Transgene SA (TNG) Earnings Call Transcript & Summary

Welcome to the Transgene Conference Call. Please note this conference is being recorded. [Operator Instructions]. I will now hand over to your host, Lucie Larguier, Head of Investor Relations, to begin today's conference. Thank you.

Thank you. Hello, everyone. I'm Lucie Larguier, Director of Investor Relations at Transgene. So today, we're going to present the first positive results of the clinical trials evaluating TG4050, our individualized cancer immunotherapy. With me today are Hedi Ben Brahim, CEO of Transgene; Eric Quemeneur, Chief Scientific Officer; Maud Brandely, Chief Medical Officer; and Kaidre Bendjama, Director Next-Generation Vaccine. We are honored to be joined by Prof. Christian Ottensmeier, MD, PhD, who is the Professor of Immuno-Oncology at the University of Liverpool and the Global Coordinator of the Head and Neck Trials, currently evaluating TG4050. I remind you that today's discussion contains forward-looking statements, which are subject to numerous risks and uncertainties. The presentation material is available on the Investor page of our website, transgene.fr. And if you wish to ask questions, you will need to connect to the conference call members available in the press release issued last month. I now hand over the call to Hedi Ben Brahim.

Hello, everybody. I'm very happy to be here today to share with you, with my colleagues from Transgene and Prof. Ottensmeier, our latest update regarding the results of myvac. You know it was a commitment we took at the beginning of the year, and we are very happy to be on time and to share the news. On top of that, these news are extremely interesting, very promising data that we're going to detail to you today. You know we've developed an individualized treatment that is designed for each patient based on the genetic mutation that can be found in the tumor. We start from the patient's tumor to identify the most relevant mutation to stimulate the immune system and then we design the treatment and manufacture it for injection to the patients. Beyond the scientific, technical and manufacturing process, we demonstrate with today's data that we are delivering on our commitments. So regarding the results. First, the safety of the product is good, and we have not observed any serious -- severe side effects. More importantly, our first results show on the first 6 patients, who received the treatment, that our approach is extremely powerful from an immunological point of view. We are also very proud to see the first sign of effectiveness, which makes us very optimistic for the further development of the product. I'd like to hand over to Eric Quemeneur to introduce you to myvac.

Thank you, Hedi. Before we enter into the details of the current trials, I take some minutes to recall the challenges we have addressed in the development of TG4050, and the way we have overcome them. There are 3 major scientific and technological challenges when designing a potent vaccine strategy against studying tumors. The first one is the tumor heterogeneity, and we had to deal with the genetic and filter typing diversity of the tumor and find the proper ways to design the vaccine for each single patient. The second challenge is the potency challenge. And we believe that by choosing neoantigens and selection of the MVA vector has been the solution for that. The third challenge was the pharmaceutical challenges and the ability to be organized and provide the product in due time for the good pursue of the clinical trials. I also should start this introduction by recording the overall collaboration we have had from the very beginning with academic people and we have really felt their request for innovation in the field of personalized anticancer vaccines. Maybe a few words on neoantigens that were selected as the way to match the challenges of a potent vaccine. The result from the accumulation of mutations in the genome of the tumor during the onset of the tumor problem. They will translate into abnormal protein sequences that will be expressed specifically by each tumor cells. They are largely unique for each patient and potentially very immunogenic, considering their difference to self. And of course, the challenge of the vaccine design is to select the best set of neoantigens. Our TG4050 vaccines include 30 selected neoantigens from the deep analysis of the tumor genome. The next slide will give you some more details. By sequencing the entire genome of the tumor, we can build an exhaustive and competitive vision of the tumor heterogeneity, including old mutations that might be responsible for escape to the immune system or escape to the current anticancer treatment. In our current calculation, a set of 30 new antigens is sufficient for optimal coverage of the diversity of mutations, provided we can select the best 30 sequences among the large number of mutations. In this respect, the collaboration with NEC has been instrumental, and we have used their machine learning environment and the possibility to classify and predict the most potent neoantigens to be included in the vaccine vector. In terms of the vaccine design, we have selected the MVA viral vector as the most appropriate platform to design this product for several reasons. The first one is it's very good safety and tolerability track record. I just recall you that the vaccine was used for a decade in the prophylactic campaign against small pox and also showed very remarkable properties in the design of anticancer vaccines in our experience. It is also a very important viral vector with its capability to induce a strong long-lasting immune response, generating both induction priming and antigen presentation and also its ability to boost durable and specific immune responses. And we have a very good knowledge on its structure and function relationship. We know how to engineer a very efficient antigen display system by optimizing the cloning strategy, by optimizing the way the [ neuron specific] sequences are built and the way we select the best early promoters for most efficient display to APCs. And last but not least, of course, we have a lot of experience underway to manufacture this product under GMP conditions. And I recall you that the manufacturing challenges was most of -- the most prominent one in the design of this program. The third challenge is really to deliver on time the product. And we have built a dedicated GMP facility to match the delay and cost requirements. We have worked on a target of 12 weeks between the sequencing of the tumor material and the release of the product on site, ready for injection to the patient. There were many issues that we could solve from the biology itself, the quality control and the customer chain. The shipments were also optimized, and we were in a position 6 months ago to have everything in place for the start of the clinical trials. By meeting all these challenges, we have made myvac and TG4050 a reality. It has assembled the best of our experience in vaccine design, [indiscernible] and manufacturing excellence to support the 2 clinical trials. So I will give the floor to our colleague, Christian Ottensmeier, to give a perspective from the point of view of an hospital practice practitioner.

Thank you so much. I look really quite disparate on that photograph, don't I? So thank you so much for giving me the opportunity to present. I have a long-standing relationship with Transgene, and I was part of previous studies, specifically with the [ MUC1 ] vaccine, but also more recently on the Scientific Advisory Board for one of the trials that Transgene is collaborating with. And together with Kaidre, we've had a long-standing immunological collaboration also, in which we've examined the immunobiology of delivering vaccines in an MVA context. So I think the particular paper that is referenced here is in revision, the journal of immunotherapy of cancer, really demonstrates that even for tumors with a relatively low tumor mutational burden, we can pick immune cells from the blood, determine their reactivity and show that they are reactive with the new epitopes much in the same way that we are trying to achieve here. Please move to the next slide. So the key driver for these two trials, actually, although I'm going to focus only on the head and neck cancer trial, is really to assess whether in a clinically optimal setting, where there is very little tumor burden to suppress the patient's immune response. We can achieve the elimination of minimal or microscopic residual disease that is present after resection of the tumor. And for head and neck cancer, we've picked a group of patients with a very high risk of recurrent disease. So human papillomavirus independent tumors. And within those patients, which account for the majority, we've picked again a high-risk subgroup, where we would predict that on average about 50% to 60% of patients will eventually relapse from the malignancy and die. So the design takes then advantage of our intention to understand whether we can reduce the risk of recurrence and whether we can generate early qualitative -- quantitative data for the risk reduction and use the data to power a definitive study, one. And then secondly, whether we can identify immune response to the neoepitopes in the blood of the patients after vaccination, two. And thirdly, if patients were to relapse, either independent of vaccination or having been given vaccination, whether we can understand if the vaccine has altered the immuno attack. And our argue has been as follows: Is if the immune system shapes the tumor microenvironment, then vaccination and relapse would lead to a different complexity or a different sequence of neoepitopes in the tumor at relapse. If, however, the immune system is completely irrelevant, then we would find or we would predict that there will be no meaningful changes in the mutational landscape of the patient at recurrence. So our prediction then is that the majority of patients that we vaccinate in the adjuvant setting will not relapse, because we will have removed minimal residual disease. If we are unfortunate enough that, that is the case, we will re-biopsy the patient and examine whether there is any evidence of immunological selection. And in the patients who have been randomized to the follow-up only without vaccination at recurrence, we will, again, sample the tumor and resequence, with the expectation that in the absence of immune therapy, the neoepitopes will be the same. So we would then be able to address multiple levels of outcome for this trial in a way that is really extraordinarily unusual. So the first, we would potentially have early evidence of clinical benefit and that is clearly the important thing for our patients and as well as linking immunological consequences to genomic consequences in the tumor marker environment. And I think this is enormously rich translational data set will put Transgene in an astounding place for looking at the further development of this platform. The reason why these particular neoepitopes, and if you want to move to the next slide, please, are so important is for really two reasons. One is that the neoepitopes that are delivered in the tumor are not subject to all the normal control mechanisms that would limit T-cell attack. And in the graphic on the right-hand side, we've tried to illustrate this by leading -- by ordering the likelihood of specificity versus the likelihood of immunogenicity of various categories of tumor antigens. The highest bar are antigens that are true cells, so molecules that are found in our healthy cells. The second highest hurdle are antigens that are not normally present in healthy cells, but that are deregulated or altered by the cancer process and MUC1 is one example of these. Then, the next most likely target that is going to be able to activate immune responses are viral antigens that transform the tumor. And finally, at the lowest bar and the highest chance of success are those epitopes that are being encoded in the TG4050 vaccine, with the intention of targeting neoepitopes. So we have not only a very safe and extremely immunogenic vaccine delivery strategy, but encoded therein a group of antigens that are patient-specific and therefore, very low risk in terms of toxicity, and that maps perfectly on what we've seen from the data generated so far as well as really immunogenic, and therefore, likely to confirm clinical benefit. And again, our data so far confirm the immunogenicity and at least within the data available so far the odds of recurrence seem to sit on the group of patients who have not been vaccinated, rather than patients that have been vaccinated. But of course, that will come out when the trial is fully completed. So from my expertise in immuno-oncology, I have taken several dozen early phase concept into the clinic, this is probably the single most exciting approach, mainly because the idea of encoding the antigens in a virus takes advantage of all the tools that our immune system has developed in the development of us as a species, which would make it very immunogenic. So I'm super excited about this. And with this, I would like to hand back to the Transgene team.

Thank you very much, Christian, for this convincing evidence on the medical need in head and neck cancer. And we have the same need in ovarian cancer, and just to remind you that we are targeting patients with [ new ovarian ] disease, meaning that patients who are operated for the purpose of curing the cancer and received complementary treatment, whether it is radiotherapy or chemotherapy. Unfortunately, for patients who are diagnosed at advanced stages of the cancer, the risk is very high of recurrence because we know that even though we are not able to detect any residual disease by conventional imaging or clinical procedures, actually, those patients have some residual, undetectable tumor cells, which may lead to recurrence. And this is -- this population we are targeting in our trial. So let me justify the selection of ovarian cancer and head and neck. So as I said before, those patients are in clinical remission, but with minimal residual disease and high risk of relapse, which can be detected by new markers. CA-125 is one example in the field of ovarian cancer, but ctDNA, new tools we had [indiscernible] useful tool to detect the presence of tumor cells. Those indication are recent or new sensitivity to checking blockers. So there is obviously a need for additional tools in the field of immunotherapy. Importantly, the immune system is functional because those patients have received limited number of lines of radiotherapy or chemotherapy. And the tumors -- two tumors, which have been selected, have low medium tumor mutational burden, meaning that we are in a good position with the tools we used, thanks to artificial intelligence to select and include all the mutation of interest in our vaccine and to test this vaccine as monotherapy. So let me move to the next slide, which is the description of the trial in ovarian cancer. So those patients who undergo surgery, followed by platinum-based chemotherapy, and the majority of them have achieved clinical complete remission, approximately 80%, let's say, but half of them, about half of them, when they are young, advanced age, are at high risk of having relapse of the disease, within 12 months. So we know that before overt clinical relapse, the patients can develop some first sign of asymptomatic relapse, whether it is increase in the specific marker I mentioned, CA-125 or appearance of the small lesion on CT scan. And at that time, the vaccine is started when the patients develop [indiscernible]. So the goal is to enroll 13 patients in total in the U.S. and in [ France ]. We have data now, which has been generated, from the first 4 patients included in this chart. So let us move now to the head and neck trials. So this trial was elegantly described by Christian. So very briefly, I just mention that they were randomized, as said by Christian, between immediate vaccination at the time of complete remission at the surgery and radiotherapy or delayed vaccination in combination with [indiscernible], including checkpoint blockers at the time of relapse. Our ambition is to roll a total of 30 patients. Of course, Christian is a Principal Investigator in this trial, which also involves France and the U.S. We have generated data on -- actually, we have 6 patients, who were randomized, but 2 were randomized immediate vaccination versus 4 in the delayed vaccination. So we have generated data on the first 2 patients in immediate vaccination. So now a few words about immunomonitoring and clinical monitoring of those patients are undergoing in both trials. So they are screened. And at the time of screening, tumor samples are removed so that tumor sequencing and manufacturing of the vaccine can be initiated. When the patient becomes eligible, before starting vaccination, the patients undergo leukapheresis. And later on, during treatment on day 64, the reason for leukapheresis is to collect enough lymphocytes so that we have enough material to test the specific new response towards the, let's say, 30 -- up to 30 epitopes, which are included in the vaccine. In parallel, regular blood samplings are taken to follow specific marker, we mentioned CA-125, but also ctDNA. And on the top of that, a regular CT scan to monitor the clinical outcome of the patient. I forgot to mention the vaccine scheme, which is 6 weekly injection during the induction period of the vaccination followed by a nearly 3 weeks regimen to a total of 20 injections. And to just to mention, as said before by Hedi and Eric the safety profile is not an issue with all material is very well tolerated. And with that, I will hand over to Kaïdre for the description of the immune response.

So thank you, Maud. And indeed, since the inception of this program and both studies, we've been working pretty intensively with Christian and other investigators to design a monitoring plan and the study that includes a monitoring plan that is exhaustive and allow us to have a pretty accurate description of what's going on in those patients that do receive the vaccine. So as you all know, it's -- one key question is whether we are able to identify those targets that are of interest in the sense, those targets and those mutations that are going to be indeed a solid target for the immune system and those targets, for which we will be able to induce an immune response once we've vaccinated the patients. So this is basically the starting point of our monitoring plan. And what we start with is an assessment of the response in the patients after vaccinations using an ex vivo ELISPOT against every single target that is in the vaccine. So in other words, it's a technology that allow us to measure or it's a method that allows us to measure whether there is a given -- there is a response -- a cellular response against each given targets in those patients. We call it ex vivo because that's also done after obtaining the sample without exposing the cells to long periods of culture. So it's important to note it's an ex vivo ELISPOT because that's the picture at the time we have taken the sample and not some potential methodology artifact. So this is a key starting point for us, and this is a technology that is giving us the major answer associated with those studies from an immunological point of view, whether the vaccine does induce a response, and we'll go through the results over the next slide. The other analysis is, we're looking at today is a phenotyping of those cells because, of course, we want cells that are trained, that do recognize the target peptide, but we also want those cells to exhibit some particular activation feature and maturation features that associate with clinical activity. And this is the other type of results we'll be looking at today. So on the next slide, Slide 29. On the left, at the bottom of the slide, there's a description of the mutational load, or in other times the number of mutations, we do see into the 6 patients we've treated so far. So we see that those patients have anywhere between 300 and low thousands mutations identified in the tumors. So those are genomic alterations that are -- that leads to the expression of abnormal proteins in the tumor, but not all of them do lead to a potential immune response, and we estimate that the actual number of immunogenic mutation would be somewhere around 1% of the mutation we observe in the cells. So the first challenge is to identify which of those mutations are going to be relevant targets. The lower part on the same side of the slide, the graph with the blue and the red bars, is showing as the Class I and the Class II epitopes that the artificial intelligence have identified among all those mutations that are seen into the patients. So you see many mutations, several hundreds, but it drives to a few predicted algorithm that we use to design the vaccine. So we clone 30 of them into the vaccines, and we give the vaccine to the patient. On the right side of the graph -- of the slide is the results we observed and the number for each patient, the number of mutation for which we respond. So you can see that for all patients, we get a response against a certain number of targets in the vaccine. This number goes from 6 to 11, with an average 10 positive response per patient. And that's the number of targets for each patient that do become positive after vaccination. When I'm saying becoming positive, it may be an amplification of a T-cell response that was preexisting in the patient or an induction and the priming of a de novo response into the patients, meaning that some of those patients did not have a response and have a response after the vaccination, and that was directly driven by the vaccinations. This number of positive response of 10 response is something we're really happy with when we compare ourselves, of course, we benchmark ourselves to other neoantigen vaccines. And up to now, all the neoantigen vaccines that have been published mainly using messenger RNA platforms have been around 5 positive targets per patients. So we're doing pretty well on that side. So besides the specific -- the number of response, we are also happy with the type of response we obtained. So of course, this is very early data, but we can see that using the viral vector, and this is a non advantage of the MVA, do induce response that as said Class I and Class II response. So I guess, for most of you, this is a concept that is clear. But basically, the Class II response are epitopes for the CD4 cells that are going to support the CD8 cells that do recognize Class I epitope. So it's important to have the 2 cell population. The CD8 will do the job, but the CD4 will provide support to the CD8 and make sure that the CD8 response will be maintained over time. So the other aspect of this early part of the data is the phenotype and the activation markers that are expressed by the different relevant immune cell population circulating in the patients. Another known advantage of viral vaccines are the capacity to the innate immunity. And this is something we can see here because in all patients basically through the treatment trial from baseline to day 63, we do see an increase in one NK cell population that is associated with actual antitumor activity. So those patients do have activated NK cells that are engaged into cytotoxic activity and we see that increasing between baseline and day 63, showing that something is happening on the innate immunity side. On the other part, in terms of phenotyping, you can see that CD4 and CD8 cells mature over the course of vaccination. By saying that what I mean is that, when you look at naive CD4 and CD8, they tend to decrease over the vaccinations, while the effect of cells tend to increase over vaccination, and this is true for both the population of cells. So in summary, on Slide 32, we are having a priming of innate immunity and this is a known feature of viral vectors. We also see maturation of cells with the shift from naive population to effect of population, and this is also a particular feature of viral vectors. We are also very happy with the number of response we obtained with basically a number of response that is twice the target we had to be at least as efficient as other vaccination platform. And this is particularly relevant as it leads to some early signs of efficacy that Maud is going to describe now.

Thank you, Kaïdre. So let's move to some data regarding the clinical outcome of the patients. So along the 4 patients with ovarian cancer, one patient was treated at the time of CA-125 elevation, went back to normal in terms of the marker without clinical progression during 9 months. I will give you more details about this specific patient story. Another patient is stable and under treatment after 9 months. Regarding the two patients treated with the vaccine, immediate vaccine, in the head and neck trial, one patient is under treatment 10 months after initiation and the other one, 5 months after vaccine initiation. So let me give you more details about the very first patient we treated, by the way, the patients with ovarian cancer. She was a 73-year-old woman with high-grade Grade IIIc ovarian cancer, with some mutation of DNA repair mechanism, meaning that she had poor clinical prognostic features. She had, in medical history, severe cardiac comorbidity with atrial fibrillation, aortic stenosis, and on the top of that, severe cardiac insufficiency. So on the next slide, you have the clinical outcome of the patient. And so she was [indiscernible] screen on January 2020. She experienced asymptomatic relapse on August 2020. And you can see that with the red curve, the continuous elevation of CA-125 with CT scan parallel increase in some lymph node lesions, meaning lymph node -- nodular metastasis. And so the vaccine was started at that time. And on October 2020, CA-125 went back to normal. CT scan was, I mentioned, subnormal because indeed lymph node was still there because they are always detectable on imaging, but apparently, reduced size, which is a good sign. And after 9 months, unfortunately, the patients died from her severe cardiac insufficiency. I just want to underline the fact that when the time of asymptomatic relapse, usually within weeks overt clinical recurrence is apparent, meaning the need for additional chemotherapy. So this is 9 months is something quite remarkable. So let's move to the next slide, which illustrates the immune response of the specific patient and in line with what Kaïdre showed. We -- you can see the simulation of the innate immunity and adaptive immunity as well with decrease in naive T cells and increase in effector T cells. On the right-hand side of the slide, you have the specific response towards epitope introduced in the vaccine with a gray bar, which represents the response at design, almost undetectable, and the orange bar, which represents the immune response on day 64 after vaccination. So overall, these patients is the type of history we want to see in all our patients.

Thank you, Maud. Indeed, this is really very exciting data. So we are very proud at Transgene and also with our partner, NEC, and all our other partners, whether it's a hospital, whether it's other companies that have supported us to share that with you. And we'd be very happy to answer your questions right now.

[Operator Instructions]. The first question comes from the line of Sebastiaan van der Schoot from Kempen.

Congrats on these results. I have a couple of questions on the neoantigens and then on the quality of T-cell responses and then on what to expect next. My first question is regarding the neoantigens that you selected. Can you maybe give some color on the type of new antigens that ended up in the final vaccine? Did this include some well-known ones, like shared new antigens, or maybe [indiscernible] mutations that are known in literature, shared between patients? Or are they mostly patient-specific and are not shared?

[indiscernible] the reply or shall we reply? Or do you want to put question...

If you could answer that first question, that would be great.

Okay. So throughout these 6 patients, we have been targeting a total of 136 mutation, and these 136 mutations were not common to -- none of them were coming to 2 patients. They were all unique mutations. So of course, many patients do have a common gene that is mutated, meaning that many patients have [indiscernible] mutation on the p53 gene, but that does not mean that they do have the same mutations and the same mutated sequence. So we do see some, like usual suspects, I would say, into the genomic profile without necessarily finding shared mutations across the patients, which is very expectable. You know that this question very often resurface, but when you look at the [ APC ] gene, which is taken from thousands of patients, and you look through an indication, you'll find very few mutations that are shared across patients.

Maybe, just add to that, the selection algorithm is based on the database for several criteria, among which the distance to the cells and the ability to be presented by the [ TTF ] in the system. And it is quite well known now that the oncogenic driver are not very immunogenic [indiscernible]. And it's not a surprise for us that most immunogenic subset of mutations were actually [ pilot neoantigens ].

Okay. Got it. And then on the machine learning approach of NEC. You show that you have absolute you get up to 1,000 mutations back from the IA algorithm? And I assume that you then perform a certain ranking of those epitopes and then select the best 30. Can you also expand on whether the T-cell responses that you observed, whether those were against those epitopes that were a lot higher in the ranking of these 30 epitopes or were more spread over those 3 epitopes equally?

So we do use the word ranking, but I think somehow it -- some -- a little bit of a misconception to think of this list as a ranking because, of course, their capacity, I would say, the pure immunogenicity potential that is taking into account, but there is also the diversity and the need to cover the entire clones population. So when we do assemble the 30 mutations, you cannot consider that the 30 epitopes is necessarily something we assume to be of lower value than the first epitopes. We have just selected an array of epitopes that do represent the maximum diversity of mutation and genes and physical, chemical features together with a relatively high allelic frequency to make sure those are mutations and not only present in sub-clones. So to answer the question, no, but it's expected not to see like the 1, 2 top 3 epitopes to be better than the other one.

To add on Eric's explanation, it's really the job of the artificial intelligence tool to propose the ranking and the selection of the new epitopes. The [indiscernible] is really done by a standard analysis of the genome of the patient, of the tumor and the genome. And then [indiscernible] you see that we select and propose the selection of the new epitopes, and then it comes to us and then we manufacture and so on.

Okay. Great. That was very clear. And then maybe on the repeated injection that you provide to boost the immune response. I was wondering whether you will do more measurements, in which you can actually see or do you actually expect to see them maybe to get additional responses against additional epitopes? Or is that out of the question? And and you would expect only to see maybe a boost of the response.

Yes. I think it's -- we have the sampling points throughout the time. And we probably in a few patients did them all because we may expect that throughout the time, we do see response against different epitopes and not have only boost of some of them and they may have a different profile through time. So we may test through our time for epitopes in patients, and if we only see book of those positive questions, then we restrict the analysis on characterizing the positive epitopes throughout times. I don't know if I'm fully answering your question, but...

May I jump in Kaïdre. So the purpose of the leukapheresis was to enable a broad screening assessment and would enable us to characterize T-cell responses at these two critical time points. The expectation would be that following those reactivities over time, all the dominant reactivities over time can be done on follow-up blood samples. So it would be perfectly reasonable. And I think Kaïdre and the team are planning to look at antigens that are not encoded in the vaccine, but that's from part of the transcriptomic features of the tumors that have been vaccinated against. So that would enable us to look at antigen epitope spreading. And indeed, the transient team already has past data with a shared antigen that observed that such epitope spreading was common. So from this background data set, I think it will be very interesting to see whether epitopes that are mutation derived, but that are not encoded in the vaccine also elicit a response and how the kinetics of these responses develop over time? And then specifically, whether any of these responses link with clinical outcomes, but I think it's too early to judge that. And for the ovarian cohort, there's also, of course, a possibility that by using the blood T-cells, it becomes possible to sequence both the alpha and the beta segment of the T-cell receptor, and then track these T-cells back into the tumor even if tissue is only available in innovative format because the T-cell receptor enables a molecular fingerprint that would allow us to look in different tissues of different origins. So I think your question is highly pertinent and expect that there will be data to demonstrate antigen epitope spreading over time also.

Great. That was a very clear answer. And then my final question is regarding update in H1 '22. How much of a large data set can we expect by them? Can you maybe talk about how many patients? What additional metrics we can expect? And at what length of a medium follow-up period, would you be confident that you can actually show a difference in relapse rates that would be meaningful?

Well, practically, what is planned is to enroll a total of about 13 patients [indiscernible] for the ovarian cancer trial. And total of 30 patients, 15 in the immediate vaccine arm and 15 in the delayed vaccine arm in the head and neck trial. So the enrollment is going very well. So what we expect is to have the next year additional data to share with you and to present that in the context of [indiscernible].

May I offer a clinical comment? So the medium time to relapse in these patients with this very high-risk disease is under 2 years. So I expect that if the relapse rate is different, 2 years into the follow-up of the cohort, then we'll have a very solid data set. I expect that the curves will begin to diverge much earlier than that. So I would expect that we would want to wait until the year after the first patient -- the last patient has been recruited and vaccinated to be able to begin assessing where there are true differences. With the data that Maud and Kaïdre presented on the ovarian cancer patients, if this is reproducible and is observed in a larger group of patients in the ovarian cohort, then I suspect that the divergence will happen much more quickly. And I think an ongoing analysis of the comparison will reveal whether my search and my expectation is true or whether the expectation of what might happen in the Phase I that is true.

Next question comes from the line of Dominic Rose from Intron Health.

This is Dominic from Intron Health. I've just got one. Of the 6 patients, who were treated, only 4 had a valuable data. So can you please help explain a bit more about why the other 2 patients were excluded? And will those 2 still be included in the final analysis?

So yes, I forgot to mention that. Those patients are in study and they will be part of the study. And there's really nothing to hide with those patients. The reason there was no immune data shown for those patients was that they did not have enough cells to allow us to do their characterization, so we could not generate the data for those patients, as you assume right now, those technologies, they require you to provide cells that are live, properly stored. And there's quite a few mishap in the way of having those samples available for analysis. So it's purely a technical issue.

Okay. I see. So we should -- I suppose we should expect to see this to be ironed out in the future. And I only wanted it because it was quite -- it was 1/3 of the total that were done, but what you said makes sense.

So we have some information about them.

Yes, we have some, but not the immune...

Yes, but we have for [indiscernible]. In the graph, you see for the CD4 and the CD8 evolution, all the patients are in right way. So it depends on the graph, but when we could, when we had them, we share them, and we have [indiscernible] and they are in line with others. We don't have a detailed analysis for the epitopes. So when we say, in average, we have 10 out of 30, on the 2 patients that were not available, we have no idea about this figure. But otherwise, it's very interesting.

We currently have no questions on the line. [Operator Instructions]. Next question comes from the line of Jean-Jacques Le Fur of Bryan Garnier.

Just one quick question regarding the future of TG4050. If I may say, in the real life, let's assume it will be approved. For the Phase I trial, I understand that it's a proof of concept. You have a careful selection of patients with clinical remission, minimal residual disease, low-to-medium TMB. Could we think that in the future, with the help of AI tools and so on, you may have a larger population or extended population with not a minimal residual disease or even whatever the TMB status is, so a larger population than the one you carefully choose for evident reasons for this trial?

Indeed, those trials are there to be sure that the concept is right that we are going in the good direction by selecting patients with minimal residual disease. Unfortunately, we know that in many clinical settings and other indications in the field of cancer, there are strong medical need to avoid relapses and the list is pretty long. And so maybe in monotherapy, but also in combination, and I'm thinking about potential combination with new checkpoint blockers, we may consider, if the concept is right, to broaden the application of this vaccine approach to many tumor types, I mean, a high risk of relapse. And maybe, Christian, you would like to elaborate a little bit about that?

We have lost him.

Yes. We've lost Christian.

Christian?

Yes. I missed the last two sentences of what Maud had said.

So. Yes, I was saying that if the concept is right, we can consider other indication, where the risk of relapse is quite high after potentially curative treatment. Do you agree with that, Christian?

Well, absolutely. I think that the current studies will bracket the assessment of measurable disease, but small volume disease in ovarian cancer and clinically disease-free patients at high risk of disease. So if we can demonstrate efficacy in the very high-risk adjuvant setting, particularly in a group where other strategies has a very poor track record, so that's in HPV-negative head and neck cancer. I think the obvious steps would be to roll this out to other tumor types, where high-risk adjuvant patients are very well characterized. So that could include multiple solid tumors where the methodology would be equally available. But I think it would also then make a strong case for developing this concept into patients with measurable disease, where objective assessment of responses in the individual patient could also be added so much along the lines of slightly worse group of patients in the ovarian cancer setting. I think if the concept in head neck cancer pans out, then, of course, the next step will also be to do a larger and pivotal randomized study that would be formally powered to detect clinical benefit. So I think if -- and the data -- all the data that we currently see as a porter of that, this has the potential to become a blockbuster approach to the management of multiple solid tumors. And I think the challenge will not be where to go, but how to limit the effort and to prioritize the clinical settings that will give the most clinical benefit for the patients, but also the best development opportunities. And certainly, if we look at other immunotherapy settings in head and neck and ovarian cancer, I think we would be very well placed to make a major impact in these 2 solid tumors, but of course, extend that to other tumors also.

Any other questions for today?

We currently have no further questions. [Operator Instructions].

Just finished, that went well as planned. So thanks again for your interest and your time and your great questions. Just to summarize, here, at Transgene [indiscernible], our partner, NEC, were extremely happy about the data that we've been able to share today. We thank all our partners in academia that have supported us. This gives us a lot of motivation to continue the existing trials and already to prepare the future of the [indiscernible]. Bye-bye.