BoneChat #104 - Storytelling with clinical data to move ortho companies forward

Okay, this is BoneChat number 104 with Laura Scham. She's a clinical storytelling expert and a longtime BoneChat member. I'm gonna say, I'm gonna pause and say something I don't normally say about the presenter, but Laura is world-class in what she does with clinical data. She's one of the best of the best. And I know this from startups that are just— everybody that's worked with her just raves about her work and how easy she is to work with. So today she's gonna share a playbook on how to make your clinical data tell a better story and potentially drive sales. So anyway, I'll put her contact in the chat and hand the mic over to Laura. Welcome.

Well, thank you for that very kind introduction.

Well deserved.

Get my screen shared.

And raise your hand. She's only got 7 slides, but it's going to be pretty dense. Raise your hand anytime.

I am one of these people that likes to have a discussion as I talk, so If you have questions, I am happy to answer them at any time. So, oh my God, there we go. Clinical storytelling. That's what I'm here to talk about today because why storytelling? Why are we talking about storytelling at all? And that's because we're human. We're designed to listen. If you look at basically any civilization, their oral history goes way back. And that's, that's how we synthesize information. That's how we take in information. That's how we learn. That's how we are engaged with information. And so if you have a device that you want people to know about, you want to tell a story about it. You want to talk about what kind of problem you're trying to solve. That's part of your clinical storytelling. Why is your device different? Is it better? Is it completely new? One of the most important parts of any storytelling is thinking about your audience. You wanna think about your audience every step of the way. And throughout this, this whole only 7-slide presentation, you wanna be thinking, who am I telling this story to? Because even if it's the same information, the same story, you need to emphasize different parts for different audiences. Depending upon who you're telling your story to, if it's a surgeon, if it's a payer, If it's a regulatory body, same story, but you're emphasizing different parts because different pieces of that matter to each of those different audiences, and you want to keep that in mind. So how do you tell a story? You want to consider your narrative, because when you consider your narrative, you're controlling your narrative, and ultimately that's what you want to do with your devices. Think ahead, think about the story you're telling, because then you're in control of it. One way that you're going to tell a story at some point is healthcare economics. Someone is going to ask this question at some point about your device. They're going to ask, is it cheaper or is it more expensive than your standard of care? If it's more expensive, does it reduce opioid usage? Does it reduce procedure time, hospital time? If it's cheaper, how much cheaper is it than the standard of care? Under what circumstances? And of course, eventually, hopefully, you someday have a clinical story, which is the basis of your clinical study. And so even from the very beginning, you want to keep in the back of your mind, you want this clinical study someday. So who's your audience? You're— you'd like to have a randomized controlled trial at some point. Not everyone does. That's the gold standard. But what about a chart review? If you're going to have a chart review, if you're going to engage with one of your KOLs, What story do you want to tell them? What story do you want them to pull out of their medical charts? You want to keep that in mind so they don't have to keep going back to the source material and they can pull out everything they need the first time. So you're thinking about the story and your through line through your entire device journey. But a lot of companies at the very beginning when things are new, they say, well, I want to tell a story. But I don't have any data. So how do you go about that? And one of the things I've talked to a lot of companies about is using what's already out there. You might have more data than you think. Um, it doesn't necessarily have to be something you generated yourself. Uh, you can look at literature that's already published. Um, the systematic review or meta-analysis, that's a literature review that gathers a bunch of other published data that's already out there.. And then the meta-analysis is a way, is a statistical method to apply stats to the very specific question you have about the literature. And if you want to answer that question with the literature that's already out there, this is when you start to build your track record. You're building your narrative, you're building your story. And so you can look at the published literature and say, where is the gap in this knowledge? And then of course, your device is the one that has that, that gap to fill. And if you start to tee up this story, you can also tee up how well, how clearly you can solve this problem. You can fill this gap.

Hey, Laura, I don't think the slides are advancing.

Oh no, what one are you on?

We see number 1.

Oh no, that's okay. I know you're flying.

You're telling a good story.

Thank you. Um, huh, well, let me come out of it and try it again. When in doubt—

there we go. Why story? That's 2, we can see that.

All right, so you can— you see this one? Yes, we see why storytelling. Yes, and we know that it's because we're human. Yep, you can see telling a story.

Not yet.

Still on 2. Can you see? Well, what screen are you seeing?

We're seeing number— we're seeing not the SlideShare, but the, uh, you're seeing the notes. The notes? No. Yeah, notes at the bottom.

Yeah, how's this?

There we go.

Full. All right, so I can tell a story, but I cannot put together a presentation on Zoom just yet. So if we want to work on a narrative, you come to me. If you want technical help, you need to go to someone with an IT degree. So we're here, we're talking about telling a story. We talked about some of the ways that you can do that, some of the things you want to keep in mind as you're telling your story all the way through. And where's my— now, how do I advance?

You're on. This is—

there we go. All right. And so now we're talking about findings and data. If you're early on and you might not necessarily have any, we talked about a systematic review, which is when you pull already published literature and you use a specific type of statistics on it to answer a very specific question using literature that's already published. And that's one way you can tee up your story or the, the story you want to tell with your device, or the gap in the knowledge that your device is then going to fill. Well, the systematic review is very popular. Journals really like them. The narrative review is becoming increasingly popular these days, and that's not quite as systematic. You're not pulling every single article that reaches that question, but this is more, once again, telling a specific story. You could pull every single article that has published with your device if it's been on the market for a while. You could pull a bunch of papers that have used a competitor device and you could say, well, how, how is this safe? Is it working well? What's working well? What's not? What adverse events? And there's a story there. A client I've worked with recently, we're putting together a narrative review that is basically telling the treatment history of a, of a specific ailment and what used to be done, what is done now, what's the standard of treatment and why is that standard of treatment not working very well. And then that tees up their technology and why it's going to work very well. And what, once again, the gap in the knowledge that it fills. And that can all be done even before you have your own data, before you've run any clinical trials. Another thing that we've talked about, uh, with some of my clients is, uh, if you have your device, um, in a surgeon's hand, in a clinician's hands, they're using it, they have experience with it. How is it going? What do they like? What do they dislike? Do they have pre and post-op pictures? Have they taken any measurements? A lot of times you can take that and turn it into a case study. You can publish that case study or potentially use it as a white paper or internal marketing or external marketing. But once again, that anecdotal data, that anecdotal experience can be used as part of your long-term storytelling experience. So next, I want to tell you, if you have thought about these things, if you've thought about your story, if you have found some sort of data or you're looking for data, what does it look like to actually put this into practice? This one's going to take a minute. Stop me at any point because we have a— we have an involved slide, and I'm glad we figured out how to use the slides before we got here. So to orient you to this slide, we're going to take a hypothetical 2-year study. Let's say that you hit the ground running in 2026 all the way to the end of 2027, 4 quarters a year. What do you do with this publication? How do you get your data out there? I'm calling this publication planning, but it's, it's really more than that. I would think of this more as your data dissemination plan. How are you getting your story out there? What are all the places you're putting it? You could think of it as the, the scientific arm of your marketing strategy with a good solid base in science. So we all want a clinical study. We love clinical studies. Maybe I just love clinical studies, but they take a while. They take a while to get off the ground. They take a while to get running. So clearly you can't necessarily use that immediately. Hopefully you start collecting data from that relatively quickly, and maybe within a few months you could produce some really short-term results and you could take those results and submit them to a conference. So now you have KOL engagement. Now you have people seeing this. And either a poster or oral presentation. And it could be actual outcome results, it could be usability results. But then people will go to that conference, they will see your poster or your talk and they'll go, man, that's kind of interesting. So if you're good, you'll time it. So then you have a publication come out right after that conference. So that way when they go to look for more information, you already have that publication at the ready. And if you didn't know this, a lot of conferences don't want you to publish or don't want you to present data that's already been published. So if you're going to present at a conference, you want to get it out before the article. So you want to time that well. But then once you have that article out, not everyone's going to have time to sit around and read it. So you want a white paper. And then you can use this to either hand out at the conference if you have a booth, you can give it to your salespeople, you can give it to surgeons, you can use it internally, externally. You could hang it on your wall if it's pretty enough. And this would all be with your very first outcomes, your short-term data. But we know the data collection for the clinical study goes on and takes forever. So what do you do in the meantime? This is where we start to talk about those literature reviews again. So if you have a literature review, if you have some ideas for that, if you want to get things out soon, you can start that right away and start the data collection and the analysis. And then you have an article out even before anything's happened with that clinical study. And same thing, as soon as that paper's out, you want to have a white paper, which is a condensed version, which is a summary. And then you can hand that out wherever it's useful for you. You're going to start to see something very similar here because there's that data collection that's still ongoing forever. So now we're thinking about the healthcare economics model because everyone's always going to ask you, what's it cost? Why is it better? So this is when you talk to the statisticians and they tell you why it's less expensive or why it's better, even if it's more expensive. And so then once you have the abstract, you send it out to a conference and then you have someone talk about it on a stage and then you publish it in a paper and then you have a white paper, a summary of that for marketing purposes. Is this getting repetitive? This feels repetitive. But the point is you're thinking about this ahead of time. But wait a second. Oh my God. Now it's near the end of the second year, and hopefully you have more data from that clinical study that's been going on the whole time. And maybe this looks once again familiar. So the point of this slide, other than the fact that I really like colors and graphics, is if you think about this from a 30,000-foot view, you have a plan in place. You're not just, oh, I have this one study, I'm going to put it together for a regulatory body, and then you're done with it. You're using all of the data you get as much as possible to start to tell your story across 2 whole years. So that way you're using all of the data you have well. You're using it to tell a cohesive story, not just bits and pieces. And in this very idealized world, in 2 years you would have 4 publications, 3 conference abstracts, and 4 white papers on your device, which shows a track record of publications. You've got evidence of expertise, you've got your KOLs, they are engaged, they're happy. You've put some papers out in their name, which makes them happy. You've got them out there talking about how cool your device is, which makes payers and regulators happy if it's based in science. And then you've got some ready-made marketing materials because you have all of this paper, all of this analysis, all of these figures and graphs already done that then you can amend those for each of your audiences. For whether you want to highlight how easy it is to use or how much more efficient it is or how safe it is because you've already done that backend work. So now moving forward, you just have a repository of information for all of these different uses that a lot of them you had to do anyway. So might as well get the most out of each of those. So, I said it was only 7 slides. I still feel like I managed to talk for quite a while, but this is, this is what I do. This is my basis is helping people to put together their, their scientific story or their clinical story. This is the fun stuff is, is taking not just bits of data here and there, but what's, what's the overarching? What's the 30,000-foot view? What is your through-line story throughout all of this?

Questions? And don't be afraid to ask about your specific products.

Mark?

I would like to start, uh, by saying that I believe that the story is everything. And I, so I, I'm already a, a convert in that regard. I'd like to know your background and why you came to combine the clinical aspect of the science, uh, how the market hears it, listens to it, uh, the rationale, and how you came to, uh, present this information in a, in a, in a storytelling way. Why does it sell for you? Why did, why Why do you think this way?

I could give a very long talk on my background, but the gist of it is when I was in grad school getting my PhD, I started going to every single science talk that I had time for because, because I'm a nerd and I like them. And for so many of them, I would sit there and go, man, I thought I was smart enough to be here. And I honestly don't know if I am. Because I don't understand anything anyone is saying. And then I went to a couple talks that were the complete opposite, that were so far outside my field or my realm of knowledge, and I understood every single step. And, uh, that was kind of my light bulb moment to realize that, um, it has nothing to do with how smart I am, and it has everything to do with how the information is presented. And so in my, in my last position, there was primarily publications and slides and abstracts. I think it's the same thing. People want to say, oh, if it's science, it doesn't matter. You can rely on the science. And that's absolutely not true. You still have to tell a story. You still have to make it understandable and comprehensive to to the people that you want to understand what you're saying. The onus is on the, the speaker, not the listener. Once you have shown up and opened your ears, your obligation to me is over.

See, you've just told a great story.

Uh, I'll say. I've practiced that one.

That's a good one.

Yeah.

Thank you.

Are you good, Mark? Okay, uh, Kyle's up.

So it's a good example to give a personal story there. I think the other thing that comes into play is people remember stories better than they remember data, right? So I tell you, I tell you, my kids football team, you know, won 20 to 12. That might go in one ear, out the other. But if I tell you with vivid detail, they were down 2 touchdowns late and there was a pick 6 and somebody had like— now you've colored it in and the whole thing is more memorable. So can you go back to the slide that you had that had that cascade, the timeline? That is a, that's a heck of a way to describe. I get it with your color coding and everything. I get why you like this one. So this is slanted towards, if not exclusively related to clinical data, right? So the idea might be that in some capacity, from the moment something gets implanted for the first time, there's the opportunity to track that. Maybe not in a controlled trial, maybe case studies and retrospective, but you can always be thinking about clinical stuff you could be gathering along the way. And I like what you described about you make your surgeons happy because their names end up being attached to it and whatnot. Is there a parallel path of, call it mechanical, benchtop, anything else stuff that you've seen go alongside of this? And be layered in?

In terms of, I mean, yes, because my background is entirely in benchtop and I came to clinical later in the game. And so that's where I think there's so much publishing done. And I am not a regulatory body. I am not a health insurance person who makes these decisions. But I think the longer of a track record you can have in in the public eye of we might only have benchtop data right now, but if you're publishing it regularly and showing that you have good science underpinning what you're doing the whole time, I think you can do something very similar.

I don't think you'd want to have one without the other, but I would suspect you can come up with a way for them to be complementary and timed out nice. Like, I like the way that you have the the ever presence of information being added into the, you know, weapons chest for somebody that's trying to sell and market this.

And that's, I mean, to toot my own horn, which is why I'm here, but this is, this is the advantage to hiring someone outside the company. If you don't have the bandwidth inside the company, I have clients that we sit down every October and plan out their entire next year. And say, all right, if these are the conferences you want to hit, what are the— when are you expecting to get data? Because this stuff doesn't have— there's no audit coming down the line where you have to have a paper published by. And so since there's no deadline for a lot of this, it tends to go out the window for some people on their to-do list or always pushed to the back. And it's helpful to have someone who's always kind of pestering you every few weeks. Hey, did you do that one more step forward?

And this probably falls into the responsibility to a large degree of people in marketing because they're the ones that will ask for it. But very rarely would they be the ones that could help deliver it.

I've worked with people in medical affairs, clinical affairs, medical education, and actually less marketing than you might think.

That's probably good. No offense to my marketing counterparts, but this is it. And I just got off a call with my marketing counterpart and like, this is the stuff they want, but they could never deliver it. They're pulled in too many other directions doing other things. So I can appreciate your— you've worked with a lot of different people that are probably better suited to be the owners of this.

But interesting. The marketing people are really useful once you get to like a white paper stage, because in my mind, a white paper is essentially marketing science.

Yeah, makes sense.

Raymond.

Hi, Laura. This is Raymond Cloutier. Thank you so much for presenting. I guess I'm going to take Tiger's advice and give you something specific, but I suspect it's common, and maybe you've got some suggestions. If the device that I have addresses a situation that is relatively low incidence but really problematic if it happens, So I'll be very specific. Let's say 4% of the time a procedure has to be aborted because the implant can't go in. So that's problem number 1. Problem number 2, there isn't any good science or data that's been published on it historically. And problem number 3 is I don't have an abundance of cash. Now Tiger, I could, um, bring my U-Haul up to his house and grab some of his money and give to you, but not me. And I don't know Tiger would let me—

It's a suitcase, not a U-Haul.

Oh, okay. And so my question is, when you power studies, or are you powering studies, and is there any creative way to minimize or somehow do this meta-analysis by inference and/or minimize the selection or the population in order to be able to come up with something statistically significant? Do you see the problems?

I think I understand what you're saying. You're saying that you want to talk about a problem that there's not enough of to really run statistics on.

That there's nothing published. So there's nothing in the literature. And the incidence is kind of like infection, pretty low. And so in order to power a study properly to have to demonstrate statistically significant differences, you have to have huge, you know, enrollment. And in order to have huge enrollment, you gotta spend a lot of money. And so it's kind of akin to, you know, the orphan device kind of situation where it's, you can't really prove it very easily. And therefore nobody ever wants to fund an orphan device. Um, anyway, any, uh, suggestions or ideas?

Uh, first one is, what is the objective specifically?

I want to demonstrate a lower incidence or rate of, of procedure terminations with the use of the implant that I've designed.

So you want to show a lower incidence of something that has a very low incidence, correct?

Ooh, so yeah, I would have figured it out myself, but when you have a situation like this, it's really, really bad for everyone. Um, and so even though the incidence is low, the risk or the harm— severity, thank you— is very problematic. So I'm just wondering, I would imagine you have companies that make evolutionary changes that are hard to demonstrate without a high, a large, you know, group size.

So it depends upon your audience. My first thought, my often thought, is to move away from statistics. And that's not just because of my undergrad grades. But if I would almost lean towards putting together, um, something like an expert opinion, a paper, uh, where you get some of your clinicians who have experienced this and gone through this. And again, it depends upon what you want to use this information for. If you have a friendly journal editor, it might be able to go in there if it's just for marketing purposes and have them put together a discussion of some sort, maybe with— probably with someone who knows a little bit more to help them ask them questions, but about why this happens, when it happens, when it doesn't happen, and have it be more of their— have it be more narrative than statistical. Because it sounds like this problem is kind of outside the bounds of stats, but you still want the information surrounding what happens. Yeah. So again, but it would primarily depend upon what you want to use that information for.

So, really good answer. Thank you. And as it turns out, maybe I'm saying that just because that's what we've ended up doing is we now have, I don't know, 8 or 9 case reports with that expert, you know, case by case. But it's anecdotal, obviously, versus statistical. And so it's difficult to get stuff like that published.

Make friends with the journal editor. See if any of your KOLs are— who have done this— are in any professional organizations that have associated journals. Or if they're on any editorial boards. And something that surprises people is the journal editors, they are human too, and you can just call them up or email them and say, this is an idea I have, are you interested, or do you know someone that would be? And sometimes they say yes, sometimes they say no, sometimes they don't answer at all.

But yeah, and if I could just have a little bit more time, Tiger, with kind of a handle the discussion because Mark Maloney, I had been meaning to connect with you on this very topic. I don't know if you were paying attention to what I was just saying, but about a month ago or 2 months ago, you brought in the guy from, um, why am I blanking on the healthcare system in Georgia?

Piedmont.

Piedmont Healthcare.

Yes. Thank you. And they're large enough to, and they do enough ALIFs in their hospital system to have data, internal data. And what I— the idea I had was to go to Piedmont and to say, okay, let's, let's try something for a year. Here's my hypothesis. Um, you continue doing what you're doing, um, or maybe look back at last year's data and then use my implant and let at the end of the year compare your previous year to your current year because they do enough of the procedure that I'm doing in order for them to look at their own internal data. And so I was going to ask you if your friend, um, would— what he would think of that idea from a proposition point of view. Does that make sense, Mark?

Yeah, um, his answer would be If it doesn't move my needle at least, uh, 1 to 5 million, I don't want to get involved. It might, because that's kind of how he thinks. He just mean it, but he may be able to refer us to somebody that would, uh, be more interested in those results.

Yep.

Yeah, let's talk. Let's, let's connect.

Uh, I would like that.

Thank you. Love to. I have a question. So, um, you know, I'm not a science person. I was an English major because I am intellectually very lazy and I just like to read. But I have a career of making new markets. And what, what do you hear a potential client, customer, surgeon say when they ask you two questions, which I hear over and over again through the years? 'Who else is using this?' and 'Do you have any papers?' What do you— what are they asking?

Uh, 'I don't want to be the first one.' That's what I think they're asking.

Yeah, you're right. I think so too.

'Show me that it works' is the publications, and 'Who else is using it?' is 'Does it work? Is someone else using it? I don't want to stick my neck out.' I'm too busy and there's not enough time in the day. If you show me that works, if other people like it, if other people are using it, I'm happy to jump on board.

But I think you nailed it. When I hear, when I hear those questions, I, I think, okay, you're not an early adopter. Let's, let's just have dinner and I'll, I'll see you later. I'm done.

Yeah, thanks.

Fascinating. You're right, Tiger, she's sharp. Oh, no. Yeah, this is fun. Yeah, AK's in the background. I don't know if you guys know AK. He was the founder of Amedica in Salt Lake City, brought a new ceramic into medicine. And he's got a question. Can you see the question in the chat, Laura? It's a long—

There it is. Me studies like that, no interim analysis. Hmm, what would I suggest? So there's no interim analysis as a condition for the study. I would say this would go— and without knowing more details about the studies or the device— is, is have you propositioned the world? Have you set up the precursor to the story? Have you set up— I keep going back to the gap in knowledge because that's what we always discuss in publishing is you want to set up the gap in knowledge, what, what hole is this filling? And so I, that's my first question is, if you don't have an analysis that you can do in the middle of the study, when the study is finished, when you do have that analysis, have you set up a good story to go so everyone's on the edge of their seat and can't wait to find out about this analysis? Have you shown where other similar things aren't doing as well or not as safe or not as quickly or not as whatever.

That's a good point. Laura, I've appreciated your comments. I'm trying to get to a conference room where it's not so busy. Give me a bit. But we are running a study of a bone graft substitute that has a very novel characteristic. It is unique in the sense that it eludes tobramycin, which is a well-known antibiotic that is used for treatment of bone joint— periprosthetic joint infections. For 8 weeks, which is unprecedented in the industry. The condition we have with our study, 204 patients, but we cannot do an interim analysis. If we do, FDA will say, well, you biased the principal investigators who are completing the study. Even though it is prospectively randomized. And as a small company, we definitely don't want to have the risk of adding number of patients because it's just more time, more money, more resources. So what we've done is we've encouraged PIs and we will get about 3 publications in the coming quarters of case studies. But we, we reserve some of the data so that they cannot make a full analysis. But they can talk about their experience and their clinical evaluation of how the cases progress relative to other cases. So just whether you think that makes sense, that's the only option we have at this point. Mm-hmm.

Or, I mean, you said the term unprecedented, and it— unprecedented in the industry. How well known is that in the industry that this 8 weeks is unprecedented? Because there's a ton of literature about bone grafts in general. So could you get one of your KOLs or a couple of them to come together and put together a study a review on, well, here are some bone grafts that are out there. Here's some of the gaps. Here we're setting up the story now on how long, on other outcomes, and why this might be better.

So we're working on that.

You don't need me then. See, you guys can do it in-house.

No, no, that's a great point. We're working on that. Many of the KOLs are super busy. And as you probably know, or Tiger knows very well, KOLs will often hew to the guys who pay the most consulting fees. So that's reality.

There are people I work for where my job is primarily KOL herding. And so just, I'm the one at the ready. Oh, they're in a car, they're driving somewhere. So I'm on the phone taking notes while they're, you know, pontificating.

Wonderful.

Wonderful. But I mean, it sounds like you're doing good stuff. You're already thinking about a lot of this, just maybe in different verbiage than I did, but you're thinking about the storyline. You're thinking about the publication track record.

We have one already submitted completely independently, a case report, a second one in the works. And we ourselves have put out our second paper, which is currently in press, so being reviewed for drug delivery and the long-term release characteristics. Nice. It's a very detailed kind of mathematical modeling supplemented paper.

So I'm glad there are people out there that can do those.

Well, like you. I mean, if you have a PhD, you've got to put it to work.

Yes.

Okay. Well, thank you for your comments.

Absolutely.

Thank you. Well, AK, he starts a new company every couple of years. So I put his company in the chat. It's called Elute, Elute Inc.

Cool.

So one of the things I learned from Laura, just, I didn't under— I thought you did a big clinical study and you published it and that was it. But there's actually a rhythm. There's a rhythm to the storytelling and you sort of warm up the audience. And that, that was new for me. I really, I learned a lot. There's a whole plan. You gotta think backwards, start with the end in mind. One question specifically, what do you think about JOEI? And it seems to be a publication, an online publication with less friction that you can publish data quicker. Do you have any thoughts?

JOEI?

Yeah, J-O-E-I. Oh, I thought you would know about it. It's started by Ira Kirschenbaum in New York. He's always been a very entrepreneurial MD, and a lot of people swear by it. You can get your thing published really fast. There, you know, there's the peer reviews super fast. I'll, I'll put it in the chat.

So, mixed. I could rant about academic publishing and what a dinosaur it is for a very long time and how it is Uh, there's, there's predatory publishing. The people who are doing most of the work are not getting most of the benefit, but it is the way the system has been for a long time, which doesn't always make it good. And the, the worry about something that can get published very fast is, is it, is it being peer reviewed and is it being peer reviewed well? Um, I don't love the fact that people are asked to peer review for free., and that people are asked to do all this hard work, and they're asked to publish, and the people who are making the money are the journals, not people who are doing the publishing or the peer reviewers. Could rant about that for a long time. But the, the slowness of that system is ensuring that it is getting looked at pretty, pretty well. Although I don't think it should take 6 months to really publish. So, as long as there are some checkpoints in place, some of the open access journals like PLOS ONE is open access. It's really easy to get in. There is still peer review. So that's— it's good. And honestly, these days it's so easy to publish that most people don't really care what journal it's in anyway, as long as they can find it somewhere online, and then they have to use their own brain on if it's a well-done study or not. And then, so really, once again, depends upon your audience, who you're publishing for, how likely they are to see it, and if they're one of the few people that still care about things like prestige or impact factor.

Okay, interesting. I think they're— I think Joey is more— the whole idea is open platform. Instead of a closed, you know, board or peer review, it's a little more friendly to new innovation.

There's a lot of experimental journals out there that are trying to disrupt academic publishing, and so I think there's going to be a better model or a lot of models coming down the line that are more accepted all the time.

Yeah, I mean, waiting for the British JBJS to make a decision for years I think those days are over.

Yeah, that's exactly what I was thinking as you were talking. I was thinking of experimental theater, Off-Broadway versus the classic mainstream, the same kind of analogy.

I like it.

I mean, I like Joey.

There's room for both of those in my world.

So do you read Joey, Mark?

Yeah, I go to it. I like Ira a lot. I've known him a long time. He and I, he showed me what a good bagel was a long time ago up in New York.

I met him at a WebMD conference in the late '90s where he, he joined WebMD as one of their first MD consultants. He's always been on the cutting edge.

He is, uh, he defines intellectual curiosity. He really is always out there and he's not young.

Yeah, he's still going. Anybody? Chris, you gotta, you've been quiet. I mean, Al, I mean the people that are in sales, I feel like, you know, we're cavemen when it comes to clinical studies. We don't know how the sausage is made, but we know we need, we need clinical stories.

Oh, I'll chime in. You know, um, clinical studies to me are difficult sometimes because if they've got a lot of company backing, you know, people don't always take them seriously. Um, so I'm pretty picky about what I show to my surgeons and what I don't show. Um, I can chime in on Joey, their Wednesday night thing. I try and be a part of that as much as possible because like last night they were going over brand new tech. So it's, I mean, plug for them. I think that they— I think Dr. K does a really good job bringing people in to bring light to things that are being improved upon in the industry. So, but yeah, I got here late, so I didn't get to hear the beginning of your presentation, so I apologize. I was on another meeting. But, um, I mean, I really like the idea of storytelling. I had a friend that passed away recently, recently, and that was his big huge thing was storytelling from— he was on the banking business side, and so that was always his stance. Um, was if you can tell a story about a business, then you can get people to buy in. So, that's why I joined in today was to hear how you could do that with science and clinical stuff. So, really interesting. So, I'll go back and listen to the beginning of it.

Yeah.

And if you— Laura, I, I, you, I was writing down just a couple of taglines you said because we're, we're developing a, a non clinical outcome, more user product. But the parallels are there relative to, of course, the storytelling. We always kind of have to tell people a story. And once we tell them the story about what we have, they kind of are like, okay, that's a different way of presenting it versus a bullet-pointed thing is learning by storytelling. So articulating that was just one of those moments of listening to you. It does translate. But I love because we are doing some white paper things now that publication planning side of things, you know, it does parallel. But to Chris's point on the clinical side of things, you know, oftentimes we just need with guys like Mark Copeland's help is utilizing those clinical studies to get through VAC committees and tell the story to make it, you know, what's going to move the needle as Mark said, you know, about getting it into these hospitals that are blocking us from bringing in innovative products. So less about the clinical side, but more— it definitely parallels even a non, let's say, implant clinical dependent product that we're developing ourselves. So I just appreciated listening to you. It definitely— you gave me some taglines. I'm gonna— I'll give you credit. We're gonna steal a little bit of it though, just open source.

I probably took them from someone else at some point, to be honest.

Now, the publication planning is just, it's just so simple because we just talk about what we have to do. But, but using it as a task, this is a task, guys, we need to sit down and talk about publication planning because we will need white papers of efficiency and different things like that that are less about the clinical outcome as it is about the user experience.

So if you think about it ahead of time, you actually, that one meeting will save you a lot of work in the future.

Absolutely. That's what I took from it. Yeah, it becomes now a a line item task we have. Okay guys, let's sit down and talk about publication planning. What's our deal with our, our clinical help, the, the designing surgeons and different things involved. So just always an education on these things, listening to everyone.

Yeah. Another thing I learned is you can start planning before you've even designed your device. You, I mean, you, you're gonna be out looking at predicates anyway and doing literature reviews. I never really thought about that, but you can do a retrospective literature review and publish it and kind of warm people up for your device before it's even designed.

If you need to do the work, might as well use it.

Yeah, I thought that was fascinating. Yeah, anything else? We got some more time. I'm hoping, I'm hoping that Ben chimes up, but he must be traveling or something. Ben's got a really cool early arthritis interpositional for the hip, but he's— I think he's in animals only right now.

Yeah, sorry, I'm recovering from laryngitis. I have a little bit of my voice back. It's okay. No, this was a really great talk. And, you know, as Tiger was alluding to, you know, we are a PMA device. We've only been in animals to date. Most recently was a 12-month study in horses, but we're about a month away from starting our first in-human study in Canada. So we're working with 2 clinical sites up in Vancouver, and we're hoping to have good news from the REB next week, and hopefully get a patient consented before the end of December and treat in early January. So we're very much about to embark on this path. You know, one thing I'm curious about is, if in addition to publications, you know, how you think about folding, you know, presences at the society conferences and presentations, you know, into a publication strategy. And maybe I just missed that part of your talk, but I'm curious how you look at sort of like the breadth of different ways that you can get the story out there.

I think, I mean, in my mind, I I don't love the term publication planning because that makes me think it's limited to publications, but it really is data dissemination. Data dissemination. You know, when you're submitting abstract to those conferences, I think of it that way because there are deadlines for those abstracts. But within that, I would also be thinking about, are you going to have a booth there? Are you going to hold a workshop there? Are you going to be handing out white papers? And does all of that kind of tell the same story? Because the story is, I mean, that we're tiptoeing back into marketing, but the story is what people remember. The story is what people remember about your device and what, you know, tugs on the emotions, hopefully, because that's the stuff that sticks. And so you do want a through line throughout all of that.

His laryngitis kicked in again. Um, can you, can you build a story around horse data to sort of warm up for the human clinicals? Why not? Yeah, I mean, have you ever, have you ever done—

yeah, they've got bones and cardiovascular system and all of that. Have I ever? Um, well, My PhD is actually in translational biomedical sciences. So all of that was based on, um, how do you, how do you translate the bench work to the clinical work? And, and how do you keep the message on how they inform each other back and forth? Um, so have I done it with horses? No, but I have written papers where We have talked about, you know, there were 3 or 4 papers that were all about bone marrow stem cells and how, how they utilized their mitochondria informed how much bone they made. But then the next paper is how if we get clinical samples of bone marrow from humans, Do they have high metabolism or low metabolism? And how does that inform the outcome of their spinal fusion in 2 months? And so it's not one paper, but it all became one story of how metabolism involved bone production, both in, you know, cells, mice, and then in humans and back and forth. So you can There's, there's so many stories there.

So you can connect the dots. That's interesting.

I will send you my thesis if you want to read it.

I actually, I would love to read it.

I don't think my own mother read it.

You gotta be a PhD. So Ben, what was the horse model? What did it look like?

Yeah, so it was a 15mm osteochondral defect in what's referred to the stifle. Which is essentially their patellofemoral region. So I mean, the anatomy of their knee in totality is a little different than the human, but this stifle structure is very similar in size and shape to the human knee. So what's interesting about it is even though it is a patellofemoral joint, it is a joint that experiences compression unlike the human. Patellofemoral region. So, you know, you have a nice big surface area of cartilage that you can create a clinically relevant defect for, you know, the human knee, and you actually get the benefit of load-bearing, uh, as well. So, you know, in our study, we did a lot of the traditional histology, but we also did MRI, and we also did biomechanics.

Wow. And when did you sack What, how many months?

Uh, 12 months was the— we had a couple, couple different time points, but 12 months was the primary endpoint.

I got to see horse surgery in Auburn once. That's fascinating. I mean, they have a giant hoist and sling.

Yeah, yeah, yeah.

They move the animal from the anesthetized room over to the op— it's incredible how big those things are.

Uh, yeah, it's not for— it's not for the faint of heart. Uh, you know, I will say, if anybody on the call is interested in talking about horse research. I've certainly learned a lot about it over the years. We worked with Laurie Goodrich at Colorado State, who's a really fantastic collaborator.

Yeah, it's a great place.

I think I've met her. I learned how to do external fixation on rodents at CSU.

Oh, nice. Yeah, I mean, they do all kinds of stuff there.

Nicole Earhart there.

Cool. It's a small world, man. It's amazing.

Yes.

Well, before we wrap, any other questions, comments?

I just want to say I, I love how we started with the focus on the listener, because, uh, when you— when I think of a story, um, I mean, there's really only two things. There's the story and then there's the listener. Stories that have this universal appeal become classics But the reality is, for most of us, we're trying to tailor that message kind of like you would tailor, you know, like an artillery shell to a particular target, or else it's not effective. Because that's all you have is really messaging and targeting, messaging and targeting. And your really sort of, you know, scientific intellectual approach to it certainly fits very well. I learned a lot. I really enjoyed it. Thanks, Tiger.

Yeah.

Thanks, Laura.

Yeah, thrilled to have her on. So maybe we'll have her back one day. Thanks. Thanks, Laura. This has been great.

Absolutely. And, uh, it's a new— I'm freelancing now for the first time. So please call me. Even if you don't have a U-Haul, we can still talk.

I love it. And if I put her, uh, contact and anybody send me a message, I'll send you her contact if you don't have it. Thanks. That was a good one. Thanks, Laura.

Thanks, Tiger Buford.

Yeah, thank you. This is great.