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BackTable / Innovation / Podcast / Transcript #7
Podcast Transcript: Viz.AI: Improving Access to Stroke Care using AI
with Dr. Chris Mansi
Bryan Hartley talks with Neurosurgeon Dr. Chris Mansi about the origin story of Viz.ai, a company using Artificial Intelligence to Shorten Time to Treatment and Improve Access to Care for Stroke Patients. You can read the full transcript below and listen to this episode here on BackTable.com.
Table of Contents
(1) Inspiration for Creating Startups
(2) Takeaways From Getting an MBA
(3) Understanding Your Market
(4) Starting Viz.ai
(5) Focusing on Changing Outcomes
(6) Raising Funding and Testing Feasibility
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[Dr. Bryan Hartley]:
Hey everyone, and welcome to the BackTable podcast, your source for all things in the vascular and otherwise minimal invasive. You can find all previous episodes of our podcast on iTunes, Spotify and of course, on BackTable.com. This is Bryan Hartley as your host this week. I'm a radiologist living in Silicon Valley, and co-founder of an early stage device company in the pulmonary space.
We're very excited to have our special guest this week; Doctor Chris Mansi. Great to have you, Chris.
[Dr. Chris Mansi]:
Thanks very much for having me.
[Dr. Bryan Hartley]:
No, of course. This is our next installment in the BackTable Innovation series, where you'll hear stories from physician innovators who are helping to shape the interventional field through health tech. Doctor Mansi is a neurosurgeon and CEO of Viz.ai, a startup in the AI space that is on fire right now. Viz.ai is using AI, artificial intelligence, to improve patient outcomes in the stroke space, reducing time to treatment and improving access to care. In today's show, we're going to hear about Chris's path through neurosurgery and what led him to Stanford Business School, and ultimately to start a high impact AI company.
Again, Chris, thanks so much for coming on the show.
[Dr. Chris Mansi]:
Thank you very much.
[Dr. Bryan Hartley]:
All right, so starting off, why don't you tell us a little bit about yourself? What do you do, where you're from, those types of things, training background?
[Dr. Chris Mansi]:
Absolutely. So you could probably tell from my accent that I'm British. So, I trained in the UK as a neurosurgeon, I was at medical school at Cambridge at UCL, followed by residency in Queen Square & Kings in London. I was lucky enough to be able to take a sabbatical to spend some time at Stanford in 2014 where I did the Biodesign program and an MBA combined, and that really changed my career a little bit. Prior to Stanford, I certainly had an entrepreneurial mindset. I started a couple of companies in the medical education space, but being out here and seeing the amazing technology, the amazing entrepreneurs, the amazing companies that are built out here, really inspired me to take what I was doing to the next level.
In 2016, I founded Viz AI, which is a medical AI company focused on improving access to care and improving the speed and efficiency of care, trying to take the average standard of care up towards the very best so you get the same care no matter which hospital you show up to, no matter what time of day, day of week. Really trying to maximize the effectiveness of the expertise that we have in medicine, so that if a patient needs a thrombectomy for example, they will be connected via our system to the right neurointerventionalist to get the treatment that they might need.
(1) Inspiration for Creating Startups
[Dr. Bryan Hartley]:
Awesome, it sounds like you have done a lot of stuff since your training. So starting back there, you've finished your neurosurgery training and you said you founded a couple of startups previously in the educational space. Can you maybe walk us through that? What motivated you to want to do that, were you in your training or were you already an attending by that point?
[Dr. Chris Mansi]:
Yeah, I was in training and I wanted to really make learning accessible. This was the early days of e-learning, the likes of Coursera, et cetera, and I wanted to develop an educational program for surgeons that was easy to use while dealing with the demands of a surgical residency. So the company EduSearch essentially puts online modules for what we call the membership of the Royal College of Surgeons, which is equivalent, I think to either the Step 3 as you take the exam when you're maybe two, three years post med school and you're looking to specialize because the system's slightly different now, in the UK.
We essentially built a bunch of content and built a platform for others to put content online and created modules for this particular exam, which is a Viva style exam. For me, what was interesting about it was, it was the first time I really started something from scratch, my first entrepreneurial experience, and I had to just learn a lot, I had to learn how to empathize with the user and put stuff out there, what I now know is marketing. I had to learn how to put a website together, I had to learn how to build a team, and so that early experience was great and it really set me up for the next stage of my entrepreneurial journey at Viz.
[Dr. Bryan Hartley]:
That's great. So you practiced for five years and was EduSearch still going, were you running it or what happened with EduSearch?
[Dr. Chris Mansi]:
Yeah, it's still being run by a small team in London.
[Dr. Bryan Hartley]:
Great.
[Dr. Chris Mansi]:
Yeah.
[Dr. Bryan Hartley]:
That's great. It sounds like that was kind of where your entrepreneurial fire was started so to speak.
[Dr. Chris Mansi]:
Absolutely, yeah. I speak to a lot of clinician entrepreneurs like yourself and I think all of us have got a very similar story where you just go, "Hey, I'm going to try something," and you don't really know what you're doing, but you just give it a go. You create something from nothing and you learn along the way and you continue iterating to the works.
[Dr. Bryan Hartley]:
Yeah. That's exactly what, I interviewed previous Rusty Hoffman, who's an IR at Stanford. He said the same thing, he says you really just have to get started. You course correct later, but just getting started is probably the most important step.
[Dr. Chris Mansi]:
Correct, I agree with that.
[Dr. Bryan Hartley]:
That's great. Did you do any endovascular work during the practice?
[Dr. Chris Mansi]:
I didn't, no.
[Dr. Bryan Hartley]:
Okay. So tell me, at what point in your career did you decide, "I'm going to take a sabbatical. I love this entrepreneur stuff, but I want to formalize my training in business," and what prompted the move to Stanford? Obviously it's one of the best business schools around.
[Dr. Chris Mansi]:
Yeah. So I have to admit, back then, I probably didn't even know what an MBA was. I was very focused on my clinical work, but I started this company and was learning a lot, and a friend of mine who was helping me said, "Hey, you seem to like this stuff, you should consider doing an MBA," and I sort of looked at what it was. I was reading a lot of the material coming out of Silicon Valley, like some of the blogs coming out of the Y Combinator program, a bunch of the books at the [inaudible 00:08:04] startup, Crossing the Chasm, and I sort of realized this stuff did really interest me. So I was lucky enough to be granted a sabbatical and came out to Stanford for two years with the plan to go back-
[Dr. Bryan Hartley]:
Of course.
[Dr. Chris Mansi]:
... and Stanford being Stanford, I was in a business school class and I was lucky to be taught by Eric Schmidt who was the CEO and chairman of Google at the time. I pitched the idea for this in the class's business school, the business plan competition, and he liked it enough that he ended up to seed funding the company.
[Dr. Bryan Hartley]:
Wow.
[Dr. Chris Mansi]:
I think back then, I didn't really understand how venture capital works, but I thought having a few million dollars to try and make this happen was very exciting, to have this conversation with my boss back home saying, "Hey, I might be out here for a bit longer, can you extend the sabbatical?" And they said yes, and that actually ended up turning into me doing this full-time and leaving clinical practice.
(2) Takeaways From Getting an MBA
[Dr. Bryan Hartley]:
Wow. Quite the jump, and I want to get into that in just a little bit, but back to the MBA, because it sounds like you had a fantastic experience there; Eric Schmidt teaching you and then funding. So what were kind of some of your takeaways from getting an MBA? And maybe you can walk us through any experiences that you had that were maybe transformational. I know there are probably several clinicians out there and other groups of people in industry who would consider doing something like an MBA.
[Dr. Chris Mansi]:
Yeah. I talked to several fellow neurosurgeons and neurologists who either have done one or doing one. I think the first thing about the program is, it's two years where you have time to think along with some really smart people from other disciplines, from business, from consulting, from banking, also from computer science, engineering. Where else do you get to take that two years to try something? And for me, my biggest takeaway was if you can, in your career, give yourself a chance and space to do some innovative things, take it. Take it, no matter where it is, no matter what the program is.
The MBA in particular is helpful because it's designed around teaching you some of the disciplines of business, but particularly at Stanford, it's not just the disciplines of business, it's things like storytelling, communication, management. You're not just learning about human resources and the ins and outs of how... I don't know, Nike set it up, or Nike, as you say in the US, set it up. But you're learning actually about the interpersonal skills of inspiring people, of leading. I think those kinds of programs are excellent at achieving those things, which is why you see so many great companies coming out of programs like Stanford.
[Dr. Bryan Hartley]:
Yeah, that's great. I'm going to reiterate what you said about taking time and giving yourself the space. From what I found in the short amount of time I was out here doing the Stanford Biodesign fellowship and then starting our startup, I think I've realized also that if you're doing full-time clinical practice, your brain just doesn't have the time or the energy to come up with some of these things that you might want to pursue. I've been surprised as well, how important the time and space is, really.
[Dr. Chris Mansi]:
Absolutely, the time and space and being around other people who are on the same or similar journeys to you, because if you're just trying to deal with the next clinic, the next operating list, then of course that's going to be your focus. But being around other people, like in the Biodesign program, who are trying to come up with other clinical needs [inaudible 00:12:05] finding journey, it gives you the permission to go and do that as well, and also like-minded people to discuss the issues that you're having as you're trying to work out what actually will move the needle and improve clinical outcomes.
[Dr. Bryan Hartley]:
And we've talked about this in other podcasts as well, about how important it is to be around a group of people who kind of give you energy with what you're working on, the same creative people who are looking to push the boundaries and innovate. And also who are going to challenge you a little bit, because I'm sure when you were at Stanford, you met people who were incredible and you're like, "Oh my gosh, how did they do this?" I know I did when I was there. And it's always nice to have that mirror kind of turned back at you, and to say, "All right, if they can do it, why can't I do it?" And it's very inspiring in a way.
[Dr. Chris Mansi]:
I agree. I agree. It gives you the courage to go and try something, for sure.
[Dr. Bryan Hartley]:
Totally. Totally. Any interesting, like what was your favorite class, I guess, in your MBA? What stuck out to you as something that you'll take with you?
[Dr. Chris Mansi]:
So I was really focused on the entrepreneurship classes as well as anything that I could go and do in the engineering school. My father is an engineer, my mother is a computer scientist, so that was, in some ways, part of my DNA, but I was always drawn to those cross functional,specialty type programs. So Biodesign was certainly one of my favorite classes and there was another one by a professor called Andy Rachleff, who is also a very successful venture capitalist benchmark as well as, I think, the founder and now is chairman of Wealthfront.
So he taught a course based on the book Crossing the Chasm, and for me, that was a very, very impactful because it made you realize that you want to start small. You want to start in a focused manner. Don't try and use a new technology like artificial intelligence and try to solve everything at once. Try and solve a real problem for the stakeholder who matters the most, which is the patient. Once you're doing that, you're going to be able to use that beachhead to expand. And if anyone is thinking any of the conditions and they're thinking, "Hey, I might start a company," that book, Crossing the Chasm, is one of my favorites and I thoroughly recommend it.
[Dr. Bryan Hartley]:
No, that's a great... definitely needs to be on the reading list. Doctor Tom Fogarty says the same thing. I mean, you mentioned the patient and he always said that if you keep the patient the center of your innovation process, then you're going to be successful in one way or another.
[Dr. Chris Mansi]:
Yeah.
(3) Understanding Your Market
[Dr. Bryan Hartley]:
I think that's very important to reiterate. One other thing that I'd like to ask, and this is something that I think if you haven't gone through some type of business or management program. It's a part of the innovation process that I think can be left out if you just start hitting the ground innovating, is the market, the market size, how well you evaluate your market to see if it's a high impact area where you're really going to be able to impact a large number of patients. How important is that, did you already understand this going in, and what did you learn about how important market is when you're trying to get an innovation to commercialization?
[Dr. Chris Mansi]:
So I think the answer is different, depending on which stage of business you're at. I think when you are at the stage where I'm at right now, which is the growth stage, the two things that really matter are how fast you're growing and what is the overall total market that you're addressing. I think when you're raising money from venture capitalists, they are the two things they most care about. In the early days, though, you really don't know exactly what the innovation, the product, the product market fit, the total market size is ultimately going to be, partly because markets change and develop. The Google team, Larry and Sergei, didn't know what search was going to become when they were first starting Google, they just had a better search algorithm. Same thing for, if you look at some of the more recent successes like Slack and Stripe. When they were starting out, people wanted to use what they had, but they didn't know it would become as big as it is today.
I often caution entrepreneurs not to be too McKinsey-like in their assessment of markets, because there's a reason why, like some of the smartest people at Stanford Business School were probably the McKinsey consultants, but very few of them went on to actually start a company because they saw all the reasons why things would fail. But we've seen in 2020 just how much the world changes, and if you built a company that was perfectly attuned to the Total Addressable Market size of 2019, well, that company is not likely to succeed now in 2021 and beyond because things have changed. And it leads me to caution when you're in the early stages of being too analytical about how large a market is. I would just make sure that it's big enough and that your technology is flexible enough that it can grow into something as the world adapts around you.
[Dr. Bryan Hartley]:
That's perfect, and I think that's a really, really great point about how markets are dynamic, they're they're never static, especially as this last year has proven. Whole new market segments have exploded with telehealth in general. So I think I will repeat what you said just now, and that is make sure your market is big enough at the beginning. I think that's important to have, I think, at the very beginning, so when you're working on something, just to make sure that it's high impact. And if you know it's a true clinical need, kind of like Biodesign says, that you've vetted that clinical need, and there are enough patients out there who need it solved, then I think you're on the right track and you can kind of just put up a ballpark number of your total market size and then just work on making it the best it possibly can be.
[Dr. Chris Mansi]:
Yeah. And like you said, center the patient and if there's enough patients who struggle with that disease, that condition, then it's likely that you have a potential business there, if you can solve that problem for them.
[Dr. Bryan Hartley]:
Perfect. So would you do it again? Let me ask would you pursue an MBA again? I know that's a tough question.
[Dr. Chris Mansi]:
Oh no, absolutely. I thought you were going to ask would I start a company again? Yes to both, I would definitely pursue an MBA again, and again, people have different perceptions of the value of what you learn in an MBA, but it's not about what you're being taught, it's about what you learn, it's about the people you're around, the friends that you build. It opens up a new space in your mind for what you can do so I would definitely do it again and I would encourage others if they have a chance to take it. But that's not just an MBA, that could be another graduate program that you take halfway through your career, I think it's a great idea.
(4) Starting Viz.ai
[Dr. Bryan Hartley]:
Awesome. So you said you came up with the idea for Viz at Stanford. What was kind of the genesis of this? What's the clinical need and what was the reason behind it? Was there a specific patient or something that prompted you to want to start this?
[Dr. Chris Mansi]:
Absolutely. So back then, this is in 2015, I'm in the Biodesign course with an endovascular neurosurgeon, Jeremiah Johnson, and the MR CLEAN data came out showing that thrombectomy was effective and not just effective, it had very low numbers needed to treat for a devastating disease that I knew well, and my grandmother had, had a large vessel occlusion stroke. And all of a sudden we had the therapy to treat a patient that was proven and not just in one trial, but in numerous trials in 2015.
But I realized that actually, if you looked at the statistics, very few patients who had an LVO, a large vessel occlusion, were being treated. It was around the 2%, 3%, and if a patient showed up to Stanford, it wasn't that they weren't being treated, that they usually were, is the fact that often if you show up to a hospital without an interventional specialist, without a stroke neurologist, it wasn't being picked up, it wasn't being referred.
Maybe it was, but the workflow wasn't appropriate or the ambulance would take too long to show up. There were a huge variety of reasons when you went through the Biodesign process, why these patients were A, not being treated as often as they should, and B, why in the STRATIS registry, which is one the largest sources of data we had at the time, we saw that the median time to treatment was between three and five hours. Whereas in the best centers you could get patients, if they showed up to the hub, you could get a patient from door to going in 30 minutes. And I spoke, you could get door-in, door-out times of an hour so why wasn't that happening consistently?
And I just thought back to some experiences I had in practice. I mean, I did the Ted talk about one young lady who had a subdural hemorrhage and who died despite the operation going well, and in the mortality morbidity meeting, realizing the reason why she died, wasn't anything we did in the operating room, it was the four to five hours it took and the delay to her to get her there. And you've been through the Biodesign program, it really encourages you to stop thinking about what you might do as the clinician and focus on the whole clinical need, because if it's the transporter that's the problem, if it's the transfer center that's the problem, that's where you need to focus.
So we realized that this new technology, deep learning, which had just come out of the labs of Geoff Hinton in Canada and was really all the rage in Stanford at the time, which was able to pick out patterns in data so it could tell you the difference between a cat and a dog, for example. We realized that potentially we could use that to pick out patterns in CT scans or in other medical data, and use that as a tool. At the time, there were a bunch of other AI imaging companies who were really focused on improving things for the radiologists, like improving maybe the measurement of something or the detection of something, but ultimately the radiologist does a good job of that for the most part. The issue is connecting the dots between the ED, the radiology, the neurologist and the interventionalist. With all of the amazing healthcare providers that go in between; the stroke coordinator, the stroke nurse, the ambulance driver, the EMT, and there's many, many people, it's incredibly complex.
But what if, within a minute of the scan, an algorithm would read that scan and alert the right neurologist or neurointerventionalist so they could go, "Yeah, these images show a patient who I could potentially treat, let's transfer them over." All of a sudden you would turn healthcare from a push model, with numerous steps and handovers and three to five hours of delays, to one where decisions could be made within minutes, where you'd have the team that really understands the disease and the time sensitive nature of the disease, driving the workflow, you could potentially shorten time to treatment significantly. That's ultimately what we have proven out.
[Dr. Bryan Hartley]:
So what I'm hearing, that's great, what I'm hearing is, it's really a workflow problem. From your end, it was a workflow problem and maybe the timing was right to use a technology like AI to help solve this problem. But again, it was probably, the workflow was the hard part for you guys; how do you figure out how to connect these dots and in a quick way? And then the catalyst would be once the scan is done, Viz would automatically read the CT scan right when the scan is done and then it starts this whole kind of domino effect afterwards?
[Dr. Chris Mansi]:
Correct, yeah. So it's reading any of the scans coming off the system. If it's a ischemic stroke, it's going to be a CT angiogram and if it sees a large vessel occlusion, a perfusion mismatch, it is going to send an alert to the relevant stroke team and associated vascular neurologist and the neuro interventionist, as well as the local emergency room physician and radiologist, and immediately they're connected, it's via mobile app. They click on the alert, they view the images in a matter of seconds and they can immediately communicate. So typically, we will see scan to decision times of around three to five minutes where you've not just got decisions of, "Hey, I can treat this patient," but you've got communication between that spoke in the hub where they're saying, "Okay, we're going to transfer this patient over to you name the comprehensive stroke center.
[Dr. Bryan Hartley]:
Yeah, that's great. I had a chance to download the training app that you guys offer and look at the images and from a radiologist perspective, the images were great, very high quality and it's a very intuitive user interface. I was curious how much time you guys put into your image quality and user interface experience?
[Dr. Chris Mansi]:
A lot, a lot. I think we realized early on that an algorithm on its own was not going to be the product and really, this would only work if the radiologist, the neurointerventionalist, the neurologist could roll over in bed and make a determination if this was a patient they needed to act on or not. So unlike a lot of the other AI companies, we kind of issued technological determinism, and instead leant into the complexity of how healthcare is delivered at 02:00 in the morning, as well as 02:00 in the afternoon at a major downtown center in Miami versus a rural spoke, and realized that actually the user interface was going to be the key.
In healthcare, and we learned this in Biodesign, the only way that you can change healthcare and workflows is if you make it easier for that clinician who's responsible for that patient and wants to do the best for their patient, you can only change their behavior if it's easier to use your product than the alternative. And the alternative [crosstalk 00:27:47]-
[Dr. Bryan Hartley]:
Also, lowering the activation energy, basically, that it takes because they have to make so many decisions on a minute by minute basis, that it has to lower that threshold for them.
[Dr. Chris Mansi]:
Yeah. I love the way you put that, exactly. Lower the activation energy, absolutely.
[Dr. Bryan Hartley]:
Okay. And so, as you say, the algorithm was not really... that's not the focus, you needed it to be a beautiful, almost like a work of art, which is what it looks like when you log in. It looks clean, cleaner than most PAC systems which was very refreshing. I am curious, how did you realize that AI was the way to go? I mean, I know it was coming out at the time and the timing did work. I mean, timing is so important for these things-
[Dr. Chris Mansi]:
Yes.
[Dr. Bryan Hartley]:
... but it also takes a lot to be able to say... first off, did you have any experience with AI? I know you said your mom was in computer science, but if you did not have any experience, that kind of takes a little courage to dive into something and say, "Hey, this is kind of the tool I'm going to use to solve this clinical need."
[Dr. Chris Mansi]:
Yeah, so I think we were looking at the system and we realized that you needed to focus on the workflow and the user experience, but you also needed a trigger. You need to try and replicate having a neuroradiologist in every CT scanner so that the neuroradiologist could trigger that workflow, because for every 1,000 scans that Viz processes, there's maybe 20 or so that actually will have a large vessel occlusion. So there's this 890, 980, sorry, but it's not [crosstalk 00:29:34], but we realized that the power of deep learning was to automate that focus. The algorithm doesn't need to, and wasn't designed to get to the level of a neuroradiologist. The point is these things, once you start looking at CTA, is a lot of relatively easy to pick up. But if you don't look at the scans, if you're an emergency room physician, they're hard to pick up, particularly the more distal occlusions.
So we needed something that could make care consistent, and we saw that in our FDA study. We were able, even in some of the best stroke centers around the country where we did the study, we were able to not only reduce the time from scan to alert of the specialist by around an hour, but most importantly, we reduced the variation from well over 120 minutes down to seven minutes, the variation of when this doctor was alerted.
[Dr. Bryan Hartley]:
Wow.
[Dr. Chris Mansi]:
To me, that's the major issue in healthcare that technology can solve. When things align, that patient is treated with the standard that we want them to be treated, but on average, that's not the case. There's so much variation in healthcare and AI solves the standard deviation problem.
(5) Focusing on Changing Outcomes
[Dr. Bryan Hartley]:
Mm-hmm (affirmative). No, that's a fantastic point. I think importantly you found, it sounds like it was a convergence of both the timing was right for AI to be used as a tool, the clinical need was there, and that's obviously, I'd say, the foundation is the clinical need. But also, it sounds like you guys just latched onto AI and said, "We want you to solve this very focused problem," rather than, as you mentioned earlier, solving 10 different things. You're not going to read the whole CT scan and generate a report for the physician, but you are going to be very good at finding a large vessel occlusion. You mentioned that before, but how important do you think that is, especially if you're dealing with something like AI, to focus in on something so that it becomes very good at one particular thing, but also to make sure that, that clinical need or that solution leads to an outcome change?
[Dr. Chris Mansi]:
Yeah. I think it's really the focus on the outcome change. Our product wouldn't work without the algorithm alerting the doctors, it has a big difference because it's alerting the specialist across the hospital network, and waiting for the process to happen as it does without Viz to happen in series, just takes too long. The algorithm is important, but really it's about how are you going to improve the patient outcome? Well, you can improve the patient outcome if, from the moment they have the stroke to when they get the clot removed from their brain, that time is reduced. You could do that in many ways, you could focus on educational campaigns to make sure people call 911 earlier, and that's absolutely essential. You can focus on better abilities to read the scans, better workflow so when the patient comes in through the door of the ER, they're immediately taken for both a CT and a CTA, and we do all these things.
If you work with Viz, what's interesting and a lot of our customers will comment, is it's not just the software, it's the team that comes with it. We have a customer success team that essentially is able to share best practices from every center that we work with, so that a hospital in Mississippi can benefit from a hospital in New York and what they've done, and vice versa. That focus on the solution is really, really important. Now AI is advancing every almost every week, right? You're seeing new techniques, new tools that are coming out from the major technology companies like Google, who we work closely with. I think it probably is logical that over time, most images, whether they're very logical images or pathological images, most of them will probably be examined at some point by an algorithm, which will do one of the three things; it will help with disease detection, disease measurement or prediction of what might happen to that disease.
But I think ultimately, unless they're part of a whole solution focused on that patient outcome, they're not going to make a difference and therefore not be adopted.
[Dr. Bryan Hartley]:
Yeah, you have to have the outcome change before there's going to be the impact and be adopted. If you have something that just is better at finding something, as you mentioned earlier, well, a radiologist is going to do that at some point. Maybe you saved 12 seconds, but that doesn't move the needle in terms of outcomes.
[Dr. Chris Mansi]:
Exactly.
[Dr. Bryan Hartley]:
So backing up just a touch, you mentioned a second ago you're working with Google. How are you guys working with Google?
[Dr. Chris Mansi]:
Well, so they’re investors in Viz where they did our series A along with Kleiner Perkins, we have a few different bits and pieces of technology that we're collaborating on with them.
[Dr. Bryan Hartley]:
Great.
[Dr. Chris Mansi]:
[crosstalk 00:34:53] I won't really go into that.
(6) Raising Funding and Testing Feasibility
[Dr. Bryan Hartley]:
Yeah. R&D, I understand. So you came up with the idea, you came up with the solution, the clinical need was strong, what did you do early on before your series A? I mean, did you have to raise seed funding, pre-seed funding, how did you prototype feasibility? I think this kind of gets to the core of what we mentioned earlier about just getting started and just moving the ball down the field a little bit. So I am curious because that's that moment where it's easy to say, "Oh, it's not worth it. This is a mountain of work we've got to climb."
[Dr. Chris Mansi]:
Right, and it is a mountain, it's a mountain where every time you get to a peak, there's another peak that you discover ahead of you. That's the joy and the curse of entrepreneurship, I think.
So back then, we really were focused on learning, so talking to the market, talking to a lot of clinicians, we were building the technology, the mobile viewer, the HIPAA compliant messaging service, which now is comparable to WhatsApp, but back then was relatively basic. We were getting guidance from some of the top stroke clinicians around the country, the people who were PIs of those trials, because we wanted to try and codify what they did in centers like Grady and [inaudible 00:36:23] in the south.
[Dr. Bryan Hartley]:
Yeah, Chattanooga.
[Dr. Chris Mansi]:
Yeah. So those places where in the stroke world, they're treating more strokes than anyone else so they've had to get really, really good at doing it. So we wanted to try and codify that workflow. So to get started you've got the AI component, which is, you're getting ahold of a data set through research collaborations, annotating the dataset, building the models, iterating on the models, talking to the FDA to try and understand and negotiate on what the clinical trial will be, and really just seeking advice from the market and getting product market fit because you can't ever develop something that’s going to work in a lab, right [crosstalk 00:37:06]-
[Dr. Bryan Hartley]:
In a vacuum.
[Dr. Chris Mansi]:
In a vacuum, yeah. You have to be out there and understanding what the real world's like, particularly the real world of healthcare. So we were just doing a lot of that.
[Dr. Bryan Hartley]:
And were you building a team at the time as well, or was it just kind of the core group and you were trying to develop that early prototyping, early feasibility data so to speak?
[Dr. Chris Mansi]:
Yeah. Well, we were lucky again, being associated with Stanford, we were able to bring in some super talent from the engineering school, and my co-founder David Golan was a post-doc there, and sort of bringing in some of his colleagues. I was able to bring in some superstars from the business school and a small team of four or five people were just out there learning. We were part of an incubator. They had other like-minded companies doing similar things, actually, most companies or all of the companies were not in health care, they were all sort of [inaudible 00:38:00] technology companies, but we were going through that journey together.
[Dr. Bryan Hartley]:
Which incubator, if you don't mind?
[Dr. Chris Mansi]:
It was the pair incubator.
[Dr. Bryan Hartley]:
Okay. So were you going off of the funding that Eric Schmidt had provided, was that kind of your seed capital at that point or did he come in at the series A?
[Dr. Chris Mansi]:
He provided the seed capital.
[Dr. Bryan Hartley]:
Got it.
[Dr. Chris Mansi]:
He's got a fund called Innovation Endeavors and they did our seed round.
[Dr. Bryan Hartley]:
Okay, great. So your funding has gone up a little bit since then, you recently raised $71 million. That was a series C, correct?
[Dr. Chris Mansi]:
Yes, that's correct.
[Dr. Bryan Hartley]:
That's a fantastic number for a lot of people. So tell me, what are you looking to achieve with the $71 million? I assume this is your growth phase, you're looking to really grow with this?
[Dr. Chris Mansi]:
Absolutely. So we've been successful in getting our ischemic stroke product into many hospitals, it's pushing 700 hospitals, I think about 680 at the last count. But what we found is that the combination of mobile image viewing with HIPAA compliant, secure communication, the on-call schedule, and then algorithms that trigger workflows so that if the CTA shows a large vessel occlusion, then that, then this workflow should happen. That's very powerful for multiple disease states. We've had a lot of other specialists, particularly interventional radiology, interventional cardiology, vascular surgery, peripheral vascular and endovascular, they've started using Viz more broadly than stroke for their own workflow needs. And so in PE it's being used to view the CT PE, the RV/LV ratio and make decisions on what to do next with the patient.
It's being used to arrange transfer from spoken hub, and what we've essentially built is this new form of software in healthcare, an intelligent care coordination platform, which in contrast to the EHRs out there, which really you can think of as the system of record, they're really the system of action. They're lightweight, mobile based tools for the most part, that allow things to happen faster and more efficiently, but most importantly, more consistently. And we see great clinical outcomes in stroke, but also see great financial outcomes, we see reduced leakage because more patients are followed up sooner. We see better satisfaction from the clinical team because A, it's easier to use and they're collaborative, so it feels like kind of this one team, one dream type mindset. And where that pull from the market has really inspired us to expand pretty broadly. So what you'll see first from us in 2021, 2022 is a big expansion into other disease states that can also benefit from this intelligent care coordination platform.
[Dr. Bryan Hartley]:
That's fantastic. So you're starting the expansion phase. You mentioned, just kind of wrapping up a little bit here, my takeaways here are your clinical need was strong because you could change outcomes. I think that's probably the number one takeaway I would have from the beginning, if you're going to work on a project like this is, you must affect outcomes, and it must be clear that you are affecting outcomes. You also seem to focus in on kind of a specific area, which was important. But now once you've mastered that and shown and kind of worked out probably the kinks that I'm sure come with the system over a couple of years, optimizing and iterating, you've kind of leaned the system out. You've made it a very lean, efficient, intelligent workflow system. Now you're ready to build on that momentum and spread out into other practice areas. Does that sound reasonable as a summary?
[Dr. Chris Mansi]:
Absolutely. And we want to work with a lot of your listeners because we need to understand where this technology can really impact patient care, and we work with a lot of interventional radiologists, because you've got Keith Sterling, Richard Saxon, I think he was part of this podcast, [inaudible 00:42:39]. A lot of these people are helping us say, "Hey, take this technology and put it here because these other patients can benefit." And that's really what our next journey is about.
[Dr. Bryan Hartley]:
That's awesome. So, Chris Mansi, thank you so much for coming on and sharing your story, your path, and now your passion. Let me ask one more question before we go, though, do you think you will go back to clinical practice at any point?
[Dr. Chris Mansi]:
I wish. I always said I wish I could do both. I've been out since 2014, so I don't think that's going to happen, unfortunately, but who knows?
[Dr. Bryan Hartley]:
Again, thank you so much for coming on. That was a great overview and what an excellent story. So thank you for sharing it with us.
[Dr. Chris Mansi]:
Right, thank you for having me, really appreciate it. (silence)
Podcast Contributors
Dr. Chris Mansi
Dr. Chris Mansi is a Neurosurgeon and the Co-Founder and CEO at Viz.ai.
Dr. Bryan Hartley
Dr. Bryan Hartley is a practicing radiologist, host of the BackTable Innovation series, and co-founder of Pulmera in Palo Alto, CA.
Cite This Podcast
BackTable, LLC (Producer). (2021, December 1). Ep. 7 – Viz.AI: Improving Access to Stroke Care using AI [Audio podcast]. Retrieved from https://www.backtable.com
Disclaimer: The Materials available on BackTable.com are for informational and educational purposes only and are not a substitute for the professional judgment of a healthcare professional in diagnosing and treating patients. The opinions expressed by participants of the BackTable Podcast belong solely to the participants, and do not necessarily reflect the views of BackTable.
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