This Week in Startups - Next Unicorns: Making surgeons bionic via computer vision & AI with Proprio’s Gabriel Jones | E1790

Episode Date: August 9, 2023

This Week in Startups is brought to you by… Superside. Design and creative are crucial for growth. Tech companies like Shopify, Amazon, and Meta have found the perfect solution: Superside. Get $2000 off with Superside's Startup Accelerator package superside.com/TWIST Vanta. Compliance and security shouldn't be a deal-breaker for startups to win new business. Vanta makes it easy for companies to get a SOC 2 report fast. TWiST listeners can get $1,000 off for a limited time at vanta.com/twist LinkedIn Marketing. To redeem a $100 LinkedIn ad credit and launch your first campaign, go to LinkedIn.com/nextunicorn. * Today’s show: Proprio CEO Gabriel Jones joins Jason to discuss the struggles surgeons face in the operating room today (23:05), the solutions Proprio’s Paradigm system provides (27:14), the future of surgery (37:03), and much more! * Time stamps: (0:00) Proprio CEO Gabriel Jones joins Jason (2:09) Proprio’s Light Field-Enabled Surgical technology (7:03) Gabriel demos the Proprio Paradigm robotic computer vision system (10:26) Superside - Go to https://superside.com/twist to get $2000 off with Superside's Startup Accelerator package (11:58) Generational shifts in medicine (18:03) The ultimate impact of this technology (21:58) Vanta - Get $1000 off your SOC 2 at https://vanta.com/twist (23:05) The data Proprio operates on and the struggles surgeons face today (27:14) Bench-top simulation (32:05) Use of AI and robotics in surgery today (35:36) LinkedIn Marketing - Get a $100 LinkedIn ad credit at https://linkedin.com/nextunicorn (37:03) The choice to utilize Proprio’s technology for spine surgery first (39:03) Reducing the time needed to perform surgeries (44:17) Academia vs. Venture, and the importance of “proof points” for investors (46:44) The FDA approval process * Check out Proprio: https://www.propriovision.com/ Follow Gabriel: https://twitter.com/aGabrielJones * Read LAUNCH Fund 4 Deal Memo: https://www.launch.co/four Apply for Funding: https://www.launch.co/apply Buy ANGEL: https://www.angelthebook.com Great recent interviews: Steve Huffman, Brian Chesky, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland, PrayingForExits, Jenny Lefcourt Check out Jason’s suite of newsletters: https://substack.com/@calacanis * Follow Jason: Twitter: https://twitter.com/jason Instagram: https://www.instagram.com/jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis * Follow TWiST: Substack: https://twistartups.substack.com Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin * Subscribe to the Founder University Podcast: https://www.founder.university/podcast

The data is actually the most important piece here because you get very detailed information and measurements about the performance of the surgery from the plan and the diagnosis, from the imaging before the surgery was ever done, through the entire surgery and through the outcome. So this is the first time in history that anybody, any company has been able to invent and bring to market a technology that could actually connect all that longitudinal proprietary data that says, what was the intent? You know, we know the plan, so we know your surgical intent. What were you trying to accomplish here? This weekend startups is brought to you by SuperSide. Design and creative are crucial for growth. Tech companies like Shopify, Amazon, and Meta have found the perfect solution. SuperSide.

Get $2,000 off with SuperSide's startup accelerator package at superside.com slash twist. Vanta. Compliance and security shouldn't be at. deal breaker for startups to win new business. Vanta makes it easy for companies to get a SOC2 report fast. Twist listeners can get $1,000 off for a limited time at vanta.com slash twist and LinkedIn marketing. To redeem a free $100 LinkedIn ad credit and launch your first campaign, go to LinkedIn.com slash next unicorn. All right, everybody, you've heard all about computer vision, cameras, AI, all of this stuff has been coming together to enable founders to create new

innovative projects. One of the projects that we've been watching, robotics, surgery, is really compelling. And today, we're going to see how real-time computer vision is working in the OR, the operating room. So with me today is Gabriel Jones. He's from Proprio, am I pronouncing correctly? Proproo, yep. Proprio, P-R-O-P-R-I-O. And you can go see their website, PropioVision.com.

Tell me, Gabriel, what is Proprio? And what are you building? Thanks, Jason. Yeah, hoping to blow your mind here with some real-time product demos. So we are just outside of the Proprio headquarters

operating room facility. Mok-O-R, if you want to think about it that way. I think it's on the door behind me the precision lab, as we refer to it, where we do real-time surgical simulations. And when I say simulation, it means there are cadavers and samples like that being used in computer vision surgery live behind me right now as we sit here. So I wanted to give you a better version of the product demos that everybody else comes on your show shows you.

I'm not just going to share a Zoom screen. There's a body in the lab being operated on by our team right now. And this is not just a demo for the sake of a demo. developing applications, including already FDA cleared applications, or performing surgeries like spine surgery, in a totally different way compared to how it was done in the past. And happy to dive into more detail there. But the simple analogy that I think is really easy to communicate with your vast audience is up until very recently all of surgery was operating in a map quest kind of a context.

What does that mean? We expected surgeons to basically take an x-ray. or a CT or an MRI, that type of imaging, effectively either print it out or have it on a screen, store this wealth of knowledge in their brain from 20, 30 plus years of experience, try to pull all that together computationally within one human brain and then apply it to take care of the patient. Oftentimes, quite literally printing out an x-ray and taking it into the OR. You and I are close to the same age. So we remember when you went from Rand McNally to MapQuest, that was amazing, right?

I have a custom map for the entire world. You know, I just have to print it out. Type in, you know, the origin point and the destination, take it in the car with me and it was amazing, right? Turn by turn. Yeah. Except for if anything changed. If anything changed at all, whether it was, you know, a construction project that wasn't on MapQuest or an accident that occurred or I wanted a sandwich. There was no real-time aspect to that information or that data.

or how it was presented to us. Now, fast forward, your good buddy, Elon and others have taught us how to navigate in real time with GPS and Starlink and all that good stuff. So now we have real time updating for driving across the city or the country. And thankfully, plenty of charging stations. Well, we forgot to do that for surgeons, which is frankly, unforgivable, given that they take care of you and me and our children and our grandparents. And so now is the time.

We'll probably talk about why now. all these technologies coming together, as you alluded to, can actually provide real-time GPS, real-time 3D volumetric intelligence for a surgeon to perform at their very best every single time, really in pursuit of perfection of medicine. I think that's the exciting moment we're in right now. And for people who are not watching,

just go to YouTube and type in this week in startups, and you'll go find this episode under the videos tab. But behind you, literally, right behind Gabriel is a surgeon working on a cadaver. Yeah, so first of all, I want to thank all organ donors out there. They make things like this possible. I'm an organ donor. It's on my driver's license.

So with a lot of sort of humbleness and respect, we and other companies developing both drugs and medical devices and software for these kinds of applications are able to acquire. Don't ask me how I get them, Jay. Jason, but bodies show up here. You don't want to know the details. And fortunately, we're able to develop applications that can perform in cadavers. And then there's a whole FDA clearance process to get that into the operating room to work

with live humans and solve problems for them. But what you're seeing is that testing and development occurring behind us. And for those listening on the podcast and not seeing, you have members of the proprio development team in mock operating room right behind us. me using the paradigm system, which is the name of our core platform made by proprio to perform surgeries. And we're going to talk more about that. But here we have a spine surgery, very common.

Think about like a lumbar fusion. You've probably had friends who have had a procedure like that. We're on the very other end of the spectrum, something like a scoliosis correction procedure. There are seven million Americans who have that affliction. And these are in the same sort of family of orthopedic surgeries that have. millions of times a year. And again, they're done with essentially that x-ray that we were talking about, that

MapQuest type of information. Just to be clear how this works, you will take a 3D model of a person's body, say, their spine. That would come from an MRI, I take it, or an x-ray or some combination of those, and build a model of my specific body as opposed to somebody else's, because everybody's body would be unique and whatever surgery is going on is unique. And then you will create a way for the surgeon to see this. Not as a surgeon wear goggles, do they wear an Apple headset?

How do they actually see this manifestation of, say, the spine? And maybe we could do a little product demo here that we could sports cast people through. Yeah, let's do it. And I love the sports casting analogy because it connects to a core principle, which is we've instrumented the athlete and the astronaut, right? There's people follow. LeBron James has a whole team of people following him. around. I bet he can't take, you know, he can't go to the bathroom without somebody

sampling that and saying, you know, how he's doing digestively. And it makes sense, right? And he's probably spending millions of dollars a year as are his sponsors to perform at the absolute peak that he can for as long as possible. There is a literal 3D computer modeling system for watching people shoot three-pointers. And the reason the NBA has gotten so much better collectively. Even the worst three-point shooters are better than the average 10, 15 years ago because of that 3D modeling system that is in the gyms that shows people there are, their stands, they're footing, you know, the release, etc. So computer vision to help people hit three-pointers. And here we have computer vision to help people do perfect surgeries or more

perfect surgeries. That's well said. If you didn't have a day job, I'd be recruiting you, Jason. So what are we seeing here? I see like some sort of an overhead. is this a projector? Is this a computer screen? What is this overhead device here that seems to be? Yeah, you're seeing the paradigm robotic computer vision system, which has an array, completely proprietary array of sensors. Think of this as like the LiDAR type systems that are on Teslas and such.

Yep. And basically we've designed and engineered a system that can dynamically reposition throughout the operating room, a set of sensors. Think of them like the satellites flying a bunch of sensors. Think of them like the satellites flying above, right? And we're mapping the mountains of the body dynamically, right? And we can use other types of imaging. You alluded to MRI and CT.

Basically, our core capability is this real-time 3D volumetric imaging. You're familiar with Lytrae from back in the days and the ability to basically capture an entire scene dynamically live in 3D. And then you can do magical things with that once you have that core kind of VR video, if you want to think about it that way. But it's live, and that's our core innovation. So we invented the system to capture that and to render it live and to give a surgeon or a user the ability to interact with it live.

So there's this overhead sensor array. Looks like the size. It looks like a pizza box, basically. And that has a bunch of sensors. It's flying over my body. I'm laying across an operating room table. And it is in real time looking at, if you've opened me up, you know, my spine, whatever it is, and it's going to make a 3D model,

in real time of what the surgeon is seeing. So it's an extra set of eyes for the surgeon, essentially. Super high precision X-ray vision without the X-rays. Think about it that way. All right. If you're listening to this podcast, you care about innovation and one sector that really needed a shake-up was design. I'm always talking about world-class design and how that is the difference between getting

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Go to superside.com slash twist. That's superside.com slash twist for $2,000 off. So generational shift in medicine, let's just go back in history. So what we're looking at here is the last 25, 30 years of progress in what's called surgical navigation, right? That's essentially what we're describing. GPS has been this map quest. So we're seeing x-rays that were used to essentially pin an x-ray to the body and then rely on the surgeon to take that x-ray, do all that 3D calculation, and then perform a surgery somewhat magically, you know, doing a lot of that in their brain. And what you're saying is a spine surgery that's being navigated in that way.

Really simple, an elegant solution 30 years ago, but we haven't really made a lot of progress since then. And so this is a product from a company like Metronic or Stryker or Johnson Johnson. And that was the whole universe of innovation. So what we're seeing here is actually that real-time light field rendering that Proprio does. Here you see real data, actually, this is light field data from multiple cameras and sensors capturing depth information, RGB information like from your cell phone, infrared, non-visible spectrum. It's all baked into the same algorithms that.

then present that information to the surgeon. Here you can see the system operating at the edge of these robots moving around in the operating room. It feels like something out of Star Trek because it's on the path to that. And here what we're showing is the ability to look into a very small incision. This would be a minimally invasive surgery. And what Jason's seeing is essentially a CAD rendering, 3D model that's the blue, of inside the body.

And all we are seeing, all proprio is seeing, is about an area the size of your thumbnail. I assume you have pretty normal and healthy thumbnails. So about 5mm square. And once we've got that, we've locked onto it. And we have telemetry for the anatomy to perform the surgery. That's wild. So you have this 3D model that's been built already of that spine, that piece of the spine there.

Then when they cut the person open, they're laying on their stomach, this array of sensors is reading it in real time and then attaching that view to the 3D model view that's already been taken ahead of time. And then by putting those two things together in real time, the surgeon that has a more accurate view of the spine in this case to make whatever incisions or manipulations are necessary to help that person. Yeah. Accurate and live. That's the big distinction. So what's hard to do about this.

this computational work to do it live. Back to the why now question, right? Our good friends, Jensen and their team over at Nvidia have helped to accelerate a lot of this work. We're going to get into AI and really practical AI applications, I think in this conversation too.

But the Nvidia GPUs you're saying have made it easier to create these real-time models. You have that massive GPU power. Forget about AI. This is just making the renderings at high fidelity in real-time being driven by

GPUs, which were put into computers to play video games. So video games, creating better surgery is, if you wanted to find the lineage of this, if people were demanding to play Call of Duty at higher and higher resolutions

and frame rates, this technology would have not advanced to hear. This would be a very expensive rig to play Call of Duty, but you could do it. Okay, so let's keep going here if I can show you this. So what we're showing is the ability

to, you had, mentioned AR VR VR. Yes, absolutely. Once you've done the hard computational work up front, and what we're seeing is, is the spinal anatomy aligned to the real physical world with the digital, and we have a surgeon with a headset on, which is a headset developed by Propro, to look inside the anatomy as he's placing what's called a pedical screw. So this is an implant used in a spinal fusion hundreds of thousands of times per year. About 1.6 million of these are done per year in the U.S., very, very common. But the problem is, if he's not using proprio, this surgeon can't see inside the anatomy

and sort of predict the potential impact of what he's about to do. And that's the true magical, revealing kind of the seeing-around corners component of what proprio does. This surgeon is going to be able to avoid putting that screw in your spinal column, which is a big deal. So when they go to put this screw in, he's going to be able to. be watching it in AR or VR? Is this going to be augmented and he's looking at your actual body and it's helping him align the screw? Or is it all done in VR? It can be done always. You know,

a surgeon who's maybe 20 or 25 years into their career might not want to wear a headset no matter how good the Apple headset, you know, becomes over time. For example, our bet at Proprio is that the data is actually the most important component and how you choose to consume it is up to you. Got it. So some folks might want, some surgeons, old school surgeons, they've got a feel for this, they're going to look at the monitor, and they're going to see it. Maybe some new surgeons coming up, they might like to put on a headset eventually and see the model in real time and then see through it with AR. So they're kind of, it's a perfect augmented reality application when you think about it. Um, obviously I'm biased, but yes, I agree with you. Got it. So how close is all this to, you know, working in the field? You literally have a cadaver. Thank you to the people who are donating.

We don't want to make light of that in any way. It's a pretty serious business here. And thank God people do donate, you know, their human vessels after they're gone to help technology like this. Because this is going to greatly reduce errors. And I guess lower costs eventually of different surgeries or make, more surgeons in the world? What do you think the ultimate impact of this is? Does it make people faster and better?

Or does it make, you know, being a surgeon, you know, a career that maybe more people can, more accessible to people? Ideally, all of that. In my background, I worked with the Gates Foundation and Bill Gates, and we were trying to solve very big problems over time, you know, 25 years out in health care globally. And so we kind of have that motivation as an organization to, extend access to care. Today, we're constrained by the ability to make new surgeons that are excellent and skilled.

And J-KAL, I don't know if you're a, you know, a Scotch fan, but I hear you and Chamath like to drink some good wine. Yeah. But similarly to Scotch or whiskey, it takes 25 years to make a good bottle. Yeah. But you can't, if you and I decided to double our consumption tomorrow, the production process to make more great Scotch whiskey is going to take. 25 years to get that product to us. It's a good analogy for thinking about my co-founder, Dr.

Browd, who's a world-renowned pediatric brain surgeon who's on the screen right now that we're seeing. He's in his early 50s, and it took probably 25 years of training from pre-med until now where he is world-class. Ah, so time to world-class could drop precipitously. Dramatically, yeah. Because training is going to be more available. And so I assume with this system, you're going to be able to replay surgeries, and I'm assuming that's how surgeons, I think, learn is they replace surgeries. Ideally, but you'd be surprised how little data is actually available for them to actually kind of beam back in to what Dr. Browd was seeing in that surgery and see it right out of his

eyes as many times as they want. So the 10,000 hours is very difficult to acquire today. So right now, if I wanted to become a brain surgeon, a literal brain surgeon, it's not like there's some corpus of here are a bunch of. of surgeries we can see deeply into the brain stem whatever spine wherever this work is occurring and so the only way to do it is to to stand to the right of somebody or be watching from one of those OR you know rooms where they have the I guess stadium seating as it seems like seems like a crazy way to try to learn how to do surgery yeah you would think they would just have

videos so when if you're an auto mechanic or you my mom repaired her own dishwasher who is like literally in Brooklyn, I was talking to my mom. She repaired a dishwasher by watching YouTube videos made for the melee person. And she's like, yeah, just watched the video and I bought the part online and I did it. It's kind of the equivalent here. You're going to have training videos that are so good that you would have people, time to amazing surgeon could be cut in half or cut by 80%. Yeah.

And this is the why this technology is particularly powerful from a training perspective is light field gives us the ability to essentially, create as many arbitrary camera positions as you want in the volume, in the space. So that means I can see right out of Dr. Brown's eyes. I can see what another doctor is seeing live in that procedure, and I can see it from anywhere in the world. So from a training perspective, yeah. So let me just double click on that for a second. If I was a surgeon, if there was a rare surgery occurring, brain surgery is rare, I think, you could have, and this, doctor, who's a legendary doctor, was going to do this brain surgery one day, you could have

a hundred brain surgeons from around the world getting to see their perspective and how they handled this. And everybody levels up from this very rare case and this very rare instance of getting to watch the pilot, as it were, navigate, landing a plane in an emergency type situation. That is wild to think about. Yep. If you're a SaaS or Services company that stores customer data in the cloud, then you need to be, a sock two compliant. You knew that from a third party. And you need that third party to close big deals.

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That's 10 hundies. Get $1,000 off at vanta.com slash twist. That's vanta.com slash twist for $1,000 off your sock, too. And let me go even further, Jason. So we capture about 250 gig of data per hour of surgery per system running out there. So that's on a compressed basis. So the real number is quite a bit bigger than that. Again, thanks to our friends from Nvidia and Intel for helping crunch through all those

data. But the data is actually the most important piece here because you get very detailed information and measurements about the performance of the surgery from the plan and the diagnosis, from the imaging before the surgery was ever done, through the entire surgery and through the outcome. So this is the first time in history that anybody, any company has been able to invent and bring to market a technology that could actually connect all that longitudinal proprietary data that says, what was the intent?

We know the plan, so we know your surgical intent. What were you trying to accomplish here? And I'll show you a very specific example right now, actually. So here's what we're looking at is scoliosis in an adolescent girl. Oh, terrible. This is in the public sphere, so there's no PHI that we need to. Yep. And this is what we're trying to accomplish in the surgery.

So folks at home who don't have the video on, you're seeing a what's called a deformity in spine. So this is a young girl whose spine is curved quite dramatically. It's impacting the rib cage and the shoulder blade and just leading to a lot of of discomfort. We don't know why the industry and academia does not know why the medical community does not know why the scoliosis of this variety impacts young girls at 10 times the frequency of young boys. Wow. And literally this poor child's or adolescent spine is an S when it should be straight, I guess. When looking at it from this perspective, from the back perspective, obviously. There's a healthy curve to a spine, but that's not this. This

is looking at it from the back, it looks like it's an S as opposed to a straight spine. But you've touched on something very important. The S is a healthy shape for a spine. From the side. Yes. But it can be contorted and twisted in 3D, which it makes for very difficult corrective surgery. And so what we're looking at here is actually a scoliosis surgery in parts, a couple

snapshots that we've taken. And we're showing a very open surgery with a curved spine that is unhealthily curved. And the way the surgery is done today is literally printed out images with target angles on them that are either brought up on a screen or on a literal piece of paper. So there's your MapQuest analogy. And the surgeon is going to do their best to try to figure out and orient themselves in 3D relative to a bunch of pieces of moving anatomy. And it's just an incredible math problem that's very hard for even the most brilliant surgeons to solve effectively. So just so I can recap here for people watching, you have this. fine, you've got 12 or so vertebrae, it looks like, if I'm using the proper terminology here,

that need to be realigned. And they're, instead of being curved looking like a tree that's leaning into the sun, we got to get this tree to go straight. To get it to go straight, they print out each of these vertebrae, as you said, like printing out a map, printing out your map quest, as opposed to using GPS in your dashboard. and they have to make their best estimate guest and how to align that spine. That is an imperfect,

you know, despite being noble and, you know, people doing it accurately, let's face it, they're not winging it, but there's a little bit of a freestyle going on here where they have to make, I guess, their best estimate on how to realign this spine, correct? That's right. And their only other real tool is intraoperative imaging.

So hitting the patient and the end up, entire staff with a whole bunch of radiation. Right? So taking like x-rays during this live? Yes. As opposed to, the better way, which is what? Is removing the need for intraoperative radiation entirely. So real-time light field-based navigation requires no radiation whatsoever.

Not only that, but I'll show you a little demo here. So what I'm showing, Jason, is a demo of a spine on a table here. This is called a bench top simulator. And in this case, we've placed a lot of screws into the spine, which is representative of the surgery. Then they're using a titanium cobalt rod to force the spine into a different shape. And what we're showing here is just live geometric calculation of each independent part of the anatomy moving. And we can actually just calculate that geometry live and updated at a moment's notice for the surgeon. And here we're backing out of that.

We're undoing what we just did in the procedure to show that it's all captured live. And what's magical about this, Jason, is this is the biggest predictor of the outcome of the surgery, both clinically and economically. This number predicts the outcome of the surgery. Amazing. So now you've got this perfect precision GPS, as we're using the analogy here. So the chances of making a mistake, the chances of successful surgery, proper outcome is going to be dramatically increased. And the number of surgeons who will eventually be able to do this surgery would not be able to. limited. We have a surgeon shortage, correct? That's right. About 25,000 in the U.S.

physician shortage, and it's growing as you and I age and we need more surgeries. The average Americans are going to need between seven and nine surgeries in their lifetime. The longer we live, the more we're going to have. But we're not making surgeons fast enough. And so this is really targeted at making every surgeon as effective as they can possibly be. And just to put a little bit of a finer point on this, the IMAX of the IMAX print of Dune, 371 gigabits. That's a two and a half hour film. About 150 gigs an hour.

You're doing 250 gigabits a gigabytes an hour. On a compressed basis, yeah. On a compressed basis. So, I mean, this is more than an IMAX film that you're recording, which you got to think when you have all this data and then you start matching it

to outcomes, the learning is going to go up dramatically as to maybe what we could do better in the next surgery. Absolutely, Jason. And then let me just challenge you to go even further than that. Okay.

Because my mind is trying to conceive of what happens when you actually have the surgery recorded at that fidelity level. What can you do with that? So we get everything from the surgery. So go back to Elon's master plan, part one and two, right? Let's make a car. Let's make it really fast. And then let's work our way down the stack.

So everybody has one. Okay. Now we need a satellite and a charging station. We've got to put all those pieces together. So effectively, that's what we're doing here, is we have invented the sort of tip of the spear, surgical navigation platform, and it must be great. It must be the best. And that earns us the right to be in the operating room capturing all these data.

And of course, we can drive deep learning models and we can train AIs with the best surgeons to perform better and better and better over time. That's very exciting. And that would be enough of a cause to build a company. It's very profitable enterprise, et cetera. But I don't think that's enough for proprio and that's not what I am here. I'm here to drive the company towards a future that is very data driven and where the entire industry has to react. And what I mean by that is the whole medical device industry is very focused on selling expensive capital equipment.

So think about a robot that performs a surgery or an MRI machine that costs $2 million. Or they're very focused on selling you a screw that goes in somebody's back. And that screw costs $1,200, $1,200 a piece, and they make it for $2. bucks. It's the most lucrative razor razor blades model maybe in the world, right? To break that model and reduce the cost of care while increasing the quality of care, we have to invent things like Proprio, the Parodon, take it into the operating room and perform and improve all these surgeries, right? But where you can break the business model is say, well, now I know what it takes to perform the surgery really well. I know who does well in what

circumstances. I know what products, both hardware and software, can be used in that surgery to improve it. So now you have more than one customer. You're not just going to a hospital whose finances might be, you know, challenging and saying, you've got to write me a $2 million check, and maybe the most innovative thing is a capital as a service model. Now you're saying for everybody else who benefits from that surgery being performed at something approaching perfection. and I can see the gears turning, you're going, well, what about when do the insurers pay these guys? Right? When does the revenue cycle management company that goes and collects the bills for the hospital start wanting access to this data?

Yeah. When does the metronic, the implant maker go, well, these guys can make my implant more effective and tell me how effective it was. Yeah. I mean, that's amazing when you think about it. And then how many of these surgeries do you need in order to feed it? into an AI and say, how do we do this better? And it's probably somewhere between 50 and 100 surgeries. I'm guessing the AI can start to have enough data to meaningfully give feedback. There's nothing like that going on in the world right now. Nobody's feeding an AI model these surgeries and saying,

how can we make this surgery go better? Or does that exist? I think there's some great work going on with like taking endoscope data, which is really, you know, video camera data of low fidelity and trying to teach models how to recognize a pall up and differentiate cancerous tissue and non-cancerous tissue. There's some wonderful work in those areas. And intuitive surgical has a lot of data from their systems, of course. No one has gone in and mapped everything that's happening in the most important areas of the body and the anatomy and the surgery end to end and capture it to everything. And I think that's where it's probably the most exciting area is, yeah, we can build models

that can confirm things that we already suspected. but I think that the messy kind of belly of the beast, if you want to go Joseph Campbell with this, is what don't we know that we don't know? Yep. And what models can we build that will drive down the cost of care, right? We're creating 10, 20, 100 opportunities to monetize the data from a surgery. I think that's where it's most exciting and that's what we're pretty fired up about here. I guess then the question becomes robotic surgery. and at some point

replacing humans in this process and that is I guess been scary or the holy grail depending on how you look at it eventually remote surgeries are correct me if I'm wrong

already occurring so a surgeon can do a remote surgery across the country with robotics is that currently the state of the art and is that actually occurring or do they just get on planes and do it live?

Yeah so the first answer is yes it's possible. Latency issues have been the sort of delay in that being adopted widespread from a technical standpoint. But you and I are human beings and we, you know, we would prefer our physician to be on site. Yeah. It was also a human being in the room with us. Even if everything goes perfectly.

It's just, it's much more comforting to have that hopefully world-class surgeon on site with you in the same room. And let's say if it was a pediatric surgery, right? If it was a child involved, then I'm the parent. Yeah, of course. I'm not sure I'm comfortable having the entire thing done today. Unless you were a parent in a frontier market, previously known as the third world, but some market where the surgery is not even available,

or there's not a doctor there capable of doing it, you might say, well, this remote doctor and a local crew to be there in case of a problem, maybe that's a tradeoff that you would want to make if you were in a frontier market. But I guess you could also fly out. That's the path that we're headed down for sure. Eventually, you pop on a headset, you've got hundreds of thousands of surgeries and the intelligence from that all beamable in, maybe via Starlink or something. And that intelligence is with you and onboard everywhere you go. Today, there's too many pieces that need to work to make that happen.

But if we wanted that future to be reality, we would go collect all the data from millions of surgeries to train the AI to be able to provide that guidance anytime, anywhere. And that's the path we're on. When you're selling to B2B buyers, you really want to get your pitch in front of the decision maker, the person who gets to sign the check. Because these upper level execs, they're the ones who make the purchasing decision. Everybody can have an opinion on the team. Of course, it's 2023. But there's always somebody where the buck stops. And that buck stops on their desk and doesn't get into your bank account.

These high level folks are hard to find. They're hard to target on social media platforms. but LinkedIn is the social network for business and they have 930 million members ready to do business with you and that includes the 180 million senior level decision makers plus don't tell anybody there's also 10 million C level executives there that's a ton purchasing power LinkedIn ads is built specifically for B2B marketers no other platform in the world can offer these eyeballs and you can target them obviously by their location the size of their organization they're vertical and their title when you think about business I want you to just think about LinkedIn.

LinkedIn equals business. Business equals LinkedIn. It's not simple folks. When you present them with an opportunity, they will, of course, be in the mindset to receive that because they're not posting pictures of their food for mentally on vacation. Make B2B marketing everything it can be and get a $100 credit towards your next campaign by going to LinkedIn.com slash next unicorn to claim your credit.

That's LinkedIn.com slash next unicorn. Terms and conditions apply because LinkedIn is so generous to that this week in startup's audience. Are you focused on one surgery, one type of surgery now in terms of perfecting this? And is that spinal surgeries? Is that where you can do the most good? Yeah. So spine is very interesting.

It's a great starting point. It's a very large business. It's $30 billion a year in the U.S. and reimbursement alone. So not counting the capital purchases or implants or any of that side of the equation. It's just reimbursements from Medicare, Medicaid, insurers is $30 billion a year and growing as the population ages, as we were discussing. So it's a good landing point. The spine is also very complex, and there are a lot of unsolved problems.

And so we chose that for various reasons. Also, my co-founder is a brain and spine surgeon, as we discussed earlier of some are now. So we knew those problems really, really well. And the market rewards you for solving those big problems. So it's a good place to start. you follow the spine up, of course, it goes to the cranium. So brain surgeries, cranial surgeries make sense. Similar set of problems.

Believe it or not, Jason, when you open the cranium and do a craniotomy, the brain is actually under pressure and in a bag called the Dura. And so when you open that up, the brain actually moves around quite a bit. Yeah. So this real-time imaging, real-time navigation, knowing where the anatomy is and what it is in 3D space live, is actually. unsolved in the cranial space too. And you start going through, you know, the stuff we do as entrepreneurs, right? You do that segmentation and you go, okay, well, does knee surgery have the same problem? It turns out in knee surgery, they have to put a pin, kind of like a QR code little marker

in the lower leg and the upper leg above the knee and lock the knee into place. Why? Because they can't track it in 3D life. So does that sound familiar to what we were just discussing in spine? Yeah. Well, knee is $23 billion a year in the U.S. alone. Wow. So the amount of time it will take to do these surgeries should go down dramatically.

What's the average time for spinal surgery? And then where do you think this reduces it in the coming years in terms of time under the knife? The faster ones are, you know, an hour and a half to two hours. That would be like a two-level spinal fusion that happens hundreds of thousands of times per year in the U.S. And then the other end would be a six-hour scoliosis reconstruction, like we were just going through. So six hours is not uncommon. Now, if you added a tumor to that, that's even more complexity. And in fact, I happen to have one for you right here.

Look at that. So this is a 3D reconstruction, a printed anatomy. And what you see, what we're looking at here is about 10 levels of a human spine reconstructed from a CTNMR scan, fused together and then print it at super high fidelity. So this is probably six-way. Do people do that before our surgery, print out somebody's 3D print out somebody's spine-like? They do. And isn't it crazy that this would actually be your pre-operative plan?

Wow. You would print this out and very skilled surgeons we know will take in a literally, I'm not kidding, Jason, a Ziploc bag because it's got to remain sterile into the operating room and hold it above the body. Wow. So they can visualize the anatomy subsurface while they're working and making a lot of changes to the anatomy and they're looking back and forth between this and they'll have somebody holding it for them in the OR.

Oh, wow. Isn't that crazy? And what we're talking about here, what you're holding up for the people listening is essentially a 3D printed model of somebody's spine with a big sponge of a pink material, which I assume is the tumor that's attached to it. That's got to be cut out without causing damage to the person. And what you can't see, but I can see here, because I have the benefit of it right in front of me,

is that it's actually inside the spinal column, too. Got it. So you got to get in there between each of those. Yeah. And take out the, wow, that's wild. So back to the original question, is it, we know that the fidelity is going to be increased, so the chance of success go up.

But does it meaningfully change the amount of time? Because it does seem like the longer you're under, in a surgery, am I correct that the increased danger goes up? Yeah. That's exactly right. So there's a number of different dangers. We anticipate shortening surgeries from 30 to 80 minutes on average, depending upon the complexity with our system.

And you can just imagine, let me give you a simple comparison. If you're going to roll in a CT scanner, which is like a giant donut. In fact, there's one in the room behind me. You can kind of see over my shoulder there. That's a million dollar scanner. And if you roll it into the operating room, it's about 20 to 25 minutes to use it once.

And that'll give a surgeon a sense of where they are in progress in the surgery. But that's 25 minutes of delay at $200 an hour minimum. So quickly you're spending $5,000, $6, $8,000 just to get a snapshot of where the anatomy is. And that is radiation and cost. Exactly. And time. So all of those things together, you could save 25% and then less radiation and less cost. Exactly. And you'd be able to achieve something like this much faster and safer. So this is, what I'm showing Jason here is the after of the before tumors that I showed him before. And here, they've removed several levels of the vertebra. Actually, four vertebra are gone.

And what they've brought in is a substrate to strengthen and support the entire spine. And you see a healthy curvature here, right? That's called lordosis and kifosis. Think of it as convexity and concavity. And the level of structural support that has been brought in is just mind-blowing. It's amazing. But when you actually have that tumor and they have to take out the vertebrae, they basically build an architecture around your spine to make up for the fact that the vertebrae

have been removed, that they're not being replaced with something? Yep. And this person needs to stand upright, right? And gravity is unforgiving. So physics doesn't quit. You have to be able to go walk out into the world. And they will if this surgery is done well. The other number to take away from this is what percentage of the time,

are they able to actually achieve that correction of the spine within their targeted range? And it's about 35% of the time. Huh. And so you are now FDA approved to do this. And so when does this go from being science fiction to reality? Well, as you can see behind me, it's happening now. We're happening on live patients.

Yep. How close is that? was achieved in April of this year, which is a major milestone. We will likely be in live surgeries again at the University of Washington doing First in Human, which is what's called kind of in the industry

within the next few weeks, Jason. Wow. That's amazing. How many years did it take you to get to here in terms of research and investment? I know you can relate. Seven years in the making. Overnight success, seven years in the making. So seven years to get this, you know,

two patients, and the venture community tends to have a 10-year window. And so this is one of the great conundrums of our time. You could do this inside of a university, which is a 30 or 40-year process of grants. It's basically your entire career. And then if you look at the venture community, we have a 10-year window. And so I know that my friend Matt Aco is an investor from VCVC. Absolutely. How does the venture community embrace a,

a technology like this knowing it's going to take you seven, eight years to start ringing the cash register. And that's when the end of the venture engagement and they need to start liquidating and giving returns to their LPs. So tell us about the conundrum of academia versus venture and where you stand on that spectrum, because it seems like this is a really hard needle to thread. Yeah, exactly. And I went back and watched your interview with Matt in 2019.

By the way, you were good then. I'm not just blowing smoke. You've been working on this, man. You're really good at this. Well, you get your 10,000 hours in like a surgeon. You can become a surgeon as a world's greatest moderator. That's right. That's right.

But it's true for venture as well. And I think what our friends at DCBC have done well is they are great at deep tech investment. And if I recall, when Matt laid out the framework for you, he talked about we're not investing in companies that are making a case that there's a new physics that used to be invented. this is not paying a bunch of PhDs to go do it, you know, deep research to see if it could ever work. Right. And so there is a sweet spot where, you know, we do real-time light field rendering. And once we had gotten a demonstration of that working well, it was a beautiful demonstration. And it could actually be run on a laptop and with an Oculus DK2.

And so you need to see that kind of a proof point. And that's the time at which investors will come in. then we need our friends who are angel investors and our micro VC investors and all those folks, high net worth individuals to lean into these kind of technologies and bridge the gap to an investor like DCVC or Lux, all of our good friends across the valley who support these kind of things. Yeah. And it's really needs to be more of a 15 year window, I think, which is what Steve Jervitson's future ventures, they just told everybody, we're going to do 15 years.

they told LPs. Tell me about the FDA approval process. You know, we, there's a lot of criticism of our government here in the United States and we're dysfunctional, yada, yada, takes too long. When you look at the FDA, you know, having to live under approvals, etc., does it feel like we are high functioning in terms of our approval process and getting through this? Or does it feel like it needs to be improved? I'm trying to be generous here because I know you have to work with them.

Yeah, I appreciate that. I was going to make a comment about that. First of all, it's a highly regulated environment for a reason. This is, you know. A lot of stake. It's a lot of stake. Is the process perfect? No.

But you have to look at the regulating agency as a partner. Right. And it's a process where you build a relationship. You're earning trust. You're building hardware and software development practices, which are documented that an agency come in and look at those and say, why did you make it? this decision, this change to the code, right? And I think this is foreshadowing for the conversation about AI that we'll get further into here.

And you have to be entirely explainable and auditable in to end. Now, that's difficult to move fast and break things in that kind of an environment. But it is very intentionally highly regulated. So this would fall under what's called an FDA 510K process, which is really a smart highway that was built. and that's a reference to the sort of the code and the regulations that says if there's a product that has some substantial equivalence, a camera system that does this and a camera system that does that plus more, you can start with a 510K,

which will accelerate your process to market. There's certain stringent proof points you have to hit, and if it's accurate and if it's faster or whatever those criteria are, FDA, if you meet those bars, FDA will give you basically a slight fast track. to market. Got it. If it recognizes your building and you're standing on the shoulders of existing technology,

they can fast track you a little bit and not make you start from zero. And I guess in your case, the sensor arrays and being able to build off of that, which already exists, what would help you? The smart strategy there, which is what we've pursued, is not try to boil the entire ocean day one. That's going to be confusing for a regulatory body. you know, what is the key innovation here and what are you enabling today and where are the proof points and where is the 10-year patient outcomes study? So that's not a great strategy for dealing

with FDA. That makes them nervous, understandably. So what you want to do is go stepwise through, build a platform, get that cleared, then come layer different software packages and upgrades. And as you said, expand the surgical adjacencies, go after knees and cranial and those kind of applications, if that's where we're going. And those are essentially additions to the regulatory strategy. And that's much less confusing for FDA. To get to this point in time, seven, eight years, about $100 million to get a product like this over the finish line. Yeah. It's a good guess. We went to very educated folks in the space early on, and I'm a very competitive person. I don't know about you. But I got them to kind of outline what it's taken,

to bring Da Vinci and other systems to market. And it was about 10 years, $100 million was the estimate for deep tech execution and innovation in space. I'm happy to report that we're at least three years and tens of millions of dollars ahead of that schedule. Fantastic. Which is exciting, and it affords us the opportunity to engage with the investment community to build a lot more on top of the platform

we've already built and launched. Well, listen, it's just great that you're out there doing this kind of work, and it's great that all of this activity from smartphones and video game consoles and PC-based video games and Nvidia storage. I mean, you couldn't do this without having a massive amount of storage.

You couldn't do it without having these sensors dramatically drop down in price, although you can spend a little bit more money on sensors. That sensor array has got to be $10,000, $20,000 worth of sensors I would take it when you're... That's not a bad estimate, Jason. Yeah. Well, I mean, if you just think self-driving cars have $40,000,

$30, $40,000 worth of sensors. If they're using LIDAR, this feels like it's a little more, it's directional. So you don't need to have it in four different directions. You'd have this in one direction, basically. So it would be slightly less. We have an advantage in that it's on a robotic arm. And so we know where the robot is.

So it gives us a computational head start. We don't need to compute the entire world. We're very focused on the area that matters most of the surgeon. And that accelerates things quite a bit. Well, I know you're hiring. and so everybody should go to the website now, which is P-R-O-P-R-I-O-Vision.com, and go to the careers page.

What are you looking for in terms of needs in terms of high-tech folks who can come and help you reduce suffering and increase the availability of these high-end surgeries to people around the planet? What do you need? Yeah, thanks for shining a light on that, Jason. To do something as ambitious as this, right?

It's not one type of software engineer or hardware engineer you need, right? We need computer vision, AI, robotics, augmented reality, medical device, software and hardware engineering. We have all those things here in Seattle. And we guess we're growing on all fronts. Amazing. So if you're interested in solving meaningful problems that are unsolved today, clinically, both in spine surgery and beyond, we would love to talk to you. Yeah, go to the career spage. I see you have you need a unity to engineer.

So you're using Unity as the 3D modeling environment? It's useful for a lot. You alluded to it. You nailed it. So the video game development environment. We not only like video game players, I think I'm working here for, but we like software engineers who've worked in that environment.

And part of that is thinking ahead to applications that other companies and teams will develop. Right. I don't need to reinvent all of the wheels or every single app that's going to live on our ecosystem or have an API to plug in to our data. to our data. If you are skilled in developing in a unity environment and you have a product that you think could be amplified by working with ProPrio with our singular data set, we would like to hear from you too. Amazing. Well, listen, continued success. Thanks so much for sharing this incredible

progress. And so coming to an OR near you soon, thanks so much, Gabriel, for joining us. And we'll see you all next time on this weekend startups. Bye-bye.