Good afternoon, everyone. Today, I wanna talk about new fusion between medicine and AI. Let me start my presentation. About 14 years ago, at the time of the 30th anniversary of SoftBank Group, we announced a new 30-year vision. At that time, Twitter also just started. I used that Twitter and asked people: "What is the saddest things in life?" Actually, I get about 10,000 reply in a day, and as a result, death, loneliness, despair is the saddest thing in life. The cause of death in Japan here, back then in 2010, biggest cause of death was cancer. Thirteen years later, 14 years later, as of today, biggest cause of death stays the same, cancer. Many Japanese and about half of those cause of death are cancers now. Unfortunately, my father passed away last year, cause of death was cancer. He's been doing very well and doing the medical check every almost month and doing the whole body check every six months. Just immediately before the medical check, he was okay. But when he feels a little bit uneasy, then that he was found that he has lung cancer and all over the places of his body, and I was crying every day. The very last days of father, my father, was really difficult, and I don't want you, your family, your friends to do the same experience. Actually, it is happening here and there, and we wanna reduce such sadness. AI is now developing, and AI... Is it the great things for human being, or is it the not great things about human being? In looking at the 14 years of technology advancement, especially these days, AI is developing dramatically. For example, total amount of data in 14 years dramatically increasing. CPU, GPU, processing power also accelerate tremendously. Generative AI, especially ChatGPT, last year, was used, by many people. I myself is also the heavy user of ChatGPT, and it is great. GPT-4 now is already passing, medical doctor exam in United States, and about 60%, is a kind of a threshold for passing the medical exam. Eighty-seven percent, GPT-4 is already achieving for passing the medical exam. In this area, in this aspect, GPT-4 is already smarter than human being, or average human being, I would say, because average Japanese average human being cannot pass a medical test. I cannot pass a medical test. And in that agenda, in that theme, GPT-4, AI is already exceeding human beings' level, but this is just the beginning. And now AI becoming AGI to ASI, and I will talk about that in a later slides. And in, when that time comes, there will be a great, a big change. So, we want to reduce the sorrows to maybe not zero, but to reduce as much as possible. That's the kind of my feeling, our feeling. And here we have, medical AGI, and we are looking for many companies, and I searched for it in US. We found one, Tempus. Tempus, actually utilizing AI to support the cancer treatment, and about 2,000 hospitals in the United States that the service has been provided by Tempus. This, gathering with them, we would like to establish a joint venture in Japan. That is about the announcement today, and the company name is the Tempus. What is, Tempus like? Eric established Tempus eight years ago. This month, the company, it was listed in NASDAQ in the U.S., $60 million-$70 million, I think, a market cap. Revenue is growing rapidly. I believe it's gonna be $100 billion pretty soon. They're providing three products: genomic testing, medical data aggregation and analysis, and AI insights and therapy selection. So recommendations of the therapy and treatment are given to, doctors. ... on real time. So those are the product offerings that Tempus is providing. What is cancer? There are normal cells in human body, and all of a sudden, cells get mutated. Then cancer cells are generated. What is cancer? In a word, genetic mutation from normal cells to cancer cells. So the mistake of the DNA copy, if I may, is leading to a cancer. And by our DNA, maybe we can find the treatment for the cancer. Let's say, lung cancer patients are there. Combination of genes, if there are different combinations, that could be a result of a mutation. Millions of patterns are there. Even within the same lung cancer, there are different kinds of mutations. So the most advanced genomic treatment is to analyze the mutation and patterns of mutation by using AI. If you can, look at a characteristic of a cancer, that could be helpful. That's exactly what, Tempus is doing. Tempus, not only it does genomic testing and the test results, but also they have a data of clinical data, genomic data, pathology data, image data. Different kinds of data or multimodal data, is what, Tempus is using for analysis, and then provide recommendations of, most optimal, treatment to, different, patients. Of course, decisions should be made by doctors and patients and patient's family, but the data, based upon informed consent, is provided by Tempus to doctors and patients. In fact, data from the 2,000 hospitals are stored in a database. EMR is, fragmented. It's the difficult and almost impossible to have a standardized data, because different, hospitals have different, systems. It's difficult, almost impossible to change the different systems. Currently available EMR can be used without burden on hospitals and patients. Tempus provides Adapter, so that currently available EMR can be stored in Tempus, and Tempus, using the central repository, the data is analyzed. Of course, paying attention to privacy, there is a filter in place to de-identify the data. De-identified data is analyzed, and analyzed data will be sent back to hospitals in real time. Based upon the data sent back to hospitals, the hospitals can utilize the data for development and research or even therapy. That is the service proposition only Tempus can provide, and about JPY 300 billion is invested. It's been eight years since inception, and they have invested in the system creation and the repository position. Like I said earlier, the company got listed in NASDAQ. I think it was two weeks ago. With that technology, with that mechanism, and with the personalized data analyzed in the States, can be really utilized as an asset in Japan. With AI, most optimal therapy selections A, B, C can be recommended by Tempus. Let's say the drug C can prolong life longer than others, but there might be some side effects. And drug A is like that, and drug B is like that. So depending on and looking at the scientific data, then doctors can make a decision based on informed consent with the patients. So, Tempus can provide the data and the insights to doctors and hospitals for better decision. Whatever under development can be accessible to hospitals and doctors, because based upon informed consent, Tempus can provide opportunity for doctors to get an access to drugs or treatment under development. In the States, like I said, provide genetic testing services. And next generation genomic testing and clinical data delivers 96% of patients presented with the clinical trial options. At least, patients gone through Tempus genetic testing, most optimal treatment options are presented to those patients. On US average, it's only 27% in the US. Even with a genomic analysis, in the States, only 27% of patients were presented with a clinical trial option. But in the case of Tempus, thanks to multimodal data, and with that matching capability, 96% of patients were presented with a clinical trial option, which is really revolutionary. So 7.7 million cancer, cancer patients, about half of the all cancer patients in Japan, the records of those patients are now what Tempus has. And the 2,000 hospitals are the number of hospitals are with the Tempus network. Even different kinds of systems, thanks to the adapter, 1 million image data, 0.97 million pathology data, and 0.22 million DNA and RNA data, 96% of patients were presented with the most optimal option, thanks to that capability of Tempus. This slide shows competitive comparison. Scientifically, with AI, based upon data, in the States, it's really revolutionary. Only 27% of patients who are presented were the most optimal trial option, like I said earlier. Most hospitals have EMR, but the systems are not integrated. 65% of academic hospitals and 50% of oncologists use Tempus. By the way, AI-enabled data analysis doesn't mean extra cost to hospitals or extra cost to doctors. Extra burden, zero. Why? Because like I said, currently available EMR can be used, thanks to the adapter provided by Tempus. No cost, no burden, so everything is good. So how does Tempus make money? Because of the vast amount of data, the data is the asset that can be utilized by drug companies for their development purpose or research purpose. By providing the data to those drug companies, they can get money. So in fact, that's good for drug manufacturers because they can save time for drug development, and it costs them money and time for drug discovery and drug development. But with Tempus, they can save cost by 20%-30%. Even paying money to Tempus, drug companies use Tempus data for their development purpose, which is great for both Tempus and the drug companies. Tempus CEO Eric Lefkofsky, he was supposed to be with me today, but we had a COVID test. And in the morning, we found out Eric was positive, so he went back to hotel. But he is good in shape, good shape. So he's gonna join us remotely, but let me share with you a short video before introducing Eric. We all know how disorienting it can be when you're diagnosed with a disease, either your own or that of someone you love. It's like walking in a forest where the way feels lost. Seas of trial and error, oceans of opinion. But what if there was a different, clearer path? One forged by the millions who have come before. Today, an unprecedented amount of data is being contributed in near real time by physicians, researchers, and patients around the world.... Tempus is at the center of this movement. We have developed novel technology that collects, structures, and analyzes vast amounts of data, clinical data sourced from electronic healthcare records, imaging data from pathology slides and radiology scans, molecular data generated at a scale that was unimaginable just a few short years ago. It's our mission to make all of this data accessible and useful. Merged with the power of AI, we have developed a platform that is designed to accelerate the discovery of novel targets, predict the effectiveness of treatments, identify life-saving clinical trials, even diagnose disease earlier. This groundbreaking technology is being used today by thousands of physicians in oncology, cardiology, neurology, and other disease areas. But this is just the beginning. Through AI-enabled diagnostics, we hope to route every individual to their own unique and optimal therapy, and help shape the treatments of tomorrow. Imagine a world devoid of the diseases that have plagued us for millennia. Imagine prolonged life expectancy. Imagine the end of trial and error. This is data-driven precision medicine. This is the future of healthcare. This is Tempus. Eric, go ahead. Thank you, Masa. Thank you. I'm sorry, I can't be there in person with all of you. Out of an abundance of caution, I'm staying here. But I did wanna quickly introduce Tempus. I started the company about 8.5 years ago after my wife was diagnosed with breast cancer, and I was perplexed at how little data was a part of her care. And so I got focused at that time on the idea that we could... The underlying technologies that were evolving could be harnessed to basically contextualize diagnostics, because at this moment in time, we can now structure and harmonize vast amounts of data that historically has been siloed and unstructured, which is what's necessary to bring any form of artificial intelligence to healthcare. To do that, all of these background technologies, many of which SoftBank plays a leading role in worldwide, like low-cost cloud computing and molecular profiling, all kinds of imaging technologies, are necessary in order to structure and harmonize clinical data, which is at the heart of understanding what drugs people are taking and how they're responding to those drugs. We got focused on the idea that artificial intelligence would come to healthcare first through diagnostics. Diagnostics sit at the heart of almost every major decision that a doctor makes. When a patient gets sick, they go see a doctor who orders a blood test, or a CAT scan, or an MRI, or maybe a genomic test, and then they make a decision how to treat that patient. We thought that if we could contextualize those diagnostics and basically personalize them for the patient for whom they were ordered, we could infuse the benefits of artificial intelligence into the healthcare system, both in the U.S. and around the world. Here's a short video. Open Samantha Johnson's report. Please select from the following complete reports found for Samantha Johnson. Can you confirm her probable BRCA2 germline mutation? ...In order to bring those kind of technologies to the market, you have to collect vast amounts of multimodal data and put it in one place. You can't have just a little bit of the data that a patient needs. You have to have all the data. You have to have the clinical data, the imaging data, and often the molecular data. And so Tempus has built a platform, an operating system, to put all that data in one place so that physicians can make data-driven decisions, and life science companies, in particular, biotechnology companies and pharmaceutical companies, can do better research and make better drugs. Our database, if you forward one, in just a few short years, has become multiple times larger than any public data set we know of. In the United States, there's a data set called the Cancer Genome Atlas, and as you can see here, in just a few short years, Tempus's database has become 50x larger. We have 7.7 million patients that we have brought in. We've de-identified roughly six million of those, and a significant percentage has imaging data, samples that we've sequenced, and at the very bottom of the funnel is this incredibly rich multimodal data set that can be used to help drug companies be more efficient. We're also focused on helping doctors be more efficient. We want our tests to be super smart. We want to make sure that every decision a doctor makes is the right decision. We want to help good doctors become great doctors, and great doctors become superhuman. And so we embed AI and the benefits of big data into every report we generate. Not just to help patients get on the right therapy, but also to find a clinical trial that might be beneficial to them, which Ryan will talk about in a few minutes. And behind this technology, we have created this self-learning system, and that's the key to any form of artificial intelligence. The system has to learn and get smarter. And so we built a system, for example, where we can track every drug that patients are taking when they have similarly situated patients, and then we can see how those patients did, so that when a physician makes a recommendation, they know that people just like the patient that they're talking to, have done very well when they took that drug or this drug. And so we help take the guesswork out of treating cancer patients. We also take all of this data and make it available both to our hospital partners and to life science companies. We want to make sure the entire system is as efficient as it can be. We hate the idea of wasting money. We don't want pharmaceutical companies to spend a huge amount of money, I think roughly JPY 150 billion, and then have a failed drug. We want and we don't want it to take 10 years. We want to shave two or three years off that cycle. We want to shave 20% or 30% off the cost, and the only way to do that is to put data in the hands of everyone who's doing research, whether it be discovery or development. Up until now, we've been focused on just the U.S., and we're excited today to announce our partnership with SoftBank, who's the ideal partner to bring Tempus to the Japanese market, which happens to be the ideal market. There's no reason that Japan should not lead the entire world in terms of precision medicine. You have incredible hospitals, incredibly talented people, and if we can help bring the tools that are needed for artificial intelligence to make its way throughout the system, you can lead in this category in a way that is absolutely unimaginable, and we're excited to start that journey. But it isn't just enough to have lots of data. You have to also create a sustainable business model around that, and we've broken our business model into three parts. We sequence patients and make sure that they have the necessary molecular data and insights they need to get the right therapy, which Masa talked about a few minutes ago. We also then retain large amounts of de-identified data that's appropriately consented, that can be used by drug companies and academic researchers to make sure that they're making the best drugs possible or coming up with novel breakthroughs. And then finally, we work on a series of AI applications that we can deploy in real time in the clinic to close care gaps and to make sure that every patient is routed to the most optimal therapeutic path, which Ryan will now discuss. All right. Thank you, Eric. How do we produce the genomic data or the multi-omic data on each individual patient case that we're analyzing, to produce actionable results for physicians and for their patients? And so with our testing approach, we've actually published on this, where by organizing the clinical history and providing broad genomic profiling, we can provide more actionable results than alternative approaches. And so when you think about our testing menu, isn't it just enough to have one test, but to have a variety of different test options for patients, not just a solid tumor test, but we also have a liquid biopsy as well. And we recently launched a new test called xM, which is our minimal residual disease test, to capture other parts of the patient journey. And so we announced this data at ASCO a few months ago, and one of the things that xM provides is that it allows us to think about monitoring disease in the early stages after surgery, but also to help with treatment selection with our variety of different assays that you can see in the middle of this page... But after those treatments are selected, the job isn't over. We really need to equip physicians with the necessary data to monitor and to follow those patients longitudinally, to track how are they responding to those various targeted treatments or those immunotherapies over time, so that we can capture the clinical outcomes and organize that data, for them as well. And so by providing that suite of services, we can now collect the necessary multimodal data that can also unlock new, sort of research discoveries and new opportunities for cancer patients that have severe unmet need. And so if we think about sort of our data business, it's not enough to just think about the treatments of today, but how are we going to develop and empower the drug companies that are developing the treatments of tomorrow? And so we have focused a lot of time and effort on leveraging de-identified datasets at true scale, and the tooling necessary to really accelerate research for addressing these unmet needs that we see in everyday cancer care. Some of the tooling that we provide can really compress and accelerate the time to get to insight, whether those insights are coming from preclinical discovery, whether you're thinking about target populations or sub-diseases within a cancer population, but also to make sure that the trials that we're designing are actually going to improve the success rates and get to market, so we can address that unmet need. Providing the tooling to simulate some of these benefits that we see in the real-world data can really help drug companies be more successful and more effective. And so with this kind of data connectivity now flowing through our various two businesses, our genomics business, our data business, we now have the necessary infrastructure to leverage and to launch our third business, which is AI applications, and truly bring AI in the palm of physicians' hands to make the best decisions possible for their patients. One application that we have already launched in the U.S. that is gaining significant traction is really around how do we run AI in the background to analyze and match patients for the appropriate inclusion and exclusion criteria across a network of hospitals that we already have launched in the United States. And so typically, this process takes about six to 12 months to identify a clinical trial site, to open up that site in six to 12 months. Now, with our approach in using AI to screen these patients in real time, we've negotiated with these sites to sign a standard budget, a standard rate card, and a central IRB to take that 12-month process and compress it to 14 days. That compression is essential so that you can provide more treatment options to patients, because it has to fit within the treatment window, because patients cannot wait 12 months to get on a clinical trial. The second application in sort of providing better options for patients is to ensure patients are undergoing and following clinical guidelines. This operating system analyzes all of the data that the hospitals that we work with to uncover sort of certain clinical care gaps, and identify and notify physicians around things that are already proven to produce benefit for their patients. In everyday care, things happen. Patients are coming in and being referred, and we want to empower these physicians to make sure that these things are identified. Oncology is one of our first areas that we've been focused on in the U.S., but the problem doesn't stop in oncology. We think about precision medicine, and we think about these other diseases, but we really focus on identifying the appropriate diagnostic in each disease, whether that disease is neuropsychiatry, whether that's cardiology or radiology. We think about the diagnostic that is the most essential in driving the treatment decisions for those patients, and we organize the clinical history or the contextual information around that diagnostic to make it intelligent. And that, in our mind, is the approach that we can really pursue, not just in the U.S., but globally with partners like SoftBank, to bring this to the Japanese market, to have the most impact on patient lives. And so in closing, you know, we really believe this approach. It can have the biggest impact, not only in the U.S., but we believe that the Japanese market is primed to really accelerate and really leverage these technologies in true partnership with the physicians that work in the Japanese market. And so I'll leave you with this patient story. I did a first sequencing when we found out about my cancer, and that biopsy did not reveal any gene mutation, so we were going with a standardized chemotherapy. So I did two chemotherapy treatments. The first one lasted for six months. It was really hard. At first, it really responded really well. The big tumor started shrinking right away. So after three cycles, we did another cycle of imaging. Unfortunately, the PET scan showed that the tumor stopped shrinking and another tumor was progressing. So it was a big shock. We couldn't explain why. A friend of mine who works at Tempus recommended that I do a second sequencing to learn more about my pathology and my tumor in particular. My oncologist ordered it, and I had a gene mutation that we didn't know about at first. The gene mutation that I have, it's called PIK3CA. It prevents certain chemos from entering into the tumors. It's actually a reason why the first chemo is not working. So I started a new chemotherapy. So with the second chemo, I think it's a little easier on my body. I'm still going through the tunnel week, but I'm stopped losing hair, and I think it's been more manageable for me. After a few cycles, we noticed that both tumors in the breast were shrinking, finally. It was such a big relief. Because it was working, I was a candidate for a double mastectomy. I had double mastectomy, and then I continued the chemotherapy, and that's been almost a year. I think that if it was not for my husband, for my family and friends, I would have not make it. I am so thankful for Tempus, because without revealing that I had this gene mutation called PIK3CA, I would have been kept in the dark, right? I would have not known what was going on in my body and why my body is not reacting to the chemo that is supposed to treat me. Thanks to Tempus, really, I was able to move forward and see the light at the end of the tunnel. All right. And so these patient stories are essential, and this is why we're all here, but we're really excited to partner with SoftBank in making SB Tempus possible. Thank you. Thank you. Thank you, Ryan. You just saw the video. Because of thanks to Tempus service, there are many people who are actually living longer in United States. So the latest edge treatment for cancer is genomic testing, and developing drug based on the genomic testing and using those drug for the cancer treatment is a kind of the way. However, 30% of the cancer patients are using taking this genomic testing the day one after the hospitalized. But in Japan, in other hands, only 0.7%. So there are about 1.7 million cancer patients are found, and about 1.5 million genomic testing has been conducted. Japan is only 20,000 cases a year. That means, even as of today, patients can only undergo a genomic testing after exhausting standard options. So you have to go through so many standard treatment after you are diagnosed as cancer, such as radiations or drug, and very end, in the first time, patients can take genomic testing. I don't understand why that is a kind of a process we have to follow, but this is the current process. But going forward, genomic testing should be the first things to do after hospitalized, like doing in United States. Not doing any genomic testing and start treatment is not really the right way to go through, from my understanding. After this presentation, we will have doctors who are expertise on genomic treatment. There are about 13 key hospitals in Japan for the cancer treatments. These 13 hospitals, leading doctors that I was speaking to them, talking about this service, and they said about 13 of those hospitals members are very much supporting this idea, and some of them are joining us after this presentation for the panel discussion. This genomic testing, not doing it in the very end, but actually bring it forward, and not only 20,000 cases a year, but we should do like 1 million cases a year. Then, we believe that we'll be able to become about the same level as United States, because within the three years course, and in the beginning of the treatment, we do need to have a genomic testing, like do, does in the United States. So we would like to make it 50x from the 20,000 cases a year for the genomic testing. That's something that I hope for. And Tempus is providing such genomic testing, and also, not only the genomic testing, but also imaging data is available in hospital or any clinical data or the EMRs. All those information can be aggregated and do the AI analysis. That service is also available in United States. As a result, there will be optimal options for the treatment can be recommended to doctor, so the doctor share with patient, and that's something that I would like to start in Japan. Hopefully, if we can start within this year, something that we can do from those three factors, that we would like to start within this year. Like I mentioned earlier, in Japan, the hospitals in Japan, they have different types and formats of EMRs, and that's kind of closed-door information. So for these key 13 hospitals in Japan who are leading cancer treatment in Japan, without changing their system, but using this Tempus adapter, that we'll be able to create the integrated database. So there will be no burden for our hospitals. So with these key 13 hospitals, that's gonna be already a great deal. And not only one key hospital, but even 13. Tokyo University, Kyoto University Hospitals, Keio, and there are 13 key hospitals for cancer treatment, and that's a big, big step that we'll be able to make this time, and that to be analyzed by AI. In addition, we would like to expand that to 300 hospitals, to 500 hospitals, so that we'll be able to cover 50% of the cancer patients in Japan can be someday analyzed in a common database, and that's something that we would like to realize in Japan sometime in the few years. I think we can do it, because there will be no burden for hospital size, there will be no cost, additional cost for hospital, there will be no technical effort that they have to do. They are all solved by adapter in free of charge to hospitals. So I believe this can be a popular service, and that's something that I am very much determined to do in Japan. In the sub... August the first is the expected start of operation this year. Our capital is with JPY 30 billion, and the investment ratio is going to be 50% from SoftBank Group and 50% from Tempus in United States. In United States, there are services that are already provided. First, those testing services equipments and the system that are used in US is going to be used. Also, I mentioned the 13 key hospitals that I'm for the first step, but not only that, but also 7.7 million cancer patient data will be also utilized in Japan as well. So it's not starting from scratch, but from the beginning, we'll be able to utilize those 50% of the cancer patients in United States. Data can be real time used for analysis in Japan. So like, stomach cancer is stomach cancer, lung cancer is lung cancer, and there are many Asian living in United States. Out of the 7.7 million, there are many Asians as well, and that data can be utilized from day one in Japan, which is a big, big first step. In addition to that, we will have a data from those key 13 hospitals in Japan, integrated and analyzed by AI. So that's a rocket start that we'll be able to make. The U.S. is very much advanced, and most advanced around compared to the rest of the world, and this is the first time going outside of United States, and the first country next to United States is Japan. So U.S., 2,000 hospitals are already connected, so 50% of hospitals are already connected, and we would like to also make that happen in, in Japan as soon as possible. Not only the genomic data, but also imaging data, CT scans, MRIs, and also the pathology data or, clinical or diagnosis, those can be also available in real time, thanks to adapter. So big the data, data basis, that can be from the day one, utilized in Japan. So we believe we can integrate all the wisdoms, not only in Japan, but also in United States. Together with the healthcare professionals, we believe, we'll be able to achieve the advanced AI technology with AI medical, expertise. Why AI? Why ChatGPT? Why Gemini all of the sudden becomes beneficial for people? In the past four years, computing power became 10,000x. Number of chip became 10,000. Capacity per chip become 10x, and also transformer in the AI model became 10x in four years. So 10x, 10x 10, so 1,000x. And in four years, generative AI computing power became 1,000x. And next four years, same things happens, so that's gonna be another 1,000x. And following four years, it's gonna be another 1,000x, and next four years, it's gonna be another 1,000x. So let me say that this is going to be the kind of case, even two, three years behind or something, but now it's already the medical test exam can be passed by AI. If you imagine 1,000x of such intelligence, and 1,000x 1,000x is a million times, and million times of 1,000x is a billion times. So by watching three Olympics game, AI capacity and capability become one billion times. So the medical exam level of the intelligence is gonna be one billion times. That is ASI, and ASI, or I say AGI, is the something similar or equivalent to human beings, and ten thousand times from there, not only medical, but also productions or logistics or in any industries and segments that I believe there's gonna be ten thousand intelligence available. But speaking of medical or sector, that's to be 1,000x to million times to billion times. You have to use it. You have to use this technology. You have to take an advantage of this technology to make sure that, beneficial for the human being. People may scare that it is really, beneficial for human being, and but I think, at least, those families that who lost, beloved members because of cancer or high blood pressure or many, diseases, that I believe that the AI will be able to reduce the people's, sadness and save people's life. I think this is beneficial for human. That's something we have to use it, we have to use it. So, medical science experts is, are here. We are experts in data science, medical science, and data science both. We-- This is not the discussion of which is right or wrong, but the medical science and the data science, that to be fusion integrated together, medical ASI world will be created. With the human's wisdom, there are many difficult diseases that not been cured, and maybe, with the, technology's capability, we'll be able to, save those, lives. And also, we will be start having a life without health issues and also staying healthy at any age, which is a great news for human. It may not be zero. Of course, it may not be zero, but still, we'll be able to reduce those. So even a little bit of a reduction of the, sorrow is something that, we should be aiming for. And for that, I believe that, data science and medical science should be utilized. So information revolution is not leading human being to the disaster, I believe is leading to the people's happiness. We are seeing this AI, ASI, and AGI, but the biggest philosophy is that we wanna bring happiness to people, and that's the reason why we are here to work on this. Thank you very much. Thank you very much. We'd like to start a panel discussion with medical leaders in Japan. Please bear with us for a moment for some preparation. Thank you very much for waiting. Now I'd like to start a panel discussion on the theme of the approach to cancer treatment in the age of ASI. We'd like to ask Ms. Madoka Mori to facilitate the session. She is a medical journalist who has several experience, of facilitating medical symposium. My name is, Madoka Mori. After hearing the presentation, I am very much excited and overwhelmed. For patients, what would be the best, medical treatment? Each and every patient, there is an opportunity to provide, most personalized, treatment to a patient. So we're gonna hear a lot more about what would be the best cancer treatment. We are going to have a panelist for today. First, Mr. Takeshi Sano, hospital director, Cancer Institute Hospital. Very nice to meet you. Mr. Yuko Kitagawa, Keio University professor and chairman, Department of Surgery, Keio University School of Medicine. And Mr. Katsutoshi Oda, professor and director, Department of Clinical Genomics, University of Tokyo Hospital. Mr. Eiichi Baba, professor, Department of Comprehensive Oncology, Graduate School of Medical Science, Keio, Kyushu University, excuse me. And Yuichi Ando, Department of Clinical Oncology and Chemotherapy professor. And remotely, we have, Mr. Manabu Muto, head of Cancer Center, professor of medical oncology. And Chief Operating Officer of Tempus AI, Ryan Fukushima. And Masayoshi Son, chairman and CEO of SoftBank Group, who just gave you a presentation earlier. Very nice to meet you all. Talking about cancer, as described in the presentation, for over 40 years, this is the leading cause of death, and over 1 million cancer patients are being diagnosed. At the moment, the way forward is how we can coexist with cancer. But eradicating, eliminating cancer can be possible. That's what I feel after hearing the presentation. So again, let me start by asking you, what's your feeling or observation after hearing the presentation? Evidence is very important, and if you can utilize the vast amount of data, what expectation can we get? Dr. Sano, please. Mr. Son's presentation is wonderful, talking about the future. If I look back, like you mentioned, 40 years ago, I became a surgeon. Back then, the only thing we could do was just to cut it. Cut a cancer, a tumor, out was the only option, almost. But it's been... we have been progressing in terms of diagnosis and the treatment, but it's been 40 years. It's been a long time. We are trying to build, guidelines-... And effort has been ongoing for 20 years. So compared to that, the progress or speed of the progress in terms of technology is amazing. Looking ahead four years and 10 years, I try to figure out what would happen, like Mr. Son does. What I'm feeling, hearing his presentation is... I think, how we can really, move forward to the future. Mr. Kitagawa, what do you think? I am a surgeon as well, and talking about cancer treatment. In this area, we are seeing a lot of data information building up and up. But reality is, we are not really sure how we can really utilize such an asset and data, especially manpower is far behind in terms of really leveraging such a vast amount of data. And with this technology, that will help us, which is really where I have high expectation. Of course, there are some challenges we need to address, but we'd like to discuss with the experts. Analyzing genes and detecting mutation, when this became possible, it would really accelerate the process of cancer treatment. Mr. Oda, what do you think? With genomic diagnosis, it's been helpful, and it's important to figure out how we can maximize genomic medicine. And the information that we get from genomic medicine is in particular, even after detecting a mutation, an outcome of the treatment needs to be looked back by utilizing a vast amount of data with AI and by adopting data science. So scientific, scientific evidence will be built up, so that we can really utilize it to help cancer treatment. I ask you, Ryan, the vast data sets, not only for gene testing, but also blood testing and everything. I think it, it's significant to have a vast amount of data in a single depository, repository. Essential to bring in this data and have it all harmonized in one common format. And this is the approach that we've taken in the U.S., and we have worked with over 2,000 hospitals in doing so. But we don't wanna add more burden on collecting this data with physicians and with these hospitals, and so you can allow the technology to organize that information so that you can start to see patterns emerge. And so we've been so focused on, at Tempus, on assembling this data and creating this, what we call this data flywheel, that allows us to collect this data, but by collecting the data, we can add more value to physicians and be a better partner to them because of that aggregation of data. By providing more value, we can collect more data in the process. So, having that flywheel move faster can help the entire industry, and we've been focused on doing that and hope to bring that here to Japan as well. Thank you very much. Mr. Ando, what do you think? No burden on hospital, no burden on changing EMR system, for example. Currently available data is used, thanks to the adapter. That approach, I think, is really significant in the Japanese hospital. Yes, I agree. We have an opportunity to hear a lot, and most of the biggest challenges is how you can enter the data and how you can collect data. I have not had a chance to see an adapter itself, but if that kind of solution is available, that'd be great. But Dr. Baba, how do you think? So data science is something a bit higher hurdle for the medical expertise and difficult to use easily. So with this kind of way, and using the technology, and if you can advance the cancer treatment, that's gonna be great for the human being. Thank you. Thank you very much. Now, we would like to be more specific to each agenda. So in Japan, genetic panel test to check the genetic mutation has been conducted. In this test, in Masa's presentation, we see that there are about 20,000 cases per year. And recently, 60,000 cases, genetic test result analysis was produced, but this is very few and very beginning, and also facilities, institutions are very limited to be able to take this test. To take this test, and timing to take this test, is only when you don't have any standard treatment, or those that who has gone through the standard treatment, when that the people are already exhausted, and so on. And Dr. Muto, I would like to ask you that, this test timing, can we bring it forward, or can we increase the scope of the test takers? How do you think about advantage for that? Yes, originally, this genetic panel testing is to provide the optimal treatment for patients so that we can save time, and also, it's like a precision medicine in United States. And to realize that, this is one of the medical policy, and start this testing. So like Masa mentioned in his presentation, once you diagnosed as cancer, and once that you start taking the drug, then that this test should be done at the same time. However, in Japan, you can only test after you go through all the standard treatment, and the policy making is not right in Japan. I believe that's the way that I should be putting. Because optimal treatment and optimal testing should be done in earlier stage, as soon as possible. For that, we should change the current system and structure, and we can bring it to them as soon as possible. And also, having more data is available and the test result as many possible. Some people say that it's gonna increase the cost, but actually, you'll be able to save the wasteful or not necessary treatment. So that's also the beneficial from the medical policy's point of view. So as a result, I believe this is also the patient's hope and wish that they will be able to take such test as early stage as possible. That's, from the patient's point of view, timing to take the. I I think that we are taking away the optimal timing for all patients to take the optimal treatment. So like Masa said, that we should bring it forward as soon as possible. So I think that we also need to work on to change the policy. And in academic conference over six years, we've been asking to take away these limitations to be able to take the timing of the this genetic test, but there is no scientific base. That was a kind of the argument back, so that we haven't been able to eliminate this limit. Dr. Muto, so bring the timing forward, so not only medicine, but the surgeries or radiation treatments. So that will be another benefit for other treatment as well. Do you think so? Yes, I believe so. Because right now, there are many great drug developed, and we've seen a great response. And also, combining with the cancer immune treatments is already available. So not all the treatments, but, like Dr. Sano mentioned, there are quite effective drug. So those patients who cannot take a surgery, but there are possibility that they will be able to take a surgery, like a conversion surgery. And also combined with the radiation treatment, some of the drug is becomes more effective than before. So as early as possible, knowing the cancer profiling, so that we'll be able to... Because we have a lot of weapons to address the cancer, and so that patients will be able to live longer. And ultimately, we hope that we'll be able to cure this disease. So there will be a strategic treatment option will be available, so that that's gonna be very important for us to take this test. Yes, when you make fight, you don't want to fight when you are all exhausted. And even you're given the weapon, but you cannot stand up and fight anymore. So you have to be full energy to be able to receive such weapon so that you can fight. Dr. Sano? Yes, that's exactly right. But maybe change a little bit of angle, that those cancers found in Japan, those are the early stage cancers, and they may not necessarily the drug, but just taking or the removing those tumors, and most of the cases are curable. So not half, but that's quite many. Those people, once that they are diagnosed as a cancer and then start the genomic testing, it's gonna be quite a budget heavy. So like Dr. Muto mentioned, when you start needing a cancer treatment, they have to be able to take the genomic testing and take the optimal treatment. And once we advance and go into the surgery, but maybe you'll be able to start this medication, then go to the surgical stage. The strategic process may different. So, I am not protecting surgeons, but there are many cancers that can be removable. So if we start doing all the genetic testing for those curable cancers, too, so gradually, not too gradual, but I believe we need to have a phased basis. Thank you very much. Mr. Son, how do you think? With surgery, like Dr. Sano mentioned, there are very small tumor, and you may be able to remove quite easily so that you can cure cancer right away. There are such cases as well, so that it needs to be flexible to address. But at this moment, after all those treatments, in very end of the process, once you are so exhausted and now available for the genomic testing, which doesn't make sense at all for me. So, there are something with this opportunity, that's something that we need to think about. And of course, medical budget is something that we need to also consider from the political point of view and policy point of view. So we do need to do many calculations, but at the same time, this can be a good opportunity that we can we all realize, not at the very end of the process, like, MRIs, CT scans, not the very end of the process, but that's already done, very beginning. So same as that, as soon as possible. First, when you know enemy, you can fight. The cancer is your enemy to some extent, so you have to know your enemy as soon as possible, so that you'll be able to decide which weapon to use. That, I believe, is a basic. So established treatment and the genetic testing, how can we decide the strategy? So timing of those has to be aggressively discussed among medical expertise, I believe. Dr. Kitagawa, right now, this is medical genetic testing is your own budget, right? Right now, our hospital does not do this test, but I do understand there are some demands for it. In our data, hospital data, those advanced cancer, which can be covered by insurance, like Evidence C, D which is outside of insurance coverage, a drug is necessary for those 45% of the patients, and if we try to use this drug, then we got this not be covered by insurance. How are we gonna address that? That's gonna be our next challenge. Technology has been progressing, and the medical field and the scientific and technology field are progressing, but I think they need to discuss more, not based upon the common sense, but more forward-looking, what would be the opportunity or a bigger possibility from different angles. I think those experts in different fields should discuss more. What do you think, Dr. Oda? Yes, ideas about the treatment need to be changed. The way it should be, that kind of idea needs to be revisited. With CGP, for example, those patients need clinical testing, but I think there's a problem of drug loss and drug lag. From pharmaceutical company's perspective, what kind of patients need to be recruited? Of course, patients with some physical strength and patients who have not had a resistance to drugs yet. So earlier is better. Clinical testing themselves, we need to have more clinical testing in Japan and composite or complex therapies treatment. For example, an antibody drug can be combined with something else. If you do, at the end of genomic based treatment, there are some drugs that cannot be available for the patient. So again, early is better, so that we can utilize the currently available genomic testing as much as possible, and also we need to communicate with the companies. Development of drugs in Japan is great thing to do. That's something that we want to communicate with the drug companies. And having a genomic testing information is advantage, because without screening, you have insights about genes and genomes. I think it's very stimulating the medical field in Japan. Talking about clinical testing, finding candidate patients is not easy always. Dr. Baba, what do you think? That's something or that area where data helps. If you can share data by connecting different systems, that would be huge advantage and benefit, don't you think? From a development perspective, patients across Japan, without burden, if you can recruit easily, I think, that would be effective for real-world data. And the patients in remote areas, sometimes difficult to participate in clinical testing, but by utilizing technology and hospital network, I think, we can advance our clinical testing approach to give more benefits to patients. Dr. Ando, what do you think? Panel testing, I think, is available across Japan, but, to the point of Dr. Baba, clinical testing, I think there is a huge, geographic divide, geographic differences. If I may, try to clarify. In the panel testing, even though it comes at the later stage with insurance coverage, patients who still can have access to participate in clinical testing can be saved, but I'm not saying that later is okay. So when a cancer is diagnosed, I think, panel test should be done. Cancer panel testing is not only for selecting drugs. There are some patients that tend to have recurrence of tumors and cancers. Cancer profiling, I think, can be something that we can know by doing panel testing, cost aside. In the future, I think all cases should go with the panel testing. Ryan, setting aside money and budget, but looking at your business model, no cost to hospital, no cost to doctors, so your business model works without asking hospital to pay money. Yes, I mean, that's correct. So we have organized the business in these three different buckets. And when we perform the testing, the comprehensive genomic profiling, in the U.S., we bill those tests to insurance companies, and that sort of coverage pays for the testing service itself. But so much of what Tempus does is more than just the lab test itself. We also will organize the information and make it very low burden or no burden to a physician, so that we can deliver these results that have clinical information and contextual information to personalize those results to each and every patient. And so we've been able to make that work by billing for those testing services through insurance or through government services like Medicare and Medicaid in the U.S. And all of the data organization comes for free with that service. We believe that it's necessary to not just provide... It provides better results, but it also creates that, powers that data flywheel, not so that we can just aggregate data, but also so that we can deliver the data back to the hospitals, so that they have structured, organized information, and they can accelerate their own research efforts even faster than before working with Tempus. If I may, different hospitals have different sets of data, so using adapter, data is, collected in a central database, and through the, adapter, the data or structured data can be, sent back to hospital free of charge, including analysis. Japanese hospitals have, siloed data and, structured data, and, it's very simple. With no cost, with no burden, data can be analyzed and sent back to hospitals. Only benefits, no demerits. So why don't we do it now? Yes. So you may have impression Japan is terrible, but, it's not really not in sync. You register data in the database, but it takes time and cost because there are a, a set, formats, and you need to fill in the, format and register in the system. But the hearing, a Tempus system, and in fact, our team is developing our own system, but if it works, the data can be collected real time, which is great because currently, medical professionals take time and efforts to build that kind of data thing. Speed and hassles can be removed. That'll be helpful for doctors and physicians in hospital. What do you think, Dr. Muto? Yes, since 10 years ago, a different EMR, we tried to integrate and consolidate EMR and including laboratory data, diagnostic data, and genomic data. We have been working on that. We get budget, and we proved that we could do it in AMED, but it was not really appreciated, actually. At the moment, we have worked with 100 hospitals to build consolidated, centralized EMR, but Tempus technology is far advanced. Japanese medical institutions from the perspective of privacy and personal data, so they are very conservative. They are not open to providing data to a third party. So we have to talk to hospital each and each- ... by each, so we need to change the mindsets of hospitals. I think, by leadership of Tempus and SoftBank, I think, we can help changing mindsets of hospital, because, this, effort is for all. In the past medical field, so we put, patients into two groups: standard and non-standard, and we compared with those groups. But going forward, each and every patient personalized, data, and if you utilize each and, every person's data, you should be able to find out similar, kind of patients, so that we can find better, treatment solution. This kind of platform is great, and, the X and digital transformation and, utilizing data is far behind in Japan. This is why we're so excited about SB Tempus, is that we believe that the timing is now and the system is set up, the healthcare system is set up to really take advantage of this AI revolution in healthcare. I think by meeting with the top centers that have already taken approaches to start to organize the information is the first step. Now we just need true partnership with these hospitals so that they have the tools that technology companies like Tempus have invested heavily in building, so that they can use those tools to collect the data at true scale. When you do that, and you can start to create that data flywheel in a way that is really moving fast, then you can start to reap the benefits or sort of from that effort to discover new drugs, to bring better clinical trials to the Japanese market. I think that based on those approaches and some of the changes that are likely to happen, we're very encouraged and very excited about this approach. But after getting the data- So vast data, size, and also the speed, can be a great contributor for Japanese medical industry, and I believe that's something that you're expecting, right? Yes. The diagnosis in hospital and effectiveness of such has been discussed. And yesterday and today, I've been discussing with the major pharmaceutical leaders in Japan, and for them, cancer drug is one of the most important agenda, not only in Japan, but in United States or other countries. They are trying to develop that part. And first, US Tempus, 7.7 million cancer patient real-time data, real-world data, they would like to utilize immediately. Some of the company, companies are already using, but they would like to expand that. So they wanna have utilize the Tempus data as soon as possible so that they can utilize for the discovery of the drug. And this time, by setting up SB Tempus, Japanese cancer data will be accessible. So right now that we can start the US data, but with this SB Tempus establishment, they will be able to utilize Japanese cancer patients immediately. That's gonna be also a great benefit for the drug companies for the drug discovery, and I believe we'll be able to see the revitalize of Japanese pharmaceutical companies. And I think that they should be the a leading company in Asian countries, and so that they'll be able to help support giving a good solution for humans. So those no time lags timely manner that that they can accumulate data and also analyze. That is something... For example, there will be some similar cancer that the especially large in Japanese populations are there as well. So that can be a good advantage for Japanese companies to address those, right? Yes, I believe that's correct. So any Japanese specific gene cancer mutation may be there, so that's something that we would like to detect as soon as possible, so that we will be able to discover the drug and get the approval. That, I believe, is going to be a great benefit for the medical industry in Japan. So pharmaceutical people are very excited to hear this. So from the drug discovery, Dr. Ando, I would like to ask you that this kind of system, I believe, can be a great light for the future of the drug discovery. Yes, that's true. What we've been accumulated as a methodology is there, so after several steps that they are creating a new drug. In the meantime, having a new view, new aspect for the drug discovery, how can they embrace is another agenda to be discussed, I believe. How about you, Dr. Baba? Maybe a bit different angle, but for the... This is a great opportunities for the drug discovery point of view to be able to utilize, and also very rare cancer, which has not been identifying the standard treatments. That is also helpful by having such databases with a huge data, and that's gonna be a very impactful. Mr. Son, database in Japan is something that you are going to create. Of course, that there are some already available, but also with this kind of system, you'll be able to encourage to advance. You mentioned about 50% of the cancer patients' data it can be available immediately, which is a great deal, I think. I think it's a great deal... In Japan, there are some database there that some doctors mentioned earlier, but 7.7 million U.S. cancer patient real-time data analyzed by AI, and the result will be available real-time in Japan for those 13 key hospitals, and they can utilize immediately, which is, I believe, is revolutionary. You may have some tens of thousands of patients data in-house, but 7.7 million cancer patients, and also you'll be able to tell after and before using this specific drug, without going to United States, in Japan, that you'll be able to know, that's a great deal, I think. And for those, you'll be able to also utilize for your research and also for your clinical diagnosis, right? Yes. Yes, and that can be a good reference for you. In Japan, you may be using papers written in the United States, but not only reading papers, but also you can utilize the real-time data immediately, and also you can match with your patient, and you may see some similarity there. But that can be analyzed in real time, so I think that's a big deal. It's not the start from scratch. Day one, you'll be able to utilize the 7.7 million real data, which is a big step. Dr. Sano, how do you think about that? Do you have any comments about it? Excuse me, Dr. Kitagawa. So you see we saw such numbers, and the 400,000 out of one million is the chemotherapy treatments, and only 20,000 of which are using this genomic testing. Not only for the insurance coverage, but also manpower for interpreting the results of the test and also the clinical doctors' manpowers, and also, or the capabilities of finding the evidence is very limited. So using the adapter or using the AI, I think the situation is gonna be changing. And with that, Japanese patient be able to participate in such a movement, and that will create a positive flywheels, I believe. So not only treatment, but also protections can be one way we'll be able to use those data benefit. Dr. Ando said, mentioned earlier, that such data profiling for the early detection of the cancer, and also can be utilized for the preventive medicine. So from the academic point of view, that's the way, but also, in real life, budget issues, regulation issues is there as well, but the possibility is, potential is huge. So there are many challenges ahead. We all know that, but at the same time, this is a new technology that is supporting our medical study here in Japan, so that's very encouraging, hearing all those discussions. Dr. Muto, you're hearing remotely, how did you think about those discussions and presentation? Things that we have not been able to do will be something available all of a sudden, and also, Tempus is providing the genomic testing, and this is something that should be available anywhere going forward. And there are only 60% of the hospitals are not doing the cancer genomic testing. So, if you have a cancer expert cancer doctor, I should be able to do the test. So, hopefully, that we can save all the cancer patients, which is written in the policy. This is not a difficult test, easy test that anyone can, should be able to do, and so that we can accumulate the data, and we'll be able to feedback to the patients, and that should be beneficial for him or herself and or his or her families. So I'm very much excited and encouraged to hear all that discussion. So, we're not going to leave one person alone. And Masa, do you have any last comment, for your expectations or any comments that you would like to, give them? So, like I mentioned, last year, I lost my father, because of cancer. It was stage four cancer. I was at a loss. So there are many regulation issues, budget issues. I understand all those, but what we are doing this for? These methodologies, Japanese methodology, there are many things, but even as soon as possible, we should be able to save as many people as possible, and this is something all common for everyone. We can talk about methodology, but at this time, Tempus coming, entering into Japanese market, I believe this is a good driver, good opportunity, so I believe that that can be supporting the dawn. I'm not talking that the past is bad, but I think it's gonna be blooming in the efforts that we've been making so far with this opportunity. So with this timing and opportunity, hope that this discussion will be more and more taking place so that we'll be able to provide such information to all the patients today. So it's a limited time, but in the interest of time, thank you very much, all the panelists. We are able to hear a great discussion here. Thank you very much, everyone. ... That concludes the roundtable discussion. Thank you very much. Thank you very much. That was the roundtable discussion, talking about the approach to cancer treatment in the age of ASI. We are going to have a photo session. Please, have a moment. Now we'll start photo shooting session. The roundtable discussion participants. Please smile a little bit. Thank you very much. That was a still photo. And then for the videos. Back? ... Thank you very much. Thank you for the roundtable discussion participants. Thank you for joining us despite busy schedule. Next, three of the executives, Eric-san, Ryan-san, and Mr. Son. Ryan-san, Mr. Son, could you shake your hands? There was a still image, and then for video, please. Thank you very much. That's all for photo shooting. Thank you. Next, we'd like to have a Q&A session, questions and answers. For online participants, please access Zoom and let us know by pressing Raise Hand button if you wish to ask us question. If you wish to withdraw your question, please press Lower Hand button. To avoid any echoing, please refrain from accessing to live distribution other than Zoom webinar. Please wait for a moment until we are ready. ... Thank you very much for your patience. We'd like to first take question from audience. We have Mr. Son, and we have Mr. Eric Lefkofsky, and Mr. Ryan Fukushima will address your questions. Please make sure to state your name and which media, and question should be addressing to those three gentlemen, and limited to this today's topic only. The first question? Ito from Business Insider Japan, thank you very much for taking my questions. Two questions. First, Mr. Son, with this partnership, so genomic testing is... Sorry, I will try to—so I have a second question to Tempus. Japanese market, I hear that a lot of medical information is available, but what's your expectation and opportunities that you can hear, or you can see in the Japanese market? That was my second question. First, insurance coverage, talking about insurance coverage, which should be covered, what should not be covered, we should discuss more. Genetic testing should be covered or not, we'll discuss more. The second question to Ryan or Rick, Ryan or Eric. What was your second question again? What was your second question again? You're talking about Japanese market, right? Yes. To either Eric or to Ryan, what's your expectation, thanks to the national medical healthcare insurance coverage? We hear that there is a lot of medical information available. So what's the value of the data set available in Japan from your perspective, either Eric or Ryan, please? I can start. Well, I think, you know, our expectation is similar to what we Masa was talking about, and what we were talking about, is that we really believe that the Japanese market is poised to start collecting not just the clinical information on patients, but also the genomic information, so that we can deliver, you know, the most actionable information to physicians to tailor these treatments to each patient, so that they can benefit and live longer and healthier lives. And in some cases, those treatment options are actually clinical trials that can really benefit that patients can benefit from. And if still there's not an actual treatment option, and there's no clinical trial that's relevant, that's severe unmet need in everyday care. We wanna use the data on in those situations to really advance drug development to address those unmet needs. And so that's why the business of our performing genomic testing and collecting the data is so essential to go together, so that we can not just help, you know, tailor the treatments of today that are already approved, but really advance, you know, the drug development and accelerate that R&D with biopharmaceutical companies, so that we can do something about that unmet need, and we can bring better treatments to those patients. And so our expectation is that the data is going to be really useful, because there are different unmet needs in different countries. We really want to bring this technology to the Japanese market in partnership with SoftBank, and that's why we believe that they're the ideal partner to help us accelerate and operate at a different scale than us alone. Limit one question to one person, so that we can take as many questions as possible. Thank you. Next person, please. And then the other. The French newspaper, Les Echos. Mr. Son, in the past, when you were interested in bringing in Japan the breakthrough technology, we were used to see you buying the company that had this technology or massively investing in this technology. Why did you choose the joint venture format this year? Or did you try to buy Tempus, and they say no, and so you went for the joint venture? We did not buy Tempus. Tempus already was preparing IPO, so SoftBank invested $200 million before the IPO, okay? And because Tempus did not need the money, because already preparing IPO. So but we want Tempus to be super success, and we decided to do a joint venture here in Japan, 50/50. We would, we are very excited about this opportunity. Next question, please. ... Nagoshi from NHK, thank you very much. Mr. Son, press conference like this, I think it's been a while since you did last time. What joint venture with Symbotic was one of the example of joint venture you established. But, you are present at the press conference, for the first time for a long time. Is that showing your passion? We have been talking about AGI and ASI. Saving as many people as possible, as many lives as possible, as early as possible, is one of the biggest missions that we'd like to fulfill, or ASI's mission to fill - to be, to fulfill. I think the medical field is a very important application for ASI, AGI. That's commitment, that's a passion that I have, so that I want to be present at the conference like this. We will take three more people for questions. MJ from Bloomberg. Currently, SoftBank LTV ratio is very low, and also cash-rich company, so I believe that you've been sending the message you should be doing more new investment activities. And this time in Tempus project, are you going to invest more in such a similar type of businesses? What is your investment plan in the future? Our investment is to realize ASI. That's the main focus, and we would like to focus in the meantime. We have as a core company of our group in relating to that businesses we would like to realize ASI. That will be our main focus in the meantime. And next question, a gentleman from there. Sugimoto from Nikkei. Nice to meet you again. Mr. Son, information revolution and medical field, by utilizing them to bring benefits to humankind, when did you start thinking about that? I remember your speech 14 years ago, and I think that you mentioned a similar thing at the beginning of a speech 14 years back. So I wonder, when did you start thinking about that? And you refer a lot of time to your dad, and it was the first time for me to see you crying so hard. Yes. 14 years ago, when we built a new 30-year vision, information, revolution, happiness for everyone. Of course, that was the philosophy that I always had since the beginning. And then, what can be utilized and how, was the question I have had for a long time. And now, AI and technology can be really helpful in the medical field. I am strong believer, and the partnership with Tempus is, I think, the fruit of the passion that I have been carrying with me. And talking about my dad, my dad, I lost him to cancer, and when he was diagnosed, it was stage four. Still really disappointing and still sad. My sadness is bigger and bigger, and again, I want to save as many patient as possible, and that is a strong commitment and passion that I have. With this person, this will be the last person, due to the interest of time for the question from the floor. I'm... My name is Miyajima from the magazine called FACTA. I think this was a great opportunity, great press conference, and I am also the same age as you, Mr. Son. So getting older, the first thing you think about is the genomic test. That's something that you would like to take. And because I think that it's great thing that you mentioned that this is not available in Japan to many people, and I believe that the people needs to pay more attention about that because of the regulatory issues that U.S. is available, but they may be difficult in Japan. And for those challenges, how do you think about? And now, like, ministers of finance or ministers of health, labor and welfare, that you may be speaking to them, no- or not, I don't know, but, I think that, that there are things that you would like to do for the humans' future, and, how do you like to address that? It's not a resistance, but, we are doing for people, we are doing for the world, and hopefully that we all be able to join the proactive and the constructive discussion. Things were not available, is now available all of a sudden, and those 7.7 million U.S. data will be available immediately in Japan, not only using U.S. data, but in addition, Japanese cancer patient data will be also available, and we need to save those patients. I think nobody can disagree with that passion, I think. The methodology-wise, there may be several procedures that we need to follow, but we or I believe the goodwill from all those concerned parties. With this opportunity, hopefully we'll be able to have a constructive discussion, positive discussion, to make the things better. Thank you. Thank you very much. That concludes question and answer session. Thank you, Mr. Ryan and Mr. Eric, and Mr. Son.