Transcription
Abigail Allen 0:08
Hi, everyone, thank you for joining us today, we are going to talk about clinical data and, and incorporate that to a quick presentation by me and then we'll sit down and, and have a q&a with you all. And we really hope that everyone ask questions and really make this a lively discussion. So the million dollar question is, we have this clinical, we have a need to collect clinical data, how much does it cost? I mean, just this past few days, I've probably been asked that question every 30 minutes and in the rooms here? And the answer to that question is, is really up to you all, how much do you what do you want to do with that data, and that, that decision really implement, you implement that from the beginning of your study. And that decision really affects the duration of your study your product, your product lifecycle approval and beyond. So we thought today, we would compare that to, to building a house, just to kind of give it a real life example of of the what you put into the beginning of your study in your decision of how you're going to design your study, to, to approval and beyond. So just like the building a house, and in Ninja blueprint, you need to have your protocol, your protocol is the beginning of, of your clinical study. And the decisions that you make that go into that protocol, affect the duration of of the study, and then and beyond with approval. So just like with, with building a house, you know, you have to get your blueprints approved by the county, you have to get your protocol approved by regulatory authorities, you have to get it approved by by FDA about your IRB is whether it's a central IRB or local IRB. And that that creates the framework and the foundation for running your clinical study, the content that goes into that protocol is is really your, you know, your playbook for the rest of the phase of your of your product. So while you're building this framework, it is incredibly important that you partner with the right vendors with the right sites for the right investigators to provide the foundation of success for your trial, the most important decision you make once your protocol is written is who's going to execute it. And you're just handing off your product or technology to just out to the world to execute that. So you have to ensure that you have someone to run the study for you someone to manage your study, that you have investigators that not only have see the patient population have the time, but have the infrastructure, the sites to support that clinical data collection. And while you're making those decisions at the beginning of your study of the framework of of your house of your study, is that database, that vendor, just yet just yesterday, I was in a meeting and I was told there's over 75 EDC platforms now, I imagine there was even more, but you have to find one that works, it can't just be the inexpensive one. Because you're trying to save money at the beginning of your study, you need to ensure that that EDC that platform where you're collecting your data is is easy to use for everyone. That's what's going to end the end give you the tables the listings, to submit to FDA to submit to the notified bodies, you need to ensure that that data that's collected is easy to use, it's comprehensible. And it's most importantly, easy for the sites because you need those sites and those study coordinators and those surgeons and PIs to be able to track their data easily. So while you're making this decisions about the database and what you're going to do and building it, and you've reached out to sites, and you've reached out to PIs, and now you have you know who you want to use, you have to develop a contract and a budget for each of those sites to enroll into your to participate in your study. That is an incredibly burdensome process of beginning of a study it can take the fastest we've ever seen it here at my company MCRA is two weeks. The longest is probably 910 months. It can take a long time and that's typically naughty even started until you have IDE approval, you have your protocol, you have your finalized protocol. So that is an incredibly important piece of the puzzle that you need to ensure that you have queued up us to just hit the ground running once you have your, your final protocol, and you have your sights chosen. So you have a lot of decisions to make to right at the beginning of your of your trial. And it always goes back to cost, right? If we spend money now, does it save us money in the future? Do we have the money to spend now? And just like with with building a house, you know, do you want the builder grade windows because it's saving you costs at that expensive time. But then in 10 years, you might realize you've lost so much money to with energy and electrical bills are so high that you have to rip out those windows? How much is that going to cost you compared to investing in the beginning and those fancier windows that are energy efficient? And that's really how we see reimbursement? Do you have the time and the capability and the funding to be able to just put some easy, quick time points into the beginning of your study, something as simple as blood loss or hospital stay returned to work, just some simple questions can go a long way at the end of your trial with payers. So throughout the trial, you have to be inspection ready. That means at any time, FDA can show up at your door, FDA can say they are reviewing your your patient files or trial master file. They can do that for cars, not for cars. We have been through multiple forecasts, not for cars, surprise inspections, and they they're there. And do you have to be prepared from the beginning of your trial to ensure that you have that compliance piece, that regulatory piece meaning the trial master file the IRB is that your sites are in line with the protocol the patients being enrolled are the appropriate patients, you're tracking adverse events, all of that has to be done from the beginning of this study. So you need to ensure that the partners you work with have that core capability that they're able to do that. So it's so enrollment is what everyone talks about. Every every CEO is like, yes, we got our first we got our first patient, we got our 10th, patient, 500 patient, whatever it is. And that's fantastic. You know, obviously, we need to get those patients and you don't want to have that process be too fast, you don't want to speed that process, you want to make sure that the sites you're bringing on when you're activating those sites that they're ready to be activated. Because you don't want to mess up that piece. So you want to ensure that the the partners that you bring in, provide that framework that they can support you with those patients that come in. Because what's so important, you can have 500 patients enroll in your study. But what you need is 500 patients to complete your study that that first data point is enrollment. But if you don't have the follow up if you don't meet your primary endpoint, because you didn't have patients follow up, what was the point of your study. So to go back to those partners that you choose, in the beginning, you need to ensure that your sites that your patients that your sponsors are CROs that everyone's working together to ensure a successful study. And that means really providing that framework of communication of commitment to the trial from the beginning. And then last but not least, is that you know that final walkthrough, getting your keys that excitement, and is the clinical study report. And that's the story that you've been telling from from that moment of your protocol development, you write that story and you submit it for FDA approval or whatever you're looking for to have those for those data needs. And that's the whole The whole purpose of doing it is to you know, get get that excitement, get those keys to the new house, get the get the data. So back to that beginning question, how much does it cost? It really is dependent on what your goals are? What are you looking for, to to achieve? And making sure that you partner early on with the correct people to help you get there. So now we are going to move on to our panelists. Our panelists are going to introduce themselves, and we're going to ask them questions that I have written already, but anyone in the crowd please just raise your hand. I'm happy to take questions throughout. We'd love to have a more interactive session.
Max Bikoff 9:55
So thank you, everyone. My name is Max Bikoff and with Longitude Capital, we are investors. So we're a venture and growth firm. Been around for about 15 years little over that raised about $2 billion over the course of that to invest exclusively in healthcare. So as a firm, we invest in biotech, medical devices, healthcare software and services. And personally I focused on our medtech practice. So I've been on the investment side for about six years. I'm thrilled to be here.
David Hovda 10:25
I am Dave Hovda, CEO of InnoVein Medical, we've developed a venous valve replacement for treating deep venous reflux. Before that I worked in spine for about 15 years, been part of for IDE studies, we've enrolled over 1100 patients for studies, but I've been part of two PMA approvals. And those two PMA approvals, we're working with MCRA Thank you very much. We were very pleased we had the two fastest PMA has ever approved in spine. So I think when it comes down to cost, time is money. Burn per month is money. If you get well organized, pick the right sites, things go smoothly, it can be very efficient. And we were very fortunate to have this very efficient study. So thanks to our colleagues. Nice to be here. Thanks.
Michael Anselmo 11:09
Awesome. Hi, everybody. My name is Michael Anselmo. I am the Vice President of reimbursement, health economics and market access for Mikra. I'm the relative new person here. I've been with the company for about six months, I came out of industry where I held similar roles for a number of companies. My most recent company was Silvercloud Health, we had a successful exit two years ago, out of the digital space. I will say one of the things I got when I got there was they were waiting around all these clinical trials, all these clinical studies. And they were having problems getting company or getting hospitals and systems and payers to buy the technology. And I said okay, great. Well, we're just health economic stuff, you know, what do we have that shows value? They had nothing. And if you want to talk about expenses during clinical trial, just wait till you spin up a Salesforce that cannot sell anything. That's even more expensive. So I'm looking to leverage a lot of my insights and findings and excited to be here.
Glenn Stiegman 12:04
Good afternoon, everyone. I'm Glenn Stiegman, Senior Vice President of Clinical and Regulatory Affairs at MCRA oversee both the regulatory and clinical groups and macro with Abigail leading our CRO, been with me for about 17 years. Prior to joining Mikra. I was at FDA, as the branch chief orthopedics. MCRA initially started in the musculoskeletal world since expanded quite effectively into a lot of other therapies. Many of those obviously require clinical data and excited about this conversation. Thanks.
Abigail Allen 12:37
Thanks, everyone. So let's let's get started. So Max, let's let's start with where it all let's where it begins to even consider a company to invest in what data do you like to see?
Max Bikoff 12:50
That's a great question. I'm gonna go back to early consulting days. And it's a little soon to play this card, but it depends, honestly. So I think first caveat is, every investor is different, every firm is different people value different aspects and are willing to take different levels of risk. Some folks really like high science, new mechanism, this has never been done before. Other firms and groups are looking for a more mature data package, we fall into the bucket of looking for things that are clinically derisked. But what does that mean? That doesn't necessarily mean you've got your PMA or your fat didn't get approved, and you're already on market. For us, there are different ways to get to clinical derisking. One, an aspect is just lateral evidence. So if this is something where you've innovated on the hardware on the procedure on the approach, but the business end is the same, right? What's delivering the therapeutic value to the patient is the same, then we can go a little bit earlier, we invested in two neuro stem companies relatively recently, and they innovated on how you power these devices. But at the end of the day, it's a lead placed on a nerve delivering electricity to a known nerve target. So we were really confident it was going to work clinically, there were other technical things to jump through. So that's an example of clinical derisking. for things that are on the newer, more, you know, novel MLA type mechanism of action type type projects, what I tend to look for things that are highly objective endpoints would you hate to do is to step back from your first 10 20 30 patients and say, This is great, patients are doing awesome, but I don't know how much of this is, you know, Sham effect or placebo. So we're looking for highly objective things. And an example here is we've got an early stage mitral repair company, treating mitral regurgitation, you know, on the table, whether or not you've helped that patient, right, there's no sham effect, you see the effects of reducing mitral regurgitation in the procedure. So that's an example where, you know, we feel like a first couple of patients are highly de risked, and that's the way we've approached it. But as I said, you know, different investors, different philosophies.
Abigail Allen 14:59
Think You. So David, when, as CEO, when do you start thinking about the clinical study? When do you put that into your business plan?
David Hovda 15:08
So I would say right up front, we recently treated our first patients, we closed around the financing round in January. But a lot of our discussion had to do with a pivotal trial design, how many patients, it's going to affect the timeline, it's going to affect the amount of capital, and we've not yet treated a single patient. So I think, of course, you have to figure out what it's going to take to get to your human clinical release and and prove that you have something promising before you get to the pivotal. But the questions coming at you about your Pivotal, are very early. Very early indeed. Yeah.
Abigail Allen 15:42
And, Mike, from your perspective, what, when should we start thinking about reimbursement in a clinical trial study design?
Michael Anselmo 15:49
To be honest, it's it's never too early. And I think, you know, we met with a customer this morning, and we're talking about, you know, let's include some of these endpoints in here, it's, you know, might add a little bit of time, a little bit of complexity, a little bit of risk or cost your trial, but you know, you don't get to that endpoint of got a great clinical thing, no idea what value it actually brings to, to our, you know, our patients at the end of the day, and, you know, you get to it, you launch a product and then you your sales stall out. And that gets really difficult. And, you know, one of the theme I've really seen here is it seems the investors are, you know, wanting to see more. Okay, what is your reimbursement strategy? I think, you know, the, the tenor investment has changed. It's no longer Hey, it's a great clinical, we'll figure the rest out later. But now it's, we need to understand the business path forward. And that comes down to the economics, the the reimbursement, why is somebody going to pay me $1,000? Every time I turn this device on, we need to explain why. And that. I mean, that's pretty much question you can ask too early.
Abigail Allen 16:47
Yeah. Yeah. And, Max, do you have any thoughts to kind of reimbursement? When do you start thinking about it?
Max Bikoff 16:54
I mean, immediately, absolutely. And you see, you see, a lot of companies kind of get caught in this trap, where it feels like you've had this gift from the FDA where, okay, this is an endpoint I know I can meet. This is something that's a little bit easier, maybe a lower bar, but it doesn't satisfy that payer question. And to your point earlier, that's where you can really lose a lot of time, a lot of money is commercializing something where you're just running into a brick wall, ie, the payers in coverage. So you can't start thinking about it soon enough, honestly. But I do think there's, you know, there are patterns here around what makes for a good reimbursement package, what's going to be meaningful to the payers. And obviously, hard outcomes is a key piece. If you're saving lives, you know, you've got a real therapy, but there are other tried and true paths here. When you take something that's based in a hospital, highly invasive, ie highly expensive, and you move that into an ASC or an office, that savings for the payer, that's a win win win for everybody. You look at some of the downstream impact if you're reducing hospitalizations, reoperations, expensive medications, dealing with compliance. I mean, these are all angles where, where it's a win. And to your point, I mean, it's probably one of the single greatest risks that companies face, oftentimes more so than FDA, which has done an excellent job and is, you know, in most cases, highly, highly predictable. But as a firm, you know, we're we're willing to take on reimbursement risk, I think for us, though, it's, it's about having the moral high ground, right. So if you've got the data that moves the needle on cost that moves the needle on outcomes, then, you know, I think that's a battle we're willing to take. Because from there, it's downhill, it's time it's money, it's execution. But you've got the upper hand in those conversations, because you know, you're bringing value to the system, and we're willing to take that on.
Abigail Allen 18:48
Right, and, David, do you have something? So
David Hovda 18:49
it was brought very clearly to my attention a couple years ago, we were talking with pretty large strategic about what are the key aspects of what they look for in acquiring a company exits and so forth? And the comment was, you're gonna hate to hear this, but for us, question number one is, can you get paid for it? Question number two is does it work? And then question number three is IP and, and so forth. So I, you know, of course, it's got to work. But it did make an impression on me, of course, you've got to have a reimbursement strategy, you've got to have a path forward. It's right up there at the top, you know, with strategics. Absolutely.
Abigail Allen 19:24
Great. So keeping in line with cost, I mean, you have to decide what type of study to start and when to start the study. So, Glenn, do you have any thoughts on a feasibility study versus just diving right into the pivotal and the ramifications? And from that?
Glenn Stiegman 19:40
Yeah, sure. So I mean, Max, kind of stole a lot of a lot of what I was going to say, by You're welcome. Yeah. De risking your the study. And, you know, there's a lot of companies here and they're still trying to figure out the best maybe approach for their product, the equipment, the instruments, so there are some serious Ask questions. And certainly starting very slow, starting with feasibility, first inhuman type studies to sort of figure out any unknown variables that could impact the long term safety profile effectiveness profile of that particular product. If it is some like nerve stimulator where you said you had a lot of confidence in, it's gonna work, then those would be scenarios where certainly don't waste your time with a feasibility type scenario, jumping into a pivotal what you have that confidence just drives a more efficient process, and it gets you to market that much faster. But it's really the confidence and de risking because those first five patients are critical to the eventual success of your study, or in the company, because it's going to set you back if there's one misstep, one, wrong implantation. If the usability is in question, whatever it may be, then all of a sudden, you're like a year delay trying to fix and fix that instrument, whatever it may be. So it's a tough decision for a lot of companies, because they do want to take it slow, be careful, but yet, every step takes millions of dollars and years of time.
Abigail Allen 21:03
Yeah. Max, do you have any thoughts on on this from your perspective?
Max Bikoff 21:08
Yeah, I mean, I think you raised a lot of good points, right? There's this tension that you have around, going fast, taking as little capital as possible. But also de risking and being ready for pivotal. And it is attention is very case by case specific. I mean, if you look at our broader industry, in the average exits in med tech are $200 million, plus or minus, you know, if it takes you $150 million to get there, we can all do that math, I mean, that's not a huge return for for your investors, which is at the end of the day, the business that that I'm in. So it's it's a real tension. But I think, you know, Mike may raise this point, which is losing time is way worse, right having to go and, and rework because that's much more expensive, right? When you're carrying the whole burn of the entire company, or a commercial organization or something like that, that's when things really start to add up. So you have to be confident that you're ready for pivotal. And you learned so much in those early feasibility studies around just execution. You know, how fast enrollment all the all the steps that you talked about, like building a house, you learn all of that, in your early studies. And, you know, that's kind of the best predictor of what's going to happen when you enter the pivotal stage. I think the other the other point, that's always very resonated. For me, it's a little, it's a little bit of a pet peeve. But patient selection, and knowing who your target patient is, who's a good patient who's not a fit is so so critical here. Because that pivotal data set, I mean, it's not just driving your approval, but you live with that for many, many years, that drives your marketing your communication to physicians, your conversations with payers, and so you have to be super confident in that. And in medtech, we ask patients to undergo a lot, right, we're asking for a permanent implant or an open surgery or general anesthesia. And I think knowing your target patient population is so important, because if you end up and 20 30% of your patients do great, but 70 80% don't even if it's safe. That's a lot to ask of the healthcare system. So you know, figuring that out early and not late is so so important. So I think most often, it's better to go go slow to go fast. But in rare occasions, right, when you can wait, you can skip the line. And there's some benefit to that.
Abigail Allen 23:34
So kind of going along with your with your study design. Right. That was that's what you just kind of start talking about. Glenn, how do you how do you think about the control arm? I mean, just this week, we've been asked so many questions about control arms, and how do you approach that?
Glenn Stiegman 23:48
I think it goes, you know, primarily to what you said in your presentation. And that's the objective of the study. You know, being from the regulatory world, obviously, a lot of the protocols that we're developing, we have the FDA in mind, and I'll include Mike into the conversation so we get the reimbursement perspective. But ultimately, we're trying to show what this product does compared to another product out there. Now if it's for strictly regulatory purposes, maybe a sham control, maybe a placebo control, we'll be we'll be fine from the FDA perspective, and they'll push that onto you. But uh, no, that's not going to do anything from a reimbursement perspective. If it's for reimbursement, then what is the standard of care if it's for distinguished distinguishing your device from others? The maybe you're going against a competitor? So there's a lot of considerations based on the objective. And then you have to consider okay, if we choose this control from a regulatory perspective, what is its effectiveness, effectiveness profile? What is it safety profile, because then you're sort of pushed into aligning yourself with that particular product, you're forever being going to get going to be compared to that particular product or that control. So it's really a a difficult decision. And as Max said, you know, you're laying the groundwork of all of this data and David's lived through it. And you want to pick that control that's going to resonate with surgeons and physicians and payers, and not do something that's outdated or not used, but also something you have confidence you're going to win, that you can make those claims make the reimbursement strategy executed.
Michael Anselmo 25:23
And, you know, just echoing on that I think it does get very hard is when you talk to payers, you know, these are patients who would get some treatment, you know, standard of care, what are they getting today, you know, they're not going to just get Sham, you know, if I need a knee replacement, they're going to get something to help their knee. So if you're, you're comparing against, okay, just, you know, no knee replacement, it's safe and effective. Payers gonna look at that and say, Well, I'm going to spend this anyway. So like, what makes you special. So it does feed into some of those downstream needs, which I know are very difficult to think of, at the early stage, when you're just trying to get a product developed, and through regulatory pathways, and you'll raise capital, it's really hard to think of like, okay, four years from now, when I launched this commercially, I need to do XYZ, that that is a real hard decision, real hard investment to make. But you know, four years from now, when your burn rate is much higher, I will keep harping on that point, because I've seen Salesforce is just saying, We can't do it. It's a real hard decision. So it's it's build those endpoints against your competition against the standard of care. I remember when I was with Abbott, we were having our trial with our left atrial occlusion device, we were going up against Watchmen, because what's the new standard of care? Watchman, we weren't going up against ablations anymore. So that was a real hard decision. But we also knew four years from now, when we launch our device, we would go to market and say, We're better than Watchmen. And ironically, Boston love this idea, too, because they said, if you go to market, you're not better than Watchmen, we're going to wave your trial around. So
Max Bikoff 26:59
it's such an important decision as you're going through, right? Is it going to be against meds? Is it going to be against Sham? Is it going to be against the gold standard? Or did you get a single arm study something like that? I mean, it. I think as we start to evaluate these, a lot of it comes down to how well do we understand this control arm? And there are lots of areas where people think they understand, but you get you get caught in a trap, right? So heart failure, for instance, if you're going up against meds and heart failure, I mean, it's been studied time and time and time again. But that drug therapy has been improving a lot over recent years, right, we've got ENTRESTO, we've got the stLt tos. What medical management gold standard looks like in heart failure today is so different than maybe that 10 12 studies that you're pulling as you're building your clinical trial assumptions for what a control arm is going to do. So, you know, we think a lot about how predictive are those prior studies in terms of what what your expectations and what you're what you're powering for. So that that's a big piece. And this maybe goes back to early feasibility studies, or, you know, a pilot RCT, which maybe isn't going to give you all the statistics you want, but you get a read on what that control arm is going to be in a modern era in your patient population. And that is a huge, huge derisking for folks. The other point, I just add on on control arm just because this this came up relatively recently with one of our companies is for single arm studies. And I'm a bit of a purist like I prefer RCTs. It's just, it brings you the context you need when you're evaluating a new technology. And I think that's true for true for me, and probably everyone else that's looking at things. But sometimes it's just not feasible. So we recently invested about a year ago in a company called limb flow, who I think presented a couple days ago. And one of the sessions it's it's a therapy for end stage peripheral vascular disease, patients who have no other options and are about to get their legs amputated. You can imagine you can't randomize a trial like that you can't go to a patient and say, Hey, we've got this new therapy, do you want to enroll, there's a 5050 shot that we're gonna have to amputate. But we have this other thing that might work, right? No patient is going to sign up for something like that. So how do you bring context to his study there and what they did, which I think is super, super clever. They ran a real world registry in parallel to their single arm pivotal trial, which you know, it's not randomized, but it's as close as you could get for a pseudo control arm and I think that will pay dividends for them. So they're, you know, different strategies here, which is sometimes you have to think a little bit outside of the box.
Glenn Stiegman 29:36
And just add to that you brought up a really good point. And while that's a extreme example, but a real world one, the choice of control you also have to think about you know, while study design decision, it's also in the Enroll ability of the study itself. You know, the standard of care when you're running up against something very novel, new and shiny. Patients won't that surgeons want to end plant that they don't want to go back to this the two decade old standard of care. So the Enroll ability of a control arm also has to be considered. Because we run up against a lot of times where, you know, we're trying to do two to one randomization three to one randomization, because no one wants to be on the control side.
David Hovda 30:18
I'll just add one thing to that, too. So we randomized a fusion. I was worried about losing patients to follow up because I could just walk in and get a fusion. Why am I coming back for two years plus, one of the things to consider we did, again, working with MCRA, we bought a dataset which we used as a control. So effectively, we did a prospective single arm study, we had confidence in the control arm because it was used for the as the basis for an FDA approved product. So FDA had already seen that data, it saved us a lot of money saved us a lot of time, we could focus just on the investigational device. So it wasn't obviously the complete randomized control. But there's statistical analyses you can do to effectively make it similar. And so that was a big win for us. And you know, something that might be something you could consider.
Abigail Allen 31:05
So, so, back to you, David, what, as you're, you know, you now have your study design, you've decided on what you're going to do with your study in your pilot, pivotal study. Talk to me about site selection, how do you how do you decide? Do you want that? Kol? Do you want that that name? Or do you want the smaller mom and pop shop that can bring in more patients? How do you approach that?
David Hovda 31:28
Yeah, I think maybe borrowing from Max, we want both, right, we, you know, you'd like to have some KOL's because it brings a certain amount of credibility, just because they're working with you. And that's kind of a semi seal of approval, but they also tend to be really busy, they've got other things going on, maybe you don't get the focus you're looking for. So I think there's an important combination, there are busy physicians who can help enroll your study, but some kale walls as well. And then, you know, I think academic versus private, you know, you like the prestigious academic sites, it depends on what you're what you're evaluating, but you get good treatment at academic sites. But you know, in the clinical trial agreement, like you were talking about that can, that can really extend to nine months, you have more overhead, you just have more hoops to jump through. Whereas you can move much more quickly in some of the private sites. So we're really focused on that to two of the things I would say, which are key focus, so you don't have to put me on this. One is previous idea experience. I mean, once once you've been through an IDE, it's almost shocking how much work it is, and how difficult the follow up is, and just the whole tremendous amount of support. So in my case of a surgeon said, Geez, I'd really like to be in an ad study, but they had never been an investigator never been a co investigator had no idea what they're getting themselves into. I was pretty skeptical about that. And one thing I learned very much is they need a good study coordinator. And we were so focused initially on Yeah, but yeah, this is great surgeon and a great site, and they've got a lot of potential patients, but they didn't have the research support. And we paid for it early on big time. So I think it's really important to have a research team slash study coordinator, that's not a med school student who's going to get rotated every three months, because there's no continuity. So Id experience great study coordinator and a combination of I take care wells and busy physician.
Abigail Allen 33:25
And as the clinical expert here at Mecca, I absolutely support that, especially with from my perspective, I've really collecting that data and ensuring that the patients come back and that they understand what the study and the purpose of this study is. So kind of switching gears a little bit. Back to kind of this reimbursement, right, we really care about. Right? That's the point like late David taught us. So what what do you tell our clients? What do you tell the startups at the beginning of the trials like this, you know, this this study design, and you always talk about that one randomized control trial isn't enough. So what, what do tell me more about that? What what do parents really want to see for the, you know, the million dollar question?
Michael Anselmo 34:10
No, that is the $10 million question. So I wouldn't even say it's one randomized clinical trials, not enough, sometimes it can be. You know, the question is just is it powered enough? Are you going to be able to walk this into a payer CMS in four years, five years, and convince them the device not only does what you say it's going to do, but does it in a cost effective manner, in a clinically safe manner in a way that is going to bring benefit for a payer? You know, so you see some trials, it's like, oh, we've got 12 people, the payers Look at that. Now, I mean, certain, certain conditions, yes. But I mean, if you're bringing a you know, a pacemaker to market, you've got a sample of 12 people, they're going to basically laugh at you and say, why are you even bothering me? But you want it to be powered enough significant Have their you want to have enough time? Because great, it works at two weeks, three weeks doesn't work at a year. You're asking the payer to make oftentimes a sizable investment into this patient by covering the technology, they need to understand that there is going to be an earn back that they are going to get their money back. When I was at United Healthcare, I saw a lot of technologies. And you know, the clinical team would say, hey, this sounds really great. They would hand it to me, and I'd be like, Okay, well, what does it cost? And they go, Oh, it's $30,000. And I would look at it and be like, well, our cost to treat the condition in a one year period is $20,000. It's gonna take us, you know, all this time, you know, a year and a half just to break even on this device, is the patient still going to even be with us as a payer? In 18 months, statistically, probably not. So we would sometimes pass on those technologies unless we had a real other important reason to do it. But just proving that there is a path for the for the payer, that there is validity to the study, that there are outcomes that they care about that, you know, will, you know, there are a lot of Payers or profit making entities, so a an outcome that will earn them a profit.
Glenn Stiegman 36:07
And just I know, we want to get to a few questions from the audience. But just from the regulatory perspective, when you're trying to go in a unified pathway with reimbursement, expectations, and regulatory expectations, you My goal is speed to market get this get this to market as quickly as possible. So you sort of have to be creative when you're, you're designing your study to include the reimbursement components as well as what the FDA is going to expect. So you're not over committing to FDA, that you're going to run a three year study, even though you know, reimbursement once that they may only want a one year study. So there's there's a component of transparency with FDA as to why you're designing the study the way you are, such that you're coming in to get approval at one year, but yet you've built the infrastructure and protocol for patients to go out three years. So that's, it's a confluence of a bunch of things.
Abigail Allen 36:58
Thank you. So let's open it up to you guys on our last five minutes who has questions from us for this group? Yeah, David?
David Hovda 37:08
Yeah, I didn't expect it to work actually, but made the call. And I would say it was used to support a product line that was no longer a feature product line of theirs. If they wanted to slow us down, they could have I think they had an interest in our technology. They had this data set. I just said it's sitting on the shelf. We could make use of it, it could be a win win situation here and allowed them to, I think, kind of monitor how we were progressing. But yeah, for recently approved product. I don't think that would work. But it was this a study that had been completed about five years before and they just, it was kind of, I suppose unique situation, but they were willing to part with it for for a fee, of course, but it was controversial. And it took a took a year of trying to get through that to get that completed.
Glenn Stiegman 38:03
And the acceptability from the FDA perspective and that scenario, because they're purists just like Max, they want randomized controlled studies. And to come in with a store bought control. They they freaked out a little bit. Now, granted, it was patient level data. It had all it wasn't you're not borrowing from a literature article where it's just sort of glosses over the details, we could dig into this dataset, and really look at it and then run propensity score matching to what the enroller bowl investigative arm was. So we really had a good assessment and argument to utilize that, that control in that case.
Abigail Allen 38:45
And one thing just to add to that, in their last couple of seconds is we even had to adjudicate that data. So we went that granular into that that all the safety data that came in we had to run a CEC. So you adjudicate that. So that was a lot. So well. It looks like we're at time. So thank you everyone for coming. And thank you guys for joining me up here.
© 2024 Life Science Intelligence, Inc., All Rights Reserved. | Privacy Policy
