The Investor Perspective on Medtech's Digital Revolution | LSI USA '23

Transcription

Paul LaViolette  0:07  

It's just a pleasure to be here a couple of years ago, we were virtual last year people kind of came out post JPMorgan and attended. I think there were 300 people, it's four to five times that this year. So congratulations on really pulling, pulling together what is becoming a, an essential meeting, I think within the medtech ecosystem. So good to be here. I'm Paul LaViolettte managing partner with SV Health Investors. Lana, I'll just turn it over to you. And then we're gonna go Andy and Simon. A couple of brief self introductions, and then we'll dive right in.

Lana Caron  0:37  

I'm Lana Caron, Senior Director at Philips Ventures representing a strategic on this panel.

Andy McGibbon  0:44  

Yeah, Andy McGibbon. My managing partner at Sonder capital, we do early stage medtech investing,

Simon Turner  0:49  

Pleasure everyone, Simon Turner, I'm a partner at Sofinnova Partners. So we invest into life sciences across all stages.

Paul LaViolette  0:56  

So it's about digital medtech, and digital medtech revolution, which may be presumptive. We'll talk about what defines a revolution. And whether we're actually in one or not, I think as a panel, we looked at our interactions for the meeting. And we all felt that a majority of every interaction, every company, every discussion around the hallways, or in the ballrooms was, in some way related to a company that had a digital element to its business model. It's hard for us to tell yet how real all of those are. But there's no denying the flow. It's active, it's real. It's becoming a proliferative part of our ecosystem. So digital medtech is here. Now we have to figure out how to build it out to frankly, monetize it, how to overcome some of the intrinsic struggles associated with it, I was privileged to be at a talk given by Tom Friedman, a couple of days ago, he's writing a new book. And he was discussing his perspective on just the rate of change in the world. And he described a curve, and the curve had two lines. One was the rate of human adaptability. And the other was the rate of technology change. His basic message was for the first time in civilization, technology is now changing at a rate faster than then we can accommodate it as humans. That hasn't always been the case within med tech med tech has evolved. we've iterated we've seen a lot of innovation, but we've always generally been able to keep up with it in the healthcare delivery system that we know well and understand. If you look today, at the provocation that digital has as it relates to the meaning of med tech, it's pretty easy to argue that digital medtech is now moving faster than the ecosystem of healthcare, delivery of payment of reimbursement of business model of delivery is able to sustain it. And I think one of our challenges maybe today is to now dive in directly to that, that conundrum. How fast is it moving? What what comprises it today? And how do we turn these really bold ideas into great businesses? So maybe, Simon, I'll turn to you and ask, how do you define medtech digital versus digital medicine, digital health delivery, and some of the broader health, digital systems that are not really linked to medtech.

Simon Turner  3:40  

It's a super interesting topic. I mean, the way we've tried to think about it as almost as two separate entities, but they're also reliant on each other. So medtech, per se, let's say it's, it's pretty approach that always requires a device or some sort of a signal generating tool. That's the kind of digital medtech side of things. Whereas when you look at digital medicine, the way we've tried to categorize it is actually there are two key components. One is data. This could be very well structured data, or in fact, heterogeneous data, but then also an ability to interact with it. So a computational component to that. So you're actually making sense of it. And the ultimate objective of this is how do you basically bring those two components together to make sense and have an action ability to it? So when we look at this, this kind of space in the the way digital medicine is evolving? To your point, Paul, it's going extremely fast. You know, we've we've seen advances like what Google's been working on with their med palm, they had a first generation med palm a number of months ago that achieved a 60% success rate on a medical exam. Med palm two came out a few weeks ago, that's 85%. That's equivalent to an expert doctor. So the rate of change the rate of adoption of this type of technology can be exponential if we kind of give it that that push,

Paul LaViolette  4:48  

Lana and Andy, some examples maybe within your portfolio or within medtech as you look at it, what might be a great example of a tangible business that has emerged today in hospital out of hospital that is really combining digital and med tech.

Lana Caron  5:06  

I think StrokeCare Pathway is a great example. If you look at the treatment or cath lab space, robotics is definitely being helped by adoption of digital virtual care. And if you look at the rest of the stroke care pathway, early detection of stroke, and stroke triage is a huge problem. It takes too long to recognize stroke currently. And it takes too long to bring patients to the right hospital to for treatment. For example, it takes about 70% of patients that get to the hospital, actually get to the wrong hospital. And 40% of the patients they'll get to, to to the hospital, are no longer eligible for treatment. So we have a huge population that's undertreated and we have a huge access to care. So the operational and the problem exists, because we have huge inefficiencies is a complex pathway, you have a lot of handoffs, so it's a perfect problem to be solved. For by data AI, interoperability. So I'll talk a little bit later in the conversation about some of the companies that we have an out portfolio, but also that exist in the ecosystem. But again, this kind of problem cannot be solved by traditional medical devices, and some of the new technologies that are being introduced, right for treatment, like robotics, like some of the med devices, we are seeing that digital health or how digital is driving adoption of those traditional medical devices. So it's really important to think about this across a pathway.

Andy McGibbon  7:03  

Yeah, and I think there's a few ways to think about I mean, I think you, Paul, you kind of refer to this, but there's the concept of the Venn diagram of digital and medtech. And maybe those two are converging. I think there's also probably an abstraction that we could do about digital technologies in medtech. So if you think about ways of integrating products into workflow that aren't necessarily the product itself, there's also digital technologies in the manufacturing of, you know, medical devices, as we think of them traditionally, those are probably beyond the scope of the conversation we can get to here. But I think in our portfolio, you know, there's, it's an, it's a theme. I mean, I think if you think of things that we're trying to do in healthcare, improve outcomes, access to care, and change how we do business in healthcare in a more efficient, cost effective manner, oftentimes, digital technologies can enable those outcomes to happen. And so, you know, I went through the biodesign fellowship. So I think when I look at digital technologies, I kind of flip it on its head and say, Well, what's really driving the need for something to be digital. And in some cases, there is something that is actually driving that in some cases, it's more a interesting product feature and, and a way that, yeah, we can fill out the buzzword bingo card that Simon was talking about.

Paul LaViolette  8:14  

Let's let's go there, because digital may or may not be crucial, it may or may not change an outcome, it may have the potential to change an outcome that may not have been demonstrated yet, which of course, is a barrier to adoption. So two questions for everyone. Where have you seen data monetized? And the second would be what sort of barriers do you think are most essential that digital models have to overcome?

Simon Turner  8:42  

Oh, well, this is the interesting thing about the kind of digital medicine side of things, at least my perspective, it's you've got so many potential business models that you can innovate on top of, you know, you have a core platform, and then suddenly, you can have multiple different services that can be developed from it. I think one of the ones that we've seen kind of be taken up the fastest is in clinical trials. So if you're looking at clinical trial, recruitment stratification of these patients, making sure that you're getting the right ones into your trial most effectively, the digital components of that have been extremely helpful. I mean, it's as simple as you know, you're able to measure gait, you're able to measure, you know, how active is a user, if you're looking at depressive disorders, for example, how lethargic is a patient just based on their smartphone movement, the accelerometers and things like that. So these types of tools, at least for the clinical trials initially, probably going on to being able to stratify for treatment efficacy and things like that, once they've been validated in the clinic. Exactly. And again, it comes back to I guess, the next part of that it's where do you need to bring these tools to and the way we think about it is, again, we're Life Science investors. So we're looking at the need first, and then the technology being applied on top of that, to really tackle that. So you're, you're treating the inefficiency of the system, if you will. I think that's the right way to do it. Well being which is, let's call the more consumer products. There's nothing wrong with that. It's just that's not where our expertise lies.

Andy McGibbon  9:58  

Yeah, and I think it's something that still has To evolve by and large, I mean, from our own portfolio, I could probably pick on a veil, which I know tomorrow morning, there's a conversation with Daniel and Fred mall, about a veil and the specifics around that. But I think that's an interesting area where it's kind of at the edge of maybe just describe that for everybody. Yeah, sure. So Avail is essentially a console that goes into an operating room or cath lab. And on the other end, really anywhere in the world, you can have someone with a tablet interacting with the, OR or the cath lab in a very rich manner. I mean, I think many of us in med tech have been in the room during a procedure kind of pointing at the screen with a with a laser pointer or, you know, trying to avoid the sterile field. And all those kinds of considerations Avail really solves that and many ways it takes that makes it so that your high performing sales reps can actually access more facilities. You think about serving ambulatory surgical centers, for example, you know, a lot of things that enable your sales force or your clinical support personnel to really support these cases in a much better, richer way. And so, you know, again, I don't want to steal the punchline from the conversation tomorrow. But they announced a large partnership with Medtronic is actually their neurovascular group, in December, in part to roll out this technology. And so when you think about the monetization there, and the business model that that's built upon, it's actually more like a utility in many ways. It relies on the footprint, and now you're charging for time, which really, you know, that's different. That's something that med techs not really used to and I can say that's kind of on the edge of med tech is not necessarily a device that is regulated in the way that we think have been definitely an interesting way to think about monetization.

Paul LaViolette  11:33  

Lana, do you have an example.

Lana Caron  11:36  

We seeing a lot of monetization happening and cross operational efficiency is top type of companies. So if you think about Suki AI that uses artificial intelligence to help drive efficiencies across documentation and reporting, if you look at stroke triage companies like Nika lab is AI and rapid. Again, all of these companies are leveraging automation and AI to help reduce cost labor content, and drive drive cost savings down.

Paul LaViolette  12:12  

I'm thinking about a Canary, right, which is new. It's taking a an otherwise passive implant and digitizing it putting sensors in capturing this, again, data on gait or other facets of joint healing and joint health. And really adding information to a healing situation to postoperative situation that would would not otherwise exist, very innovative, difficult to say, out of the gate, exactly how to monetize that, how much of a premium if I'm the owner of that, can I charge, but there's just some awesome potential there. 

Andy McGibbon  12:52  

Yeah, and I was gonna maybe build on that. And, you know, I don't want to pump up our portfolio too much. But another company in our portfolio is called Wondr Medical. And one of the use cases that they're looking at, is actually bringing devices that are otherwise not really connected to people, but actually making them connected. So you can imagine a virtual room or virtual space, where you can have clinicians really anywhere, again, that can access the image can see the image and you start thinking of abstraction layers, you can pile on top of that when you start looking at more advanced applications of AI or machine vision and those kinds of things. Back to the to the buzzwords, but yeah, and so I think, you know, bringing these devices that otherwise are traditional medical devices, but making them modern, I think the parallels with Canary there as well.

Paul LaViolette  13:37  

I think the question still remains How to imagine our markets, whether it's a market for fundraising, a market for IPO, nevermind that a market for m&a, where digital elements are a component and who's paying for it? And to what extent are they paying incrementally to access that technology versus something more conventional that oh, by the way, happens to fit into an existing reimbursement code, which happens to pay the bill. So that to me begs the question is this really isn't a revolution yet? Is it the first night and the first shots had been fired? Or is it deep in the revolution? And the pace is accelerating? Where do you How would you characterize it?

Simon Turner  14:24  

I'm very bullish on this. So I would actually say it's, it's really kind of surpassed what we've seen traditionally, in fact, when we kind of mapping out what's happening in the space, you tend to have kind of five potential exit opportunities, at least for us from investors. To your point, well, you were saying IPOs okay, maybe we let's put those next year. Yeah, let's, let's see, you know, we'll get there eventually. But of course, private equity. So we being VC, you know, private equity are very interest because very often these digital medicine companies are actually generating revenues. And if you're able to use that, consolidate them, in fact create these kind of bundled approaches, you can really turbocharged that revenue growth. We've got then of course, the tradition No innovators, so pharma CROs, very classical in that space. You've then got the next level, which are more the payers, because of course they're interested in how do we change outcomes? How do we bend that cost curve that we're seeing? And lastly, we're seeing AWS being extremely active. Google, even Uber has been toying with how do we work in clinical trial recruitment and such. So from our perspective, it's vast in terms of the actual actors you see in this

Lana Caron  15:23  

and maybe to add to this COVID really accelerated adoption of digital technologies across the board, providers. Patients are willing to adopt. And we also are seeing reimbursement. more favorable reimbursement, right again, COVID helped us here quite a bit. So I think that is definitely accelerating revolution. I think there was an evolution element here as well. But I'm also very, very bullish on what we are going to see over the over the coming weeks, months and years.

Andy McGibbon  16:06  

Yeah, maybe just to add, also, I think, I think we are in the early days of this, though. I mean, it's a period of experimentation. There's a lot of different models being tried. It's still a very fragmented marketplace where Yeah, I mean, you have some big folks that are experimenting, but they haven't yet established their dominance in the field of, you know, like Google's, the search company, but they're not the medical company yet. I mean, could they be there, maybe. So I think there's a lot of experimentation that's happening. And it'll be interesting to see how that plays out.

Paul LaViolette  16:36  

And I just want to let folks know, we will open up for questions toward the end. So if you have any, be thinking about that. And we look forward to answering, I had a meeting last week with the president of Mass General, and they're building two big towers to try and optimize their revenues. The one of the comments he made was mass generals, the number three, a hospital to be built in the United States opened its doors in 1810. Prior to that, there were no hospitals and everybody was treated at home. And there was a very interesting sort of coming around full circle to the idea that actually, most health systems are trying to figure out how to monetize patient care outside of the four walls of the building, because you know, you really can't just limit yourself to that. And so I really want to ask the question of the group about the digital transformation inside of care, and whether digital is really enabling the dislocation of care outside of the hospital toward the home. What's driving that? Where might it be having an impact? You mentioned robotics as an example, in the hospital, or for for non hospital, whether it's hospital at home, or whether it's aging in place, technologies in medtech that are helping really reengineer healthcare delivery? What are you seeing there?

Simon Turner  17:58  

I mean, pulling out an example, one of the areas that we've seen a lot of innovation happening is quite frankly, based off of your mobile phone. Now, these things are so powerful these days, because they're able to take very high resolution imaging of you in in a dynamic way. One of the things that we saw very quickly being adopted was this this way to treat musculoskeletal disease. So being able to provide basically a on demand continuous, you know, be it seven days a week approach to creating a home care pathway, basically, for these patients to do exercises, stretches, etc. versus going once a week to a chiropractor, or somebody expert in this field changes, the dynamics are quite radically one, you get the patient to actually just be at home and do these things on daily basis. But secondly, you're gaining benefit from it being a regular interaction rather than you know, once a week where the patient gets better. But then you have this delay for a week. And then you need to bring them back up to that level. These are the types of approaches we're seeing, you know, drastically change healthcare outcomes. And at home,

Lana Caron  18:57  

there was a huge push from different provider organizations, this time to develop and expand their home care programs. We speak with customers all the time that talk to us about what kind of digital technologies do you have to to enable this and again, reimbursement is very fear favorable now for remote patient monitoring, and virtual care. So what we are seeing is that digital is enabling screening, diagnosis, treatment and post treatment in the home setting. So it's just a matter of time for that to expand across different diseases and different geographies, maybe to double click on the stroke example. So we are we now have portfolio companies that are able to do early detection in the home setting that you can also do post treatment rehab stroke rehab, in the home setting company. Like, can do a health, unfortunately not part of our portfolio. And some of the other companies that help patients navigate, post treatment, stroke, rehab, and get to, to work and life a lot faster. I also wanted to double click on the treatment and robotics example. Currently, if you, if you, let's say are in a remote area, or in a country where you just don't have access to high qualified physicians, you are not going to be able to get treated. So if you you refer to MGH in Brigham. So we've got access to top leading physicians, if they have access to robotics, and virtual care, then they can actually provide treatment to somebody in Afghanistan or rural rural area. They might not be able to be in a home setting, but they're going to be as close to home setting as possible. 

Paul LaViolette  21:12  

I want to talk about maybe a tangible chapter in this discussion, something that individual entrepreneurs in the room can actually relate to. So let's talk about what success actually looks like. If you're building out a business model, you're building out a pitch, you're building out a story that is integrating the convergence of digital and medtech. What do you look for? And what might a great example of a success story be that you might share with the group?

Andy McGibbon  21:48  

But I think there's also a question of de-skilling of labor, I think the labor issue is a major one in healthcare that we should be talking about as well in the context of what digital enables.

Paul LaViolette  21:58  

We may not have time to talk about it, but health equity and ultimately, access is really the point. If it's, if it's a remote controlled the technology, if it's a de skilled service, if it's a remote cloud based analytics that can then allow for local decision making that's not directly derived from specific specialist physician on site. That's where ultimately, connectivity adds benefit to the individual. But let's go back to the portfolio examples.

Simon Turner  22:33  

Maybe taking one example, I guess it's in radiology, something we can all relate into. When you're looking at what's happening radiology 10 years ago, we were seeing the early signs of AI adoption was beginning to occur. And the entire kind of radiology community said, we will never adopt AI in radiology, or at least a large portion. Today, the reality is, it's quite the opposite. It's it's radiologists, even admitting those that use AI will replace those that don't, because quite frankly, the benefits of it are so drastic, you know, we're talking about improvements in workflow, we're talking about improvements in diagnosis, the ability to actually have reports being generated almost automatically by the systems. And the impact here is we're seeing it because one, you have a reducing expert workforce in most cases. Secondly, you have an increase in inflammation of the modalities. And again, because you're getting just so much more richer imaging systems. So you need this next level of expertise, quite frankly, to assist the entire process. But again, it comes back to you're assisting the healthcare practitioners, you're not trying to replace that.

Paul LaViolette  23:30  

Well, there's really no facet of the healthcare, human resource community that has sufficient talent available. Absolutely. It's just nowhere

Simon Turner  23:39  

Exactly. And you need to tackle these inefficiencies where actually it's high burdensome in terms of time, but not in terms of the skill set. So if you can, therefore redirect the skill to those very required tasks, you're able to basically use the healthcare resource you have much more efficiently. So that's how we see this kind of major advantage happening.

Lana Caron  23:57  

And I can talk a little bit about, again, companies like Niko lab, right and stroke triage company. What they do is the the help radiologists get to the images for patients that are at a higher risk for stroke and elvio, right, large vessel occlusion, so that so that those those kind of patients can get prioritized and get to the lab get into the cath lab faster than some of the some of the other patients and so that helps increase access to care and that helps drive the numbers that currently exist. So it also helps reduce the cognitive burden on some of the some of the physicians. And now the example again, some of the company that I mentioned earlier, Sookie AI the the have developed a voice digitalist system that helps accelerate and makes the process of documentation a lot easier for the, for the physicians. And what's, what's important here is that by the time you are done with your day, you're not worried about your physician notes, you're pretty much you can review the notes. And you're done. Right? So the burnout is a huge issue that drives so many physicians out of the profession. And so the value, right that Sookie brings is reduction, burnout, and potentially catching some of the errors. Or maybe if you have a lot of notes, sitting in on the back burner, because he had just exhausted and don't have the time to do them, then you're not able to really optimize your revenue cycle, you're not able to bill as fast as you want. So there are multiple, many different value drivers here from burnout to revenue optimization.

Andy McGibbon  26:02  

Yeah, and I think in our portfolio, our most recent addition to the portfolio is actually a company that's automating blood draws. So if you think of venous blood draws, and I think the labor issues that are prevalent, there are significant, we spoke to a hospitals network that has over a million blood draws per year. And they talked about one of their satellite offices, a few of the phlebotomist not highly trained, not highly compensated, went to lunch and never came back, because they saw that were that lunch place was had a higher wage. And I mean, you know, I think we're, you know, maybe the economics of, you know, the macro situation right now is going to change those kinds of things slightly. But I think it still speaks that up and down the skill curve, there's a shortage in the healthcare system and burnout and turnover are huge issues. And for if your hospital system, this has an impact on your top and bottom line. And so I think, you know, these are things that hospital systems are thinking about and trying to get ahead of the curve on. So

Paul LaViolette  27:00  

yeah, it's, it's impressive how this post COVID era with the macroeconomic drivers that you mentioned, has reduced workforce availability, burnout is immense. And so hospitals are not thinking about paying more for anything, but they will adopt technologies that are going to reduce eye time, hand time, labor time, because they need throughput to bill, and they can't drive throughput without people.

Andy McGibbon  27:30  

Yeah, that's right. And I think that is the way to think about it is augmenting the workforce, it is really enabling your core workers to do a lot more and to be using their time on the higher value pieces of their job.

Paul LaViolette  27:43  

Let's take, let's take AI to the to the nth degree and talk about interaction and even ChatGPT as it's been as it's now being applied, in some cases, in medtech, we looked at a company recently, that made a device for weight loss, and surrounded that device with a platform associated with patient support, interaction coaching motivation. And they realized, based on the obesity problem, we're not going to be able to scale an interactive resource. If we need to have a person, let's say, for every 100 patients on this system, or a person for every 500 patients, which would be remarkably efficient. So they started to integrate ChatGPT into the texting interaction with patients, and found that it would enable significant scaling of their business model without adding humans to the back end. Have you seen examples like that? And are you intrigued by that? And where does that nth degree of ChatGPT fit into medtech?

Simon Turner  28:50  

I mean, on our side, dozens of these examples, and I guess the best kind of use case initially, at least is if you think about triage, what are you trying to do when you're working with a patient, for example, that's going to a GP or something like that, you can actually use these automated systems, if it's LLM based chat, GPT, three chatGPT 4, whatever, to basically start actually collecting the information, those critical components for patient before they even set foot in the doctor's office. So what that enables is a physician to be able to look immediately a set of annotated notes in real time, basically the visit that the patient has produced, but that has been then restructured into a very effective report. The other advantage is that we're seeing is again, thinking about it beyond that for healthcare system. This will help standardize those reports. So for example, if its patient is receiving treatment X for headache, let's say that's the way that it will always be annotated versus, you know, the patient has x and therefore is receiving this type of treatment, which again, makes it very difficult to use for clinical trials or even just for general health review, for example. So these are the kind of the standardization approaches of we're seeing enormous potential it but I mean, the reality is, we're only starting to scratch the surface of what these types approaches can actually do they have limitations. Of course, you know, one of the perfect examples is, if you ask chat GPT 3 or GPT 4 for a question, it will respond with almost a certitude attitude towards you. The reality is, sometimes it doesn't know, it won't tell you that it doesn't know yet. So we need to be careful for that perspective. It's like a good teenager. Yeah, basically, you know, you're never wrong. That's the that's the answer that will give you

Andy McGibbon  30:25  

Yeah, and I think I think similarly, I'm intrigued, huge promise, but also huge risks. I mean, we also heard this morning about some of the inherent biases of what has, you know, what these platforms have been trained on today? The lack of healthcare specificity. I think there's opportunity there, it gives me a little pause. Depending on the application, though, again, in terms of how it's used in clinical practice, I think there are opportunities to leverage that because it does help scale it. I mean, that's the advantage of digital, broadly speaking, I think in the context of medtech is it helps you scale something. So if you can use that in a smart way, that's great. But I also would like to know when they're wrong,

Paul LaViolette  31:05  

yes, yes. Yes. Just, I want to move to one final question, then we'll open up to see if there any questions we can answer for you. But let's just talk about platforms, we commonly refer to digital platforms. And in some ways, they can be agnostic, they're there. They can be built around one clinical specialty or another. How do you think about a company that comes to you with a platform strategy? Is that beneficial? Is it problematic? How do you decide

Andy McGibbon  31:38  

The gift and the curse. I mean, it's both and I, maybe I'll, again, put the biodesign hat on for a moment here. But what ends up driving the conversation in my eyes is where is this really compelling application for the platform that's going to drive some kind of growth? Yes, you can use it here. Yes, you can use it here. But why? What does that really get you? Typically there is that application where the combination of you know regulatory path, reimbursement, clinical interest, all those kinds of things? point towards a certain direction? Once you're there, yeah, land and expand, I think is a nice way to go. But we have a lot of platforms. And I think that's a common struggle. The second piece, I guess, putting back on the sonder hat instead is what is the exit situation in that case, and who's going to buy it? If this is likely m&a activity, you know, the number of large caps that have, you know, the full scope of clinical areas that something might be applicable for is relative,

Paul LaViolette  32:39  

and in which those clinical areas talk to each other throughout the course of the day. Lana?

Lana Caron  32:44  

Yeah, I think what we are focused on is understanding the building blocks of the platform and what's repeatable and reusable, we have an investment in a real time image processing company. And they are currently focused and going after a cardiovascular space. It's, you know, they they're planning to expand, but we don't know, at this point in time is how long it's really go into, for them to take to shift, right? Or how long for them is going to, to gather the data, to train algorithms to validate those algorithms to then go through the the entire pathway, right of getting the FDA approval? So it's great to have a platform play. But the question is, how long it's going to actually take to, to bring it to market?

Paul LaViolette  33:46  

Yeah, great. We can't really see, are there any questions that we can answer? Does anybody have a question that we can address? Go ahead. And please shout,

Simon Turner  33:55  

should I take first, I mean, this is where we need to be very careful. I mean, we in Europe, we have GDPR compliance and these types of things. Now, the reality is, it's quite bespoke and specific. So it's about you, the individual patient. However, if you think about it more of a macro level, or taking a higher level of that, you know, we can take generalized information about a population and then start actually using that for other purposes. So for example, if you're a lab data company, for example, you're collecting information about an individual patient, you have that knowledge, you have that insight, you're able to make new inferences to diagnose diseases earlier, for example, that is GDPR compliance because that is patient specific information. If you anonymize that though, and take it up a level so you can't actually identify bespoke patients. Healthcare systems are very interested because it gives you a great overview of what the population it looks like how they're changing over time, but also, for example, Pharma would be interested from a clinical trial recruitment perspective, or even just overlaying that with their sales and marketing teams. So suddenly, you're able to see you know, where am I selling products? But where is there an increased amount of population that would benefit from it. So hence, why should I redeploy my sales and marketing efforts? That's the kind of thing that we can see happening. But again, it's just being clever with how you use that type of data. And making sure you you keep that limit. Let's save it.

Andy McGibbon  35:12  

Yeah, maybe also proactive about it. I think there was some recent news about some of the health tech companies getting in trouble, because now, their patients are being targeted for specific ads, because that, you know, it's generalized to a certain point, but our targeting on the online is so specific that you can actually kind of back into a lot of that. This is way out of my paygrade. But I think there were some interesting applications of people monetizing their health data through the blockchain, again, not anything that I could speak intelligently about, but it's intriguing the idea that you can kind of have some ownership of data and ways to monetize it that are a little different. I will

Paul LaViolette  35:47  

also say, the health systems in general, especially health systems that have a particular vertical in a disease state, that have been generating very specific evidence, and have a repository of it, but don't necessarily know how to convert that into something. At the same time, that's happening, you have companies that are now tapping in with a with a technology that will accumulate data and start to process it, though, there's a convergence of those two dynamics so that health systems and tech platforms are starting to say, hey, we put our data richness and your data scale and aggregation together, we can really accelerate our understanding about a disease category that we didn't know before. And so I think that's happening at a very rapid rate, and it's going to accelerate. Closing, we have closing minutes. So 20 seconds each. Tell us about the future of medtech digital revolution.

Simon Turner  36:46  

I think maybe I'll make a prediction. I I expect that in the very near future. We won't see many companies in the life science space that do not have a massive data and computational prowess component of it. That's my personal prediction, I think.

Andy McGibbon  36:58  

Yeah, I would second that. I think, for me, digital medtech is all about personalized medicine at scale. So better outcomes, while simultaneously increasing access and, you know, improving efficiencies. I think robotics is a piece where a lot of promise on that as well, which we touched on.

Lana Caron  37:15  

I think digital is going through to make a huge change at pop health level. And we see data, helping health systems, improve utilization of staff equipment, and increase access to care.

Paul LaViolette  37:34  

So plenty of barriers difficult still to monetize. But the revolution is happening, so get ready. Thanks, everybody.