25
So we're hoping to continue this.
10:27
So as I mentioned, Olink Reveal was what we launched this year and without giving away for the trade secrets, there might be some more things coming out this year and the year after.
10:36
So look forward to sharing those as we go on.
10:40
So actually I'm just going to change tack a little bit just in the interest of time.
10:45
We actually came across this publication that came out in 2024.
10:53
And this primarily is a study looking at immunotherapy in squamous cell lung cancer patients in a phase III trial.
11:03
And the study actually was conducted at Mount Sinai alongside MD Anderson Cancer Institute and it was funded by the NCI as well.
11:14
And I guess the major findings of this study was that when we started looking at serum proteins, they actually saw there was some activation in T cells and certain biomarkers around that.
11:26
And the signatures actually they found were able to then suggest or predict certain responses to the immuno checkpoint inhibitory therapy.
11:35
And what they were looking to do was to understand additional therapy using certain drugs, what was going on.
11:44
And they also found that there was an inflammatory response signature that actually had the adverse effect on overall survival as well in some of those patients.
11:55
So this was kind of an interesting study.
11:58
I think the need the overall follow up median was around 29 1/2 months.
12:05
And basically just to give you a little bit of background, this is obviously some numbers coming from the American Cancer Society where they actually suggest, you know, in 2024 234,000 new cases were diagnosed in the lung cancer and around 125,000 deaths.
12:28
So it seems to be that it was a five year survival rate from 2013 to 2019 around those patients with lung cancer was 25%.
12:38
And as some of you are probably better known than I am, ICI therapy is very prominent in cancers.
12:45
Looking at PD-L1 expression has been the sole predictor of efficacy and one of the other aspects is the heterogenicity of PD-L1 expression being pretty challenging in terms of a predicting response.
12:57
So the overall goal was to look at what are those features that actually guide the ICI treatment comparing them to certain drugs, things like nivolumab and ipilimumab.
13:10
So they were actually looking at those drugs either in a monotherapy using nivolumab or combined therapy using these two drugs.
13:18
And then what were the effects of that?
13:21
So just on the left-hand side was basically the kind of overall approach that they were using.
13:26
So around 275 patients, which was around 50/50 in terms of the monotherapy versus the combined therapy.
13:35
And actually, once they did the study, they actually realised there wasn't really much difference in the two different therapy approaches.
13:46
However, as they dug deeper in terms of the follow up later on in some of the studies, they actually found, oh, there may be some differences in some of the responses in a subset of the patients.
13:59
And that actually then warranted to further investigate what was going on.
14:04
So they actually considered to do a multi omics approach, looking at various different techniques such as Multiplex immunofluorescence, looking at targeted transcriptomics, whole exome sequencing.
14:18
And when I was reading the paper from the author, they were actually making comments about the ability to use blood or serum as a solution that's non invasive, pretty dynamic and also could not be so much affected due to the intra-heterogenicity of the tumour as well.
14:35
So then decided to correlate all of this data and they actually used our Olink target 96 immuno oncology panel.
14:44
And these are just some of the key findings really.
14:47
So just at a high level what they actually found was that in those subset patients, serum chemokines and activated T cell markers such as CDX CL9 and CXCL13 actually demonstrated ICI immune regulating effect in some of those treatments.
15:07
What they also found out was that certain markers activated such as those ones listed there were actually found to be increasing at the baseline, but also in early stage of those therapy and that was around the people that were being the respondents.
15:26
They also found the converse as well looking at hyperinflammation biomarkers that were significantly upregulated in the non responders.
15:37
So this was something that they hadn't uncovered before.
15:40
So this was additional data they were able to get.
15:43
And once they did some additional analysis and modelling, they actually found that CXCL13, CSF-1, MMP12 and IL8, by doing the additional modelling within those longitudinal studies, they actually found that kind of suggests increased risk of death in those particular cases.
16:08
So taking this into consideration as well as looking at those cell activation markers plus those hyperinflammation markers, they were then able to actually have a better correlation as to what's going on in those subsets of patients.
16:24
And now they're wanting to go back and look at all those multiomics data and come with some sort of decision tree as to how they can help suggest the right course of treatment that could be effective but also ineffective to those patients.
16:42
So this was actually something that they managed to figure out using the Olink platform in those subset patients.
16:50
And I think with that, I'll close and happy to take any questions.
16:55
Thank you very much.
