The Doctors’ Lounge
Where scalpels meet systems — and physicians say what they really think.
Co-hosted by Anish Koka, MD & Anthony DiGiorgio, DO. Candid talks on healthcare policy, reform, physician autonomy & patient care.
The Doctors’ Lounge
Right-to-Try 2.0: Inside the Montana Model with Niklas Anzinger
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Episode Summary
Anish Koka and Anthony DiGiorgio sit down with Niklas Anzinger, a venture capitalist and founder of Infinita VC, to unpack Montana SB535 — a new law that lets doctors administer treatments to patients that have only cleared FDA phase one trials, through licensed "experimental treatment centers" overseen by independent review boards. The conversation covers why Eroom's Law has made drug development slower and more expensive despite scientific advances, how the Montana model differs from existing right-to-try and expanded access programs, the thorny question of who pays when a treatment sits outside FDA approval and insurance coverage, the risks of messy observational data replacing randomized controlled trials, and how Anzinger's work connects to special economic zones like Prospera in Honduras, where he's speaking to the hosts from.
Chapter Markers
00:22 Introducing Niklas Anzinger and his path from economics and VC to biotech policy
03:05 Montana SB535 explained — right-to-try, but with a for-profit pathway
06:01 Phase 1 vs phase 2 vs phase 3, and why bypass the later stages
11:37 Does SB535 cover devices as well as drugs
14:15 The semaglutide timeline as a case study in regulatory delay
18:36 Federal right-to-try, the baby KJ case, and why it isn't enough
23:25 The payment problem — how a non-FDA-approved treatment actually gets paid for
33:11 What "smart regulation" would look like with carte blanche over the FDA
48:31 Why Montana's biggest need right now is clinicians, not biotechs
49:57 The practical burden on a private practice running these treatments
53:32 Observational data vs. randomized trials — the risk of junk data
59:15 Is this a domestic answer to China's faster phase one pathway
1:04:22 Roatan, Prospera, and the case for special economic zones in medicine
1:09:18 Closing thoughts and where to find Anzinger's Stranded Technologies podcast
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Mr. Niklas Anzinger on X:
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SPEAKER_03This is the Doctor's Lounge.
SPEAKER_01Okay, welcome to a Sunday evening episode of the Doctor's Lounge. Very excited to have Nicholas Enzinger here today. Nicholas is uh in his mid-30s, we just established, though he's on the other end of his uh uh 30s, so but still not nearly as old as me and Dr. DiGiorgio. He is not a scientist, not a clinician, but he is doing something extremely interesting in the health care space, and uh and so we definitely were very excited and interesting to have him on. His training is in economics. He has a BA in philosophy and economics. He uh spent some time at the American Enterprise Institute, market research at a research firm uh where he ran strategy and growth. I guess you were what, 15 or 16 when you were doing that? He's a venture capitalist, and you kind of come to biotech through somewhat this is near and dear to our heart, a little bit libertarian governance theory, and not really through establishment conventional uh medicine. The backstory is interesting because he's done so much. There's a VC fund, um, there's a company, uh, the VC fund is called Infinita VC, and there's something called Infinity City, which he's gonna talk to us about. And he also hosts the stranded technologies podcast. And the organizing concept for this is that there are stranded technologies, meaning there are therapeutics interventions that are held back by current regulatory frameworks. And his belief is that there's special economic zones with a different set of legislation that would uh allow these stranded technologies to be applied for the good of the public. So, Nicholas, welcome to the show. Fantastic to real need, guys.
SPEAKER_02Like I've been listening to your show for a long time and have learned a lot from it that also inspired me partly for some of the things that I'm doing or how I'm approaching things.
SPEAKER_01Wow. Are you sure it's the right doctor's lounge you have? Yes, you must be mistaken. No, I'm pretty sure I'm not. All right. So, Nicholas, tell us a little bit about how you got to Montana. What are you hoping to achieve in Montana? That journey to Montana will give us and the audience a lot of backstory.
SPEAKER_02So I can tell you a bit where we are now with Montana, specifically with a new law in Montana called SB535 and how we got there. So Montana SB535 is sort of in the category of right to try laws, but it's kind of much more than that. Right. So what I'm interested in, or what I want to do, is just make biotech move faster, have sort of clinical evidence generation that is as much faster and cheaper. So I think the key problem we have right now with medical regulation and FDA drug approvals, many components feed into sort of the legacy system we have now, but it's just too slow and expensive. So um, and that's what I want to change, and I think Montana SB535 is a first, is a step in that direction. Right. So under SB535, patients on doctors, doctors can give treatments to patients that are not approved by the FDA that have passed only a phase one trial, right? And other than traditional right to try laws, it's not just for people with life-threatening diseases, but any patients can access it. And then what's further the case is traditional right to try as a provider, as a manufacturer, you can make a profit. Under Montana, you can. Now, this is obviously very big steps in a sort of libertarian free market direction, but we wanted to make this a model that can scale to other states and then we can have conversations with institutions like the FDA and confidently assert that this model is a win-win. So we actually added in very specific, um, a very specific regulatory pathway with sort of specialized clinics called experimental treatment centers, and a review board that has scientists and medical practitioners sitting on it and that has oversight, similar to how IRBs are done. So, and that's what I am operationalizing with my company with Infinita. Right. So we have firmed to formed the first ETRB, the first review board that has scientists such as Matt Caberline or Jamie Justice or Philippe Sierra on its board and will review treatments. And we're helping especially, we have a very large network of biotech companies, many of which in longevity and regenerative medicine, but we actually are getting much more interest now from neurodegenerative disease, cancer oncology, and even from your field from cardiovascular diseases. So happy to talk a bit how we landed there, but Montana basically can be accessed now. So if you're a biotech, you can come to us and to the review board. Um, what we're actually most looking for right now might be interesting for you and your audience. What we're looking most for right now is clinicians that are interested in opening up experimental treatment clinics or join one in Montana right now.
SPEAKER_01Fascinating. So how did how did this come to pass in Montana? Yeah. This idea that, you know, and again, the normal, just so folks understand, normally it's phase one, phase two, phase three. Phase one really is typically in non-human models in that you show some type of activity of the therapeutic that you're studying. It's actually first in human, right? First human, sorry, first in human. Yes. Sorry. So that you that that you show signal, apologies. Phase two is kind of dose finding toxicity, right? And then finally, phase three is uh is usually some type of placebo randomized control trial to kind of really get at the size of the effect. And normally the public does not have access to therapeutic unless there's a certain bar of efficacy that's passed by a phase three. So obviously, Nicholas, that structure exists for some reason. Why is it that we should bypass phase two and phase three? Yeah.
SPEAKER_02So I mean, it's great to have data on safety and efficacy. Right? I'm all for that. I'm all for knowing whether a drug or treatment is safe and whether or not it works or not. I think randomized control trials are great. They're a fantastic tool. I just think the way we're administering it and the way we're currently doing approvals pre-market, it's not necessarily the best way that we get uh that we do the evidence generation process, right? Right. So there's something called EROM's law in biotech, right? So that is the reverse of Moore's Law, right? So Moore's Law has increased computing power or has roughly doubled computing power every two years. ERUM's law does the reverse for drug development. So since the 1960s or in the 1960s, for one billion dollars, you got about 100 new drugs. And now you're getting less than one, right? And that is despite loads of advances in science and technology, right? So we've decoded the human genome, we have computational biology, we have all sorts of ways in which it should actually be cheaper right now to generate, to generate data and generate evidence and develop new drugs and treatments and things like that. But generating data in human is a bottleneck. Uh that's very regulated and many good reasons. So many of these reasons are fine. And here we are, right? So everyone at FDA and NDC would like things to be faster and cheaper. The question is how we do it. And Montana has an answer to that. And it comes kind of not necessarily from sort of right to try is something that originated kind of outside DFDA, right? So America has a very deep tradition around medical freedom. There were the HIV-AIDS community protests in front of DFDA in the 1980s. There was the Abigail Alliance case arguing for constitutional right to try for patients. So it was very, very much a patient-led movement for basically saying, like, okay, I'm an individual and I'm willing to take the risk, right? So great what you're doing, great that we get all the data, right? I'm all for having treatments that we know works. But right now there isn't, there is no treatment for me as a patient. But, you know, and that's what's obvious during AIB and AIDS, but in also other cases, like human insulin took like more than 30 years to be approved, where it's just too late for many patients. So as a result, there were right-to-try frameworks starting in around 2014 or 15, I think, that were popping up in different states, which are unfortunately to this date not very effective. So DFDA has a program called expanded access that's much more effective than the right-to-try laws. But I think now with Montana, we're having a model that could be much more effective. Now, what's also interesting about that, besides sort of patients having under informed consent and doctor prescription, being able to access treatments, you sort of have very strong informed consent and things like that. It's also that the review boards are required to collect the outcome data. So if there's adverse events, they need to report it in the regular way. Safety and outcome data need to be reported publicly on an annual basis in an aggregated, anonymized way. And also, the medical practitioner, with the oversight of the review board, they can't or withhold relevant information from patients. So this way we're updating actually our knowledge of these treatments in light of new evidence. Right. So I think this can be a very effective way to generate evidence. Now, we cannot do randomized controlled trials under this model, which is not because I wouldn't want to. It's just legally, it's a different jurisdiction. So I do think, and I would eventually like for there to be a more flexible model that even under the state access model, we could also do offering patients basically to be part of a randomized study, but currently that's not possible. It sits in medical practice law and in the jurisdiction of states. So it's kind of the broad overview. I think it's great to generate evidence for new treatments, and I think it's great that patients have a free and informed joystick make.
SPEAKER_00I was gonna ask, does this cover devices as well as as pharmacology?
SPEAKER_02Yeah, so devices are named in the law, but I think it wasn't precise enough to be too attractive for devices, right? Because the language is kind of very explicitly requiring phase one, and phase one in devices, there's a different approval pathway. So it's not entirely equiblical, right? So there might be some ways to make it work, but it's not been optimized for devices yet. Future laws hopefully will be.
SPEAKER_01So sorry, I just wanna I don't want to uh perseverate too much on this, but I do want I do want to get this uh uh correct since I uh butchered it uh in the intro. Phase one specifically is what dose can a human tolerate. So it normally that's like 10 to 50 people total in the trial, right? And then if you look at the overall numbers, there's a very, very small, if you look at the regular FDA process, right? If you look at who makes it through phase one and who ultimately gets approved, right, it's a tiny, tiny fraction of folks that are phase one trials that are getting approved. So either we're getting it wrong, right? We are, there's lots of uh therapeutics that work but are unable to make through the FDA process, right? Or it is the case that biology getting stuff that has actual signal is extremely hard. And yes, you're only gonna get a breakthrough five to 10% of the time, right? Meaning five to five to ten percent of the time, something that is tolerated by a human with some mechanistic reasoning where you think it works, right? That's how you get to phase one. You don't just randomly try black licorice on some some derivative of black licorice to treat something to a phase one trial. Nobody's gonna put up that money. Nobody's gonna take some type of risk, even for something that's, of course, novel and not black licorice, right? So you're gonna have to have some strong mechanistics of reasoning, some strong animal studies, and then it gets it to phase one, which is human trials, right? And that's 10, 10 to 30 four. And that's just dose finding. Like what dose can a human tolerate? Phase two is does it plausibly do anything at what dose? So that's the dose finding, dose escalation to see where is this efficacy signal. Then comes that phase three that quantifies does it work when it by and you do that by comparing it to placebo. But so Nicholas, how I mean, just by the numbers.
SPEAKER_00If I could just uh interject, I think it's it's worth looking at the time points. So I just looked it up, semaglutide, so Ozempic. Yeah. Yeah. Phase one was completed in in October of 2009. It took about eight months for phase one. Ozempic was FDA approved, finally FDA approved, December of 2017. So that is how long, how much time you're cutting off for drug approval.
SPEAKER_02Aaron Powell, I believe even the GLP ones were in trials already much earlier. Even in 2003 were some pivotal trials. And even in the 1980s, some of them started, right? So I think it's actually a much longer history. Aaron Powell Yeah.
SPEAKER_01But the problem is, of course, is that it's easy to just focus on the 7% that do make it through, right? For every one semaglutide that exists, the GLP1 exists, there are 93 of those, right? Yeah. Sorry, uh whatever. Many, many multiples of those that simply don't make it through. So then and then on top of that, you're making it a commercial venture. So why wouldn't why wouldn't a bunch of folks that have, as some have turned as someone termed beautifully, scientifically elegant placebos, set up your clinic in Montana to have a scientifically elegant placebo and uh come pay us money. And that setup sets up a whole different type of incentive structure.
SPEAKER_02So yeah, so we should be under no illusion that after phase one, we do know whether a drug works or not. Right. So that has to be, and that's part of what the review board needs to do, properly disclosed in the informed consent process. Like here's what we do know, here's what we don't know. And based on that, patients can make an informed choice, right? So the headline number and why that's often brought up in articles that are skeptical about the model is which is true, that 90% of post-phase one drugs or treatments fail. They don't get final approval. Now, what's interesting when you actually look at the clinicaltrials.gov data is that it's less than a third of those that are explicitly rejected for scientific reasons, for a lack of safety or efficacy signal. What happens with the other two-thirds? Like these are drug programs that get abandoned voluntarily by the sponsor. And that's typically for insufficient recruitment, which often has to do with that the trial was badly designed or that the company simply ran out of money. So, how many of these drugs are promising work? Well, that's unclear. What is the reality for many of these companies, and we spoke to hundreds, is that it's very difficult to fundraise, right? So there is like the valley of death problem without having more data to show whether it could work or not. Right. So this is catch 22. If you're a biotech, you need more data to raise more funding, but you also need more funding to raise more data, right? So the trials are just like a very high and expensive all-or-nothing hurdle. Versus if you actually have the opportunity to gain more experience in medical practice and have more data, then you can raise more funding. Maybe you even say see that it doesn't work. So you actually save the trial system time and money. Or you detect something, maybe you have more data on a different subgroup, you have more data on clinical endpoints. You just can sharpen the design of the trial to reduce your potential your rate of failure for phase two or phase three. Right. So the companies that we work with, and they're not interested, they're mostly not interested in a completely like a parallel path to the FDA. They will all want FDA approval eventually, right? But they see the value of getting more data that could sharpen their official trials. Now that's one, and there's actually a second interesting pathway. Right. So many drugs or treatments get approved in different countries, but not in the United States, right? Often because they're past the patentcliff, right? So one of the peptides, for example, Timosine Alpha 1, is approved in 35 countries, but it's not patentable. So nobody has an incentive to do the trials. In Montana, you can actually do it under that pathway, right? So you basically use the phase one safety data from one of the other top regulators in the country, and then you can do it there through a legal pathway. Right? So I think it just gives more options and sort of oils the engine for evidence generation. And when it comes to treating patients, we're there to ensure, or that's the requirement of the law and of the review boards, that patients have a free choice, but it's an honest choice with an accurate description of what they're getting. How do you the plan is to generate data, right?
SPEAKER_01Well, I guess two questions. One is you have a mechanism through the FDA, and you mentioned this earlier, just please clarify and go into depth. There is a federal right to try legislation that exists. And my understanding is that um you know the baby KJ case in Philadelphia that I'm sure you heard about, this baby that was born newborn in CHOP in Philadelphia, with one gene that's off, and it results in a metabolism problem, which is fatal. Uh and pretty rapidly you had the FDA regulatory pathway kind of moving to allow a bespoke kind of single gene therapy just for baby KJ to be designed and administered. So if that exists, and it my understanding is that a lot of these kind of type of federal rights to try cases are approved by the federal government. What like what's the problem with using that?
SPEAKER_02Federal regard try cases actually don't need to be approved, right? They don't require FDA approval, they just require proactive compliance. What you're thinking of is probably expanded access, right? So expanded access is basically asking the FDA for approval for treatment for one patient. One program, one thing that's kind of similar is you can actually also do single patient INDs, is what they're called. And they're actually quite common. So expanded access has about 2,000 patients treated per year. And sort of the idea to get additional data and evidence from that is not new. In fact, there's like NIH grants of like 40 million for like expanded access to patients in ALS, for example. Right. So the idea is not new that to get data, especially to get data outside of official trials, but through patients, that kind of falls through the cracks. Right. It's also a whole different story of that I really love to get into because I'm kind of can get very nerdy on the data science side of patients that are excluded and why we exclude them and what that does to the representativeness or the generalizability of results. But that aside, so the problem with expanded access and right to try is they're used very little. So 2,000 patients per year is not a lot, right? The FDA is not the problem. The FDA approves more than 99% of expanded access requests, typically in 24 hours. What is the problem is that not enough providers participate in these programs, right? So when you're a biotech or a small biotech and you're in your phase one or phase two or phase three, um, it is actually you can see from some of the bigger ones that they have expanded access programs. Right. So especially when the founder is like a scientist or biologist or medical practitioner, they want to save people's lives, right? So for them, they want to do that, right? But the problem is the risk-reward ratio, right? So there is a very strong, at least perception that the FDA could punish you if something goes wrong. And especially when you're dealing with very sick patients or patients that have sort of a terminal disease or life-threatening disease, right? Was it a disease or was it a treatment? So you're afraid of the headline that generates and what it does to your standing with the FDA. So there's a pretty high perceived risk. So in reality, the FDA is um has been tolerating many of these, has been tolerating these programs, it has been quite amenable. And the other is the reward. What do you get from it? Right. So there is a high compliance burden on you, and you have the risk of potential FDA consequences. And then for what? For losing money. So all these programs, and we talked to several companies, are losing money, right? And that is because you can charge at cost. You can charge more than at cost, right? So you can't make a profit, right? So that is very limiting, right? So that just means these programs don't scale, right? Because eventually a board member will say, wow, we're doing this, right? So this is just introducing a risk and we're not getting any reward for it. So that means, right? So we need to, and it's what profit does in a free market system, it allows things to scale. But it comes with safeguards, and I think ultimately that's why we designed the Montana program this way. Sort of a free market for me doesn't mean no safeguards. It just means we're using market mechanisms for some of these safeguards, right? So we're using private review boards, we're using kind of Amazon review style mechanisms. We there's private oversight bodies and things like that. So that's why I think it can be an alternative to some of these existing programs.
SPEAKER_00You you mentioned making money. So the FDA kind of has this weird dual role, right? It not only evaluates efficacy and gets the drug approved, but then in doing so sets it up for payment via government payers, right? And now I again I function more in the world of devices than drugs. And so there's an additional gap you have to make if you're a device to actually get a CPT code and a rock valuation and all that. If you're not going through that pathway, how is a drug through this program going to get paid for in Montana? Or private insurance. You know, I imagine it's going to be difficult to get private insurers to pay for a drug. Certainly you're not going to get Medicare or Medicaid to pay for it. So what's the pathway there?
SPEAKER_02Yeah. So this is actually where I learned a lot from you guys, and you guys have really been the best in sort of pointing light at that problem. So I used to think, well, all these accelerated approval pathways are great. All right, the FDA needs to be much faster and approve it and then let the market sort it out or whatever. But then it was like, hey, wait a minute, then it almost certainly has to be covered by the taxpayer and by insurance. Well, that is a problem, right? Because if the drug then gets approved and then gets like seven-year market exclusivity, you're crowding out other good drugs and letting the taxpayer pay for it. And that with the sort of American, all right, you have free price setting, or you can charge two or three million for it. That's like the worst of all worlds, right? That's not good. Right. So no police FDA can sort of be very strict as sort of the phase three gate where it's decided what insurance has to cover, right? So that's something that I learned from you guys, right? So I was definitely much more on the side of all right, the FDA is kind of too strict with things, but now I believe it's too strict and too lax. And I think that's insurance dependency is actually a very big problem, right? For that reason. So even in Japan, which is very forward thinking with regulations, especially because of Shinya Yamanaka, the Nobel Prize winner, for the hallmarks of aging and induced pluripotent stem cells and things like that, they're kind of very proud of that. So they have all these pathways, some of which are exactly mirroring Montana, but they actually made the mistake to have sort of a faster. Pathway, okay, then it's covered by insurance, right? So this stem cell treatment can be sort of outside of the system and get fast track, but then it's covered by insurance. And then you have a constituency of patients that has a vested interest or wants to continue it, right? So the post-market surveillance stuff doesn't work, right? It doesn't work in the United States, it doesn't work in Japan for like public choice reasons, right? Once it's there, once it's paid by insurance, there is just a lobby for it. And when you have patients to point out, oh, these patients are not going to be treated, that's just a very good story that you have. So I do actually think it would be good or important to really have these state programs like Montana be sort of outside of Medicare and Medicaid into public insurance, right? So I'd like to sort of be started, or Montana started with the assumption of a cash pay model and it's basically saying this is just flexible. Private insurance can, of course, cover it. And in fact, some of the biotechs we talk to have like insurance codes for some of the things. So they can cover it if they want to, but I'd like it to be kind of a market where that is decided by market mechanisms, right? It doesn't mean that you only get these treatments if you pay a lot of money for it. There can also be philanthropy that covers it. There can be private insurance. There can even be things such as data donors, right? So many companies have an interest in generating data, right? So the data makes the drug it de-risk the asset, it makes it more likely to be good FDA approval. So you can contribute to patients sort of under consent to share their data to fund them basically to trade. This is happens with normal tribes, right? It's the same commercial model, basically. So I don't have an a solution how we solve insurance in the United States in Medicare and Medicaid. I mean, that is right. So if I had a solution, I but I really don't, right? So you know I spend a lot of time in DC, and this is like the first rule of DC or of politics: nobody can touch Medicare and Medicaid and Social Security. So we're just kicking the can down the road and the cost is increasing for everyone and keeps going down, keeps going up.
SPEAKER_00Yeah, so you're almost saying like the Montana model, almost just there are these signals that could be transmitted that would show knowledge based on local supply and demand of a good or service. I wonder if anyone's ever studied that before.
SPEAKER_02Yeah, you can say that. I mean, uh I do think that companies DC, Washington DC kind of has this model, all right, uh consumers or patients are dumb and companies are greedy and public servants are angels. If they're in my political tribe. If they're in the other political tribe, they're the devil. Right. So I actually think obviously and you see that as skewer practitioners, like patients are often misinformed. They see something on you know, Joe Rogan or something like that, it doesn't work. And um but at the same time, people have wanted try things and why not let them? And we're all gaining if we get the data from it. Right. So right now the situation, sort of the Utah stem cell law is kind of an example, really has very little oversight, right? And I kind of, you know, I'm fine again with patients having an informed choice, but there's no oversight, right? So there's very limited data, and that's um that is also not great. Right. So why um now with the same with all the peptides, right? So thousands of people are taking it. Some of them probably work, some of them definitely don't work. So why not have a model where there's like a regulated pathway with oversight and we get the data? Right. So this way we're all learning and updating our beliefs on what works and what doesn't.
SPEAKER_00Yeah, I mean, I I've had some fairly wealthy patients come through traumatic brain injury, spinal cord injury, and they're always looking up what can I go get overseas, stem cells, peptides, biomechanics. Um if you have enough money, essentially anything can be obtained outside the FDA, go to another country and get it. Um so this idea that we have to protect people from themselves is very paternalistic, right? That we know if people if somebody wants to go to Montana and pay cash for an unproven drug, who are we really to say no? Because if they're not going to do it in Montana, then if they're wealthy enough, they can go to some other country and probably get the same drug or peptide or stem cell or who knows what. And then the data's lost. So at least this gives us the option of keeping the data.
SPEAKER_02Just one example, um, you may have seen Sitsi Brandi, the founder of GitLab, right? So he's a billionaire at this point, and he went what he called founder modonus cancer, right? So, and he used different treatments in the United States under single patient INDs, right? He went to Germany, to China, different jurisdictions. And it was just, all right, I don't want to die, right? And I'm gonna find a way to see what the best scientists in the world can do. Now, obviously, he can afford that because he's wealthy. Now, and there's two things or conclusions you can draw from that when you look at that. Like, one is no, we should all be equal, right? So nobody should be able to access that, right? If not everyone can equally access that. Or the other is how can we more make it more accessible for everyone? Like how can we reduce the costs for more patients who are not as wealthy to have these kinds of options? And again, under a more regulated model with oversight. So instead of offshore stem cell clinics in Mexico or in so or in Honduras, where I'm actually am, right? So there's actually also an offshore clinic here in Prosper, and it's a whole other story. I think offshore clinics don't have the best reputation, and many of them don't work. Some of them do, right? So don't have the worst intentions. But anyway, we can want to bring the costs down for individual patients. I think something would be gained there. And the other thing is, and that's something that I frequently, sort of my podcast is all about regulations, how to do it well and how to not do it well. Unfortunately, lots of the regulations we get are bad, but there's a way to do good regulations, right? And I just want to create a process where we good regulations survive and bad regulations don't survive, right? So any sophisticated market will have regulations, right? So even the free market will gravitate towards institutions with regulatory functions. And one thing that I learned is, and that's very relevant, the um sort of as Milton Friedman said, that you know, a policy that someone in DC uh dreams up often has the opposite of the intended effect, right? So judge a policy by its effects, not by its intentions. So many policies that have the intention to protect someone, like to protect a minority or to protect a patient, what they do is the opposite. Why? Because they increase the risk for a company to serve that person. So if there's lots of protections, there's potential risks and liabilities for any company to serve that person. So what they do as a result, well, they serve that constituent less. Right? That's why, for example, pregnant women have like what the very little uh few amounts of drugs, I think no drugs that are FDA approved available, um, and they're using sort of off-label drugs that we don't have a lot of data on, right? Because like um mothers with uh pregnant mothers are some of the most protected in terms of other regulations that we have. It's like the worst thing that can happen if something goes wrong. So it's a human impulse or instinct, right? We all want to do the right thing and protect patients, and that's a good thing, and some of these regulations to protect patients are good, but we tend to overdo it because we have a bias and we don't see the unintended sort of bastia-like consequences of these kinds of policies.
SPEAKER_01It's certainly frustrating that drug regulation and the therapeutic regulation takes as long as it does. And there's certainly a lot of uh excitement about uh people developing bespoke therapies for themselves, for sure. Uh it's just that it's hard to get around the the small and single-arm nature of you're trying to do, in the sense that it's great to generate that data, but not all data is equal, right? So if I have a single-arm trial, it's just gonna be very hard to sort out one toxicity because the N is so small. So you may have a 30-patient, even 80 person, uh, in an 80 person study drug looks at least it looks okay and it's not toxic, right? But we know with the COVID vaccine, for instance, right? The rate, I mean the large randomized control trials miss the fact that young teenage boys had a one in five thousand rate of vaccine mycorrhis. So essentially you're running people need to understand that you're running an experiment. As long as people understand that and people are straight about it, then yeah, sure, why not avail yourself of these type of therapies? But you talked about talk to me about smart regulations. So you started that talking about there is smart regulations. What would you do? Like if you controlled and you had carte blanche over the FDA. I mean, this past FDA, the prior governance of the FDA, they put out a lot of output that was actually pretty impressive, that wasn't a rigid framework, right? They outlined a plausible mechanism pathway. They outlined the fact that you don't need two randomized control trials, you could do one plus confirmatory evidence. They even kind of left the frequentist model, which is of statistical analysis, and said, look, if there's a pre-existing likelihood of something working different from a variety of different sources, then you don't necessarily throw away that information when you're doing that next trial, generating that next level of evidence. Is that the type of detail you're talking about when you're talking about smarter regulation, like what they were doing? Or do you have something different in mind?
SPEAKER_02Yeah, I mean that pretty much like all the policies that you mentioned. I think these are all pretty good. Like, I mean, plausible mechanism, of course, would need to be administered well, right? So otherwise it has the same problem as the other sort of accelerated approval pathways that you mentioned before, right? So and I think that's often the problem with giving, with having everything centralized in one regulator at the FDA, right? So the assumption behind every regulatory change is that they administer it well. Very often the regulation is not the problem. Guidance by the FDA is often really good, but it's the administration of it, right? So you need to have like very advanced scientific concepts be able to administer it by a bureaucracy, right? By people that are, you know, tending to be risk-averse, tending to not come from the free market or from the private markets, where you need to be like very customer-friendly. People who are not necessarily getting the upside when something works, but they're getting the downside if something doesn't work. So I think smart regulation is kind of has is using market mechanisms instead of having everything centralized in one organization, right, instead of one regulator. So, and by the way, this one bookmark, I'm really love to note out about Bayesian trial designs, because actually, in the previous company that I did in market research, I'm actually one of the first ones who developed a commercial product around with Andrew German's post-stratification and multilevel regression techniques. So these are kind of a very strong Bayesian frequentist kind of fusion. And actually, that would be also eventually my dream to use sort of the evidence generation in streamlined data collection from the state programs to do exactly that. But I'm bookmarking this in case you want to double-click on that. But your question was around smart regulation. So I would kind of distinguish between sort of three stages of smart regulation. One is the one we have now, one is the one that's ideal, the last one, and the second one is kind of what's realistic or feasible right now in the United States as is. There's private auditors of firms like Deloitte or an Accenture, right, that are having kind of a regulatory function, right, to provide private review. Right. And there's sort of still a backstop in state authority, right? And there's still oversight, you need to be registered, right? So in case something goes wrong, the state can take away your license, right? But you're using more market mechanisms. So you're creating a business model where private reviewers can do more of the work. So you're relying less on sort of the administration of what is just a very inefficient model of running an organization as a public agency, right? And you're using market mechanisms. And I think that's feasible, and that's kind of what the Multana model is, right? And you know, precedent for that is notified bodies in Europe for medical devices, IRBs in the United States are kind of also a mechanism that follows like the FDA common rule, and you just register with them, but you don't have to, the FDA doesn't approve human subject, every individual human subject research. There's a whole bunch of other problems with them, but I think sort of the regulatory form of it, it's actually quite good. Sort of a more notification-based system where you're regulating outcomes after the fact rather than being prescriptive about it, right? So you need the approval before I let you do certain things. Sort of that is generally sort of within the realm of the possible. Now there's kind of a third possibility, right? And that's kind of what I learned and what inspires me a lot from being here in Prospera, right, which is kind of a free market-oriented, special economic zone startup city. You find lots of podcasts where I talk about that. But they have this very interesting model where they say, hey, nobody has a monopoly to be the health authority. But if you're doing activities in a regulated industry where there is a risk of harm to unconsenting third parties, like there is in healthcare for sure, you need to get mandatory, regulatory or liability insurance. Right? So you need to be a registered business and you need to have insurance before you treat anyone, say when you're a clinic. Now then you go to the insurer and the insurer will give you a policy, i.e. a regulation. Right. And the insurer will have the incentive to not over-regulate you. Otherwise, they wouldn't have enough business and you would go to someone else. But they also don't want to under-regulate you. Otherwise, they have to pay. Right? So this way you have market mechanisms that select for the right kind of risk innovation trade-off. So I think that is called kind of ultimately the best idea how to do regulations in a smart way. But we're not ready for that yet. It's a bit too early for that. We're kind of testing it out a bit in a sandbox in Prospera, and lots of businesses actually run already like that. But in the United States, there is several blockers to that. So I think sort of the building on things that Dubai or Australia for that matter are doing right with sort of notification-based phase one trials. I think that is ready for in the United States for change. And it's also, in fact, many of those things are also discussed at the federal level. Fascinating.
SPEAKER_01One of the things that you mentioned, well, one, sorry, the story, you know, the story of the uh GitLab, right? GitLab. You remember that story? And one of the things that struck me about that story was that he had some cancer osteosarcoma, I believe. That is, I mean, it's a miserable, miserable cancer, high rates of recurrence and very disfiguring surgeries, typically depending on where it is, uh, was that he yeah one, he did not just use the therapy that he had fashioned. And one, the therapy was not one that he fashioned, right? What he did was he found through some German company that there was overexpression of some receptor, right? On of his tumor, right? And that was the thing that wasn't being conventionally done. But there was something on the shelf that bound to that receptor, and that was what he elected somehow to get. But that was part of a multi-drug regimen. That wasn't just the only thing he got. And the fact so one, we don't know for sure which one is working, right? Seems reasonable. I mean, I don't know what do I know? It seems, you know, I'm basically a lay person when we're talking about oncology. It seems reasonable to do, but who knows? And then the other thing that was really interesting was that, and I this really struck me on his thread, was that his biggest frustrations weren't necessarily getting somebody in the United States to allow him to access this, this, this ligand that his tumor was the tumors were overexpressing the receptor of. His biggest issue was the hospital IRBs, that there would be some guy in some IRB that would be like, nope, this is too dangerous for you. I can't give it to you. I don't want you to get it, right? And then the other thing was the pathology departments. Do you remember this thread where he said uh they they won't give him his tissue? Yeah, exactly. All right. So how does uh Montana solve the problem of hospital IRBs? Yeah, yeah. Because he's gonna need because somebody's gonna need to go get a biopsy at a hospital. I I assume most clinics, outpatient clinics are not gonna be doing liver biopsies, say, right? And then you're gonna, I guess depending on, I guess the infusion if it's done at a private clinic, that can be done there. But suppose somebody like this, cancer lift, for instance, is complicated, he needs a bunch of different things. I guess if he has to do it at the hospital, hospitals not gonna necessarily allow him to do that. So how does Montana solve that? And and I guess is the Montana health system establishment infrastructure are they supportive of what you're trying to do?
SPEAKER_02Yeah. Yeah. So uh Sit had this post of like these 14 policy proposals, like from his experience and what he would change and what he would recommend changing. And the Montana model is knocking out like eight of them in one, right? So one is so about the IRB thing specifically, which is the first. Now it has to be kind of a bit seen how the market develops, right? So we are the first kind of IRB, but it's not an IRB, right? So an ETRB is not the same as an IRB, it's a different jurisdiction. But we're kind of transferring the same model into the state. One thing that's different is that the ETRBs on the state level in Motana, they're actually required to be independent from the hospital or from the clinic or from the institution, the university. Now, in the beginning, I actually didn't like that because I thought, hey, free market, let's be flexible and let's see what survives the market test. Now I actually think that's quite a good idea because what I've seen before, if I put the analogy in a different industry in market research, I think the problem with IRBs and why they're so fragmented is that each institution, like especially large institutions, have a lot of stakes, they want to have control, right? So they, you know, they want to not rely on trusting like an IRB from another organization if they don't have to, right? If there's no strong incentive to be fast. Right. So they kind of see it as a risk mitigation thing, and they don't see a strong business need or urgency to sort of coordinate with other IRBs or like what SID wants where that you have that you can choose any federally compliant institutional IRB, and then you can basically do it without the IRB review at that site. It could lead to a model where IRBs are a bit more functional, a bit more centralized, because they have the market incentive to do so. Right. If you as the ETRB does not part or doesn't make the money from, like you're not paid by the hospital that you're in or by the university, right? You're not sitting, you're not a professor at this institution, you have the commercial incentive to be available in um sort of quality assured ways at lots of different sites. Maybe you even have the incentive to be focused on specific treatment areas. Maybe there will be TRBs that are very focused on oncology or whatever. And then I think you'll have much more streamlined kind of review for like the state medical practice in that case, right? It's not the same thing as clinical trials. So it remains to be seen how it turns out, but I actually think that the idea by Montana to make to require this independent IRB is very good. It's very regulated, right? So you see you have many different parties that you need, sort of the biotech sponsor, the ETRB, and the clinic, right? The experimental treatment center, which is a separate clinic license. Now we're doing seeing a huge interest in Montana right now. We do but um there's about like six or seven parties that are saying that they want to open a clinic. One is actually a very large one, a very large hospital system in the state that have been kind of on the forefront on this very much from the beginning, right? And one of their board members was actually one of the key advocates for SB535 in the legislature. So I was very surprised by how fast they want to move there. But still, it remains to be seen, right? So right now, um, for since two weeks, clinics can apply for licenses. And the process to get a license may take, you know, it can take longer than 90 days. Um, but we'll see. And we're actually actually really looking for clinics and hospitals in Montana that that want to adopt it. So we see curiosity, but we also have to see now all right, now are you gonna put skin in the game? Are you gonna do treatments? Because the biotechs are ready. We have more than 20 companies that are what that wanted to give their treatments to make their treatments available in Montana.
SPEAKER_01So the big ask seems to be for you to have clinicians who want to deliver services, whatever those services are, or the biotech, you've got a bunch of biotech folks, but you need clinicians to be able to deliver those in clinics. Is that will that be accurate?
SPEAKER_02Yeah, I mean, ultimately, we think sort of the demand from patients is mediated by the clinic, right? So the clinic and the physician, the practice knows their patients, right? We actually have gotten guidance from one of the potential large hospital systems there that they're actually particularly interested in the usual treatment areas like oncology, neurodegenerative, cardiovascular, but they're also interested in what they call healthy aging, right? So it's not sort of the biohacker peptide, self-optimization longevity, but it's for an older population, but that it's addressing things like frailty and well, as the name says, healthy aging. Right. So that's I think a plausible indication of the demand there, right? So I don't see the demand for Brian Johnson type, biohacking, interest in sort of the longevity side, but still for concrete diseases of aging and attending older and wealthier population.
SPEAKER_01So question the immediate thing that comes to mind as a guy that runs a or tries to run private practices who is, I mean, so I would be responsible for data gathering, follow-up, if there's a reaction in the clinic, that'd be in charge of managing it. That requires a certain infrastructure. Yeah.
SPEAKER_02So you would have to, you would know a bit better how to assess sort of the regulatory framework specifically for you as a clinic. But what Montana did is my impression is basically largely copying it from other similar clinic categories. Right. So this is not completely novel, other than that you do need a review by a review board, by an ETRB, right? So you can't provide a patient with treatments unless you have the approval for it by an active ETRB. Right. So other than that, I presume most questions around how do you what do you require to report, the regulator and whatever, are pretty similar to other clinical categories.
SPEAKER_01You do have to How is that paid for? Like if you're running, if you're a site for oncology or cardiology, et cetera, you're getting paid by the pharmaceutical companies to run these trials per patient. There's an enrollment. And then of course, if you're actually commercially doing it, meaning if you're if you know, if you have an oncology patient that you're administering a drug to, right, there's a Built-in amount you get paid relative to the to the drug, right? There's a percentage that you make for the drug because you're storing it and ordering it and all that other stuff. So how does that work? How does that work?
SPEAKER_00Data collection is extremely expensive. I mean, data collection is really expensive. Yeah. Being in the neurosurgery world, the drug things are not that not that bad. Just a prospective observational trial. I mean, if you're going to enroll 100 people, you essentially need one FTE just to take the numbers out of the EHR, write them on a clipboard, submit it into the other computer system that doesn't talk to your EHR. These are real obstacles just in gathering and collecting data.
SPEAKER_02Now in my ideal worlds with my company with Infinita, we can provide a streamlined solution for that. So I can't promise that yet, right? You haven't done it or build it yet, but I actually have looked into one very clear kind of solution that could streamline that data collection. I haven't deployed it yet, right? So I'm not confident saying I have sorted it out. But that was kind of my career before, right? So in market research, I basically built large data collection infrastructures, right? So it wasn't with medical data, right? So but some of the tools that I've seen would already ensure that it's collected in HIPAA-compliant ways and all of that. So if um if I do a good job, I hopefully have most of that solved if you're a clinic and want to and want to do this, right? So other than that, and what's sort of the payment model? Well, the law is completely open and non-prescriptive, right? So they very explicitly says you can it's not required, a patient it cannot, it's not required by insurance to be paid, right? So insurance don't have to cover it, and it's flexible to any payment arrangements. So these can range from for profit through again private insurance. But I do think that or the assumption is generally that's that it's starting at least as a cash payment.
SPEAKER_00I see. Really interested in the the data further in the data analysis and because you're essentially going to be collecting a lot of observational data, not randomized controlled trial data, which is important. There's flaws in both, right? I think the RCTs are extremely flawed. Again, coming from neurosurgery, we have very few RCTs. Most of the things that we do have no randomized evidence behind them and really can't because we don't see clinical equipoise. So one worry I have is, and maybe this is a good problem to have, but some some observational data may carry such a strong signal that once you have that, it's going to be really hard to subsequently do a randomized control trial because the equipoise window will have passed. But also is that there's going to be a lot of really messy data, as Anisha alluded to earlier, a lot of N of one type situations where you don't know how much of the results are influenced by patient preferences, any of the other millions of things that you can try to adjust for in a regression model, but may not. So how do you think that this is going to handle it? I always think, of course, more data is probably better, but there's a real risk of having some kind of junk data out there as well.
SPEAKER_02Yeah. I mean, ultimately, that's I think where the biggest upside is if someone, and I hope I'm the one, to figure that out, to streamline that data collection. Right. Again, it's something that I've done before, and it's kind of why I'm doing this. So uh, but the alternative is of course that it could be sort of a very fragmented system, everyone's trying their own solution. Right. I'm going to try to play the role and tell like the biotechs, the companies, hey, work with me on top of the solution that I have already built. And same with the clinics, right? So how successful I will be with that, we'll see. But I mean, the solution that I want to use is already used by a lot of clinics. So I think that makes that a lot easier. I don't have to build that from scratch. So we'll see how that turns out. But I think that's ultimately what will be a large part in determining the success of these state programs. When it comes to like what do we learn from it for public health, right? That's ultimately my pitch also to the FDA. Like, guys, we generate additional data, that data could be used as part of official INDs. We all gain from this. Right. So in my ideal world, we can also hopefully at some point randomize through these medical practice-based legal framework, right? So I'm not against randomization of RCTs. I like them. I think they're very expensive and you don't need to use them all the time, right? And you also just often have don't have enough data beforehand, right? Because you have like this one shot on goal to like sharpen the trial, right? So when you have a sort of hundred million dollar line item of a trial, like aren't there like smaller steps? So you learn this like the iteration loop is not is not ideal, right? When you're a company, when you try to you need to try new things all the time. And like the key variable when you have startups is keep your cost of failure low because you're gonna fail all the time, right? So it's just that the clinical trials, the way they're currently done, have a very high bar, a very high cost of failure that makes a lot of testing and data collection simply uneconomical. And I think this is again, could be a way to collect data in a cheaper way. Um, one thing that I'd be actually very interested in, right? So I've been following a bit this literature, and it kind of intersects with what I've done before in market research studies, or would be kind of one of my critique of clinical trials is so there are often not representative or generalizable to the clinical population, right? So uh you have these studies and you do want to have a clean signal, right? So you're randomizing two populations, and you need to select people that don't, ideally without, you know, that don't have all these comorbidities, that don't take other medications. So you're selecting a systematically much healthier population that's not necessarily representative of what real patients with some of these diseases look like, right? Because they are on other medications and they have comorbidities in all these things. Right. And you need to do that to isolate the signal, right? So again, when you then do it, sort of you have the more lab condition results, does it apply to your clinic? That's actually what I found a very large literature, surprisingly large, which basically says it isn't, right? And there's you know all these factors that is complicated. Like when you're in the clinic, there's all these complicated factors that you just don't have a clean read or a lot of data on. Right. There's even more literature that's saying are proposing the model of what they call clinically embedded trials. Right? They're proposing this more for like post-market studies, right, after it's FDA approved. They apparently don't have the idea that that could also use sort of to generate much of the same data. But I'm like, okay, why don't we start in a more real-world condition, right? So in the clinic, streamline the data collection as much as we can. Some patients want access to things and are willing to pay for it, right? This can drive down the cost of data collection, and then offer patients, all right, or the let the biotech decide, let the company decide, all right. We do need FDA approval now, right, because this gives us like insurance coverage or whatever. So we can't give this to people anymore. We need to recruit people for a randomized controlled trial, right? So we're no longer making this available for right-to-trial early access. So I do think, you know, between companies and patients, they can make the choice. And I think with the insurance system as it is, that would be a very good incentive for them to do so. And we can actually advocate for the FDA, like do what you're good at, right? So be actually strict when you're gaining access to public insurance, where then all the taxpayers have to pay for it.
SPEAKER_00Is this largely a domestic answer to what China's doing? I mean, they they've really reduced the friction in getting phase one and phase two data and then are licensing a lot of those molecules to US firms. Is this kind of a domestic answer to that?
SPEAKER_02Yeah, I mean, my knowledge on China is largely based on one of your previous guests on Premier, right? So uh they definitely have been able to reduce the timeline to phase one trials, one of which was just really the IND approval, right? So they reduced the timeline, I think, from like a thousand days that's their regulator reviewed the IND, like three years, um, to like 40 days that you can start a trial, right? So just really being competent at the administration of things. China also has this a system, I think it's also somewhat similar to Australia, where basically when you have sort of the IRB-like approval, we have like a principal investigator at a university, you don't need to sort of wait for the centralized approval, but you can like already start and then like report results. I'm not 100% sure how exactly that works, right? I haven't seen it live, but China is definitely doing sort of some of the best practices from Australia and just being more competent at the administration. Krim, you also talked about something like along the lines of that they just do a much better job afterwards and making sure that the companies are being are able to profit from that after. So but I'm to be honest, it should leave that to explain to someone who knows that much better than I do.
SPEAKER_01Yeah, so the randomized control trials with the ideal population kind of represent the maximum, probably the maximal effect that you're gonna have. If it's run right, if there's no fraud, which is all, you know, which is of course, we hope that happens most of the time. Um so that's the maximum signal. No fraud. That's the maximal signal you're gonna get. Then when you generalize it to the population, as clinicians or want to do, because you have patients that need things, they they check off a box in terms of indication, but like they're different. Yeah, it's anyone's guess whether you're actually giving them that type of benefit, the same type of benefit. You know, so and there's ample, ample, ample data to suggest that approach of generalizing creates harm. So Serepta elevitis, that gene therapy, Peter Marx, the former FDA CBER had uh expanded the indication for a drug that was questionably that questionably worked. It wasn't even clear that it worked in the target population, but because it was an unmet need and these their patient advocacy groups were obviously very convincing, extended this to beyond the trial, and there were multiple children that unfortunately died. Speronalctone, a common drug for heart failure. You know, it's this you know shown to have mortality benefit and heart failure. Interestingly enough, when you do a real-world analysis of what happened after spironal lactone was widely administered to the population, well beyond its trial population, there's a lot more hospitalizations for hyperkalemia, which is one of the common side effects of spermal lactone. So medicine is just extremely, extremely hard.
SPEAKER_02So uh I mean that's just like I learned so much from from you guys on that, actually. Like once you see it, you can't unsee it. Like when you see all these like mid-cap biotech investors on X, like shilling their Unique or whatever, and like the stock moves basically with a press release from and these companies then have like hundreds of millions in cash to like lobby for things. It's like there's something deeply wrong here.
SPEAKER_00It's yeah, it I I don't think the public really realizes like how hard it is to recruit a patient for a clinical trial. For example, you may be a high volume center for condition X, but again, as we alluded to, the the criteria are so restrictive, right? I mean, I I've been a part of these clinical trials, but somebody comes in and they don't speak the language that's on the consent, so you can't, you know, or they're you know slightly outside the age range, so they go out, or they're homeless, so you don't think that they're gonna follow up, right? Because follow-up is is an issue. You need long-term follow-up for these. So they're out, right? And so you really have like a sliver of the total patient population with a condition that actually get into these trials. It's very disheartening trying to run them.
SPEAKER_02Yeah. And then you simply also don't have like the data on what happens to these other patients that will have all these problems and comorbidities or whatever, right? Very systematically excluding or making the sample less generalizable, um, and you don't know in what direction, right? You're blind or left.
SPEAKER_01Yeah. So it does seem like you're hitting on the one of the bottlenecks, I should say, but it's an important one in terms of how does one easily generate data from a real world. And of course, that's fraught, but right now we don't even have a great way of doing that in a way that doesn't like, you know, bog down physicians or require extra expenses and stuff. This has been great, Nicholas. Thank you so much for coming on. I I have to ask you a little bit off topic, but uh I have to ask you, you're talking to us from a island near Honduras, is that right? Yeah, it's a part of the country of Honduras, it's called Robotan. Yes, Robotan, which is a kind of a this is the the biology Srinivasan network state, set up economic zones. You don't, you know, the you don't need to be uh anywhere, right? So it's like the you know, blood and soil, you know, forget that part. We can we can set up these collections elsewhere. Now, biology has run into some issues in Malaysia, I guess. What is the feasibility of economic zones, uh, do you think, generally speaking?
SPEAKER_00It's basically a libertarian like paradise island, is it not? This uh Prospera. I was just reading about it too.
SPEAKER_02Yeah, sure. I mean, though, Rotan is not just Prospera, right? So Rotan is uh it's only two hours daily direct flights from Miami and Houston, actually, and it has like one to two million tourists per year, most of which are from the United States. It has large and massive cruise ships. It's an early Hawaii, basically, right? In Prospera. Island has the size of about Hong Kong Island and a population of 50 to 100,000. And Prospera there has land about the size of Monaco, right? So we're like 100, 150 people in there, I give and take, right? So yeah, we're kind of in that space. Uh lots to talk about there. I've been on lots of podcasts about that. Balgi is also an investor in my company, and I've been presenting at his network state conference or whatever. There's some disagreements I have with him about the concept, right? So I think the most important thing, and he learned that in Malaysia, is you kind of set up a win-win relationship from the beginning with the country you're in, right? I also now think that it is actually good to be in one place, at least when you build a physical location, right? So there is some ideas of how you can have like different nodes, and there's some use to that. But special economic zones are not a new model, they are proven model, right? So there's more than 5,000 special economic zones around the world. They're basically what made China's economic miracle. So there's a very interesting book by Ronald Coase, the Nobel Prize winning economist, about exactly that. And yeah, they looked at the success of Hong Kong, then of Singapore, and Panama is very successful with special economic zones, Uruguay these days, right? So opportunity zones are not even uncommon in the United States. Right. So the approach to have kind of smaller jurisdictions that have more local autonomy, sort of Switzerland style, um, that is not new, right? Dubai has kind of also perfected that, right? So they have like 30 different special economic zones. Much of these zones you can incorporate a business in some of them. In some of them, you have like an international arbitration center that's based on British common law to be more business friendly. So this is not like a completely sort of libertarian utopian idea. At least that's, you know, you can have these ideas, but then you need to go kind of into the real world to do something what benefits a partner. And you need to make sure you have sort of some alignment or tie-in or benefit or externality, positive externality that you create with the government that has you in their territory, right? Sort of the whole talk about, you know, state within a state or whatever, you know, that's something that people try to accuse of in prosperity, but it's just not true. Right? So the model, the framework that was developed here in Honduras came from Honduras, from actually really, really smart attorneys that were like Harvard educated and are basically, you know, hey, our country is in a desperate situation. What can we do to make this country attractive? And they were looking at Dubai, at Switzerland, at China. It was like, this is what we're going to do. And they developed a really good framework for that. So I think that has a lot of potential. I tried originally to do sort of to realize some of my ideas around biotech and healthcare here. I kind of realized that, you know, it will take a very long time, right? So until like an offshore jurisdiction has sort of that institutional credibility that the biotechs could count on, or right, if they generate data here, the FDA could accept it. It would just take a very long time, you know, generating the medical infrastructure and clinics here until that's the case. So I still still kind of proudly aware it as a brand, and I'm organizing conferences here, and you we had like major like scientists here and the biologies or Tim Drapers and other Ravi Khan's of the world. And it has a lot of potential, but commercially I'm now focused on the Montana model in the United States, where I think it is there's just much been much higher demand on the side of biotech companies. And I also just feel like even in my discussions with the A at the federal level, there seems to be an appetite. Hey, we need to try out some of these things. And this is sort of not something medical freedom outside of the institutions, but it is a model that's built to gain institutional credibility and adoption eventually.
SPEAKER_00So Anish, when they pass Medicare for All and we need to go set up a hospital. I'm calling Nicholas.
SPEAKER_01Two hours from Miami, there we go. Yeah. Where is the economic zone that we can set up?
SPEAKER_02So there's actually in two or three weeks, there is a free cities conference here in Prospera on September 5th to 6th, right? So there you see some other projects in some other parts of the world that are doing things like that. And um yeah, it's pretty easy to get here, right? So Miami and Houston have daily direct flights that take only two hours. And from there it's a 15-20 minute car ride to get here.
SPEAKER_01Oh wow, fantastic. Well, cool. Another place to go, sir.
SPEAKER_02Yeah.
SPEAKER_01All right, Nicholas, thank thank you so much for being patient with us as you kind of explained everything. That was really great. Thanks so much for having me on, guys.
SPEAKER_02And I mean, you guys are really on a roll, like the guests you're bringing and the insights you're getting. So super excited to continue follow your trajectory and learn more. I appreciate it.
SPEAKER_00Don't forget uh plug your podcast again for us, please.
SPEAKER_02Yep, the Stranded Technologies Podcast that uh you should also be on at some point. Oh, wonderful.
SPEAKER_00Thanks so much.
SPEAKER_03Thanks.