David Zakariaie Presents Senseye at LSI Europe '23

Transcription

David Zakariaie  0:05  
Hi, everyone. My name is David Zakariaie. I am the CEO and founder of Senseye. And at Senseye, our goal is to solve a mental health crisis. And as large and complicated and personal have an issue as a mental health crisis has become, we actually think the underlying reason behind it and the foundational step to solve it is relatively straightforward. The biggest problem in the mental health industry is that the way we diagnose and treat and manage patients today is basically the equivalent of diagnosing someone with type two diabetes but never measuring their blood sugar. It seems like such a ridiculous concept, but that is the standard of care. In mental health right now, the there is a very accurate and objective way to diagnose patients. The problem is it requires a very highly skilled psychologists or psychiatrists and about four to five hours of a patient's time, and so and so and so. And so, in the real world, that process doesn't actually occur. About 70% of all mental health is diagnosed and treated exclusively in primary care. And it's essentially the equivalent of you show up at your doctor's office. We log on to, you know, we log on to a telehealth session, you answer a couple of questions, they call it depression, they call it anxiety, you're prescribed with an SSRI or a Xanax. And it's the end of the day. And in the last surveillance study that the NIH debt, they showed that the best diagnosed mental health condition in the United States is major depressive disorder. And it's misdiagnosed 65% of the time. And that's the best condition. As you get to more complicated conditions like PTSD or bipolar, that misdiagnosis the rate skyrockets between 80 and 90%. And that's not the clinicians fault. It's certainly not the patient's fault. It's just the reality of of system built purely on patient self reporting. And so that's, that's really the problem that we're trying to solve. And so at its core sensai is the first is the first platform for the diagnosis and severity tracking of specific mental health indications. Starting with PTSD, generalized anxiety disorder, and major depressive disorder. The way the product works, it's an app on a mobile phone. We've gone to mobile phone to solve distribution, but it is regulated, it's a class II de novo medical device, the first time a patient interacts with it, it's about a 10 minute test, we show ocular stimuli on the screen of the phone as he videotape your eyes response to it. And then on the other side of that we spit out a binary diagnosis as well as a severity score, there has been a shorter about three to four minute version of a test that a patient is able to take as often as a clinician wants them to as a way to see how that severity is changing over time in response to treatment. And, you know, on the neuroscience side, we've known that this has been possible for a very long time, the problem has been to measure a lot of the more novel ocular metrics, you traditionally need a series of either of series of traditional eye trackers that would cost anywhere between 70 and $80,000 each. And so our breakthrough is less on the neuroscience side. And it's more that we've built the computer vision to be able to do with the front facing camera of a cell phone, what you normally need hundreds of 1000s of dollars of very expensive equipment for and there's really three things that we're measuring in response to the stimuli. The first is all the normal conventional ocular metrics you would think about. So things like pupil size, gaze blinks, the Qods. The second is more novel ocular metrics, were able to differentiate between changes in the sphincter and dilate or muscle fibers to the iris as a way to understand if the stimuli is activated your sympathetic or parasympathetic nervous system. And then the third is heart is is a heart rate variability off the face, and all those three, all three of those things combined in response to the stimuli is what is allowing us to work. Right now. We're deep in clinical trial. And we conducted our first clinical trial, it was a pilot stage trial. Last December, it was very successful, but it was small was about 68 patients and we ran it at at a UCLA, we're now in the middle of a larger 750 patient trial, we're about a third of the way through it. It's across nine sites on the academic side, Harvard Mass General is the primary site, and there's five other universities. As as, as, as well as a couple of private sites as well. Our accuracy right now is slightly north have a slightly it's slightly north of point eight, on both sensitivity and specificity. But we feel based on what we see in the data that by the time we by the time we train the model on the complete data set, we can probably get the accuracy somewhere around 0.91 1.92. the reality of mental health as the human condition is a little bit too messy to ever have, you know, a diagnostic, a diagnostic that's 100% accurate, but when the standard of care right now is somewhere between 20 and 30% accuracy. You know, we think it's a pretty large jump. And so it's kind of what are essentially what our pipeline looks like right now. The first indication which is PTSD is Class II de novo. We're targeting submitting it to FDA early next year. And then the agreement we have with our review team at the FDA is that the the code, the comorbid indications, which are control groups on the PTSD trial, which are anxiety and depression and anxiety and depression, anxiety and depression can be 510k on top of it. As soon as PTSD is approved, our go to market strategy is a little bit unique in that what we've built is what we've built is 100% software. And so rather than do a traditional door to door medical device sale, our thought process has been to find the aggregators of mental health patients, and turn those into our customers instead. And right now, the largest aggregator of mental health patients is, is a lot of the largest telehealth platforms about 80% of mental health is diagnosed and treated on telehealth right now. And that could be your local doctor using zoom or a lot of specialty platforms such as talkspace or BetterHelp. And so our go to market strategy is we essentially sell enterprise SaaS to the large telehealth platforms banded on volume, it becomes a standard way that they diagnose and track the severity of their patients. And then, and then from, from a unit economics level, it works out to about $350 per patient per year, about half of that we expect to be captured by Senseye. And the other half to be split between the between the telehealth platform and the individual provider. There are existing insurance reimbursement codes that we're able to use, the larger problem is most of mental health right now is cache. So it will take time to kind of transform mental health from the fee for service model is right now, which is primarily cash pay to aid to a value based based system. But there are existing codes that we that we that we are able to use, it pays about $100 for the upfront diagnostic and then $25 a month for the remote patient monitoring. After that, and although we are pre FDA, we have started to generate some revenue right now. We did about 2.2 million in revenue last year, and we're on track to do just under four this year. Our revenue right now comes from two places. The first we have a series of customers, we have a series of customers in the Department of Defense in the US who have started to deploy it as started to to deploy and pilots by getting away from a waiver from the FDA to start testing it pre FDA approval. And then we have a couple of pharmaceutical partners who are using it as an exploratory or a secondary endpoint on their own clinical trials. So that they have a more objective way of showing the FDA that their drugs actually work. We have a great team. We're about working with 23 primarily based in Austin, Texas, and we've been able, we've been able to get we were able to get four four of the leading tailors in the space to, to to who to engage with us as well. We have about we filed nine patents. Six had been granted, six have been granted. And the other three are still pending. And we're currently raising a $10 million series A we signed a term sheet a couple weeks ago. And we have about seven and a half million of attend. So we'll have to kind of close out close out the last part of that round. And we're I'm David from Senseye and thanks for listening