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Travis Bond, Altoida - Technology to Predict Neurological Disease | LSI Europe '22

Speakers

Travis Bond

Travis Bond

CEO, Altoida
Read Biography
The company's platform evaluates an individual's risk by interrogating 800 digital biomarkers collected through a digital assessment and augmented reality (AR). A proprietary artificial intelligence (AI) algorithm analyzes these findings to assess brain health and predict neurological disease development.

Transcription

Travis Bond  0:07  

Good afternoon. Thank you so much for your time brilliant presentation, by the way, very intriguing. It is exciting, I think, to see, you know us as entrepreneurs, really be able to leverage just technologies, certainly including, you know, not just virtual and augmented realities, but AI. And so I do really have the distinct pleasure of being the CEO of Altoida, in that we spent the last 12 years taking smart devices, and turning those into basically mobile PET scanners, and the ability to do neurological testing at any place in the world at any time. And as a result, we're all about democratization of neuroscience. And we believe that with these smart devices and AI, that we can unlock neurology at scale for everyone. So a little bit about neurology, a lot of things. If you don't know the CNS space, it is a very expensive place for science, especially drug manufacturers to operate on, but it's equally as frustrating on the provider and the caregiver side. And so this is really represents the current sort of clinical Odyssey, if you will, of diagnosing somebody with dementia or Alzheimer's, this takes place in terms of down in the lower left here, a writer led interview. And so asking you questions, whether there's questions, you'd go for 30 minutes, or whether they go for four hours, this is all about the interviewing process, a very labor intensive, doesn't scale at all in his work, and has a lot of subjective bias. And then you go to sort of imaging and you go to blood biomarkers. And in this case, this is between two and a half to three years. So the average person to be diagnosed by all that time is going by that you starting to see symptoms. And clearly, symptoms are required for a lot of these sorts of medical procedures, but what's really going on as you're missing your therapeutic window. So we believe very, you know, we're very, very passionate about the fact that if you think about every doctor out there has a stethoscope, but not every doctor is a cardiologist. And I think that that makes really just sort of kind of a fantastic visual, in the sense that a simple device that allows you to listen to the inside of the body, whether it's the heart, the bowel, the the bowels or whatever. But the point of it is it becomes part of your training part of your training to understand these sorts of vital statistics. What we did was we took a phone that everyone has, and said, Look, could we put it through a set of learnings, these are known as observational trials, and over a 12 year period of time, we knew everything existed in terms of PET scan, MRI, all the blood biomarkers, and we use our test results, which generate about 800 Digital biomarkers to then be trained using AI and ground truth data. And the reality of it is is that it becomes frighteningly accurate, and really creepy, accurate, meaning that we have the ability of telling whether you have mild cognitive impairment with a 99% statistical accuracy. And we're actually now going through breakthrough to do something I'll show you in a minute. That's even more exciting than that. And so what does it look like? And so really, what we do is we actually just create activities of daily living, we simulate them on your phone, and we have you do these sorts of tests, as you're holding on one hand, you're sort of, you know, sort of leveling it or poking on dots that come up or using AR to create a situation like go put this object down virtually, and then come back and find it. All this takes less than 10 minutes, but we collect about 15 megabytes of data and 800 Digital biomarkers that really bring back strong statistical evidence in terms of specificity and sensitivity around neurological disease. We've trained our AI to really look up on all the continuum of Alzheimer's disease. And now we are progressing into Parkinson's and other neurodegenerative diseases, because we have found that all of these diseases of the brain actually have subtle and sometimes not subtle digital phenotypes of disease, which I think it's just completely fascinating because it really does create a whole new realm of understanding the brain and unlocking what it's trying to tell you when it's not doing well. For anybody that has heard about COVID long haulers, we actually have an 86% accuracy of diagnosing COVID long haulers. And we stumbled on it. Because our normal population we did 1000 People study in q4 of last year, and 264 of those people got in that had confessed to be healthy and had no prior family history of neurodegenerative disease. But our AI came back and said these 264 Don't look like the same. And so basically, that population had then gone back on intake, either had gone to the hospital or not, but otherwise it recovered from COVID. Or at least they thought they recovered. So I do think that using a smart device and tweaking every sensor on it to sit there and go through a self guided exam really is I think the future of neurology. In this case, you can see the fact that yes, we can tell the in between healthy and MCI or 99% but miraculously, we can tell you if you have symptomatic amyloid. No I'm not pausing because of out my words, I'm pausing, because let's think about that. So for those of you don't know, amyloid is considered the first thing that goes wrong in the brain that then ultimately gives you Alzheimer's, which you probably don't know is it 20% of the whole population of the planet 50 and older are starting to accumulate amyloid. And so when you think about Alzheimer's, it's twice as big in terms of a market than diabetes. And so what how do you sit there and take 5,400 PET scanners on planet Earth and scan the population for amyloid, if you now have therapies that are pointing for early detection and early intervention, before amyloid starts to sort of evitable eat all holes in your brain. And so quickly, what we're doing is we're really expanding to where we are going in terms of regulatory right now, we're 510 K exempt around the world as a computerized cognitive assessment aid. What we're now going for with REG regulatory approval is that we want to be adjunctive diagnostic. And this adjunctive diagnostic would be the first time that you could use a smart device to diagnose mild cognitive impairment, which is part of the disease profile, up to 150 diseases and ICD 10. We then we'll also do an adjunctive diagnosis diagnostic to basically detect MCI due to amyloid. This is sort of a subsection of our performance, if you will, we have already generated $14 million in revenue from pharma. We've generated more than that, in the last 10 months of sale. We started commercializing our technology in October of last year, and so we've not quite hit 12 months yet. We will do about four to $5 million of revenue this year, and it will continue to climb. But if you just tease out what's going on in sort of the CNS trials perspective, there's a big there's a big market there. One of the things that many of you may not know is that 60% of the cost to build a drug for the brain goes to diagnostic testing, and cognitive assessment, the cognitive assessments plural. And so in this case, we believe that we'll get a junked of diagnostic status with the FDA at the end of 2024. And we're working in parallel to generate a new code, a new code that would diagnose MCI as well as MCI dude ad. We have a great team of people, you know, Antonella, our chief medical officer, we were able to recruit her from Biogen. , she was a lab manager for those who invented Agicle. And so we have just a good group of people that are really obviously excited about, you know, neurology and neurological diagnosis being more than Gestalt and being more than a three year diagnostic odyssey. And then I would just finish up by saying that I believe that all things in digital have the opportunity to be democratized. And with this, you have the opportunity of using a platform sort of way to reach an entire audience. And so not only do we help pharma build better and faster drugs for treating neurological conditions, but we also are a platform that extends into educating the consumer to self test, as well as the provider to use is an opportunity to sort of screen there's a half a dozen MC eyes that are due to dementia and Alzheimer's related conditions of that family than how do they treat and understand the other 240 something, right. And so I think a platform is really a great opportunity to not only monetize the entire ecosystem of healthcare, but really not democratize that people can self activate. And I think self activation is really important. Maybe we should talk about pre diabetes. Or we used to talk about diabetes as if that was sort of it you were either it was buying, you know, with binary you had it or you didn't have it. Now we talked about pre diabetic, I think we're now getting to a place where have sensitive enough equipment, we can start to think about pre neurodegenerative diseases, we can start thinking about the preclinical phases, where I think drugs will have the best opportunity, lifestyle intervention and other sorts of management that will help us remain at the top of our game when it comes to cognitive cognitive performance. Thank you very much for your time.

 

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