Bridging the Gap: Avoiding the MedTech Valley of Death with Dr. Adam Saltman

In this episode, host Etienne Nichols sits down with Dr. Adam Saltman, Chief Medical Officer at NAMSA, to explore the treacherous "valley of death" that exists between a medical device prototype and the patient. With a unique "triple threat" perspective as a cardiothoracic surgeon, former FDA official, and industry consultant, Dr. Saltman reveals why technical brilliance often fails in the face of commercial reality.

The conversation dives deep into the common pitfalls of early-stage startups, specifically the tendency to develop technology in a "tech echo chamber" without validating the unmet clinical need. Dr. Saltman shares a sobering story of a company that achieved regulatory authorization and reimbursement only to find that no one wanted to buy their product because it solved a problem clinicians didn't have.

Finally, the discussion shifts to the evolving landscape of AI in healthcare. Dr. Saltman warns against "automation bias" and emphasizes that regulators and clinicians are no longer satisfied with "black box" explanations. Whether it's navigating FDA guidance or choosing between a 510(k) and a De Novo pathway, the takeaway is clear: start with the end user in mind and validate every hypothesis with real-world clinical perspective.

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Key Timestamps

• [00:01:45] Introducing Dr. Adam Saltman: The surgeon, regulator, and consultant perspective.
• [00:03:10] The #1 Mistake: Building a product that doesn't address an actual unmet clinical need.
• [00:05:40] The Echo Chamber: Why engineers must look beyond their own circles for product validation.
• [00:06:50] The CFO vs. The Surgeon: A cautionary tale about who actually makes the purchasing decisions in a hospital.
• [00:09:40] Staying Current: How to manually and digitally track the constant stream of FDA guidance documents.
• [00:11:45] AI in MedTech: Moving from "black box" algorithms to transparent, explainable technology.
• [00:13:30] The X-Ray Failure: A real-world example of AI predicting mortality based on patient location rather than clinical data.
• [00:15:20] Automation Bias: Why you should treat AI as an assistant, not a replacement.
• [00:18:15] Marketing vs. Utility: The "Billboard Effect" of surgical robots and AI features.
• [00:20:00] Signs of Success: How Dr. Saltman identifies startups that are likely to succeed versus those "wasting" capital.
• [00:23:10] Calling the Baby Ugly: The necessity of pivot-readiness and adult influence in startup management.
• [00:25:30] The 510(k) Trap: Why the fastest regulatory path might be your biggest commercial hurdle.

Top takeaways from this episode

• Validate the Unmet Need: Before investing in R&D, ensure your target customer actually sees a need for the product. Technical viability does not equal market demand.
• Avoid the 510(k) Trap: Opting for the easiest regulatory path may pigeonhole your device into low reimbursement codes by labeling it as "the same" as existing technology.
• Combat Automation Bias: Never assume an AI or automated system is 100% correct. Maintain a critical eye and perform regular "smell tests" on AI-generated outputs.
• Engage Clinical Input Early: It is almost impossible to get professional clinical input too early, but it is very easy to seek it too late. Consider fractional clinical leadership to save costs.
• Identify All Stakeholders: Your user (the surgeon or nurse) is often not the purchaser (the CFO). Your evidence strategy must satisfy both.

References:

• Zotero: A free reference manager Dr. Saltman uses to track and tag FDA guidance documents.
• The Founder’s Dilemma: A book referenced regarding the challenges of early-stage startup management and decision-making.
• Etienne Nichols’ LinkedIn: Connect with Etienne here.

MedTech 101 Section: The 510(k) vs. De Novo 

Memorable quotes from this episode

"You really need to start with the end in mind and test that hypothesis. Get out of the office and go out there and talk to people and really confirm that." - Dr. Saltman

"This is my assistant, not my replacement." - Dr. Saltman

Feedback Call-to-Action

 We want to hear from you! Do you have a MedTech success story or a regulatory hurdle you're currently facing? Send your feedback, reviews, and topic suggestions to podcast@greenlight.guru. We read every email and love providing personalized responses to our community of innovators. 

Sponsors

This episode is brought to you by Greenlight Guru. When navigating the "valley of death" between prototype and patient, you need a robust ecosystem to manage your data. Greenlight Guru offers industry-leading QMS (Quality Management Software) to keep your compliance on track and EDC (Electronic Data Capture) solutions to ensure your clinical evidence is ironclad. Whether you're avoiding the 510(k) trap or preparing for a De Novo submission, Greenlight Guru helps you close the gap with confidence.

Transcript

Etienne Nichols: Hey, everyone. Welcome back to the Global Medical Device Podcast. My name is Etienne Nichols and I'm the host for today's episode. Today I want to talk to medtech founders and innovators, talking to them about the distance between the prototype and the patient.

Because a lot of times that distance, that gap can be a valley of death to a certain degree. A lot of different regulatory pitfalls. A lot of different pitfalls, honestly.

And so, on today's episode, going to talk a little bit about what can actually move the needle in medical device development. We're talking, we may delve into some clinical strategy, some FDA insights, maybe some future of healthcare, healthcare technology.

The road is kind of wide open. But joining us today to talk about all these different things is Dr. Adam Saltman, the Chief Medical Officer at NAMSA. Dr. Saltman is a powerhouse in the medtech space.

He brings what I consider kind of one of those rare triple threat, triple threat perspectives to the table. He's a board-certified cardiothoracic surgeon with over 25 years of clinical experience.

He's also worked with FDA for about 12 years and now he's working with many different medical device companies, helping them with their clinical, their, their clinical needs. So good to have you with us today, Adam. How are you doing?

Adam Saltman: Great. Thanks for having me on Etienne. It's really an honor for me to be here. I'm excited to have this conversation with you and hope I live up to your introduction.

Etienne Nichols: It feels like I've been seeing quite a bit of you lately because we first met at LSI where we did a panel together and we talked a little bit about the future of medtech.

Saw you at Medtech Innovator where you were a judge, and then most recently the talk you gave at Greenlight Guru's most recent Virtual Summit. So really covering the gamut here.

I'm glad you're willing to put up with me as much as you have. So great to have you maybe to open, maybe to open up our conversation. I'm curious.

Well, let's start with the biggest mistake you feel like companies are making when they're trying to figure out what it is they need to be doing. Whether that's about guidance, documents or whatever the case may be.

I'm curious. Curious what you've seen.

Adam Saltman: Yeah, I mean, it's been amazing because When I left FDA and went into industry, I thought I was going to learn a lot about the commercial aspects of medical devices. Right. Because I learned about the clinical application, I learned about the regulatory issues, but. But I didn't really know much about the commercialization yet. When I went into industry, the first thing I found out was there's an incredible lack of, if you will, clinical direction. And by that, I mean these medical devices are invented by incredibly intelligent people, but most of them are engineers or lab researchers or maybe a clinician who identified a pain point, but they don't have the time or really the bandwidth to, you know, sit down and really work on it.

So, they kind of hand off the idea to those groups. I was just talking about the engineers and stuff. And the problem is they don't do the fundamental first question, which is, is my product really addressing an unmet clinical need?

Because if it isn't, you're basically building a product for one person, and that's never going to fly, even though you can go through all the other steps. And I actually saw this in action when I took my first job out of FDA, where there was no unmet clinical need. And this company had gone through regulatory.

They were authorized for sale, they had established a reimbursement pathway, and, and they were sitting around wondering why nobody would buy the product.

And I walked. Yeah, I know. It's, it's, it's. I mean, it's. It's so many different reactions. Right? I mean, it's perplexing. It's a whole bunch of things.

But I walked in there and I said, okay, well, how come you're not selling any product? And they were like, we don't know. We have all this data, we have all these publications, we have all this stuff.

And then I said, wait a minute.

Your target customer doesn't see a need for your product? So, okay, let's, let's restart.

Let's start at the beginning.

And so, I guess that's a long way of answering your question that you really need to start with the end in mind and test that hypothesis. Right. To say, okay, I'm going to build this thing.

I think it addresses an unmet need.

Get out of the office and go out there and talk to people and really confirm that. And once you do, then you can start to work on all the other things you need to work on. We can talk about that, you know, forever, right?

Etienne Nichols: Yeah.

Adam Saltman: But anyway, that I think is my answer to your question. What's the biggest pain point?

Etienne Nichols: Well, and maybe if I can Just pull that thread just a little bit about what you said, because I love that example of you going into that company and experiencing that.

You said, okay, let's. Let's start there and work our way backwards. I would guess, you know, I'd venture to guess that many of the companies listening, uh, maybe they're not necessarily there yet to that point where they have that realization. Hopefully they're figuring out before they get on the market.

What's your advice? Or how did you go about rectifying that, righting the ship once, once you realize, you know, we're not meeting a clinical need, we actually need to go this other direction.

What's your advice for companies at that point?

Adam Saltman: It's really. Where are you getting your input from? Is it coming from people who invested in your company?

Is it coming from one or two clinicians? Is it coming from your own echo chamber of your own fellow engineers?

You know, this company had started very much from a tech perspective, and they had amazing technology, no question about that.

And so, they were able to get traction in that community, like funding and, you know, support on their board of directors and things like that. So, the problem was there was nobody there representing the final end user.

Right. Nobody representing the purchaser, nobody representing the regulators. I mean, you really need to get a 360 view and then say, okay, I get it, you've got your opinion. Let me go talk to this other person, what's their opinion?

And then you go home and say, okay, how do I sort all this out? How do I finally come up with a direction? But if you go off with like one input, you're at pretty high risk of making the wrong decision.

Etienne Nichols: Yeah.

What I like to describe or how I describe a little bit of what you talked about is almost like the supply chain of who you need to be talking to.

Because I have a manufacturing mechanical engineering background. It's supply chain. But if you think about from the inception of your product to the disposal of your product, you even mentioned the purchaser.

Those are important voices. You know, the nurses who may handle it or hand it to a surgeon or how that transfer happens, all of those things are important.

Adam Saltman: I'll have to tell you a funny story.

Etienne Nichols: I love it.

Adam Saltman: It's not immediately related to what you asked me, but it's a funny story. When I was still in clinical practice, it was generally accepted that one particular suture manufacturer made the best sutures and everybody used them. They had a dominant market position.

I mean, you know, life was happy, right? And one day, totally unannounced we all came to work. It's like 6:30 in the morning.

All the sutures have been changed out to a different manufacturer. And every surgeon, as you said, my background is in surgery. Every surgeon, like, we looked at each other and said, what just happened?

And we found out it was a purely money decision made by the CFO of the hospital because this other suture manufacturer came in at a better price point.

Did the CFO ask any of us?

No, but the point of the story is the user is not the decision maker.

Yeah. So, you really need to understand all those parts of the ecosystem and say, I'm not selling to the surgeons, I'm selling to the CFO. How do I make this work?

Who's involved? Who are the stakeholders, what are their roles, et cetera. So, you're absolutely right. You need to understand, just like with the supply chain, you know, where are all the moving parts?

Etienne Nichols: Yeah, that's, that's a great story because I could see someone making the argument, well, at some point you influenced the decision. And maybe, but there are probably not many hills that surgeons are really willing to die on for that sort of thing.

Adam Saltman: That one we did. That one we did. Yeah, we, we like almost went on strike that day and we went down there and said, no, this suture is inferior.

We're not operating on human beings with inferior sutures.

Yeah, the one back. And we got our way. But that is an exception to the story, to the, to the rule. Exception to the rule, yeah.

Etienne Nichols: Well, when we first met, we were talking a little bit about the FDA guidance that came out around wellness devices. And I don't know, I'm happy to get into that directly if you want to talk about that FDA guidance.

But if you zoom out a little bit and almost think of it from a meta concept, how do you see or advise companies in maintaining with the FDA guidances that come out?

Because, I mean, obviously there are many. How do they all apply to me?

Do I have to read every single one?

How do you keep track of that? What are your thoughts?

Adam Saltman: Yeah, that's hard. I mean, I'm currently really, up until almost today, I'm doing a very manual approach to it. I mean, I subscribe to the FDA newsletters, and they tell me when there's a new guidance, and then I go off and I look for it, and it's very manual.

I'm using a little bit of AI help in the sense that I can very quickly either point the AI to the website, they can look at it or just download it and then Upload it to the AI and say, give me a summary.

But it's still a laborious process. I don't have a.

Well, let me put it you this way.

I have a reference manager I use. I happen to use Zotero. It's free, so I use it. But the point is, I have probably 200 guidances loaded into that thing.

And the reason I do that, I kind of take a shotgun approach, is because that reference manager has a very good search and tag capability, but I still have to search and tag it myself.

So, I'm not that good at doing that.

And sometimes I just get lucky. Like a colleague will say to me, did you see this new guidance? And then I go run off and I go find it and I read it.

But yeah, there's a lot of you. You can't just tell by the title.

I mean, that's not.

It's helpful, but you really just need to take a quick look. Frequently, you know, the first page or two will have kind of a scoping paragraph or two. That's also helpful, but for me, it's still quite manual.

Etienne Nichols: You know, there's.

You mentioned AI there, and I want to talk a little bit about AI, because I know you have kind of an extensive background in that region.

So, there's two lanes that I see AI taking, and there seems to be a lot of people talking about AI in the product, which is, you know, the actual medical device product. But then we have a lot of areas for AI to be used in the process as you build your medical device, whether it's your QMs or the SOPs, all the different things, maybe even taking a step back, we can go either direction.

We mentioned we were kind of kicking the idea around for this, this podcast. I use the example of AI almost being like electricity. And in the past, we lit our homes with oil lamps, you know, or whatever, and the user could easily troubleshoot.

Okay, I know I need to put this in it. I know you need to do that. Then we moved to electricity, and now we have electricity. It's better, it's faster, its clean energy, I suppose.

But when something breaks, we don't exactly know what's going on behind the walls or in the breaker box. It's a lot more complicated. We have national standards and codes. You mentioned an example from as your time as a surgeon working with different things.

I just wondered if you'd want to discuss that a little bit, how users can interact with AI or think about it.

Adam Saltman: Yes, it's become.

It's become.

Well, it's interesting to watch the field evolve because six years ago when I was working at FDA and I was working on the regulation of artificial intelligence in medical devices, either a standalone or incorporated into hardware, the whole concept was, what are we going to do with adaptive technologies that change on their own, like from day to day as they gain experience. And if you want to freak out a regulator, just tell them the product changes on its own.

Right.

So that was, we were trying to get a hold of that before, you know, the flood came.

And as far as I know, to this day there aren't any adaptive AI medical devices. But the concept was to establish sort of guardrails around it and that's, that's where we, we ended up.

But what's happened over the last six years or so is there's an increasing sophistication on the part of both the users and the regulators.

To look under the hood and the explanation of how your device works, meaning it's a black box. I don't know how it works. It just does what it does. That is no longer acceptable. Right.

And so even as recently as maybe two years ago or three years ago, that used to be okay, like, well, I did my validation. I've shown that it performs on this user population.

Okay, approve my device that's not carrying the water anymore. And so, people are like, well, how does it actually work? What model does it use? What are the features that are incorporated into it?

There have been some spectacular failures of these devices that really. I don't know what's the chicken and the egg here? But like, oh, well, you just read the recent news about.

I think it was a Claude algorithm that wiped out an entire company's database. Yeah, one problem and it went. And then when somebody asked Claude, why did you wipe it out? Claude said, whoops, I did what I wasn't supposed to do. Well, that's not very helpful. Yeah, but, but it is, it is one more story about why people need to understand more of these things. Now I can start as a clinician.

I need to know how my products that I'm using, my devices work.

Because, because I can't go to a patient and say, I'm going to use this artificial intelligence powered device.

And they say, oh, that's great, but how does it work? And my response is, I don't know, that's not good for anybody. That patient's going to say, I'm going to go see another doctor who knows what they're doing.

So that's not good.

Regulators want to know how it works. When it breaks, you want to know how to fix it.

And by the way, the story I want to tell you, there's. I love to tell stories, so just stop me if I'm.

Etienne Nichols: Please. No.

Adam Saltman: So, there was an AI X-Ray reading device several years ago that was built to predict a patient's mortality risk based on their X-Ray.

So, you were admitted to the hospital, you got a chest X ray, the device read it, and then said you were high risk of mortality or low risk, whatever. It performed extremely well.

And at one point, somebody said, okay, how does it work? Let's, like, break it open and let's figure out how it actually works. And what they found.

It had nothing to do with the actual chest of the patient. Like, it had nothing to do with the heart image or the lung image.

It was reading the patient's location.

Etienne Nichols: Oh, wow.

Adam Saltman: And if the location said intensive care unit, it said, you have a higher risk of mortality.

Now, it was not wrong. It was not wrong, but it was not providing helpful insights into, you know, what's wrong with the patient. How do I fix it? Is it a lung issue, a heart issue, whatever. And so that was a cautionary tale about, you know, you need to understand how these things actually work and what they're actually doing.

Sometimes they even provide helpful feedback, like, oh, it's looking at something we never thought to look at before. Not the location, but maybe something like changes in the bones or something that would make you want to then investigate that and learn more about the disease or.

Or how to treat it or whatever. So, you know, there are ways to do that. But, yeah, I mean, a lot of it comes down to independent validation at this point. And the whole concept that you can't use these things blindly.

You always have to validate what they're doing, even after they've gotten through regulatory scrutiny or whatever.

You know, always be like, this is my assistant, not my replacement.

Etienne Nichols: Yeah, there was. There was a story you had told me. Trying to remember what it was about, the wiring of doing a medical device, as when you were going through college or in med school.

Do you remember what I'm talking about? Or we can move on. If not where you were experimenting. You. You had to know how the.

I don't know. It wasn't a pacemaker. It was something like that, where you had to do the wiring feedback.

I may be. I may be shooting a blank here.

Adam Saltman: I don't remember. If I remember later, I'll jump on it.

Etienne Nichols: I'll bring back that. Maybe later. Okay, we'll cut that out. So.

But young, ex. young engineers are starting to use a lot more AI and they may not understand how to use it.

Are there recommendations you.

I mean, aside from just opening that black box and understanding it, are there pieces of advice that you would give when it comes to either the product or the process?

Adam Saltman: Yeah, well, the first thing is to avoid at all costs what's called automation bias, which is where you basically trust that the Device is right 100% of the time.

In a way, when you think about it, that's actually kind of ridiculous because not even the best physician or the best anything is right 100% of the time. And so, to assume that an AI product is just doesn't make sense.

Right? The best they can be is as good as the human that trained them.

Right? Or all of the images that they've looked at or whatever it is. And so even as an engineer, you know, you have experience, et cetera.

Just do a smell test, right? Just look at it and say, wait a minute, there's something wrong with this. And then like, crack it open.

But if it all, if it looks okay, you know, from the first pass, then you're probably okay to continue proceeding. But I've had many times where.

So, for example, if you want to talk about people using AI as tools instead of medical devices for a second, but using them internally as, like, development tools, I do a lot of consulting for companies.

And so, I will sit down.

I have found AI to be an extremely helpful assistant, a first pass kind of assistant. I'll say, okay, this company wants to.

They want to apply for breakthrough designation from the FDA.

I'll pull the guidance document from FDA. I'll pull their technical files. I'll put it into my AI. I'll say, please draft an application.

The application comes back to me.

Of course I read it. I don't send it to the client. You know, I'd look like an idiot if I did that. So, I'd read it and I'm like, wait a minute, this doesn't make sense. This just doesn't pass the smell test.

And then I go back to the AI, and I said, wait a minute, this part's wrong.

Well, will happen is the AI will usually say, oh, good catch.

Okay.

You know, that's.

You can only have an assistant who says that so many times before you get kind of frustrated with them. But you need to just run it through at least that first review kind of kind of situation, right?

Don't just accept it and put your name to it. You'll end up at high risk of destroying your reputation, if not more, if not worse.

Right?

Etienne Nichols: Yeah, I agree. And it's interesting because a lot of companies, it feels like, are bringing out these products that have AI in them that maybe don't necessarily need AI. And it makes me think someone was telling me about when surgical robots came out for different hospitals.

They were better for the billboards than the hospital.

I mean, they brought people in. That was you.

I thought that was you.

How does that apply to AI?

Adam Saltman: Yeah, well, I mean, and I think that's a great example, not because I told it, but because it is a way to really put a frame around this. Right. To put it in perspective.

Because this was an example of a hospital, I won't say where or anything like that, but this is an example of a hospital that had bought a robot. They'd spent however much, a couple million dollars, whatever it was, they spent a significant amount of money, put it up on the billboard on the highway. So, you're driving down the highway, oh, hospital so. And so has a robot come here.

It generated a huge amount of patient influx. I mean, it worked from a marketing perspective, but the surgeons at the would always say, well, actually, you're not such a great candidate for the robot. We have to do your operation the old-fashioned way.

So, they captured the patients.

I don't know how many of them converted, you know, to actual procedures.

But the point is, yeah, it works for advertising. So, AI is kind of in that, kind of in that same space, right? We use AI. I mean, I'm almost sick of it because it's like, AI's in my pinky. I mean, AI is everywhere and. But it's only to attract people.

And at NAMSA, we have that problem because people actually will ask us, I'm not making this up.

People will actually ask us, do you use AI to help you do X, you know, find sites for investigations or write documents or whatever? And I'm kind of like, is that the right question you should be asking?

Yeah, probably not, right? But yeah, we hear it.

Etienne Nichols: Yeah. I mean, honestly, it feels like we need to just get back to the fundamentals, which is what you started about talking about, which is the unmet needs that we're addressing and who those users are, who those who the supply chain of your, your medical device is going to be and really meeting their needs.

So, we, we get to back to those things.

We talked a little bit about pitfalls. What are some of the signs? Because you, you've judged MedTech Innovator, you worked with a lot of early-stage companies, LSI, etc. Other places.

What are some signs that you tell, oh, this company seems like they're going to go places. I can already tell anything like that that you see.

Adam Saltman: Yeah, it's really number one, understanding that ecosystem around your product. Right. Do you understand everybody who touches it along the way, the impact they have?

Also, what kind of evidence they need to buy your product, want your product, approve it for marketing, whatever the particular role is.

And that if you can demonstrate that you understand, you know, all the stakeholders in the ecosystem, how you need to address their needs, that says to me that you have your act together and you're likely to succeed.

Because I've seen many companies in those venues that you've just mentioned and in just other, you know, at NAMSA, we have a lot of companies come to us, they need testing or, or consulting or whatever and they, I'll look at them and I'll say, okay, do you really understand all these parts, all these components? And they're like, no, I just need to raise $500,000 to get to my first in man.

And I'm like, okay, you're going to waste $500,000? I mean, I don't say it like that. Okay, I say it much more nicely. But the point is my confidence level goes down. Or as we used to say on, on scientific grant study sections, we would say it dampens my enthusiasm.

That's the phrase we would use.

But the point is, you know, I'm kind of like now I'm a little skeptical, I'm a little doubtful, you know, I'm not so willing to part with my money if I'm an investor, you know, or, or to, to, you know, to dive in and engage because they really don't understand those things. Maybe they'll get their $500,000, maybe they'll do their study.

What are you doing after that? And the answer can't be I don't know.

So, you know, that's, I want to, they have to demonstrate a solid understanding and for what rolls from that is how much money they need, how much time they need, the tasks they need to do.

I mean, it all comes kind of naturally from that fundamental first step.

Etienne Nichols: Those early-stage founders, especially a first-time founder, it seems like having those answers will be difficult.

Is there a clear path to them to even know what the unknowns are?

Adam Saltman: That is such a fundamental question. I know we've used the word fundamental a lot, but really.

So, there's a book called the Founder's Dilemma that most people listening to this podcast know.

But I have seen it. I've seen it go the bad way.

And, you know, you have to be willing to be open minded, to seek advice, to help, you know, get to get help and to not rely on just one person helping you to get different perspectives.

And you have to be willing to integrate that into, you know, your overall plan.

So, when I run across a founder who says, here's my device and I'm sticking to it, you know, I, So I think we've, I probably said this in a conversation with you before, Etienne, which was part of my job, is calling the baby ugly.

Yeah.

And I know that sounds harsh, but I don't say it that way, but you get the point.

Sometimes there has to be a little, you know, adult influence or however you want to phrase it. But the point is someone has to say, hey, wait a minute, you might have a better pathway to go this way. You might have to pivot, you might need to change your indications, whatever it might be, but you just have to be open to that. And if you're not, then you're, you're in for, you're in for a tough time.

Etienne Nichols: Yeah, yeah. There's a phrase that I'm.

I stole from someone and, but who I stole it from, I don't remember. But anyway, that it's like a man with a hammer looking for a nail in a world that's predominantly screws.

If you're in love with your technology.

And you know what? You don't need a hammer, you need a screwdriver or whatever the case may be, you need to listen to the right person. You mentioned even get multiple surgeons or whoever your end user is, multiple input, not just one or two, because even they may have kind of an off.

I, you know, not being a surgeon myself or a medical professional, but everybody has. Sometimes you get your own way of doing things and you get a broad enough cross section, you realize actually that's not the norm and it's actually not usually a problem with the way most people do this.

Would you agree?

Adam Saltman: Yeah, I do, I do. And I think when I'm not talking thousands of people here, we're talking, just get a few different perspectives from people in different roles. And I've just mentioned the ecosystem before. Right. So, pick people around different places, get those inputs and remember, you know, you're the one responsible for being successful.

Etienne Nichols: Right.

Adam Saltman: People are investing in you. So, yeah, you gotta get that right, Etienne Nichols: that clinical need that clinical. All the things that you do, especially at NAMSA, what Are some of the benefits of someone or maybe the timing of when they need to come to you or come to someone like you about getting that clinical study together?

Yeah, talk to me a little bit about timing.

Adam Saltman: Yeah, somebody asked me that question not too long ago and actually I thought about it for a minute and I gave them this response. I said, it's hard to engage too early, it's easy to engage too late.

Now when you're a small company and I mean, you're strapped for cash, you're strapped for time, you're trying to figure out how to do this.

The way I've seen the life cycle go, most people will wait to get real professional in clinical input until series B or C.

And that's when you're well along the path already. Right. I mean you're trying to actually expand; you're trying to grow, you've got the fundamentals already done by that point to get clinical but then can be too late. And so, the concept is, is there a way to get that input without committing to a full-time person, without incurring that kind of expense?

I mean, you don't need full time input, you just need an hour here or there. I mean a couple hours a month would be enough to get some real value.

Right.

So how do you figure out how to do that?

I've tried to work some fractional engagements, right. Where I can work with a company providing my perspective for an hour a month or two hours a month. Or they call me and say, can you come to a meeting tomorrow?

Sure.

They don't need me 40 hours a week, not by a long stretch, not for a long time. You know, if they're going to stand up, clinical operations, medical affairs, things like that, maybe they need someone full time, but you know, at the early stages just getting another perspective or something is extremely worthwhile. So, it's hard to be too early, to be honest with you.

Etienne Nichols: Yeah, well, I talked about the distance between the prototype and the patient and that's a longer journey than the prototype to the submission or to the first sale or whatever the case may be.

So, there's lots of pitfalls along that way. One of them I believe, or I suspect would be insufficient clinical data after submission.

So not just clinical data that the FDA demands and I loved it. You're smiling. So, what about the clinical data that's needed after? Especially if maybe you're just a Class II device who, hey, we don't actually need clinical data.

What are the thoughts, either of those scenarios?

Adam Saltman: I've actually, I've actually recently started calling that the 510(k) trap.

Okay?

Because everybody, everybody's laser focused on regulatory, regulatory, regulatory. What do I need to do to get through regulatory? And the reason I say it's a trap is because you, as somebody with limited time and money, are trying to get through the regulatory pathway as quickly and cheaply as possible. That's completely understandable. Right.

That's a worthwhile goal.

But you have to be careful because what am I actually getting out of that pathway? And if I can do something like a 510(k). And FDA will be very happy to facilitate a 510(k), because if you just step back and think about it for a second, FDA is incentivized to do what's quickest and easiest for them too. Right?

So, yeah, if you come to FDA and you say, well, I could go 510(k) or I could go De Novo, FDA is going to say, hmm, I'm going to help this person try to go through 510(k).

It's easier for everybody, it's faster for everybody. Let's do it.

You, as the, as a manufacturer, have to say, what do I end up with?

I end up with a product that, by the nature of the 510(k) process, I am the same as this other guy.

And so, is that what you want?

What, to go to market to say, I'm the same as this other guy?

So, you don't have the evidence, which is what your question originally was, to convince reimbursement to pay you more. Right. You're going to be stuck.

And I've helped several clients now who went that pathway and said, now I'm stuck under a very low reimbursing code.

Etienne Nichols: Well, yeah, that makes sense.

Adam Saltman: Yeah. How am I going to get your reimbursing code now? You have to generate clinical evidence. Right. And so, you're either going to do it before or you're going to do it after.

But the point is, you're going to need that evidence to get that higher code, to get clinicians to say, okay, I'll drop what I'm doing now and I'll use your product.

You're going to need evidence to get them to do that.

So, think about all that at the beginning when you're really thinking about what do I want my product to be, who do I want to use it and who's going to pay for it.

And it's not just the regulator in that discussion; it's all those other people.

So, yeah, you need to be comprehensive about your evidence strategy from the beginning.

Etienne Nichols: I really like that. And I've never thought about it.

I want to bounce something off of you because a thought just popped in my head. In any other industry, if you said, I'm the same as, let's say I'm. My shoes are the same as a Nike Metcon, the consumer would assume, okay, maybe it's an equivalent product, but since it's not a Nike, I'm going to expect to pay less for it.

And so, yeah, no, it makes total sense.

Adam Saltman: That's right. And I will actually just say it. I'll say it exactly like this. I'll say if you're the same as the other guy, you're in a commodity space and now you're committing on, you're competing on price.

So, you think about that now, if as a business you can do that and you think you can take over the market at a lower price, go for it. That's your business model. But most of the people I see, as a matter of fact, I'll go far as say all of the people I see are not interested in that business model.

Right.

Etienne Nichols: Yeah. Okay. Well, let's talk a little bit about endpoints then. We don't have to get too in the weeds necessarily. But I would assume when we talk about the clinical trial endpoints and the different pieces of the data that we're trying to pull out, oftentimes we may try to meet whatever the requirements might be for that additional CPT code, et cetera. But there's that other additional piece, the what the clinician themselves will expect.

What is actually going through their mind when they compare these different products are there.

Obviously, that would be the conversation with the future users, but is there some sort of generic way of thinking about how they approach that conversation?

The clinicians, the clinician themselves?

Adam Saltman: Yeah.

So, the clinicians are really motivated primarily.

Okay, this is going to be a little bit cynical, but they are promoted primarily and still to this day by doing good to their patients, doing well by their patients. Right.

They want their patients to have good outcomes. They want them to, if they're on like a chronic therapy, they want them to be well controlled. They don't want them to be crashing into the emergency room. Right. They want to do good by their patients.

So that's the primary thing.

So, the evidence you need to generate is really aimed primarily at that. How are you doing something better for the patient?

Followed by faster, cheaper. Right. So those are what I think are the three most important things for clinicians.

However, I will say that money is a necessary evil in the system.

And the second things clinicians are worried about is am I going to get paid for this?

And you know, I was very naive when I left FDA and I went into industry and I remember we were trying to get a reimbursement code for, for a product and a clinician said to me, look, I think you got the greatest thing since sliced bread, but I'm not using it unless I get paid for it.

And I almost fell off my chair the first time I heard that.

But I realized, hey, grow up, Adam. You know, this is the world and if they're not getting paid for it, why should they use it? They're doing work for free. You can't keep the lights on working for free.

So, you know, that is part of their calculus.

So, then you have to go backwards one step to the payers, right to reimbursement. How am I going to get this product covered with a code that physicians can use?

I can't just go to market like with no code or anything like that.

You're never going to get off the ground. So that's a different kind of evidence, right? In the words of CMS, are you reasonable and are you medically necessary?

That's not regulatory language. That's a totally different language, totally different evidentiary requirement.

Etienne Nichols: Yeah, I think that's a really good way to look at it. And you know, I've looked at the money side as a necessary evil in the past as well. And my, my thinking's evolved a little bit, and I would love to get your input on this and then maybe get your advice for all medical companies.

But money is almost like the air a lot of companies have to, have to breathe. And you know, I, without air, I'm going to die, but I don't go through my life dreaming about breathing.

But if I'm not breathing, that's all I'm thinking about. So that's a problem.

Yeah, but I know we're close on time here. This has been a really fun conversation for me. Any last piece of advice for some of these companies that you work with or should be working with?

Adam Saltman: Yeah, I think the best advice I can give you, it was summarized by one of my colleagues here at NAMSA who just said, start with the end in mind.

And honestly, all the other tasks that are in front of you, which seem daunting at first and they are, they are, they require money and time. And someone said to me, it takes $55,0 million to get a product from conception to market, which is amazing.

And also, there are many years between these steps sometimes, right. So, you know, the average time between getting regulatory authorization and getting reimbursement coverage is average five years.

A lot of companies won't survive that drought, right, for five years.

So, you got to think of this. But start with the end in mind and make sure you pressure test that. Right. I'm going to build this amazing device that's going to do amazing things.

Let me make sure I have all of that in line. Like, what am I going to claim, what's it going to be, you know, how's the user going to see it, et cetera.

And all the other stuff will actually fall into place.

It won't seem as daunting anymore.

And, you know, pressure test that concept. Don't just think it up in the shower one day. Go pressure test it, you know, So I guess that's my best advice.

Etienne Nichols: Where can people find you or where are you headed next? I know you go to a lot of these events, but where can people find you to reach out and talk directly to you?

Adam Saltman: Well, the best place, just send me an email at my work. It's asaltman@namsa.com. I'll going because I feel like I'm doing a Las Vegas thing here.

I'm going to be appearing at.

But in terms of meetings, I think Euro PCR is the next one I'm going to. That's in May in Paris and there are some meetings in the fall. But anyway, that's a ways away at this point.

So just email me. I'm more than happy to engage and respond and help you, you know, any way I can. Thanks so much, you know, for having me on.

Etienne Nichols: Yeah, really appreciate you coming on. And those of you listening will definitely put his information in the show notes. So, if you want to reach out to him directly, you'll be able to reach him.

That or LinkedIn or whoever else reach out to me as well. I'm happy to make the connection if I'm able to help in any way.

Adam, really appreciate you coming on. I hope you enjoy the rest of the year. I'm sure our paths will cross. I look forward to it every time. But up until then, I will let you get back to it.

Those of you listening, thank you so much.

Take care.

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