One Urine Test Can Detect 50 Diseases Before You Ever Feel Sick | #193

We started talking and saying, look, you know, the dog is smelling the urine and the nose is detecting the things that evaporate from the sample. How can we replicate this result with technology?

They built a fully AI hospital. No humans. They treated tens of thousands of patients. You walk in, it's a fully AI-equipped hospital. It's absolutely incredible.

I want to optimize the most precious resource we have with the technology that I have in my hands. And the most precious resource we have is time. It's doctors' and nurses' hours in the day that they can see patients and actually do medicine and not fill out forms. I don't know of any physician who can keep up with new technologies coming to market. Why not use technology to help you with that?

And I think with the way— the new way of how medicine is done, it absolutely needs AI because you're actually uncovering layers and layers of data that sometimes are subclinical manifestations of conditions. Hello, welcome back to the Dr. Joy Kong podcast. You know, my mission here is to make sure that you live a longer, happier, and healthier life. So today, I'm so honored to have a guest with us to teach us about technology in medicine and what we can do to detect diseases earlier. So I'm really excited about our conversation. And, uh, Diane's So happy to have you here.

Thank you very much. It's a pleasure to be invited.

So Dayan is a co-founder of Luventix, is a diagnostic startup using AI to detect over 50 diseases from a single urine sample. So that's an idea that came from him watching a study about dogs detecting cancer by smell. He has navigated FDA processes and clinical trials for nearly a decade and is also the founder of Panaton.

Correct.

It's a health IT firm specializing in connecting different healthcare systems and hospitals and labs and clinics all across the US. So thank you so much for being here, Dayan.

It's a pleasure. Thank you very much for having me, Dr. Kong.

I'm so curious about what you found out about this diagnostic tool. We all know that animals are very intelligent. They've used animals to detect seizures and, in this case, cancer. So what was the study? What popped into your sphere?

It's a funny story, actually. One of my two co-founders and I were sitting in his home after a day of skiing. Watching television and we saw this TV program of dogs smelling urine samples and sitting down when they detected cancer. And, you know, both of our backgrounds are technology. He's a biophysicist and spent most of his professional life doing drug discovery using machine learning methods and AI technology long before it was sort of a household word like it is been now for 4 years or so. And we started talking and saying, look, you know, the dog is smelling the urine and it's— the nose is detecting the volatiles, the things that evaporate from the sample. So what is that? How can we replicate this result with technology? Well, the nose of the dog is essentially a gas chromatograph. You know, it's quantifying the presence of certain molecules in the vapor or the the volatiles. And I said, well, what happens then? Well, then the brain's dog is doing classification. It is determining whether the molecules that the nose detected are indicating the presence of a condition or the absence of a condition. So how can we do that? Well, you know, we have now artificial intelligence technology, or more properly, it's a branch called machine learning, which allows us to train models to do classification, basically saying, give us data from all population of patients that have a condition, give us data from population of patients that don't have the condition, and more than likely, uh, in most cases, not all cases, we can build a little bit of software to then detect and classify an unknown sample in one of the two categories. It's not quite as simple as that, obviously, but that is the fundamental theory, which is very straightforward.

Yeah. So what, what disease did you go after first?

Well, uh, Martin, my co-founder, did his initial two studies as a proof of concept with bladder cancer and prostate cancer, and they were very small studies, but, uh, they demonstrated that the technology was viable, that we are actually being able to detect the signal and do classification. It took us a few years, uh, to start Luventix, uh, and then, uh, fund our first, uh, clinical study in which we did, um, four different GI diseases: colorectal cancer, Crohn's Crohn's disease, SIBO, which is a small intestine bacterial overgrowth. And so we are in the final stages of closing that study and you can, you can find it on clinicaltrials.gov. It's IRB approved with about 1,250 patients and the results are actually very, very encouraging. We, we are able to build models that do classify the, or correctly identify the presence of the conditions.

Hello, my loyal listeners. I want to interrupt this podcast for just a second because I want to let you know that if you're looking to help solve a major health issue, or you're looking for health optimization and just for longevity purposes, you can find us at Chara Health. We are considered the leader in the regenerative medicine and longevity space, and we utilize modalities like stem cell therapy, peptide therapy, plasmapheresis, ozone treatments, laser therapy, all to create a beautiful symphony to get you to where you want to be. You can find us at www.chara-health.com. That's C-H-A-R-A. I'm just curious about, since you're using AI technology, are there some major misconceptions when it comes to AI and healthcare?

That, that, that could take probably several conversations rather than one. I spend a lot of time actually in my day job working on artificial intelligence. For personalized medical records analysis and summarization. Fundamentally, healthcare cost is growing faster than GDP across the world, and that's unsustainable. I personally believe that artificial intelligence technology is one very powerful tool to allow us to bring that cost, to control that cost. And so, you know, as I'm an engineer and I say, how do I solve the problem? I want to optimize the most precious resource we have with the technology that I have in my hands. And the most precious resource we have is time. It's clinical time. It's clinicians' time. It's doctors' and nurses' hours in the day that they can see patients and actually do medicine and not fill out forms and type data into Epic, right? Yeah. So the AI is actually very good at this. And you see the deployment of ambient listening technologies and note-taking that automates that. On the front end, what we're doing is we're saying, Let's have the AI prepare the full summary of the medical history of the patient before they walk into the door. So you can save, you know, the first 5 to 15 minutes interviewing the patient and doing the anamnesis, but be able to jump, you know, to have a very summarized view of what the current complaint is versus the full medical history and be able to hit the ground running. See the summaries of previous diagnosis, current medications, do the medical reconciliation automatically, see any, you know, chronic conditions, surgeries, etc., etc. And so that technology is available today.

Oh yeah, human doctors can miss things.

30, 40 years of medical records, when you drop them and you see, you know, you have hundreds and hundreds of pages of stuff, which part of it actually could be related to what I'm complaining from today, you know, so being able to see the full picture and not miss something, be able to see a summary of possibly relevant pieces of information, be able to have a menu of possible diagnosis. You don't miss something and possible treatments, which quite frankly, I don't know of any physician who can keep up with, with new technologies coming to market. Why not use technology to, to help you with that?

And I think with the way the new way of how medicine is done, it absolutely needs AI because I can see how, you know, functional medicine, I think, is taking the forefront of where the medicine is going because you're actually uncovering layers and layers of data of, you know, the sometimes are subclinical manifestations of conditions.

No, absolutely. I can speak to that from personal experience. My, again, very close friend's daughter for several years developed brain infection condition that was very, very rare, maybe only a few cases in the country and literally the way it was diagnosed by trying different treatments until something was found that worked for her. And very complex case, you know, pre-AI. But I would like to believe that if we had the AI tools that we have today, the physicians would have seen additional possible treatments early on rather than having to navigate specialist to specialist and, you know, 10 states until, you know, everybody's suggesting, well, maybe it's this, maybe it's the other thing until they hit the right treatments at a half. That's what it is.

Exactly. Yeah. Are you— you've heard about that AI hospital in, in China? Actually, it's in the university that I grew up in, Tsinghua University. They, they built a fully AI hospital, no humans.

I have not. I'm ignorant of that. That's very interesting.

They treated tens of thousands of patients. What one thing that China is not short of is people. So they have a lot of patients. And doctors are, are incredible because they've seen— by the time they finish medical school, they've seen more patients than a doctor in the US who I've seen in 10 years, right? So that's the power of experience. But they're using, yeah, AI everything. You walk in, it's a fully AI-equipped hospital. You don't need human. It's absolutely incredible. That would be a place to visit.

For now, until you have to get some surgery that you still probably want a human surgeon supervising at least. Oh, I do appreciate my human orthopedic surgeon very much, even though I know he's using robotic technology to do the procedures.

Wonderful. So when you look at the future, so in the next 5 years, what does success look like for Luventix?

Diagnostics available in the market, ability to give a urine sample at the point of care, you know, when you're seeing your physician or to get a kit mailed to you at home and mail it back to a lab and get a panel result back. Even at the level of triaging conditions to put you on the right diagnostic pathway, that would be a success. Obviously, we are much more ambitious than that. You know, again, at the macro scale, if we can bring in technology which costs only a few hundred bucks but can do panels of dozens or theoretically hundreds of diseases, that puts population-level screening and early diagnostics into an economically feasible position. For us, the ultimate success would be, you know, to have a diagnostic panel based on our technology from a urine sample that costs so little that it's accessible to essentially anyone around the world.

Something like a pregnancy test. You can just buy it and then put your pee on it and then you get the results.

That's right. I mean, again, I mean, we go to a doctor now when we get sick, but we can catch conditions before we feel bad enough to go to a doctor. Anywhere between 3 to 18 months in advance if we had the screening tools at a cost-effective level. Fundamentally, you know, I personally believe that the annual exam should cover dozens, if not hundreds, of conditions, not just 4 or 5 killer diseases.

Right, right. Amazing. Well, thank you so much for your, your, uh, courage and, uh, your drive to make something new in the world and, and bring something that's super helpful and hopefully saving a lot of lives. Yeah, so thank you for your work. And where can people find you and follow your work and, and follow your progress?

Our site is levantix.com, and the moment we have tests available, we will be marketing them. Maybe we'll even have another conversation with you and tell you about the products in the market at that point.

Thank you for watching and listening. If you enjoy this kind of content, please subscribe and turn on your notification bell so you don't miss any of my future content. And if you want to learn more about regenerative medicine or other modalities in anti-aging medicine, please go to my YouTube channel, Joy Kong, MD, and there are all kinds of videos to help you keep learning.