Intelligent/Digital Surgery: Innovation & Opportunities Evolving Rapidly


David Uffer

David Uffer

Senior Partner & VP, Alira Health
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Rachel Van Stratton-Kirk

Rachel Van Stratton-Kirk

Robotics & Digital Solutions, Ethicon
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Tal Wenderow

Tal Wenderow

Venture Partner, Genesis MedTech
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Oliver Keown

Oliver Keown

Managing Director, Intuitive Ventures
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Christopher Cleary

Christopher Cleary

Senior VP of Corporate Development, Medtronic
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Daniel Hawkins

Daniel Hawkins

CEO, Avail Medsystems
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This panel will explore one of the hottest areas in medtech. Where are we and how far do we have to go? Hear the views of the investor, innovator, and strategic.


David Uffer  0:05  

So thank you very much, Scott as our panelists all filing, I'll tap dance for a minute. Last year, I hosted a panel on robotics. And throughout the year, many people said nice topic, Dave. But I think we get it now, what's next? And I see probably as an advisor 800 to 1000 Different companies each year and a lot of people were asking Where's where's surgery going from a digital and intelligent perspective. They wanted to hear from our industry leadership on that. So I have to thank my esteemed panelists all for joining me on this, I'm very proud and pleased to have some of our best in the industry that have a very unique and diverse perspective on this. Just as a setup to this conversation, this could be an all day or an all week topic to dive into. For the purposes of this panel, I like to define digital as the digitization of people processes, product procedures. And when we are going to talk about surgery. I don't want to think of just open or laparoscopic surgery, but I'm looking to discuss everything from any procedure that would be done endoluminal endovascular, percutaneous. We're talking about interventions here. So with that, I'm going to turn it right down the line to each of the panelists to introduce themselves, their companies and their roles. All right,


Rachel Van Stratton  1:33  

Rachel Van Stratton, part of J&J's robotic and Digital Solutions Group, specific into our business for global strategic marketing. But I'm focused on advanced imaging, end to end spectrum kind of pre op all the way through post op.


Tal Wenderow  1:52  

Thanks, Tal Wenderow. I'm a venture partner of Genesis Med Tech, which is an upcoming strategic player. Doing both devices and looking also in digital surgeon will define it better, hopefully, than what Dave did. Before that was in robotics, co founder of Robotics.


Daniel Hawkins  2:11  

Daniel Hawkins, founder and CEO of Avail Medsystems. It's, as I mentioned in two panels ago and been in this space 30 years. Actually, the earliest stages of robotics is part of Intuitive Surgical back in the very, very early days. In, you know, what I'm doing right now with Avail Medsystems is we've deployed a network of access points into procedure rooms that allow remote access into those procedure rooms, but it also provides an ecosystem to connect, I'll describe them as digital capabilities, into procedures that are not currently robotic. And I think that's really the relevancy of what we're doing in this particular battle.


Oliver Keown  2:50  

Hi, everyone, my name is Oliver Q, and I'm managing director of Intuitive Ventures, the venture arm of Intuitive Surgical, which pioneered the field of surgical robotics last 25 or so years, my role is really focused on ecosystem investing in early stage transformative companies that are pushing the field of minimally invasive care forward across digital device therapeutics. We spent a lot of time being thoughtful about the opportunities in digital working with our stakeholders, our colleagues internally to understand where Intuitive is today where it's going, and trying to translate that into opportunities to identify to support to accelerate companies in the broader ecosystems that we can support and advance.


Chris Cleary  3:30  

Hi, I'm Chris Cleary, I run corporate development for Medtronic. And, you know, I've looked at a lot of investments and acquisitions in the digital surgery and technology space. We bought one a couple years ago, digital surgery out of London. And, you know, I'm an avid follower of, you know, the technology, and its applicability for our surgical franchise.


David Uffer  3:57  

Thanks, Chris, let's start with you. Since you're the end of the line, and we'll work backwards. We'll shift it up a little bit. But I want to start at the end of the discussion and then work backwards as well meaning, let's talk the overall objective of what you're expecting out of digital surgery. Where are we trying to go with this for the ultimate goal?


Chris Cleary  4:19  

I mean, look for us, we kind of look at it and say there ought to be, you know, logical guardrails for what the surgeon auto expect to see in their camera, or their line of sight and what they actually see. And, you know, you can inform surgical procedures in terms of, you know, timing turnaround time, the procedural steps. You know, one of the really cool things we found out from doing diligence on digital surgery was that the majority of surgeons for like a hernia operation thought there were like five steps But when you get down to the actual steps that are kind of loaded into the procedure process, there's like, you know, 43. And, you know, people aren't aware of how they kind of glide between different steps in there, there's very different approaches, people absolutely take a different path to the same surgical target a lot of the time and, you know, seeing what it ought to be in working that into your planning, working that into some kind of a system where, you know, potentially you can deactivate and defectors, if they're in a no fly zone, you know, to increase safety. We think that those are very logical extensions of, you know, a database that shows, you know, 1000s of procedures that the surgeon is doing, as opposed to the one that they're doing that morning. So I think it's a major advancement in the potential for safety, for planning, for the integration of not just the procedure, but the imaging and, you know, all of the aspects that are just fundamentally data. And, you know, right now, surgery, my son is a neurosurgical resident. I think he's on a 15 year program or something like that easy is in your six. But, you know, it's an apprenticeship and that's how he would describe it. And, you know, I think having data to kind of augment your, your experiential apprenticeship is a really it's an important function of that. Yeah, the end of the day are a lot of our customers are physicians and surgeons and improving their ability to do what they do more safely, hopefully, a little bit more efficiently. That's that's a completely valid goal.


David Uffer  6:47  

Oliver, do you see it the same way? And, and by anybody, if you have a different viewpoint, even of the definition of digital surgery, please offer?


Oliver Keown  6:56  

Yeah, I expand upon that. I think that's all exactly right. It's about unlocking insights and actionability through data. It's really about the integration of hardware of data of analytics across that surgical journey and no way I think about it and get to look both external and internal to Intuitive. There's the clinical view, there's all the hardware, the procedural elements, the medical devices, the computer vision and opportunity to really unlock value and outcomes through innovation there. And then it's the broader or setting there, there's an incredible amount of opportunity to unlock value. As you look at the room is looking at teams, you look at performance, you look at both from a surgeon perspective and a broader workflow around surgery. And then you look at the perioperative journey, and comes in cared and care journeys can be improved upon activated by data inputs that are coming maybe from that intraoperative view. And And then ultimately, I think it's about tying that to the broader patient journey, maybe even going as far as diagnosis to recovery and cure. And I'm selling a grand vision vision there. But I do think digital surgery is that continuing, I think it's connecting the dots. And it's not going to be one player, it's going to be an ecosystem of players. And I think that's where I'm excited about finding companies and startups and the collaborations between new med device companies where it's going to be at the fringes of those ecosystems.


Daniel Hawkins  8:17  

You know, I couldn't agree more with how you position that. And I'm reminded of 1999, when I'm with Fred Mall, in Mountain View, California, and we're talking about the opportunity for what is now robotic surgery, we actually ran from that word, because it was scary at the time, if you can imagine that. But we talked about a future where we could record procedures, we talked about a future where libraries could get created, where you could deploy artificial intelligence where you could learn as the surgeon treating a patient incident on the table from the experience of the 5000 that preceded you, not from the exactness of what they did, but from the overall understanding of how to how to use that body of information. Could you use artificial intelligence algorithms against live video recorded at that point asynchronously to provide you information, incidentally, while you're treating a patient, that was a vision. And then we got back to our day job, right? Because that's the time computing power wasn't there. The capabilities weren't there. There was no way to gather that information. We were not. We were we were speaking of the vision, but not talking of the reality, if you will. Fast forward a handful of startups later, I left my last one, Shockwave medical, in 2017 pre pandemic, with a charge to create a network. And that network is actually putting eyes and ears in operating rooms. We're doing it for a whole slew of reasons. But one of the key reasons underneath all of that is we want to digitize every procedure, calf based procedures, open procedures orthopedic, neuro, robotic, and otherwise, with a basic notion that there's an ecosystem that get can get created, where you are acquiring optics inside of the operating room intraprocedural imaging through scopes through Cath Lab feeds in the like. And if you've got a proprietary way, with hardware and software to aggregate all that deliver that content back to industry who makes the devices in that in that field in that world, in a consistent platform across procedures, that's now actionable. Right? One of the challenges that that I recognize back in '17, is you can't really get outside of robotics, the kind of information you need in every procedure possible, because the cameras aren't there. The interface imaging isn't there, the audio isn't there. So we created a system that allows that I couldn't agree more with your vision, that if you gather those, those those bits of information live during a procedure, you have learning opportunities, from 1000s of procedures proceeding to benefit the patient whose incident on the table at that time?


Tal Wenderow  10:59  

Yeah, you know, I don't want to repeat it, because otherwise we'll say the same thing. But to me fundamentally, is, the way we treat patients is exactly what's happened that patient and delete all the previous memory. And the way physician trained are like your son, Chris is the way this his physician who is hospital doing cases today. And we you know, people using democratized all of that, in the end of the day, we're not personalized for that patient that day. So to me, digital surgeries, smart devices, connected devices, it's things that come in pre op, post op, we've probably all seen the same things, but from different angles. We always pick up in the hands of those that doing those 10,000 cases, the majority of physician not doing a lot of cases. So how do we help them see through how do we help them identify new things that they don't see a complex procedure that you can log in with your system to help them and, and there's just so many opportunities, but in the end of the day is to me is how you personalize and how do you follow on the procedure and post treatment. Because most of us are all as a medical device company, we think about the entire procedure of post or pre. But we don't think about continuum of care because we don't have that platform in the treating physician posts is not the same ones, the operating physician or the diagnostic physician. So to meet that digitalization of that process of throughout the entire ecosystem, more than the surgery will benefit patient even post because we all know what happened, the rehab people don't take medication, you can take that to digital health, and all of that it's all connected at the end of the day.


Rachel Van Stratton  12:27  

Yeah, I agree. I think it's as you start to look at the amount of data that's available, and being able to utilize that to transform outcomes, and reduce healthcare costs and give patients more hope and ability to recover faster. That starts to set things in motion from all of the things that the panelists have have identified as ways to do that. But being able to really manage and help to improve outcomes.


David Uffer  12:59  

So these are quite lofty objectives. And I think that's the only way we're going to make meaningful impact in our procedures, in our outcomes, is this the strategy of 1000 mile journey starts with the first step. In other words, do we have to start it someplace with standardization? Or do we even go earlier with training? Do we try to get to optimization? How do we start all over in, in this journey?


Oliver Keown  13:29  

So I think everything you just described, and there's such a kind of glut of amazing companies that are putting it into action today, right there unlocking value through digital in the surgical setting and the procedural settings. I think of intuitive that's been digital for 25 plus years, as you say, capturing data at a systems level from sensors, using that and 10 million procedures worth of it to power a variety of analytics, and I think, has an exciting roadmap and pipeline of innovation to happen. But I also get excited about how had the from these unique assets that's going to power potentially the ecosystems of the future to across training, customizable training, can we understand the surgeons performance Postback, but maybe even real time on where you know, they are maybe falling short, or where there's opportunities for improvement and maybe intervene in a way that's and then also on the training side, opportunities to use that data again, that's being utilized today in the operational side of the healthcare system to use real data from real systems real procedures to inform how to manage how to optimize a robotic surgical practice or otherwise and very intuitive examples in there. As I said, there's, there's so many startups that are using AR VR on the trading side various technologies to utilize some of these datasets. So I think there's just so much opportunity and there's a lot of proof points in the market today. The builds towards the the grander visions. I think we've all laid out


David Uffer  14:59  

There's, there's an obvious reason why the panelists here have deep history, and even current interaction, as you bring robotics to the market. There's a computer interface between the user, the patient and the devices. We're looking at a very low penetration today of of robotics, across the entire definition of procedures that we earlier discussed. How do we capture all of this data in the rest of what we're doing from non roboticized processes and procedures? And then not only how do we capture the data, I want to take a little bit of time talking about how we store that how we depersonalized that? And then the really difficult one and how we share that. Rachel, you want to start us? There? I know Daniel,will go on for a while.


Rachel Van Stratton  16:01  

You know, I think, to answer your question about other procedures, right? This is not just robotics out there. So how do you look at the ability to utilize devices? I think even people talk about whether or not it's open source, you know, how do we share data across multiple companies? You know, how do we make that happen? Because as you said, we're all competitors. But at the end of the day, we all are driving toward the same, the same goal. So looking at all of our devices that we have today, trying to really understand how do we gather data from those that can also be applied in other aspects of surgery? You know, just the idea of of obtaining that data. I was talking with someone yesterday, there's a balance, right? It's it's there's the government's are starting to put a lot of restrictions in place on how to get access to that data, whether it's consent, or does the surgeon have the rights to it. And that starts to become a hindrance from a digital perspective, because you want these improved outcomes, and you want to get there. But then when you go to implement this in a hospital all their IT folks are like, 'Well, wait a minute, wait a minute, like what are you connecting to' because they can't afford the breaches, right? The breaches are bad, and bad for all of us. So that's where we have to strike the balance and really try to understand how do we manage it in the most compliant and cohesive manner? With the tools that are available and storage available today and being able to share it widespread?


David Uffer  17:36  

Tell you shared with me some unique perspectives on that?


Tal Wenderow  17:40  

Yeah, I mean, the data is always challenging, you know, first, you can take all these cyber companies and just bring them to healthcare. And you see more and more coming, we need the technologies out there. That, you know, Amazon know exactly what they're going to order, and it's tomorrow on my front door, we don't care about it. So it's also meaningful, okay, giving all my data and to the them. So I think it's also a consumer side that the consumer, I think most of them don't care about their own data, it's more the hustles protected because some lawyers sue them once in a while about the liability, it will take time, meaning it just a transition, we obviously need to do our job to protect the data, analyze the data, and do it from our end, right and gain the trust of the customers and the physicians. I've been advised in some companies are trying to monetize that and trying to create a database. And their challenge is exactly that the May of the world and the MGH of the world, I don't want to share any data, I want it locally, I don't want it on the cloud. And the challenge of the hospital, they don't own the data. They think they own the data, because the data is actually the patient. So the best solution is somehow those go to the patient and get from there the data. But that's not simple. Because how do you get them? And how do you load that? I think it will take time, I still have CDs of MRI of my son in my house, that I don't know what to do with that. Someone wants to digitalize those, but it's time it's progression. It's trust. It's over the above.


David Uffer  19:06  

Chris, you see a lot of facilities you have probably one of the most diverse portfolios does the mayo, want to share with you down the road here, Scripps or UCSF says we want to compete in Northern California, and be the best and don't let anybody learn from our experience? Are they saying let's rise all ships and improve?


Chris Cleary  19:27  

Look, they're all saying both? Right? I mean, everyone's coming at this from a different direction. And I think if you're in the industry, you've got to play through and understand that at some point, data rights and security are going to work themselves out and people will have access to the data because it has so much value. You know in the intervening period, yeah, look different personalities inside. The same companies are gonna have different viewpoints on this and a lot of them are felt very strongly and, you know, you got to play through you have some serious demands for being paid for their data rights and stuff like that. But you know, the reality is, sometimes it'll be worth it. Sometimes it won't. If you go back to the, you know, the founding of the internet and kind of how choppy that wasn't the beginning, I think we're kind of at that phase for digital surgery. And, you know, we're all going to have to play through understanding that history is very likely to repeat itself, and we're all going to have access to this data down the road. So I think everybody here is probably behaving that way. You know, we are it's not easy. You know, we're all fighting for proprietary access to the pack system sometimes. And, you know, we're not all going to get it. You know, there, there may be a real estate constraint. In the market, there's only so much room for so many boxes that have universal access to all this data. And I think that's like a real, you know, like, scarcity factor in the market that we all have to understand, I think there's a value to being to having a workable ecosystem early, as opposed to late. But I do think at some point, we're going to get through all the competing rights and security concerns.


David Uffer  21:14  

Oliver, tell us about your attitude toward open source, sharing of the data as well, and that you're going to capture so much, but you're still going to need many other inputs as well to make more meaningful use out of even your own instruments and technology data. Is this something that all the data you'll keep proprietary? Or is it again, going to be an open source and shared across the industry?


Oliver Keown  21:43  

Well, I think, you know, data's really only as valuable is the insights, right? It can unlock. And I think it's the connectivity across different data sets, different environments, it's going to create value in the applications that can run on that I do think it comes down to value exchange between participants in that equation, right, where there's value between access to data and collaboration. We invested on the venture side in a startup company called flywheel that IO that's trying to address some of the challenges that you highlight that it's, you know, the interoperability, the sharing the the kind of uncertainty around sovereignty of data as it relates to surgeons or hospitals or patients, ultimately, and how do you facilitate collaboration? What are the business models you mentioned, you know, Mayo, they have wonderful collaborations with external companies that are helping kind of activate the value of their data. And I think we'll see more of these kind of federated learning platforms that are able to support the connectivity between different datasets to power applications, be it research, be it you know, some of the tools that we described around training, and other things. So I think it's, it's in the early innings of how these various assets that different stakeholders are bringing to the table are going to unlock value, but I think it'll come in the collaboration with different participants.


David Uffer  23:03  

Daniel, we talked a lot about the perioperative process. And a few of the other panelists hinted at that too. But for just what happens inside the OR, because we all understand that you have to have somebody prepped and prepared appropriately before they get there and then taken care of after the procedure. But everything that happens not only in vivo, within procedure, but ex vivo, around the entire OR suite, you shared a lot of different insights about the data and the need for different capture in the entire suite. Share a little bit about what we spoke yesterday.


Daniel Hawkins  23:44  

Sure, yes. So a couple of points, I guess on on a few of few things mentioned by other panel members. I actually started off as most entrepreneurs in this venture thinking, 'You know what, I'm going to create a data warehouse.' That's what I'm gonna do. And then I'm going to layer AI on top of that, and I'm gonna go clinical by every procedure, and it was this grand, grand grand vision. And of course, you need to start somewhere. So we started somewhere. And they spent a little bit of time with a provider networks, in an appropriately frame framed conversation around recording in an operating room, with the appropriate set of folks will turn into what what we'll hold on a second. We own that data. And we're not going to let you on that data, in fact, we're going to forbid you from recording. Now the physician might want to record, but if the physician has administration administration might have different opinions about that. Right. So those conversations turn into a really interesting dialogue about Providence, a really interesting dialogue about where's it going to be housed, who's going to be allowed to use it, we own it, we might license it, but not to you not to a third party. We're going to license it to somebody in industry. Right, any of the three on this on this panel and others For a particular procedure related access, so pick, pick your robotic platform, a provider might license recordings associated with that platform, to that particular vendor, but to a third party that aggregates everything, normalizes it, make it open source, bad idea not going to happen. That's a really interesting set of dialogues. That informed a little bit about what we're doing at my company. But the other thing that I learned very, very quickly is there's so many different platforms of capability that are getting created. And to your earlier your question just a moment ago. The reality is that from our perspective, and we actually frankly retooled how we think about this a bit. The digitization of a procedure means every procedure. So where do we fit in that world, we fit in that world where we provide the eyes and ears in a room with local edge based high powered computing, and a secure approved internet connection to a cloud. In other words, we're kind of like an app store for the capabilities that are out there being created by companies that are probably right here. Right. And in that world, we believe that the right place for us to sit in that ecosystem is to be the input device, if you will, for the acquisition of material meaning audio, video, intraprocedural, imaging scope views, operative field views to bring in for that interrogation to a third party resource of some type developed by again, companies here and otherwise around the world. And then the output of that goes on to either the robotic surgery screens or on the screen in our operating room, because our console has a screen on it, to provide an output for that type of intelligence. But when you start creating asynchronous libraries, I've arrived at an opinion from the marketplace talking to us, from providers speaking to us that a single repository is highly highly, highly unlikely. Those relationships will be between the Cleveland Clinic and intuitive between MGH and Medtronic around specific use cases specific devices specific applications, and those are likely to be value exchange relationships. And, you know, our place in this world where I might have thought it was the entirely is really a facilitation of that whole dialogue. And, and my personal view of it is that expertise that is gathered from 5000 robotic procedures on an intuitive system is valuable to intuitive users on a Hugo is invaluable to Hugo users. On, you know, for a an open surgery, knee replacement is valued to the maker of that device. And and really my view of that, that that universe, if you will, is that those those relationships are commercially driven, between provider and the the developer of that device. And it is around optimizing the care of the patients treated in that facility. Now, we talked about anonymization. I think he could do that with artificial intelligence, you can do that with scrubbing, much like the license plates on Google Streetview. You can't read them. Right? You theoretically, you could do that same thing. In fact, we're doing some of that in our own labs, right now, engineering labs, then you can get into a conversation of making them available more broadly. But unless and until that's fully solved, it seems like a challenge.


David Uffer  28:24  

So let's play off of what you're building and developing. And I want to go back down to Chris, traditional device diagnostic manufacturers, they haven't historically been structured to develop software for data analytics AI. How do you bridge that challenge? Is this license partnering, co developed? Or let the others build that and acquire or integrate?


Chris Cleary  28:53  

Now it's the right question. You know, Medtronic is a software company, the degree to which we have historically written algorithms for hardware, you know, we're not a by any means a software company in the traditional technology sense of the word. So you know, when we buy a company, like digital surgery, we're buying the capability for software encoding and stuff like that. Excuse me, the, you know, the reality is, if we're going to get big, we're going to have to rely on third parties to, you know, get bigger and better and to make our ourselves more market oriented. I don't think we're going to turn into Oracle overnight for you know, for that kind of capability set. So, you know, we're we're counting on the ecosystem of data that's been described up here, I think, for us to be able to evolve our hardware into, you know, usable data that improves the surgical experience for the surgeons and for the patients. And, you know, the algorithm writing expertise that we've got where you're kind of optimizing outcomes that that's an ongoing valuable skill set that we want to preserve. And, you know, we're going to have to augment our engineering capabilities to include, you know, enhanced software capability that we don't, you know, we just, it's not who we been. So, you know, we don't think any major strategic can go it alone. You know, we've got to have a partnering attitude toward this. And, you know, just one random thing. If you look out 10 years and say, you know, what's really going to drive this market, the the med students that are getting trained today, we're gonna get trained in these kinds of digital platforms, and the demand for increased reliance on these libraries of data in imaging, and you know, benefiting from the 10s of 1000s, procedural experiences that are stored, you know, whether they're Medtronic, or Intuitive or J&J or whatever, that's, that's going to be a market demand. And it's going to come from our customers, you know, 10 years into the future. And that's why I just figured this stuff's gonna sort itself out the demand from the the ultimate customers of large strategics that can afford to build and implement robotic platforms, is going to make us have to work this out amongst ourselves one way or the other. And we probably don't know how yet but you know, figure it out.


David Uffer  31:28  

Somebody's going to argue, disagree. Thumbs up,


Rachel Van Stratton  31:31  

We're not. Very well stated.


Tal Wenderow  31:38  

So tell me to disagree now.


David Uffer  31:41  

Well, you I'm sure you will. That's nature. You have a tech center looking at a lot of digital solutions. Is this going to be something that you look to roll out for others? Or is this to be integrated within your other commercial offerings?


Tal Wenderow  32:02  

Yeah, meaning to be transparent, the short answer for everyone on the panel, you will not integrated that, right, because there are stakeholders and market and a lot of things. But I think, obviously, data is the fuel to everything. And we all speak about the holy grail of AI and identify the lesion and just press the button and go, we're far away from that. I think you can start with digitalizing. Take a stapler, make it smart, take a grasp, make it smart, take a stand to make it smart about it, then feed it back to a specific procedure, get the data from there, then grow meaning I think AI I run an AI company before that. You speak with the AI folks. And first most of them are very theoretical, right and they speak ay ay, you see that I had to Google what is AUC and go back to statistical course and understand what you see. And then 85% That seems very low to us in healthcare that you have 85% probability to be successful in your prediction. So how do you take those AI and use that to augment the skill set, meaning we're not trying to replace the ducks, let's make it obvious. But I think robotic and I'm a big believer in robotic, obviously, to your point has a low penetration, you can start taking a lot of manual procedure and digitalize them, and intraprocedural all the surrounding of the procedure. You take that as a first step and find that where you create the most value in digitalize that aspect. And then you move to more sophisticated one, whether it's soft tissue characterization, whether it's robotic, whether it's how they look in the previous 5000 cases, how they connect to remote, but we have to start with something. And to me, the biggest challenge of digitalization is how do you monetize? And how do commercial commercial launch that because the hospitals are all in the red, especially after COVID. They hate into this new stuff. And you know, you have the startups as trying but get pockets of information, but no one wants to pay. You have the strategic that we want to launch but we care about our devices, so you have to marry them. So to your point, we actually did try to do the hybrid approach, because we are young companies with two innovation hubs, one digital surgery, like full startup, ping pong tables, all of that Minneapolis, the otherwise vascular intervention in the Bay Area. And try to combine that with, you know, staplers and devices and think about it. But in the end of the day, there's so many companies will agree with that, and you have to connect them all and the first to connect them all and spend the money and think five years ahead and not one year ahead. We'll, we'll be ahead of the time, but it's a big bet. That's the problem. It's a big investment to retrain, and kind of cannibalize your own business. And that's the biggest challenge right now.


David Uffer  34:42  

You talked about the commercial models. Rachel, this is a great place for you to start talking about. Is this going to be monetized? Is this going to be just an added service to offer to your customers that use your technologies, you're going to have to live get different commercial models? Are you looking at different commercial models? Who's going to pay for this? How do you demonstrate the value? Or what the price point for something like these solutions could be?


Rachel Van Stratton  35:13  

Yeah, price points are difficult. Especially if you're looking to get something out of it, right, you're getting data out of it trying to get value for your product out of it as well. So we're looking at a lot of different commercialization models, marrying it with our own current products. Building on those having packages of things, we then also have to start looking at service and how do you manage through the service aspects of that for your different software? Because software, historically, you know, you've whether it's bugs and getting people understanding, you know, okay, this is bugs is this what? But yeah, commercial models in general are going to continue to be a moving target, especially as all of us continue to go to market. And everyone has some really great creativity. And so one of us comes up with something and then the other ones like, oh, wait, that's a really good idea. And so, there's a lot of different options out there. But monetizing it, something that's digital is is definitely going to be difficult, and is already I think proving, proving to see that.


David Uffer  36:27  

Oh, ever, you've, you've introduced a lot of different concepts and technologies here. Tell me when we get to digital, and the intuitive model minutes, what is the commercial and the monetization of this look like?


Oliver Keown  36:41  

Yeah, I think, you know, just echo it's a challenge, right? For for the bigger medtech players to kind of navigate is this direct pricing? Or is this an opportunity to differentiate and to drive stickiness and, you know, kind of commercial models for our core business, I get the luxury of spending my day meeting early stage companies and startups and, you know, they have to hustle, you guys have to hustle to figure out how to create value to monetize that without, you know, the fallback of selling more, you know, capital equipment and the like. And so, I look to some of the exciting models that are being experimented in the startup space, you know, across creating value, the subscription models, the ability to demonstrate longitudinal outcome improvement and tie healthcare economics to that the reimbursement strategies in certain domains, even going straight to the payers or even like care navigation, right, as you think about some of the outcome improvements that minimally invasive care that many of the platforms that features and outcomes this technology is represented here could unlock could align with right in terms of the peer model. So I think it is in the early innings. But I think we're going to see a lot of innovation in that space. And you know, I look to early stage companies figuring out some of that, probably on behalf of the med tech companies, and then med tech companies themselves, creating value being really disciplined to demonstrate that prove it out and find paths to monetizing it.


David Uffer  38:04  

I have a lot of people very bullish on digital surgery. And, of course, we're going to find a lot of people that are skeptical. And typically I found that because of the enormity of the topic where people just say this is a giant issue to tackle. We're gonna get there and I wouldn't have put this panel together if I didn't think we would be able to add supreme value. Tell us about the biggest challenges though, that you're seeing Chris to be able to roll this out.


Chris Cleary  38:34  

Yeah, look, I think short term, it's it's access, it's figuring out the data rights you know, how you make a scale business model out of sub scale deal data availability? I think the mid to long term you know, it's not a challenge I think it'll be an exciting ride this will turn into an actual real business you know, medical devices really hasn't been if you think about it, it's kind of like you set your price it declines over time. It's dictated by you know, government set reimbursement that's copied by insurance companies it's not really like a real business no one's really competing all that hard. You know, this this is going to be the freakin Wild West and I think it is a decade of massive business model innovation to look forward to so I I won't be around for it, but I'm going to wish all of you I'll be watching I just want


David Uffer  39:34  

Chris is give me the funny look, because I think the only thing standing between him in St. Patrick's Day is is this panel. That I don't think that's standing between noon St. Patrick's Day. I'd like to thank each of the panelists. This is really been a joy to hear these different perspectives. I invite anybody here in the audience. They're very approachable unless they were linked to another meeting, but I expect they'll be here Throughout the rest of the few days, we have left 32 years in med tech and I gotta say, I've never seen an assemblance of this volume in med tech investor conferences. So very, very happy for Scott and what he's been able to accomplish with he and his LSI stuff. So a round of applause for LSI and thank you for our panelists.








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