Dr. Ward : What can we do besides standard-issue testing an animal labs to get answers in a more cost effective manner?

Anyone that has ever built or designed a device from the ground up know, when it’s a sketch on a napkin, it’s cheap to change things. When it’s production tooling, that’s when people start to cry.

If it’s 1x in the concept phase, by the time you get to the production and test side of things, it’s 500 to 1000 times what the cost was in the beginning. So you do simulation work first.

Okay, so everybody wants to foster innovation, they want to create innovation, they want to bring innovative devices to market they want to do innovative things. And there’s lots and lots of theories about how to do that, right?

Every device company I know of talks about innovation in one way or another, from their mission statement all the way through to every corporate meeting they have in their R&D department, because they have the most innovative people and they come up with all these great devices. And they, every single one of them, changes the world, even if it is a laparoscopic device that we change the shaft length by an inch and a half. And it’s the most innovative thing that they’ve ever seen.

Not that I’ve ever been a part of those projects.

But here’s the debate, because everybody says, everybody knows, these are all self-evident things. So if you want to be innovative, half of the world says, you have to “Fail Fast.” In fact, you have to “Fail Often.” They write books about these things.

And I had to pick this one because it has the arrows and whatnot. But there’s probably three dozen books out there on innovation and failing fast, even Mark Zuckerberg is famous for the line, you know, move fast and break things at Facebook. And that’s what they credit with a success and things like that.

The other half of the camp is that none of that works. That’s just complete garbage. And you need a plan. And it’s not that we want failure, both of these people, both people are people in both of these camps, what they want is answers, right?

So the “Fail fast and fail often” crowd is “go try it and get an answer.” And the “All that failure stuff is garbage crowd” is just go get the answer.

Everybody’s after just getting that answer. And the way you get that is through testing things and trying things out and analyzing things. And using all those engineering skills that we’ve been talking about today

The problem is the budget.

If I say I want to try 300 different tests, nobody’s budget really will sustain that. You know, the product development budgets are smaller and smaller and smaller, you’re expected to do things faster and faster and faster.

And the small text over here in the corner says, “Pre-clinical data collection costs go up about 15% a year” – that’s independent of any changes to your product launch schedule.

So if you are a company that puts out things on a regular basis, you can expect those costs to go up 15% every year. And it’s not because only not only because those tests get more expensive.

It’s because the regulatory requirements, the questions that are asked at the FDA, or the EU, or the fringe cases that people are interested in, those are all things that have to be investigated. And so those costs go up.

So if you have a two year device development process, where you have a budget for your pre-clinical testing, by the time you get towards the end, where you’re burning most of that money, you’re off by about 30% or a little bit more than that.

What’s the alternative to standard issue testing in animal labs?

The question I wanted to talk to you about today was, you know, initially, no surprise, based on our conversation this morning, is, what else can we do besides the standard issue testing an animal labs that might get us those answers in a more cost effective manner? We’ve talked before about how much faster it might be. But really, at this point, we’re looking at the cost. And what do we save by looking at these in a different way.

So we want to address these changes as early as possible, right? So as everybody that has ever built a device, or has designed a device from the ground up, when it’s a sketch on a napkin, it’s really cheap to change things. When it’s production tooling, that’s when people start to cry when you tell them that they that they need to change something about their design.

And that’s where this line here in the middle comes from, the cost to extract defects. You know, if it’s 1x in the concept phase, by the time you get to the production and test side of things, it’s 500 to 1000 times what the cost was in the beginning.

And if you wait until you start testing things, which is in the production and test phase, where it’s literally called out right there. That’s an expensive time to start answering questions about about whether your device does what it’s supposed to do, and whether you really want to be making those design changes.

So we do simulation work again, that was the the hot seat question this morning, where Joe and I got a chance to chat.

And as a company, what we look at is using tissue testing as part of your development. We’re certainly we’re not against using tissue testing. In fact, it’s it’s definitely a requirement around understanding how your device works. But if there is a way that you can answer those questions that doesn’t involve the variability of tissue, you know, certainly worth investigating from the problem with invention vivo testing.

The problem with those is they’re time consuming, expensive and difficult. And the difficulty comes in the fact that the tissue is just not the same.

The more control we have over technology in that energy tissue interaction space, we’re looking at control of that energy. You can control lasers and electrical energy in ways today that was unheard of 25 years ago. Control systems are much faster, processors are much faster, sensors are more accurate.

So the question becomes if we start to have that fine level of control, and a lot of different knobs, and the way we are designing our device, if we’re looking at that effect, in something that’s expensive and difficult, difficult and noisy as a data source, you’re going to lose a lot of those subtle effects, not because it didn’t exist, but because of what you’re using to measure it. It covers that up unless you’re looking at a very large sample sizes.

Some studies we’ve been a part of looked at the variability of forcing renal arteries, which is used a lot in bustle ceiling, there was a 30% variance in that data collection, even when controlled to the same animal, the same side, the same day, and everything else they can think of, there was still that variance in terms of performance of the device that couldn’t be accounted by anything that they could come up with on the environmental side.

So collecting data through computer simulations, the FDA and other regulatory bodies refer to that as In Silico data, or In Silico trials. They view all of these different data collection sets in the same way. They consider simulation to be a model much in the way that they consider animal testing to be a model because of a model of what they expect to happen in humans. And in fact, even clinical data is considered a model because it should reflect what’s happening in the larger population, even though they’re working with a subset.

The FDA puts those all in the category of models. We have different ways of doing this. For the In Silico side of things we are looking at what is the device, the design of the device, how does the tissue behave, the tissue, whether you’re talking about liver versus a cardiac muscle or something, those things are going to behave differently, they’re going to react differently to the heat, to force, to energy absorption, like that. And also, the way that you apply that energy, if you turn it up to 11, as the show goes, you know, things are going to vaporize in different ways.

If you, if you apply the same amount of energy over a longer period of time, you’re going to get a different effect, if you pulse it, you’re going to get a different effect. If you put in a control system where you’re getting feedback from a sensor, you’ll get a different effect, those are all things that you have to take into account for specific cases when you’re doing a simulation.

So it used to be that in order to do these types of simulations, it was really in the purview of places that had a lot of computing power. And that was, you know, places like IBM, where they had people that spent their entire careers designing new mathematical models, pushing the envelope slightly, you know, because a lot of these can get very complicated.

If you’re looking at computational fluid dynamics, you know, you could have easily have multi-million degrees of freedom problems, even just when you’re looking at the fluid flow, much less anything else that’s happening in the system.

And so that required a lot of computing power are a lot of trade-offs in terms of simplifying your model in order to get to something that you could actually calculate in a reasonable amount of time versus what it is that you needed to answer from the standpoint of the application. And it was expensive, you know, you had to have in house experts that that was their full time job. You had to have it staff that can support those large computing centers, and things like that.

And that’s really no longer the case, because Amazon and Google and places like that have made made data centers available. And there’s even commercially available companies like Rescale now where you can use cloud-based computing resources to do the processing for you. So even though it used to be that IBM was a place that did all of this, all these calculations, now, even a startup has access to this, because when we do this, these types of simulations, and you run even hundreds of processors against a problem, and it runs for six hours, Amazon is super-excited about this, because it’s not user interface. So you don’t need it answer back in sub-second kind of things. And so when you say, I don’t care when it comes back, as long as it’s not days from now, they can load balance among all of their their different data centers around the world.

And then you get your answer back. And instead of something that would run on a very powerful workstation under your desk for a month, you get an answer back in a couple of hours. And then you can look at your result before you forget what it was that you changed in the model in the first place, which is key.
[Laughter]

Doug and I can commiserate about that – you know, where something runs for a few days. And then you realize that you forgot completely what it was that you changed from the last time you run it and, have to go back into it again.

But now, that’s a thing of the past. And it puts that computing power in the, in the hands of small startups and design houses, and you need to use it on a on a intermittent basis, you don’t have to build up your own computing systems, and then maintain them even when they’re idle.

At this point, you’re only paying for the time that you’re actually using, which is surprisingly inexpensive, when Amazon started to monetize their idle processing speed.

This was something that came up last April [at the 10x Conference], when we were talking about using simulation and speed of time-to-market simulation isn’t really a one-shot. And you haven’t answered everything.

I know from the very beginning of that my time and working in simulations and medical devices, the Holy Grail that everybody would love is to be able to take their SolidWorks model and upload it into a simulation and get an answer to everything that they ever possibly might want to know about that particular device in a very short amount of time.

But that’s not how this works. At least not yet. Not yet, is I’ve been working on this for 15 years. And it’s still not yet.

Instead, what we have to look at is that particular application and add enough complexity to answer those questions. And as we can see, these those orbits around and each orbit were kind of touching base with, with the physical validation, we get a little bit further out into the complexity space. But eventually we get out where we believe our models, we have confidence in our models.

You’re eventually out there, where you’re answering the questions that you need, with a model that you believe, and not only will you believe it, but also you have the data to show it to the FDA. And they’ll believe that as well.

So when you start looking at multiple design parameters, and you even if you just have two or three options for each one, those numbers of iterations get huge in a hurry. So once you have those models that you feel like you have all those things collected, where you’re, you have the physics represented in ways that that makes sense for your application, you can turn it loose on another parameter space and get response curves like this, where you’re looking at things like, you know, maybe this is, you know, tumor ablation size versus power and time, or electrode diameter, or whatever it is that you need to get an answer to. And you can look at maybe where your math minimums are, and drive it from there.

You can also look at things like designed tolerances. So if you know your middle-of-the-road cases, right? But then your manufacturing guy says, “Well, you know, how much room do I have to work here?” You can look at those best-case, worst-case scenarios or, the worst case scenario is if they’re on either end and and look at the performance and see if you if you’re on the edge of a cliff, or if you have some room to work because that can cut down on your production costs.

There are optimizations, but I’ll show you in a second. And then on the Monte Carlo side – Monte Carlo is where you basically, instead of putting just individual values in for things like tissue properties (because we all know the distribution of the thermal conductivity tissue isn’t one value, it’s a distribution for various patients and whatnot), you can put those distributions into the simulation and look at what kind of distribution you get out on the other end of the thing that you care about. Ablation size was the example we used earlier.

On the regulatory side, even though there are increasing requirements, we can start using some of the simulation information to address things around: patient BMI, differences between disease tissue and healthy tissue, you can look at things like we validated all of this in a porcine model and here’s the simulation that matches the porcine model, but when we change the properties to match them, and this is what we expect in our in our human cases.

And the FDA is completely on board with this. There’s two things that have come out recently, in the last couple years.

The first one is the guidance document that came out in 2016 around using reporting computational modeling studies as part of your device submissions.

What’s in there is there’s a whole bunch of checks that you need to hit in order to include simulation data as part of your submission, but the spolier alert is it’s exactly what you should be doing as a good simulation person anyway, where you’re validating your model, you’re you’re verifying that your code is calculating things correctly, all the things that you should be doing anyway, as a good simulation person are things that the FDA wants to see as part of that submission as well.

And the other one is ASME V&V 40: Verification, validation of computational modeling of medical devices. That’s a standard for the ASME that is supposed to come out this year, that’s a committee meeting. And in April, it was supposed to be out in July, and I haven’t seen it yet. So hopefully before the end of the year, that should be out.

But that is less about what actual verification validation you have to do and more things along the lines of context of use, what kind of risks are you looking at, and that’s going to drive how what kind of simulation is appropriate. And some places where it’s high risk, you’re going to need to do both, the simulation and the animal studies, and, you know, answering questions like applicability and things, things along those lines,

I put this slide in pretty much every presentation I do, because it’s important, and it’s surprisingly important in medical devices.

But you have to do validation, this isn’t an either-or sort of thing. We don’t get to just do simulation and never, ever actually go work in tissue.

And you have to do convergence tests, especially if you run lots and lots of these so that you know, that you’re getting to the right solution.

And the last line the bullet point down there is one that I never thought was going to be an issue in medical devices. But it turns out it is more often than, than I think we’d be comfortable with, but you can’t model what you don’t understand. If you don’t know the physics of why your device works. You can leverage simulation as part of your development because even though the FDA I don’t know if it’s still the case, but it certainly was a while ago where if you know that you do X, Y and Z and you always get the result that you want and you do that enough times and get it through the FDA if you don’t understand why x y&z drive that, that will prevent you from being able to use at least physics-based modeling for accelerating and saving your budget.

Rough examples real quick. One thing that we were involved in recently was, this is actually a device that came out of the Texas Medical Center that we were talking about with, with Lance Black. And I think he referred to someone at Methodist that was just handed their IP with no strings from the from the hospital.

This is that project. This is a urologist that came up with an idea for a device, they’re going to move from their initial concepts into a first-in-human trial. The top design is the end of the probe that they’re using. But actually they wanted to, rather than having to build their own prototypes that get those approved to us and humans, they wanted to use bipolar forceps as as their proxy electrodes and wanted to know what the difference was, whether there was any risk with damaging the tissue by applying these electrical pulses through bipolar foreceps, which is what’s in the bottom versus their device.

So we did a lot of simulation work around how far away is that from the ureter. We were looking for current concentrations of possible places where you get some thermal damage from application of these electrical pulses.

So we were able to create the visualizations and say it’s unlikely you’re going to get it have any thermal damage. They were able to take this to the IRB and get approval for their first-in-human, based off of this type of analysis.

So when they, rather than requiring more porcine models, another powerful technique using simulation is the optimization, where if you can describe something mathematically, you can turn the computer loose to solve those sorts of things.

I found videos are a good way to communicate what we do in simulation world with non-technical audiences, because it kind of gives them an idea and walks them through it at a reasonable pace. But what we’re looking at here is half of a jaw set, a hemostat-styled device where they’re trying to

minimize the mass of the device of the jaws themselves in order to increase visualization down at the tip of the device. But at the same time, it can’t be so flexible, that the jaws are going to deflect and touch and short-out if there’s no tissue between them.That was a subset of the different iterations that were done by the computer and try it and ran through all of this, for the shape optimization, I think it ran through about 350 different designs as it zeroed in on what would be the, the proper curve to that, given a certain load at the root, and then just simply supported at the tip. So it was an opportunity to drive through a bunch of those, have those then created, and move forward from as the first pass for prototypes.

Another example is a device where you’re looking at renal denervation. And this is a cooled catheter, where you run coolant through the balloon that occludes the vessel. There’s a nerve about four to six millimeters below the surface, that you want to apply RF energy, and ablate the nerve, but you want to run enough coolant through there, that you protect the vessel itself. And we were using optimization techniques on applying the energy into the end of the tissue to get a good idea what that behavior needed to be on the algorithm and energy delivery side rather than on the device itself.

Joe Hage: Are there some medical devices or situations that are not suitable for simulation first?

Arlen Ward: I would say that’s a balance, right? If you have a device that’s easy to prototype and not expensive to test, simulation is going to lose out to just building the prototype and and testing it.

If you if you’ve done a lot of these, whatever the devices that you’re looking at, and your experience tells you, you know, answers to those questions within a certain amount, that becomes an area where you’re just going to want to build it and test it rather than spend the time on the simulations. I certainly don’t say that the simulation is the be-all, end-all and applies in every case, I think it’s you use them both, it becomes just another tool in the toolbox.

Tor Alden: Great speech. Tor Alden, HS Design. We’re seeing a lot of AI, artificial intelligence and coming into the SolidWorks models and basically taking away our jobs eventually. But what at what point do you see the use of AI with your simulation tools? And when you mentioned you said you went through the ablation blades and yet you ran 137 – I forget how many models – did the machine optimize and pick the best one?

Did you just run it overnight and it gives you the right one, or do you have to do the post-modeling analysis to choose which one is the ideal?

So in that, in that particular case, for the job, we had a math equation that defined what would be optimal.

We basically said, we want to minimize the mass in the jaws by changing the shape by subtracting things away from the shape, but not exceeding a certain deflection in the job.

So those were the two things that had to be driven. In that case, it was just turned loose. And as it solved cases, it took an initial guess to the first one and looked at it, how it compared to the original and work its way through until it came to a minimum on in terms of mass, where anytime they would remove more mass than that or change shape in any direction, that it would increase the mass or exceed that limit of deflection.

So if you can describe your design goals, in terms of the optimization equations, you can turn it loose and have at the end, you have one one result that that simulation run says is the optimum based on where you’re at. For the most part, if you can describe what you’re trying to do in terms of that you can turn it loose.

Now there’s a whole other side of a whole other field of topology optimization were there it’s removing material from designs, and it works very well with additive manufacturing, because it’s no longer constrained by what you can machine. It’s now kind of printing out designs, that’s a whole other area that’s just getting started. And the impacts that I think are yet to be seen.

Srikoundinya Punnamaraju: I have a couple of questions.

At the interface of biology and engineering in a way. Are there other simulation tools available? The simulation is as good as the model of the inputs you to begin with. So, do you account for the biological environment of that to see the adverse impacts of, if any, of the simulation on the on the environment?

And, and the second question is, if you have to do like a number of models to get there? How does that compare to the testing?

Joe Hage: Well, let’s repeat the question because, despite protestation, he still spoke softly.

Arlen Ward: So the second half of that question was, if you have to go back and you’re running multiple simulations, how does that compare to to building these things, right.

A good time to use simulation is if you’re looking at six to eight weeks lead times to build something or you have a system where you have an energy delivery side and a disposable side and maybe you need to make progress on the disposable but your test fixture for the energy delivery side isn’t ready yet, that’s a great time to use simulation because even though you may not get 100% of the answer, if you’re 80 or 75% or something short of that, you’re still gonna be making progress towards for getting you know narrowing in on the answer that you want.

So time-wise I’ve yet to come across well I mean other than the things that we passed on doing the first place where you said you know you’re better off for your device just going out and testing it.

The one that I’m thinking of in particular was a needle-force insertion test where they had already built the prototype and it was a matter of sticking it through some porcine and skin and putting (??) on it. And it’s like, just go do that. You you don’t need us to develop models to address that. So time-wise, the simulation wins out.

When it’s the other side of that, where they’re complicated things to physically build and get answers to, but then you also have to instrument them up and find appropriate test.

On the boundary condition side, depending on whether you’re looking at mechanical (??) or Lachlan thermal boundary conditions, you can certainly match those to the soft tissue and the biological environment. Things like profusion are included in a lot of these models because it matters.

If you’re looking at polls, electrical pulses, and want to know whether it’s going to be a thermal damage risk, the blood that’s going through there is going to reduce that risk. So you want to include in the model, right? So those are those conditions are included as they need to be.

One of my pet peeves in the simulation world is companies that are using, especially implant companies that are using analysis to analyze their their implant, but they don’t analyze the soft tissue that’s around it, right? Because that’s the loading condition for the tissue, right.

Joe Hage: Dr. Ward Thank you very much. Thanks.

Dr. Lance Black: So, because we don’t take equity, we don’t charge.

We’ve had companies come through who are your typical accelerator companies all the way to companies who are 30, 50 strong, who’ve raised their Series A, Series B, who want to use Houston as either their US launching pad or a new sales channel, or just a new market that they can evaluate.

When you have 10 million patient visits per year, [we’re our] own market, as you can imagine.

I’m here to talk about something pretty exciting. It’s actually a parking lot company. And you may be asking, “What the hell is this guy doing, talking about a parking lot company?”

And really, there’s one word: is innovation. And I know we’re kind of sick of hearing about innovation. Everybody wants to be innovative. It’s a hype word. Every hospital, every business, every business unit is putting innovation on their forefront. But really, I contend that innovation may be easy to define. But sometimes it’s difficult to tell unless it’s in retrospect.

It’s kind of like to me defining a law, but not understanding the spirit of the law. So, what is innovation? Implementation of novel and useful ideas that are going to be for the betterment of society, in this case for healthcare.

So let me start a little bit of backdrop, the great city of Houston. I did not know this when I moved there two years ago, but it is the most diverse city in the US, over 140 languages are spoken inside of Houston. It’s more diverse than New York City and Manhattan, which is pretty crazy. What does this mean? Great restaurants, good food, but it also creates an environment, or a culture of innovation and we know that diversity, not just based on race, gender, ethnicity, but a culture where there’s diversity in thought, diversity in personality, innovation, bubbles up, innovation grows.

We can’t mention Houston without talking about the energy industry. We’re actually the energy capital of the US with over 4800 energy firms within the city of Houston. So, if you’re an engineer, and you’re in Houston, chances are you’re petroleum, you’re mechanical, you’re working on oil and gas, had something to do with this oil boom, several hundred years ago, or 100 years ago.

Lastly, it’s the space city. Who here knows what the first word spoken on the surface of the moon was? That’s what Governor Perry thought, but he’s actually wrong. It was “connect,” connect light, I think it was the first term used. Then later on “Houston, Tranquility Based here, the Eagle has landed” is the famous line that people sometimes quote, but that came after several technical words. So, Houston was not the first word even though that’s what it says. But we are definitely a city known for the space industry. NASA, obviously, the Johnson Space Center is located in southeast of the city limits.

And so why am I mentioning all this? Well, first and foremost, just to kind of give a little plug, I’m actually sitting as a scientific advisory board member on the mission to Mars and space health. So, talk about innovation. Think about 30 years in the future when we’re going to be traveling to Mars for astronauts, a six-month journey there, 12 – 18 months on the surface of Mars, six months back, what kind of medical technology do they need? What are they going to have to have in place so that if something does happen in space, none of which the plan is right now we’re going to be physicians, how are they going to take care of themselves? How they’re not going to go –with my biggest concern is their mental health — how are they not going to go crazy? If you have four people in a room for six months? I think anybody would go nuts. In fact, they’re doing studies right now where they’re sticking four people in a hotel room and it got up to about 90 days before things start breaking down, and people start going a little crazy. So, they’re trying to figure out team dynamics and everything in place, how do you, how do you a qualify or how do you overcome that problem? I mean, imagine you can’t even speak to your family members without a 90 minute, or depending where you’re at, delay, so it’s kind of hard to have a conversation like that.

So that’s the backdrop and it is not, this is not a pitch to sell you on Houston how amazing of a city it is, although I’m learning that that is the case, but really it’s a backdrop for what I’m about to tell you next which is the audacity a cotton gin former had, and he had done really well on the cotton gin industry and he said “you know what, I’m going to buy this swampy part of the land just south west of downtown Houston and I’m going to make it the world’s best, most innovative medical healthcare system”. And everybody was like, seriously, kind of laughed at him, but he had this intention because his family had suffered through some health care issues and he really wanted to leave a legacy. He really wanted to, as most of us do, have value and what we bring and have value once we’re gone from this earth, that we can point to or our families can point to and say “it’s because of that person that this exists”.

And so he bought this land, and he posted this sign on the empty swampy land, “Texas Medical Center, coming near you” basically. And what he did is through a foundation, and many of you may know the hospital MD Anderson, but through the foundation known as the Anderson foundation, same name, he set up a third party TMC corporate organization that he bequeath the land to, and he said “Okay guys, you take care of the land. One condition, the land is for free to anyone who has a mission to change healthcare, innovate, and conduct research”. He said, “give the land away, I want you to take all this land that I’ve, you know, kind of drew a circle around, it’s about two square miles, and give it away!” Now it’s on you, as this real estate company, to make a sustainable business, and to pay yourselves and to be able to support the land and everything that goes around real estate. So, what did they do? And that’s kind of the innovative part I’m talking about here in a second, but the rest is really history. From that first open land available to anybody, can you imagine how else to get hospitals to come to your lands, like “Hey, you can have this for free!”

Amazing things have been occurring all the way till present day, and I have a medical city, and I’m going to tell you a little bit about what this medical city entails, but just in the background is downtown Houston, in the foreground is a Texas Medical Center. It truly is a medical city. The history is astounding, the legacy that’s been left or continues to develop is astounding! In 1964, Dr DeBakey does the first coronary artery bypass graft. In 1968 Dr Denton Cooley, first human heart transplant. And I don’t know if you guys know, and if you don’t, but if you look up the Denton Cooley and the DeBakey debacle, the conflict, the fight that went on between them, between Texas Heart and Methodist I believe. Methodist hospital, interesting story, that’s a whole other lecture on its own. They were really competitive but also friendly. But that competition, they were racing to be able to be the first to do something, to be able to create the new artificial heart, to be able to, to implant the next LVAD. That competition bred innovation and it’s set a really a legacy for the Texas Medical Center. In 1971, Texas Children’s collaborated with NASA to produce a plastic isolator bubble for this child who had severe immune deficiency, and you guys probably all know the story of the boy in the bubble. That’s where it came from. 1976 Dr “Red” Duke came up with an idea for Life Flight which was the first air transport ambulance service. And it goes on and on and on.

Then fast-forward to a few years ago in 2014, our community looked back and said “There’s some amazing things happening and we’re having a difficult time just keeping up with it. There’s hospital on top of hospital some are competitive, some are duplicative some friends, some are not friends, how can we support this amazing medical city?” And from that came a couple of things that I’m going to talk to you about here in a second, but I wanted to kind of show you some of the names that are now part of the Texas Medical Center: Baylor College of Medicine, MD Anderson, Texas Children’s, A&M, to Memorial Hermann. Some of these names I’m sure you’ve heard before, any one of these health systems could stand alone and be considered innovative and amazing within themselves. But they’re right next door to each other, and what I mean by right next door to each other. So, if you do a two square mile circle, within just south west of downtown Houston, you would capture 61 institutions, 21 of which are hospitals, academic centers, and research institutions, including the rest, all of which are dedicated to healthcare. So, you literally are walking on the street looking at these different organizations. And by the way, they’re all independent and they’re all competing with each other. 10 million patient visits per year in this health system. 15 million developed square feet. This numbers wrong, 9200, it’s now over 10,000, and before I came to San Diego, I looked up the entire San Diego County and I counted how many beds are included in all the different hospitals, they have 7000, they just went up 2000 as of two years ago. So, within two square miles, we have more beds available than the entire San Diego County has. And why am I telling you all this? Because the critical mass that’s present within Houston is a playground for innovation. It’s a petri dish, and I’m going to tell you how we’re kind of leveraging that and exploring that as we go along.

So that 2014 conversation with the community leaders included the sea level suite folks, and each of these institutions, included community leaders, included those who had any decision-making power within the Texas Medical city. And we said, “What do you need? Where are your strengths Where are your weaknesses? How can we combine certain things? How can we fill in certain gaps?” And we came up with these five themes. Really straightforward, practical themes. One, of course, innovation, everybody wants to be innovative. Two, health policy, we want to be able to set the standard, we want to be able to be forward thinking in how health policy comes down instead of being reactionary clinical research. Imagine, this is an example, 21 Hospitals, so TMC corporate has a Clinical Research Institute, their first goal is to create a single IRB to have access all 21 hospitals. Talk about a multi-site opportunity that’s just under the umbrella of this third party TMC corporate and they’re actually making really good progress. So, a quick step back before I finish TMC corporate. Remember, is a real estate and parking lot company and I will tell you why parking lot is important here. Fourth, genomics. Fifth, regenerative medicine.

Parking lots, OK. So now you have land, you’re going to give it away for free, but you got to have some kind of income capital to continue to sustain yourself to maintain that land. We’re essentially like a little municipality, we provide security, we do landscaping, the roads are our roads and other cities’ roads, we have to take care of all that. Well, how do you do that? We created a crap ton of parking garages. And we make over 90 million a year in parking. When you have 10 million patient visits per year, when you employ over 115,000 people, including physicians, nurses, technicians, etc. They all need a park somewhere. So that’s the great to me, that’s the genius that really allows for this, some of these programs to be kicked off. And now as a third party, who owns the land we can, we have this godlike view, we can look down and say, you know, what we’re going to try to make you guys work together, we’re going to force collaboration with these five themes supporting us, because these are themes that you guys told us you need. And I’m going to focus on the Innovation Institute, that’s the one that I work for. It’s the one that really got off the ground the fastest and the soonest, about four years ago, and I’m going to show you how we kind of are, forcing collaboration to an extent, but it’s a welcome force, if, you know what I mean.

So, the TMC Innovation Institute really, we can say, is shaping the future of health, because we’re uniting not just these institutions, but we’re uniting, promising innovators, researchers, scientists. Incredible stuff is happening in the Medical Center, but half the time one organization doesn’t even know what the other organization is doing. Right next to each other, it’s really kind of interesting. And so now we have this perspective, we can kind of filter through that and see who’s doing what, and how to combine, how to separate, how to challenge what they’re doing, and really support innovation. So, we do that in a number of ways. We have five different programs, and you can think of these programs really just at from a stage of supporting start-up companies at different stages within their life cycle. So, we focus primarily on medical device and digital health. Our partners focus on therapeutics, and diagnostics, and we’ll walk you through what each of these programs mean, and how they affect innovation. So, this is our campus, it’s about a mile south of the Medical Center, it’s about 700,000 square feet. Guess what, we own it.

So, it’s really good to own real estate in this business. So, we can do everyone with this building, it’s actually an old Nabisco cookie factory, originally turned into just overflow. So, for the hospitals who needed a little bit extra space, so they’re building an extra wing, they can lease a stays, they can lease a room to be able to, you know, have the Change Manager take place while they have someplace to go. Then we started to push them out slowly. we occupy now about 250,000 square feet with all of our innovative efforts. The idea is to overcome this empire building to be an innovation neighborhood.

So TMCx is our kind of most well-known program, it’s a medical device and digital health accelerator. The program lasts four months, we invite companies from all over the world to participate, February to June we focused on digital health companies, August to November we focus on medical device companies. We don’t charge anything, we don’t take any equity. That has caused us to be somewhat stage agnostic from an accelerator standpoint. Generally, an accelerator obviously, gives a little bit of financing up front, then takes a certain percentage of equity, and they do that with certain types of companies, because not all companies are willing to give up that kind of equity for, let’s say, $100,00, 6%. So because we don’t take equity, we don’t charge, we’ve had companies come through who are your typical accelerator companies, all the way to companies who are 3050 strong, who’ve raised their series A, series B, who want to use Houston as either their US launching pad or a new sales channel, or just a new market that they can evaluate. When you have 10 million patient visits per year, it’s its own market, as you can imagine.

And so, we’ve been able to really capture a unique piece of the accelerator puzzle here. Now, we get about two to 300 applicants per cycle, and we accept 20 to 25, so not everybody comes through as accepted. But more recently than anything, we’ve been seeing a high propensity of people coming from the west coast and the East Coast international. Houston itself, we don’t have that many folks. Actually, in this Co Op, we have 23 companies, I think Houston based or Texas based, 9 International. The majority are West Coast, some East Coast as well, and what the West Coast companies are telling us is, it’s crowded in Silicon Valley, it’s crazy. We’re competing against 27 other start-up companies. You guys have a Greenfield, it’s like a playground, like I mentioned earlier.

So, we’re getting really good feedback. To date, we’ve supported 88 companies, we’re now somebody another 23. So, we’re going to add well over 100, after this cohort is over. We’re on our seventh cohort, those companies have collectively raised about 130 million, before and after the accelerator. This is a number that we’re really proud of right here. 220 customer engagement. The way that we measure that is through formal agreements that these start-ups have with our institutions. As a third party, we can’t force collaboration, we can’t say,” Okay, start-up A you’re going to go work with Memorial Hermann, Memorial Hermann is going to do a pilot study with you, or they’re going to support you through some kind of co-development effort.” We can’t do that, unlike some other accelerators can. So, at first concern, are these hospitals responsive? Are they going to work with these start-ups? How are they going to appreciate innovation? Are they going to look at it like we look at it? And right off the bat, we’ve noticed that they’re willing to engage almost at the outset of the cohort because they see TMC acts a filter. These guys have looked at a bunch of start-ups, they understand what’s good, what’s bad, they’re vetting them for us, and they’re pushing it forward. So on average we get per company two to three letters of intent, or formal engagements, or some kind of pilots, that these companies walk away within four months of a time of, within a form of time period. We thought there was no way hospitals are going to move that fast, it was going to take 9-12 months and these numbers are going to come slow, but it’s been pretty impressive, and we’re pretty excited about it

These are our companies, from out last medical device cohort. This is TMCx five, we’re now on TMCx seven, and I wanted to just kind of show you that we don’t have any particular therapeutic focus, we don’t have any necessary requirements for stage except one, which is you have to be fully dedicated to your company, or at least have one founder that is, and you have to works as prototype, whatever that means. We just want to make sure that this is not a side project. This is not something a professor is working on, or a physician is working on the side, but it’s something that they’re fully dedicated to supporting. So that’s our minimum requirement.

The other thing is we, these companies represent therapeutic areas, all from ob/gyn to cardiovascular to at home use, to direct-to-consumer to direct-to-hospital, variants of business model, variants in therapeutic focus. We’re just looking for the best companies, we were looking for the most disruptive companies, ones that we can really support and live with four months, which includes their personalities. So, we screen a lot of crazy entrepreneurs out because of that, but I want to let you guys hear from them for a minute.

So, let’s start with a couple of them. Poly Vascular. This is a really good case study for us. This is a company that came out of Baylor College of Medicine, that we had to convince to be a company. It was a physician and two researchers, two engineers, that worked for Texas children’s and Baylor, and they’ve been working on this heart valve for some time. And they didn’t know, they had no idea how to commercialize, and Baylor had no idea how to commercialize it, not talking about Baylor, but they just, in this case, didn’t know how to do it. And so, we convinced them, like, “listen just form an LLC come through our accelerator program and we’ll support you.”

I am Henri Justino with Poly Vascular, and our aim is to transform the care of children with congenital heart disease by developing an entirely new generation of valves made of medical grade polymer. The most commonly used valve is a human cadaveric valve. Our body’s immune system really targets this tissue and destroys the valve, sometimes very rapidly. The valve we’ve designed is entirely devoid of any biologic tissues. our approach would allow us to deliver these valves in a minimally invasive fashion that can last over 200 million cycles and even grow with the child. We saw a gap in the care of children with congenital heart disease and we said let’s roll up our sleeves and do something about it.

So, I’m really proud of that company because I feel like they wouldn’t exist, had it not been for us just kind of pushing them along and getting them out. So now they’re doing really well, they’re hiring their CEO because they realized that they can’t run a company on their own, but they’re born through our program and they’ve been able to kind of see what they’ve been working on. The research is actually something that’s commercializable and it doesn’t need to sit on the shelf of an Office of Technology Transfer and hope for licensing. You can actually do the activities required to bring it to patients sooner and faster. So pretty exciting company. This one, vitals, I make fun of them because it looks like vittles, if you guys are from the south of that is, but this is a company that was born in South Africa. They thought, because like most of us do, that Silicon Valley is where things happen and they moved to Silicon Valley, and they found themselves struggling because of all the competition, because of the crowd and it’s because of the kind of the green innovation that’s taking place there. But there’s just too much of it for them so they came through our program and have subsequently moved to Houston, so I’m going to let Werner and talk a little bit about vitals.

My name is Werner and I’m the founder or Vitls, and with Vitls we’re developing a platform that enables healthcare providers to continuously and remotely monitor their patients’ vital signs. It’s unobtrusive, it’s very thin, we built a ton of sensors into the device, Temperature sensors, PPG sensors, accelerometers. We monitor body temperature, pulse, RR intervals, respiration rate, blood oxygen levels, sleep and movement. hospitals that implement a contact free or continuous monitoring can save up to 20000 dollars per annum per bed. What we would like is to run our pilots with TMC hospitals and then commercialise our device.

So, these companies, they come through Houston for the better part of four months, it’s really six weeks, where I put them through some significant curriculum and programming. In fact, Jon Speer is one of our advisors and he teaches some of the classes related to quality. We have something we couldn’t do without, you know, these advisors, is we have 250 folks that support us, ranging from specialist physicians to regulatory quality experts that are willing to get back and commit to the innovation that’s taking place in Houston. And so those advisors, actually the ones that do the teaching, they’re the ones that sit in the panels, workshops, all the office hours, and really nurture these companies as they’re going through the process. My job along with some of the other strategists is to support them one-on-one while they’re going through. So, identifying some of the milestones they want to achieve for themselves, while they’re going through this four-month program. Because, as we all know, four months is a snapshot in time, right? We don’t want it to be, here’s four months, here’s a bunch of curriculums, learn it and then leave. We want to provide some stickiness, some opportunity for relationships to grow. So, if they’re coming from outside of Houston, there’s a willingness and desire for them to stay. And so that’s exactly what happened to Werner. He got his pilot with Texas Children’s, and he’s actually starting to run it right now. And so, it was because of that relationship that he actually chose to move his company to Houston.

One last example, another one that I’m proud of, Alleviant Medical. And I’m going to talk a little bit about the program that they went through which is called TMC Bio Design, very reflective of Stanford’s Bio Design. But they went through a program that we have that’s intended to build out start-up companies. Then, they went through TMCx, and then, they used some of our other programs. But I’m going to let, I think Jake, tell you a little bit about their project or product development.

Mark Rutkiewicz: We’ll start with the five questions here.

The basic starting point that everybody typically has is the baseline – what’s the cost? And if you make the selection just on cost, you may, in about a year, be very sorry about what decision you made.

There are a lot of other things also. You might be looking at the quality system and the technical expertise associated with that contract manufacturer.

There are many types of contract manufacturers doing:

• Box builds
• Part assembly
• Catheter assembly

At Innovize, we do:

• Converting. high-volume film roll converting;
• Printed circuit board assembly; and,
• Sterile packaging and prep.

But those are just the baseline that you should be looking at. We’re going to go through five questions on:

• The right information being shared;
• What kind of product development services they provide?
• What contract manufacturing services they provide?
• Is it convenient for you? And,
• Is it a good business fit?

I’ve been in the industry 30 years. As part of that, I’ve been in the large medical devices. I was at Guidant for about 3 years, and that was my first intro into contract manufacturing. We had an in-house circuit board assembly, and we needed to outsource. And so it was given to me to look for a new house.

We ended up choosing a facility down in Southern Minnesota called EMD. They were not the fit. They never did medical before, but they had the expertise in the technical side. They were close, and cost-wise I think they worked out. And they became a long-term partner with Guidant and now Boston Sci. They’re now called Benchmark.

We didn’t use a formal process at that time. Since that time, I’ve been in multiple other medical device companies selecting contract manufacturers, and now I’m on the other side as a contract manufacturer. We have a lot of our customers come to us, and we’re trying to provide the right kind of service and support and fit, and culturally match each other.

MaryBeth Privitera:: I like to take pictures of things. I observe people for a living, and I observe the surroundings I live in.

Carsten Horn My speech today is not about showing you what great motors we have, and what great gearboxes, and whatever we have. It will be more about the methodology that I figured out over the years – how to design such small medical devices and the impact on miniaturization – and what I learned over the years, what is beneficial and not.

About maxon precision motors

Of course, I need to talk a little bit about Maxon first. That’s part of the story, that you have a bit of an impression of that. I will talk a little bit about some driving factors for miniaturization. There’s a lot around. I can spend hours on that. And if you look on the internet, it will be endless.

Then I will use one example – what I want to use to follow along during the process of the development of a miniaturized version. I will talk a little about the outside in, inside out. Maybe you heard about the development. The design’s always from inside out. I also want to bring the part from outside-in in here.

I will talk a little bit about technologies that make it possible. Miniaturization has a lot of technology that’s behind it that gives us the opportunity to go so small.

Then some of the design principles to follow. Miniaturization is always about tolerances, about sizes, about handling, and some impacts on costs also.

In miniaturization, it is not always the case, if you go smaller, that it is getting cheaper. That’s a misunderstanding, I can promise you. It doesn’t matter.

I will go to some points, and we’ll talk about the good-enough design for many of these things.

Let’s talk a little bit about Maxon. We are a Swiss-based company with about 2500 employees worldwide. About 10 percent of all these employees are engineers in the R&D department. So, we’re mostly driven by engineers, also our CEO and everyone. It is still private owned, so there is no stock available for the company. And our biggest strength is really the development part of ultra-miniaturized stuff.

We have a wide range of standard products. You, maybe, have seen we have a big catalog that’s been around for years. It has about 500 pages, and there’s a lot of DC and BLDC motors, and gearboxes, and encoders, and controllers inside. The good thing on that one is, if you want to make a fast prototype, we can put these things together and you have very fast prototype running because everything fits together.

I need to admit also if this thing has more than 400 pages now, that’s only 20 percent of our turnover. 80 percent of our turnover is strongly customized or at least modified. We make much more than just only these motors.

Typically, we design, for customers, mechatronical units.

Medical Technology Reliable, Compact, Efficient

I need to say that about 60 percent, in the U.S. it is even higher as about 70 percent of our turnover is medical. So it’s medical devices. It’s typical that you find us in applications like drug pumps, atherectomy devices, surgical robots, in surgical instruments, and on and on in many devices out there.

I think one of the major reasons is the reliability of our components, and the quality of the components that we have. And this is pretty much a leading factor. And, also, the power density that we can generate, and the sizes that we generate on motors, which leads me to the main topic of my speech today, which is the miniaturization of products out there.

Driving factors for miniaturization

I think the major driver, from my experience, is the patient. And everything that we do, that we develop, we should always have him in our focus. Smaller devices, if you talk about ambulatory stuff, so the thing that you wear around with you, like a drug pump, stuff like that. So, these things need to get lighter and smaller. The reason for this is it is much more comfortable.

So, what we see at the moment, the push on the drug delivery devices is the patch pumps, for example. You wear them like something you glue on your arm, and you don’t feel them. They shouldn’t bother you. You should be able to do your normal sports, your swimming, your daily business like you want, and they shouldn’t bother. That’s the whole goal of the story.

But, this means you need to make them extremely small. For the pharmaceutical industry, it means you need to have really high concentration on your drugs because the viscosity of the system is increasing.

Other examples – surgery tools, the insertions or the wounds that you generate or the number of insertions you make should be minimized. We have heard about the cost in hospitals and stuff like that.

So healing is a very big point of all that is minimally invasive. This is the driving factor for getting people to recover faster and getting out of the hospital.

Going there, you need to minimize. We are working on micro robots and miniature robots that are working within the body and doing the surgery, not from the outside anymore. That will be the future, and you need to miniaturize for that.

Other things like the example you see over here – This is a heart support system.

With all of that size – this thing has an outer diameter of six millimeters – you wouldn’t be able to help patients with that one. This is a small pump that supports your heart system. So it’s just a heart support system, but it gives you the opportunity that the heart can heal. Stuff like that is driving the miniaturization. And it’s always about the patient.

Micro ambulatory drug pump

I will use an example, which I will follow through my speech. This is a small-pump system. This is an ambulatory pump. There is a special pump that is named the double-chamber pump. So, you have two nice chambers on that side. There are pistons down there.

While the pump itself is moving, you have a pumping mechanism and the valves that are switched over there. So you have two ways of switching it. This gives you a continuous flow, pretty much, so you don’t have a lot of pulsing in the system while you control the speed of this pump mechanism precisely.

And, of course, this is just a prototype. What is shown here is just showing a little bit of the pump unit because the requirements are very tough on that. The footprint should be extremely small, as small as possible, because it’s ambulatory. The power consumption should be low because, otherwise, you’ll make the batteries big, and you don’t have any advantage out of that. And this unit needs also to be sterilizable. So, it needs to be cleanable after a while.

Some more of the requirements: I think one of the most important points when it comes to designing such units – and this is always the first step in the design process, as far as I can tell from my experience –­ is build up a strong mathematical model. Try to get from the outside requirements that you have from your customer and understand these requirements precisely.

I think this is one of the key things – I can’t explain it often enough to my engineers – really understand the requirements.

There’s a really wonderful speech from Meghan Thorne from Medrobotics. You maybe have heard that. She had been on the MD&M show in Chicago. I think she will be on BIOMED in Boston once more.

It’s really interesting because she was the girl who goes into operation rooms to look in on the surgeons and finds out that 70 percent of all surgeons are doing the operation with socks, no shoes, and she was wondering why.

You need to understand this sort of application, and you need to really write them down. And now the tricky part is, transform these external requirements into internal requirements that you can design from the inside out. To do that, I strongly recommend, build up strong mathematical models. Try to get the requirement and transfer it to an internal function.

Back to my example from the pump. So, you need to understand torque/speeds. I just used here two physical sizes. There are the forces for the pump itself and a little bit of friction for the valves themselves. So, you need to understand how this is applied, what you will really see to understand that, and how the forces and torque on the motor on the slide will look like. Because this gives you the option to understand what are the peak forces and the average forces.

What this is determining later is the size of every drive unit. It doesn’t matter if it is ultrasonic or with an electric motor or something else, you need to understand it.

Also, you should understand the motion exactly, how this thing is moving, because there is a switching point – we talked about that – where the valve is switching. So the question is how precise you need to be at that point.

Outside In => Inside Out

Build up a really, strong mathematical model. This is very simplified here, so evaluate it and try to transfer it. This has a lot of impact later on your design. I use that all the time.

I need to be honest. I worked for 20 years with this sort of mathematical models and increased them over the 20 years. I built them up, and I have a lot of templates, so I’m pretty quick with that.

It gives you really the inside out. If you start to design and change parameters and change your model with it, you always have your requirements in your hand. You always see the impact. You’ll immediately see, “Okay, my efficiency’s going down, my current is going up. This has impact on my electronic side.” For that reason, I think it’s pretty important.

It also helps you later on in the change process, if you do changes. And change is normal, expect that. The customer will change requirements.
I don’t know how many pumps I have designed, from syringe to linear peristaltic, all the way around. I have never had the project where they haven’t changed. We always had changes in the requirements. Always. So, expect that it will happen.

I need to say that because I’m from Europe, we have more the understanding of, “Oh, golly. We get a specification, and then we do the design and off we go.” And that’s not the reality, to be honest.

Technologies – Design from inside out

Design from inside out. If you have the strong, mathematical models finished, then start with a technology assessment. But, as the design engineer, automatically in your brain, you’ve already started designing. So, you have something in your mind – “that’s how it will look. I’m going to put this there.” You know, the mechanical part. Also, the electrical part, it’s the same thing – “how I put the controlling mechanism okay. If I put the encoder on the output, I need to handle the–” All of this is going on. That’s normal.

But why try, then, to first do an assessment on the technologies? Because this has an impact, later on, on your tolerances and sizes. You can’t decrease parts with the tolerance. If you miniaturize something, the part is getting smaller. But you can’t decrease the tolerances in the same percentage. It’s not possible.

I have an example for that, a simple one. Take a look around on technologies that are available. It’s not only the mini motors or micromotors from Maxon, there are more around. For example, take a look at the clock industry, what they use for technologies, for production, down there.

Take a look at how connectors are produced, how you can integrate stuff easily, what is available on that. Define, for yourself, a technology base. I think it’s pretty important.

Then comes the big point – if you have figured all that out, then you start the design, really, from inside out. And I believe, in this technology, there’s no way around.

If you start from the outside and try to get to the inside, this is always going to be a nightmare. Start from inside; get to the outside. Really understand the power dimensions or the power that you need. For example, for the drug parameters, determine the sizes of the magnets, the winding technology that you can use.

Or using the ultrasonic motor, determine the frequency that you need to have and the diameters that are necessary for that. Start from inside to out.

If you have concerns, regarding some parts, of strengths and stuff like that, FEM analyzers is the way to go. Start FEM analyzers. And, if you have electromagnetic circuits here, do simulations down there. Dynamical problems can also appear. Not in this case, to be honest.

So, for example, Also, build up a risk analysis in parallel. Always, on the bottom part, take a part to say, “Okay, I have a technology risk. I have a design risk, whatever it is.” That is typically the input for your design FMEA that you need to do anyway.

Design principals – technology to make it possible

I talked about that already – you can’t size down and expect that you have the same tolerance fields.

So, for example, if you have a shaft with one millimeter or have a shaft with 10 millimeters and have 10 microns on it as the tolerance, which is possible, and now you just shrink them down ¬– and the shaft is looking the same way, by the way – it’s going down to one millimeter. You will see that your tolerance is, unfortunately, getting to 0.1 micrometer. Then that’s not possible anymore.

The dimension is changing, so expect, on small parts, lots of relatively large tolerances that will exist.

Also, production – for example, if you produce a shaft with one millimeter, it’s something different than producing a shaft with 10 millimeters. All this world is changing.

If you have small parts like that, unfortunately, dust is going to be a problem. If you have small gear wheels, they have only the diameter of a millimeter.

At the point of dust, it’s a big animal. It will stop the working of your gearbox. It will stop working because it will be blocked.
So, you have requirements like clean rooms, unfortunately not because of medical, but because of dust. And this is impacting all of your designs. Be aware of that, if you go really small down there.

Prototypes – design from the inside out

Then we’ve heard about a lot of prototypes. Rapid prototyping, very important part. I am the biggest fan of that.

Unfortunately, when it comes to small parts, there’s not so much technology around. The tolerances are not there. So, I need to talk to this guy. We need something that is for 1 mm parts, super precise,that will have only micrometers of tolerances.

Then we would use it immediately, and much more than we do at the moment. We use it, but we always know it’s a little bit of pain that we are working to.
If you build a prototype, I think one important point is to check your mathematical model. Verify that it is working, that it is correct, because this gives you a strong and robust design later on.

Try to separate functions. I think this is also very important. Don’t try to combine things in one part. This is a misunderstanding – trying to integrate functions in one part and thinking that the cost will go down and it will be much easier.

This is where you get your problems. I promise you, from experience, it will be that part. Because if you change or optimize one function on this part, you always impact the other functions. So you can’t optimize that.

So keep one function for one part, if possible. I think you can optimize one function, you can optimize the next function and so on. You can optimize your product by that. If you integrate it and you start working on that part, it has impact on the next one. It is a running wheel, and you never come to an end, if possible. I know that it’s sometimes not possible, but mostly if possible, try it.

Also, sometimes it’s cheaper to have two simple parts and assemble them, instead of having one super-complex part where an injection molding guy loses his hair and gets mad with you all the time when he tries to produce it. Just an example.

Try to test your mathematical model on your prototypes, function by function, to see if they are working, separately. Then, later on, if you have mistakes in your unit, you can easily use those results for analyzing where your problem is coming from. I think this is also pretty important.

And always share that information with your customer. Every result you should share because he also has impact, he gets a better understanding from that, too. And, also the impact on that.

Prototypes – Verification of the requirements

Prototypes testing – whatever is possible, step-by-step verification, it really depends. You need to have good equipment for testing like thermal cycles, like vibrations, like low tests, like lifetime test. There are a lot of things that are going on there. So be aware of that.

Check out what you have, what you can do in house, and what you need to outsource. And don’t save money on the testing. You’ll pay it later.

You know what experience is? It’s the number of mistakes you ever made in your life. I have a lot of experience. And this was one of them.

Miniaturization and costs – Good enough is good enough

Okay. Good enough is good enough. A little bit on costs – target costing, also around in the world, I don’t know how popular this is in the U.S., but in Germany, typically, we build up a BOM – a bill of material. Immediately we have the technologies in there, we try to analyze the cost per part.

We also build up the route. We have every step – the minutes of production – down there. And during the development process, we try to reach all that cost.

So, you hold that at a certain point, and then you follow up with your cost and try to figure out where you are.

It’s not only that. You need to fulfill the requirements regarding some technical issues or quality issues. You also need, at the end of the day, to reach your costs. Because, otherwise, this is not a product you should produce as there is no win-win situation for you and your customer. So this is also very important to take into consideration.

Sometimes if you can’t reach your cost point, you need to go back to the starting point, if necessary, and rethink everything because you can’t sell it into the market because the market price is not there. I think this is very important. So you need to follow up on that one.

I think this is concomitant calculation meant here. We also look a little bit at engineering time. That’s also pretty nice, but it really depends on the projects. If the volume is higher, then engineering time is not a big issue because, typically, they are divided by a lot of parts over years. It depends on what is the company policy out here. On smaller amounts, this is much more critical. You should also follow that one.

Jad Mubaslat: Let’s forget about how many of you have invested in Bitcoin. How many have just heard of Bitcoin or blockchain?

Now, how many of you feel like you understand it? Okay, perfect. Then this presentation is made for you.

So, “how blockchain will change the way you develop medical devices.” It’s a little bit of a clickbaity title. It’s not going to completely revolutionize how you build medical devices, but it is going to revolutionize how that data flows in the background, and how effective your medical devices can be, and how they can take advantage of the data going around.

So I’d like to give a thank you to 10XTS, they helped me get out here. They are a blockchain venture lab building enterprise blockchain products and solutions. So if you’re interested in learning more about blockchain or you want to try and implement blockchain into what you’re doing, check out “10xts.com”

So, who am I? Like I said, I’m Jad Mubaslat. I have a bit of a unique background. I’d like to think that this is the perfect scenario for me to talk about blockchain and also healthcare. My academic background — I have a biomedical engineering degree from Ohio State University, focused on tissue engineering, and I also just recently got my master’s degree in Industrial and Human Factors engineering from Wright State University, where I studied the application of blockchain to the healthcare space, specifically care coordination, but medical devices just as well fit inside of this entire healthcare ecosystem.

I’m also the organizer of the Dayton Bitcoin blockchain and cryptocurrency meetup. And, like Joe mentioned, I founded a Bitcoin exchange back in 2013. We were acquired back in 2016, so I’m just an advisor for them now. But they’re actually still going strong. So, if you do want to dip your toes in the water, buy some Bitcoin, go check out “bitquick.co.”

So I mentioned I was working on a master’s thesis that focused on blockchain and healthcare. If you want to check out the full paper, 9xc.us/10x — Demonstrating the functionality and efficacy of blockchain based systems in healthcare using simulation tools.

So within that paper, you’ll find some more directed readings in the literature review. Some of those actually go in depth of all the different applications that blockchain can have in the biomedical and healthcare space.

And we also have an in-depth review of “how does blockchain Bitcoin work?” and “how can we simulate this in a healthcare system?”

So first, if we want to understand how this technology is going to revolutionize the healthcare industry, finance — even past these two industries. Think about real estate. Multiple industries are going to be affected by this. It’s similar to thinking about the internet didn’t necessarily change how medical devices were made, but the fact that your medical devices can now be connected to the internet changes the way you think about things.

So now hopefully after this presentation, the fact that blockchain exists and how blockchain functions will hopefully get your mind to think about what additional capabilities your medical devices could have.

Bitcoin

So let’s start with Bitcoin, the original blockchain. It was released in 2009 after the financial crisis by a pseudonym, Satoshi Nakamoto. No one really knows who that is. It doesn’t really matter. They released some open source code and a white paper that described it. People just ran with it from there.

So what Bitcoin did — it is a digital currency and a software that, for the first time in history, allows anyone anywhere around the globe to send any amount of money virtually instantly with a low fee and, most importantly, without a third-party intermediary like a bank or PayPal or Visa, someone telling you who you can and can’t send money to. You’re essentially immune to financial censorship in this kind of system.

Bitcoin & blockchain today

And if we look at Bitcoin and blockchain today, Bitcoin has a market cap of about 117 billion dollars. And if we look at the total market cap of all tradable tokens out there, it’s somewhere around 260 billion. Now if we look maybe just a month ago, it was about three times this amount. So, this is not financial advice whatsoever. Don’t take it as such.

We’ve also seen $8.8 billion raised by these initial coin offerings. Companies creating tokens saying that these tokens will one day have value or one day will provide some kind of function in our new product. And we also have major players in finance getting involved. You have futures being traded by the CBOE, CME, so you have even Wall Street involved at this point.

So, how does Bitcoin work at a very high level? Let’s say Bob wants to send .1 bitcoin to Allison. This creates a transaction that we see at the bottom. This transaction will go float in an unconfirmed transaction pool.

So everyone who is running the Bitcoin software, they have a copy of these unconfirmed transactions. These transactions aren’t final, but we’re just trying to broadcast to everyone on a best-effort basis that we’re trying to have this transaction settled and put into the blockchain.

You’ve probably heard about miners. It’s like “what the heck are these miners doing? They have shovels? They’re digging something in the ground?” A better term for miners is think of them as transaction validators.

We have people running specialized computers that are trying to group together transactions that are not confirmed yet and, every 10 minutes, one of those miners will win a lottery-esque system, put together a block of transactions and append it to the Bitcoin blockchain.

So once your transaction is included inside of one of these blocks inside of the Bitcoin blockchain, it is now permanently stored in an immutable distributed ledger.

And these miners are rewarded with Bitcoin for their services. So they’re actually incentivized to validate transactions in a proper way because, otherwise, all that power that they’re dedicating towards the system is going to go towards nothing. If they attack the system and they put bad transactions in the blockchain, their investment is going to be worthless.

Key implications

So some key implications — We’ve created a trustless method to transfer value without a third party. We’ve created an auditable, provable, immutable log of transactions. Each one of those blocks is cryptographically connected to the previous one.

So if we manipulate any content within one block, let’s say a block that was mined in 2013 or something like that, everyone will be able to see through cryptography, basically advanced mathematics, that that modification is invalid.

And third, with these public blockchains like Bitcoin, we have a financial incentive for everyone to behave honestly by rewarding digital tokens to these users and minors. So in the case of Bitcoin, those are Bitcoins. But we also see other cryptocurrencies such as Ethereum that rewards Ether to their users. We’ll talk briefly about some of these other technologies.

So, what is a “blockchain?”

So, at its heart, a blockchain is simply an append-only, cryptographic, hash-linked ledger. And we have two types — we have public blockchains and we have permission blockchains. And I imagine that they’re going to affect the industry in different ways.

Public blockchains, anyone can participate in them. You guys want to go run your own Bitcoin node, run your own Ethereum node, run your own Monero node, feel free to do it. No one is going to tell you that you can or cannot participate in such a system, but the drawback to these systems is there are some privacy concerns.

Anyone can go on the Bitcoin blockchain and see transactions that are being made. In fact, there’s a lot of speculation that the NSA and whatnot has already been able to de-anonymize some significant percentage of users on the Bitcoin network.

We also have scalability issues. Whenever I make a transaction, every single other user on the Bitcoin network is going to have a copy of that transaction in their Bitcoin blockchain. The current Bitcoin blockchain is some 200 gigabytes of data today. So it’s quite large and, like I said, it’s append-only. It’s only going to get bigger.

So then we look at permission blockchains. These are blockchains where the identity of the participants must be known. There is no underlying cryptocurrency incentivizing people to use these.

So there, you have privacy benefits in the sense that only the people that are allowed to use the system can see the transactions happening; scalability, we’re not putting transactions from everyone on this blockchain; and, it’s easier to integrate these with legacy systems. You don’t have to haggle and discuss with the entire Bitcoin community to get your particular function implemented. You’re creating and running your own blockchain.

But the drawback is these private blockchains are not going to grow as quickly as public blockchains. They’re censorship-prone. The people that are working together, maybe it’s six EMR providers working together, there’s a more centralized point of failure. It only takes compromising six entities in that scenario versus with the Bitcoin network, you’ve got some thousands of users that are running copies of this ledger. So it’s much more difficult to attack a public blockchain than a private blockchain.

So in terms of the implications to you guys, my prediction is that these permission blockchains are going to be easier to integrate with the industry incumbents. Good luck trying to convince ePIC to adopt this new public blockchain system. They might be more likely to adopt their own private blockchain.

But on the flip side, if we start seeing these healthcare blockchains that are public, that anyone can participate in, that anyone can buy their tokens, the same way that Bitcoin attempted to disrupt finance from the ground up — it’s a product meant for consumers — that’s how you might see these public healthcare blockchains disrupting the healthcare space.

So the private blockchains, they will be implemented from the top down, whereas the public blockchains, I think in the end, are going to dominate as they will be disrupting from the bottom up. Maybe there’s going to be a lot of consumers using these blockchains, and the data will simply be so valuable that healthcare incumbents will have to integrate that data into their systems.

Here is a quick way to think, “Do I even need a blockchain for what I’m doing?”

• So do you need a database? If you don’t need a database, you certainly don’t need a blockchain.
• Do you need many people to write to it? We need multiple participants. So if you have multiple participants, all right, we’re on the right track.
• Do those people trust each other? If they don’t, then great. We’re still on the way to needing a blockchain. If they all trust each other, it says, “You don’t need a blockchain.” The fact is, actually, you might be able to use a private blockchain.
• If there’s one person in common that they trust, well then, you might as well just use that centralized database. You don’t really need a blockchain in that case, either.

But if you answered yes, yes, no, and no, you need a blockchain.

Care coordination and major themes

So my studies at the university, we focused on care coordination. And within care coordination, we have multiple stakeholders. We’ve got providers. We’ve got hospitals, and there’s interdependence among each other. They need to have access to each other’s roles and resources.

And the same thing with medical devices, if we have a consumer that has, let’s say, a Fitbit, it might be useful to have that data being fed into this ecosystem, so that information can be actionable immediately.

Blockchain and healthcare

And when we look at blockchain healthcare, it might be bigger than you think. We’re looking at various use cases. We even see medical devices and IoT security down there, Spiritus and NeuroMesh. Those are startups working on blockchain with medical devices today.

And actually, if we look at Patientory, Meta Block, Medicalchain and MediShares, these are four blockchain healthcare projects that currently have tradable tokens. And in February, the total value of those four tokens was trading at $400 million.

Now realistically, it’s probably somewhere down in like 250 million as many of you block Bitcoin holders have been feeling the pain recently.

Blockchain features and capabilities

So let’s talk about the features and capabilities that a blockchain has.

The technical features:

• we have an immutable ledger. All that information when it’s put in the blockchain, we can’t change it. It’s cryptographically secure.
• we have consensus among the participants as to the state of that blockchain; what data do we perceive to be valid? We have a set of rules that we use to determine that.
• smart contracts. Now, these aren’t present in Bitcoin, but when you look at Ethereum, another blockchain platform, smart contracts are basically functions that can automatically execute depending on data that happens on a blockchain. So let’s say you want to automatically issue some kind of report, if you receive data from a patient that they’ve hit some kind of threshold, some kind of goal for their health, you could have a smart contract automatically trigger some kind of reporting or payments could automatically be issued.
• we’re looking at multi-signature. This is the idea that we can have addresses controlled by multiple parties.
• cryptography — that’s involved in the underlying infrastructure for all blockchain-based systems.
• we also have asset digitization. So, for instance, the ownership of a certain medical device could actually be put on a blockchain and be represented as a token. So if someone holds that particular fraction of a token, fraction of a Bitcoin, that could also mean that they own such a medical device; and,
• these networks are naturally peer-to-peer.

And these lead to certain operational capabilities:

• we’re now able to transfer value. In the case of Bitcoin, it’s just money. But if we look at Ethereum or these other blockchain-based systems like hyperledger, we’re able to actually transfer data from one party to the other
• we also have security
• we have auditability. Anyone can go look at this blockchain and see the history of the blockchain; and,
• we have decentralization of trust, in the sense even if we’re looking at a private blockchain as opposed to relying on one person to manage all the records — Just look at Equifax. That might not be the best idea — we’re now depending on six. That’s better than one. Or in the case of a public blockchain, it could be an infinite number of participants.

And it’s important to note that having an immutable ledger and consensus are the key features that lead to these operational capabilities.

Healthcare Requirements

And so within my work for my thesis, we also tried to identify the healthcare requirements in general. And we see that we have cost reduction, fraud prevention, identity management, record availability. We want HIPAA compliance; we want universality of records, auditability, reconciliation of records, interoperability, and a way to encourage patient engagement.

So we see these operational capabilities, some of them contribute to enabling different healthcare requirements. We see that auditability enables eight out of the ten healthcare requirements out there. So just the ability to audit the records of a certain patient or the data that a certain medical device is outputting, that’s going to help you achieve many of the requirements that these healthcare systems have and that these medical devices have.

Potential design

To give you a mental model about how could such a system work – are you going to have all this medical data sitting on the blockchain itself? Well, no, that wouldn’t be efficient.

So what we’re going to do is this — for example, if you see looking at this MDChain blockchain, what it’s doing is it’s storing pointers to the actual local database records. So you’re still using the classical databases that we already have. But now, we’re actually able to link them together using the blockchain.

So you think of it as the mortar that’s connecting these different bricks, these different databases together. And so hospitals, patients, payers, local provider offices would all be feeding data into their databases, and they would have record locators on the blockchain to those databases.

What can you do?

So what can you all do?

Stay aware of blockchain developments. Coindesk.com is a great place to check out general blockchain news;

Consider how blockchain may apply to your use case specifically; and,

hire developers that are familiar with blockchain.

So in conclusion, we see that blockchains have the potential to disrupt more than just finance alone. Healthcare systems and the medical devices within them can be greatly improved by implementing these blockchain solutions.

If you want to send me an email — jadmubasat@gmail.com — and if you want to check out my details — jadmubaslat.com

Feel free to reach out to me. Happy to talk about blockchain, Bitcoin, healthcare, whatever. You name it. Now happy to answer any questions.

Joe Hage: That was fascinating. Would you say that it’s almost certain that blockchain, as I’ve heard, is the new internet — just as pervasive. It was nothing, and now you can’t be without it? Is that the future of blockchain?

Jad Mubaslat: I do believe that, yes. It might be five, maybe even up to 10 years before we actually interact with blockchain applications on an everyday basis. In the same way that, back in the 90s, who knew that we were going to be using the internet every single day for every single thing? Who knew that it would lead to this entire phenomena of social networking?

So I think, in the same way, we’re going to see similar disruptions from the blockchain industry.

Joe Hage: Do you think the average user or average manufacturer is going to know how to use the blockchain or will it be in the background and we don’t even know that it’s happening?

Jad Mubaslat: The end goal is for the consumers. You’re not going to have any idea that you’re using the blockchain.

The same way you don’t really care how Facebook’s backend works, but at the same time –

Joe Hage: I do now.

Jad Mubaslat: Yes, I guess so [laughs]. Right. But in the same sense, we want to abstract blockchain away from the user and just provide them with the benefits.

Joe Hage: From where we are to having something on the market, is there one that’s just so intuitive for medical devices that it’s almost certainly going to lead the way and others will take that as the permission to believe that, “Yes, we really have to change the way we’re doing business?”

Jad Mubaslat: I think it’s difficult to predict exactly what’s going to be the killer use case. In the same way during the dot-com bubble, we had things like pets.com that were popping up. I think, in the same sense, where we’re not so sure what’s going to be the killer application here.

But, for instance, maybe just looking at provider data or having your medical device actually have access to information from other medical devices in a live manner. Maybe it’s using a public blockchain and these users are now incentivized to actually participate in the system because they’re rewarded with tokens. So there’s a lot of different ways that could go.

Joe Hage: Thank you very much. Yes, that was great. Are you a consultant? Can they hire you for your time and advice?

Jad Mubaslat: So I’m not officially doing consulting, but I did just graduate. I’m going to start working for a Bitcoin exchange coming here soon. But like I said, happy to answer any questions. And if there are more involved projects, we can talk.

Joe Hage: Any friend of 10x is a friend of mine. Jad, thank you so much.

Nersi Nazari, 10x for Design and Manufacturing keynote speaker and CEO of VitalConnect, bet the fate of his company on the widespread adoption of continuous patient monitoring.

Sounds like a reasonable bet to me.

In his 40-minute keynote at 10x for Design and Manufacturing, Nersi said patients and consumers are accepting the technology and clinical evidence supports its efficacy. After all, the continuous monitoring of vital signs is not new. In critical care, life depends on it.

So how to make continuous monitoring portable, inexpensive, and effective?

Mr. Nazari answers that question and many more in this enlightening talk. Watch below and click through for the slides and transcript.

Nersi Nazari: There’s basically, to go through quickly, it has to be novel and non-obvious. And non-obvious is some ordinary people skilled in the art. Imagine a fresh biomedical engineering graduate with a library card, but not inventive.

Would it be obvious that all of the elements that make up that patent are obvious to him?

What I’d like to also present tonight is that besides the challenges of the healthcare system, there are three other things that are at play which makes 2018 a very exciting year for this sort of technology.
• One is acceptance by patients and consumers.
• Second, the technology is here.
• But the third, and the most important thing that is unique to 2018, is the clinical evidence.

We’re now starting to have clinical evidence and as we speak, I know a number of a prestigious journals that are viewing this type of data for publication. And leading institutions are starting to use these products in their hospitals and healthcare systems.

We all know that nobody wants to be the first to use new technology.

But, as a chief medical officer reminds me, nobody wants to be the last. So, the trend is there, the clinical evidence is here, and with all those other underpinnings of the cost of healthcare, the technology and also the need that is seen by the patient community, I think this is going to be an exciting year for all of us.

So, I’m going to start with the first of the concepts that I talked about is that really the acceptance is there by everyone to be continuously connected. So, as we know, socially, everybody is connected and if you have a teenager, you know they’re more than connected – they’re always connected. On finances, banking, on purchasing stocks, and all of those type of activities, payments, again, everybody’s continuously connected.

And then, even parenting, you know, having virtual boundaries for your children, looking after them and so forth. So, this concept is becoming widely used and accepted. And I could also extend to alerts for remote control of your house and lights and all of those types of conveniences. Then moving to the temperature of your house, energy-saving, that sort of activities, plus monitoring your house by utility companies it’s all there. Nobody seems to be upset about these anymore. And at the same time, they are enjoying the convenience and the cost savings.

In the healthcare market, also the wellness, the unregulated part, the health and wellness part has also enjoyed and a number of acceptances in the market.

So, for example in fitness, how many steps you took, your exercise and calorie burn, a whole bunch of applications in that area.

On the consumption of food, and as you know, there are some that even try to estimate the number of calories you’re consuming by taking a picture of what you’re eating, so again, more health and wellness applications.

And if you live in California, and maybe on the east coast as well, there are also applications for your pets. So, for example, you want to make sure your dog took the appropriate number of steps and walked the right amount of time, and if you’re not the one who’s walking the dog, you want to make sure the person who did, walks a certain number of miles or steps for your dog.

So, that’s sort of a starting with the fact that everybody wants to this sort of monitoring. Again, moving it to the healthcare side, statistics are also revealing on both on the wearable and for the medical apps. And again, that’s an area that you see almost a tripling in a matter of just a few years.

So, we are accepting these types of monitoring and moving it to healthcare, first, to their wellness area where we’ve seen rapid growth. So, I want to now expand out to the medical side, which is what we’re concerned with in this audience.

What do we do right now?

The continuous monitoring of vital signs has been around for a few decades. And we know if anybody’s in ICU, essentially their life depends on it. So, it has been done. But obviously that is a type of technology that you cannot extend because of costs. And, not just cost, the complexity of device. It has to be operated by very skilled technicians and it has to be interpreted by doctors.

Then, as far as the monitoring is concerned, when a patient is a released to the general ward, again, these types of equipment are too expensive to move.

So, what do we do? We do a spot check. But when we do a spot check a good number of times 96-97 percent of the time, the patient is not monitored.

So, if there is a technology that can do that, obviously, the hospitals will look at it favorably because they know if somebody was sick, they want to do a hundred percent of the time, if somebody was really sick.

As you know, when patients get discharged, they essentially get a phone call and that’s about as much as most people get. They ask you to come for a check-up in a week. So, this is what we are dealing with right now. But again, if the technology is ICU grade but is inexpensive, convenient to use, obviously for a good portion of patients, we could have extended to general ward and, also, to home use after discharge. And obviously, from the price point of view, the first is super expensive, takes a lot of time for nurses to visit in their rooms, and the phone calls are very inexpensive but also very ineffective.

How do we get this thing outside the ICU?

Let me show some statistics really quick. You’re all familiar with that? We have a lot of hospitals. The average stay is about five days and staying in a hospital is like a super expensive hotel.

So, these are the stats that we’re familiar with and, obviously, we want to do something about them. But, I pass through these quickly to get to the part that I think is a more exciting part. Again, a lot of expenses in readmissions and also in Medicare cost, which has ramification in public policy, taxes that need to pay for those and so forth.

The economic part, as I said, has been well known and I want to spend more time on why, this year, all of those have been around. The clinical evidence that helps us move along, too, solves some of these problems.

Essentially, what we’re trying to do is to keep the patients out of the hospital.

I will show you some data on a leading hospital system that has gone beyond monitoring their patients after the ICU or the surgical procedure. They’re trying to actually admit some of the patients, right off the bat, to their homes. It has very, very promising results, for that institution.

Obviously, we want to keep the patients healthy at home. How do we know they’re healthy if we do not take measurements? Obviously, the continuous monitoring is helpful for that.

The patient deterioration is the cause of all these readmissions, and possibly worse. If we could know that the patient is deteriorating, we could do what is possible to avoid it. Obviously, we want to have a more preventive healthcare system.

Finally, under clerical burden, once the data is continuous and electronic, you can always find the interface to put it in your EMR or EHR, so, that’s also an additional advantage.

So, let’s see how we can do to that. Again, I go through these very quickly, you know, the costs are extremely high, population is aging, and continuous monitoring is the solution that we’re going to deploy to look after these costly situations.

Now, what are the statistics? Has the continuous monitoring been shown to be useful? Before we had the technologies that are a cost effective, people have done quite a bit of analysis on the patients, and how they could be helped. For example, the number of people who have preventable adverse events annually, in just the United States, is over 400,000.

So obviously, if these patients were monitored, since these are preventable adverse events, they could have been helped and this is not just costs, obviously saving lives.

Other statistics, their Medicare expenses, 50 percent are for readmits that are preventable. And again, to help that, we want to be monitoring patients, so we can prevent it.

Right now, patients that have cardiac situations are usually identified, on average, 15 minutes before. So, if you have systems that can predict that, it would be, obviously, a huge, not only cost-saving, but more importantly, life-saving. I will show some clinical data later that this can be done.

Again, in the hospital, as much as it’s a burden for the nurses, an inconvenience for their patients, at the same time, 96 percent of the time, there is no one in the room to take a look at the patient. So, a lot of bad things can happen.

So, obviously, early warning signs can be extremely useful for a number of these conditions and I could go on and on. I just want us to give this as a motivation that this sort of monitoring is extremely useful for both saving lives and expenses.

Another condition that is extremely sensitive to monitoring is sepsis. Sepsis is huge in terms of the damage that it does to the patients, to the costs and to the healthcare system. And this is one of those conditions that early detection is extremely important. Even every hour is important.

If we could have these technologies in hospitals so they can administer the right medicine and treatment in just a few hours, it can make a big difference. And on a regular spot check, that could be every four, six or eight hours depending on the hospital system and the protocol. This makes a huge difference.

So, when you talk to hospitals, if you say you have a solution that can help in any way with Sepsis, you get immediate attention. One, that this early detection is extremely sensitive.

How can you monitor the two – there are three, really, things to look at – the subtle changes in heart rate and breathing rate is an indication of an infection, which sepsis really is.

So, if you have every heartbeat and every breath looked at very carefully and with accuracy, you can make those detections. The other measurement is temperature, which is also useful.

So, this deterioration or preventable, why haven’t changed? And again, that goes to the thesis, that, obviously, we need the technology and the clinical every day. The things that we have up to now and some of those clinical studies that I showed you, they were done with bulky, expensive devices, they were done for research purposes and this was not a solution-oriented study.

But what is the condition that needs to be done? Now, that’s where we need to develop medical grade devices that we’ve been able to do now, and it’s not just my company. There are a number of companies that are developing extremely accurate, yet small and affordable devices.

But, it has been hard and part of that is not just a medical device development. You have to have the infrastructure, the Bluetooth, low energy, Internet, also ability to do the cloud computing, analytics and so forth, that I have touched on.

Let me also go back to show another aspect of these devices that is often overlooked. The intensive care unit, which is accurate, it’s not just cost of this that we’re trying to avoid when we go to the general ward, but also inconvenient and uncomfortable.

Now, that inconvenience and discomfort also cause patients to rest less. And again, there has been a lot of studies that if a patient rests better, they recover faster.

Later on, when I show you the clinical study for patients that are admitted at home, one of the leading reasons that they recovered faster was because they could rest. There were not all these noises, the machines, the lights and so forth. So that’s a very important aspect. And that’s why I wanted to show this in a picture for you.

The other part in the hospitals, obviously, you want to be visited by technicians so you’re not out there. But the other thing that some of you, I’m sure know, from visiting loved ones, in hospitals, that it seems like they’re often coming at the wrong time, when somebody is studying, sleeping, or resting. And again, going back to my previous thesis that, when you rest, you recover faster.

And then the other point is that with the devices that are out there, the telemetry devices and so forth, not only are they bulky, you can look at the data there, so it’s been very useful for the nurses and technicians to warn doctors or nurses to help the patient, but at the same time that data is almost temporary. You can look at it in the screen, but they have not been well documented into a EHR or EMR system that’s almost disconnected. Most of these devices have like 96 hours of memory, not well connected to internet or other systems for post-analysis.

Why can we make these changes now?

And again, obviously, the technology is the solution and the ecosystem that now we’re enjoying. And as I started, the culture has evolved, and people do not mind to being monitored.

And, if fact, what we have seen is people have legitimate concerns about privacy. But, when you talk to the patient population, they’re still concerned about their privacy. But, a lot more than that, they’re concerned about getting their data to the doctors as soon as possible. So, they do not deteriorate or if help needs to be sent, it is sent immediately.

How has this technology evolved?

We have four components I touched on. A one is obviously cloud analytics. We can get this data and not run one computer on it, but as many as you essentially need, if you’re on, as you know, in IBM Watson or Amazon AWS, essentially you can get as much a computing system as you need as you pay for it. And no one wants to sort of short-change you when you are analyzing healthcare data.

Connectivity, very important, one of the things that we are trying to do, and other people, that this is not just in hospital, so when the patient is discharged, this continuum of care continues. So obviously, good cellular connections, LTE and whatnot.

The third one, one of the things that we make in our company, we make these biosensors. I’m holding one and I’d be glad to show you later on. They’re very small, very flexible, but at the same time they’re as accurate as devices that are the size of a table, for measuring your breathing rate, heart rate, ECG, and so forth in the hospital. These devices enjoy the same standard of FDA and regulatory clearances and obviously can be relied on to make medical determinations.

Last but not least, obviously, artificial intelligence and more analyzing of these data, which is very, very important for some of the conditions that I talk about in a few minutes, such as heart failure, and a very, very subtle changes that need to be calculated and looked at.

How has Culture Evolved?

Again, under culture, I go a little faster. We all have busy lifestyles, but at the same time we’re very happy to be using mobile devices. But, the change that we really are seeing now, this last year in 2018, the hospital is not viewed as the best place to be. A lot of people in healthcare, a lot of us knew that the hospital, in a way, is a dangerous place. That other than proximity to doctors and great caregivers, which is great, when you’re sick, there is also opportunity to catch other diseases. You don’t rest well, you don’t sleep well and so forth.

And that is becoming more widely known. And in fact, patients that a clinical study, I will talk to you about later on, in the random study, most of the people that wanted to be on the home side, rather than the hospital side for the clinical study have meaningful comparison.

Continuous Monitoring – One Patient Story

Let me just talk a little bit of a clinical studies that we did.

And again, this is showing one of the things that is only can be done by continuous monitoring. When we developed

our products, we wanted to make sure people can use these things easily at home, that you don’t need a doctor or a nurse to help you out. So, we did a study of two months, so we have 50-60 volunteers and they took these home, a showered with them, you know, did whatever they usually do.

And, we collected all that data for an FDA submission.

But one of the interesting things that happened was that one of the patients actually had a heart rhythm issue. If you see the bottom graph, some missing heart rate pulses. And if you do get the data, that happens very, very infrequently.

So, obviously, our chief medical officer sent that patient to a cardiologist, and it turned out that she just needed a simple a pacemaker to resolve her condition. Again, coming back to the case that you really need continuous monitoring to come up with some of these diagnoses.

Continuous Monitoring – HF Patients

But, let me talk a little bit more detail about one of the other clinical studies that was done with our device with a third party, analytics company called physIQ in Chicago. They did a very large study at the VA. The paper was published, was based only on 100 patients, but that’s, obviously, still statistically significant.

This paper was published in the American College of Cardiology and showing very, very promising results for the heart failure patients. This is the sort of study that I was talking about that they’re coming out with and they going to be the catalyst for wide acceptance of these devices.

For this study, they again, had to measure every beat, every day to come up with these subtle changes. And, what they essentially found out is that you could predict heart failure condition, that the patient is in the wrong trajectory about six days in advance.

And for those of you who are practicing medicine or know more about heart failure, when it’s six days in advance, sometimes it’s just a change of diet, and moving patient, walking more, or things of that nature, diet and so forth that can help you prevent this type of things. You don’t need to be admitted to the hospital.

So, this was a very, very big a study for both VA and also for our partner because it had indisputable evidence that if you can have accurate measurements, but it has to be continuous, and over time, you can make this sort of a prediction.

Why Continuous Monitoring?

Again, I’ll go through this quickly because I think I talked about it enough, you have to have the continuous time to tell the whole story. And also, the fact that you have the continuous monitoring of your vital signs in presence of activity that is also very, very important in terms of the analytics. So, now it is viable to have these types of solutions.

State-of-the-Art Hospitals

Let me move to hospitals. I have two cases are of using these sorts of devices in hospitals. The first case, let me just show you the chart. This is probably better. Essentially, the data goes from the biosensor to a relay, which we make something that is very dedicated for hospital use. And the data goes through the nurse but also goes to the cloud for aggregating this data, analyzing it, and a command center, so somebody out the hospital or team can watch the entire hospital systems. So, that’s sort of the architecture.

Continuous Care Systems

But let me just jump to the, and this is sort of how it looks, the upper right picture is looking at the single patient, and the bottom right is when you’re looking at a whole bunch of patients, and it has all these analytics to see which patient to look at, which one has an alert, and that sort of stuff. All of this has to be FDA cleared, go to quality system, and so on and so forth. But let me just rush this through in interest of time, to talk about their results.

A patient experience, obviously, for the cardiac patients is so different with the halter monitor is something that we have here for a sleep analysis. Again, the same type of thing, once you have all this data, you can do analytics to do Sleep Analysis, as good as, Capnography and the picture on the left.

Again, the one of the two studies that I wanted to emphasize more, this was on at Brigham & Women’s Hospital in Boston. Dr. Levine, has a video on YouTube if you want to look at it, is a professor of medicine at Harvard Medical School, but also is the leader in this hospital-to-home type of program that they’re doing.

In this case, this is the published result, there’s a much bigger study with hundreds of patients that is going to be published later, but this is what I can share with you. And, again, on this, when they did the biosensor and randomly admitted some patients to home for mid-acuity, they saw enormous saving in costs, but more than that, they also saw fewer readmission for the patients who went home, they recovered faster, and they’re all, obviously, did not ever catch some other infection or anything like that.

They were more active. They were happier. Some payers, the measure of satisfaction of payer has influence on how much the hospital gets paid. So that’s obviously something that was appreciated by them. And since we measure activity, we could also see that they are more often… and so forth.

Mercy Virtual

So, let me go to another hospital system that we had the privilege to work with, and that’s the Mercy Hospital system in St Louis. They are so committed to this sort of technology, they built that building on the upper right, which is a Mercy Virtual. That’s a hospital with no patients in it. But, they have ability to look at thousands of patients with the technology that they have, and we have this small part of giving them the biosensors, to look at their entire hospital, thousands of people that are in the hospitals and monitor them continuously and they have shown better care at a lower cost. And I let their officers give, maybe, the presentation, at the next opportunity.

Hospitals as the “Hub & Spoke”

One other thing that we see is that the heart hospitals are also becoming very expensive themselves to build. Cost of a hospital bed is becoming one to one and a half million dollars to build. So, what do you want to do is that you want to have the hospital as the sort of the center of the care, but, push the care outside. And that’s what they’ve done in Boston. Their activities similar to that in California by leading teaching hospitals. So, that way we can essentially have hospitals that kind of move out and be able to give a patient care outside the hospital. And again, this sort of technology is required to get the data from the patient, but analytics experts, doctors and so forth or in the hospital. Which brings us back to those numbers that I’d talked about.

Tomorrow’s Standard of Care

This sort of technology, not only saved the patients, maybe the number of hospitals over time goes down, and the length of stay, and the significant cost associated with that. Same thing for the admissions for the patients in Medicare and so on and so forth. So, this technology really has the capability, now that we have clear medical evidence by leading institutions and very carefully published results, that I’m very optimistic that this gets picked up by more and more hospitals for 2018.

Continuous Connectivity

We are sort of a year for the tipping point on this technology, more than anything else, it would save lives, improve patient experience. When we were looking for volunteers in hospitals there were usually more people who wanted to be on the biosensor than the ones who did not want to be monitored. Because as you know, you have to have two groups to do the clinical comparison.

Clinicians also very happy. This is not the type of technology they look at as they’re replacing doctors or nurses, they say, essentially, helping doctors and nurses to do what they like to do, which is givingcare to patients rather than measuring the pulses or looking at their ECG or things of that nature.

So, we essentially think that with this sort of technology, not only you can do that in hospitals, but you can monitor patients anytime, anywhere which leads to post discharge and, obviously, extending the hospitals to the neighboring communities. So, thank you very much and thank you for your attention.

Joe Hage: Nersi, I’m really, really pleased that you’re here with us today. As I said in my introduction, I can’t think of anything more contemporary and on trend in medical devices right now then this combination of IOT in miniature and immediate feedback. A|s I understand it, there is no standard yet. You have a number of competitors, if I’m not mistaken, how do you compare and are we going to look at a Sony versus Beta situation where one of the formulations is going to win versus the other? Is there a risk there for someone to bet on you, for example, versus another standard?

Nersi Nazari: There’s not as much of a standard point, between one and two things, because everybody, really, is going to provide an end-to-end solution. Like we provide the cloud, the biosensor, the connectivity, and so forth. And other people are probably going to be doing the same. So, this is gonna be like Medtronic versus Boston Si versus St. Jude. You know, it’s who has better overall technology. We are a long way from a day that you buy the biosensor from this company and the cloud from the other company and so forth. And on top of that, the regulatory regime, right now, it is that you have to submit the entire system to get approval.

Joe Hage: So, is it rare that a hospital will be your customer, but rather you have a strategic that you work with and you helped them bundle their product offering, is that more likely the way it works for your business?

Nersi Nazari: Yes, yes, that is one of the business models.

Joe Hage: I know there are a couple of questions in the audience.

Walt Maclay: Hi, I’m Walt Maclay. I’ve got an interest in wearable devices. I’m curious what challenges you had in developing the wearable device and what was the main challenge in how long it took to develop?

Nersi Nazari: Thank you for the question. It took us five years to develop this device and one of the challenges that… one of the speakers this afternoon, our friends at 3M, adhesive is always a challenge to get it exactly right. But, accuracy is probably the most important challenge. These devices are small. And we had also a speaker about the dangers of miniaturization. The tolerances have to be higher, the algorithms have to have more accuracy. But, I think those were the two, being accurate and yet small and adhesion and all of those issues that you have with the device that is on or in your chest.

Hitesh Mehta: Hi, I am Hitesh Mehta. Great talk. I was just wondering, you have the system for the hospital? So, could I buy for my parents and monitor them and see… “Oh, you live 6,000 miles away so I can know what’s going on and say, OK, you got to go to the doctor because something is not right and help them out. Is that a possibility?”

Nersi Nazari: Technologically, it’s possible. When you have a patient wearing one of these. If fact, we’ve had cases that the consulting expert is somebody that is at Cambridge University, but as far as putting medical devices outside the country and so forth, there are regulatory and other restrictions.

Del Lawson: It’s a great talk. And just a quick question. The data seems to be potentially overwhelming, if you have to keep all the data for liability or other reasons. And, how much human interaction is required? Or can the algorithms spot the anomalies so that the nurse or someone doesn’t have to look at all the data?

Nersi Nazari: Thank you. Very, very good question. What we have done is that we really looked at these things from the current standard of care, the telemetry machines. So, we have simple thresholdings for various measurements which the nurse or the doctor orders that. Some of those are very subtle things, like that heart failure prediction and so forth. Those were done essentially by experts. And those were done in clinical study. They have not been done on live patients yet because we need to get regulatory approval for prediction more than the algorithms.

Joe Hage: Nersi, this kind of dovetails on Hitesh’s question. It sounds as though almost everything you’re focusing on now, at least from a strategic, all the things you could be working on, prospective is the hospital level of monitoring. And there are so many consumer level risks and body suits and other things. Do you think that sensor technology, the kind that you specialize in, we’ll find a consumer application or is that strategically off-plan for you?

Nersi Nazari: You know, it could, one day. But, right now, we almost even speak different languages. Because, you know, you’re measuring the number of steps. I measured the number of steps, like a versus some of the consumer products. But the standard quality system is so different. We have to worry about a patient that is sick and is walking like this, which means a lot more testing and so forth. Whereas, for a pedometer, that is for a healthy people, they want to know if they do the 10,000 steps or not. So, even the simple things like number of steps, the approach is so different that the emphasis on accuracy is so important. And, I also find it that if somebody is perfectly healthy, like we wear it for our own studying and so forth, we don’t find this much useful, to be honest with you on a perfectly good engineer. We just gathered the data for analysis, but they’d rather use the Fitbit for the jogging in the morning anyways.