Only going to continue to grow. What's also clear is the healthcare burden, it keeps increasing, and we need to address that. And then there is a need for a faster and lower-risk development of new medicines. And that's exactly what we set out to do: we need to rethink and revolutionize the development of new medicines. And that is what Evaxion is about. Who are we? I mean, we were founded back in 2008 as an AI company with the objective of decoding the human immune system. And I think it's interesting: when we were founded back in 2008, going to use AI to discover new drugs, everybody was looking at the two founders, smiling a little bit, thinking, "Yeah, that's not really going to be possible." Of course, fast forward to today, the world is completely different.
Now, many companies are focusing on AI and claiming that they are very good at AI-based drug discovery. As you'll also see later, our clear advantage here is our head start. The fact that we're, during the past many years, have been developing and refining and iterating around our AI platform that has brought us in a clearly differentiated position. So today, today Evaxion is a pioneering clinical-stage TechBio company, and we have a validated and leading AI platform, which we call AI-Immunology. And what we can do with AI-Immunology, that is, we can fast and effectively find new vaccine targets, we can design the vaccines, and develop the vaccines, currently within cancer and infectious diseases. And you can say, every day, our platform, AI-Immunology, brings us closer to a future where we can treat a number of critical diseases. And that links perfectly into our purpose.
Our purpose of being here—that is, saving and improving lives with AI-Immunology. That is what excites me every day. That's what excites the organization: knowing that we, with our pioneering and leading AI platform, can be contributing to saving and improving lives. And who is the team? I think it's fair to say that we have a strong leadership team with, say, extensive experience across all relevant fields. Here you see the management team of Evaxion. Our Chief AI Officer is also one of the two founders, Andreas. He has been with us since the inception of the company back in 2008. Then I have my Chief Science Officer and Chief Financial, as well as Operating Officer. Birgitte is a Chief Science Officer. Jesper is a Chief Financial and Operating Officer, both coming with strong experience from Novo Nordisk, bringing that to Evaxion here.
Personally, I've also been spending a number of years, to be precise, around 20 years, with Novo Nordisk across the world, across the value chain, with a strong focus on corporate development and as well as business development and commercialization. So a strong team with a broad capability base, aiming at delivering on our strategy. And if I should just sum up this about us section with a few highlights, I mean, AI-Immunology, our pioneering clinically validated AI platform. It also has a, I would say, very unique modular architecture, which I'll get back to later, that allows for quite unique scalability. We have a clinical preclinical pipeline which offers several value triggers. Most significant is our EVX-01 phase II asset, which is a personalized cancer vaccine within metastatic melanoma, where we will have the one-year readout of the phase II in Q3 2024.
We also have several pipeline assets which are ready for partnering. I think the potential of our pipeline, it is validated by recent partnerships, including our recent partnership with MSD, which is the European name of U.S. Merck, where we entered into a partnership in September last year, aiming at discovering and developing a novel vaccine for bacterial infectious disease. We also have a number of 2024 milestones coming up, both across clinical and preclinical assets, which have the potential to drive significant value generation. We also have the ambition of generating business development income in 2024 equal to our operational cash burn of $14 million. This would be the first year that we would be self-funding from an operational cash burn point of view. And then lastly, MSD, or U.S. Merck, is our single largest shareholder with around a 15% equity stake.
A few words about the capital structure: as Alex also said, we are listed at NASDAQ under the ticker EVAX, share price around $4, and market cap just above $22 million. So that was a very brief introduction about Evaxion. Let's then zoom in on our strategy. What is the Evaxion strategy about? The core, the core of our strategy, that's our AI- Immunology platform. To make it simple, it's about being able to decode the disease. It's about being able to decode the immune response. And then it's about being able to design the vaccine. In reality, of course, much more advanced than that, but it is about those three elements. What our platform does is it uses advanced AI machine learning to enable this. We can design both personalized and precision vaccine candidates. We have the model currently trained in cancer and infectious diseases.
What is important, as you'll also see shortly, is that it can be used in other areas, due to this unique modular architecture. Then, we have a potential for generating a new target in just 24 hours, which is, of course, a super important value proposition towards potential partners. And worth mentioning here also is the fact that it is clinically validated. So that's about AI-Immunology. That's the core of our strategy. What's also important and which links back into the fact that we started out in 2008 as an AI-focused company is the fact that we have built a very strong multidisciplinary capability set around our AI-Immunology platform, starting with disease biology over the target discovery into the vaccine design, preclinical CMC, clinical translational medicine.
This unique multidisciplinary capability set enables us to do quick learning iterations, combined with the fact that we have a state-of-the-art lab here at our site in Denmark and also an animal facility. This means that we can, whenever our AI model makes a prediction, we can go into the lab, we can design the vaccine, we can go into the animal facility, test out the vaccine, and apply these iterative learning loops. This, this does mean that, we have a platform which is significantly more advanced due to these continuous iterative learning loops. We can, on an ongoing basis, expand data sets with our priority data, and we can also do very rapid predictions or validations of our AI predictions. This, having full control of the process from idea to validation, that is something which allows us to swiftly expand our pipeline.
And if you look at the right-hand side here, you can see that this also means compared to many of the newer companies out there, mainly using retrospective data, then our platform is a much more advanced stage in terms of value generation. So AI-Immunology being the core of our strategy, we have built a multidisciplinary capability set around it, combined with our state-of-the-art lab and animal facility, allows us to do these iterative learning loops. So how does that translate into our strategy? This is depicting our strategy in one slide. We have what we call a three-pronged business model, which is based upon AI-Immunology. That's the core of the strategy. And the three prongs: that's targets, its pipeline, and its responders.
For the target piece, that's pursuing value realization via a multi-partner approach, focusing either on single or multiple, vaccine target discovery, design, and development agreements. And, the vaccine discovery and development agreement we have with MSD, or U.S. Merck, that's a good example of what we want to do here: teaming up with pharma, partnering around discovering novel vaccine candidates, and bringing them forward in a collaboration. Pipeline: that's around bringing forward select high-value programs on our own, bringing these programs to a major value inflection point, whereafter we will be pursuing outlicensing. And of course, here EVX-01, our personalized cancer vaccine in phase II in metastatic melanoma, is a good example of that. The final piece of our strategy: that's what we call responders.
That is, in reality, taking the data insights, the predictive capabilities we have from our AI-Immunology platform, utilizing that in a slightly different context than bringing forward assets. Here we are focusing on harnessing these capabilities to develop responder models. The first responder model we have developed is a model which is capable of predicting who are the patients that will not respond to a checkpoint inhibitor therapy. Checkpoint inhibitor, of course, gold standard within immunotherapy of cancer. This year alone, it's going to be a $54 billion market effective therapy, but only in a subset of patients.
So if we upfront can be able to predict this patient is not going to respond to checkpoint inhibitor therapy, get the patient onto a new therapy quickly, that will help, of course, the clinical outcome of the patients, but it will also, importantly, help us address the growing healthcare burden in society so you don't spend several months on a drug which is not going to work anyhow. Here we just presented proof of principle for our checkpoint inhibitor responder model towards the end of 2023. Our strategy: three-pronged business model based upon AI- Immunology at its core, and then a three-pronged, three-pronged targets pipeline and responders, and pursuing value realization in a multi-partner approach.
And I think it's also fair to say that, if we look at what we have generated based upon our AI-Immunology platform, we have a broad and exciting pipeline which really talks to the performance and scalability of the platform. Most advanced is our EVX-01, which I already talked about. In phase II development, we have a number of other cancer vaccines, both personalized but also working on a novel precision-based cancer vaccine concept which we're aiming at bringing to preclinical proof concept this year. Within the infectious disease area, we have a preclinical but highly interesting pipeline addressing a number of both bacterial and viral diseases with high unmet need and where no vaccines are available today. Most progressed is our Staph aureus vaccine candidate which is in late preclinical development.
And here you'll also see the vaccine developer agreement we have with MSD, which we gave an update on some months back where we have successfully completed the first couple of phases of this collaboration. So a broad pipeline speaking to the performance and scalability of our platform. Looking back over the past months here, I think what we have achieved clearly confirms that we are on the right path with our strategy execution. In third quarter last year, we did release the initial encouraging phase II data on our EVX-01, which is what makes us excited about the one-year data readout we'll be getting in Q3 this year. We also initiated a collaboration with Afrigen Biologics around developing an mRNA-based version of our gonorrhea asset. And then, as I talked about, proof of principle for our responder model and initiation of our precision vaccine candidate.
The MSD vaccine collaboration completion of the initial stage is here. And in parallel to that, we have raised funds in a couple of rounds, each of these rounds with participation of MSD or U.S. Merck, which now has made MSD our single biggest shareholder with around 15% of the company. So a strong validation of their belief in our platform, our competencies, both having them as our largest shareholder and as an important collaborator for bringing forward novel vaccine concepts. Just quickly touching upon the AI-Immunology platform. What is that about? I already said in reality it may sound simple. It's about disease decoding. It's about immune response decoding. And then it's about vaccine design. In practice, of course, it's much more complicated than that, but what it does allow for fast and effective vaccine target discovery, design, and development.
What is important to understand is that we have this quite unique modular buildup of the platform. We have a number of building blocks which we can combine in different ways to give the desired outcome. This also means that, there's a high degree of scalability and that it's easy to adapt and tailor our platform and our AI models to what we want to achieve. Here you see, the building blocks we have, which we have used to create five unique AI models. And those five models are here: PIONEER, ObsERV for cancer, RAVEN, EDEN for infectious diseases, and AI-Deep for our responder efforts.
I'm not going to go into detail with this, but it's just important to understand that even though five models might sound like a lot, it's all based upon the same building blocks which we combine in unique ways to give the desired outcome. This also means that when we optimize one of the building blocks, it will have a benefit across all the different models where this building block is used and hence amplifying the performance of our AI-Immunology platform. Finally, on the platform, this building block architecture allows scaling to other therapeutic areas. I think it's clear right now, significant unmet needs remain within cancer and infectious diseases. However, we could easily scale it to new therapeutic areas, be that autoimmune diseases, be that allergies, and hence this is an important enabler of long-term growth opportunities for Evaxion. Going from the platform into our pipeline.
I already touched upon this. What I'm just going to do here is just spend a little bit of time on our EVX-01, which is our lead asset, and give you a bit of insight into the clinical data here. What you see on the slide here, that's the clinical data from our phase I/II trial which we published last year. In total, we had 12 patients. Eight showed an objective response to the treatment. That means an overall response rate, objective response rate, of 67%, which compared to, for instance, checkpoint inhibitor therapy is very high. Also important, we had two complete responders. So even though this was primarily designed for safety, we did see from a clinical outcome point of view a highly encouraging result. Also important is proof that the EVX-01 was safe, well tolerated, and we only saw grade one to two adverse events.
The final thing that's important, because this is a personalized cancer vaccine where we are designing a unique vaccine for each patient, we were actually capable of effectively manufacturing the vaccine for each patient in six to two weeks. So even though you are developing a specific vaccine for a patient, with our supply chain setup, we were capable of consistently getting the vaccines to the patients on time. This is another cut on the data from the EVX-01 phase I/II trial. What you see here in the slide is two cohorts. The blue cohort, that's the patients where our AI model predicted that the neo antigens or the targets used in those vaccines are of high quality. The red one is where our model predicted that the targets were of lower quality. Not every tumor has high-quality targets.
So some will have an opportunity for designing a better vaccine because there are many high-quality targets. Others, there are fewer high-quality targets. And what we see here is when our model says, "These are high-quality targets," then we actually see a statistically significant longer overall progression-free survival. And that means that the predictive capabilities of our AI platform have been validated clinically here when the model says, "These are high-quality targets," the patient also survives longer in this clinical setting. And I think that is also quite unique that we have this clinical validation of the predictive capabilities of our model. Finally, on EVX-01, now we are in phase II currently, enrolling patients in Australia and Europe, and we are having the interim readout in Q4 2023 and are looking very much forward to that.
So with that, I just want to sum up and zoom in on some of the milestones coming up ahead. We already, in the beginning of Q1, early April, announced the conclusion of a final MTA study with a potential partner on our Staph aureus vaccine. Highly encouraging data because this was data in large non-rodent animals which showed very strong protection of our Staph aureus vaccine candidate, and that serves very well, looks very well for a clinical continuation of the development of such a vaccine. Then we are launching an upgraded model of our EDEN model mid this year. We are expecting the preclinical proof of concept on the mRNA-based version of our gonorrhea vaccine which we are developing together with Afrigen Biologics. EVX-01 phase II, one-year readout, I think I already mentioned that a few times.
Then, we are also going to conclude on the target discovery and validation work which we have in collaboration with Merck in the second half. Also, important preclinical proof of concept, we are aiming at obtaining that for our precision cancer vaccine concept in the second half as well. Then finally, as I also mentioned in the beginning, our ambition is to generate business development income for the full year which equals our cash burn of $14 million. With that, I'm not going to go through this slide again but just say that we are a uniquely positioned TechBio with a clinical phase II asset and a very strong pioneering and clinically validated AI platform for vaccine discovery, design, and development.
Our potential has been validated by both the commercial or research partnership we have with Merck and the fact that they are our largest shareholder with around 15% of the company. So with that, Alex, back to you.
Thank you, Christian. Very exciting. At this time, I'll remind folks that they can submit questions using the Zoom Q&A interface at the bottom of their screen. But maybe we can just start things off. You know, you've mentioned, your collaboration with MSD and Merck. Could you tell us, you know, just a bit more about that and how it aligns with your broader partnership commercialization strategy?
Yeah, no, I'd be happy to, Alex. And, I mean, this aligns perfectly with one of the three prongs in our business model, right?
The one around targets where we are aiming at teaming up with pharma biotech partners with the objective of deploying our unique target discovery capabilities which we have with AI-Immunology to discover novel targets and also using the AI-Immunology capabilities to design the vaccine. And that's exactly what we have been doing during the first couple of phases here with Merck where we did first discover the relevant targets, then we have been designing the vaccine, and now we are testing it out in a preclinical setting. And then, I mean, that's the target prong. And then, of course, we are also looking at potential partnering of some of the pipeline assets that we have been bringing forward, both from clinical but also from a preclinical point of view.
And, that's where this multi-partner approach is an important element in the value realization of our strategy. We do not intend to bring an oncology vaccine to the market ourselves but will be teaming up with partners who have the commercial capabilities to make this a success.
Great context. Thank you. And, I know you just showed us your milestones, some of the upcoming milestones. Could you talk about, you know, which asset, you know, you see coming to market first? And do you anticipate a European or FDA approval first?
I think that would all depend upon how a partner is going to prioritize the development.
I have said part of our focus on the platform and bringing forward assets into early clinical development also means that, we are not going to do the large-scale phase III trials ourselves. So that's something that would be decided in combination with a partner. But of course, it's clear, I mean, the U.S. market is an important market, and that would be a natural priority. And we also have the Fast Track designation for EVX-01 in the U.S., giving opportunities there.
That makes sense. Another question that we just got is, could you talk a little bit more about your role once an asset reaches the clinical stage? You know, what are some of the milestones and typical timeline associated with that?
Yeah, I mean, of course, it again, it depends whether we are talking about cancer or whether we're talking about infectious diseases, right? I mean, we from a competency point of view, then, as I talked about, our multidisciplinary capabilities also means we have the clinical development competences for doing the early clinical development. That's where we can support a partner. You say if we look at the phase II trial from EVX-01, then you see the timelines here. We had the first patient first visit in September 2022, and then this year in Q3 2024, we will be having the one-year readout. So that's to give a little bit of insight into the timelines of such a phase II trial.
Makes sense. Thank you.
We have one minute left, so I just kind of wanted to zoom out and ask you if you could sum up the value proposition for investors who may be looking, you know, across AI and drug and vaccine development or more broadly, you know, in immunology.
Yeah, I'd be happy to. I mean, I think our value proposition is fairly simple: that we do have a clinically validated AI platform for fast and effective target discovery, design, and development within cancer and infectious diseases. And this platform has been continuously developed and expanded with proprietary data set throughout the past many years.
And now we also, on top of that, have the external validation via the partnership with Merck on the design and development of a novel vaccine, as well as, of course, the fact that they are as our largest shareholder. And on top of that, quite a number of important milestones this year, including the one-year readout of EVX-01 phase II, which is, of course, going to be an important event for us. But also from a, say, future asset point of view, getting the preclinical proof-of-concept for a precision-based breast cancer vaccine concept, which opens a totally new commercial opportunity in terms of addressing cancers you cannot address with traditional immunotherapy today. That's going to be important.
And then the fact that we have a strong focus on entering into partnerships, and of course, we'll update on that as discussions with potential partners are progressing into tangible agreements.
Great. Yeah, very very helpful context. And with that, we are at time. So, Christian, I'd like to thank you for sharing the Evaxion story with us, and I'd also like to thank everybody listening for spending time with us today.
Thank you, Alex. It's my pleasure. Thanks for having me here.
Thank you.