Data Quality vs. Data Quantity — Getting to Market Fast or Getting to Market Right? | LSI USA '25

George Lewis  0:00  
All right, so it should be an exciting session today. It's about data quality, quantity versus data quality, and getting to market fast versus getting to market right? I in particular, was really excited about this topic because my organization arena, which is a QMS tool, we're always talking to companies about high quality, getting to market fast, but it seems to me, getting to market right is just important as getting to market fast, it's effectively two sides of the same coin. So excited to get started here today. Let's do some quick introductions, Caitlin. Can we start

Caitlin Morse  0:34  
with you Sure? My name is Caitlin Morse. I'm the CEO and co founder of BrainSpace, and we are in neuro trauma and neurosurgery, where we are managing brain pressure to avoid long term brain injury. And so data is a big part of the conversations we're having.

David Constantine  0:50  
I'm David Constantine, co founder and CEO of juniper biomedical we're developing dramatically improved therapies for pelvic health conditions with a unique neuromodulation micro implant and with a novel technology, we've had to pay very close attention to our downstream risks and make sure that our data was really, really strong as we approach not just FDA approval, but all of the market opportunities.

Cynthia Yee  1:11  
I'm Cynthia Yee, a partner at Vensana Capital. We're a Medtech focused venture fund.

Tonya Dowd  1:18  
Tonya Dowd, Executive Vice President of reimbursement, health economics and market access at PRIA Healthcare.

George Lewis  1:24  
Excellent. This should be an exciting discussion. I know when we talked last week, we overfilled our time very quickly. So we'll kick it off quick and get into some of the questions to the panelists here. You know, first thing to point out is most of the folks in the room here are probably Series A, B, maybe C funding, and many organizations are solely focused really, on, you know, FDA, you know, submission and eventual approval. And that's the sole focus for the business, right? We have to get to it. It's the only milestone to think about, or the primary milestone to think about. We all know there's a lot of other things to consider, and so I'd like to ask our panelists about some of those things. You know, first one would really be around reimbursement, and when should organizations begin to think about reimbursement

Tonya Dowd  2:04  
yesterday? Yesterday? Could I answer that yesterday? Yesterday? And I always tell clients, your reimbursement pathway impacts your market access and reimbursement strategy, so quicker to market with a 510, K clearance, maybe with a predicate device that doesn't have reimbursement. Well, that's a that's a bad decision, right? But really not even thinking about that and just getting to market quick. I would also say that FDA and looking at how they look at look at technologies, and how the payers and providers who are going to be using your technology look at it. FDA is looking at evaluating the device specifically for safety and efficacy, whereas payers and providers are looking at how does the device perform in terms of improving clinical outcomes for patients. And those are two very, very different endpoints and thought process. So really thinking about that as you develop your reimbursement strategy yesterday,

George Lewis  3:02  
absolutely other thoughts, things to add.

David Constantine  3:05  
One of the first things we did when we started the company was landscape analysis, on coding, coverage and payment for the technologies that we were developing. And we chose to do that because we recognize that a lot of our choices in clinical study design, a lot of our development choices really didn't have as much to do with the FDA as you would preemptively think about, because the measures are all a little bit different in terms of what the doctors are thinking about, what's going to drive their adoption, what's relevant for coding, coverage and payment, what's going to reinforce that motivation, and in the long run, what's going to Help with growth. So that was one of the first things we did, actually, and we do it cyclically, on a on a periodic basis, to make sure that we're well informed of how things are changing. Because it's certainly a moving target.

Cynthia Yee  3:52  
Yeah, I think when you think about a reimbursement strategy A lot of times, particularly for an early stage company, it is very theoretical, and thinking about whether or not existing codes are available or you have to develop a new pathway, and then coverage is a separate question. But in order to really pave out and make that a reality, you have to develop a Clinical Strategy early to get support and get coverage, particularly in a newer category. So I think starting from the beginning and thinking about what's necessary to get approval and then what's necessary to get coverage, are questions that kind of go hand in hand,

Caitlin Morse  4:37  
yeah, and in our case, it was actually something we looked at, because the technology we're replacing is 100 years old. One of the very first questions, before we even started the company, was, is there enough room here? Right? Is the existing reimbursement giving enough room for new innovation to get the kind of margins that we know either we will need later or strategics will need later, and so having worked on it from that side with people and known what. Needed. It was an early conversation before we even really got too far down the product prototype conversation to go, what's the room to really improve things, and can reimbursement cover that? And it was one of the key criteria why we chose to do this, as opposed to some of the other ideas we had, was there was sufficient reimbursement. And so I think it's really if you're looking at not just is technology beneficial? But is it a business? Is it an actual company that can be venture backable, that can be fundable? A big part of that has to be, what's the business model and reimbursement is a huge part of that conversation.

George Lewis  5:33  
Absolutely. I'd like to double click a little bit on what Tony began with is, you know, the regulatory pathway, you know, PMA versus 510, K, how does that have an effect on the overall plan for reimbursement? Is there a change earlier I assume?

Tonya Dowd  5:47  
Well, you don't need any data for 510, K clearance, and you don't really need much data for a de novo, and you need some data for a PMA, of course, but that's not enough data for the providers and the payers. They're a bar for evidence, again, is much higher, and they're looking at different endpoints, and they're looking at looking at it from a different scope and lens. So I mean, I would also say that I've seen a lot of lot of technologies in the neuro space, in particular, who are looking at a predicate that is actually low paid and not covered for certain indications. And they're, you know, kind of using that predicate, but not understanding that there is no payment opportunity, and trying to get themselves out of that bucket after is 10 times harder than just doing it the right way first. Well, especially

Caitlin Morse  6:36  
if you've just gone and convinced them that your equivalent for 510, k, right? Undermines that part of it. Yeah. I think in our case, one of the things we really look at in terms of when you get that clinical data is what your opportunity is to continue getting data once you're in the market. So in our case, our device, in addition to the therapeutic benefit it's providing for patients in the ICU, one of the things that intensivists are really excited about is the data that we're going to be generating, having AI ready, data that can be used in training models that can advance understanding of coma and how TBI is resolved, that is part of the value proposition people are excited about. So for us, having data that was sufficient for people to feel comfortable with the therapeutic but we have an opportunity, once we're in market, to be collaborating with those users and really building out those much more robust data sets in a much more capital efficient way, right? If the product you're taking to market is not going to continue to produce that data post market, then I think that changes your calculation on what you want to be doing pre versus post. And that's a conversation you and I have had quite a few times, right? We're coming at it from totally

David Constantine  7:39  
different angles, but but the takeaway is, is resonant and consistent. In our case, we have a PMA, so we we have to do a whole bunch of clinical but in in looking at what would the FDA is going to require, it's very different. I mean, the guidelines are very specific in what you're supposed to measure in the context of urinary incontinence. Our case mixed urinary incontinence, for looking at both urge, overactive bladder and stress incontinence guidelines from the FDA and those measures, for instance, pad weight is not an attractive measure clinically, they're not. They're not using that downstream in market to make a lot of decisions in the same way. So we have to look at what measures are pertinent for both the FDA approval and the consideration of regulators and the consideration of the doctors on the other end of that. Yeah,

George Lewis  8:30  
so I'm curious to double click on that a little bit. I know, Tony, you have a lot of experience talking to many organizations around this subject in particular. I mean, is the are they thinking about just the data needed for the submission, or do organizations, or are you advising organizations to collect other data earlier for, you know, bringing it to market? For example?

Tonya Dowd  8:48  
Yeah, we're advising organizations, and oftentimes we have to advise them on that, because they are thinking of the regulatory milestone as the endpoint, which we know. I think we would all agree that's not, that's not an appropriate way of thinking, but But thinking about an end to end evidence generation strategy, which includes real world evidence really kind of fit for purpose studies, which is kind of the new buzzword now, which is combining that clinical trial data right in a controlled setting with real world evidence, and bringing it all together in a continuous pattern, because it's not just one study that's going to resolve all the issues and to speak to all the stakeholders. It's a multitude of different different data

Cynthia Yee  9:29  
sets. I think there's really interesting ways that you can kind of design a study for regulatory purposes, because I do think that we don't want to try to do too much in one study and risk, you know, putting all your eggs in one basket and failing. But there's different ways in terms of follow up that you can split out the control group and follow up, follow them up, or cross them over, and that can be a separate study in and of itself, even though it's one study. And so that could be a capital efficient way of, kind of getting those two you. The studies that you need for coverage, but it's really kind of the same patient population. So we've known companies that have done that,

Caitlin Morse  10:09  
yeah, that's, that's a good point of what you call a study versus what the patient experiences as a study, right? Being able to do those different parts. We you also make a really good point about who are your stakeholders, because we talk about the clinical endpoints a lot, but for us, we have a very heterogeneous population in the ICU, if we only want to show clinical endpoints, that's a much bigger, longer, higher powered study. But for our hospital systems, if we can show a shorter length of stay in the ICU, that's a much smaller study to be able to show that, in our case, that has much clearer timelines associated with it, but has a lot of value on the economic side. So I think also, you know Tonya, when you're kind of saying for your stakeholders, who are your stakeholders, and where can you get what benefits from different studies? And so we'll start getting that clinical data, but we don't have to reach that clinical endpoint to start showing the economic benefit

Tonya Dowd  10:58  
right now. That's a good point about this. Who are the stakeholders? Because the payers aren't always the end stakeholder. It's the hospital system mainly, or the providers who are purchasing the device, the device and a buy and Bill model and showing them the value is is really critical, not necessarily the payers.

David Constantine  11:15  
It's a multitude too. I mean, it's it the the voice of the different clinical audiences that you may be approaching. And you've got a number of different clinical audiences that clinical audiences that you're speaking to. We speak to both urologists just for their first application, urologists and urogynecologists who approach things from a very different vantage point, their organized bodies approach things from a very different vantage point, and have different roles in reimbursement and encoding, coverage and payment, and talking to all of those different voices takes a lot of time, takes a lot of time to connect to them. Takes a lot of time to have those conversations and retain the relationships for continuous engagement, and to really make sure that as you're charting your path for clinical study design, regulatory approval, et cetera, and the downstream market work, pulling all that together to formulate your clinical strategies. It can be a bear, but it's, it's a it's a much worse bear to get to market. Have had total blind spots and complete the crater. So, yeah,

George Lewis  12:11  
yeah, yeah, no, I would agree. I mean thinking about like our customers and things like that. It's look just getting to market as quickly as possible, probably a poor choice. So how do you get there with, you know, a thoughtful product, and you've thought about everything in advance is probably massively important. Caitlin, I think you started to talk about this a little bit. But in looking around LSI and all the devices, it's obvious, if any of these things are generating a whole lot of data, you know, how does that play into the discussion? I mean, is, what's do you market that information? I mean, obviously there's patient confidentiality and HIPAA rules and things like that. I'd be curious to hear from the group on that. Yeah. So

Caitlin Morse  12:44  
obviously, it depends what type of data you're collecting. Right in our case, while we do have HIPAA considerations, we're not primarily looking at data that would be patient sensitive. So in our case, we have physiological wave forms, how pressure, volume relationships change those wave forms, and so anonymizing that data is very simple to do. There's not a whole lot, right? If you're doing computer vision and you've got the person's face in the image, it's a whole different conversation. In our case, one of the things we're really looking at from that data perspective is which data actually has a clinical action associated with it. Because there's a lot of ways where you can say, Oh, this is cool data. This is interesting data, but if the clinician doesn't know what to do differently based on that data, it's probably not going to see that value prop. And so coming back to all the different stakeholders you were talking about clinically, right? If we're talking about hemorrhagic stroke patient and how the color is changing of the CSF, that's a very different conversation than a pediatric neurosurgeon who wants to know, can this kid get up and walk around while they're recovering, right? So really understanding where the existing data and consensus is for clinical treatment, and then can I get you to that decision more quickly? So in our case, there's a number of guidelines and protocols that are just very labor intensive to comply with, and so that's low hanging fruit for us to be able to say, we'll give you the numbers you need, we'll do the assessment that you need. You don't need to bring in neuro PT. You don't need to have a nurse sitting there for 24 hours. So then you can do what you already know is the right thing to do once you get there. If the data is now giving you a new parameter, I think that's a whole different conversation, and that now requires the consensus building around what action do I even take with that new parameter? And that's where having these much more controlled clinical studies, right? If I say to you, if you had this number and you know what to do with it, there's a much lower level of control that's required in the in the post market study than if you're trying to say something brand new. And now the clinicians, you know, most of what they do is protocol driven. Most of what they do is consensus driven. And so when you come in with new innovation, you have to understand Understand where it fits in that clinical workflow and and that's the same for data as it is for everything else. It has to make sense for what the clinicians trying to accomplish

George Lewis  14:50  
for the patient. Excellent. David Cynthia, anything to add, thoughts,

Caitlin Morse  14:55  
anything to add. I

David Constantine  14:56  
agree with Cynthia's prior point. That aligns with what Caitlin was saying. Has to do. Do it, the segmentation of the of the data. So if you're if you're doing a study that's trying to tell too much, it's really hard to make that, that story resonate with the different audiences that you're trying to use it for. And if you think about it from a publishing perspective, in our case, and in your case, I think the trail of bread breadcrumbs that you're ultimately trying to create to the profound data that you're landing in market with, is also an art that warrants consideration for all the downstream characteristics, and parsing out, just like you're pointing out, parsing out your clinical studies in a way that tells a very, very clear story in itself, not all stories in one shot makes a big difference, and sometimes that can be more time consuming, but I think in the long run, is ultimately more valuable positions you better for being attractive for strategics and to be more successful in the market, whatever case may be for your company,

Caitlin Morse  15:56  
Cynthia, you mentioned risk around not overburdening Your study. Do you want to speak a little more to that? I'm guessing you've seen some of that go both ways. No,

Cynthia Yee  16:06  
I just think a lot of times people want to do everything in one study and in an ideal world that wouldn't add more risk. And it's okay if you do that as a secondary endpoint, but your main goal is to get to market and not, you know, try to answer too many questions at once, and then afterwards, you can do that in a post market thing. So when you say, like, speed to market versus, you know, getting to market, right? I don't necessarily think those are mutually exclusive, meaning you can get to market fast and then still with that 510, K in hand, go and run your clinical studies with a little bit more freedom to demonstrate your value proposition, whether that's a workflow question or data and efficacy question, I think that's sort of table stakes. You have to do that, where you do it before, pre market or post market? I don't think it matters.

Caitlin Morse  17:04  
We were very fortunate to have clinical advisors who had been down this path, because, let's just say, the first version of the study that I was proposing, they were like, this is way too much to try and do all at once. And kind of re back in of, okay, what do we really need to start off with? And then, like you said, what are some of those secondary endpoints that we can accomplish over time?

George Lewis  17:25  
That's really good input. I mean, as long as we're on the subject, I mean, how do we collect as much evidence as possible to support some kind of pricing strategy? And when do you think about it

Cynthia Yee  17:35  
from the beginning?

George Lewis  17:36  
Yeah, I think from the softball, right? But, yeah, I'm not sure. Many organizations, I'm sure looking at the goal posts of FDA submission and not necessarily thinking about it as early as maybe they should.

David Constantine  17:47  
I mean, from from my vantage point, it's taking into account any commercial perspective. Early is crucial. But in the case of pricing, as an example, we're not going to price the product at the beginning, especially when you've got something that's that that's going to provide a different value proposition than what's in the market today. So there are good comparables lead into the comparables, from my vantage point, that's at more than adequate to gain insight into what your outlook for margins and outlook for for your forecasting can be. But I mean, we wouldn't actually price it at the beginning, but we're certainly thinking about it. I mean, we have one of our investors as a pricing strategist, so we've had a lot of conversations with her about

Tonya Dowd  18:29  
it. I think another thing that maybe isn't as as well embraced is collecting data during your IDE study, and you have the ability as a medical device manufacturer, if you have a category B designated device through FDA, you can submit, you can submit to CMS for reimbursement for your PI sites and the routine care cost during the IDE study. But even if you don't have that designation, you still have an opportunity to collect data, health economics data, populating the claims database with certain coding mechanisms. And that's that's really valuable to start laying the groundwork during your clinical trial, your pivotal study. Essentially, I

Cynthia Yee  19:09  
think pricing strategy is something that I've over the last few years, spent more attention on. It really depends if there's sort of an existing um, comparator device and you're trying to displace that. But I I feel like people don't spend enough time on pricing, and they either look at existing benchmarks and they undercut the value that they're bringing to market with their new technologies. And so we always look at pharma and say, they kind of can price it whatever they want, and we can't always do that in med devices, because we're just under a different reimbursement paradigm. But if you are, for example, a breakthrough designated device, or you are a new category, and you do actually have to go after new codes, it's a new way of looking at price. Pricing higher so that you can, you know, drive a much higher APC, and then that flows into your outpatient setting, pricing and everything like that. So I think we should learn to value ourselves more and price more aggressively, even though there might be a new technology out there that or an existing technology out there that, you know, has an existing framework, and you have to fight against that. But if you look at the predicates, whether it's Farrah, pulse or Shockwave, they've built billion dollar new markets by pricing aggressively and understanding the value that they were bringing to clinicians. Some of it was a clinical value, some of it was workflow. But I don't think we get to these billion dollar opportunities by pricing us, you know, at levels that were 10 years ago.

Tonya Dowd  20:49  
I agree with you, Cynthia, I couldn't agree more not I mean, I see a lot of companies look at the Medicare base payment and what their where their technology might fall, and base their pricing based on their kind of their cogs, and then what that reimbursement is, and that is, there's so many other factors to consider, value based pricing, looking at doing a retrospective claims analysis to see what's being paid for analogs. I mean, there's, there's so many more things to do, primary research, to press pressure test pricing assumptions. There's a lot that goes into it. They shouldn't cut themselves short. I agree, and

Caitlin Morse  21:25  
I think you make a good point, not only about that for the individual company, but for what that does for a whole ecosystem. Right? There have been a lot of conversations about the lack of IPOs and lack of exits influencing the total capital in the market, but it goes the other direction as well, which is, if you think you're going to get a billion dollar exit as a VC, your models look very different than if you think you're getting a $200 million exit right? And so we not only limit for native jewel company their opportunity, but actually how the Medtech industry itself is perceived. I

David Constantine  21:52  
think where this all ends up driving though is is looking at these intentions to identify a more appropriate pricing for for a novel, profound impact, you have to design your studies to illustrate that impact, taking the time to break down what what data you can collect during that study, economic data that's going to help to support it more aggressively,

Cynthia Yee  22:16  
yes and no, right? Because shockwave never had that level of data on a clinical side, but when users had the product in their hand, it was kind of a wow moment. You could see the IVL breaking up the calcium, and it took patients that might have been open heart candidate surgeries because they had complex coronary disease and made them an interventional patient. And so you're adding value to the system in that way, clinically, but you were also it was a painful several years, and I wasn't an investor, but I know the story well. It was a painful several years as they establish new codes, but once they maintain their pricing discipline, they were allowed to establish new reimbursement that actually was very beneficial to the hospitals and the providers,

David Constantine  23:04  
would you, would you suggest that it's not advantageous to capture that data during the clinical studies, not that it's necessarily requisite, but, but that it's there's a downside to it? No,

Cynthia Yee  23:15  
there's a downside, okay, except for maybe time,

Caitlin Morse  23:19  
sure, well, and your access to capital, right? I mean, depending on how a how able you are to raise, I've seen companies who just never actually get to market because they set the bar too high for what they were trying to do in their clinical evidence, and then never actually got the product there because 2008 hit or whatever. So I think that's probably the one, the one other consideration in all this is each each founder, each company, has different levels of access to capital, and so considering what's doable from that standpoint as

George Lewis  23:48  
well, let me turn the conversation on its head. Then, are there ever situations where the product itself should be free?

Tonya Dowd  23:55  
What part of the product? Well,

George Lewis  23:57  
that's a question the device. I mean, are you collecting data, providing a service of some sort. Have you experienced that? I think it depends. Yeah. I

Caitlin Morse  24:05  
think it's a conversation that med tech should have more often. But I will say Digital Health gave us a good window into watching that process. And hospitals don't really know how to buy things that in that structure, they're getting better at it than they were 10 years ago, but I still think you have to look at what your what your buyers willing to do, right? And if they have a line item for a physical object, but they don't have a line item for data or subscription or whatever, it's an uphill battle. You also have to look at what are your own gross margins, right? If you have great gross margins to begin with, you have the flexibility to say what's the best way to get this adopted. We have looked at whether or not free, in some cases, is better than a lower price that you have to battle against later. So I think if you're looking at from a timing standpoint, sometimes your first people being free could be a better option. Option, then starting off with discounts that you then kind of get stuck with, yeah,

George Lewis  25:05  
I'm thinking some of the direct to consumer stuff that's out there. Maybe less so what people are selling to hospitals and physicians. But certainly there might be a strategy on wearable tech with regard to some of those things we have some of those conversations today, not we're not in a position to advise people at what I was kind of curious to get your thoughts on, you know, the industry, I

Tonya Dowd  25:23  
think there's a potential to cannibalize your future pricing and reimbursement strategy, if that is your plan, if you kind of come out of the gate with a consumer price product, and they're going to change that with no tweaks to the device, right, or no changes it, there's a, I think it's, there's a lot of decision making that has to, you know, really be considerate on what you're doing, but, but I think that is a lot of times the a thought process that we're going to come out to the market with a cash pay price. We don't have reimbursement. Well, not a lot of, not a lot of companies do, or technologies do right out of the gate, but there are strategies to put in place, you know, to do, you know, case by case, reimbursement. But I think it's a good it's a good question.

George Lewis  26:02  
I'm trying to be provocative here.

Caitlin Morse  26:04  
Well, then I'll be provocative back when is the last time you paid more than dollar for an iPhone app? Yeah? I mean, that's the that's the other thing you got to think about. If you go cons, if you're going direct to consumer, and you're going free, and you now condition the market that that's their expectations, right, right? You know, if you were buying a software on a CD, you're expecting to pay a whole lot more for it. You're downloading something on your phone. You're like, why does it cost more than 99

Cynthia Yee  26:28  
cents? I don't think you can build a business on free. So you have to understand what you as a company are getting with that strategy. And if you don't have a good answer, then it's probably not the right go to market strategy.

George Lewis  26:38  
My Apple Watch wasn't free, so,

Cynthia Yee  26:41  
yeah, it's kind of like low stakes, low commitment,

George Lewis  26:44  
right? But no, exactly that makes sense. Makes a lot of sense. So we're almost out of time. Closing thoughts from the team Caitlin, start with you

Caitlin Morse  26:52  
your first I think it's important we're having these conversations because there isn't a one size fits all. I think the earlier you have the conversation, the more you can really understand what makes sense for your business. I do think there are a lot of opportunities to solve a clinical problem while building that data. And so whether that's getting reimbursed for some of your studies, or whether that's starting with one version and then building on product two and three, I think we have to make sure that we're serving patients. And then what else can we do alongside it? And if your primary goal is data, you're probably not going to be meaningful enough to the health system or to the patient to get the data you wanted in the first place. So as long as we're keeping that at the center, you're going to find the ways to get the data

George Lewis  27:37  
30 seconds. David,

David Constantine  27:38  
I just say it's about it's about balance. It's about balance between putting yourself in a position to be successful in the market, to be successful at the different inflection points that you need to pass through, and not losing sight of how quickly you need to do it, and as long as you're not sacrificing the the ultimate success, the product falling flat in your face when you get in market. You know, I think it's really important to build robust, meaningful data sets that are going to inform your downstream risks. Just got to do it fast.

George Lewis  28:08  
Thank you.

Cynthia Yee  28:10  
I think my personal bias has always been in clinical evidence generation and having a plan that is going to support other your value proposition.

Tonya Dowd  28:21  
Yeah. I agree with everything they said. I would say again, you know, start early, even in the R and D phase, start understanding and really recognizing that you are going to have to raise capital to continue generating that evidence and having that end to end evidence generation plan and and knowing who your stakeholders are. I mean, there's a lot that goes into this, but FDA is not the only milestone, and the end game,

George Lewis  28:47  
excellent. Thanks for the feedback, everybody. This has been a lot of fun. I thought we'd have a fun discussion today, and we certainly have. We're just about out of time, so I thank all of you for being part of the panel here today. I, for one, can hang around for a little bit outside. I can't speak for the panelists here, but if anybody has questions, some of us questions, some of us might be lingering around out there. So thank you.

Tonya Dowd  29:05  
Thank you. Absolutely you.