SoftBank Group Corp. (9984) Earnings Call Transcript & Summary

Good afternoon, everyone. So today, I want to talk about new fusion between medicine and AI. So let me start my presentation. About 14 years ago, at the time of 30th anniversary of SoftBank Group and that we announced a new 30-year vision. And that time also just started the Twitter. And that Twitter that I used and asked people, what is the saddest things in life. And actually, I get about 10,000 reply in a day. And as a result, death, loneliness, despair is the saddest thing in life. And the cause of death in Japan here, back then in 2010, biggest cause of death was cancer. And 13 years later -- 14 years later, as of today, biggest cause of this stays the same, cancer. Many Japanese in about half of those cause of deaths 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 6 months. And 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 a lung cancer and all over the places of his body, and I was crying every day. The very last days of my father was really difficult. And I don't want you, your family, your friends to do the same experience. Actually, it's happening here and there, and we want to reduce such sadness. And AI is now developing and AI, is it the great things for human being? Or is it not great things about human being? And 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 the United States and about 60% is the kind of a threshold for passing the medical exam and 87% 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 the medical test. I cannot pass a medical test. And in that agenda, in that theme, GPT-4 AI is already exceeding human beings label, but this is just the beginning. And now AI becoming AGI to ASI, and I will talk about that in later slides. And when that time comes, there will be a great big change. So we want to reduce the sorrows to maybe not 0, but to reduce as much as possible. That's the kind of my feeling -- our feeling. And here, we have medical AGI. And we were looking for many companies, and I search for it in U.S.. We found one, Tempus. And 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. And 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 8 years ago. This month, the company was listed in NASDAQ in the U.S. $60 million, $70 million, I think market cap. Revenue is growing rapidly. I believe it's going to be [ 100 billion ] pretty soon. They are providing 3 products: genomic testing, medical data aggregation and analysis and AI insights and therapy selection. So recommendations of the therapy and treatment are giving 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 over 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 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 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 generic testing and 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 patients' family, but the data, based upon informed consent is provided by Tempus to doctors and patients. In fact, data from the 2/3 hospitals are stored in a database. Our EMR is fragmented. It's difficult and almost impossible to have a standardized data because different hospitals have different systems. It's difficult or almost impossible to change the different systems. So currently available EMR can be used without no burden -- without burden on hospitals and patients. And the Tempus provides adaptor, so that currently available EMR can be stored in Tempus. And Tempus, using the center repository, the data is analyzed. And of course, paying attention to privacy, there is a filter in place to depersonalize the data. Then personalized data is analyzed and analyzed data will be sent back to hospitals at real time. And based upon the data sent back to hospitals, the hospitals can utilize the data for development in research or even therapy. So that is the service proposition only Tempus can provide and about the JPY 300 billion is invested. It's been 8 years since inception and they have invested in the system creation and repository position. And like I said earlier, the company got listed in NASDAQ, I think it was 2 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. And 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. 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 data and insights to doctors and hospitals for better decision. Whatever underdevelopment 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 underdevelopment. 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 our patients gone through Tempus genetic testing. Most optimal treatment options are presented to those patients. On U.S. average, it's only 27% in the U.S. 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 patients, about half of the all cancer patients in Japan, recourse of those patients are now what Tempus has. And 2/3 hospitals are -- the number of hospitals are with the Tempus network. Even different kinds of systems, thanks to the adaptor, 1 million image data, 0.97 million pathology data and 0.22 million DNA and RNA data, 96% patients were presented were the most optimal options, 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 were presented, were the most optimal trial option, like I said earlier. And most hospitals have EMR, but the systems are not integrated and 65% of academic hospitals and 50% of oncologist 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 adaptor 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. And 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 -- in good shape. So he's going to join us remotely. But let me share with you a short video before introducing Eric. [Presentation]

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 want to 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 we're 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 health care. 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 how -- 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 health care 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. And we thought that if we could contextualize those diagnostics and basically personalize them for the patient whom they were ordered, we could infuse the benefits of artificial intelligence into the health care system, both in the U.S. and around the world. Here's a short video. [Presentation]

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' database has become 50x larger. We have 7.7 million patients that we have brought in. We've de-identified roughly 6 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 that doctor makes is the right decision. We want to help good doctors become great doctors and great doctors become super human. And so we embed AI in 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 the 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 patients 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. And we don't want it to take 10 years. We want to shave 2 or 3 years off that cycle. We want to shave 20% or 30% of 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 is 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 3 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. [Foreign Language] how do we produce the genomic data or the multiomic data on each individual patient case that we're analyzing to produce actionable results for physicians 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, it isn't 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 minimum 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 a 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 target treatments or those immunotherapies over time, so that we can capture the clinical outcomes and organize that data for them as well. And so 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 treatment 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 on 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. And so 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. And so 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 2 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 6 to 12 months to identify a clinical trial site to open up that site in 6 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 essential IRB to take that 12-month process and compress it to 14 days. And 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 go 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. And so 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. And 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. And so 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 organized the clinical history or the contextual information around that diagnostic to make it intelligent. And in 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, we really believe this approach 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. [Presentation]

All right. And so these patients 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. 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 stage treatment for cancer is a genomic testing and developing drug based on the genomic testing and using those drug for that cancer treatment is kind of the way. However, 30% of the cancer patients are using -- taking this genomic testing, the day 1 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 radiation or drug and very end and 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. And these 13 hospitals, leading doctors that I were 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. And this genomic testing, not doing in the very end, but actually bring it forward and not only 20,000 cases a year, but we should do like a medium cases a year, then we believe that we will be able to become about the same level as the United States because within the 3 years course and in the beginning of the treatment, we do need to have a genomic testing, like 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 the Tempus is providing such genomic testing and also not only this genomic testing, but also imaging data is available in hospital or any clinical datas or the EMRs. All those information can be aggregated and do the AI analysis, that service is also available in the United States. As a result, there will be optimal options for the treatment. It can be recommended to doctors, so the doctor share with patients. And that's something that I would like to start in Japan. So hopefully, if we can start within this year, something that we can do from those 3 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 adaptor that we'll be able to create an integrated database. So there will be no burden for hospitals. So with these key 13 hospitals, that's going to be already a great deal in not only 1 key hospital but even 13, Tokyo University, Kyoto University Hospital, Keio's 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 analyze in common database and that's something that we would like to realize in Japan sometime in a few years. Why you think we can do it? Because there will be no burden hospital size. There will be no cost -- additional costs for hospital. There will be no technical effort that they have to do. They are all solved by adaptor 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. August 1 is the expected start of operation. This year, capital is with JPY 30 billion. And the investment ratio is going to be 50% from SoftBank Group and 50% from Tempus in the United States. And in United States, there are services that already provided. And first, those testing equipments and system that they used in U.S. is going to be used. And also I mentioned the 13 key hospitals 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 the scratch. But from the beginning, we will 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, lung cancer and there are many Asian living in United States. Out of this 7.7 million, there are many Asians as well. And that data can be utilized from day 1 in Japan, which is a big, big first step. In addition to that, we will have 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. And the U.S. is very much advanced and most advanced compared to the rest of the world. And this is the first time going outside of the United States. the first country next to United states is Japan. So U.S. 2,000 hospitals are already -- so 50% of hoses already connected. And we would like to also make that happen 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 adaptor. So big data basis, that can be from the day 1 utilize in Japan. So we believe we can integrate all the wisdoms not only in Japan, but also in the United States. Together with the health care professions, we believe we will 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 4 years, computing power became 10,000 times. Number of chip became 10,000, capacity per chip become 10 times and also transforming the AI model became 10 times in 4 years. So 10 times 10 times 10, so 1,000 times. And in 4 years, generative AI computing power became thousand times. In next 4 years, same things happens. So that's going to be another 1,000 times. And following 4 years, it's going to be another 1,000 times. And next 4 years, it's going to be another 1,000 times. So let me say that this is going to be the kind of case, even 2, 3 years behind or something, but now it's already -- the medical test exam can be passed by AI. And if you imagine, 1,000 times of such intelligence and 1,000 times x 1,000 times is a million times. And millions times of thousand times is a billion times. So by watching 3 Olympics game, AI capacity and capability become 1 billion times. So the medical exam level of the intelligence is going to be 1 billion times. That is ASI -- that's AGI, is the -- something similar or equivalent to human beings. And 10,000 times from there, not only medical, but also productions or logistics or in any industries and segments that I believe, there's going to be 10,000 intelligence available. But speaking of medical sector, that's to be thousand times to million times to billion times. 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 a beneficial for human being, but I think at least those families who lost beloved members because of cancer or high blood pressure or many diseases, 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 here. We are experts in data science. Medical science and data science, both. This is not a discussion of which is right or wrong, but the medical science and the data science that should be fusion-integrated together, medical ASI world will be created. With the humans wisdom, there are many difficult diseases that are not being cured. And maybe with the technologies capability, we'll be able to save those lives. And also, we will start having a live without health issues and also staying healthy at any age, which is a great news for human. It may not be 0 -- of course, it may not be 0, 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 the data science and medical science should be utilized. So information revolution, it's 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 want to 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 the 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 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 facility the session. She is a medical journalist, who has several experience of facilitating medical symposium.

My name is Mori Madoka. 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 the patient. So we're going to 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. Mr. Katsutoshi Oda, Professor and Director, Department of Clinical Genomics, the University of Tokyo Hospital. Mr. Eishi Baba, Professor, Department of Comprehensive Oncology, Graduate School of Medical Science Kyushu University. 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 the 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. And if you look back, like you mentioned 40 years ago, I became a surgeon. Back then, the only thing we could do is just to cut it. Cut the cancer tumor out was the only option almost. But it's been -- we have been progressing in terms of diagnosis and treatment, but it's been 40 years. It's been a long time. We are trying to build our 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, 4 years and 10 years, I tried 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 and 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 and 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 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 without the testing and everything, I think it's significant to have a vast amount of data in a single repository.

Yes, 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 want to 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 Tempus on assembling this data and creating, 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. And by providing more value, we can collect more data in the process. And 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 bundle on changing EMR system. For example, currently, available data is used, thanks to the adaptor. 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 it. I have not had a chance to see an adaptor itself. But if that kind of solution is available, that would be great.

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 in using the technology and if you can advance the cancer treatment that's going to be great for the human being.

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. And 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 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 the 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 like a precision medicine in the United States. And to realize that this is 1 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 this test should be done at the same time. However, in Japan, you have to -- you can only test after you go through all the standard treatment. And the policymaking is not right in Japan. I believe that's the way that I should be putting optimal treatment and the 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 results as many possible, and the many -- some people say that it's going to increase the cost. But actually, you'll be able to save the waste for or not necessary treatment so that's also the beneficial from the medical policies 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 think 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 6 years, we've been asking to take away these limitations to be able to take the timing of this genetic test, but there is no scientific base. That was 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 for there 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 been seeing a great response. And also combining with the cancer immune treatment is already available. So not all the treatments, but like Dr. Sano mentioned, there are quite effective drug. So those patients who cannot take the surgery -- but there are possibilities that they will be able to take a surgery like a conversion surgery. And also combined with radiation treatment, some of the drug becomes more effective than before. So as early as possible, knowing the cancer profiling so that we will be able to -- because we have a lot of weapons to address the cancer and so that the patients will be able to live longer and ultimately, we hope that we will be able to cure this disease. So there will be a strategic treatment option will be available so that that's going to 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've given the weapon, but you cannot stand up and fight anymore. So you have to be full energy to be able to receive such weapons 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 at early-stage cancers and may not necessarily the drug but just taking or the removing those tumors in most of the cases are curable so not half, but that's quite many. And those people, once that they diagnosed as a cancer and then start the genomic testing, it's going to 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 it phasely 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 then it needs to be flexible to address. But at this moment, after all those treatments and very end of the process, once you are so exhausted and now available for the genomic testing, which is -- it doesn't make sense at all for me. So that's 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 -- 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. [indiscernible], which is outside of insurance coverage drug is necessary for those 45% of the patients. And if we try to use this drug, then this not be covered by insurance. How are we going to address that? That's going to be the 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 will be the opportunity or what will be the 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 needs to be changed. The way it should be, that kind of idea needs to be revisited. They will -- CG, for example, those patients need clinical testing. But I think there is a problem of drug loss and drug lag from a 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 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, antidrug 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 patients. 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 a great thing to do. That's something that we want to communicate with the drug companies and having genomic testing information is advantage. Because without screening, you have insights about genes and genomes. I think it's rarely 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's the area where data helps. If you can share data by connecting different systems, that will be a 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 will 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 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 a later stage with insurance coverage, patients who still can have -- 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 a 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 3 different buckets. And when we perform the testing -- the comprehensive genomic profiling, in the U.S., we build 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 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, all 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 could 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 adaptor, data is collected in a central database. And through the adaptor, the data or structured data can be sent back to hospital, free of charge, including analysis. Japanese hospitals have [indiscernible] data. And it's very simple with no cost, with no burden, data can be analyzed and sent back to hospital. 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 registered data in the database, but it takes time and cost because there are set formats and you need to fill in the format and register in system, but the hearing Tempus system and in fact, our team is developing our own system. But if it works, data can be collected in real time, which is great because currently, medical professionals take time and efforts to build that kind of data.

Speed and hassles can be removed. That will be helpful for doctors and physicians and hospitals. What do you think Dr. Muto?

Yes. Since 10 years ago, a different EMR, we try 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 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 prospective of privacy and personal data, so they are very conservative. They are not open to providing data to third parties. So we have to talk to hospital each by each. So we need to change the mindset 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 2 groups: standard and nonstandard, and we compare with those groups. But going forward, each and every patient's personalized data. And if we utilize each and every person's data, you should be able to find out similar kind of patients so that we can find a better treatment solution. This kind of platform is great. And DX and digital transmission 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 health care system is set up to really take advantage of this AI revolution in health care. I think by meeting with the top centers that have already done -- taken approaches to start to organize the information is the first step. Now we just need a 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. And when you do that and you can start to create that data flywheel in a way that it's 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. And 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.

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 the United States or other countries, they are trying to develop that part. And first, U.S. Tempus, 7.7 million cancer patient real-time data, real-world data, they would like to utilize immediately. Some of the companies are already using, but they would like to expand that. So they want to have utilized 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 U.S. data, but with this SB Tempus establishment, they will be able to utilize Japanese cancer patients immediately. That's going to be also a great benefit for the drug companies for the drug discovery. And I believe we will be able to see the revitalize of Japanese pharmaceutical companies. And I think that they should be the leading company in Asian countries. And so that they will be able to help support us giving a good solution for humans. So those no time lags, timely manner that they can accumulate data and also analyze, that is something. For example, there will be some similar cancer that 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 recovery.

Yes, that's true. What we've 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?

May be a bit different angle. But for the -- this is a great opportunity 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 data bases with a huge data, and that's going to be a very impactful.

Mr. Son, database in Japan is something that you are going to create. Of course, there are some already available. But also with this kind of system, you'll be able to encourage to advance. And 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 data base there that some doctors mentioned earlier, but 7.7 million U.S. cancer patient real-time data analyzed by AI in the result will be available real time in Japan for those 13 key hospitals. And they can utilize immediately, which is -- I believe, is revolutionalized. 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. Not only reading papers, but also you can utilize the real time data immediately. And also, you can match this with your patient and you may see some similarity there. That can be analyzed real-time. So I think that's a big deal. It's not start from scratch. Day 1, you'll be able to utilize this 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 1 million is the chemotherapy treatment 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 the capabilities finding the evidence is very limited. So using the adaptor or using the AI, I think the situation is going to 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 has had mentioned earlier, that such data profiling for the early detection of the cancer and also can be utilized for the protection medicals. So from the cutting point of view, that's the way, but also in realize, of course 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 by hearing all those discussions.

Dr. Muto, you're hearing remotely, how did you think about those discussion and presentation?

Things that we have not been able to do will be something available all of the sudden. And also Tempus is providing the genomic testing, and this is something that should be available in 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, should be able to do the test. So hopefully, that we can save all the cancer patients, which is written in a policy. This is not a difficult test. Easy test that anyone 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 last comment for your expectations or any comments that you would like to give them?

So like I mentioned, last year, I lost my further because of cancer. It was stage 4 cancer. I was lost. So there are many regulation issues, budget issues, I understand all those. But what we are doing this for, this methodology -- 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 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 dorm. I'm not talking that the past is bad, but I think it's going to be blooming the efforts that we've been making so far with this opportunity. So with this timing and opportunity, I hope that this discussion will be more and more taken place so that we will be able to provide such information to the -- all the patients today. So it's a limited time and about 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 a round table discussion. Thank you very much. That was a round table discussion. Talking about the approach to cancer treatment in the age of ASI, we are going to have photo session. Please have a moment. Now, we will start photo shooting session, the roundtable discussion participants. Thank you for the roundtable discussion. Participants, thank you for joining us despite busy schedule so next, 3 of the executives, Eric-san, Ryan-san and Mr. Son. Okay. Next, we'd like to have a Q&A session -- questions and answers.

[Operator Instructions] Please wait for moment until we are ready. Thank you very much for patience. We'd like to first take questions 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 your question should be addressing to those 3 gentlemen and limited to this -- today's topic only. The first question from [indiscernible] Business Insider Japan.

Two questions. First, Mr. Son, with this partnership, genomic testing as -- sorry, so I have the second question to Tempus Japanese market. I hear that 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 will discuss more. The second question to Ryan or Eric, so 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 Health Care Insurance coverage, we hear that there was a lot of medical information available. So what's the value of the data sets available in Japan from your prospective, either Eric or Ryan, please?

I can start. Well, I think 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 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 severe unmet need in everyday care, we want to use the data 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 cannot just help tailor the treatments of today that are already approved, but really advance 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. And so 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 to add it alone.

[Operator Instructions] So next person, please. And then the other...

The French Newspaper [indiscernible] Mr. Son, in the past, when you were interested in bringing in Japan a break-through technology, we were used to see you buying the company that had this technology or massively investing in this company. 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 the 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. Mr. Son, press conference like this, I think it's been a while since you did last time. 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 emissions that we'd like to fulfill or ASI's mission to fulfill. I think medical field is a very important application for ASI, AGI. That commitment, that passion that I have so that I want to be present at the conference like this.

We will take 3 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 and relating to that businesses, we would like to realize ASI. That will be our main focus in the meantime.

And next question, a gentlemen from there.

[indiscernible] Newspaper. Mr. Son, information revolution and medical field by utilizing them to bring benefits to the human client, when did you start thinking about that? I remember your speech 14 years ago. And I think you mentioned a similar thing at the beginning of our speech in 14 years back. So I wonder when did you start thinking about that? And you refer a lot of time to your debt, 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 evolution happens 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 a 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, I lost him to cancer. And when he was diagnosed, it was stage 4, 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.

This will be the last person due to the interest of time for the question from the floor.

My name is [indiscernible]. And I think this was a great opportunity, great press conference, and I'm 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 a great thing that you mentioned that this is not available in Japan, too many people. And I believe that the people need to pay more attention about that. Because of the regulatory issues that U.S. is available, but it 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 or not, I don't know. But I think 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 will be able to join the proactive and constructive discussion. Things were not available is now available all of the 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. And I think nobody can disagree with that passion, I think. In the methodology-wise, there may be several procedures that we need to follow, but we or I believe that goodwill from all those concerned parties. And 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. Thank you very much. That's all for press conference hosted by SoftBank Group Corp. Thank you very much once again for joining us and watching the live streaming. Thank you.