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Euan Thomson, PhD, CEO of Zeiss Meditec, Inc., is passionate about using large-scale collaborations and large-scale sharing of data, with machine learning, to extract insights he says “will really move the needle on healthcare.”
In this episode of the OIS Podcast, Thomson and our host Ranya Habash, MD, discuss how the Covid pandemic accelerated the use of telemedicine and remote collaboration, and the trends that may continue going forward.
Thomson says artificial intelligence is very logical for use in ophthalmology, due to the number of images used, but also because there is “less of a barrier to entry” for AI here than in some other fields. He also says telehealth will have a role with remote testing and monitoring.
Thomson said Zeiss sees digital technologies as the future, both from a device and platform standpoint, and said, “When I think about digital it really is the ability to connect from anywhere, operate in a different way, streamline your workflow, and then ultimately when you do have data at scale and you can figure out new insights from that data, we start to improve patient care in some really big ways.”
Click play to hear Euan Thomson talk about how digital technologies and large-scale sharing of data will bring big changes to healthcare.
Ranya Habash: I’m here today talking with you and Thompson from Zeiss. And we’re very lucky to have him here, we’re going to have some really good digital health talk today. So Euan, why don’t you go ahead and do the honors introducing yourself. There’s so many titles, I’d rather you do it yourself.
Euan Thomson: Well, thank you, Ranya. And it’s, thanks so much for the invitation to chat today. And we’re looking forward to it. So yes, I’m Euan Thomson. I am President of Ophthalmology, and Head of the Digital Business Unit, for Meditec, I’ve been with Zeiss, about 18 months, originally, I actually joined to drive the digital business and to sort of create the digital transformation strategy for Meditec. And then I took over ophthalmology about almost exactly a year ago. So yeah, and enjoying it very much.
Ranya Habash: Great. Well, you took over right in time for the big surge in the digital health, right.
Euan Thomson: Yeah, that’s, that’s certainly true. Which, you know, pluses and minuses there, in terms of, you know, kind of need to adopt digital solutions, it was certainly a really good sort of convergences of opportunities. But in terms of really getting out and meeting customers, it’s certainly not been ideal. But you know, like everybody else we’ve got through it. And, you know, all the stronger for it, I think.
Ranya Habash: Definitely, well, you know, actually, last year we are, we saw a big explosion in digital health technologies anyway. And we thought that maybe that would wane a bit. Once you know, the COVID restrictions were lifted, and things were starting to get back to normal. But interestingly enough, this quarter has been the most funded quarter for digital health technology. Can you tell me why you think that is? And what kinds of digital health trends you’re looking at?
Euan Thomson: Yes, yeah, absolutely. There’s, I think there’s two different questions. And on trends, like I’m pretty good at the first question, because I could kind of talk all day on that one, but I’ll keep it brief. But I think the Why is obvious to everybody, certainly driven by telemedicine, I mean, the need to communicate remotely, was clearly a driver for adoption. You know when people couldn’t get together. And I, you know, when I think about this, it’s such a logical thing, it always has been that it’s a shame, it’s taken so long, and it’s a shame, it took something like COVID, to really accelerate adoption the way that it did. And my hope is, of course, that it doesn’t wane afterwards, that we don’t go back to solely in person meetings, at points where in person meetings aren’t necessary. You know, when I think about ophthalmology in particular, of course, there’s also a need for a great deal of testing and monitoring and imaging, for all aspects of ophthalmology. And that’s probably meant that Teleconsults play a relatively minor role in management of patients. So across the board, probably ophthalmology, less adoption, and maybe even less of a need going forward, in some respects, at least, compared to other branches of medicine. So, you know, really the Teleconsults, I think, rather than the remote testing and remote monitoring and remote management that have got traction so far. I think future trends, to me are just really interesting. And so many different drivers that point in the direction of digital health, it’s not surprising that the investment is there, to pull out a couple that are kind of near and dear to me. Artificial Intelligence, firstly, I would say, very, very logical in the field of ophthalmology. And it’s the interesting thing for AI, I think, is that it’s a sort of convergence of technology and politics that drives adoption and success. If you take certain data rich data intensive areas of medicine, like radiology, there’s no doubt that artificial intelligence from a technology standpoint can really offer benefits in terms of decision support and, you know, kind of a safety net to radiologists to make sure things aren’t missed and even guiding towards interpretations where full radiology support isn’t available. But it runs into somewhat political challenges when it comes to adoption. Because it can be seen as a threat it can be seen as doing the radiologist job for them. And I think when you when you look at the state of the of play today in radiology, great technical advancements and some really great tools available, but in terms of real practical adoption, and making a transformational change the business it really hasn’t happened to me and I think this is one of the reasons at least is this sort of, you know, complexity with figuring out and how to positioning it without positioning it as a threat to core services, core businesses, core expertise and, and the human factor. In ophthalmology. You know, we use a lot of images in this space, now you use a lot of images in this space as an ophthalmologist, and therefore, there is a role for AI. But interestingly, I think it’s less challenging role from a political and procedural standpoint, because, you know, the business of ophthalmology is not interpreting images that is necessary to interpret images to do the business of ophthalmology. So there’s, I think, much less of a kind of a barrier to entry, I think. And then finally, and I’ll keep it brief on this, I would say what interests me personally, is really the influence of IoT, which is really all to come. And I think this is something I worked on when I was at Samsung, and it’s something that I feel quite passionate about, particularly when we think about chronic diseases. They’re not just an ophthalmology, but across the board. But it’s certainly relevant to ophthalmology, things like diabetic retinopathy, and even myopia and so on. There’s a sort of Holistic Management of the patient that IoT enables, at least theoretically, you know, this idea that we tend to focus on the medical aspects of the disease process, and we manage those medical aspects medically. We don’t really have the tools and the availability of more holistic systems to monitor the lifestyle of the patient. And yet, we all know how important lifestyle is to chronic disease. So clearly, in diabetes, I mean, clearly in diabetic retinopathy, but also in in sort of myopia, for example, where we know such things as diet, and you know, outdoor activity and exercise, and sleep and lifestyle, and so on makes a difference. But we haven’t really yet found a seamless way to incorporate wellness devices or the connected home, you know, to monitor and to help guide people with those lifestyle changes. So I think personally, you know, we’re just really scratched the surface and the impact of IoT on healthcare. And I’m just really excited about the possibilities.
Ranya Habash: Yeah, you know, I can’t agree with you more. And I’m actually very passionate about IoT as well. And for those who don’t know what that is, that’s the Internet of Things. And that means, you know, when there’s an alert that goes out from a device, for instance, I want to go back to something you said earlier about how ophthalmology may be, you know, one of the lower adopters for telehealth and some of these remote home monitoring and IoT devices, you know, I would challenge you to think twice about that, because, you know, you think that there’s not a lot that we can do remotely, but actually, it’s turning out that we are so device dependent, that we do have a lot of opportunity for digital health in ophthalmology. And one of those things, that’s a testament to that is IoT and the rise of these remote home monitoring tools. So not just for things like myopia or diabetes, but glaucoma now, which was basically the slowest adopter to telehealth now has this whole host of remote monitoring tools. And it’s exactly like what you said, you know, patients or consumers these days, and with some new CMS guidelines, which, you know, allow patients to have full access to their medical records. You know, aside from them, calling us every five minutes to ask exactly what nuclear sclerosis is, you know, they want all their digital information, they want to have that information and just like they’re wearing Apple watches that allow them to monitor everything. They also want devices to monitor their glaucoma or their macular degeneration or their diabetes, for instance. And I think that’s a very big play for the digital health space. And specifically, actually, for Zeiss,
Euan Thomson: No, I 100% agree. And I probably said it wrongly what I meant was, in terms of ophthalmology, I was talking about the Teleconsult versus, you know, sort of more of a full spectrum approach to telemedicine and the role of a Teleconsult. In other words, you know, what you can achieve by using Zoom to talk to a patient, for example, is not as much as in some areas of medicine, the role of telemedicine or the role of telehealth, I completely agree, I mean, remote monitoring of patients, you know, sort of, and hopefully in the future more and more reliance on remote testing and in home devices and in pharmacy devices, to screen and to and to test and to manage patient 100% agree. I mean, I think there’s huge prospects for that. And it is a very strong area of investment for us. You know, we see it, we see it as the future and, you know, both from a device standpoint, and also what we’re doing from a platform standpoint, you know, enabling connectivity, and enabling the connection and the management of data remotely, to a net go to really drive those applications of, you know, sort of remote management and remote screening, remote diagnostic diagnostics or patient. It’s a big area for us a big investment.
Ranya Habash: Well, that’s the other thing actually you, it’s almost like you saw my questions in advance or something. But the next thing I was gonna ask you, I mean, is that where the Microsoft – Zeiss relationship comes in? Is it about that secure platform?
Euan Thomson: Yes, there, it really is, you know, when I think about our areas of expertise, and what’s necessary to build that type of environment where you’ve got, you know, connectivity and secure management of data, you know, we have experts in those for sure, you know, we have people who are very strong engineers in a cloud environment, we have people who are experts on data security, but if we really want to build those types of solutions globally, at scale, this is where a company like Microsoft can really be a huge support to us, and they’re proving to be that. So I mean, security, you mentioned that this is a great example. Again, you know, sort of different requirements, security in different parts of the world, some common elements, but it’s a constantly changing environment. So to rely on any medical company, I would say, to be up to date with the latest threats, that there are to secure management of data. It’s a really tough ask.
Ranya Habash: It is yeah, it’s a big animal to swallow. You know, so why not? pro like Microsoft sort of handled that part of things for you. So
Euan Thomson: Exactly. And that’s, and that’s well said, that’s really what’s exactly buying the partnership. Yes.
Ranya Habash: Yeah, that’s great. And then, you know, the other nice thing that I’m familiar with the Microsoft structure through Azure as well, you know, we, we do it at Bascom Palmer, and one of the things that we do is upload photos, you know, from our machine, our Zeiss machines, you know, right onto there, and then those can actually reside the identified, etc., and be shared across institutions. And so the way that everything is set up, it’s kind of like the central backbone that’s secure that can be basically plugged into. And I think that’s actually really important when we’re talking about Zeiss and collaboration with other institutions or other industry partners.
Euan Thomson: Yeah, no, again, I completely agree. And, you know, if you think about the benefits of moving into a cloud environment, I think it’s a at a local level, when I look at a product like forum that we’ve been making for many years now and successfully helped customers to manage their data locally, and to manage the workflow in a local environment, I mean, those things have been incredibly helpful. And, you know, it’s still a major investment for us, we will continue to support that, and continue to grow it. But when we think in the future about a cloud environment, there are all sorts of advantages, some of them are practical, and some of them are really far reaching, from a sort of a vision standpoint, that the practical elements are by us building an infrastructure as we just described as secure and accessible, we can help with lowering infrastructure costs locally, we can help with making data accessible, supporting different types of workflow that are more convenient for customers. Those are sort of the practical elements. But the strategic vision idea that you’re talking about, I think, is massive, I mean, it enables with all the data in one place, it enables data to be shared appropriately by other practitioners, by collaborators by the patients themselves. And, you know, data at scale contains insights that you just can’t generate from, you know, local data. So that’s the part again, there’s so I guess, as a scientist, that really excites me the insights that can be gathered using in a new types of machine learning techniques to really learn about patient care as a result of the cloud infrastructure.
Ranya Habash: Yeah, that’s exactly right. That’s where I was headed with that, you know, actually, so that that only strengthens and makes these algorithms that we’re using for AI and ml a lot more robust. And it gives us much more geographic and socio-economic diversity as well, when it can be from several different places. So
Euan Thomson: That’s absolutely right. I mean, you know, sort of geography no longer matters when it comes to collaboration, particularly if you can create sort of anonymized data. I mean, there’s certainly a hoops you have to jump through when you think about collaborating across international boundaries, but they are all in sort of that, that overcome ability, like we can’t get over those, and we can solve those problems. So it’s just a matter of opportunity to drive the new innovations in patient care.
Ranya Habash: Well, I’m very impressed with the sort of the direction that Zeiss is taking, by approaching this from more of a platform standpoint, and a clinical workflow standpoint. So forum is a perfect example of that. I mean, it just sounds like such a no brainer now to think that you can see all the machines and all the, you know, results from those machines all in one sort of database and then, you know, use them in a clinical sense that way. So I’m just so surprised that this hasn’t come about before, but I think you guys are one of the leaders in even just thinking this way. So can you talk a little bit about that part.
Euan Thomson: Yeah, I like to think we are, thank you for saying that. I appreciate it. You know, I’d say what’s really driving us is bigger than even just digital and more profound than just digital. What’s really driving us is this need that we feel to provide more of a solution type approach to supporting our customers? And you know, digital to me, the No, I have no sort of I come from a digital background, it’s the enabler to a solution mindset is not an answer in itself. And so and this came to a head, I think, during COVID, you know, when everything went shut, when everything shut down, we spent a lot of time talking to customers about the types of solution they would need in order to reopen in a new normal type of environment. And it led us in all sorts of directions, some of them were, with simple hardware directions, you know, we provided free brass shields to hundreds of thousands of customers, just to enable examinations to take place. And, you know, we came up with solutions involving, you know, longer cables, for example, just to enable people locally, but more remotely. But that was really what was driving us long in that point was it wasn’t a commercial endpoint; it was this solution mindset. And I think about digital, I mean, you’ve said it, you’ve mentioned it, to me, it really is the, you know, the the ability to connect from anywhere and, you know, sort of operate in a different way to streamline your workflow. And then ultimately, with the big picture that we just discussed, you know, when you do have data at scale, and you can figure out new insights from that data, we start to improve patient care in some really big ways. So it’s this solution mindset that’s driving a lot right now in pretty much everything we do, including digital.
Ranya Habash: That’s great. Yeah. And I love how you listen to your customers as well. Although, I will say some of the things that you mentioned, like longer cables, they sound to me, like the faster course part of the analogy.
Euan Thomson: Yeah, these were the sort of short-term fixes that we were able to bring to bear. Of course, you know, sort of midterm, what we’ve been doing more recently is really figuring out how, for example, combinations of our technology can be used together, in order to streamline workflow. And then, you know, we’re working on and sort of heavily investing in a more streamlined flow of data from one device to another. Now, one of the things I think about size, generally, in this ophthalmology space, is we cover such a broad range of products, you know, everything from sort of diagnostics to sort of surgical tools, you know, refractive tools. And so we probably have a bigger opportunity than pretty much any other player to leverage the value of being in a connected environment and streamlining workflow in a very meaningful way. So that’s our medium term. And then the long term of the things we’ve talked about in this sort of connected cloud environment, but as a solution.
Ranya Habash: Yeah, great. I had a couple of questions where if you don’t mind, what I was looking at some of the things that you guys are interested in doing. And I was hoping that you could tell me a little bit more about digital twinning, and AI, image analysis and 3D and 4D analysis, can you come up with? I haven’t heard those terms that much. Can you tell me about them?
Euan Thomson: Trust me a lot. You know, let’s start maybe with the low hanging fruit in AI, and we can bring in some of those other concepts as well. You know, when I look at AI, AI functions on multiple levels, and I actually refer to them fairly routinely as sort of, you know, 1D, 2D and 3D sort of AI. And what I mean by those is, for example, if you have a single image, and you want to bring out features in that image, that might be hard to spot, or you just want to be certain that they’re there, then AI plays a sort of what I call a 1D role because it’s in a one data set. And you’re using AI in one data set. Introducing 2D for me is where you then have combinations of images. And this could be the temporal changes in the image. Or it could be between images. So if you want to bring in two different types of image, and you can use AI sometimes to spot patterns that the human eye maybe not be able to see, because you’re sort of combining the data sets supposed to look at looking at them sequentially, or going back and forth of one or the other, you can really look at the data sets digitally at the same time and sort of extract new insights, or temporarily as I said, you know, look at changes from an image from one time period to the next, you know, monitoring the patient with Dr. as a great example, looking for those small changes that that’s, that to me is 2D because you’ve got, you know, sort of two data sets or multiple data sets you’re using in sequence. And then when I think about sort of, in my mind 3d, it’s really three dimensional AI, it’s really around the other data sets that go outside of that image completely, or the image data set completely. So this is where you might go into the electronic medical record system and look for other disease patterns that might be there. And you then start to say, well, I can use a medical image for monitoring cardiac disease, or I can use a medical image for monitoring for detecting sort of cognitive changes, and but you need a completely different data set with outside of the data set related to those images. So that’s at least how I think about artificial intelligence and how it will evolve and develop over time.
Ranya Habash: That’s a really good explanation. I love how you stack those. I mean, I totally get that. That’s great. Yeah. Again, you were just thinking far ahead. Really.
Euan Thomson: We’re trying? You know, it’s such an exciting time, right? Because it’s such a fast-changing environment. And, you know, we can think of ourselves as being ahead, but there’s no way that anyone any of us can keep up with all the disruptive changes that today, we just have to, you know, do our best to monitor them and sort of, you know, think laterally about how to harness them.
Ranya Habash: Yeah, no, I think it’s great. And you know, you obviously have, because you’ve also set up a Zeiss Innovation Hub, isn’t that, right?
Euan Thomson: Yes, the Zeiss Innovation Center here in the Bay area where I’m speaking from today. This is a real showcase showpiece center for us, you know, we’re very proud of it. So it’s a new building just opened in the Bay Area. It contains some really, really nice facilities, a customer experience center, we have training areas, both for customers and for, you know, our internal teams. And it’s staffed, of course, with great people from the local area. So you know, I’ve been in Silicon Valley now for 20 years, and I’m a firm believer in what you get from the Bay Area. But at the same time, I recognize it’s not the only place that you can do these things, there are other innovation hubs. And there are other great places to be. But for us, generally, when we think about it, I mean, it’s hard to imagine an environment where we wouldn’t have some kind of presence in the Bay Area. And, you know, for us, we decided that we will make it our headquarters for Zeiss North America for Meditec. And we will use it as a way of driving innovation, bringing in academic collaborations and customer collaborations and just continuing to hire great teams, as we do now. So you are very welcome to come visit, as I would say, any of our customers or collaborators.
Ranya Habash: I’m definitely taking you up on that. And I would be very interested in Bascom Palmer doing a collaborative partnership with you too through the Innovation Hub. And might I suggest Miami as your next hub.
Euan Thomson: You know, I could list it, I could list it, and I can tell you stories about Silicon Valley. And in a way in the end, it’s still remade, retains some kind of unique, disruptive character, sort of a, you know, ecosystem has overused word, but it’s kind of a unique kind of ecosystem with academia and venture capital and, you know, sort of companies all in one place that just sort of fosters this kind of disruption. But it’s not the only place I know that, you know, in the US. some great centers, from great centers. Yeah.
Ranya Habash: Well, let me ask you this. From a personal standpoint, let’s say that you had a genie who granted you a wish and you could make any product you wanted, regardless of money time, even if it took you 30 years or something, it doesn’t matter. And $300 billion, what kind of product would you make? What kind of product do you think is missing? Or that could fill a gap? And that you would make ideally?
Euan Thomson: Yeah, you know, that’s, you put me on the spot with that, because it’s hard to come up with an answer. But you know, for me, personally, I actually guess I don’t have too many problems, at least coming up with some kind of answer. Because I’d go back to what I talked about before, you know, I was fortunate enough to be, you know, to have sort of commercial and personal success building a robotics company here in the Bay Area. And at that point, when I decided to move on, I thought long and hard about where I felt the big changes would be in healthcare, because I’ve really just wanted to be a contributor to those big changes in any way that I could. And I really decided at that point that it was the field of data science that was going to change things, and specifically in the space of larger and more enhanced data sets around patients. And these are the themes we’ve been discussing and talking about today. So if I had, you know, sort of that amount of money to spend and, and the time to do this to devote to it, I would go back to a lot of the things that we’re trying to drive here. And it’s why I came to Zeiss. And it’s why, you know, we’re driving for me at least I’m so passionate about driving the programs for driving, if we can create an environment where we take a broader view of the data around Patient Management, that we bring in, you know, long term data we bring in millions of patients without expectations. So we’re not probing clinical studies, but we’re doing large scale data collections that extend into lifestyle, we can really start to understand the disease cycles that take place. And we can really understand how to manage disease in a more holistic way. And I think personally, I still believe that’s where the big changes in healthcare will come through these large-scale collaboration through large scale sharing of data through a broader view of what constitutes medical data, in this case, extending into lifestyle, activity, diet, sleep, stress, all these things that we know influences, but we can’t quantify today. And then having you know, the time and the team to really use machine learning to extract these insights, which I think will really move the needle on healthcare. That’s my passion. And that’s what you know, I will always try to help drivers, as long as I can.
Ranya Habash: Well, you should just drop the mic there. That was the best. No, honestly, I very sincerely, that was an incredible answer. I mean, that’s like somebody telling you that you could have all the money in the world, what would you buy? And you would say, I’m what I exactly what I have now, I wouldn’t change it. But I would just improve or optimize what I’m already doing. That’s a great idea. And I think exactly the same way you do. I mean, the one thing that’s really come out, I think of COVID, is we have collaborated a lot more than we did before. And now you have these institutions who never spoke before. And we’re sort of competitive now sort of all collaborating on one common operating picture. And I just think there’s nothing more powerful than that. I completely agree with you.
Euan Thomson: Yeah, yeah. You know, when I, when I ran accurate, the company that I was sort of built here in the Bay Area. And on the back of all of our business cards was this sort of tagline, our business begins with patients. And I’d say that’s really my personal philosophy that, you know, if you focus on doing the right thing for patients, ultimately, you know, good business will follow somehow. And sometimes we don’t even know how it will, how well, it will happen. And to me, that’s really, you know, my personal and I believe it’s an organization now North Star, and it explains why we behave the way that we did during COVID. You know, what we were focused on in that time was not, you know, offering discounts to try and, you know, sell products, despite the fact that our customers were really, you know, suffering from, you know, cashflow problems and suffering in ways that, you know, we could only hear and listen to, you know, we felt that by focusing on the things that would make our customers more successful, even when it results, even when at the thought process was what we need to give away a bunch of brass shields that even work in our competitive devices, that was really doing, what I’m explaining to you, which was sort of telling you about which is, you know, let’s just focus on the right things. If you do the right things, and you keep focused on those things, then, you know, somehow business will follow from it. There’s never a bad a bad outcome from that.
Ranya Habash: Once again, just honestly, just a very sincere pleasure to speak with you. I mean, it is just so refreshing to hear from you and to talk with you. And I thank you so much for your time. And I’m so glad that OIS has brought us together again this year to talk like this.
Euan Thomson: Thank you, Ranya. Thank you, to OIS. It’s really been a pleasure to talk. Thank you so much for inviting me.
Ranya Habash: Yeah. Well, thank you again, and thanks to everyone out there. I hope they really enjoyed Euan Thompson and all your amazing insights just as much as I did. So thank you guys.
Euan Thomson: Thanks Ranya
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