Evaxion Study update

I'm Birgitte Rønø, CSO and COO at Evaxion. On behalf of the entire Evaxion team, I would like to welcome you to this exciting webinar focusing on our EVX-01 program in advanced melanoma and the phase II result presented on Saturday at the ESMO Annual Congress. I'm delighted to have Professor Adnan Khattak with us today. He led the EVX-01 phase II study at the clinical site in Perth, Australia, and he will be presenting the data from the EVX-01 study. Professor Khattak is a medical oncologist at Hollywood Private Hospital in Perth and is a key investigator on many international cancer trials assessing novel cancer immunotherapies, including personalized cancer vaccines. Before we start, just a short reminder, today's presentation may contain forward-looking statements, which are statements about the future. Actual results may differ materially from them. Here is what we'll cover today.

First, I'll introduce Evaxion, the EVX-01 concept, and the results from the EVX-01 phase I study conducted prior to the phase II study. Second, Professor Khattak will introduce us to the unmet medical need in advanced melanoma, and then he will present the data from the EVX-01 study. Then, in the end, we'll open the floor for your questions. You can type them into the Teams chat at any time, and we will answer as many of your questions as possible at the end of the session. Yes. First, an introduction to EVX-01 and the key data from the EVX-01 phase I study. Evaxion was founded in 2008 with one aim, to decode the immune system with AI to address serious unmet medical needs.

We are based in Denmark, and our team of more than 40 experts cover the whole value chain from target discovery to clinical development. Today, Evaxion is a pioneering clinical validated TechBio company. This means that we work in the intersection of life sciences and advanced data technology. AI, machine learning, and computation are deeply built into how we discover and develop novel therapies. Our AI platform is called AI-Immunology, and it is an integrated set of models for rapid, high-quality target discovery, drug design, and development. We are focusing on antigen discovery and product development in cancer and infectious diseases, and we recently expanded into autoimmune diseases. We have been listed on the Nasdaq Capital Market since 2021 under the ticker EVAX. AI-Immunology allows for rapid development of product candidates, with all of our pipeline candidates designed with AI-Immunology.

The focus of today's webinar is on our EVX-01 program, EVX-01, and the phase II data we presented at ESMO. EVX-01 is a personalized cancer vaccine, and we design a unique vaccine for every single patient in our trials. It is based on up to 10 different targets, neoantigens that arise from mutations specific to the patient's tumor. These neoantigens are selected by our AI-Immunology platform, and the vaccine is a peptide liposomal formulation. Let me show you what is behind our AI-Immunology platform. AI-Immunology has a unique building block architecture. At its core are three engines. The first is disease decoding, which identifies key pathogenic drivers in a given disease. The second is immune response decoding, which shows how the immune system sees and responds to potential targets.

The third is a vaccine design engine, which we use to design the product candidates. We can apply the platform across disease areas, and currently, we work within cancer, infectious disease, and autoimmune diseases. EVX-01 is one of the cancer applications of this architecture. AI on its own does not give you a therapy, and that is why we have built a multidisciplinary R&D capabilities around the AI-Immunology platform. These different capabilities include disease biology, target discovery, and further also preclinical development, CMC, and clinical development. Now to the concept behind EVX-01. EVX-01 is a personalized cancer vaccine targeting multiple private neoantigens. Neoantigens are ideal cancer vaccine targets as they arise from cancer-specific DNA mutations exclusively found in tumors and absent from normal tissue. They trigger strong, highly tumor-specific immune responses, and they work well together with current cancer immunotherapies.

AI-Immunology models the neoantigen process inside the cancer cells. This starts with identifying these cancer-specific mutations. Then it looks at the expression and translation of these sequences. It goes on to look at presentation on MHC molecule and the T-cell responses, and further into the clonality of these neoantigens. The AI-Immunology platform is part of a larger process that runs from mining the patient's tumor fingerprints to designing a personalized treatment. For every patient enrolled in our trial, we collect a tumor biopsy and a normal blood sample, and then we sequence the DNA and the RNA. This information is fed into our AI-Immunology platform, which then identifies and ranks the neoantigen according to their predicted likelihood of inducing a tumor-specific T-cell response.

The prediction only takes 24 hours, and AI-Immunology currently predicts immunogenic neoantigens with an 89% precision, and we will come back to this target precision rate later in the presentation. The vaccine is then manufactured and administered to the patients in combination with checkpoint inhibitors. The turnaround time from biopsy to vaccine administration is about 7 weeks. We tested this concept first in a phase I study, and it enrolled patients with unresectable stage III or metastatic stage IV melanoma. In the phase I study, each patient received a vaccine of up to 10 patient-specific neoantigens, again, designed with AI-Immunology. The patients were dosed with EVX-01 to activate the T-cells together with a checkpoint inhibitor according to label. The phase I study tested three different EVX-01 dose levels. These are the key results from this phase I study.

EVX-01 was safe and well-tolerated with only grade 1 and 2 adverse events reported. 8 out of the 12 enrolled patients responded to treatment with an objective response rate of 67%. EVX-01 induced a specific immune response in all these 12 patients. We also looked into the individual ability of the neoantigens to induce a T-cell response, and we saw that we had reactivity against 53 of the 91 neoantigen analyzed across the patients, with a target precision rate of 58%. Manufacturing was efficient with a turnaround time of approximately 7 weeks. We took three learnings from this trial into phase II. We selected the highest dose level of 200 micrograms per peptide as the recommended phase II dose. We added EVX-01 boosters to sustain the T-cell level, and we improved the prediction power by updating AI-Immunology. All three shaped the phase II study.

With this introduction, I am now happy to hand over to Professor Khattak to present the EVX-01 phase II data.

Please go ahead. Thank you, Birgit.

Thank you everyone for joining online. Today, specifically talking about advanced melanoma, where the role for vaccine has been proven, but the discussion, obviously thinking ahead, can be obviously rolled out to a much broader level across other tumor types as well based on some recent data. When we talk to our patients in our clinic, our current standard of care is immune checkpoint inhibitor treatment as a single agent or as double immunotherapy in the form of ipilimumab and nivolumab combination or nivolumab and relatlimab combination. As you can see, the 5-year survival statistics, now we have got 10-year survival statistics as well, but roughly you can expect about 50% of your patient to be alive at 5-year time point despite having a diagnosis of metastatic disease. Then the problem is, what about the rest of the 50%?

If I was to see a patient in the clinic today, I can share this data with them, but I cannot tell them whether they are going to be in this 50% of patients who are likely to live, or they are going to be in those 50% that unfortunately do not benefit from checkpoint inhibitor treatment. Now, these treatments are very generic, very broad-brushed approach. If I get 10 advanced melanoma patients, my standard of care treatment options that I will discuss with them will be pretty much the same in terms of these agents that I just listed. With the unmet needs that obviously we have got a significant proportion of patients who would not benefit from our standard checkpoint inhibitor treatment, a single agent or even double agent as well, and obviously, there is significant toxicity as well.

The field in oncology moved obviously to personalized treatment, but that was primarily the personalized targeted therapy what we saw in melanoma as BRAF targeted therapy or EGFR/ALK or other targeted therapies in lung cancer. Obviously, reading in the immune system at a personalized level has always been a challenge and remains a challenge, although we have made significant advances, particularly in the last 2 to 3 years, including the data that was presented at ESMO recently. In terms of personalized treatments now, as we mentioned, how the neoantigens work, it is just like the fingerprint of cancer cell, which is unique to an individual patient's cancer that is different than any other patient on a particular clinical trial that we are enrolling on at that particular time.

These are called neoantigens, what we used to call personalized cancer vaccine, and now we call them INT, or Individualized Neoantigen Therapy. The data that was presented at ESMO from Evaxion, from the presidential session, from Moderna data, and some trial that have completed recruitment, hopefully, we will see more and more success of these new novel therapies. I will move to the next slide. In the phase II study, last year in Berlin, we presented the 2-year data, and now in Madrid, we presented the 3-year data. The objective response rate, I will discuss the design of the clinical trial in the next slide, but in summary, the objective response rate was 75%, meaning 3 out of 4 patients benefited. We enrolled 16 patients in this phase II trial.