Founder Stories: Özlem Türeci, mRNA: From Cancer Therapy to Infectious Disease Prevention

So let's start.

We are a bit in advance, but we are still respecting the 15 academic—

oh, I can pull off the mask, that's a liberation, thank you. So we are keeping with the tradition that we started a few years ago of having some outstanding lectures in the field of immunology. I'm saying, I remember we hosted here the Nobel Prize, Jim Allison, for the laurea honorum, and he talked about the, the conquest of immunotherapy. Now we have the privilege of hosting another person who has shaped the way we live thanks to immunology. Professor Özlem Türeci is here because a few years ago, before the pandemic, when we didn't have any idea that this was possible, we organized a winter school, a collaboration between the German Society for Immunotherapy, KIMT, and Özlem is president, and the PhD School in Life and Health Sciences. At the time, I was president of the PhD school. So the idea was to train early career scientists specifically in the field of cancer immunology and immunotherapy. So everything was stopped because the school had— the winter school had to occur— had to start in March, and we were in lockdown in February. So this is the first time we are rejoining and convening in the presence for a summer school that is going on in Ilhasi, and we have 24 students from all over the world, from 12 different countries that are participating at the moment. So graciously she agreed to give us a lecture. Just few words for those of you who don't know Özlem. She is professor of personalized immunotherapy, right, in Maine's university, the University Medical Center in Maine, but also at the Tron, and she has founded different companies. She founded Ganymede, and she was CEO of that company, and she founded what you know probably better, a company called BioNTech that has contributed to the race for vaccine discovery. But this is just part of what Oslem has contributed to the scientific community. She has worked on antibodies against cancer, she has worked on vaccine against cancer, she is now working on different therapies including CAR-T. And you think that, you know, this is a classic PhD CV, but she is a physician. And I will never forget one of the first times we met She told me something that makes a lot of sense to me. I'm an MD too. We need to find a cure, an option for those patients who don't have any. So this has been her motivation and the motivation of her husband, Ugusay, who is co-founder of the company. And I remind you that she was leading, and they are still leading, the Lightspeed project, right, who allowed in less than one year to have a vaccine that has been administered worldwide. Today she will talk about this technology, the RNA technology, and we are collaborating on this technology as University of Verona in covering different aspects, from cancer immunotherapy to infectious diseases prevention. And again, thank you for accepting the invitation.

So thank you very much, first of all, for co-hosting the KIMT Summer School here in Verona, which is really a great experience, and for inviting me to this lecture here at this wonderful university, and also for your kind and flattering words which speak more to our friendship and how— and its nature than to any of my merits here. I will talk about mRNA technology in my lecture and how it contributes to cancer immunotherapy, where it started, and to infectious disease prevention, and what our team in Mainz contributes contributed to this field. Our contribution started— can I move this? Yeah. Our contribution started in the 1990s with a vision. As Enzo has pointed out, we are physicians and immunologists. So, we were on the one hand treating cancer patients, on oncology wards and experiencing back in the 1990s how scarce the therapeutic options were. And on the other side, we were working in the lab and learning about the beauty of the immune system and the potential it has. And so the vision was to use the foreignness of cancer cells and leverage the armamentarium of the immune system for tumor rejection. And there were free fields areas which we defined as our future research engagement. On the one hand, cancer cell selective targets, and we engineered a couple of technologies to find such cancer cell selective targets which could be used for immunotherapies. The second area in which we engaged were— was development of potent immunotherapy platforms, and the third, understanding that tumor tumors are unique for each and every patient. The third field was individualized medicine. In this context, we became interested in cancer vaccines, therapeutic cancer vaccines and platforms. And what we already recognized in the 1990s comparing different vaccine formats and vaccine platforms was that mRNA is a very versatile platform to deliver genetic information, which is basically the key for vaccination, namely delivering in a suitable form the immunogen against which you want to have an immune response. And mRNA is versatile, its production is easy, it's an enzymatic in vitro transcription from a DNA template. You can put mRNA into nanoparticles, which which then on the one hand protect from the degradation by ubiquitinases, RNases, but also can be engineered to bring the mRNA to the place you want to target it to. And for vaccines, obviously, this place are dendritic cells. Even though we understood that mRNA has a great potential, we also realized that a lot of effort had to be invested in order to make mRNA suitable for preventive and therapeutic use in humans. And this was an endeavor for which we invested more than two decades and a number of discoveries, a number of modifications, a number of improvements. What I would like to do on the next couple of slides is to highlight 3 areas in which we invested efforts to make mRNA therapeutics feasible. One area was, in principle, the key disadvantage of mRNA. mRNA, if you bring it from outside into a cell, has to compete against all the gazillion other mRNA molecules in this cell, which are translated at the ribosome. And if it comes from the outside, it activates a primal defense mechanism, toll-like receptors, other innate sensors of mRNA, and this then leads to even stronger stalled translation of mRNA. So we needed to do something to address the short half-life of mRNA in the cell and also the poor translational efficiency, the AUC, so to say, of protein produced from it. And what we found out was that the non-coding elements of mRNA can be tweaked and designed to give mRNA, so to say, a VIP pass at the ribosome, meaning to increase the half-life of the mRNA so that more molecules of protein can be translated, and also the translational efficiency, so the potency of protein translation, and by this then also the potency of an mRNA vaccine. The synthetic mRNA which is used for vaccination basically looks identical to mature processed cellular mRNA. That means it has a cap, it has untranslated regions, it has a poly-A tail. And by high-throughput screenings and panning experiments, we found in a systematic approach caps and pre-prime UTRs and poly-A tail designs and lengths which allowed us to get this better translational performance. And as you can see, even the length of the poly-A tail and which cap you use has an effect on the protein translation. There is another way how you can address the poor translational efficiency of mRNA, which was pursued by our colleagues, Kati Karikó and Drew Weissman. They addressed the fact that defense mechanisms of mRNA stall mRNA translation. And they understood that the reason for this are the uridines, one of the nucleotides of the 4-letter code of mRNA. And if you use uridine-containing mRNA, the innate immune sensors bind this and stall mRNA translation. But if you substitute the uridine by other naturally occurring nucleosides, such as, for example, pseudomethyluridine, this does not happen, and you get good mRNA translation. And the same effect we got by modifying the non-translated elements of mRNA. At that time, I have to admit, we were not very interested in this type of technology because we were really focused on using mRNA as a vaccine for tumors therapeutically. So there was a lot of tumor mass and we needed a strong immune response, and we wanted to benefit from the excellent intrinsic adjuvanticity of mRNA. And therefore, all our cancer therapies are based on uridine.

MRNA.

I may add here, the modification of the non-translated elements was done in human dendritic cells, because this is really cell type specific, and was an important part of our approach. So the second area in which we worked extensively was the identification of lipid-based envelopes, so delivery technologies for bringing mRNA into dendritic cells, and not only any dendritic cell, dendritic cells in lymphatic compartments, because these are the places, the professional and natural places in which priming of strong T-cell responses and expansion of T-cells, CD4 and CD8 T-cells, takes place. What we had observed was that there is an impact of the delivery route on vaccine-induced T-cell response. Back in those times, there were already cancer vaccination trials ongoing in patients with peptides, for example, and the approach for delivery route which was used was intradermal or subcutaneous. And what we found out was that this results not in meaningful T-cell responses against the used antigen. Only if we injected the mRNA into lymph nodes, into lymphoid compartments, and this was done in mice by basically surgical means, then we get good immune responses. CD8 cells expanded in those injected lymph nodes, but also circulating in blood and spleen, so being active systemically. And the T cell responses were really strong. These are injected lymph nodes, and you see a strong proliferation of CD4 and CD8 T cells against the vaccine antigen which was injected. What we also found out that this is a very fast process. mRNA, naked mRNA, not enveloped in any way, injected into the lymph node is taken up very fast. So within the first couple couple of dozen minutes into certain cells. Everything which is not taken up is degraded by RNases, but this accumulation in cells is very strong and very fast. And these cells are resident dendritic cells, CD11b-positive cells. And we also found out that this mechanism of uptake is macropinocytosis. It can be entirely inhibited by rotlerin as immune responses induced by this methodology. This was an important finding that macropinocytosis is a constitutional natural mechanism for take-up of such mRNA. And we tested this in humans as well, injected into lymph nodes naked mRNA, which can be done under ultrasound control, and found out that the mechanisms are the same there and immune responses are induced in a very strong and unprecedented way. So we asked the question, is if injecting a single lymph node via this mechanism ends up in a strong immune response, shouldn't the targeting of all lymphatic compartments in the body not be even more potent for vaccine induction? And Therefore, we defined as next up-grade project to develop a liposomal combination with a liposomal formulation in which we could envelope the mRNA, inject intravenously, but target these liposomes in a very selective way into lymph node or lymphatic compartment resident dendritic cells. And we used concept that macropinocytosis as a mechanism can help us, and we need— we would need the specifications for those liposome-mRNA lipoplexes or nanoparticles which would support macropinocytotic uptake. Experimenting with different liposomal combinations in mice, we found that DOTMA/DOPE-formulated mRNA, and these are lipid- which are already used in the clinic, which is contraintuitively in terms of charge close to neutral and medium-sized and with low polydispersity. Nanoparticles of this specs allow us to prevent the first-pass effect and expression uptake and the expression of the antigen in the lung, which normally happens when you inject intravenously such nanoparticles. But what we we actually get with these specific nanoparticles is accumulation selectively in lymphatic compartments, for example, the spleen, which is the largest one, and their expression in the resident dendritic cells. And we could show this with depletion experiments. We only get strong immune responses and also expression of the respective protein in if we don't deplete resident cells. And this is not only in the spleen, but also in lymph nodes body-wide and in the bone marrow. And we found out that these RNA lipoplexes in mice induce strong immune responses. They are, as I said, primarily translated in dendritic cells resident in lymphatic compartments. The RNA brings in its intrinsic adjuvanticity, namely that it binds, single-stranded mRNA binds to TLR7, TLR8, but also other innate immune sensors. And this triggers a very strong but distinct cytokine signature dominated by interferon gamma response. And this again results in potent induction of antigen-specific T cells, as we have shown in different models, and translates also in different to treat tumor models to anti-tumor response and to growth inhibition of tumors. So we decided to bring this concept into clinical testing, and this, one of our first studies was in melanoma patients, patients with advanced melanoma, where we used a combination of 4 different melanoma-associated tumor antigens, which collectively are expressed or cover 95% of melanoma patients. And this was a Phase 1/2 study in which we tested different dose levels, tested this vaccine as monotherapy, but also combined with anti-PD-1 compounds, which are approved in this setting and assessed immune responses and also anti-tumor responses in this heterogeneous patient population. First of all, it was encouraging for us to see that in terms of mode of action, which we had described in mouse models, we could see the same effects in humans on 3 different levels. One level was that we could see shortly after injecting the mRNA systemically, after a couple of hours, metabolic activity by PET CT in spleen, which indicated that we have a mobilization, a proliferation of immune cells, similar as we have seen in mouse. We could also reproduce the intrinsic adjuvanticity of the mRNA. This is data from one patient who in weekly intervals received increasing doses of the vaccine, low doses as you can see, this is how potent our platform is, and what we could see is a dose-dependent increase of exactly the same cytokine profile, interferon alpha and gamma dominated cytokine profile in these patients. Not supraphysiologic, so that we did not induce cytokine release syndromes, and pulsatile, so this peaked within 2 to 4 hours after vaccination and was back to normal within 24 hours. But in a way that we could— the required activation of immune responses on top of the antigen we had presented via the vaccine. And indeed, on the third level now, we were able to induce T-cell responses. And this, for example, is the T-cell response against one epitope of one of the antigens this patient has been immunized this with. We have polytopic immune responses, so this is really only a fraction. And what we observed, that even this one fraction of the polytopic immune response is up to 10% of the circulating CD8 cells of this patient. So these are dimensions you normally seek to reach with adoptive T cell transfer. So this was very What we also observed was clinical activity. These were very advanced patients, and this is a subset from this study in which we treated more than 100 patients, namely patients who had stage 4 disease at inclusion into this trial and had been heavily pretreated, including checkpoint inhibitors, and were now receiving the vaccine in combination with checkpoint inhibitor or not. And as you can see here, there is a strong clinical activity with target lesions which are regressing and some patients having durable immune responses. In the recommended Phase 2 dose we selected in a patient subset where With anti-PD-1 refractory and resistant disease, we saw in combination with anti-PD-1 tumor, an objective response rate of 35%, which with standard of care would be 10%. And this trial now has led to a randomized Phase II trial for which we will have data this this year. So the third area in which we invested efforts was towards the vision of developing individualized, truly individualized cancer vaccines that are really tailor-made for each patient on demand, so to say. And the basis for this is that the most interesting tumor-associated tumor antigens are somatic cancer mutations. That means really mutations which happen in the cancer are not expressed anywhere else. They are highly selective and there is no immune tolerance against which you have to work. And these tumor cancer mutations can give rise to neoantigens when they create binding motifs for MHC class I and MHC class II. The drawback here is that cancer mutations are randomly, happen randomly over time and therefore are highly individual to patients. Patients and a very good platform to be used for highly individualized immune therapies. And what that really means is that you take a sample of a tumor from this patient who is newly diagnosed and a PBMC sample as normal counterpart. Next-generation sequencing is performed to identify the mutanome, so the entire, entirety of mutated, of mutations in this patient's cancer. And every cancer looks different in there. If you want to do this on an individualized level, highly specific, you have to develop specific bioinformatic mutation detection tools. So we have to invest efforts in that. Then we have developed a computational pipeline which allows us to predict which of these mutations bind to the polymorphic MHC class I and MHC class II alleles, of this patient, which of them are highly expressed, which of them are from genes which are from proteins which are specifically prone to have an effect when targeted with T cell responses, et cetera. And we use this data in order to select in that case 20 mutations per patient and engineer based on our improved mRNA platform, a vaccine on demand tailor-made for this patient. And this is just the first clinical trial which we started in 2014, which was published in 2017, with 13 patients with localized inoperable or stage 4 metastatic melanoma. Panoma. And what we had observed by immunizing these patients with unique neoantigens is shown here, some clinical activity. These are the 13 patients, and we mapped the recurrences, the metastatic relapses of these patients prior, in the 2 years prior start of the vaccination and after start of the vaccination. And if you look into this cumulatively, you find out that the number of— the cumulative number of relapses of these patients has dropped under vaccination dramatically. And we have still now for 5, 6 years these patients under follow-up, and several of them are still alive and in fact have those T cell responses we have generated in them, those against the neoantigens, which are in the meantime effect or memory phenotype. The challenges for establishing individualized mRNA vaccines are not only scientific ones. You have to bring such a vaccine manufacturing and all the computational part of of it and so on into a clinical practice setting, which is challenging. And you need for each and every step basically an SOP, a standard operation procedure, which is validated. And this is sort of the flow. Each of these boxes has an entire process which is well defined in it, a standard operation procedure. And on the next slide, I want to show you for this part, which is just the biobank, so getting the samples, which give the information for engineering the vaccine for these, for this patient, extracting the mRNA out of them, doing the next generation sequencing. This all has to be documented. So what I will show you on the next slide refers only to this, namely on this slide, this is 2014, the inspection of a regulatory authority which visited us and wanted to see all the documents, documentation, and this is the documentation for one patient only for that part of the entire process. So there was a lot to read for those people when they visited us for inspection. And at that time we had to do the manufacturing all manually under GMP for ice principle and so on. So the lead time for getting a vaccine for one patient was rarely under 3 months because of all this which needed to be handled. We improved over time, and end of 2019, the lead time by paperless documentation and semi-automatic manufacturing, etc., was down to 3 to 6 weeks per patient. So basically, needle-to-needle time taking the biosamples, processing all that, and delivering the vaccine of unique composition for this patient to be injected. And in the meantime, we have treated hundreds of patients with our individualized vaccine all over the world, each of them with an individual composition. We don't have any one vaccine seen, which is identical for two patients, which meant that when the pandemic hit at that fateful last week, January 2020, when we realized we are in principle already in the midst of a pandemic, we thought this is some technology which we— maybe we can use it to contribute. To pandemic emergency vaccine development, because this race against each patient's tumor, through which we had to go hundreds of times in the context of our individualized cancer vaccine, had taught us so much to be also ready for an emergency vaccine development for COVID-19. COVID-19. 2 weeks before we started, the SARS-CoV-2 genetic sequence was already published, which was really a blessing for everyone. We started then our mRNA vaccine program. There were so many unknowns, so that we started preclinically with 20 different vaccine candidates and funneled them through preclinical lab and animal studies, in 3 months later, we had boiled this down to 4 candidates which went into a phase 1 testing in Germany, starting in Germany. We used the time to forge alliances with companies who could complement what we as a small German company did not have, so big machineries to conduct global clinical trials in tens of thousands of people in different regions of the world, manufacturing capacities later for commercial supply in the case of success, and so on, so that we had our colleagues Pfizer on board and Fosun for China on board, and they pitched in into the clinical trials. The Phase 1/Phase 2 testing allowed us to identify to identify the candidate, BNT162b2, a.k.a. Comirnaty, which proved to be the best of best in our candidate list to go into a Phase 3 trial, which started in summer 2020. And in November 2020, we had our data from a large Phase 3 trial, global Phase 3 trial, which showed that we in fact had a functioning vaccine and a vaccine which was highly potent with an efficacy rate of 95%. We had planned for success. This is the only thing you can do in this desperate situation. So we had started to talk to the regulatory authorities all over the world very early on. Had started also rolling submissions. We had ramped up manufacturing capacities, had bought manufacturing plants and so on. Everything at risk as a cash-burn company at that time. So it was really a risky situation also for that, which allowed us to be prepared also for success. And in the meantime, more than 1 billion people have been vaccinated in more than 170 regions with our vaccine, and we hear that millions of deaths could be averted. What was important for us from the very beginning was that we induce a holistic immune response, so T cells as well as antibodies. In the pharmaceutical industry against respiratory viruses, there is a very strong focus on virus-neutralizing antibodies, which are definitely important, in particular to prevent SARS-CoV-2 infection and also transmission. But we have, as MDs, know that also thinking of disease and severe disease and hospitalization and death is important, and here is where T cells come to play. So this was an important part of that. And how we selected our final candidate. Our final candidate, BNT162b2, encodes for the entire spike protein of the virus, and it is mutated so that it's conformationally stabilized, and that piece that docks on the cellular receptor to ACE2 is stabilized and and is erected so that antibodies against this important part can be generated. There was some drama backstage because it was very clear we could not use our wonderful intravenous RNA lipoplex formulation. Such a vaccine, in particular in a pandemic situation, has to be administered that intramuscularly, so that we had to use a different formulation. And this formulation, which we found with a cooperation partner, Acuitas, had some own intrinsic adjuvanticity. It was not as inert as our Lipoplexes, which meant that we had to boil down the sort of total adjuvanticity and go with nucleoside-modified mRNA and basically redesign the entire formulation part. What we kept in mind when we designed these new nanoparticles was the need to get this to lymphatic compartments and to the dendritic cells there. So for the design of these new nanoparticles, we took in account, we had in mind all the specs we needed for these nanoparticles to be, to travel via lymphatics to lymphoid compartments and taken up by dendritic cells there. And as you can see here, even though we inject the mRNA into nanoparticles into the muscle, the mRNA itself and also the protein is not detected in the injected muscle, but is detected and expressed in the lymphoid compartments in exactly the right cells. And on the one hand, this is the delivery, how we construct the nanoparticles, but it is also the cell selection of the non-coding parts on which I had already alluded, which have been designed such that they are favored by dendritic cells and not other cell types. So what we saw already in our phase 1 study was, yes, even at lowest doses, our vaccine induces not only binding antibodies but also virus-neutralizing antibodies. Antibodies. We need 2 doses for this. We decided to go with 2 doses of 30 micrograms, 21 days apart. 21 days is not something— it's a bit short for an immunologist, but we were in a pandemic, so this was not about immunologically optimizing, but optimizing for the purpose. And this dose also induced induces strong CD4 and CD8 T cell responses, which are after also some time comparable to recall responses to common viruses like EBV and CMV and flu, as shown here. The effect of all this was that in our phase 3 As I said, we could show 95% efficacy. We treated 20,000 patients with placebo and 20,000 approximately with our vaccine and could see a case split of 8:206:62 cases of symptomatic validated COVID-19 disease, and this translated to a 95% efficacy, also in the older population, which was maintained over a longer duration, 91% still after 6 months. We understood very early on that just by developing the vaccine and being able to deploy it, our job probably is not done, but we have a responsibility, we're responsibility to stay on board and think about what might come in future. And already at that time, the question was, how long will the duration of this vaccination be? When do we lose protection by this vaccine? This is obviously very strongly entangled with another question, namely, how will the will the virus evolve? And therefore, to be prepared for what may come, we installed very early on, already in 2021, once we had this vaccine in its first version going, a system, a process for us. First of all, we developed an artificial intelligence or machine learning-based early warning system which would use all the sequences which are made public, for example, by GISAID, of circulating viruses, virus variants worldwide, and assess each of them for how fit they are to infect, to bind to the cellular receptor, but also the likelihood of immune escape, so that we had a tool to stay a step directly behind the virus. And what we then did, all variants of concern which would appear, either declared by the WHO or just because we thought this could also be a vaccine of concern, were tested with the sera of BNT162b2 vaccinated individuals in order to to look on the antibody, neutralizing antibody level for immune escape. And everything was fine until Omicron BA.1 appeared, because we could basically always see this type of results for the entire part of the alphabet prior Omicron. This, for example, The Delta variant, which is well still neutralized by BNT162b2, which is the Wuhan spike, as you know, in antibodies. The one which bothered us most was the Beta variant, but it was still fine. However, as you can see here, Omicron was under the threshold, so there is no neutralization. What we found out was that a third booster, so a third injection of vaccination, brings this back to protection also against Omicron. So all of a sudden, a virus against which two vaccinations were sufficient turned itself, by mutating, to a variant for which you would need three vaccinations as primary series. What was encouraging for us was that the T-cell epitopes which we had shown to be CD8 epitopes against which our vaccine induces T-cells were highly preserved also in Omicron. So this made us sleep better at night because we knew that there is some protection at least against severe disease, death, hospitalization. However, it was very clear to us and at some point also to regulators and governments that an adaptation of the vaccine is needed to the variants. So exchanging the Wuhan spike against the Omicron BA.1 spike. And we actually immediately started that process last year, November. We were sort of slowed down a bit by the regulators because the requirements were extensive clinical trials and so on. And the manufacturing part was easy for us because we trained this hundreds of times with our individualized cancer vaccines. So what we observed in our clinical trial, and this is only the preliminary analysis, we have in the meantime the final analysis and in fact all the data is with regulators and there are the first approvals for this adapted vaccine going on in different regions. So what we observed was that against BA.1, which was sort of the declared enemy, we get with our vaccine as a monovalent vaccine, but also if if we mix the monovalent Omicron vaccine with the BNT162b2, very nice immune responses. The sad news, unfortunately, was that even though we had succeeded with our milestone to develop a vaccine against BA.1, in the meantime, the virus that the virus had not waited for us to do this but had continued to mutate. And as you all know, we have BA.4, BA.5 dominance in the meantime in almost all regions. We say BA.4, BA.5 because both variants have the same spike. It's the same spike, only other parts are different. And we could show that unfortunately the BA.1-adapted vaccines did not work as well anymore against BA.4/5 in the monovalent as well in the bivalent form. And here's just a part of the virus spikes of both variants compared, which shows that BA.1, against which all the current vaccine variant-adapted vaccines have been developed, is different in terms of mutation profile quite considerably as compared to BA.2-derived lineages, sublineages, which are, for example, BA.4.5. So that means we— again, it's not only a scientific challenge. The challenge we have as community, as a global community, is also a regulatory part. Which still are not adapted for the pandemic situation with a fast mutating virus. The pathway which we have to follow, which we had to also follow for the BA.1 variant, means clinical data, and that takes 8 months to develop, to have the regulatory package ready. What we had proposed and continue to propose I propose is to go without the clinical data, but with the preclinical model data and CMC, exactly as we do in our cancer vaccine patients, for which every time N equals 1 without previous studies. Only that way we can cope with the fast following variants. So, there are regulatory challenges, and there were manufacturing challenges already in the early times of this vaccine development. In 2019, we were able, planning for our cancer trials, to produce 10,000 doses when we engaged— of vaccine per year. When we engaged into COVID-19 vaccine development, it was clear to us there has to be more supply, and we turned every stone basically and managed to upscale to 25 million doses of vaccine. And then during 2020, we realized that many of our peers, more than a dozen companies, had started vaccine development early 2020, and many of them had to give up because this is really not a trivial a very difficult job to do, and it was clear that there would be even a higher burden on us, and we had to deliver. So by 2021, we managed to upscale to 3 billion doses and still upscaling, which, as you can imagine, also meant innovation and investment into discoveries and inventions. There is another challenge with which we had to socialize ourselves and which sort of changed our perspective as a small company in Germany, as which we started, namely the challenge of vaccine equality. We all know that in those regions where this vaccine, other vaccines are needed most, people don't get the vaccines. We address this by distributing at-cost vaccines into low-middle-income countries. 40% of what we have produced went into those countries that way, but we think that we need to enable those people there and help them to build their own vaccine hubs, produce for themselves. And this is also something into which we have invested with what we call a Biocontainer concept. So we have miniaturized our production processes. This is also part— this comes also from our individualized cancer vaccine efforts so that they fit into containers and are fully automatized. And we are building these containers, equipping them with all what is needed, doing test runs, qualifying them from a regulatory or validation perspective in our plants, and then ship them and want to ship them. So this is the plan, want to ship them around the world. The first steps have— and so that they can at the target location then be built and qualification runs can be done locally, and production can then happen in those locations. And we have started with that on the African continent. A couple of weeks ago, we had the groundbreaking for such a facility in, in Kigali, in Rwanda, with support of the African European Union, with the WHO, and the African continent is really mobilized and has also implemented— is implementing their first own regulatory authority, which will also be located in Kigali. So that this will be a very interesting joint program to find out whether such concepts sets work. So this is the journey of mRNA technology from cancer to infectious diseases, and it will definitely go back with everything it has learned to cancer again. And with this, I would like to thank you for your interest and acknowledge only this sort of tip of the iceberg of people who have contributed to for this work. Thank you.

Well, thank you very much. This was an incredible journey in such a small time, and that people tend to forget there are two decades of development before.

Yes.

Was not possible without their hard work, daily work for many. So this is something I want to say to many people. The technology was right and the moment was perfect.

Absolutely. And not only our work, generations of scientists have built the foundation. So this did not come from nowhere.

Exactly.

So we have time for questions.

Actually, I don't know if there are questions from the audience because—

No, nothing in the chat.

Okay, so I will—

There are many applications. For example, one which is obvious is development of infectious disease vaccines in a broader way. We have now the pandemic situation, a pandemic vaccine which is very special, but there are also other neglected diseases diseases where we don't have vaccines, and malaria, tuberculosis are only examples for that. And one of the draw— one of the hurdles there is that these diseases are so complex that you need even to test different antigens in order to find out which are the best tests in humans to proceed with vaccine development. And mRNA is so versatile that it is not a problem at all to make an entire battery of different antigens, test them in phase 1 trials. You don't have what comes with recombinant protein technology, where for each of the antigens you would need years to express and formulate the protein. Here with the mRNA, you You can choose a battery of antigens and 2 to 3 months later you can have all of them in clinical testing in Phase 1. That's an advantage. Other areas are autoimmune diseases. mRNA, the way we have built it, is a toolbox. So you can— we have different non-coding elements elements with which we can tweak whether we have long expression, short expression, pulsatile expression. We can assemble the mRNA and the liposomal formulation such that we don't expand CD8 T cells, but expand antigen-specific Tregs, which would mean applications in the autoimmune realm where we We have projects ongoing for multiple sclerosis, for example, because antigen-specific tolerance induction has a very broad space where you can use it. Other areas are, for example, rejuvenation, because many of organ aging processes come from inflammation, so suppress those inflamed tissues are also an application. So very broad.

Could machine learning be used to predict further developments of the virus? Could you use machine learning to predict rather than be one step behind the virus? And another thing that I'm wondering is you mentioned the cancer vaccine, but when you mean vaccine, like you prevent the formation of metastases essentially?

Yes, it's therapeutic vaccines, obviously, so the cancer is already there. And there are different spaces where you can position cancer vaccines. We are very much interested in the minimal residual disease setting. So post-adjuvant treatment, for example, where, for example, in colorectal cancer, we identify stage 2 high-risk, stage 3 patients with colorectal cancer, and after curative surgery, they go into watchful waiting, as you know, as standard, so to say. In our vaccine arm, we vaccinate and vaccinate them. That I think is a perfect setting because immunotherapy is a numbers game. If you have a low tumor load, that's even more promising. But there's also the metastatic setting where in particular with anti-PD-1 combination, we see objective response rates. So there it would be about complete remission responses or partial responses responses, and by continued vaccination, maintaining those T cells alive and controlling the tumor growth. And the first question was machine learning. Yeah.

We are one step behind the virus for SARS-CoV-2. So because you're using machine learning to predict once we have the sequences, which would be the sequence that will most likely most likely be the next dominant one. So could you use machine learning to be one step ahead rather than one step behind? So start to predict the confirmation of the spike protein with respect to what the distribution of that?

Yes, we and also others are playing around with that. But we are not sure whether the biological reality is such that technology allows allows us to use, for example, machine learning for predicting what will happen. What we see is with the current machine learning tools or databases which we have, that there is quite still some mutational space for the virus to change. We would not have predicted BA.4.5 now, because what happened is the virus went back in the NTD domain and sort of lost what it had acquired in terms of mutations for Omicron BA.1 and looks more like Delta again. And this is not because of recombination, this is not a segmented virus, it's because it acted contraintuitively, it appears. So there are things we might be not pick up and not be able to reflect in machine learning tools, which does not mean that we shouldn't try and learn. And this is what we are doing.

Francesco?

Thank you so much for the presentation. Going back to the cancer immunotherapy field, I was curious about your opinion about the platform that you established and all the issues that you already overcome in, uh, to make available a personalized vaccine for these patients. However, for any kind of treatment, there are people that respond better than the others, and I guess this happens as well for this kind of approach. So I have a couple of good questions. The first is how you can manage in a short time in order to understand which are the patients that are good responders. So if you can find any predictive biomarkers, for example, in your response or something else to predict the patient that will respond better to the treatments. And in general, in the deep, the patients that say, hey, you are not getting the best results from this treatment, which are usually the issues. Is it about the activation of our tumor-specific immune response, or is it about tumor T cell infiltration inside the tumor, or is it because of immunosuppression, or is it because of evolution of tumor that is losing antigen presentation or antigens?

Yes, these are important questions and should be, and and in our case also are parts of a clinical development program to collect as many as possible meaningful biomarker data points and characterize them and meta-analyze them. Because in general, doing this in only one study is not sufficient. It needs to be validated across different sort of cohorts. Cohorts. We are doing that. We have indications which might also be obvious what predictive markers might be. Cold tumors respond less well as compared to hot tumors. Mutation-rich tumors respond better. So there are a couple of observations but it really needs more data in order to sort of build a narrative out of it and make it actionable for the clinical setting.

Other questions? Let's see if there is any.

It says, can I make a question? Yes, you can. Hello, can you Can you hear me? Oh, yes. Okay.

So yeah, I'm just a voice. So I have actually a basic question on the mechanism of the vaccine. So you said the mRNA is uptaken preferentially by dendritic cells. So I guess that the antigen is also made endogenously by dendritic cells. And do you have a specific strategy that is enhancing MHC class II presentation of those antigen that are made endogenously in dendritic Yes, we in fact have.

That's part of the optimization of mRNA backbones. So the first part of the three parts of efforts I have described, what we have observed is that if we— if we use a secretory domain in front of the respective antigen, so N-terminally and C-terminally, the intramembrane and intracellular domain part of an MHC class I molecule, we get on the one hand CD4 responses. So presentation of MHC class— on MHC class I— MHC class II, which is not the case for this exogenously delivered mRNA otherwise in dendritic cells. And we also get an increase, a strong enhancement of MHC class MHC class I response. So there is also a tinkering in the design which increases MHC class I and MHC class II responses. Okay, thank you.

I do have one last question.

No, okay. Oh, there is another question, so it's not last. Okay, you go first.

Thank you so much for the talk. I was just wondering, in terms of the cancer vaccines, have there been any significant side effects as well? So the effects have been useful?

Yeah, no, we had to do a dose finding, obviously. We have defined defined 50 to 100 micrograms per vaccination as our dose because we see very strong immune responses and it is well tolerated at that dose. We have treated more than 400 patients with cancer with this dose. The patients are getting an initial initial vaccination series weekly of 6 vaccinations, 6 shots, and thereafter every 6 weeks for 1 year and then every 3 months injections of the vaccine. That means we not only have sort of the one-dose data, we also have follow-up dose data for quite some repetitive administrations. And there are patients who have received this for 4, 5 years. So the discussion around COVID-19 vaccine and long-term data, for the cancer vaccine, we have that. And the vaccine is well tolerated. We see reactogenicity, so patients can have fever, chills. This can also be grade 3, so that you really need to give something which is fever and the chills, or fatigue, or arthralgia. So, everything which is sort of flu-like, which is understandable with intrinsic adjuvanticity. It is manageable and can be, for example, treated with paracetamol, so that we even consider to develop the vaccine for community hospitals, for example, on an outpatient basis.

Mucosal immunity, and the related question is that is mucosal immunity really important to protect against infection, not only the disease? What are your thoughts about it?

Yeah, we are working on mucosal vaccines. We are experimenting with other types of formulations, for example, for nasal vaccines, also in the COVID-19 setting. And that's obviously a field into which one should invest some efforts, because we cannot answer yet how much mucosal immunity we get with all the intramuscularly administered vaccines. From real-world we know that BNT162b2 has also a strong infection protective component. So if the mucosa plays an important role there, we might induce some immunity also there, migrating T cells, for example.

Well, if there is no other question, I would like to close this excellent lecture.

Thank you again.

Thanking you again. And I will just remind that Stefano Rugel is responsible for a project collaboration ongoing with BioNTech within the framework of the National Center for RNA Therapy that was recently supported by Next Generation EU funding in Italy. And this will be about autoimmune diseases as possible potential application extension. So again, thank you very much for coming, and I think everybody is excited to have listened to a piece of history.