Evaxion at Jones Conference: AI-Driven Drug Discovery in Focus

On Wednesday, 09 April 2025, Evaxion Biotech AS (NASDAQ: EVAX) showcased its innovative AI-driven approach to drug discovery at the Jones Healthcare and Technology Innovation Conference 2025. The discussion, led by CEO Christian Kansrup, highlighted both the potential and challenges of using artificial intelligence in precision medicine, particularly for cancer and infectious diseases.

Key Takeaways

• Evaxion's AI platform significantly accelerates drug discovery, reducing timelines from years to days.
• Collaboration with Merck includes a 20% ownership stake and potential for significant financial gains.
• EVX-one, a lead asset, shows promising results in Phase II trials for advanced melanoma.
• Upcoming presentations and FDA discussions signal strategic growth and regulatory progress.
• The company emphasizes partnerships for later-stage trials and commercialization.

Financial Results

• Evaxion received a $3.2 million upfront payment from Merck, with potential for an additional $10 million if options are exercised.
• Merck's 20% stake in Evaxion underscores its financial commitment and interest in the AI platform.

Operational Updates

• The AI platform can identify novel entities for infectious diseases in just 24 hours, a significant improvement over traditional methods.
• The Phase II trial for EVX-one is extended to further assess immune response durability.
• Current trial sites are located in Europe and Australia, with ongoing FDA discussions for a pivotal U.S. trial.

Future Outlook

• Evaxion plans to focus on preclinical and early clinical development, leveraging its AI platform.
• Strategic partnerships are sought for Phase III trials and commercialization.
• An upcoming presentation at AACR will include biomarker data and neoantigen hit rates.
• Expansion into other cancer indications beyond melanoma is planned with partners.

Q&A Highlights

• EVX-one's differentiation lies in its high response rate and immune response elicitation in trials.
• The company is considering various solid tumor indications, including lung cancer, for future development.
• The goal remains to use the AI platform for drug development across different indications without selling the technology.

Evaxion's strategic focus on AI-driven drug discovery positions it as a transformative player in the biotechnology sector. Readers interested in a deeper dive can refer to the full transcript below.

Full transcript - Jones Healthcare and Technology Innovation Conference 2025:

Shomitra, Head of Healthcare Research, Jones: Fireside chat with Evaxion. We have I'm Shomitra, head of health care research at Jones. And with us today, we have CEO of Evaxion, Christian Kansrup. This is a very appropriate venue for AI driven, and we have a lot of talk of AI today. So, Christian, Evaxion is developing vaccine using the AI platform.

And as we all are learning about the incorporation of AI for drug discovery, Could you just briefly tell us about Evaxion and what is your focus?

Christian Kansrup, CEO, Evaxion: No. I'll be happy to. And first of all, great to be here. Thanks a lot for the invitation. No.

In in essence, what Evaxion does is we are an AI driven company focusing on developing precision medicines. We have an AI platform, which we call AI immunology, which we use for discovering and developing novel candidates within cancer and infectious diseases. And I think an interesting thing about Evaction is we were actually founded back in 02/2008 as an AI first company. The two, cofounders, they wanted to use machine learning to decode the human immune system to develop novel medicines. And today, we have evolved into a clinical stage tech bio company with a broad pipeline.

So we heard about the tech bio concept from the keynote speaker this That is actually what we have been positioning ourselves as for a number of years. So I think the fact that we were founded in 02/2008 also means that we have had a significant head start compared to many of the newer AI companies out there today, allowing us both to develop our platform, but also importantly validate it.

Shomitra, Head of Healthcare Research, Jones: So one other question which always comes up and essentially, is a black box Yeah. To most people. We had, you know, twenty, thirty plus years of high high throughput way of looking for either designing peptide or looking for structures and small molecules and trying to identify 10,000, bring it down to, like, 20, then bring it up to, like, 10 in the animal and one to the clinic. Yeah. Does the AI aspect of it accelerates the process?

Where where is the poll?

Christian Kansrup, CEO, Evaxion: No. First of all, this is about the black box. I would say that we also hear when we are discussing with potential partners. I mean, it is a black box. How do we know it works?

But I would say very clearly that it is clear that AI has transformed drug discovery both in terms of drastically speeding up the process, also improving the precision of how we discover and develop new candidates. So instead of relying on, you can say, time consuming lab work, we now have a significantly different speed compared to what we had previously. And I would say the difference compared to to the high throughput is a much higher sensitivity we see with and specificity we see with AI approach to discovering novel drugs.

Shomitra, Head of Healthcare Research, Jones: If you have to quantitate, like, the time saved versus prior approaches, new antigen identification, it was, like I think if I have to guess, like, two and a half years Yeah. Something like that, how much has it reduced down to? Is it just a pace of it, or do you see the quality of the antigens it's predicting are more immunogenic? Where do you see it?

Christian Kansrup, CEO, Evaxion: Well, it's actually both. I would say, now now if we look at the the neoantigens, think that's probably around two point five years you're saving. Also, if we look at infectious diseases where you have a proven approach like reverse vaccinology, which typically takes three years, we can deploy our AI platform. And just in twenty four hours, we can get a ranked list of novel entities.

Shomitra, Head of Healthcare Research, Jones: Within twenty four hours, you'll get it. Wow.

Christian Kansrup, CEO, Evaxion: And of course, that's a significant, time saving. But on top of that, we also get this ranked list of potential new targets, I. E. We can just select the top ranked ones and hence in terms of testing, we can go by by testing significantly fewer targets than what you would have to do if you were doing it in a traditional way.

Shomitra, Head of Healthcare Research, Jones: Do you think there is a marked difference? Because, neoantigens are hard to predict Yeah. Versus, bacterial, viral. They're almost epitopes are known for a long time now. These are the highest immunogenic Yeah.

Epitopes because from the sequencing and all. Do you see this is more effective in predicting the neoantigen side versus bacterial because only a few things

Christian Kansrup, CEO, Evaxion: you can do there. Well, I would say, of course, given that if you look at the tumor mutation, the neoantigens are patient specific. Right? That also, of course, means that you cannot have a large database where you can use that to predict the right, neoantigens. So you need to do that on a patient by patient basis, which of course require a swift and rapid approach to do that in an effective way.

So that's where the AI approach really makes a difference. I would say, also for the infectious diseases, it is clear that not only they increase the speed, but it also allows us to discover novel targets that you have not been capable of discovering previously. Take, for instance, our EV XB2, which is a gonorrhea candidate. It is still in preclinical development, though. But now the field have for the past fifty years been trying to come up with an effective, vaccine against gonorrhea.

And here we had the have in in preclinical models shown that we can, 50 different gonorrhea strains completely eradicate the the the bacteria.

Shomitra, Head of Healthcare Research, Jones: So it picks up the those glycolipids of the gram positive? So okay. So I didn't know that. So that's that's really interesting. Talk to us about a little bit on the training the AI Yeah.

Software itself. Like, the the database when you train, do you have you propriety developed it, or you took it from other institutions, cancer research?

Christian Kansrup, CEO, Evaxion: It's it's a mix of different things. We have, I would say, three sets of data. We have, what I would say, proprietary data, which are data we have been generating ourselves, both preclinical data, but also we have been conducting three different clinical trials with our personalized cancer vaccines, generating a lot of data which we have been feeding into the model. So that's one set of data. Then we have, semi proprietary data where we are collaborating with hospitals, universities in order to get access to data which are not in the public domain.

And then finally, of course, we are using publicly available data. But I would say one thing that's important also is it's not just about the quantity of data, but it's very much so about the quality of data as well. And and that's where having this mix of of different datasets which you can use to further refine and enhance your platform is very important.

Shomitra, Head of Healthcare Research, Jones: So this might be a little unfair question to you, but, where is there room for improvement on your database itself? And if we have to compare yours versus, let's say, Moderna's on BioNTech's Yeah. It's just that they have a larger access to a larger patient sample, they have better trained model, or is it like that is not where the delta lies, that delta lies in something else?

Christian Kansrup, CEO, Evaxion: Well, I would actually claim if you if you look at data that's available that we have a much higher predictive ability of our model than both, Moderna and BioNTech. In our EVX-one Phase II trial, we published the one year data in, the fall of last year. There we saw that 79% of the new antigens were eliciting an immune response. If you look at Moderna, they have not, yet published data from their completed Phase II trial with their personalized cancer vaccine, but they have published, I think it was Nature, a data on their Phase I trial, which is a basket trial, where they showed that only 25% of the new antigens elicited immune response. And that's where we have, published last year that seventy nine percent of the identified new antigens actually elicit an immune response.

BioNTech, they showed in, their Phase 1b trial, that was it eight out of sixteen, patients saw an immune response. Hence, it points at of course, it's always difficult making these cross trial comparisons, but it do point at the predictive capabilities of our AI technology platform is very high. And that also comes from this continuous refinement. In the Phase I trial with our EBX-one, we saw that fifty eight percent of the new antigens elicited an immune response. And by refining and further training the model, we got that to 79% in the data we released last year.

Shomitra, Head of Healthcare Research, Jones: Probably this speaks to the fact that you guys just did a big deal with Mark, and they took, like, 20% position in the company. Give us a little background on how that conversation went and,

Christian Kansrup, CEO, Evaxion: like Yeah.

Shomitra, Head of Healthcare Research, Jones: What is their main focus as they are? Because, you know, they are Yeah. One of the biggest pharma in the world. Yeah.

Christian Kansrup, CEO, Evaxion: No. I mean, we we have a we have multiple collaborations with Merck. And it's true, they are our biggest shareholder. They have a 20% ownership of the company. But we also, in September, entered into a large optional licensing agreement covering two of our infectious disease candidates.

And that actually started out in, that was in, 'twenty three where we were approached by Merck saying, Hey, guys. We would really like to utilize your AI technology platform to develop a novel bacterial vaccine candidate within an area where there are no vaccines available today, but a high unmet need. It has not been disclosed what the pathogen is, but, it's one where there are no vaccine available today. That collaboration we started in September 2023. Then they invested into us first time in December 2023.

And then they have actually participated in our three last financing rounds. And then in September, we entered into an optional license agreement both around the original asset, but also they actually included our EBXB2, our gonorrhea candidate in that collaboration. So very pleased around having a world leader in Vexa in development and commercialization. They're not only partnering around one asset but actually two assets. On top of that, taking a 20% ownership stake in the company.

So very pleased with that collaboration. And I think their interest was driven by exactly the fact that we can discover novel antigens, which you can't discover with traditional methods. We can also do it in a fast way. So, it was the predictive capabilities of the platform that was attracting, the interest. Then we actually also, we have a supply agreement with Merck there supplying Keytruda for our EBX-one personalized, cancer vaccine trial, but that's just a supply agreement.

It's much broader, the collaboration around the infectious disease side of things.

Shomitra, Head of Healthcare Research, Jones: And Merck has an option trigger second half of this year on

Christian Kansrup, CEO, Evaxion: the panel Yes. Yeah. The agreement we entered into last year, we got 3,200,000.0 upfront. And if they exercise the option to both candidates in the second half of this year, we are set to get an additional 10,000,000 plus future milestones and and royalties, of course.

Shomitra, Head of Healthcare Research, Jones: This is what I'm trying to understand is, like, why isn't Mark developing their own internally, I just like every large pharma is doing? And second is, how deep is your relationship? Can you because they probably have one of the largest cancer tissue repository of the data bank. Can you train your model on their dataset, and do you have that kind of agreement?

Christian Kansrup, CEO, Evaxion: That's not part of the agreement. The the agreement now is focusing on the, on the infectious disease, candidates that we have in scope. And then you can say, why aren't they just doing it themselves? We need to remember we have actually been spending fifteen years in terms of developing, developing our platform and also, you can say, maturing it and constantly refining it to increase the predictive capabilities. So it is something that takes a lot of time.

And I think now I've been working with Big Pharma myself for many years. I think focus from an AI point of view in pharma is probably more into the whole clinical trial area, how do you utilize AI to optimize those processes rather than it's the early drug discovery.

Shomitra, Head of Healthcare Research, Jones: Right. I understand. Your lead acid EVX one in phase two trial in advanced melanoma in combo with Keytruda. Do you get the question where you have to really show how it is differentiated versus any other personal vaccine? Is it just the response rate, or is it something else you see that looks better versus other?

Christian Kansrup, CEO, Evaxion: Well, there's a lot of focus on on, of course, the response rate. That that's, one thing. And I am pleased also to say that in the, in the phase two one year data we presented last year, we actually showed a sixty nine percent overall response rate. And if you compare that to the KEYNOTE-six, the KEYTRUDA registrational trial, there they showed a thirty three percent overall response rate. But there is also a lot of focus on how many of the new antigens are actually listing an immune response, I.

E. The seventy nine percent. And then there's focus on, you can say, the durability of the response. And that's also why we actually just, early on this year announced that we are extending the trial with another year, not because we haven't seen good data on the contrary, but because we have seen so exciting data and are curious to see how long is, the durability of the the immune response actually.

Shomitra, Head of Healthcare Research, Jones: The other hot button issue is the selecting the indication itself. Yeah. Melanoma for a while has turned into a proof of concept indication Yeah. Versus you have to go show it in in lung, in CRC if if if you can, or some other indication that makes the model work. Yeah.

What how are you thinking?

Christian Kansrup, CEO, Evaxion: Well, I I I fully agree with you that melanoma, that was chosen due to a number of different reasons. First of all, it was actually developed as part of a consortium. The original thought was around a consortium with the a Danish research institute. And that's where you can say focus was naturally on melanoma also because you have a very high tumor mutational burden here, hence a lot of new antigens to potential new antigens to select from. But it's also clear that the whole concept has broad applicability in other solid tumors.

I think right now our focus is on establishing the clear proof of concept in melanoma. And then, our focus is also not on the later stage, large scale Phase III trials. We will do that together with a partner. Hence, it will be also up for discussion with a potential partner, which is the next indication you want to bring it into. But it has a broad potential in, look across solid tumors where you have high tumor mutational burdens.

Shomitra, Head of Healthcare Research, Jones: What comes to mind first?

Christian Kansrup, CEO, Evaxion: Well, I think we have been looking at a lot of different things, but we have we have not really made a decision yet because, again, we we can have our own own picks. But, I mean, we I think we have also seen some of the indications are more challenging than others. So it needs

Shomitra, Head of Healthcare Research, Jones: to DRC, you have quite a pleiotropic situation, CRC is really hard to correct.

Christian Kansrup, CEO, Evaxion: Yeah. Yeah. No. The other

Shomitra, Head of Healthcare Research, Jones: hand, lung, you have a lot of mutations, but you have targeted medicine for each of those.

Christian Kansrup, CEO, Evaxion: So No. We we have we have actually been discussing, long quite a lot. But it it even though you have a lot of mutations, it also comes with other other challenges. So I think for now, focus is on on continued generation of great data within the current Phase II trial. And then in parallel with that, be preparing for taking that discussion with a potential partner.

And we are, of course, also looking at what's the clinical path forward from completion of the phase two trial, how do we, as quickly as possible, get to a potential registration.

Shomitra, Head of Healthcare Research, Jones: So what's your goal as a for the valuation of the company? Is it proved prove the technology in one indication, like, let's say melanoma, works well, is applicable, will get adopted, long duration of response, and then sell the technology platform? Or do you wanna use the platform and become a therapeutic company and just keep developing drugs for different indications?

Christian Kansrup, CEO, Evaxion: More the latter. I would say we do not have the ambition of becoming a commercial scale, company. We have the ambition of doing what we do best, which is deploying the AI immunology platform, doing the preclinical and early clinical development, and then, of course, bringing novel concepts to the market. We are also within the cancer era, we are working on a precision cancer vaccine concept where we have been discovering a novel source of potential cancer targets, these endogenous retroviral, where we are actually having discovered that these are shared across patients. Hence, we can make precision medicines for a group of patients.

And the advantage here is that is actually found also in cancer type where low tumor mutational burden, so hence you have the opportunity of expanding the use of immunotherapy.

Shomitra, Head of Healthcare Research, Jones: AACR, you are presenting some data?

Christian Kansrup, CEO, Evaxion: Yes.

Shomitra, Head of Healthcare Research, Jones: What should we expect? It's more biomarker?

Christian Kansrup, CEO, Evaxion: It's more biomarker. It's a we have been doing a lot of immune, data analysis. Among us, we have had further data, of course. So the we will be presented updated data on, on the hit rate for the new antigens. And then on top of that, we have been doing a lot of exciting, further immune data analysis, which we will be presenting.

So we are looking very much forward to, to that. In a couple of few weeks.

Shomitra, Head of Healthcare Research, Jones: Yeah. Then you have also guided that the two year readout for the phase two is gonna come out

Christian Kansrup, CEO, Evaxion: Yeah.

Shomitra, Head of Healthcare Research, Jones: Second half of this year. So what should we expect as the the benchmark, which gives you confidence, you know, we we should push it towards a pivotal trial?

Christian Kansrup, CEO, Evaxion: Well, I would say given the data that we have seen so far, we already have lot of confidence in EBX-one. Of course, what's going to be important is to see the durability of the response. And then, of course, if we can continue to see an even further increase in the overall response rate and also looking at, you can say, the number of converters and comparing that to the checkpoint inhibitor data in order to further solidify that the strong data we are seeing are generated by EBX-one on top of the checkpoint inhibitor. That's, of course, always a challenge when you have a single arm study, what's driving the good clinical response. But that's what we are looking forward to seeing when we get to see the phase two, two year phase two data, which is coming out in in the second half of, this year.

Shomitra, Head of Healthcare Research, Jones: So for context and response rate wise, ketradiolone gives you around 3033% response rate, and you are seeing seventy nine percent response rate?

Christian Kansrup, CEO, Evaxion: It was sixty six nine. Yeah. Sixty nine.

Shomitra, Head of Healthcare Research, Jones: Yeah. 69% response rate. And in terms of PFS, is it Ketra only gives you, like, five months, five and a half months? Yeah. Something like that.

So we wanna see anything above that Yeah. To be additive. And remind me also on in terms of the clinical trial sites. Are you primarily in Europe or you're

Christian Kansrup, CEO, Evaxion: It's conducted in in in Europe and in Australia. So, we have, we have, two sites in Europe and, two sites in in Australia. Yeah.

Shomitra, Head of Healthcare Research, Jones: What's the plan of expanding it to coming to U. S. Also get the IND and

Christian Kansrup, CEO, Evaxion: Yeah. We actually have fast track designation in in The U. S. So we will be, now entertaining discussions with the with the FDA as well in in order to guide the the design of, how would a pivotal trial, look. So it would be, so most likely after we get the second half long term data, then those further conversations will start.

Well, we are preparing the conversations now also because, I mean, our intention, as I said, is not to bring it into a pivotal trial ourselves but to do so with a partner. And, of course, coming into partnering discussions with a clear view as to what could be feasible from a clinical trial point of view is a strong advantage.

Shomitra, Head of Healthcare Research, Jones: This is great. If you have any concluding remarks. No.

Christian Kansrup, CEO, Evaxion: I would just say that, I mean, it is clear that the AI and use of AI in drug discovery and development really is transforming, the way we develop novel medicines. And I think one thing is, of course, speed. But more important so is that it allows us to do things that we couldn't do before. I mean, having a seventy nine percent hit rate in terms of selection of new antigens in a personalized cancer vaccine. Those are amazing data, which really gives me the hope that we have the opportunity of doing something about the still way too high unmet need within cancer.

Also, infectious diseases, having the ability of being able to bring novel, vaccines to the market where the field have tried for many years to to discover vaccine candidates. And combining that with the ever growing resistance towards antibiotics, it's clear there is a significant unmet need here and, that we have the opportunity of addressing via the use of AI. So it is truly transforming the way we we develop new medicines. So I'm very excited about that.

Shomitra, Head of Healthcare Research, Jones: Thank you so much for coming in. Really, good luck. Thank you. Great to here. Thank you.

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