Bill Hunter Presents Canary Medical at LSI Europe '23

Transcription

Bill Hunter  0:05  
What we're trying to do is basically connect the world's major medical devices. Right now what we have in the US is this. It's the stem that goes into the best selling knee in the world. It's the Persona name made by Zimmer Biomet, but just to show you how fast things are progressing, this is what's coming next. And so what Zimmer will be able to do is simply put voids in all of their different implants. And this will provide all the connection that is required. So in that tiny little device is a battery, and a transmitter and all the sensors, you would need to follow an orthopedic patient. So the screening that we're doing is screening for post operative complications, and following our patients through the post operative journey. So the device goes in, believe it or not, those batteries are good enough to last for 20 years. So we can collect data from the patient's knee without anything to wear a charge for, for 20 years, there's a base station that sits in the patient's bedroom, much like a pacemaker, and it relays the data every night to the cloud. The next morning, the patient and the doctor are looking at all that patient's data from the previous day. So what exactly are we collecting? It's on from seven in the morning till 10 o'clock at night, every single day. Most of the time, it's in low resolution mode. So it's about 20 observations per second. The human eye is 20 observations per second. So that's things like walking speed, Cadence stride length distance traveled. So is my patient on the couch? Or are they moving around? Are they active? Then three times a day? It goes to 800 observations per second. So sub visual, and that's telling me is my implant loose? Is it vibrating? Is it in position? Is it osteo Integrated? You know, is it starting to fail. And we do that three times a day, we've actually collected now over 1 billion data points on post operative patients. And we've done a full millennium of 1000 years of patient monitoring. So we're really starting to understand how it works. So we use 3d gyroscopes, 3d accelerometers, and a step counter because orthopedics is about movement. So what is it was it looked like it? Well, it looks like this as you're walking. Obviously, this is a wearable version, not the implant, but you're moving through 3d space, that's what the gyroscopes and accelerometers are doing. And you're able to see that limb moving. And you can turn that into a range of motion. So you can tell the doc you know precisely how they're walking. If I put a knee brace on you so that you can't fully extend your knee you lose, say 20 degrees of extension, you get a totally different tracing, afib doesn't look like normal sinus rhythm. That's how you know what it is. It looks entirely different. Yeah, different tracing, we turn that into a range of motion. And we tell the doc not just that my patient took 1000 steps. But were they limping or walking normally? And if they were limping, why were they limping? Well, they're limping, because they've lost extension. The physiotherapist everybody knows what to do with that and how to manage it. Once you have millions of these, and as I said, you know, we have a few billion of them now, you're able to do more elaborate things with it, right? So the first thing you're able to do is tell what's normal, and what's abnormal. So, you know, when we first put these in, we knew what step counts were and range of motion where but we had no idea how that was relative to what was going on, in the patient itself. But once we got further along, we could say, okay, the 95th percentile is at the top, the fifth percentile is at the bottom. And now with a simple look, I can look and see the patient on the left, their activity is average above average, their range of motion is well above average, they're recovering perfectly well, the patient on the right actually ended up having a manipulation having to have scar tissue broken up in the knee. And you can see right from the beginning, they're not walking very much, they're very inactive. And the range of motion is really, really poor. So our Doc's are now starting to use this information to identify the patients that are lagging, bring them in and get treatment to them before they have a more significant problem. The next step, I always use the analogy is like ECG. So these are actually the motion waves that happen while the the leg is moving. And you can see we have 3d gyroscope, 3d accelerometer, so we have six channels. ECG obviously is an electrical wave, there's 12 channels, but we do exactly the same thing. First, we can tell normal from abnormal, which is what I just showed you. So we have an idea of which of our patients are lagging, but then we can also start to match the problem to the pattern. Right? So we use ECG to diagnose infection, myocarditis, ischemia, all kinds of things. Why? Because an abnormal heart beats differently than normal heart does. And you can see that in the electrical pattern change. Well, if you have a hot red knee or you have a DVT or you have something else going on in your leg, you walk differently than you would if you're walking normally. And with enough data points, we can use machine learning to match those up up. So we've already been able to find contracture, which has scar tissue build up, we can already kind of find loosening, which is when the implant is starting to fail, we can see a vibration pattern that's not there otherwise. And soon, we hope to be able to match these different patterns to infection, and all the major complications that come with postoperative treatment. We get paid two different ways we have reimbursement for the implant itself, we receive breakthrough status for the knee, the hip and the shoulder. I think it's the first time that's happened in orthopedics to get three different breakthroughs. So that allowed us to get both Ntap and soon will apply for TPT. Ntap is for hospitalized patients. TPT is for patients and ASCs patients who are done same day. And we also have built the device to be able to do billing directly for remote patient monitoring. And so what's really kind of interesting is how far we've come on the data side in the last year and a half. So, you know, as I said, very first day, what we had to do is figure out what normal was what abnormal was, I think we can do that very, very well now. And now what we can do is put the entire practice onto one dashboard. So our biggest user probably has done four or 500 of these right now. So most of those patients, 80% of those patients are going to be completely normal, but 20% of those patients are going to be lagging behind. Well, that would be an awful lot of work to screen manually, or have everybody come in for a physical exam, or do something like that. Now, we can do it much more quickly. The Doc can set their own parameters as to what their concern levels are for range of motion or activity levels. With a single click, it can go through all 400 patients and show the, you know 2030 patients who are lagging behind that actually needed to be seen. And the next step of this is that, you know something I don't think anybody is able to do right now is have the doc look at their phone on a Monday morning and see the four or five patients that are the highest risk from you know, their entire cohort. So, you know, we've gone from normal to being able to sort and filter to be able to give the care team alerts as to how things are going. I don't think there's any other knee product out there that can do anything remotely like that. And then those can then be further billed. So the software can literally take it from the knee to the billing platform. So the clinician can bill an extra $100 per month for remote patient monitoring. A lot of our Doc's are doing three 400 Knees a year $1,000 per patient and monitoring follow up is meaningful to them. So that's a big part of what they want to do. So that's really the story. The knee is the flagship, they the hip and the shoulder are coming shortly, we have a small implant that goes into spinal cages that will do similar things. Our first cardiovascular programs will go into clinic by the end of the year. But the goal is basically to take these implants and put them implant within an implant to connect the major medical devices out there, and then build the entire data platform to support them. We are doing a series D but a $50 million round right now. It's a classic, last private round. This is all for the scale and launch. Now that we have all the data products in place, you know, Zimmer and ourselves will be going full force on a big product launch around the Persona IQ knee, and the round is to scale and grow. So if you're interested, we're around. And if you're a device company that could benefit from this type of technology, let me know. Thank you very much