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Why is this Company combining Artificial Intelligence and Psychedelics to address Mental Afflictions

Dave Jackson Dave Jackson, Stockhouse
1 Comment| May 11, 2021

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(Click image to play video)

Did you know that in Canada, it is estimated that by the age of 40, half of the population will have, or will have had, a mental illness? The recent surge of interest in psychedelic drugs is due to their potential for more effective treatment.

Case in point is Calgary AB-based MedXtractor Corp. (MXT) (CSE.MXT, OTCMKTS: MXTTF, Forum) and its SHAMAN platform. SHAMAN is a machine-learning system designed to generate probabilities of a range of afflictions and the treatment potential of psychedelics.

In this fascinating video podcast, Stockhouse Media’s Dave Jackson was joined by company Founder and President of MedXtractor, James Durward, to give investors a brief background on MXT and get them up-to-date on all things MedXtractor.


SH: Jim, thanks so much for joining us today at Stockhouse.

JD: Hi, Dave. Thanks for having me on.

SH: So Jim, let's start off by providing us a little bit of information about yourself and MedXtractor.

JD: Sure. I've been developing advanced technical solutions for over 25 years and I've got a couple of patents under my belt. One of my projects involve large-scale data conversion, image analysis, and pattern recognition. It was complicated stuff, and all the programs had to be written from scratch. At one point we had over 20 computers working full time for almost two years, just to convert images into a format that computers could read. I wrote the specifications and drove it from concept all the way through to commercialization. Medxtractor the company started life as a manufacturer of small-scale CO2 based essential oil extractors. We now sell them worldwide and we're a market leader in that horizontal. I started watching the psychedelic space a couple of years ago. It's focused on mental illness applications and what really got my interest were some shocking misdiagnosis statistics I came across.

SH: And this is where SHAMAN came from?

JD: Essentially yes, I've seen misdiagnosis rates well over 70% for a variety of mental illnesses. In the case of bipolar disorder, we see them over 90%. When I looked around the psychedelic space, it was all about, could this drug replace that drug? I couldn't find anybody addressing the misdiagnosis problem.

SH: How could the effect of a drug be known on an illness? If the illness was misdiagnosed.

JD: Precisely. First you have to figure out what causes the misdiagnosis. Misdiagnosis rests on the size and relevance of the available data and the ability to correlate new data with existing data. That's the way we learn. That's the way opinions are formed and opinions in the medical world called a diagnosis. If you're trying to diagnose something in the limited amount of time and you don't have sufficient data and you're constantly interrupted, your diagnosis will probably be suboptimal, lack of data, lack of time and interruptions are the three fundamental causes of misdiagnosis. So, I decided to build a high quality reference database and combine it with uninterrupted machine learning to create a diagnostic platform. I don't see this as a medical problem. It's a data and data correlation problem.

SH: So, this is how your past date experience fits in?

JD: Yes, I've been here before. Shaman is an application that sits on top of the platform and is designed to provide probabilities of mental illnesses and predict probable drug effects. MedXtractor owns both.

SH: Can you expand on this?

JD: There are numerous mental illnesses each with its own brainwave pattern, drugs can cause changes in the brain. And brainwaves are a way of measuring the effect of a drug on the brain. This image shows a baseline and an abnormal reading, the wider the differential, the worst the situation. In some cases, drugs can bring abnormal patterns back into the normal range, but unfortunately drugs can have serious side effects, addictions, and even new illnesses can result. And when you add the misdiagnosis problem, you end up with a very, very big problem.

SH: You've mentioned a reference database. What is it? Where do you get it? And what can it be used for?

JD: The reference database is the foundation of everything it's made up of proprietary data records. These records are collected under strict conditions to maximize their cleanliness, relevance, and coherence. Top, top quality data to maximize the quality of privacy. We collect these records at our own facility.

SH: That sounds like a lot of personal data. How do you deal with privacy issues?

JD: Once the record is in the reference database, we strip the contact information. This makes the record totally anonymous going forward. Shaman doesn't care who you are. It only cares why you are.

SH: The company recently acquired a provisional US patent for shaman's foundational processes. How significant is this for the company and what will the next steps be?

JD: It's always wise to crystallize intellectual property when proprietary approaches are involved, I wrote and filed the provisional patent and I signed it over to the company for a dollar. I am a very large shareholder, probably the largest shareholder in the company. And I like to have my interests aligned with the other shareholders. Our patent attorneys are now preparing to file a full application. As far as the reference database is concerned. It's 100% owned by MedXtractor.

SH: What's the company's overall business model, and how does it generate cashflow?

JD: Our extractor division continues to fight cashflow, it’s pretty stable. For SHAMAN we expect licensing fees from researchers and practitioners and the underlying platform can generate application developer fees and speaking of applications, you've probably heard of those DNA testing kits, 23andMe and ancestry DNA. They use your DNA, which is essentially your genetic record to tell you about your past. Fitbit, Apple EKG, and some heart rate monitors all provide information about the present. And while it's interesting to know the past and important to know the present, what people really want to know is the future. Particularly as it relates to their health, a promise of machine learning is the ability to generate high probability health predictions, but even machines can't do it without a reference database. And we are adding records daily to ours.

SH: How big is the market for this type of thing?

JD: DNA tests, Fitbits, Apple watches are all part of the mobile health revolution. It's called M health. And there's a huge appetite for this. It's already around 50 billion and it's expected to grow to almost 170 billion over the next seven years as more and more people become proactive with their health.

SH: And finally, Jim, is there anything else you'd like to cover that I might have missed?

JD: To give you an idea as to the M health company valuations 23andMe has entered a financing deal at values of that $3.5 billion. Google just bought Fitbit for 2.1 billion. These prices are based largely on the data these companies have, considering medic structures, market capital, less than 8 million. It has over 2 million in cash and no debt and ongoing cashflow. And it's referenced database is growing every day. I believe MXT represents a very good investment opportunity. I hope you agree.

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FULL DISCLOSURE: This is a paid article produced by Stockhouse Publishing.

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