[Non-English content] Shahram, would you like to start introducing yourself? We could do quick introductions around the table. Yeah. Hi everybody, I am Shahram, PhD in cancer and immunology, and I am a Specialist in the Proteomics. Hi, I'm Arunima. I am a Specialist in Microscopy and Imaging, which I will show you some flavors of our advanced microscope today. Hello, my name is Olof. I'm a PhD in biophysical chemistry and Specialist in Structural Biology and Protein Interactions. Hello, I am Farhan. I have, done PhD in bioinformatics and cancer genomics. My main work is mainly on the cancer genomics data analysis. Ines, I'm PhD in infection biology and microbiology, and I also work on the transcriptomic response, mostly in the infection projects. My name is Suzanne. I'm a Project Manager, I'm responsible for the clinical studies, I have more than 25 years experience in clinical trial management. I'm overseeing the clinical studies and to make sure they are progressing according to plan. Thank you, Suzanne. You're a new face for everybody, and we welcome you as well from our side. Yes, I'm Atefeh. I'm a Research Engineer, so I have been working with therapeutic protein and peptides for many years now. I work mostly with protein technologies from in vitro experiment to recombinant protein expression and also in silico analysis. Jakob? I'm the CEO, as you probably know. As you know, in addition, we have a very rich network of specialists and consultants around the world, and not least the medical competence that is required for the clinical studies. I will share the screen and say some few introductory comments, and then each of the scientists here will tell you a bit about what they do. [Non-English content]. There is always something with this. Today's meeting is made especially for you to meet some of your questions and your interests in the company. We have made a lot of progress. We're in a very positive phase of development, actually all around, both scientifically, commercially, and also with the different projects, different studies that we are doing. We are truly translating innovation into what we hope will be clinical success. Preliminary data, of course, has shown success already. I'm really sorry. I don't know what is happening to this one. I'm trying to go back. Good. I apologize. Recently, we press released a Letter of Intent regarding a partnering discussion that is ongoing with a pharma company that has experience especially in the area of bladder cancer. This study is progressing. The discussions are progressing very well, and we have finished the due diligence part. We look forward to letting you know more about the outcome, of course, in the future. We are also progressing with the phase III studies, where protocols and regulatory workup have been finished, and we are also recruiting new study centers, which is part of the process. The ones that are already in place are there and ready to go. We are doing a lot of work with the phase III drug production, which I think we should make into a special digital meeting when we have more news for you. Also, in the area of novel alternatives to antibiotics, I think some of you are aware that we recently published our clinical study in Nature Microbiology, showing in a phase II study that our approach to treatment with the IL-1 inhibitor has comparable efficacy as antibiotics. This is a huge step. It's the first time that a study like this has been performed. As you will also hear in the near future, there are new ideas, new drugs, and new patents in this area. We just, I think yesterday, published a new patent relating to a broader use of our anticancer compounds for systemic treatment and other aspects of cancer disease. As I said, you're used to seeing the team on our presentations with this image. Today everybody, or most of us, are here. I will give the floor over to the first speaker, Farhan... Shahram. Yes. I know your name, actually. We will go backwards. This overview shows you what many of you have seen many times, which is how molecules are made in cells, starting with the DNA in the cell, which can be studied by genomics technology, and translating to RNA, which is the matter that is in between the DNA and the proteins that decides which proteins are going to be made. That can be studied with transcriptomics, and the protein that can be studied with proteomics. Today we are going to start. Proteomics with the proteomics Yeah and then go backwards to the RNA and the DNA. Yeah Shahram, please. How can we define disease severity and analyze the patient response to the treatment, a platform to measure the immuno response? We have different project in the lab. First one, bladder cancer patient treated with alpha1-oleate, febrile urinary tract infection, patient with bladder pain syndrome treated with anakinra, patient with cystitis also treated with a nakinra, and also effect of BAMLET in metabolism. Here I present one of the advanced technology we use in the lab, proteomics analysis by Luminex technology. Based on this technology, we are able to detect more than 100 proteins in the one single assay. For the bladder cancer patient and also for infection patient, we have 25 most important immuno response proteins. In this technology, we have, based on the protein of interest, we have different beads. All these beads coat with specific antibody, and then we add samples and different material to these samples. Finally, we check the fluorescence intensity by this advanced machine. Since we use the different standard and control, we can calculate the concentration of the different proteins in the end of the assay. I'm going to show you some more interesting result of immuno response. A potent immuno response to alpha1-oleate treatment may be protective in bladder cancer. Here we can see some example, then I will show you more interesting result. IL-1RA and IL-1 alpha. The blue is placebo, the green is low dose, and the red is high dose. Just look at here, pre-V1. Before the start of the treatment, the level of, for example, IL-1RA is almost around zero. After two hours, just two hours, you can see the level of the IL-1RA increased from zero to more than 40,000 picograms, and they stay high until end of the treatment. IL-1 alpha, this is another example. You can see the kinetic of response when we increase the dose. Since when we treat the patient with alpha-1, we have a lot of cells in the urine. We, okay, we have the protein in the urine. Let's check the protein also in the cells. We stain all these cells based on this protein of interest. You can see in the right side, it's the lower dose. The fluorescence intensity is quite low, but when we increase the dose, you can see the color. It's everywhere, and we can see the same trend also for IL-1 alpha. The most interesting part, they used the BCG treatment for more than 50 years to treat the patient with bladder cancer, but after the surgery. We used the alpha1-oleate treatment before surgery. We have the immuno response, we said, "Okay, they use the BCG for the treatment for 50 years. Let's check the BCG treatment and in immuno response to alpha1-oleate treatment." You can see in the Venn diagram, most of the protein is shared between the BCG treatment and alpha1-oleate treatment. In the right side you can see we have more protein when we treat the patient with the alpha1-oleate, and the response almost is same. We publish a nice paper with our colleague in Prague, U.S., and Lund, and also Catharina here. Since the project is work, we try to do the same assay for infection project. Here I explain this part, protein, and then I leave the table to Ines to continue the rest. Thank you. Thank you, Shahram. Yeah. Thank you. Hello. Going upwards here in the chain, we also study what is called a transcriptomics. It's a study of all the RNA that is expressed in the cells, and we use a genome-wide platform to look at the whole response. To do that, we have different samples. A lot of the patient samples, for example, that comes from either the blood or the tissue. We do RNA sequencing to measure all the genes that are regulated, either I mean, yeah, for the patients it's in response to the treatment, so Alpha1H treatment for the tissue in the bladder cancer, or the blood response when we treat patients with the anakinra, the IL-1RA, for example. We use programs to analyze these large data sets and identify the actual disease processes that are happening in those treated patients, and measure how strongly they are regulated in response to the treatment. Here I show an example. It's called a volcano plot, so it looks like a volcano, and every dot here that you see is a gene that is regulated. This type of assay looks at 20,000 different genes, and looks at the differential expressions. Here we compare those patients' samples during the acute phase compared to the follow-up six months after when they don't have the infection anymore. In red, it's all the genes that are activated, that are higher during this acute response, the acute phase. This data is based on hundreds of samples, 200 samples actually, because we have some patient sample in the acute phase and we compare to the follow-up. Here every dot correspond to one sample, and you can appreciate the difference. They all group together. Oh, me too. Shahram talked about the proteomics, and what we see as well is the cytokine storm at this RNA level, and we can visualize the acute disease and the activation of the cytokine storm in those samples, in those patients. The red is activation, and you can see that the whole pathway, in every node here is red. In addition, we also look, because this is an infection model where the kids are, have kidney problems, so we also look at the renal toxicity and the regulation of the genes that are activated in those patients. In red, it's the same. It's the genes that are activated that are higher in those patients during the acute infection. By understanding that, we know exactly how to treat those patients because we know exactly what gene to target and what gene to inhibit. Then we have new treatment approach, because if we know what to inhibit, then we can use our treatments for different proteins and sRNA that we are actually developing for the treatment of infections, bacterial infections. In LPD, the long protein, DRF7 sRNA, and the IL-1Ra treatments that we just finished the phase II trial now in patients. Those treatments inhibits this excessive innate immune response that I showed you in, that we see in the patients. They inhibit the inflammation and the disease, very interestingly, they also accelerate the bacterial clearance. With treatments we can remove the infection and lower the number of bacteria that the mouse or the patients can get rid of those bacteria. You've seen this one before. We took this molecular discovery all the way to the clinic with this phase II control study comparing the IL-1 receptor antagonist to antibiotics. This is the protocol of the study. You've seen that before. We directly compared five-day treatment with anakinra, which is an IL-1RA receptor antagonist, to antibiotics, and we saw that both treatments were effective to reduce the symptom score, the recurrence rates, improve the quality of life of the patients. Very interestingly, the purpose or the focus on my talk today is the transcriptomic response. We actually saw a difference in the treatment efficacy between the anakinra and nitrofurantoin at the transcriptomic level when we look at those gene that are expressed in the patients. The anakinra was able to really trigger broad inhibition, suppression of the innate immune signaling that is causing the symptoms in those patients. We didn't see that with the antibiotic treatments. To conclude, we can apply these techniques to study all different things. Febrile neutropenic infections, but also the bladder cancer patients, treated with Alpha1H that Farhan is gonna talk about. Patient with Bartter syndrome that are treated with anakinra. The patient with cystitis, also treated with anakinra, and also all the animal models and the treatment effect in those. Farhan. Thank you. Thank you. Thank you very much, Ines. Yes, as she mentioned that, we explained the proteomics and transcriptomics in the infection and cancer biology. I will go more into the detail that with the alpha1-oleate how what type of response we get when we look into the whole transcriptomic of all the patients and compare it with the untreated patients. Here what you are seeing is that if you look in the beginning that alpha1-oleate treatment, which is compared to the placebo treatments. What we did was that we had all the patients with the tissues which have which were treated with alpha1-oleate, and the tissues from the patients which were without the treatment. Then we compared the whole transcriptome of both of the groups. As Ines mentioned, there are thousands of genes, like more than 20,000 genes, protein-coding genes, and we want to look at what are the actually specific genes which are actually regulated when we give the alpha1-oleate. If you look at the first left slide, this is the volcano plot, and it shows that out of those 20,000 genes, you can see that there's only 2,800 genes which were left and which were regulated. The most important part was that when we give alpha1-oleate and compare it to the placebo, more than 2,000 genes were inhibited. Like the blue shows the inhibition, and there were very few or compared to less than the inhibition which were upregulated. When looking into the greater detail about these genes, like what are these genes and if they are inhibited, what it will cause. What was the most interesting part is that the top functions or the top genes which were downregulated were actually the genes which were related to the cancer functions. Not only the cancer function, but also the cancer invasion and metastasis, all of those were strongly inhibited. By inhibited, I mean if you see the blue color in the low panel, that is the prediction that these functions were inhibited in the Alpha1H treated patients. Also, since this was a bladder cancer study, we looked into the bladder cancer genes that there were a lot of genes which were already reported in the literature that which were associated with bladder cancer. What we see was that if you look at the blue color, the blue again is the inhibition, just like in the volcano plot. We see that all the genes, most of the genes of the bladder cancer, when we give the alpha1-oleate, were strongly downregulated or inhibited, like 240 were inhibited and only 91 were. Since we published a dose-dependent study, dose escalation study, what we see was that at the lower dose, 1.5 or 1.7 or eight or the higher dose, we see the effect, the same effect on the cancer functions and apoptosis, but there was an increase when we give the 8.5, as you can see in the first histogram. We did the gene set enrichment analysis to see if the apoptosis function is itself regulated. What we see was that there was a strong activation of apoptosis in the cancer genes which were treated with alpha-1. On the right side, you can see the TUNEL staining to be experimentally validated that if there is a higher apoptosis in the Alpha-1 we treated, and you can see that the comparison with the placebo, that there is a very strong increase in the apoptosis or cell death. Also, just to summarize everything, we also do look to the pathways that which were the major pathways which were inhibited at lower dose or at the higher dose. We see the same regulation at both, but there was an increase when we do the Alpha-1, when we give the 8.5 or higher dose. On the right side, if you look at the tumor microenvironment pathway, which is a most commonly activated pathway in cancers, you can see that most of the major signaling pathways, like here if you see this is a RAS signaling and other functions, like at the end you can see that tumor invasion and metastasis, these functions were strongly inhibited. Most of the transcriptional machinery was also strongly down. It gives us an overall impact on the, that alpha1-oleate treatment gives, strongly inhibit the cancer functions, increase apoptosis, and which is also in the dose-dependent manner. Next, I would request Atefeh to further present, like we were looking at all the genes, and then she looked into the specific proteins and their effect. Thank you. Hello again. You already heard about our state-of-the-art technology, omics technologies, and now I'm going to introduce another platform that we have here, which integrates computational tools with recombinant protein production and also experimental methods. This support our drug discovery and drug producing platforms. Here I explore biological molecules, specifically proteins, understanding their structure, their function, and investigating their interactions. Here we have an overview of our pipeline. We have started usually with computational tools, mostly AlphaFold 3. I would like to mention that AlphaFold is developed by the scientists who won the 2024 Nobel Prize in Chemistry, and it highlights its impact and its importance. This tool enables us to predict 3D structure of the proteins and also how these proteins are interacting with each other or other macro molecules. Another platform that we have in-house is recombinant protein production. This enable us to produce protein of our interest in-house very quickly. We come from an idea to lab work very quickly because we produce the protein and after confirmation of the identification and also purity, we go to the lab work in vitro studies that some of the experiment already have been explained to you and some of them, which is imaging facility that we have, we will explain to you. Then we evaluate the effect in the cells, and then we go forward to the animal models. We evaluate their efficiency, and also we measure the toxicity and also safeness in the animal living creatures. If everything goes and works perfect, and as is expected, we can go to clinical trials. Here I'm going to give you an example. This is a very fascinating molecule that we have and we work with. This is Lon, a bacterial Lon, which is a protease, and it is very vital for the bacterial system because it's a kinda a molecular machine which degrades misfold or damage or regulatory proteins. It consists of an N-terminal domain which binds to the target and also recognize the target, an AAA domain which use ATP, which is the energy source inside the cells, and a peptidase domain, which is a scissor of the molecule, cut the proteins in small pieces. Then we produce this protein in-house, full lengths, and also different domain of that. We thought maybe we can use of this protein to target one of the most important molecules in cancer, which is Myc. Myc is dysregulated in more than 70% of human cancer. If we see, look at the interaction of Myc and Lon in AlphaFold, we can see that Lon with its N-terminal domain is interacting with C-terminal domain of c-Myc, which is the most important part of c-Myc because it is vital for execution of its activity. If we only modify one single amino acid here by phosphorylation, we can see that the peptidase domain also comes into action and fold over the molecule. Inhibition is not only from degradation, but also inhibiting its activity. If we look at the multimer of the protein, we can see the native protein is binding to the N-terminal domain and it stays there. If we modify the protein by phosphorylation, it goes inside to the peptidase chamber, and it will be degraded. Thank you for your attention. Yeah. I will ask Arunima now to continue. Hello, everyone. Today I would be speaking about our amazing imaging platform, where we have a very advanced microscope with which we shine light using lasers and LED to samples. We see very high-resolution images which help us to analyze patient samples, address disease-related mechanisms, and treatment effects. The technology of imaging has really revolutionized in the last decade, and we are very fortunate to have access to all these advancements that allow us to see or visualize molecules of interest in very high detail. With that, I'll give you an example of a drug candidate, Alpha1H, which is here, the constituents of the complex is shown in the peptide constituent is shown in green, and the lipid constituent is shown in magenta. The picture on the right shows how both the constituents are present inside the cell, and shades of white shows you their colocalization. What I mean by colocalization is they're present together. This is an extremely important clinical observation because you see this drug as early as 10 minutes has not only come from outside, has interacted with the plasma membrane, which is the periphery of the cell. It safeguards the cell, enters the cell, accumulates in the periphery, and enters the nucleus. The nucleus is like the heart of the cell, and it's able to cross all the way from outside to inside. We are able to see this in very high resolution because of our advanced microscope. Another technique that we use quite often is three-dimensional reconstruction. Here is the same image of the treated cell in which you see the nucleus in blue and the constituents of the drug candidate Alpha1, the peptide in green and the oleate in magenta. This nucleus has been cross-sectionally cut to basically allow the visualization of how packed the complex is inside the cell. To just give you an example, if you think of the nucleus like a cake, we have used a knife to just cut it through, and we want to see the layers inside. You can see that it is packed with the drug. This is also a very important clinical observation because most drugs don't make it to the nucleus. It's very hard for the drug to basically pass all the way from the cell periphery and enter the nucleus. This is a marvelous example of how potent our drug is. Inside the nucleus, this has several consequences for the cell survival. With this, I would show you another way in which we can visualize the uptake of the complex inside the nucleus, again, using three-dimensional reconstruction. Here we are seeing from the top. On the left you see that the nucleus is shown with a solid fill, so you don't really see the inside. On the right I have made the nucleus transparent. You can actually see how the drug is inside and how it is basically entering from the periphery. This is an example to give you that what we can actually see with these kind of 3D reconstructions and learn about the mechanism of action of the drug. We wanted to also give you a flavor of a very fantastic study that we are currently doing, where we are trying to understand how cancer cells are detaching and dying. Towards that end, the image on the left, you see that if we just add PBS, there are just a few spontaneously detached cells. With the drug candidate, you have humongous shedding of cells, which we can visualize, and we can actually study the mechanism of detachment. On the right is an EM or electron microscope image that a lot of people show, and this is the kind of resolution that we can attain with our in-house instrument. With that, I really hope that I have convinced you that this is a very versatile technique with which we can understand how drug candidates or molecules of clinical importance enter the cell and learn about their intracellular life and their dynamics. Thank you. Thank you so much. You may wonder, what does all this binary, all these molecular tools and this advanced technology have to do with clinical trials and commercialization of drugs? We would like to emphasize that modern medicine needs these types of tools. We have been pioneering in some areas the use of these tools for the clinical trials. Shahram, Ines, Farhan, you described the use of these tools in the clinical studies. I think one of the reasons why we publish so well in international journals, publish our clinical studies, is because there is the strong clinical observation of effect in the patient. That's at the core of every clinical study. We can answer how much. We can quantify the disease and the response. We can also, to some extent, ask why, what is determining, which molecules are determining. It also means that we can tailor treatments in the future to the disease, because we understand a lot. Of course, never enough, but we understand a lot about the diseases that we study. We are also seeing, talking about the advancement of partnering and the advancement of our clinical trials. We're seeing that we become interesting to the rest of the world because we have those tools. Not just doing the clinical studies, but actually having the molecular tools that very few people use gives us an advantage and makes us visible as a futuristic organization as well. Before I hope you all have lots of questions. Just to summarize, you know that our overall goal is to reach the market with the phase III-ready assets that we have, drive the clinical development of the preclinical portfolio, which now is quite big. 180 patents is the latest number. We are looking for financing and partnering to solve financing and also access to the market in the future. With that, we would like to stop the presentation and invite questions from all of you. Who would like to start? Yep. Wait. Please feel free to just speak in the microphone as well. It's nice when we recognize who you are. We have a question on the chat here. What limitation currently exists with Alpha1H that prevents it from achieving a 100% complete response? How unique is the ability to quantify the treatment effect in this way, and how does it influence commercial discussions with potential partners? A 100% complete response rate, I think, does not exist for any tumor, because a tumor is a mixture of cells of different malignancy, and also there are factors in the host that will determine. What we can say from the published studies, and Ines, you know the statistics, is that the response rate of the tumors in the patients that we have studied is very high. There is a measurable significant response in over 80% of the patients who have received the higher dose, and also there is disappearance of certain tumors. I think one of the goals of the phase III study is to establish the sort of called complete response rate, comparing Alpha one to other standards of care, and we very much look forward to doing that. Yes. There's another one. In what company is the patent for the Lon molecule? It's in Linnane currently. All of the discoveries that we make are made and patented in Linnane. Hamlet is dealing with drug development and commercialization. Linnane is dealing with discovery and science. This is normal. For the future, depending on financing and resources, molecules can be moved to Hamlet or to other partners. Yeah. By the country you never really know. Hi. Hi, Catharina. Tim here. Hey. [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Foreign language]. Do you have any information about the recurrence rate after the Alpha1H treatment from the phase II study, or will it be publicized? This is also a technical question to a large extent because in the first study we were not allowed to follow the Alpha1H treated patients. They were immediately after TURB, they were put on standard care, which means that we don't have a clean follow-up endpoint. This is also a goal of the phase III to have a longer follow-up. [Non-English content] This will be addressed in the press release form and in the relatively near future. All right, we have another question here. With Alpha1H showing effects through repeated rounds of dosing, is there an expectation that patients potentially could remain in rounds of treatment with Alpha1H instead of progressing to TURB? Yes, that's definitely what we are thinking about. I mean, the clinical data needs to be there. It's the role of the authorities that you have to do things step by step. Sometimes we wish we could do everything at the same time. This is within grasp. Yes. Another question here in Swedish. Will the study protocol for phase III be made available somewhere? Could you show how it's thought to be done in a monthly investors meeting? Yes, that's a very good idea. We're just waiting for a few sort of few critical steps and then we'll be very happy to share the protocol with the investors. The protocol design is finished, but there are some formalities around it. There's a question about the due diligence. I perceived it as the DD that it was ready. Is it wrong? I think we already discussed that. Yeah. All right. Could you comment on the systemic data from the recent patent and how it potentially relates to the design of the phase III protocol? The most recent patent, I think, is one that is related to animal models of colon cancer. What is interesting there is that, again, you're here as well. You did these 40 very long studies of per oral treatment, in this case with BAMLET, but I mean, it's also relevant to. The outcome there is, to our surprise, that there is not just local effects on colon cancer, but also effects on other types of cancer in the periphery. We are not quite sure how that works, but the paper has been published and that's the basis for this study. It's very exciting. Another question here from the chat. Thank you for the presentation. With this amazing technology, do you get benefits in phase III? Fewer patient? That's a great thought. It is not directly communicating, but because of the technology, we are becoming interesting for key opinion leaders in the world who want to work with us to get more data out of the patients that they treat you. I think there will be benefits also in terms of the clinical trials. There is a thank you for your hard work. It is highly appreciated. Thank you. How is the partner negotiations going? Can you specify a rough timeline going forward? I think it's outlined in the letter of intent. I'm sorry, but you know that we cannot comment beyond what is already published. [Non-English content] Catharina. [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] Yes, [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Foreign language] [Non-English content] [Non-English content] [Non-English content] [Non -English content] [Non-English content] [Non-English content] [Foreign language] All Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] [Non-English content] That's a great question. I keep answering, does anyone else want to comment? I mean, we have been approached by leaders in the field of urology because this combination of molecular data and clinical trial setup is not very common in the field of bladder cancer. I mean, we could, Farhan, you're an expert on biomarkers and risk assessment, and we could spend time using all this molecular information to do that kind of work. Our intention is to drive the treatments as fast as possible. I think there will also be papers in parallel on biomarkers. With the omics data, you get so much information that the traditional biomarker concept becomes a bit old. You know, we can define as Farhan and Ines both did, we can define profiles of these diseases. The cytokine storm, I don't know how many hundreds of immune molecules are overactivated and you have the cell death response, for example. Arunima showed you the cell shedding. There is a rich flora of these wonderful parameters, you know, that I think whether it makes us more attractive to partnering, we've been talking to quite a few companies, as you know, over the last year, and they have largely been very congratulatory in terms of this technology part. It's often a question of how well it fits with their own development strategy and it's hard for me to give you a good response to that. I think it is one reason why we are so visible to people in the industry. Yeah. [Non-English content] "Is the idea that the infection molecule should be used in combination with each other?" Any comments? We haven't. For cancer, we have done combinations with bactovacin and other things, but not for infection. Yeah. Yeah. I mean, combinations with, if you, if you think of a more severe infection than cystitis, so a febrile infection, I think testing would be in combination with antibiotics before you can go to the testing of the drug alone in severe infections. But this is our goal. Mm. Hey, Catharina. Peter here. Hey, Peter. Yeah. Can I turn him on? No, I think, he must have been thrown out of the meeting. Okay I think for some reason. No, he's here. Where? Oh, there he is. Peter, you are muted. I'm sorry. Okay. We have to go on. Is there any question? Yes. Is there a INN name for Alpha1H or is it coming up, INN? Yeah. This of course is a question that we have discussed. We are aware of the rules for naming molecules. No, we're not there yet. Um. Oh, Alpha Tide. That's a good one. Thank you very much. That's a great suggestion. I think that was all the questions. Again, we really appreciate your involvement and your willingness to come with, I mean, with the questions and also the dialogue with us. We promise to come back soon with a different digital meetings so you can get more information about what's happening. Thank you so much. Thank you, [Samsung SM], for telling us that we do great work. Take care. Take care. Everybody says hello. Bye-bye. Bye. Thank you. Bye-bye.