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Dassault Systèmes

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[ MUSIC ] So, I want to begin with a massive purchase and acquisition you did, but it's really in many ways a change in strategy. You just earlier this year, you bought a company called Metadata, a US company, for $ 5. 8 billion or so, 5. 7 billion, something in that range. It's a lot and your largest purchase by far by a factor of seven or eight or something that you've ever done. Anyway, when you think about your company, it's about 3. 4 billion in sales each year. $ 3. 8 billion. I mean that is a very large commitment. Tell us why you did it. Well, first of all I agree with you. I have no more money. [ LAUGH ] But the point is the following, we have observed the life science sector for years. I think it's a little bit provocative what I'm going to say. But if airplanes were done this way, company will do hundred of plane, put them in the air and look at the one which is flying I said this is the way, this is the one I'm going to produce. So what I'm trying to say is we need to contact to connect clinical trial with modeling and simulation. On media data, it's about clinical trial. They do 50 % of the worldwide clinical trial. So they analyze the data from these trials. Yes. Twenty years worth of trials. They organize the trial- Right. Target them, and then analyze the data, capture the data and create what we call virtual arms. So next time you do it, you can compare one [ UNKNOWN ] with a [ UNKNOWN ] one. So it's very key, especially in your sector which is highly complex as the biosciences, on connecting now, this to the power of modeling on simulation, I believe can be a game changer for the industry, that's why we did this move. So combining imaging or in your cases, 3D imaging or simulation with a new data platform, is this idea of super charging this. And so you'll notice the theme here for those paying close attention, cuz I'm gonna follow up with that same question to you, Karen. This is your holy ground, right? Combining the imaging with a new data, data platforms and figuring out different ways to analyze that data. You just got FDA clearance for a type of lung cancers screen or lung scan. It allows you to identify pneumothorax which is a collapsed lung. Tell us why that's so important. So, first of all, in the world we live in, there is a lot of data, but far too often not enough insight. And so, what we're trying to do at all times Is take data and from that data create insight. And so if I look at that alone, three axes. Your example is perfect for where a radiologist or a physician that's under stress has maybe 200 scans to read 200 scans of various kinds, the X ray, that included that new more thorax, Rihgt. Could be sitting for hours down in his workflow. And the beauty of what e've done is, Life or death. Life or death, Right. So it goes maybe from up to eight hours down to 15 minutes. This is right at the top of the queue. It is flagged that this patient has collapsed lung you need to pay attention now. And so this digitization gives us the chance to be faster Reduce Stress for the physician and obviously much better outcome for patient which is what we're all trying to do. And Bernard, when people talk about bringing AI into the system, and I've heard you say, this is like, we've been doing this for 25 years, I mean, you were doing it secretly as a defense contractor. But you have this extraordinary thing. I wanna show the audience You do this 3D brain virtualization. And in fact, we've got some images and I'm wondering if we could show those images and if you could just talk over them for a second. You can look at them on the screen. Yeah, tell us what this is. Yeah. This is the reconstruction in 3D of a brain with all Older characterization is the follow up to what we did for the Living heart program. Living heart was adopted by the FDA, as a matter of fact, as the best platform to investigate heart surgery. So we are doing exactly the same here. But don't think it's only geometry. It contains all the characteristics, electro characteristics of the brain. So you have the characteristics of the brain you have older conducting elements of the brains. So it's what we call murky physic simulation. Now, so we've been doing this for IO space In multi physics simulation for years. Yeah. I remember the time where people told me you will never simulate an airplane in the Gulf or to the air. We don't do physical prototyping on the first airplane will take off. Right. So we are applying that same discipline of representing complexity on addressing three things. Collaboration between disciplines which don't necessarily understand each other. To memory, meaning you remember the experience. Sense memory too. You actually, you're not reading in a book, you're actually doing it. Absolutely. Yeah. And then everything related to capturing experiences and comparing It to during your life of passion, so it works very well for heart surgery. Right. So we wnat to apply it to brain now. And we have also done it for propagation of cancer in human cells. Right. I'm just interested because effectively That's what we're trying to, we live in an ecosystem. And I think, we were talking about this backstage, our industries are fragmented. And so if you think about what we're trying to do, it's a very similar concept. How can we create a platform for the ecosystem where we can bring different communities? Vas mentioned it earlier In relation to clinical studies if we can integrate what pharma companies know with what's in the medical records with imaging with genetics and metabalomic data, all of a sudden you have This much better 360 degree view of the patient. Is the integration of that data that's really powerful which is kind of similar. Yeah, our intent is to really do the virtual twin. Right. Of an entirehuman. We did it for planes on cars, there is no reason we cannot do it for. For human, and the problem you know is that people are over communicating and they under understand each other in those disciplines. It's siloed as we discussed, it's very siloed, but innovation will come from the cross examination of things. So but you are going through this transformation between The sort of world of steel and aluminum and and you know widgets and hard things like that. You wrote a beautiful essay for the the Nikon Co Yu Shimbun which is the largest Business Standard or one of the leading business dailies in Japan and you wrote about. I'm going to quote from this I believe in the century of living matter, industry will be remodeled by the bio sciences, the material sciences in the Information Sciences. Tell me what you meant by that? Well, if you look at the 20th century industry, it's very siloed. It has been based on a limited number of principles. Physical principles, chemistry principles, even pharmacy, we've small molecule. You know, you see in front of you here 28 molecules. 28 molecules? What do you mean? 28. A human is 28. This is 54. [ BLANK_AUDIO ] I knew we were- 2854. Think about it. I knew my phone was smarter than me. I didn't know it was more complicated than me. It's more complicated and less smarter writing I think. Right. But the point I want to make is when you observe the world of living You discover things that have never been applied to the industry. On to your to your question about your question. I think today we can create materials from the atoms. It's the unknown 50 years anniversary of the Mandela EF table. It's a very important table. the periodic table and there is a limited number of filaments 28 here 54 and 58 in my phone. And when you when you think about blessed, there was 28 It's magic. So the point what would lift Tony MD what's new, what's the new element that you would create and we'll name it after? Well, first of all, we for additive Additive printing whether it's leaving out or games or static, you can start for molecules or form human cells and print. You teach new skills. This is happening as we speak. So there is no reason why this will not change the frontiers of the life science world. And it's happening in biology because biology is quite complex, and it's not a small molecule it's a big molecule, and it's difficult to produce, and it's difficult to Replicating at scale. So I believe modeling and simulation will transform that. And that's what I wanted to communicate. So you're also a scientist by training and by virtue of you being Irish, you're also philosopher as it just like Bernard So you talk about the ways in which you're going to see truly transformative change. I mean, we've been in the age of the gene, we went through the age of the computer. We're now in the age of confluence, where all of these revolutions in technology, 5G, AI, sensors, big data analytics, The new science of bio they're all coming together and you're combining many of them in your business where are we gonna see the benefits of this? So I think ultimately there are three beneficiaries economies because if you look at The cost of healthcare and the waste that occurs today. We can't afford to keep going the way we're going now. And so achieving better productivity, achieving better outcomes is going to help eventually. I know you're going to ask me when and quantify. Yeah. it will happen at some point. And I think if I look at it, as national level of you can, you know, transforming the images in the UK, I'm familiar with. There's something to really start to integrate how they look at first of all, Healthy volunteers now track them over a number of years and see what changes that occur in many different molecules of their body lead to disease. And I think that's going to provide a whole new rich data set that's going to be very interesting. But you know. I said, I know Steve Carr is here in the audience. He's very interested in short term. What's thins gonna mean for hospital productivity? And for hospitals today we can see that using digitalization and combination of data sets means that, and we've proven this with use of things like command center We can reduce waiting time in the emergency department by up to five percent, which is really important for patients. We can speed that patient through the hospital safely and create in one specific hospital, it was 50 extra beds in capacity. In a year You're doing this with And you say well that doesn't matter okay 50 beds doesn't matter, it's a million dollars a bed. So I mean for a hospital, that's a lot Wait till you get your hotel bill for her. A million dollars a bed You know the sole cause of mortality, Yeah. After heart accident or oncology is in practices, think about it. Human error. You wanna know why because there is no way to be actually trained. Right You only practice as a top specialist You will not put a pilot in a plane without virtual training. Right. So, for example in the Children's Hospital in Boston they are using the not living breathing but the living Houghton mansion to plan all children repair On the small heart on reviewing all the characteristics under different options before going to the surgery room. I was discussing with the doctor last week, he was telling me that, he receive children which have been operated Across America where he has to fix the previous errors. So, I think it's not digitalization, it's a virtualization of those practices that will make them pervasive, reliable, auditable, Which is not the case today. And think about the training of neurosurgeon, so I think it's game changer for the entire sector. So I think that it's clear that the technologies that you are both talking about up here, are making us better, smarter. Faster, more reliable, less error prone. What isn't clear is that they're making things cheaper. And for both of you, when you brought out your phone before Bernard, and we know this thing called Moore's law. Where we get more and more productivity for less and less investment, and less and less cost. And yet in health care, for whatever reason seems to be a reverse Moore's Law, right? The cost keep going up and up. When are we going to start to see this? Okay, I think it's going to change quite soon. We're talking about seven gene therapy earlier. I mean, the early days of cell therapy, and the mirror oncology, for that matter have ended up with very expensive treatments. But, you know, we will end up within, I suspect within the next 10 years with more allergenic rather as opposed to specific patient treatment, more allergenic treatments and that will bring cost way down. And fundamentally, you know that the principle of precision Of precisely diagnosing a patient and giving them a [ UNKNOWN ] gene therapy, this is transformational for the whole family and Th healthcare industry. Combined with I think technologies in the hospital, you're putting people into hospital Only when they need to be there. You reduce hospital acquired infections when they're there. You get them out of the hospital as quickly as possible. And through various mechanisms, you monitor them in a social setting when they've been treated. I mean, I think the ecosystem we're working in now. Is everybody incentivize to make this work. And it is an ecosystem. And that's why we're investing in something called the Edison platform. Because effectively, the industry needs a host system to allow algorithms and data to be gathered so that it can be utilized more effectively. I've heard that you both work with ecosystems. You create your 3D experience labs and partner with a lot of startups, many of which you'll invest in later. What is it that is so effective about that model as opposed to just going out and buying the company? Well, innovation, the speed of innovation, the freedom to try many things quickly. And I think that's that's really what under attraction of talents, because you know, so many young generation want to be their own entrepreneur and if we can help them We have a gigantic ecosystem, we have about 40, 000 partners. 40, 000 partners? Yeah, 1. 5 trillion of innovation program are based on [ UNKNOWN ] system in the world, so we are very secret company. Wow. And we don't talk too much about our company but we are there and So many sectors. The point I want to make for the cost because I think it's very important. You know, this industry has also been living as a rich industry. Yeah. As compared to many other industries. We must admit it. The second thing is 20 years of protection. Full patterns. Right. Ten years to develop. Half of it is for clinical trial. So on so many failure that you need to compensate with the successful blockbusters, and then you have the summary of the industry. So it's about success rate It's about speed and it's about better targeting. So I believe that this industry is like the industry of aerospace on space 30 years ago. Document based. Please provide the documents that proves that you have done the right thing. But you never know if the document of a present the reality FA certainly years ago was receiving documents that would not work reason what was flying with modeling and simulation fa EC today. experiences that does represent the plane which is flying Document based versus the distance between reality and virtually is reducing, and that will change the industry. And the loss of flight don't change that often, and yet what we're learning about the body with the immune system's ability to be harnesed now and fight things like cancer Or what we're learning about the brain, the last frontier of humaneness, and this is changing all the time. Our knowledge base is doubling and tripling and changing all the time. What do you look for in terms of a regulatory environment that speeds innovation? And I wanna get a question here too. So if you've got it, yeah, we've got one up in front. I think I can very simply endure, we need the regulatory environment to fully utilise the data that's there. And I think there's a huge challenge in all of the regulators now with the urgency of AI because all of a sudden the speed of which these tools can be developed and deployed has provided them with enormous Challenge and of course, some of these things if they're not properly developed, and curated with really good data can be dangerous. And, again, that's why I got back to the platform. We only put things in our platform that are based on data sets that have sufficient volume and sufficiently well curated. That's what we save. Right, all right. We have a question right here. You just please identify yourself. Yeah, Robert HD, head of bureau United States presidency. Thank you for this very inspiring panel. Your biotech is obviously at the cutting edge and when it comes to the the brain is fascinating Also very touchy, as regard of the mystery, you said that you capture it data and is it only for purpose of surgery and research and development? Or is it also for defense purposes? And the second question, sorry, it's going to be very short one, are you sharing this with The global hospitals are going to be remaining only private. Thanks. Yeah. Capturing the clinical trial is about capturing data. I think the value of clinical trial sharing is very high. On the company called MIDI data, what this is exactly what they do. So when a new player will do clinical trial on a new molecule, lets say. The previous experiences [ UNKNOWN ] will be used to do what we call [ UNKNOWN ] to compare to other possibilities, therefore enrich The level of quality of targeting or risk assessment or efficiency assessment of the clinical trial. Yes, of course the value is about sharing. Right. That's the mechanism. It's not used for anything else, of course. Ken we have 40 seconds left You're an almost $ 20 billion company. If GE healthcare stood by itself, it'd be 160 on the Fortune 500. There was talk about spinning it off, it fell off the table, is it back on the table now? So I was hoping we'd run out of time before you asked me that question. Yes, that's why I had to get it in, yes. [ LAUGH ] Well, so I'd make a couple of comments. First of all, I'm very jealous that borrowed so much money to spend. Yes, yes. So at look at some point and we don't have a timetable, we will probably emerge from under G but. You know as you said Gee healthcare is a $ 20 billion business. We're the top biggest med tech company in the world. And we have global scale and we're big enough to stand on our own two feet at some point Thank you, Karen Murphy. [ UNKNOWN ] Thank you so much. [ APPLAUSE ] [ MUSIC ] [ BLANK_AUDIO ]

How Technology and Digitalization of Data Empowers Doctors and Benefits Patients

Leadership

An in depth conversation about health care with Dassault Systèmes CEO Bernard Charles and GE Healthcare CEO Kieran Murphy. 

Dassault Systèmes

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