Thursdays 5:00pm - 6:00pm (EDT)
EPISODE SUMMARY:
The audience will get to discuss with the participants Questions about main discussion points in the book: The Great Healthcare Disruption including AI, Vaccines, Big Tech Innovations and Genetic Treatments
After having discussed the book in detail last week, now we get to ask the pivotal questions live with Dr. Marschall Runge along with David Yang who can get to the Technological Innovations meant to serve as disruptions towards refinement of healthcare delivery.
This will be a continuation of promoting the book and serving the audience with a more detailed summary of the disruptions in healthcare that are meant to serve us.
Website: https://drmarschallrunge.com/
LinkedIN: https://www.linkedin.com/in/marschallsrunge/
Facebook:
https://www.facebook.com/people/Marschall-Runge-MD-PhD/61552211200167/
#HealthcareDisruption
Tune in for this healthy conversation at TalkRadio.nyc
Host Frank R. Harrison opens the episode by celebrating the success of recent broadcasts and doubling down on the importance of The Great Healthcare Disruption, a book now central to the season’s discussions. Guest David Yang brings his perspective from the medical device industry, emphasizing how diagnostics and molecular testing have revolutionized early disease detection, especially in contexts like HIV and COVID-19. Together, they critique the fractured state of U.S. healthcare, highlight the economic realities of innovation, and advocate for transparent, preventative, and technologically integrated systems to better serve patients in a rapidly evolving landscape.
Frank R. Harrison and David Yang delve into the complexities of preventative medicine and healthcare economics, highlighting how unplanned illness and lack of transparency strain patients and systems alike. Yang explores how emerging technologies and faster information dissemination—especially through social media and diagnostics—can prepare us for future healthcare crises more effectively than traditional systems. They also reflect on the evolution and limitations of retail healthcare, noting its initial promise for greater access and convenience but also the risk of dehumanized, transactional care in contrast to comprehensive primary physician relationships.
Frank R. Harrison and David Yang explore the consequences of ending telehealth reimbursement, particularly for rural and aging populations who may lose both access and infrastructure. They present a compelling vision for next-generation care through at-home diagnostics and telehealth integration—what Yang dubs a “Fluber” model—emphasizing the need for innovation, accessible delivery systems, and continued government investment. Drawing parallels to past initiatives like the Human Genome Project and Operation Warp Speed, they highlight how public-private collaboration is essential to creating patient-centered, future-ready healthcare solutions.
Frank R. Harrison and David Yang explore the promise of AI in discovering new therapeutic applications for existing drugs, such as uncovering unexpected benefits or off-label uses through population-level data analysis. They highlight how AI can dramatically accelerate the process of identifying safe, effective treatments by leveraging real-world data, bypassing costly and time-consuming traditional trials. Concluding with a call to responsibly integrate AI into clinical workflows, they stress the importance of patient privacy, equitable access, and the collaboration between technologists, clinicians, and policymakers.
00:00:52.980 --> 00:01:18.869 Frank R. Harrison: Hey, everybody, and welcome to a new episode of Frank about health right here on Talkradio, Dot, Nyc. And all you Youtube, linkedin Facebook and twitch listeners. Especially you Linkedin viewers out there who saw the last 2 weeks with Dr. Marshall Runji and Phyllis Quinlan, and last week, when we promoted heavily with the QR. Code on the top of your screen or on the bottom, depending on which part of zoom you're looking at right now.
00:01:18.870 --> 00:01:27.830 Frank R. Harrison: where we had over 400 viewers on Linkedin, and I want to thank all of you for watching the show. I hope a percentage of you actually went out and bought this book.
00:01:27.830 --> 00:01:40.839 Frank R. Harrison: and for that reason alone I'm letting you all know that every future episode of Frank about health will feature this QR. Code because this book is pretty much the narrative for this particular season of frank about health.
00:01:40.920 --> 00:01:48.649 Frank R. Harrison: Well, there are 2 reasons for that. One is, we have constant ongoing chaos in traditional media every single day.
00:01:48.660 --> 00:02:14.890 Frank R. Harrison: with regards to cuts, to Medicaid, cuts to your medications, expenses no longer being covered, the list goes on, but, more importantly, Dr. Marshall Runji, who has promised to be here today, is actually going to appear at any point, and we just don't know when, because he's involved in such chaos right now at his organization. So it serves as an opportunity for us. Me and David.
00:02:14.890 --> 00:02:29.269 Frank R. Harrison: who was here a couple weeks ago, when we paid tribute to our Alma Mater Brooklyn Technical High School. But he has experience in the healthcare space which I'm going to let him talk about in more detail, and at the same time he also
00:02:29.450 --> 00:02:32.999 Frank R. Harrison: has read the book and has a lot to say so.
00:02:33.360 --> 00:02:56.780 Frank R. Harrison: Marshall Runji has agreed to come in next week. David will probably be back, but also bring back another guest, because this book is so complex and is so, must have must read whether you're a patient, a professional in the industry, or even just someone who wants to get your honest information while a lot of it is being cut away. Now, that being said, I must issue a disclaimer.
00:02:57.080 --> 00:03:26.920 Frank R. Harrison: These are not the thoughts or views of talkradio, dot, Nyc. Or of this podcast frank about health. But they are my reactionary views as a patient advocate, as a caregiver, as a patient with an ongoing illness, epilepsy, and, more importantly, I need the truth to be out there for all my listeners and viewers have been with me for now going on 4 years. That is right. 4 years ago, on the 21st of May, I debuted the show
00:03:27.050 --> 00:03:51.369 Frank R. Harrison: after we were in the middle of the covid pandemic, May 2021. So, in honor of my anniversary on Talkradio dot Nyc. In honor of our 40, or, in your case, 41 years at Brooklyn Technical High School, David, and in honor of Dr. Marshall Runji, who, I hope, joins us at any point during the hour we are going to continue to talk about the great healthcare disruption on this show
00:03:51.440 --> 00:04:07.990 Frank R. Harrison: with 3 particular focus on this particular show because they are revolutionary, and they are ongoing and changing every day, and 2 of them are hard hitting and kind of personal. If you don't mind my saying, David, when it comes to the work that you've done
00:04:08.200 --> 00:04:28.309 Frank R. Harrison: pharmacies as well as new generation medicines and technical tools that you've used in the trade, and then, of course, we'll wrap it up with artificial intelligence, which is my favorite issue affecting the space. So that, all being said, David, I'll let you introduce yourself. You're the man.
00:04:29.730 --> 00:04:36.750 Frank R. Harrison: Thank you again for coming and for really helping to promote this book. And more importantly, hopefully, when Marshall gets on.
00:04:36.850 --> 00:04:39.159 Frank R. Harrison: really given the hard-hitting questions.
00:04:39.500 --> 00:04:45.529 David Yang: Yeah. Well, thank you, Frank, for having me. I'm hoping that Dr. Ranji Marshall
00:04:45.690 --> 00:04:47.789 David Yang: will be able to make it on. But
00:04:48.790 --> 00:05:04.469 David Yang: you know, just for the audience to know Frank. Dr. Ranji Marshall and I had a call a little while ago, and you could tell. You know he's in the middle of a lot of different things, plus he's about to retire. So he's probably planning for that. And then there's a lot of chaos going on.
00:05:04.880 --> 00:05:05.270 Frank R. Harrison: Yeah, but.
00:05:05.910 --> 00:05:15.000 David Yang: But basically. You know, I'm here. At Frank's invitation, I I spent most of my career in the medical devices industry.
00:05:15.561 --> 00:05:20.088 David Yang: We spent a lot of time building tools that really help
00:05:20.870 --> 00:05:28.409 David Yang: life science and diagnostics. So basically, the most basic thing, most basic idea is
00:05:28.840 --> 00:05:31.350 David Yang: you're sick. You go to the doctor.
00:05:31.490 --> 00:05:35.279 David Yang: they will do a bunch of physical checks, and then they will do some tests.
00:05:35.450 --> 00:05:36.780 David Yang: And so my
00:05:36.950 --> 00:05:44.500 David Yang: career has really been focused on developing the tests and ensuring that they they are, they do what they're supposed to do
00:05:45.200 --> 00:05:47.750 David Yang: and provide value to the clinician.
00:05:48.311 --> 00:05:54.100 David Yang: If you you know, if if you think about it, you know, a thousand years ago.
00:05:55.110 --> 00:06:03.689 David Yang: you know, if you were sick a thousand up to 200 years ago, if you were sick. The only way to find out if you were sick is you didn't feel well.
00:06:04.090 --> 00:06:07.419 David Yang: You had a fever. You were nauseous.
00:06:08.670 --> 00:06:13.819 David Yang: Skin change rash. But but basically there's a body's response.
00:06:13.960 --> 00:06:25.329 David Yang: And then, about a hundred years ago, they discovered all these proteins and markers in your body that help diagnose what is making you sick.
00:06:25.710 --> 00:06:38.170 David Yang: And and so those antibodies, the immune response system. That that's great, too. But but there's a delay between the point that you get sick
00:06:38.630 --> 00:06:50.670 David Yang: and the onset onset of symptoms and the onset of an immunological response. And so that basically can take months a case that
00:06:50.810 --> 00:06:54.299 David Yang: Frank, you and I, we kind of lived through in the eighties is HIV
00:06:54.440 --> 00:07:01.649 David Yang: person who's HIV positive may not have any symptoms may be serologically negative.
00:07:02.660 --> 00:07:06.440 David Yang: but they have HIV, and so they can start spreading the disease.
00:07:06.670 --> 00:07:21.060 David Yang: But most recently, over the last 25 years ago. So there's this new modality of testing called molecular diagnostics, where we can actually now find at low levels, the actual infectious agent.
00:07:21.090 --> 00:07:37.780 David Yang: whether it's HIV virus or covid or influenza, so much so that you can be perfectly healthy and walk into a doctor's office, but if you're at risk of being HIV positive they will be able to take a test and tell you before you leave the office
00:07:38.000 --> 00:07:41.759 David Yang: that you're HIV positive, even though you feel perfectly fine.
00:07:41.890 --> 00:07:49.139 David Yang: So the clock of when you get sick has gone from well, you have to feel sick to
00:07:49.800 --> 00:07:53.000 David Yang: predictive. Hey, you know what you're infected. You will be sick.
00:07:53.620 --> 00:07:56.079 David Yang: and as we'll go to later.
00:07:56.390 --> 00:08:19.550 David Yang: there is this hypothesis that AI will be able to predict, based on your history and the population's history. What's going to happen to you in 2 years in 3 years that you can now take even more preventative care, so that you don't decompensate. So these things are all really exciting. And I think Marshall's book
00:08:20.100 --> 00:08:28.460 David Yang: captures a lot of aspects of that because it talks about. You know one of the things. It's funny I keep referring to my notes because I I have feel free to.
00:08:28.460 --> 00:08:28.800 Frank R. Harrison: Do that.
00:08:29.150 --> 00:08:32.830 David Yang: Pages of notes, to talk to, to Marshall about.
00:08:33.240 --> 00:08:41.810 Frank R. Harrison: Well, not only that I find myself reading actually his words when I need to, especially because he's the one that's gonna get the word out.
00:08:42.380 --> 00:08:48.170 David Yang: But but one of the things that you, Phyllis and Marshall talked about and is in his book is
00:08:49.040 --> 00:08:54.250 David Yang: the sentence. You know we speak about a single healthcare system that is not reality.
00:08:54.570 --> 00:08:55.180 Frank R. Harrison: Right.
00:08:55.310 --> 00:09:01.549 David Yang: What health care in the Us. Represents is a vast construction of independent parts and problems.
00:09:01.870 --> 00:09:05.300 David Yang: And I wrote down in my narrative that I can't agree more.
00:09:06.073 --> 00:09:11.369 David Yang: This is something that I had to basically learn over a long period of time.
00:09:12.246 --> 00:09:17.560 David Yang: As a Phd scientist, I was trained to build the next cool widget.
00:09:18.140 --> 00:09:30.960 David Yang: and what I didn't understand at the time is that it doesn't really matter how cool the widget is. There has to be. You have to get involved in the entire healthcare ecosystem. If you want that widget to be disruptive.
00:09:31.290 --> 00:09:32.020 Frank R. Harrison: Correct.
00:09:32.480 --> 00:09:36.610 David Yang: So what I mean is, you know, everything has to start with a clinical problem.
00:09:36.870 --> 00:09:48.270 David Yang: So you know. So if you so before you even think that there's a problem. You should probably go and talk to a bunch of doctors, and that one aspect of the healthcare ecosystem
00:09:48.370 --> 00:09:52.310 David Yang: which is the clinicians. If you identify a real problem
00:09:52.710 --> 00:10:01.019 David Yang: and you come up with a solution, I'm already jumping to solution, which is something bad to do. But I'm going to do that. But if you're forward thinking.
00:10:01.890 --> 00:10:21.839 David Yang: if you have a widget, then you got to go figure out well, if this widget is going to be applied to a physician's office? Are they capable of even working with your widget? Are they trained to do that? How does that interfere with their workflow? Do they have enough people do. They have the 220 voltage that may be required?
00:10:22.070 --> 00:10:24.380 David Yang: It's a barrier to the adoption.
00:10:24.590 --> 00:10:30.040 David Yang: And then another part of it is, you know, the the financial aspects.
00:10:31.171 --> 00:10:37.350 David Yang: I think Marshall mentioned this in conversation a couple of weeks ago that you know
00:10:37.560 --> 00:10:44.190 David Yang: no one wants to talk about the fact that medicine is you know, is a is a financial aspect.
00:10:44.400 --> 00:10:46.200 Frank R. Harrison: It's a business.
00:10:46.330 --> 00:10:47.170 David Yang: What?
00:10:47.330 --> 00:10:48.970 Frank R. Harrison: It's a business at the same time.
00:10:48.970 --> 00:10:59.050 David Yang: It's a business, and we all live in a capitalist society. At least that's what we say. So and so the idea that health care should be exempt from that is a little bit crazy.
00:11:00.540 --> 00:11:10.880 David Yang: you know. Patient care providers, physicians, nurses, the phlebotomists. They all need to feed their family, and so they need to make money. So there is this
00:11:11.536 --> 00:11:18.650 David Yang: there is this economic aspect of having getting your widget into the marketplace.
00:11:19.120 --> 00:11:19.640 Frank R. Harrison: Right.
00:11:19.640 --> 00:11:27.330 David Yang: You know, how is it gonna help the the ecosystem? Does it make the response better? So you save money
00:11:27.620 --> 00:11:35.270 David Yang: with preventative care, or, you know, getting to patients before they have a decomp, the
00:11:35.780 --> 00:11:39.054 David Yang: not decompose. But before they get sicker,
00:11:39.990 --> 00:11:41.260 Frank R. Harrison: A decline.
00:11:41.675 --> 00:11:42.919 David Yang: Declining. Yep, yep.
00:11:42.920 --> 00:11:43.870 Frank R. Harrison: Yes, yes.
00:11:43.870 --> 00:11:47.760 David Yang: You know. Are you making a manual task more automated?
00:11:48.513 --> 00:11:50.529 David Yang: Because here in the Us.
00:11:51.085 --> 00:11:57.129 David Yang: As Phil has pointed out, I believe. You know, healthcare people.
00:11:57.604 --> 00:12:00.950 David Yang: healthcare providers. There are just fewer and fewer of them.
00:12:01.410 --> 00:12:15.619 David Yang: And and so, unfortunately, we need to automate a lot of these things. And so, you know, Marshall Runji's book is really great at taking all these various aspects and and tying them in together.
00:12:16.220 --> 00:12:20.766 Frank R. Harrison: Yes, no, you, you know it's very interesting. The word disruption is kind of like
00:12:21.590 --> 00:12:25.340 Frank R. Harrison: I don't know if you call it a misnomer, or, if you call it a
00:12:25.670 --> 00:12:37.810 Frank R. Harrison: a word that is kind of used in the opposite direction, because think about it. We all try to live our lives daily with a level of homeostasis balance.
00:12:37.810 --> 00:12:38.360 David Yang: Yep.
00:12:38.360 --> 00:12:40.900 Frank R. Harrison: Nutritious health focus
00:12:41.050 --> 00:12:52.949 Frank R. Harrison: hopefully, a good quality of life, good quality of mental health. And then every now and then we get an illness, or we had the pandemic right, which was a big disruption. But the whole disruption
00:12:53.190 --> 00:12:58.910 Frank R. Harrison: is the illness itself, you know, and so we're never prepared
00:12:59.150 --> 00:13:08.179 Frank R. Harrison: because you want to live and prepare in a society or an ecosystem, as you called it, when you're already living a good quality of health, a good quality of life.
00:13:08.610 --> 00:13:12.150 Frank R. Harrison: you know. So I think, why this book is so
00:13:12.720 --> 00:13:17.120 Frank R. Harrison: like to me, in my view, a movement is because
00:13:17.350 --> 00:13:37.039 Frank R. Harrison: our healthcare issues are now becoming the norm, especially as our social system is slowly taking away the transparency of what we need to be mindful of, and therefore, as a result of not being mindful or not being given the information to be mindful, we're opening up the doors to become sick more often.
00:13:37.360 --> 00:13:38.760 David Yang: That's right. That's right.
00:13:38.760 --> 00:13:41.680 Frank R. Harrison: You know, and so go ahead. You were gonna say.
00:13:41.680 --> 00:13:59.729 David Yang: No, just one last comment. So as I'm reading through this book, I work with a lot of startups, and I work with a lot of university students, postgraduate students. This is really a great book for people who are looking to disrupt the healthcare industry by learning the lessons
00:13:59.730 --> 00:14:16.609 David Yang: of how disruptors worked in the past in the present. And what are the gaps? What are the traps? So so I'm going to go to university actually after this podcast and talk to some masters and Phd students. And I'm going to bring this up that, you know.
00:14:17.530 --> 00:14:23.170 David Yang: Don't worry about having the best thing in the world figure out how to get it into become a real disruptor.
00:14:23.460 --> 00:14:33.669 Frank R. Harrison: Exactly now, ladies and gentlemen, we're going to go to our 1st break, and when we return we will be still awaiting Marshall Ranji to join us, but we will be discussing 3
00:14:33.670 --> 00:14:58.859 Frank R. Harrison: particular chapters from the book that both David and I have some relative expertise in, and at the same time really have debatable questions about. And if you have questions out there, especially, you guys on Linkedin, please ask them away, and our engineer will track them and ask them. Live, and hopefully David and I will be able to answer them all right. Stay tuned right here on Talkradio, Dot, Nyc. And on all of our socials. We'll be back on a few.
00:16:41.290 --> 00:17:03.510 Frank R. Harrison: Hey, everybody, and welcome back. Remember the QR code that I just showed you during the commercial break as well as on the other corner screen right there is available to use right now using your QR code on your mobile phone or tablet, it'll link you into amazon.com. Anyone watching the show right now will just immediately be getting.
00:17:03.560 --> 00:17:12.880 Frank R. Harrison: you know, through Amazon Prime, or whatever your delivery service is. You'll have the book within a day or 2, and you'll get to know more about what we will be speaking out through the rest of the show.
00:17:13.470 --> 00:17:31.220 Frank R. Harrison: Now, David, you were onto something very big about the whole ecosystem. I mean, you've got our overall business ecosystem in this country, depending on the industry you're in. And then you're looking at healthcare, which is really the main way to stay profitable is to be in preventative medicine.
00:17:31.370 --> 00:17:44.110 Frank R. Harrison: But that's our reality. Our reality is that you have elder populations that are getting sicker, whether it's because, you know, when you get older, your immune, your in your immune system declines.
00:17:44.630 --> 00:18:05.489 Frank R. Harrison: You know I've got a personal case of my cousin, who at a young age developed Alzheimer's, and is now having to deal with the financial ecosystem of a nursing facility totally unplanned for unexpected. So it disrupted pretty much the entire system that she was used to living with economically. Now that all being said.
00:18:05.630 --> 00:18:28.609 Frank R. Harrison: you're on to how, what's going on with all the information being parsed out or not being as transparent as it was during the last administration. It's almost inviting that to be the new norm. So did you notice anything in the book that reflected that, or that you wanted to really debate issues with Marshall on? That would be ways that we could
00:18:28.850 --> 00:18:35.340 Frank R. Harrison: still manage those issues with little to no information compared to where it's been. I mean.
00:18:36.230 --> 00:18:44.449 David Yang: Yep. Well, you know. Maybe it's not directly related to to the book, but I think that preparing for the next crisis
00:18:44.670 --> 00:18:45.565 David Yang: is
00:18:46.690 --> 00:18:58.179 David Yang: is it, in fact, a funny thing to say, because I think Marshall has pointed out that we don't know what the next crisis is. Gonna be right. So no one predicted Covid.
00:18:58.360 --> 00:19:21.589 David Yang: People thought respiratory infection could come back like the influenza of 1918. This was a respiratory infection, but it was not influenza. It was covid which has basically been ubiquitous, I mean, coronaviruses have been around for years and years and years, and it was this particular mutation that caused the biggest problem.
00:19:22.146 --> 00:19:27.353 David Yang: But but, Frank, I think that you and I touched on this a couple of weeks ago.
00:19:28.030 --> 00:19:35.929 David Yang: in light of the changes to the government programs. You know the jewels of the American healthcare system
00:19:37.240 --> 00:19:40.990 David Yang: being cut back. I think that a
00:19:41.140 --> 00:19:54.460 David Yang: an opportunity arises in social media that could be moderated, so that information can be gathered.
00:19:54.790 --> 00:20:01.589 David Yang: perhaps not as accurately, but certainly more efficiently than could otherwise exist.
00:20:02.154 --> 00:20:09.450 David Yang: An example that I that I use is back in the 19. Someone had related the story to me
00:20:09.600 --> 00:20:16.150 David Yang: that back in 1979, someone, I think, actually in Michigan, where Dr. Ranji is from
00:20:16.310 --> 00:20:20.369 David Yang: had noticed that a patient had died of a horse. Virus
00:20:21.950 --> 00:20:34.879 David Yang: horse viruses are ubiquitous, but most people it's not a big deal. Your immune system fights it. Your immune system is really a great system. It it prevents all sorts of little things from just never even impacting you.
00:20:35.010 --> 00:20:40.950 David Yang: But they discovered. They found this patient with a well that was weird, and then a second patient came up
00:20:41.310 --> 00:20:48.269 David Yang: with the same disease that killed them, and so they found that these patients were immunosuppressed.
00:20:48.730 --> 00:20:53.380 David Yang: and that's, you know, the beginnings of HIV and the Aids crisis.
00:20:53.640 --> 00:21:04.879 David Yang: And so, you know, they lacked at the time the social media to very quickly disseminate that information. It was probably published in a journal. It probably took time.
00:21:05.000 --> 00:21:09.789 David Yang: But now we have this opportunity, I think, with podcasts and with
00:21:10.658 --> 00:21:28.990 David Yang: you know, social media as well as you know, other Internet tools to be able to maybe have a more holistic, band aid to try to understand more quickly on how you know what's happening in the world, what's happening in the Us.
00:21:29.170 --> 00:21:35.450 David Yang: You know, there are journals that now have fast publications. They are reviewed eventually, but
00:21:35.570 --> 00:21:48.040 David Yang: the information is so important that it's more important to get it out and let people decide before they go through a full full peer review. So I think that there are some tools that can become available.
00:21:49.360 --> 00:21:50.210 David Yang: But
00:21:50.450 --> 00:22:01.110 David Yang: it goes back to the ecosystem. Who pays for this. How does you know, you know, how does the person who's running this get financially incentivized?
00:22:01.320 --> 00:22:25.740 David Yang: There's a lot of mistrust in the United States? I think that if if it was, you know, if it was Amazon there'd be a population of the segment says, Oh, no, I don't trust it, because Amazon just wants my money. Well, okay. So we're not going to let a private company do that. Well, how about you know an Ngo non-government organization? Well, no, they're just in it. To make money for themselves, would say another population.
00:22:25.880 --> 00:22:30.810 David Yang: And each one of these guys have, you know, the same microphone as
00:22:31.140 --> 00:22:34.082 David Yang: as maybe you know other people who are
00:22:34.870 --> 00:22:40.830 David Yang: it's the democratization. Everyone's got a voice. So at least a little bit to chaos.
00:22:41.150 --> 00:22:42.460 Frank R. Harrison: Yes, yes.
00:22:42.750 --> 00:22:53.270 Frank R. Harrison: no, I think if anything, you were also alluding to how the pharmacies are trying to capitalize on the limited population of
00:22:53.400 --> 00:23:09.329 Frank R. Harrison: of healthcare delivery as as indicated in Marshall's book. Was it something specific that also came to the conclusion that the because of the pharmacies taking a control in that it is undemocratizing healthcare delivery.
00:23:09.590 --> 00:23:13.099 David Yang: No, actually, the the whole idea, I think, of retail medicine
00:23:13.380 --> 00:23:20.600 David Yang: was to try to make care much more democratic, less expensive. Right?
00:23:20.730 --> 00:23:27.090 David Yang: You know you have a segment of the population that never goes to the doctor until they are dying.
00:23:27.090 --> 00:23:27.610 Frank R. Harrison: Too.
00:23:27.880 --> 00:23:31.310 David Yang: And then they go to the er which is the most expensive
00:23:31.520 --> 00:23:50.349 David Yang: portion of our healthcare ecosystem. And so these these urgent care systems have popped up that have been doing a job. But even now we see that a lot of the urgent cares are steering away from some of the more acute illnesses. But the retail medicine.
00:23:50.540 --> 00:23:54.689 David Yang: you know. I think, that the idea is great in the sense that
00:23:55.380 --> 00:24:01.670 David Yang: you know the Cvs. The Walgreens. They've got a brick and mortar place. They have many locations.
00:24:01.810 --> 00:24:08.109 David Yang: and if you're going to be there, for whatever reason that you can then get your you know your health check
00:24:08.240 --> 00:24:17.609 David Yang: performed. Perhaps if you have an acute problem, you you have a fever, and the urgent care is closed. You want to go there.
00:24:17.990 --> 00:24:25.020 David Yang: and and you know Marshall talked a little bit about how. Some of the companies are kind of backing away
00:24:25.250 --> 00:24:27.752 David Yang: from those models, some of the
00:24:28.350 --> 00:24:32.040 David Yang: the pharmacies and the retail companies.
00:24:32.600 --> 00:24:48.200 David Yang: and and a few years ago, when, as this was all developing the company that I was with, we, you know, we did a quite a bit of analysis on that. And you know, one of the things that people just don't understand is our healthcare system.
00:24:48.330 --> 00:24:54.840 David Yang: because of the economic aspects has been really optimized. So that
00:24:55.060 --> 00:24:59.960 David Yang: tests are done at the right time at the right place, but at the right cost.
00:25:00.300 --> 00:25:13.709 David Yang: And one thing that you see is that there are a lot of reference labs. These are the quest, the Lab corps, the hospital lab system, where they will literally run hundreds, thousands of tests per hour.
00:25:14.040 --> 00:25:22.039 David Yang: because, you know, Marshall talks about getting, you know, the getting the right healthcare to the right people at the right time.
00:25:22.140 --> 00:25:26.479 Frank R. Harrison: And sometimes you don't need those test results immediately.
00:25:27.210 --> 00:25:32.609 David Yang: I think that the retail medicine space was trying to capture some of those ideas.
00:25:32.840 --> 00:25:34.927 David Yang: and quite frankly, the
00:25:36.270 --> 00:25:42.760 David Yang: the what's the word I want to use. The characteristics of a retail health
00:25:43.813 --> 00:25:48.529 David Yang: diagnostic test. Again, which is my expertise. The instrumentation
00:25:48.740 --> 00:25:56.939 David Yang: is really different than for a reference lab. The things such as footprint. The machine has to be small. Machine has to be
00:25:57.777 --> 00:25:59.120 David Yang: easy to run.
00:25:59.720 --> 00:26:03.560 David Yang: So called over the counter, or clear waved.
00:26:04.210 --> 00:26:06.540 David Yang: they, the tests, have to be
00:26:06.650 --> 00:26:12.080 David Yang: relatively inexpensive. But, more importantly, the tests have to be fast.
00:26:12.710 --> 00:26:21.510 David Yang: because, if you know, if David is, is has a fever and wants to, you know, wants to forego our my normal
00:26:22.220 --> 00:26:24.150 David Yang: primary care provider
00:26:24.750 --> 00:26:36.493 David Yang: wants to go somewhere. He doesn't want to sit there for 3 h, 2 h, but and quite frankly, the Cvs don't want me there, either, because I might be making other their other people sick.
00:26:38.310 --> 00:26:41.399 David Yang: And so you know. And so I think that there is a role
00:26:42.010 --> 00:26:51.030 David Yang: for health care in the retail stores. But I think that the model has become less ambitious and more pragmatic as to the things that they do.
00:26:51.140 --> 00:27:09.260 Frank R. Harrison: Right, and also kind of I don't know if the right word is dehumanizing, but it becomes more transactional, and then what you find is that I can see how economically like the lab Corps and other quests laboratories have the volume discount approach because they're running thousands of tests a day or whatever it is.
00:27:09.260 --> 00:27:09.760 David Yang: That's right.
00:27:09.760 --> 00:27:26.539 Frank R. Harrison: But yet, when you get to see your Pcp. Or your specialist that ordered the test, that's when you get the quality of care when it's all done in the store. It's kind of taking away both the 3rd party lab and your primary care. Is that a correct assumption, though.
00:27:26.540 --> 00:27:39.710 David Yang: No, no, that's exactly right. So you know, again, I want to talk about the drivers again, for the idea of retail people wanted to drive healthcare closer to the patient.
00:27:40.080 --> 00:27:48.769 David Yang: Right? And so, you know, a simple story is, you know, David wakes up one day. He's got a fever. He's nauseous
00:27:49.360 --> 00:28:03.620 David Yang: right now he's got to call his physician. Set up an appointment. If you're in New York City as you are, Frank, you get on the subway, perhaps, or the bus. And you're making people sick. So so we want to get
00:28:03.980 --> 00:28:15.149 David Yang: so that you know David's and Frank's and the sick people of the world can get closer to the actual place where they can be diagnosed and treated appropriately.
00:28:15.310 --> 00:28:15.790 Frank R. Harrison: Right
00:28:16.660 --> 00:28:31.590 David Yang: I, in some analysis that I did. This is pre pandemic. We found that some 50% of people with Ili influenza like illness, actually never even seek treatment. They just okay. I have a fever.
00:28:31.810 --> 00:28:38.680 David Yang: But I'm just gonna go do what I got to do. Why? Because it's a pain for me to go set. Maybe I don't have a doctor.
00:28:38.790 --> 00:28:47.359 David Yang: so I'm not even I'm not even, gonna you know. Let you know be diagnosed on this. I'm gonna go to work. Well, I'm gonna figure this out all on my own.
00:28:47.620 --> 00:29:07.020 David Yang: and most likely I'm spreading it to my family, my coworkers, my colleagues, and and that kind of segues again. Now I'm going off of Marshall's book to talk a little bit about potentially, you know, at home medical diagnostics. Maybe we'll do that after the break, and.
00:29:07.020 --> 00:29:14.300 Frank R. Harrison: And I mean that kind of also falls into the category of next generation therapies. Right? I mean, it's not whether whether it has to do with
00:29:14.782 --> 00:29:22.750 Frank R. Harrison: specialized genetic therapies, or whether it has to do with you being your own therapist when there is no easy access to.
00:29:22.750 --> 00:29:23.520 David Yang: That's right.
00:29:23.520 --> 00:29:29.759 Frank R. Harrison: All right. So yep, he's on the money. David Yang is definitely ready for our 3rd section as we are.
00:29:30.560 --> 00:29:43.419 Frank R. Harrison: but it's unfortunate that we don't know if Marshall will be joining us, so even more so. We know he will be on next week. All right, so please stay tuned. We'll be back in a few.
00:31:18.100 --> 00:31:32.959 Frank R. Harrison: Everybody and welcome back. Now I have a feeling, David. This was the point where we thought that you and Marshall would be talking about next gen therapies in more detail, especially in areas where you had touched upon with me.
00:31:32.970 --> 00:31:57.079 Frank R. Harrison: how people in rural communities are going to start losing some of the benefits that were put in place during the pandemic, such as easy access to broadband as a result of telehealth needs which will probably at some point no longer be covered, based on the new Administration's policies that they've introduced. So why don't I be the buffer, and express to me the same impassioned
00:31:57.170 --> 00:32:18.100 Frank R. Harrison: understandings that you got both from your own knowledge as to what's happening, but at the same time from the book. And since I've read the book 3 times already. Hopefully, I can come up with some understanding of where the benefits and of course the disadvantages are. But, more importantly, it'll also be more room to really ask Marshall more questions when he's here next week.
00:32:18.500 --> 00:32:25.550 David Yang: Yeah, yeah. I mean, one of the things that the covid pandemic really,
00:32:27.190 --> 00:32:38.510 David Yang: spotlighted was the inequity in healthcare across the United States, and this whole idea of telehealth and telemedicine pre pandemic.
00:32:38.750 --> 00:33:08.670 David Yang: It was basically just an idea. The adoption was really low. Probably the greatest adoption at the time was in mental health, which I think it continues to be. But, prior, you know, prior to the pandemic people were concerned about things like privacy, and you know, information keeping information in the right hands. You know the pandemic. It was a little bit of a free for all, because people were dying, and
00:33:08.880 --> 00:33:17.089 David Yang: we're not going to let the hypothesis of of, you know, health information prevent us from trying to reach out to all the people.
00:33:17.650 --> 00:33:26.780 David Yang: And so you know. And so there was a lot of this center for Medicare and Medicaid services started reimbursing for telehealth.
00:33:27.570 --> 00:33:30.820 David Yang: and the physicians that I spoke with
00:33:31.240 --> 00:33:48.700 David Yang: few years back about the stickiness of telehealth. It basically all came out to the same problem. We like it for certain situations. But will it still be reimbursed, because again, physicians need to make money to feed their family
00:33:48.830 --> 00:34:10.429 David Yang: perfectly fine. And so right now I believe that September 30, th 2025 is the is the period when the reimbursement for telehealth services is going to be, you know, ending, hold on, I don't know what ending means. Maybe there's some carve outs.
00:34:10.530 --> 00:34:11.530 David Yang: Yeah. But
00:34:11.690 --> 00:34:17.909 David Yang: but, as frank as you know, you know, half the population of the United States is in rural communities.
00:34:18.500 --> 00:34:22.879 David Yang: and some 25% of rural communities do not have broadband.
00:34:23.040 --> 00:34:38.540 David Yang: So so you know, everyone who's watching this are, you know, are really probably unaware, because we all have broadband, and we expect it just like we expect to turn on the water and be able to drink it without getting. We expect to be able to turn on the Internet and get to it.
00:34:38.719 --> 00:34:50.729 David Yang: And so and so there was a drive to try to increase broadband by universal broadband by 2030, Internet for all we'll we'll see if that's still gonna happen.
00:34:51.208 --> 00:34:58.430 David Yang: But you know, 9, 1 1 service, just every service, you know, we we just expect to be able to get online
00:34:58.800 --> 00:35:03.580 David Yang: just like we expected to be able to make a phone call 2530 years ago.
00:35:03.970 --> 00:35:04.560 Frank R. Harrison: Yes.
00:35:04.790 --> 00:35:08.960 David Yang: So, yeah, so, so you know.
00:35:09.300 --> 00:35:15.630 Frank R. Harrison: And and the way that I see that is that if already they're using well for those that
00:35:15.850 --> 00:35:18.179 Frank R. Harrison: that do have broadband now.
00:35:18.310 --> 00:35:27.919 Frank R. Harrison: and because they are 25 miles away from their physician. They really need the telehealth, because they also have the advantage of it being covered
00:35:28.120 --> 00:35:28.740 Frank R. Harrison: so.
00:35:28.740 --> 00:35:29.240 David Yang: Right.
00:35:29.560 --> 00:35:38.250 Frank R. Harrison: If it's not, if their healthcare isn't being covered through telehealth anymore, there'll be no need for the broadband unless they, of course, use it
00:35:38.360 --> 00:35:53.759 Frank R. Harrison: just to have Zoom calls with their family and friends, and among other things, but the bottom line is is that if they don't have broadband, then they also can't get to their doctor, so there'll be no service on their needs at all.
00:35:54.100 --> 00:36:08.420 David Yang: That's right. And even, you know, even if you're not in a rural situation as the American population, the global population ages, there's a lot of other reasons why people can't go to their primary care physician
00:36:08.630 --> 00:36:17.494 David Yang: to just even check in, you know, because you're you have a leg problems. Your elderly can't manage whatever the stairs or whatever
00:36:18.180 --> 00:36:21.849 David Yang: and and you know this kind of segues into something that
00:36:23.050 --> 00:36:27.779 David Yang: just pre pandemic. And then, now post pandemic. There was a lot of talk.
00:36:27.910 --> 00:36:32.490 David Yang: and quite, quite frankly, not much traction, which is at at home.
00:36:32.880 --> 00:36:36.459 David Yang: Medical testing coupled with telehealth.
00:36:36.952 --> 00:36:41.309 David Yang: I you know I'd like to talk a little bit about the potential disruptor for that.
00:36:41.500 --> 00:36:47.470 David Yang: So the idea is you know, once upon a time.
00:36:47.590 --> 00:36:52.359 David Yang: pre pandemic, that if you had a fever. As I said.
00:36:52.760 --> 00:37:00.609 David Yang: you don't want to go to the doctor. You don't feel well, you know. Wouldn't it be nice if you can call your Cvs pharmacy.
00:37:00.800 --> 00:37:03.790 David Yang: and they can actually send a test to you.
00:37:04.270 --> 00:37:11.340 David Yang: And then your doctor is also tuned into that test, so that when you take the test at home.
00:37:12.120 --> 00:37:24.529 David Yang: The doctor will see the results and potentially prescribe Tamiflu or Paxlovid, or some sort of treatment, and you never leave the leave, the leave, the your home?
00:37:25.293 --> 00:37:31.890 David Yang: You know I I made a joke once upon a time that if my daughter can order
00:37:33.118 --> 00:37:39.550 David Yang: Boba a boba drink on Uber and get it within a half hour, I should be able
00:37:39.880 --> 00:37:43.900 David Yang: to order a test. Assuming it exists which doesn't yet
00:37:44.060 --> 00:37:56.859 David Yang: a test as well as the drug have it delivered to my house, where the drug is actually available. Only if the physician agrees to it. I I coin a term fluber which is flu uber. So
00:37:57.770 --> 00:38:07.087 David Yang: where an Uber driver can just drive over the materials. Yes, there are issues that I'm not gonna get into. But I think some of them are solvable.
00:38:08.260 --> 00:38:15.320 David Yang: but it requires it requires a lot of different things for that disruptor to happen. One is, it has to be
00:38:15.510 --> 00:38:20.919 David Yang: telehealth enabled you have to have a clinician, read the results and make a decision.
00:38:21.400 --> 00:38:25.889 David Yang: And and what the next step is. The other thing is the device itself.
00:38:26.180 --> 00:38:32.570 David Yang: which has to have certain features it has to be easy to use. I spoke about fairly inexpensive.
00:38:34.630 --> 00:38:37.639 David Yang: Someone's got to build the ecosystem to deliver the system.
00:38:38.160 --> 00:38:53.019 David Yang: You know. Marshall talks about Amazon and their foray and Dell, and so you know, Amazon has solved the distribution problem quite well. Right. If I can order a you know a new baseball bat, and it comes in 4 HI think I
00:38:53.930 --> 00:39:10.189 David Yang: it would be nice to be able to order, you know, a test for some sort of infectious disease. Again, the right test or the right people at the right time. I'm not talking about every test in the world, only ones where we really don't want the sick person going out and infecting other people.
00:39:11.100 --> 00:39:12.119 Frank R. Harrison: Right right?
00:39:12.560 --> 00:39:41.980 Frank R. Harrison: I mean, correct me if I'm wrong. But I'm gathering that when all of these disruptions are occurring, such as disabling telehealth, coverage, or even making the patient fend for themselves. You have the convenience, ecosystem of Amazon that already proved itself across other industries. And now one of our friends well, and not a personal friend. One of our famous shark friends, Mark Cuban, is closely involved in Amazon, especially with cost plus drugs, or at least with.
00:39:41.980 --> 00:39:42.460 David Yang: That's right.
00:39:42.460 --> 00:39:45.779 Frank R. Harrison: That are primarily generic, but that still doesn't
00:39:46.040 --> 00:40:08.869 Frank R. Harrison: solve the delivery situation with like the flubur idea you just said. I wonder if that's at all, even in his wheelhouse going forward that we just don't know about. Or maybe that's something that is sorely needed, which is to have someone with an entrepreneurial mindset with an understanding of patient needs to be able to add that to the system, if the other traditional means are disappearing.
00:40:09.250 --> 00:40:11.808 David Yang: No, yeah, you're exactly right.
00:40:12.450 --> 00:40:30.270 David Yang: you know there are some, probably some regulatory hurdles. I'm not a lawyer about delivering a prescription drug, but quite frankly, Cvs delivers prescription drugs. All right. So it's a non issue. You can order pharmacy online pharmacy. It's not a problem
00:40:30.540 --> 00:40:45.510 David Yang: in my specific model. The biggest problem is that most of the diagnostic test that gives the physician the information doesn't exist yet, or if they exist because I can name a number of them.
00:40:45.860 --> 00:40:56.060 David Yang: There are logistics, problems. There are manufacturing problems. There's efficacy. There's the clinical trials needed to get these tests through the FDA.
00:40:56.510 --> 00:41:10.309 David Yang: You know, when we talk about the healthcare ecosystem. Government is a part of that ecosystem. I don't care who you are. You can pretend to say government shouldn't be in this, but in the fact they are, and they should be.
00:41:11.280 --> 00:41:33.659 David Yang: And the reason why I bring this up is that pre-pandemic there's a program called Barda. It's part of Nih. It's the Biological Advanced Research and Development Agency whose goal is to put seed money out for companies to build all of these things. And they actually
00:41:33.760 --> 00:41:41.419 David Yang: invested in a lot of at home testing technologies. And and we just need to continue to do that because
00:41:41.920 --> 00:41:48.869 David Yang: someone's going to have the right combination, the right formulation to be able to have that fundamental piece of hardware.
00:41:49.010 --> 00:41:54.713 David Yang: And and then again, you get the. You make the room, bring in the room of
00:41:55.870 --> 00:42:16.109 David Yang: of subject matter. Experts in the logistics in the, in the supply chain, build the system, and then you could roll it out. But having that that again going back to kind of my roots. The oh, wow! Moment! The gearhead moment, the innovator in his garage in her garage, who's building the device, you know, that's really important.
00:42:16.590 --> 00:42:27.538 David Yang: And and I just want to point out, maybe just tell one more, very, very quick story. You know, we talk about the Mrna vaccines and the
00:42:28.844 --> 00:42:39.989 David Yang: immune response using messenger rna things of that nature. All of these things are really possible, because back in the nineties the Government spent
00:42:40.170 --> 00:42:44.330 David Yang: 4 5 billion dollars on sequencing the human genome.
00:42:44.470 --> 00:42:56.139 David Yang: That was an enormous project whose goal it was was to figure out for some representative person. What are the agct letters that make up that person's composition.
00:42:56.520 --> 00:42:57.140 Frank R. Harrison: Right.
00:42:57.140 --> 00:43:16.559 David Yang: Time there was a lot of question, why would we ever want to do that? And the idea is that it's an investment in this technology. It took some 13 years for that project at a cost of 4 billion dollars, 8 billion dollars. I don't remember the numbers. But today, because of that foundation, that investment
00:43:16.830 --> 00:43:25.890 David Yang: there are what's going on a second next generation and 3rd generation sequencing that can take the same, get the same information in hours.
00:43:26.880 --> 00:43:37.439 David Yang: So we are probably a factor of 2 or 3 away from basically sequencing everything that's in your blood to figure out. Do you have Covid. Do you have flu, you know.
00:43:37.660 --> 00:43:38.220 David Yang: So.
00:43:38.220 --> 00:43:38.710 Frank R. Harrison: Yes.
00:43:38.710 --> 00:43:44.969 David Yang: So the government role in this ecosystem to help seed the startups
00:43:45.380 --> 00:43:55.999 David Yang: that can then take the ingenuity, the innovation that you mentioned that Marshall mentioned to build the disruptors that don't exist today.
00:43:56.270 --> 00:44:14.169 Frank R. Harrison: Yes, yes, but you know what the thing is is that it's so ironic, because, if you remember, when Mrna was tested by Pfizer and rolled out into the Covid vaccine within 18 months. Operation warp speed. That was the Government's involvement with private sector.
00:44:14.170 --> 00:44:14.559 Frank R. Harrison: That's right.
00:44:14.560 --> 00:44:34.940 Frank R. Harrison: Don't know why the pushback I mean, it doesn't make any sense, because that would be, if anything, where all of the accolades and rightfully so would be attained, which is what this administration is seeking, you know, but they're doing it in reverse, and that's why there is more disruption and more chaos. But
00:44:35.170 --> 00:44:44.469 Frank R. Harrison: in order for us to mitigate it like like what we patient-centered care, or even just being focused on to ourselves as much as possible.
00:44:44.770 --> 00:44:56.609 Frank R. Harrison: I guess that's that's their their way of making everything all privatized or commoditized. I don't know if commoditized, actually fits, because not everybody would have access but
00:44:56.770 --> 00:45:05.200 Frank R. Harrison: it it. We we know what ladies and gentlemen, I've said on every episode own your healthcare even more so now we're about.
00:45:05.200 --> 00:45:09.399 David Yang: Yeah. Marshall pointed that out, too.
00:45:09.400 --> 00:45:31.110 Frank R. Harrison: And so we're about to take our final break. Everything that myself and David Yang have discussed about retail pharmacies, genetic therapeutics, Mrna, the Government's role in healthcare, not self-centered care. Patient-centered care is in chapters 2 and 5 of the book, and when we return
00:45:31.110 --> 00:45:39.800 Frank R. Harrison: both myself and David are going to be talking about artificial intelligence in healthcare, which is chapter 6. If you want more information on the other chapters.
00:45:39.800 --> 00:45:45.640 Frank R. Harrison: please click on the QR code during the commercial break, or even when we come back, see you in a few.
00:47:30.520 --> 00:47:41.460 Frank R. Harrison: Hey, everybody, and welcome back. Well, it appears that Marshall will probably not be joining us on the show as planned. I know he's eager
00:47:41.520 --> 00:47:47.360 Frank R. Harrison: to talk about the book and to talk about the feedback that we've gotten from the last 2
00:47:47.390 --> 00:48:01.250 Frank R. Harrison: discussions we've had. And of course, David, I hope you're able to join us next week as well, because I know you have so many things that only Marshall can best answer for you. But I think, if anything, you and I have a lot in common with
00:48:01.270 --> 00:48:22.470 Frank R. Harrison: with Stem and Brooklyn Tech and artificial intelligence. So I wanted to dedicate the final segment of this show to talking about Chapter 6, about AI in healthcare. Now I know you had some key takeaways you wanted to discuss. Why don't we start with that I think it was about the medicines and genetic testing, and then I would talk about how it fits within the business.
00:48:22.560 --> 00:48:24.999 Frank R. Harrison: Oh, well, the business and profession of healthcare.
00:48:25.290 --> 00:48:25.950 David Yang: Yeah.
00:48:26.140 --> 00:48:33.090 David Yang: So you know again, this is, you know, real tangential, maybe to what to what Marshall is talking about. But
00:48:33.490 --> 00:48:36.290 David Yang: you know one of one of the things that we
00:48:36.640 --> 00:48:47.119 David Yang: we understand this is that we expect medicines to do what they're supposed to do. So they're supposed to lower blood pressure, we expect, and we measure that.
00:48:47.440 --> 00:49:04.529 David Yang: And we know that that's what they're supposed to do. And in part of the clinical trials we need to make sure that they're safe, because if you don't have high blood pressure, we don't want to give you this drug, and it causes kidney failure or something like that. So in clinical trials they go through all this testing.
00:49:04.920 --> 00:49:16.500 David Yang: But one thing that we don't understand, and is very difficult to understand is what other benefits there are to potential drugs, to medicines.
00:49:17.830 --> 00:49:44.899 David Yang: And I'm not really talking about potential multiple effects as Marshall talks about with the glp-one drugs that causing lower weight can cause fewer comorbidities. But I'm talking about other features of a drug that maybe aren't as apparent. I think a good example is Viagra. Viagra was tested
00:49:45.040 --> 00:49:54.620 David Yang: for yeah, cardiac issues. And the people men observed this other side effect.
00:49:55.140 --> 00:50:00.580 David Yang: And and so no one went looking for the side effect. But people reported it.
00:50:01.100 --> 00:50:07.770 David Yang: And you can imagine that in a population that takes this drug.
00:50:08.690 --> 00:50:19.040 David Yang: perhaps there is a side effect that your rate for kidney cancer, I'm making it up now drops by 50%.
00:50:19.490 --> 00:50:29.770 David Yang: Now, the only way for us today to know about this is to actually take do a clinical study or review the data specifically on
00:50:30.995 --> 00:50:35.679 David Yang: the impact of drug X on disease y.
00:50:35.890 --> 00:50:39.830 David Yang: and if it turns out that that's not the case, then
00:50:40.030 --> 00:50:53.859 David Yang: okay, didn't happen then. But maybe it does something else. Each of these cases may be backed in science, but you got to go see if the data exists to support your hypothesis that there is another treatment for this drug.
00:50:54.070 --> 00:50:55.140 Frank R. Harrison: Right, so.
00:50:55.300 --> 00:51:02.300 David Yang: So the potential for AI is to do is to let the computer do the study.
00:51:02.690 --> 00:51:09.709 David Yang: So for every population that's taking a stand making this up. This is not real.
00:51:11.680 --> 00:51:19.439 David Yang: Do they also find another comorbidity, another disease that actually gets reduced
00:51:20.380 --> 00:51:28.429 David Yang: at a, you know, that's not a hundred percent, but at 75% or 50%, that the incidence of
00:51:28.970 --> 00:51:36.839 David Yang: kidney stones again making it up. Not a doctor. The incidence of kidney stones in population of people who take statins drops in half.
00:51:37.740 --> 00:51:45.330 David Yang: and and so the old way is to go. Go. Do those studies one at a time? Go? Do those analysis, one at a time.
00:51:46.030 --> 00:51:53.509 David Yang: The new way with AI is to do a population analysis to see if there is any correlation.
00:51:53.830 --> 00:51:54.520 Frank R. Harrison: Right.
00:51:54.930 --> 00:52:02.549 David Yang: That if a correlation is found, it's not causation, but it allows you to then take the next step to focus on
00:52:02.730 --> 00:52:23.700 David Yang: a clinical trial to prove that hypothesis, that it does in fact, decrease the frequency of model Z. And just one more thought. So that's right. Now, that would be an off-label use of a drug. And what's so beautiful about that potential is that this drug has already gone through the safety
00:52:23.800 --> 00:52:30.179 David Yang: analysis. We already know it's safe. The supply chain is already available because we already make the drug.
00:52:30.300 --> 00:52:33.679 David Yang: It's now just finding a new application for this drug
00:52:34.460 --> 00:52:38.620 David Yang: and quite frankly, for the hundreds of drugs that are on the shelf
00:52:39.150 --> 00:52:46.829 David Yang: because they failed the clinical trial because the efficacy didn't show what it was supposed to do. So there's there's this
00:52:46.960 --> 00:52:51.970 David Yang: unlocking, the potential, unlocking for all this population statistics.
00:52:52.730 --> 00:53:05.500 David Yang: in addition to being better at finding tumors on Mris and and finding you know, in a cat scan. You know, all those things are great, and they're ubiquitous, and they probably have
00:53:05.990 --> 00:53:14.829 David Yang: enormous savings in the healthcare system. But this is just another area where having population analysis can can really
00:53:15.010 --> 00:53:17.779 David Yang: disrupt the way we do studies.
00:53:18.260 --> 00:53:36.380 Frank R. Harrison: Yes, I mean, the irony is is that, I guess, with the whole Llm and Chatgpt, the machine language population data analysis that goes deep learning that is going on. You're able to look at, let's say, for example, a population of those who already take Viagra.
00:53:36.380 --> 00:53:48.420 Frank R. Harrison: or a population of those that are already taking Paxlovid, or who are taking the glp-one drugs and seeing from that patient population that's being tested. What percentage of besides a weight decline
00:53:48.420 --> 00:54:09.240 Frank R. Harrison: have had a decline in the rate of diabetes, or in the rate of whatever. And then, all of a sudden, you take that data and you can speed up the time that it would have taken to at least package the product to be offered through different marketing channels for different types of patients rather than oh, I didn't know that I was going to benefit by taking this drug.
00:54:09.300 --> 00:54:10.460 Frank R. Harrison: you know. Yeah.
00:54:10.640 --> 00:54:17.880 Frank R. Harrison: Oh, we got a question from somebody for every one successful drug at treating ABC.
00:54:18.560 --> 00:54:25.240 Frank R. Harrison: There are probably dozens or hundreds of failed drugs that could treat Cba Bac.
00:54:25.240 --> 00:54:25.670 David Yang: That's right.
00:54:26.240 --> 00:54:34.579 Frank R. Harrison: Yeah, I I guess. Well, that's true. While Chatgp well, AI is trying to get rid of those
00:54:34.730 --> 00:54:48.199 Frank R. Harrison: failed mechanisms much quicker than through trial and error, and that's what you're pretty much outlining in terms of what artificial intelligence can do in terms of increasing the rate of discovery as well as the rate of the of the best.
00:54:48.400 --> 00:54:51.360 Frank R. Harrison: A medicinal cure for the situation.
00:54:51.790 --> 00:55:02.530 David Yang: Yeah, yeah, I think the the person who posed the question is, is, you know, is spot on in the sense that these orphan drugs potentially can have a new life.
00:55:02.870 --> 00:55:23.289 David Yang: And maybe as a derivative of the response, maybe we can figure out what population it was effective for, and now becomes this personalized medicine that Marshall Rangi talks about. You know Marshall's book touches on all of these things.
00:55:24.200 --> 00:55:36.159 David Yang: Technology is able to is to able to do things that quite frankly, people can't do manually because it's expensive, it's time consuming. And this idea that
00:55:36.270 --> 00:55:39.640 David Yang: still exists, which is, where do you get the data.
00:55:39.940 --> 00:55:43.080 David Yang: You got the this real world data.
00:55:43.270 --> 00:55:49.259 David Yang: You know, we are all uber sensitive about our, you know our privacy.
00:55:49.370 --> 00:55:51.650 David Yang: But we need to get
00:55:52.100 --> 00:55:57.539 David Yang: public information on all the people who are doing this, and that it's really hard to do that. Now.
00:55:58.380 --> 00:56:04.460 Frank R. Harrison: Well, we're about 1 min to ending, and I'm going to read a takeaway that he writes in the book.
00:56:04.500 --> 00:56:30.170 Frank R. Harrison: and I think I read it last week, but I'll read it again. Our challenge is to harness AI as a powerful tool to enhance human capabilities in medicine, not replace them. We must integrate AI seamlessly into clinical workflows, always keeping the needs of patients and providers at the forefront, protecting privacy, addressing algorithmic bias and ensuring equitable access to AI driven care, which are all top priorities.
00:56:30.920 --> 00:56:31.910 David Yang: Yeah, well.
00:56:31.910 --> 00:56:41.140 Frank R. Harrison: Marshall. That was my way of speaking on your behalf being that you couldn't make it. But I am holding you to being here next week. David, are you able to be here as well.
00:56:41.540 --> 00:56:43.948 David Yang: I am 99% sure.
00:56:44.350 --> 00:57:13.210 Frank R. Harrison: We always allow room for error, and then I will try to bring in no promises. But I will bring in James Swanson as well, who has done a lot of genetic research with neurological issues, including a technology known as Crispr, which is in the book. And I think that both Marshall Runji and James Swanson would have a lot of interesting things to add again, buy the book on amazon.com use the QR code. I'm not going to have time to flip the screen back, because the next show
00:57:13.210 --> 00:57:21.270 Frank R. Harrison: at 6 o'clock is success with a splash. Stay tuned right here on Talkradio, dot Nyc. And I will be back again next week.
00:57:21.370 --> 00:57:47.180 Frank R. Harrison: continuing the month of May, as we deal with the great healthcare disruption affecting us all. Thank you again, David Yang for being here. I really appreciate your time and energy in us, exploring the future together. And thank you again, Jesse, behind the scenes for engineering the show. Thank you, whoever you are. That asked that question, and if you need to reach out to any of us Frank R. Harrison, one@gmail.com
00:57:47.280 --> 00:57:49.390 Frank R. Harrison: see you next week. Bye-bye.
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