Space at the bottom of your screen, and after the presentation, we'll open to your questions. With that, Christian, I'll hand it over to you.
Thank you so much, Alex. As always, good to see you and great to be here and having the opportunity of presenting Evaxion. I'm Christian Kanstrup. I'm the CEO of Evaxion, and I think it's fair to say we are at a very exciting point in time in the Evaxion journey. We early this year raised a decent amount of cash, now have cash into mid-2026. At our latest public offering, we also had Merck participate in the offering. That's the third time in a row Merck is participating in one of our offerings, and they now hold around 20% of the company. What we also have is we have a transformative option and licensing agreement, which we signed with Merck in September last year. It is tracking towards the decision point of option exercise expected in the second half of this year.
If Merck decides to exercise the option to both the vaccine candidates included in that optional licensing agreement, we can get $10 million in cash, which would in turn extend our runway into 2027. On top of that, we are seeing our lead candidate, EVX-01, continuing to deliver solid data, and we are on track for our two-year readout in the second half of this year. With that brief intro, let me take you through a quick Evaxion update. First and foremost, I will be talking about the future, and we know how it is when you talk about the future. That is uncertain. I direct your attention to our forward-looking statement slide here. Briefly, who is Evaxion? For those of you who do not know us, we are a pioneer in fast and effective AI-powered development of new medicines.
The core of Evaxion, that's our AI-Immunology platform, clinically validated and leading platform. An interesting thing about Evaxion is we were actually founded as an AI-first company back in 2008, i.e., we have had a significant head start and have been spending the past 15 years in developing, perfecting, and validating our platform. That is a key differentiator compared to many of the newer AI companies out there today. On top of that, we have been spending time building a multidisciplinary capability set around our AI platform. Today, we, on top of that, have a state-of-the-art wet lab here at our site in Denmark, as well as animal facilities. What this has allowed us to do is to build a broad pipeline, pipeline of preclinical and clinical programs across cancer and infectious diseases. With that, we are focusing both on platform and pipeline to create value.
That offers quite significant and unique opportunities for value creation, which we are pursuing in a multi-partner approach. I'm just going to spend a little bit of time on the focus on both platform and pipeline because, of course, you often hear people are saying, you got to decide, are you a platform or a pipeline company? You can't be both. I firmly believe due to the unique capabilities and properties of our AI-Immunology platform, we can be both. If we look at the platform, what that does, it enables what we call high-value, low-risk partnerships on target discovery, design, and development. Here, teaming up with pharma, teaming up with biotech to develop novel vaccine candidates.
A good example of this is in 2023, where we entered into a collaboration with Merck on developing a novel vaccine candidate for an infectious disease, bacterial infectious disease, where there are no vaccines available today. We were approached, asked if we could deploy our AI-Immunology platform to develop a novel vaccine candidate, and that is one element of the option and licensing agreement that we entered into with Merck last year. On top of that, we can, of course, use the platform for fast and cost-effective replenishment of our internal pipeline, as we have a strong focus on partnering. When we are partnering our existing pipeline candidates, we need to continue refilling that. That can be done in a very effective and fast way via deploying our AI-Immunology platform.
For the pipeline, this is really around advancing select high-value programs into preclinical, early clinical development ourself, focusing on retaining value and then partnering at the right point in time. An example of what we want to do here is EVX-B2, which is our proprietary gonorrhea vaccine candidate, which we actually partnered with Merck in the optional licensing agreement entered into last year. This is really about retaining value by bringing assets into either preclinical or early clinical development before pursuing partnering. There is a lot of complementarity between both platform and pipeline, enabling us to pursue both. Just a few words on the partnership with Merck. I have talked about it already. It is an optional licensing agreement covering two candidates, our proprietary EVX-B2 gonorrhea candidate, and then EVX-B3, which is the target discovery collaboration we entered into with Merck a year earlier.
Of course, having the opportunity of partnering up with the world leader in vaccine development and commercialization is of significant strategic and financial value to us, but more importantly, it allows for fast and effectively bringing these novel vaccine candidates towards the market. Both areas are diseases where there are no approved vaccines today, so a significant and serious unmet need. The structure of the agreement is we got $3.2 million upon signing last year. As I said, if Merck exercises the option to either one or two candidates, two candidates, we get $10 million. If they exercise the option for only one candidate, we get $7.5 million during the second half of this year. In addition to that, significant downstream payments up to $592 million per product, plus royalties on sales.
On top of that, I already mentioned it, Merck is our single largest shareholder with around 20% of the company. This, of course, further solidifies our relationship with Merck. Let me just touch a little bit upon the markets that we are addressing today. Cancer and infectious diseases, both of these are markets with significant, significant unmet need. Think about it. Within cancer, 10 million people dying a year due to cancer. Way too many. Also within infectious diseases, we actually have 8 million deaths a year due to infectious diseases. Significant unmet needs just in the two areas we are in today. In terms of market sizing, the cancer immunotherapy market is expected to be almost $280 billion by the end of the decade. The infectious disease market, almost $70 billion.
Fair to say we have ample opportunities for addressing significant unmet need, thereby also significant market opportunities with our AI-Immunology platform. Let me just dive a little bit into what is AI-Immunology actually about. It is for vaccine target discovery, design, and development. First and foremost, it's a validated platform. Due to the fact that we embarked on this journey in 2008, we have already now validated the platform in three clinical trials. This is a unique differentiator compared to many of the companies who have emerged over the past couple of years focusing on utilizing AI for target discovery. We have shown in a clinical trial setting there is a clear link between the predictive capabilities of our platform and outcomes. The platform is fast.
In just 24 hours, we can run the model to get proposed targets for a given either infectious disease or a cancer vaccine candidate. The model is also very targeted in the sense that it gives a ranked list of targets, and we know we can choose just the highest ranked ones and only need to test those. That means that we can test 80% fewer targets than what you have to do if you applied conventional methods. Taking this together, it also means that it's a very cost-effective platform to utilize for novel target discovery. Actually, it's 90%+ cheaper than deploying reverse vaccinology for identifying novel targets. This in essence means it's fast, it's cheaper, and hopefully also leads to lower risk in novel drug development. It's also scalable.
We can deploy the platform into more than 100 different diseases, creating a lot of growth opportunities for the future. Just a few words on the actual architecture. If we look at the infrastructure, we're deploying all the modern novel tools, large protein language model, AML, proprietary data sets, Python, et cetera. We have a quite unique setup with a mix of cloud and on-premise setup, but where the really differentiating element comes in, it's in a unique building block architecture we have for the platform. The platform consists of 26 different building blocks. These building blocks we can put together in different ways to give the desired properties of the model. That's important because that means by just improving the performance of one building block, we can improve performance across multiple places in the platform.
With the things that are happening, the rate of change in AI, of course, being able to continuously improve the performance of the model with limited investment is a key enabler to staying ahead of competition. That we can do with this unique building block architecture. I already talked about it. We can easily expand into new therapeutic areas. Today, we are in cancer and infectious diseases. Tomorrow, we could expand into autoimmune diseases, allergies, multiple opportunities for future growth. What we also have, I touched upon it, we have been building a multidisciplinary capability set around the platform, starting with the disease biology understanding, ranging over target discovery into the vaccine and adjuvant design, preclinical work, CMC, and clinical development. We have the full range of capabilities in-house. What we also have here is a state-of-the-art lab and a state-of-the-art animal facility.
That is important because that means whenever the bioinformatic team comes up with some AI prediction, we can go straight into the lab, which is right out here, design the vaccine, take it into the animal facility, test it out, validate the AI hypothesis, and generate proprietary data. This allows for driving continuous differentiation. If we look at it, due to the multidisciplinary capability set we have around it, we can do these continuous iterative learning loops. We can expand our data set with proprietary data, and we can rapidly validate AI prediction. What is also important is, of course, we have full control of the process from the very early idea to validation. We are a one-stop shop towards pharma partners, given that we have everything in-house.
That also means, as you see on the right-hand side in this slide, that the value of our platform is significantly higher than what you see for the less mature AI companies who have not been building the broad capability set around the platform. This, the capability set, the AI platform, has allowed us to build a quite unique pipeline within cancer and infectious diseases. You see the pipeline here on the slide. Our lead asset is EVX-01, in phase II development in metastatic melanoma. I will have a few slides on that later, so I will not be talking much more about it here. Our preclinical infectious disease pipeline, lead asset, Staph aureus, late preclinical development. You see the two assets here, EVX-B2, B3, which are partnered with Merck.
Common for all of our infectious disease assets is its areas where you do not have approved vaccines today. If you combine that with the growing antibiotic resistance, then you have significant unmet needs that need to be addressed. Let's take a closer look at EVX-01 . It is a personalized cancer vaccine for first-line treatment of advanced melanoma, i.e., skin cancer. The concept here is patient gets diagnosed with cancer, a biopsy is taken from the tumor, biopsy from healthy tissue, it is being sequenced, and it is being fed into our AI model, which then designs a personalized cancer vaccine specifically for that patient. It is a combination trial with anti-PD-1 antibody with the aim of improving clinical outcome. If we look at the data here, on the right-hand side, 69% overall response rate is the data we presented at the one-year readout of the clinical trial.
If you compare that to what, for instance, Keytruda have shown in the same population in their keynote six trial, the registrational trial, they showed a 33% response rate. A significant improvement compared to what is gold standard within metastatic melanoma today. What we also have seen, and that's very important for the concept of the personalized cancer vaccine, is that 80% of the neoantigens in the vaccine candidates are eliciting an immune response. What you really want to do when you develop a personalized cancer vaccine, it is to have the components in the vaccine activate your immune response. Here, the 80%, that is significantly higher than what we have seen other companies present with their personalized cancer vaccines. Just a few more words on EVX-01 . These are also from the one-year readout of the phase II trial.
We saw that 15 out of 16 patients saw a reduction of tumor target lesions. Actually, three out of 16 patients saw a complete remission of tumor target lesion. Very strong data, which makes us excited about the two-year readout on track for the second half of this year. Just a few words on two of our infectious disease programs, EVX-01 , our Staph aureus candidate. We have shown significant protection in lesion, sepsis, and skin infection in mouse models. We have also actually shown protection against surgical site infection in large rodent animals. No vaccine is approved for Staph aureus, so we are very optimistic about the prospects for our EVX-B1 . EVX-B2 it's including the optional licensing agreement with Merck. We have shown protection against gonorrhea in 50 different strains.
An area where no approved vaccines exist today, and the problem of growing resistance against antibiotics just continues to increase. Very strong evidence here that not only within cancer and the data we have generated here, but also within infectious diseases, we have the opportunity of making a significant difference by targeting huge unmet needs with our AI-Immunology platform. Just looking a little bit ahead, what are our strategic ambitions and imperatives? What we want to do is, or what we want to be, we want to remain a leading AI-powered tech bio company. To do that, we really need to maintain the leading AI platform. That is where this unique architecture we have with the building blocks is so important because that has allowed us to stay at the forefront. We need to drive best-in-class drug discovery and development.
We need to develop a novel pipeline of R&D assets. We need to become the R&D partner of choice. I think the optional licensing agreement we have entered into with Merck is a good step on the way, really to become the preferred partner of choice when it comes to AI-based drug discovery and development. Ultimately, we want to generate a positive cash flow. As I said, currently cash at hand into mid-2026. We have been optimizing our burn, so we have an annual burn of around $14 million. With an option exercise from Merck and an additional $10 million in income, we will have cash into 2027. We have already achieved the first couple of milestones for the year. We have a number of important milestones coming up for the second half. Merck option exercise decision on that. We have the EVX-01 phase II data.
We also have a strong focus on generating new partnerships. We have the ambition of entering into at least two new partnerships throughout the year. We have a strong business development pipeline supporting that. We are also going to select a lead candidate for a precision-based cancer vaccine concept where we presented proof of concept in the fall of last year. Truly exciting because that will allow for a much broader commercial scope in terms of what we're addressing with our cancer vaccines. Significant value catalysts coming up in the second half, Merck decision on option exercise, EVX-01 phase II data, and for new partnerships as well as several events within our R&D portfolio. Good thing is I'm not doing this alone.
I have a strong team helping me to drive this with relevant experience from both industry, Big Pharma, biotech, and we are ready to execute upon our strategy. To sum it up, I would say we are in a very good position. We have seen strong momentum in our strategy execution throughout 2024 into 2025. We have raised needed cash in the beginning of the year. We have a 20% shareholder with Merck and an exciting collaboration with Merck on EVX-B2 , and B3, and we continue to see EVX-01 , generate strong data. All in all, exciting times ahead with significant value triggers coming up. With that, Alex, I will hand it back to you for any questions.
Absolutely. Thank you very much, Christian. A lot of exciting updates. Maybe we could start with today's release.
You know, you had a release on EVX-01 . You're now in a position to explore the vaccine as a standalone treatment. And so I'm curious, is the vision, you know, primarily monotherapy in the end, or, you know, do you see a pretty well-developed market for combining with checkpoint therapy, you know, inhibitors or other mechanisms?
I mean, we actually see hopefully broad applicability. Of course, so far we have explored EVX-01 , in combination with checkpoint inhibitor. What we also do know is that even though checkpoint inhibitor is a gold standard of immunotherapy, there are still a large number of patients who don't respond to checkpoint inhibitor. There is clearly a need for bringing additional treatment options to the market where you are not pursuing it in combination with a checkpoint inhibitor.
That is where today's announcement, which is around we have dosed the first patient in the extension of our EVX-01 trial. It was originally a two-year trial. We have now extended it to a three-year trial, not because we have not seen good data, but because we have seen so good data that we were curious to see how would it look on a three-year horizon. Also, how would it look if EVX-01 is administered as monotherapy? Because, so far the first two years it has been co-administered with a checkpoint inhibitor, but as the label for the checkpoint inhibitor is indicated for two years, we now have the opportunity of exploring it as monotherapy.
I think, Alex, we will need to let the data speak, but at least I am very excited about the data we have generated so far and getting not only two-year data, but also three-year data for EVX-01 is going to be very exciting.
Great context. Thank you. You know, something else that I thought was interesting, right? You have multiple shots on goal. You know, the AI-Immunology engine has generated multiple assets. I'm curious, you know, has that process improved over time with faster development, better response rates? You know, is there potential to continue improving that with advances in AI? Even a question from the audience on the use of quantum computing and that to improve the drug development, vaccine development.
There is no doubt.
I mean, we have seen a continuous improvement of our AI-Immunology over time, and we continue to improve that. There is still room for improvement. You can say, of course, EVX-01 , if we take the 80% of the new antigens eliciting an immune response I talked about, that's the latest data point. The first data point in the phase two trial, that was 71% eliciting an immune response, then it got to 79%, and now it's 80%. We see this improvement over time. The same goes, of course, for our infectious disease part of the business where we are working on constantly improving the platform, not only to be faster. We are at a point where it's not so much about speed, but it's more about being able to detect novel targets.
That's where we, last year, launched an upgrade of our bacterial part of the AI platform where it can also predict toxins, which is also an important possible target for infectious diseases. I would say quantum computing, I think it's still early for that in a drug discovery context, and it's probably right now more a matter of having access to the right data, not necessarily only the amount of data, but the combination of data and then having sufficient computational power to execute upon that. Quantum computing is still in early days, but of course, definitely something that is going to be interesting to follow for the longer term.
Makes sense. Thank you. We're getting some questions around, you know, partnerships and licensing.
Maybe we could start with Merck and, if you could talk a little bit about the development of that partnership and, you know, the ability to continue and expand it and also even if they've, you know, participated in some of your recent fundraising rounds.
Yeah. No, the R&D collaboration with Merck actually started in 2023 where we were approached, asked if we could utilize our AI-Immunology platform to discover a novel vaccine candidate within a bacterial infectious disease. It has not been disclosed which bacterial disease this is, but it is one with high unmet need and no vaccine today. That kicked off in September 2023. During 2024, we were in partnering discussions with other companies around our gonorrhea vaccine candidate. Merck also had an interest in that candidate.
As we were progressing with other parties, they decided, let's include both B2, the gonorrhea candidate, and B3 in one agreement. We entered into the option and licensing agreement in September 2024. Assuming Merck exercises the option in the second half of this year, they will assume full responsibility for the further development and commercialization of the two vaccine candidates. We will be entitled to milestones and we will incur no further cost. As also said, Merck have participated in the three last financing rounds. They invested the first time in December 2023 in a private placement we did. We did a public offering in February 2024 where they also invested.
Then again here in February or in January this year, we raised $10.8 million in a public offering and Merck came with $3 million out of those, bringing their total ownership to 20%. This is the Merck Global Health Innovation Fund, i.e. the internal venture fund that is responsible for that investment. We are super pleased with having them in as a shareholder, very supportive and of course with a long-term view for the company and broad interest in the platform.
Great context. Thank you very much. Maybe we could talk a little bit about, you know, trends in the share price over the last couple of years.
For folks newer to the name, you know, could you give a little bit of context and also maybe could you touch on, you know, what particular things you think the street may be underappreciating?
Yeah. As you know, Alex, we IPO'd in February 2021, which was more or less at the peak of the current biotech valuations. We were IPO'd by Oppenheimer and they were actually, we were actually their last IPO before the full market more or less collapsed and closed down. You can say it has been tough years for both biotechs in general, but small biotechs in particular. No doubt about that.
but I also think it's fair to say from a fundamental point of view, Evaxion has never been stronger than we are now with a good cash position, with a significant shareholder in Merck, and of course the optional licensing agreement combined with a strong business development pipeline. I would say, where we are now, it's a matter of executing upon our strategy. We are in the good position that we don't need to go to the market for cash, have cash into mid 2026. With the $10 million from Merck, we would have cash into 2027. I think from a fundamental point of view, we are very strong. I think are there specific Evaxion elements that the market don't appreciate?
You could say, for instance, when we announced the Merck agreement last year, bringing in near-term cash in excess of our market cap, we only saw a very small increase in share price. I would say the current environment has not really been reflected in the share price, but my focus is not so much the share price. It is on delivering on the strategy. I am hopeful that that will also be reflected in the share price with all the exciting things we have ahead.
Absolutely. That is a great, you know, summary of the value proposition for folks looking, you know, across AI, you know, drug development, cancer vaccine development. I think that is a great place to end because we are at time.
I'd like to pause, you know, and thank you, Christian, and also thank everybody listening for joining us today.
Yeah, thank you, Alex, and thanks to all of you, those of you listening in. As always, great to be here and good to talk to you all.