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Speaker 1: Hello, and welcome to another episode of the All Thoughts Podcast.

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Speaker 1: I'm Tracy Alloway.

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Speaker 2: And I'm Joe Wisenthal.

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Speaker 1: Joe, would you ever go on ozembic?

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Speaker 3: Oh?

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Speaker 2: Yeah, definitely?

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Speaker 3: Yeah?

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Speaker 2: Really well yeah, well not. This seems fun.

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Speaker 4: It reduces your appetite, probably lose weight. It seems like

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Speaker 4: it also has a bunch of other I keep seeing

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Speaker 4: these other things, like it's good for like, you know,

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Speaker 4: impulse control and all kinds of positive things that, yeah,

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Speaker 4: why not.

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Speaker 1: Yeah, it's supposed to be good for impulses and addiction.

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Speaker 1: And also I think there's some new stat out saying

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Speaker 1: that it reduces the risk of heart attack and stroke

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Speaker 1: by twenty percent. Well, anyway, who would you?

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Speaker 3: I think?

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Speaker 1: Yes, however, I would definitely wait for the price to

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Speaker 1: come down a little bit and maybe for more of

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Speaker 1: the side effects to become a parent, but I'm very

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Speaker 1: cautious with these sorts of medical breakthroughs.

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Speaker 5: Uh.

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Speaker 2: Yeah, I have to. I feel like my like, I

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Speaker 2: don't know that.

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Speaker 4: Much about all these drugs like ozimpic and mcgovey and

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Speaker 4: the other golp ones, but they seem pretty great, and

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Speaker 4: I'm just like, yeah, upward and onward. The March of

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Speaker 4: progress science. I love it, no, but I actually do

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Speaker 4: think like it is. Something I've been thinking about is

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Speaker 4: like people are so skeptical of even the possibility of

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Speaker 4: the existence of a wonder drug.

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Speaker 2: The people are like, Oh, it's.

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Speaker 4: Going to do this, it's going to do this, it's

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Speaker 4: going to be bad, it's going to reverse, it's going

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Speaker 4: to and maybe that's possible.

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Speaker 2: But what if it really is a wonder drug?

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Speaker 1: Well exactly, And I think it opens up a ton

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Speaker 1: of interesting questions, specifically about what it means for wider

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Speaker 1: society and the wider economy. When we know that obesity

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Speaker 1: and diseases like diabetes have been this huge weight on

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Speaker 1: both the socio economy and the healthcare industry.

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Speaker 4: Obesity itself is like just this gigantic economic force. It's

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Speaker 4: a business force. There are businesses that thrive on how

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Speaker 4: much people like to eat unhealthy foods.

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Speaker 2: They're huge costs to ensures.

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Speaker 4: There are other second order effects of related to injuries

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Speaker 4: and heart complications and so forth. It's such a modern

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Speaker 4: important phenomenon that we're there to be and maybe it

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Speaker 4: kind of looks like there is, but.

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Speaker 2: We're there to be.

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Speaker 4: This sort of like straightforward way to reduce obesity. It

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Speaker 4: seems like the implications would be huge.

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Speaker 1: Right, And I keep getting visions of like Star Trek

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Speaker 1: in my head where everyone is kind of slim and

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Speaker 1: dressed in tracks great and very athletically capable, and we

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Speaker 1: all just wander around spaceships. So that sounds great.

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Speaker 5: Well.

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Speaker 1: Anyway, on a serious note, I think we need to

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Speaker 1: dive into these new sets of drugs. What exactly are they,

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Speaker 1: how do they work, and more importantly, more interestingly, what

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Speaker 1: do they actually mean for the wider economy and the

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Speaker 1: business environment.

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Speaker 4: So many I'm so glad we're doing it because it

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Speaker 4: does feel like beyond just the companies selling these drugs,

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Speaker 4: which we know have been taken off. We're recording this

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Speaker 4: on August ninth. Just yesterday Nova and Nordis, the Danish company,

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Speaker 4: soared because they had another test showing that one of

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Speaker 4: these drugs was very good for fighting heart disease. So

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Speaker 4: we know that there's like the interest in the vendors

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Speaker 4: the sellers of these drugs. But again, what does it

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Speaker 4: mean all these second and third order effects if they

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Speaker 4: really become extremely widespread and it kind of looks like

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Speaker 4: they're on the trajectory feels very unexplored.

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Speaker 1: Yep, So let's dive into those second order effects of

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Speaker 1: miracle weight loss drugs. A fun episode ahead. We have

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Speaker 1: really the perfect guest. We're going to be speaking with

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Speaker 1: James Van Galen of Citrinidus Capital also known as Citrini

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Speaker 1: on Twitter. So, James, thank you so much for coming on.

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Speaker 5: All thoughts, Hi, Tracy, Joe, thanks for having me.

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Speaker 1: So, James, from what I remember, you actually have something

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Speaker 1: of a medical background. Is that right?

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Speaker 5: Yeah? I worked my way through undergrad as a paramedic

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Speaker 5: for a while in Bridgeport, Connecticut, and then when I

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Speaker 5: transferred to UCLA, I worked as a paramedic in Compton, California.

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Speaker 5: So I'm not a stranger to the medical field. Then

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Speaker 5: for about four years I started what co founded one

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Speaker 5: of Connecticut's first medical marijuana dispensaries. So I definitely am

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Speaker 5: not a stranger to the medical field. Now I do

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Speaker 5: the hedge fun thing, and it comes in andy once

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Speaker 5: in a while.

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Speaker 4: Investing in medical technology or sorry, you know, I or biotech.

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Speaker 4: Often it seems like the sort of like Roulette wheel,

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Speaker 4: And I'm always skeptical that anyone who is like not

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Speaker 4: a scientist can actually have informed insights on new medicines

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Speaker 4: and how big they could get, et cetera. Can you

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Speaker 4: just sort of like give your overview of like how

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Speaker 4: do you even like think about these things? Like if

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Speaker 4: you're not like a scientist, how do you even begin

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Speaker 4: to wrap your head around like how do these drugs work?

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Speaker 4: And how big they could be? And which ones I

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Speaker 4: have more potential than others? Like what's your like framework

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Speaker 4: for like sort of just like evaluating some breakthrough in

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Speaker 4: the first place.

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Speaker 5: I mean, I don't do a ton of like biopharma investing.

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Speaker 5: I'm not a scientist, but I do have a bus

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Speaker 5: network of channel checks and I'm a big proponent of

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Speaker 5: basically if you don't know something, ask you know, and

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Speaker 5: we are so so I am. You know, I'm always

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Speaker 5: bothering them, and you know I'll cost me as a

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Speaker 5: couple of dinners or something. And but you know, I

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Speaker 5: don't do much, if any investing in companies that are

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Speaker 5: still clinical stage, right, And you know, a lot of

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Speaker 5: my investing is kind of thematic investing. It's focused on

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Speaker 5: these kind of paradigm shifts, these mega trends essentially, and

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Speaker 5: when you see something like this, right, you know, all

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Speaker 5: the feedback from channel checks is good, and it's something

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Speaker 5: that we kind of needed as a you know, as

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Speaker 5: a in developed markets at least for decades, right, And

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Speaker 5: you just see the kind of behavioral incentives that exist

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Speaker 5: surrounding it. And I always come back to basically you

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Speaker 5: look at like viagra in the nineties, and you know,

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Speaker 5: you did not have to be a doctor to kind

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Speaker 5: of see Pfiser just killing it, you know, just doing

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Speaker 5: amazingly with this drug that solved the problem that people

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Speaker 5: had that you know, needed to be fixed and it worked.

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Speaker 5: And you know, honestly, that might be the reason that

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Speaker 5: most of us know who Phiser is, right. So you know,

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Speaker 5: whether it's buying Maderna when they're developing a co vaccine,

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Speaker 5: or buying Eli Lilly when they're developing, you know, a

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Speaker 5: fat vaccine, or a Pfiser with Bager in the nineties,

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Speaker 5: it all falls under the mega trend looking for kind

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Speaker 5: of these paradigm thematic shifts.

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Speaker 1: I think people forget nowadays that viagra was initially developed

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Speaker 1: for something totally different to what it's used, and that

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Speaker 1: happened to be a sort of happy side effect of

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Speaker 1: the medication. I guess and then it became known for that.

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Speaker 1: But just on this note, let me ask the basic question,

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Speaker 1: So how did these drugs gop one I'm not even

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Speaker 1: sure what that stands for, but how did these come

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Speaker 1: into being? And how are they starting to spread through

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Speaker 1: the market such that I meet vcs who will openly

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Speaker 1: say that they're on a zempic and I'm pretty sure

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Speaker 1: they don't actually have diabetes.

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Speaker 5: You know. So GOLP one stands for glucagon like peptide,

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Speaker 5: not to get I don't want to get like two

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Speaker 5: scientific but basically, the peptide helps kind of prime insulin release, right.

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Speaker 5: It allows the body to absorb glucose after a meal,

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Speaker 5: and you have specific cells in your pancreas that can

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Speaker 5: recognize GLP one through what molecules called receptors. Right. So

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Speaker 5: essentially we've been looking into these drugs you know, called peptider.

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Speaker 5: The medical field has been looking into them, you know,

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Speaker 5: since the seventies. And GLP one's primary benefit was the

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Speaker 5: fact that it was able to produce blood glucose levels

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Speaker 5: via insulin release, which is you know, very desirable in

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Speaker 5: a patient with diabetes. And the thing was the you know,

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Speaker 5: when it comes to peptides. Normally, you're trying to mimic

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Speaker 5: the peptide that your own body produces. So the actual

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Speaker 5: molecule glucagon like peptide one is only to able to

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Speaker 5: create these effects for a very short time span. And

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Speaker 5: so what these genius anders discovered was that they can

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Speaker 5: essentially mimic these hormones and have these molecules that bind

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Speaker 5: to the receptors they're called agonists, right, and that can

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Speaker 5: create an effect that lasts, you know, four hours or

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Speaker 5: even weeks. And that was basically the basis of the

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Speaker 5: initial development and the impetus for it was essentially to

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Speaker 5: go after diabetes. Right. If you have something that can

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Speaker 5: regulate glucose that is possibly dysregulated in a patient with diabetes,

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Speaker 5: that's kind of something that seems desirable, right. So they

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Speaker 5: were kind of predicted to also prolong this feeling of

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Speaker 5: you know, fullness and slow gastric emptying. And they also

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Speaker 5: provide a variety effects in the brain. And these drugs

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Speaker 5: do cross the blood brain barrier. And the first GLP

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Speaker 5: one drug that was approved by the FDA was Exenotide.

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Speaker 5: It was marketed under the name Bieta. So Bieta was

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Speaker 5: approved in two thousand and five, right, and primarily be

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Speaker 5: used in type two diabetes. And while you have something

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Speaker 5: like semic glutide right now, which is ozembic generic name frozenpic,

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Speaker 5: and then Munjaro, which is Lily's drug. Ters Appetite is

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Speaker 5: the generic fan. And the thing is once you have

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Speaker 5: a class of drugs, but you can kind of anticipate

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Speaker 5: what the side effect profile will be. It's not necessarily

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Speaker 5: that you can, you know, anticipate every single side effect,

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Speaker 5: but you kind of you get an idea of the

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Speaker 5: structural activity relationship. You get an idea of, you know,

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Speaker 5: this dose dependent curve and where side effects start becoming apparent.

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Speaker 5: And so with GLP ones they have side effects, right,

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Speaker 5: they have some gi side effects, and these GLP one

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Speaker 5: receptor agonists, like semic glutide, they can be pretty bad.

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Speaker 5: But what Lily saw was essentially it was decided that

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Speaker 5: they would try it to go after different receptors in

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Speaker 5: the same system, right, so they kind of get this.

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Speaker 5: It's got like Ter's Appetite. Munjaro is basically a a

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Speaker 5: dual GLP one receptor and then GIP receptor agonists. So

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Speaker 5: the way that that works is the GIP activity allows

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Speaker 5: you to take a higher dose before experiencing the side effects,

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Speaker 5: the GI side effects, and we also kind of know

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Speaker 5: you know these since these drugs, you know, Trulicity was

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Speaker 5: a big one that it was approven I think twenty

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Speaker 5: fourteen for type two diabetes. It saw very wide use.

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Speaker 5: So when you encounter someone and they're like, oh, you know, no,

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Speaker 5: for sure, these drugs are going to aunt your insides,

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Speaker 5: you know, like I don't. I don't blame them for

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Speaker 5: that because if you look at the history of weight

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Speaker 5: loss medication, you think Fenn Fenn, right, which like basically

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Speaker 5: melted your heart. Then you know vermon event, which was

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Speaker 5: like this genius invention where the scientists were like, well,

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Speaker 5: you know the cannabinoid receptors basically the receptors that THHC

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Speaker 5: act on, those make you hungry, So if we block

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Speaker 5: those receptors, then it should make you not hungry. And

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Speaker 5: it did. But you know what else the cannabinoid receptors

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Speaker 5: make you is happy. So I don't know how they

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Speaker 5: didn't see it as coming, but it made people very

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Speaker 5: sad and increase the likelihood that they would commit suicide.

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Speaker 5: And that so that drug was pulled very quickly, and

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Speaker 5: you know, you kind of look at the pass of

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Speaker 5: the weight loss industry. People take you know, tapeworm pills

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Speaker 5: and just doing absolutely insane things, and it's kind of like, Okay,

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Speaker 5: now you have this drug and the absolute worst concern,

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Speaker 5: you know that there's a warning on the FDA label

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Speaker 5: is that it may you know, it may result in

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Speaker 5: thyroid cancer. But the thing is the only time that

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Speaker 5: that's ever been observed with these gop one drugs is

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Speaker 5: in mice. And the thing about mice is when you're

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Speaker 5: doing a trial with a mouse, the mouse is not

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Speaker 5: going to tell you I can't handle these side effects anymore,

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Speaker 5: I'm going to stop taking the injection. Right, No mice

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Speaker 5: drop out of trial studies. So what happens is, you know,

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Speaker 5: like the if you were to take the equivalent dose

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Speaker 5: that caused you know, these endoprin cancers in mice, before

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Speaker 5: you reach that point, you would be so sick to

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Speaker 5: the level of not being able to function. And it

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Speaker 5: is so the dose was much much higher, and that,

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Speaker 5: you know, the it has not been observed in humans.

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Speaker 5: And the other thing is this is probably a little controversial,

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Speaker 5: but the fact is, like obesity is devastating, right, it

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Speaker 5: is absolutely terrible the way that increases mortality. I mean,

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Speaker 5: I'm going to drop some statistics that Lily dropped on

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Speaker 5: an earnings call, which is that you know, there are

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Speaker 5: two hundred and thirty six OBC related health conditions. Type

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Speaker 5: two diabetes risk is increased by two hundred and forty

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Speaker 5: three percent in people with obesity, heart disease by sixty

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Speaker 5: nine percent, high blood pressure by one hundred and thirteen percent,

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Speaker 5: high cholesterol by seventy four percent. And the contribution to

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Speaker 5: all course call all cause mortality is so significant that essentially,

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Speaker 5: if I had a drug that would again this has

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Speaker 5: never been observed in humans, It's probably not going to

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Speaker 5: be because of the relationship that I described with the dose.

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Speaker 5: But let's say I had a drug that one hundred percent,

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Speaker 5: no matter what, forty years you're going to develop that

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Speaker 5: word cancer from me. Even if that was the case,

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Speaker 5: if it also one hundred percent of the time made

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Speaker 5: you not opdes anymore, the net effect on your life

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Speaker 5: expectancy would still be positive.

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Speaker 4: You know, you mentioned in the beginning that you as

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Speaker 4: an investor, you like to think about people called paradigm

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Speaker 4: shifts or mega trends and so forth, and one of

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Speaker 4: the things that thinking about it in this context, and

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Speaker 4: I think there is a very good argument. I'm basically

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Speaker 4: sold that the rise of these drugs will constitute a

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Speaker 4: paradigm shift or a mega trend or something like that,

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Speaker 4: and I feel like many people buy that. But the

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Speaker 4: other thing is that like betting on mega trend often

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Speaker 4: is not trivial in terms of even if you could

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Speaker 4: predict the trend, you might not know what to invest in.

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Speaker 4: And so, you know, a good example might be say

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Speaker 4: like the rise of Chinese industry or something like that

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Speaker 4: over in the you know, in the twenty first century,

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Speaker 4: since it's entry into the WTO. And it's not like

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Speaker 4: I don't think like buying like Chinese stocks have like

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Speaker 4: been like some like extraordinary winner certainly like long stretches

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Speaker 4: of time where that doesn't work. So like, what's the

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Speaker 4: next step from identifying mega trend to then thinking about, okay,

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Speaker 4: these will be actual winners as public market investments.

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Speaker 5: Well, let me talk a little bit about hype, right,

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Speaker 5: You just had Dan Lobe and talking about how it's

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Speaker 5: more important to monitor you know, Reddit boards than it

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Speaker 5: is to monitor fund.

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Speaker 4: Baby Tracy's Tracy's message in her bloombergs.

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Speaker 5: Tracy's ready to ready to spend up a fun that

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Speaker 5: takes advantage of that. I think she's very proud of

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Speaker 5: the redd investors. What was that the guy in the

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Speaker 5: basement has the edge If that's the case.

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Speaker 1: Yeah, well it's all about the story, all about the narrative, right,

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Speaker 1: and the guy reading Reddit might have a better handle

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Speaker 1: on that.

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Speaker 5: But go ahead, right, this kind of you know, the

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Speaker 5: metic investing. So yeah, you guys, ever heard of the

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Speaker 5: Gardner hype cycle? Yeah? For those who haven't, the way

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Speaker 5: that it looks is you have this kind of parabolic

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Speaker 5: rise between the technology trigger and then the peak of

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Speaker 5: inflated expectations, and kind of the axiomatic way to give

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Speaker 5: an example of this would be the dot com bubble. Right.

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Speaker 5: You have the technology trigger, which is the Internet, and

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Speaker 5: then you it kind of goes parabolic all the way

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Speaker 5: up to the peak of inflated expectations, which would probably

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Speaker 5: be you know, in nineteen ninety nine pets dot com

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Speaker 5: type stuff where the things that are happening are absolutely ridiculous, right,

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Speaker 5: the forecasts are insane. And the thing about a mega

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Speaker 5: trend or you know, a theme that is persistent, is

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Speaker 5: it doesn't go unnoticed for very long. It can be

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Speaker 5: a significant amount of time. But you know, you speak

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Speaker 5: about like Chinese industry in the twenty first century, you know,

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Speaker 5: like there was a period of time where you could

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Speaker 5: have been early on that and you could have invested

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Speaker 5: and made excellent returns that you know, the peak of

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Speaker 5: inflated expectations, and then uh kind of exited before I

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Speaker 5: guess I think maybe there was kind of a byphasics,

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Speaker 5: so maybe it would have been the Asian currency crisis.

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Speaker 5: But the then what happens is you get this trophic

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Speaker 5: disillusionment right where it's like this technology isn't real. Everything

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Speaker 5: is kind of hyped up. It was all bs whatever. Right,

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Speaker 5: it's a bubble, and that's exactly it was a bubble.

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Speaker 5: And then you get this well, you know, the thing

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Speaker 5: funny thing is people say it's a bubble while it's

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Speaker 5: going up, which is kind of like when people say,

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Speaker 5: you know, like, okay.

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Speaker 4: This is the difference between a journal instor just a

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Speaker 4: bu blah blah blah blah, and then other people are.

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Speaker 2: Making a for chane.

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Speaker 4: It's like right, like you know, like this is why

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Speaker 4: no reporter should ever should ever get into trading.

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Speaker 5: I mean, you know, like how long was you know,

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Speaker 5: Bitcoin had a you know, awful year last year, but

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Speaker 5: like how long was it going up for before? You know,

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Speaker 5: like obviously it was a bubble. But like, you know,

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Speaker 5: that doesn't mean that you have to like be like

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Speaker 5: a monk about it. You don't have to have this

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Speaker 5: monastic view where God forbid I benefit from a bubble.

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Speaker 5: You know, those people are wrong. Who cares? So anyway,

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Speaker 5: you get to kind of this trave disillusionment. And then

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Speaker 5: the next phase is kind of the slope of enlightenment

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Speaker 5: where you know, you borrow a phrase from the VCS,

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Speaker 5: it gets democratized. You know, you can go out in

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Speaker 5: the street right now. If I got on the street

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Speaker 5: and I ask someone what the Internet is, they're going

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Speaker 5: to look at me like I have five heads. They

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Speaker 5: don't necessarily have to know how it works, but they

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Speaker 5: know what it is, right, And then you get the

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Speaker 5: plateau of productivity. In the prototypical Gardner hype cycle, the

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Speaker 5: plateau of productivity is actually below the peak of inflated expectations.

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Speaker 5: But I think most of the time in markets it's

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Speaker 5: actually higher. Obviously, there's a bit survivorship bias on this.

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Speaker 5: You know, nobody that owned pets dot Com benefited from

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Speaker 5: the plateau of productivity. But if you think about you know, Facebook, Amazon, Apple,

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Speaker 5: you know these you know they or even you know,

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Speaker 5: you look at like the nifty to fifty in the seventies, right,

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Speaker 5: like some of them have had very bad returns, like IBM.

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Speaker 5: But then you know, honeywell or carry your global you know,

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Speaker 5: you get the uptake on the GDP effect. And essentially

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Speaker 5: this is kind of the enemy of the mega trend,

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Speaker 5: right because it's very easy to recognize it in the beginning,

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Speaker 5: and then if you're too late with it, you're gonna

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Speaker 5: think that the peak of inflated expectations is just the

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Speaker 5: pullback right when it's not. You know, So this is

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Speaker 5: kind of something where it's good to continuously monitor whether

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Speaker 5: your thesis is playing out, whether it is actually had

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Speaker 5: you know, whether it's artificial intelligence or you know, like

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Speaker 5: you said, the rise of Chinese industry, or the Inflation

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Speaker 5: Reduction Act and the impact and impetus of fiscal spending

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Speaker 5: or you know, GLP one drugs that as long as

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Speaker 5: you are on top of it and you can see,

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Speaker 5: you know, what are the earnings expectations like and what

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Speaker 5: are the actually you know, like like Nvidia is probably

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Speaker 5: gonna you know, beaten raised for the next couple of years,

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Speaker 5: but then you you know, where is going to be

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Speaker 5: the point where the expectations aren't sustainable and when it

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Speaker 5: comes to you know, you said you wanted to talk

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Speaker 5: about the knock on effects, which kind of I mean,

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Speaker 5: that's my favorite part of these things, right, like like

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Speaker 5: when you actually capture a theme and you know, let

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Speaker 5: me ask you a question like do you think the

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Speaker 5: knock on effects are happening yet?

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Speaker 1: I don't know what the take up. So my impression

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Speaker 1: is that actually we should ask how much do these

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Speaker 1: drugs actually cost because my impression is that they're pretty

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Speaker 1: expensive and so they're not making huge inroads into the

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Speaker 1: general population just yet, but that could easily change.

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Speaker 5: Well, you know, right now, as far as weight loss

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Speaker 5: is concerned. As an FDA on label indication, Novo has monopoly, right.

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Speaker 5: Novo has wegov, which is the drug that you know

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Speaker 5: just was had the big headline about twenty percent production

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Speaker 5: in heart attack risk and essentially when they had you know,

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Speaker 5: they can much charge what they want, right, and the

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Speaker 5: way that it's going to develop is Lily's drugman jar

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Speaker 5: which is much more effective, and there are other drug

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Speaker 5: bredits true Tide which is still in clinical trials, but

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Speaker 5: Munjara will be approved for weight loss. But at the

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Speaker 5: end of this year, you know that was reaffirmed by

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Speaker 5: or within the next six months. Right, that was reaffirmed

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Speaker 5: by the Lee on their earnings call. And let me

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Speaker 5: get the answer to the question first, because I want

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Speaker 5: to go into something that's going to answer your question,

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Speaker 5: but I do want to assess, right, so you think

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Speaker 5: that the not going effects are happening yet no?

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Speaker 4: So actually I've been wondering about this because I actually

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Speaker 4: was kind of under the impression link. When are we

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Speaker 4: going to see a company crash on earnings because they say,

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Speaker 4: you know what, we're seeing our sales collapse because.

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Speaker 1: No one's eating our chips.

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Speaker 4: Has it come up on any like fast food calls?

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Speaker 2: Yet?

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Speaker 4: Has it come up on any like CpG company earnings

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Speaker 4: calls yet? Like I remember, like last quarter, like check

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Speaker 4: the textbook company said like, all right, we're running into

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Speaker 4: trouble because AI is like affecting our ability to sell

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Speaker 4: this product that helps people with their homework.

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Speaker 5: So have we seen someone will ever say that again.

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Speaker 5: You know that, right, Joe. Yeah, Now, even if it's happening,

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Speaker 5: no one will ever blame AI again, right, they know

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Speaker 5: what happened to Shtags.

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Speaker 4: So is there are the companies yet that are saying,

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Speaker 4: you know what, in our customer base, we're seeing a

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Speaker 4: change in consumption patterns of something because of these drugs

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Speaker 4: A ton really a ton?

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Speaker 5: Yeah? So just to go through a couple, right, and

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Speaker 5: this will answer your question Tracy right where First up, Yes,

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Speaker 5: the drugs are expensive. These drugs cost about eight hundred

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Speaker 5: to twelve hundred dollars a month, you know which is

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Speaker 5: a lot, and that is for ozembic gob And like

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Speaker 5: I said, you know, you don't have anything that makes

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Speaker 5: this much money that doesn't have competition. Right, So, yes,

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Speaker 5: Lily will get approved for Munjaro on weight loss and

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Speaker 5: then there will be a duopoly and that'll probably last,

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Speaker 5: I don't know, you know, anywhere from a year to

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Speaker 5: three years or something like that. But to come back

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Speaker 5: to Viagra, right, if you think about it, Viagra in

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Speaker 5: nineteen ninety eight cost eighty eight dollars a pill. Okay,

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Speaker 5: now it costs two. There there is whether it's through generics,

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Speaker 5: whether it's through competition, you know, the cialis what the

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Speaker 5: way that it works is, you know, you have you

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Speaker 5: have competition, you have economies of scale, you have insurance coverage,

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Speaker 5: you have you know, the generic drugs. Eventually, glp ones,

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Speaker 5: in fact, in twenty thirty one will face mandatory discounting

435
00:22:19,400 --> 00:22:23,560
Speaker 5: under the Inflation Production Act. So are they expensive right now? Yeah?

436
00:22:24,040 --> 00:22:27,040
Speaker 5: But and to come back to what we were saying

437
00:22:27,080 --> 00:22:30,600
Speaker 5: before that still did not you know, GLP ones were

438
00:22:30,640 --> 00:22:33,679
Speaker 5: mentioned a thousand times in the in the in the

439
00:22:33,800 --> 00:22:37,040
Speaker 5: Q two Q three earnings. Wow, that's interesting. Only half

440
00:22:37,080 --> 00:22:39,080
Speaker 5: of that was by pharmaceutical companies.

441
00:22:39,240 --> 00:22:43,119
Speaker 1: Okay, I just I just did a transcript search and

442
00:22:43,200 --> 00:22:46,280
Speaker 1: there's a there's a Herbal Life earnings transcript where they

443
00:22:46,320 --> 00:22:50,680
Speaker 1: talk about GLP one drugs, like possibly back in the business.

444
00:22:51,240 --> 00:22:54,359
Speaker 5: I will never short Herbal Life just because we also

445
00:22:54,440 --> 00:22:57,680
Speaker 5: what happened with that. I am always willing to learn

446
00:22:57,680 --> 00:23:00,240
Speaker 5: from another person's mistake. And you know, like, but of

447
00:23:00,280 --> 00:23:02,040
Speaker 5: luck to actman if he wants to go after it again.

448
00:23:02,119 --> 00:23:05,240
Speaker 5: But you know, if you have documents searched up, Tracy,

449
00:23:05,280 --> 00:23:10,520
Speaker 5: you can look at metafest yeah, and metafest Yeah, Metafest.

450
00:23:10,560 --> 00:23:13,720
Speaker 5: They heerbal life didn't get hit as bad. But you know,

451
00:23:13,760 --> 00:23:15,359
Speaker 5: I don't know if that's I don't know what that

452
00:23:15,480 --> 00:23:17,600
Speaker 5: was a function of. I think they tried to explain it.

453
00:23:17,640 --> 00:23:21,200
Speaker 5: I didn't really vibe with the explanation, but Metafest basically

454
00:23:21,320 --> 00:23:24,560
Speaker 5: said that, you know, we're we sell things that you know,

455
00:23:24,600 --> 00:23:28,480
Speaker 5: people use to lose weight, and there's like we cannot

456
00:23:28,520 --> 00:23:32,800
Speaker 5: handle the competition from a drug that actually works, right

457
00:23:32,880 --> 00:23:35,320
Speaker 5: that they you know, I think the direct quote is that,

458
00:23:35,359 --> 00:23:39,280
Speaker 5: you know, customer acquisition is being pressured by GLP ones.

459
00:23:39,280 --> 00:23:41,800
Speaker 5: But you know what they're doing now. Their strategy is

460
00:23:41,880 --> 00:23:46,399
Speaker 5: essentially okay, let's do it too, you know, yeah, everyone

461
00:23:46,400 --> 00:23:51,439
Speaker 5: else's maybe right, just do something similar, yeah, exactly, and

462
00:23:51,480 --> 00:23:53,800
Speaker 5: that you know, like I love a company that is

463
00:23:53,880 --> 00:23:58,080
Speaker 5: like torqued up levered melting price like a melting ice cube,

464
00:23:58,520 --> 00:24:01,679
Speaker 5: and then position and right in the center of like

465
00:24:01,760 --> 00:24:05,280
Speaker 5: a you know, like a burgeoning you know, huge trend,

466
00:24:05,400 --> 00:24:09,080
Speaker 5: right because you know, like a good example from another trend,

467
00:24:09,200 --> 00:24:11,879
Speaker 5: artificial intelligence would be like applied opt to electronics, right,

468
00:24:11,920 --> 00:24:15,080
Speaker 5: which is like like it was destroyed and then you know,

469
00:24:15,440 --> 00:24:18,119
Speaker 5: with eight hundred G and the data center demand for

470
00:24:18,720 --> 00:24:25,399
Speaker 5: optical you know, it's a we're so back right, It

471
00:24:25,520 --> 00:24:25,760
Speaker 5: was so.

472
00:24:26,200 --> 00:24:28,480
Speaker 4: But I hadn't heard of Metafest, but I'm reading their

473
00:24:28,520 --> 00:24:32,199
Speaker 4: descriptions and among the things that they and among the

474
00:24:32,240 --> 00:24:36,760
Speaker 4: things that they make are pretzels, puff cereal, crunch drinks,

475
00:24:36,840 --> 00:24:40,600
Speaker 4: hearty choices, oatmeal, pancakes, pudding. So I'm basically I don't

476
00:24:40,640 --> 00:24:43,560
Speaker 4: know that maybe the products are delicious, but I'm imagining

477
00:24:43,600 --> 00:24:45,560
Speaker 4: the type of things that people who are sort of

478
00:24:45,600 --> 00:24:48,320
Speaker 4: like really trying to lose weight are, Like, I'm going

479
00:24:48,359 --> 00:24:50,800
Speaker 4: to eat these puffs and shakes because they're a little

480
00:24:50,800 --> 00:24:52,159
Speaker 4: bit healthier than the alternative.

481
00:24:52,600 --> 00:24:53,840
Speaker 5: I mean, you don't need to That's the thing you

482
00:24:53,840 --> 00:24:55,119
Speaker 5: don't need to work like, like, you know, I was

483
00:24:55,119 --> 00:24:58,359
Speaker 5: talking about my channel checks earlier, and I have an

484
00:24:58,480 --> 00:25:01,000
Speaker 5: end of chronologist, you know, like Eli Lily was one

485
00:25:01,000 --> 00:25:03,320
Speaker 5: of my biggest positions from you know, twenty twenty two,

486
00:25:03,400 --> 00:25:06,800
Speaker 5: twenty twenty one even, and it kind of got surpassed

487
00:25:06,880 --> 00:25:09,840
Speaker 5: during the AI stuff. But I built up a basically,

488
00:25:09,920 --> 00:25:11,199
Speaker 5: you know, like I would go to like an end up.

489
00:25:11,560 --> 00:25:13,359
Speaker 5: Whenever you have a position that's super big, you know

490
00:25:13,359 --> 00:25:15,640
Speaker 5: you're on top of it, right, and you can expense

491
00:25:15,680 --> 00:25:19,560
Speaker 5: a trip to enoprenologist conference and you go there and

492
00:25:19,720 --> 00:25:21,600
Speaker 5: like I'm speaking to these people and they're like, I

493
00:25:21,640 --> 00:25:25,480
Speaker 5: have a patient who was eating five thousand calories a day,

494
00:25:25,720 --> 00:25:28,320
Speaker 5: which is like a full time job, right, like like

495
00:25:28,680 --> 00:25:30,399
Speaker 5: five thousand. Once you get to like five thousand and

496
00:25:30,440 --> 00:25:33,159
Speaker 5: six thousand calories, that's like I mean that that is

497
00:25:33,200 --> 00:25:35,840
Speaker 5: like eight full meals a day, right, And he's like,

498
00:25:36,160 --> 00:25:39,880
Speaker 5: I am, he's having issues because I have to recommend

499
00:25:39,880 --> 00:25:43,800
Speaker 5: protein supplementation because he can't get above five hundred calories

500
00:25:43,800 --> 00:25:46,040
Speaker 5: a day. So if you look at a company like Metafest,

501
00:25:46,119 --> 00:25:49,480
Speaker 5: that's basically you know, selling this food that's a little

502
00:25:49,480 --> 00:25:51,520
Speaker 5: bit healthier for you and you know, maybe taste the

503
00:25:51,560 --> 00:25:53,960
Speaker 5: same so that you know you don't have to you're

504
00:25:54,040 --> 00:25:57,000
Speaker 5: kind of getting better macronutrients or something. I mean, there

505
00:25:57,080 --> 00:25:59,720
Speaker 5: might be an opportunity there for the protein shakes, but overall,

506
00:25:59,840 --> 00:26:01,920
Speaker 5: like you don't really need to worry about if you're

507
00:26:01,920 --> 00:26:03,680
Speaker 5: taking this struggle, you don't really need to worry about,

508
00:26:03,720 --> 00:26:05,679
Speaker 5: uh oh, you know, let me buy food that's like

509
00:26:05,760 --> 00:26:09,040
Speaker 5: more that's less calorically dense, because like it doesn't matter,

510
00:26:09,040 --> 00:26:11,600
Speaker 5: you're not going to eat it anyway. And this is

511
00:26:11,680 --> 00:26:14,400
Speaker 5: kind of interesting because when you're looking at when you're

512
00:26:14,400 --> 00:26:17,159
Speaker 5: like monitoring social media, you know, like always monitoring, like

513
00:26:17,200 --> 00:26:20,520
Speaker 5: you know, Google trends, Wikipedia trends, and for a little bit,

514
00:26:20,840 --> 00:26:22,520
Speaker 5: I think this was like the middle of last year,

515
00:26:23,000 --> 00:26:25,240
Speaker 5: you know, monitoring Google trends, and this Google trend comes

516
00:26:25,320 --> 00:26:26,560
Speaker 5: up called ozempic face.

517
00:26:27,640 --> 00:26:31,440
Speaker 1: Oh yeah, people get really gone from weight loss.

518
00:26:31,880 --> 00:26:34,040
Speaker 5: Literally like I had, and I'm like my fingers on

519
00:26:34,160 --> 00:26:36,359
Speaker 5: the sell button. I'm like if it affects your face,

520
00:26:36,400 --> 00:26:39,600
Speaker 5: like I'm out, you know, And it turns out like

521
00:26:39,640 --> 00:26:42,199
Speaker 5: people were like, oh god, like ozempic causes you to

522
00:26:42,240 --> 00:26:44,240
Speaker 5: have like, you know, like a gaunt face or something,

523
00:26:44,280 --> 00:26:47,720
Speaker 5: and it's like not really, what's causing you to look

524
00:26:47,800 --> 00:26:50,080
Speaker 5: gaune is the fact that you're losing a ton of

525
00:26:50,080 --> 00:26:52,640
Speaker 5: weight very quickly. Right. And you have another one where

526
00:26:52,680 --> 00:26:54,760
Speaker 5: like people are like worried about hair loss and you

527
00:26:54,800 --> 00:26:58,479
Speaker 5: know that is it's a condition called intelligent effluvium, right,

528
00:26:58,480 --> 00:27:00,679
Speaker 5: which is basically the same thing when you lose too

529
00:27:00,760 --> 00:27:03,639
Speaker 5: much weight. You you know, your body is kind of

530
00:27:03,680 --> 00:27:06,480
Speaker 5: like burning nutrients for energy. You're at a caloric deficit

531
00:27:06,560 --> 00:27:09,840
Speaker 5: and you lose cair it's totally reversible, and with like

532
00:27:09,840 --> 00:27:12,399
Speaker 5: ozembic face, It's like you can't see wrinkles on like

533
00:27:12,400 --> 00:27:15,879
Speaker 5: an inflated balloon, right like it that's just how it works.

534
00:27:15,920 --> 00:27:19,600
Speaker 5: And it's kind of amazing to me because you have

535
00:27:19,800 --> 00:27:22,840
Speaker 5: this kind of imphasis where people are like, oh, like

536
00:27:22,920 --> 00:27:25,080
Speaker 5: this is that, this is the side like we gotcha,

537
00:27:25,280 --> 00:27:27,119
Speaker 5: you know, like this is I knew there was going

538
00:27:27,160 --> 00:27:29,120
Speaker 5: to be a catch. And it's like people are so

539
00:27:29,200 --> 00:27:32,040
Speaker 5: unaccustomed to the idea of there being a weight loss

540
00:27:32,119 --> 00:27:35,600
Speaker 5: drug that works that they are confusing the side effects

541
00:27:35,600 --> 00:27:37,840
Speaker 5: of the drug with the side effects of the effects

542
00:27:37,880 --> 00:27:40,840
Speaker 5: of the drug, which is you know, success being successful

543
00:27:40,880 --> 00:27:41,480
Speaker 5: weight loss just.

544
00:27:41,520 --> 00:27:42,120
Speaker 2: For voice worth.

545
00:27:42,160 --> 00:27:44,159
Speaker 4: I'm sorry, I keep going back this. I'm reading the

546
00:27:44,280 --> 00:27:46,720
Speaker 4: metafest transcript from earlier in the week and one of

547
00:27:46,720 --> 00:27:49,880
Speaker 4: the one of the questions is rbal life doesn't say anything.

548
00:27:49,960 --> 00:27:50,840
Speaker 2: I'm paraphrasing.

549
00:27:51,080 --> 00:27:53,640
Speaker 4: Well, one of the questions from the analysts is erbal

550
00:27:53,680 --> 00:27:56,720
Speaker 4: life didn't say anything about GLP one drugs affecting their business?

551
00:27:56,760 --> 00:27:58,359
Speaker 2: What about you? And they're like, well, we're not going

552
00:27:58,440 --> 00:27:59,040
Speaker 2: to comment.

553
00:27:58,840 --> 00:28:01,000
Speaker 4: On rbal life, but yeah, we're feeling it, so yeah,

554
00:28:01,000 --> 00:28:03,800
Speaker 4: it actually it came up. They also cited higher customer

555
00:28:03,840 --> 00:28:07,440
Speaker 4: acquisition costs. Again, they say, pressured by less prospects being

556
00:28:07,480 --> 00:28:11,760
Speaker 4: identified by coaches, impacted by competition from GLP one drugs,

557
00:28:11,960 --> 00:28:12,879
Speaker 4: inflationary pressure.

558
00:28:12,920 --> 00:28:13,719
Speaker 2: So it's coming up.

559
00:28:13,960 --> 00:28:15,840
Speaker 1: Wait, so can I ask you a basic question?

560
00:28:16,160 --> 00:28:16,280
Speaker 5: Wait?

561
00:28:16,320 --> 00:28:18,040
Speaker 1: Wait, just before we go further, can I ask a

562
00:28:18,040 --> 00:28:20,560
Speaker 1: basic question, which is, like how many people are on

563
00:28:20,680 --> 00:28:22,080
Speaker 1: these drugs right now?

564
00:28:23,560 --> 00:28:26,879
Speaker 5: I mean, so I would rather not comment, right, I

565
00:28:27,200 --> 00:28:29,560
Speaker 5: think that I would never be talking about something like

566
00:28:29,560 --> 00:28:31,560
Speaker 5: this if I didn't think that it was early, right,

567
00:28:31,640 --> 00:28:35,320
Speaker 5: and the so like you can look at penetration like

568
00:28:35,359 --> 00:28:39,000
Speaker 5: type two diabetes, right, you know, talking about like penetration

569
00:28:39,160 --> 00:28:41,120
Speaker 5: of a drug that's been approved for an indication for

570
00:28:41,400 --> 00:28:43,560
Speaker 5: a year. You know, it's like you're not really going

571
00:28:43,640 --> 00:28:46,200
Speaker 5: to get an accurate picture, you know, majarro And also

572
00:28:46,240 --> 00:28:48,320
Speaker 5: a drug where like there's only been one approved for

573
00:28:48,560 --> 00:28:51,080
Speaker 5: you know, and then you get also the fact that

574
00:28:51,200 --> 00:28:54,200
Speaker 5: like there are talking about, you know, mentions on earnings.

575
00:28:54,720 --> 00:28:58,560
Speaker 5: There are significant supply chain issues with these drugs right now,

576
00:28:58,680 --> 00:29:02,240
Speaker 5: like like Novo's having trouble sourcing the drugs coming in

577
00:29:02,360 --> 00:29:05,080
Speaker 5: autoinjector right, which is basically if you think of an EpiPen,

578
00:29:05,400 --> 00:29:07,440
Speaker 5: you know, you take it once a week and you

579
00:29:07,480 --> 00:29:09,640
Speaker 5: know it's like a button that you wish but you

580
00:29:09,640 --> 00:29:12,720
Speaker 5: look at like like talking still about like the earnings mentions,

581
00:29:12,800 --> 00:29:18,440
Speaker 5: if you look at Stevenado or Garretsheimer or even Beckton Dickinson.

582
00:29:18,960 --> 00:29:21,520
Speaker 5: The problem is that they can't produce enough of it,

583
00:29:21,640 --> 00:29:23,719
Speaker 5: which would tell you something about demand, right, like, like

584
00:29:23,800 --> 00:29:24,120
Speaker 5: even I.

585
00:29:24,200 --> 00:29:26,840
Speaker 1: Know this would turn into a supply chain episode eventually.

586
00:29:28,680 --> 00:29:30,080
Speaker 5: Please don't try to get me to talk about the

587
00:29:30,080 --> 00:29:33,920
Speaker 5: sly chainer so I will seem very silly. But the

588
00:29:34,000 --> 00:29:37,600
Speaker 5: thing is just even Lily, right, Obviously they have to

589
00:29:37,640 --> 00:29:41,560
Speaker 5: temper their optimism, but they're having to ramp up production

590
00:29:41,760 --> 00:29:45,440
Speaker 5: at all, you know, five global facilities just because of

591
00:29:45,480 --> 00:29:47,720
Speaker 5: the fact that like they're like overwhelmed. They could not

592
00:29:47,840 --> 00:29:53,479
Speaker 5: even have anticipated this level of demand. Right during Lily's

593
00:29:53,520 --> 00:29:56,720
Speaker 5: earnings call, Chris Shibatani and analyst was asking a question

594
00:29:56,760 --> 00:29:59,840
Speaker 5: that was basically like Novo and Lily, you've been confronted

595
00:29:59,840 --> 00:30:02,400
Speaker 5: by this demand that was like beyond what you could

596
00:30:02,440 --> 00:30:06,560
Speaker 5: have possibly planned for. And with Lily, you know, Majar

597
00:30:06,720 --> 00:30:09,760
Speaker 5: isn't even a proof for weight loss yet, and so

598
00:30:11,080 --> 00:30:14,760
Speaker 5: essentially it would be kind of premature to say, you

599
00:30:14,760 --> 00:30:17,240
Speaker 5: know what the penetration of these drugs is right now.

600
00:30:17,680 --> 00:30:21,280
Speaker 5: But what I will say is that and I have

601
00:30:21,320 --> 00:30:22,920
Speaker 5: a chart that I can you know, send you maybe

602
00:30:22,920 --> 00:30:26,840
Speaker 5: can put it up on the site that essentially the

603
00:30:26,880 --> 00:30:29,760
Speaker 5: obesity rate in the US in nineteen seventy four was

604
00:30:29,800 --> 00:30:33,000
Speaker 5: twelve percent, right, and now it's forty two percent. And

605
00:30:33,120 --> 00:30:36,040
Speaker 5: for the past five decades, there have not been two

606
00:30:36,160 --> 00:30:39,320
Speaker 5: sequential years in which the obescd rate has ticked down.

607
00:30:39,760 --> 00:30:45,040
Speaker 5: It hasn't happened for fifty years. So you know, when

608
00:30:45,040 --> 00:30:47,080
Speaker 5: you look at that, I first off, I think it's

609
00:30:47,240 --> 00:30:51,200
Speaker 5: not just reasonable but rational to think that you can't

610
00:30:51,200 --> 00:30:54,400
Speaker 5: have a society that has both advanced medication and then

611
00:30:55,240 --> 00:30:58,440
Speaker 5: half of its populace affected by a disease and not

612
00:30:58,480 --> 00:31:01,240
Speaker 5: think that eventually those two things were resolve each other. Right.

613
00:31:02,200 --> 00:31:04,400
Speaker 5: And if you look at the sixty eight week trial

614
00:31:04,480 --> 00:31:07,840
Speaker 5: data Munjarro, and you adjust for you know, the average compliance,

615
00:31:07,920 --> 00:31:11,360
Speaker 5: and you know which patients dropped out prematurely, and then

616
00:31:11,840 --> 00:31:15,160
Speaker 5: you adjust for the fact that about after you drop

617
00:31:15,200 --> 00:31:17,640
Speaker 5: out of the trial, about half of the weight loss

618
00:31:17,760 --> 00:31:20,760
Speaker 5: you still maintained about half of the weight that you lost,

619
00:31:20,760 --> 00:31:23,840
Speaker 5: but about half of it goes away, and so you

620
00:31:23,880 --> 00:31:27,160
Speaker 5: adjust for all those things. If Munjaro a sixty eight

621
00:31:27,160 --> 00:31:30,959
Speaker 5: week trial data has a thirty percent penetration rate in

622
00:31:31,240 --> 00:31:35,160
Speaker 5: the obese population. Right, the obeset rate in the United

623
00:31:35,200 --> 00:31:37,640
Speaker 5: States would be lower than it was in nineteen ninety seven.

624
00:31:38,200 --> 00:31:41,000
Speaker 5: And you know, like that could happen over the course

625
00:31:41,040 --> 00:31:43,880
Speaker 5: of two or three years. And so for a line

626
00:31:43,880 --> 00:31:45,960
Speaker 5: that has gone up into the right to go down,

627
00:31:46,080 --> 00:31:59,880
Speaker 5: you know that significantly.

628
00:32:04,120 --> 00:32:08,560
Speaker 4: So I'm not surprised that, you know, mentions of GOLP

629
00:32:08,720 --> 00:32:11,959
Speaker 4: onees are popping up on various conference calls. You know,

630
00:32:12,040 --> 00:32:14,680
Speaker 4: some obvious ways, like the company that maybe makes the

631
00:32:14,960 --> 00:32:18,040
Speaker 4: devices for its use, or the companies that have some

632
00:32:18,240 --> 00:32:21,800
Speaker 4: other weight loss solution that may be feeling pressure. But

633
00:32:22,000 --> 00:32:26,080
Speaker 4: like for example, today again August ninth, we got earnings

634
00:32:26,080 --> 00:32:30,520
Speaker 4: from Wendy's. No mention of GLP one there. Yet I

635
00:32:30,520 --> 00:32:33,680
Speaker 4: looked last month, we got earnings from PEPSI. And you know,

636
00:32:33,680 --> 00:32:36,600
Speaker 4: if I were to think about, like, okay, in theory,

637
00:32:36,800 --> 00:32:39,840
Speaker 4: in some future world where these drugs are very cheap

638
00:32:40,040 --> 00:32:45,560
Speaker 4: and widespread, and who would theoretically be losers from drugs

639
00:32:45,600 --> 00:32:49,880
Speaker 4: that reduce one's appetite for fast food, for salty foods,

640
00:32:49,880 --> 00:32:53,560
Speaker 4: for high carb foods, whatever it is in your mind,

641
00:32:53,680 --> 00:32:56,480
Speaker 4: is it obvious that A some of these big consumer

642
00:32:56,520 --> 00:32:59,200
Speaker 4: oriented companies are going to be losers, and B if

643
00:32:59,240 --> 00:33:02,520
Speaker 4: it is, when would you expect to see, like what

644
00:33:02,680 --> 00:33:05,440
Speaker 4: pick a predicted quarter when maybe this would.

645
00:33:05,240 --> 00:33:06,600
Speaker 2: Come up on a Wendy's earnings call.

646
00:33:07,480 --> 00:33:10,200
Speaker 5: Well, so let's think, you know, first off.

647
00:33:10,080 --> 00:33:12,720
Speaker 4: Or or if the premise of the question is totally

648
00:33:12,720 --> 00:33:13,640
Speaker 4: off the mark, that's fine too.

649
00:33:14,200 --> 00:33:16,040
Speaker 5: No, no, no, I mean it's a it's a I don't know,

650
00:33:16,080 --> 00:33:18,120
Speaker 5: we're talking about second order effects that this seems a

651
00:33:18,160 --> 00:33:22,200
Speaker 5: little first order Joe, Okay, you're right, you're right. No,

652
00:33:22,240 --> 00:33:24,240
Speaker 5: but no, no, I mean it's a great point, right,

653
00:33:24,320 --> 00:33:26,920
Speaker 5: And I think that the sent I mean, you know,

654
00:33:27,040 --> 00:33:32,280
Speaker 5: Wendy's sells so much food right like it's it's uh

655
00:33:32,320 --> 00:33:35,360
Speaker 5: me too. I don't want to I don't want to

656
00:33:35,400 --> 00:33:37,880
Speaker 5: malign Wendy's. But the thing is, I think that if

657
00:33:37,920 --> 00:33:39,640
Speaker 5: you wanted to be able to predict this, what you

658
00:33:39,640 --> 00:33:42,239
Speaker 5: would have to do is you'd probably have to use

659
00:33:42,240 --> 00:33:44,680
Speaker 5: all data or you know, credit card data, and you

660
00:33:44,680 --> 00:33:47,120
Speaker 5: would have to look at the company and maybe eat

661
00:33:47,120 --> 00:33:48,960
Speaker 5: a lot of fast foods for a month to figure out.

662
00:33:49,000 --> 00:33:54,440
Speaker 5: But like, which of these companies you're going to be

663
00:33:54,480 --> 00:33:57,360
Speaker 5: my new analyst. No, which of these companies are willing

664
00:33:57,640 --> 00:34:01,520
Speaker 5: to or are basically making up for or low margins

665
00:34:01,560 --> 00:34:04,360
Speaker 5: with high volumes, right because the because it's not like

666
00:34:04,400 --> 00:34:07,520
Speaker 5: these drugs are going to automatically make you, you know

667
00:34:07,760 --> 00:34:10,200
Speaker 5: the Jack Lalane right, Like, you're not gonna You're not

668
00:34:10,239 --> 00:34:12,360
Speaker 5: just gonna be like the hell you all your habits

669
00:34:12,360 --> 00:34:15,120
Speaker 5: are healthy now, Like if you're eating fast food every day,

670
00:34:15,120 --> 00:34:17,319
Speaker 5: you will probably continue to eat fast food every day.

671
00:34:17,320 --> 00:34:19,319
Speaker 5: You will just eat a lot less of it, like

672
00:34:19,400 --> 00:34:24,000
Speaker 5: a lot less of it. And let's say chapatte for example, Yeah,

673
00:34:24,080 --> 00:34:26,279
Speaker 5: probably not going to be that negatively affected, you know,

674
00:34:26,400 --> 00:34:28,600
Speaker 5: like like people you know, they'll probably have the same

675
00:34:28,760 --> 00:34:30,360
Speaker 5: order and they'll just finish, you know, a couple of

676
00:34:30,360 --> 00:34:33,200
Speaker 5: bites bit or something. I don't necessarily want to speak

677
00:34:33,200 --> 00:34:35,640
Speaker 5: to this, but just thinking of like RBI's for example,

678
00:34:35,680 --> 00:34:37,160
Speaker 5: I think it's owned by a private company, so I

679
00:34:37,200 --> 00:34:40,680
Speaker 5: can you know, talk about without issue. But like the

680
00:34:40,800 --> 00:34:44,960
Speaker 5: prototypical let's just speak theoretically, there's you know, all you

681
00:34:45,000 --> 00:34:47,400
Speaker 5: can eat Biffet or something. They might do really well

682
00:34:47,680 --> 00:34:50,799
Speaker 5: because people eat less, but at the same time they

683
00:34:50,880 --> 00:34:54,040
Speaker 5: might be patronized less because you know, nobody wants all

684
00:34:54,040 --> 00:34:55,760
Speaker 5: you can eat, and you're not getting a good deal anymore.

685
00:34:56,080 --> 00:34:58,000
Speaker 5: So if you have a company and you look at

686
00:34:58,000 --> 00:35:00,360
Speaker 5: the data and basically the way that they make money

687
00:35:00,480 --> 00:35:02,960
Speaker 5: is by selling a ton of food that they get

688
00:35:03,080 --> 00:35:06,000
Speaker 5: very cheaply and make up for you know, kind of

689
00:35:06,080 --> 00:35:08,720
Speaker 5: lower margins by selling a ton of it, that company

690
00:35:08,719 --> 00:35:10,759
Speaker 5: probably isn't going to do too great. But you know,

691
00:35:10,840 --> 00:35:13,440
Speaker 5: it wasn't just metafest for example, you know, going beyond

692
00:35:13,520 --> 00:35:16,760
Speaker 5: the idea of like food being impacted, Like right now,

693
00:35:17,120 --> 00:35:20,120
Speaker 5: Lily has a trial for Munjaro. Basically, what these companies

694
00:35:20,160 --> 00:35:23,520
Speaker 5: are doing is they are on this kind of blitz

695
00:35:23,520 --> 00:35:26,719
Speaker 5: scale for like the data, right because like most of

696
00:35:26,719 --> 00:35:30,240
Speaker 5: these things you can kind of rationally expect, like for example,

697
00:35:30,280 --> 00:35:33,560
Speaker 5: with the Wigobi headline, Gooby reduces heart attack risk by

698
00:35:33,600 --> 00:35:36,080
Speaker 5: twenty percent. I mean kind of like duh, you know,

699
00:35:36,360 --> 00:35:38,880
Speaker 5: like like oh, like you know, if you if you

700
00:35:39,000 --> 00:35:40,880
Speaker 5: go from being obese to not obese, you're going to

701
00:35:40,920 --> 00:35:42,960
Speaker 5: have a lower chance of heart attack. Right. But they

702
00:35:43,080 --> 00:35:44,960
Speaker 5: but what they have to do is you know, have

703
00:35:45,080 --> 00:35:48,200
Speaker 5: these you know, vigorous trials that actually prove it. Like

704
00:35:48,400 --> 00:35:51,440
Speaker 5: so for example, Lily is going right now for obese

705
00:35:51,480 --> 00:35:55,880
Speaker 5: induced sleep ABNA or ni osio or arthritis, and so

706
00:35:56,360 --> 00:35:58,719
Speaker 5: like a company like res Med. Right, ResMed was talking

707
00:35:58,719 --> 00:36:01,480
Speaker 5: about it for you know, like a while on their

708
00:36:01,520 --> 00:36:05,759
Speaker 5: earnings call, and the response was essentially, you know, I'm

709
00:36:05,800 --> 00:36:07,920
Speaker 5: trying to remember exactly what they said, Oh right, a

710
00:36:08,080 --> 00:36:11,640
Speaker 5: seatbad machine. The costs over a lifetime for a seatbad

711
00:36:11,680 --> 00:36:16,359
Speaker 5: machine are like about fifteen thousand dollars. And then they

712
00:36:16,360 --> 00:36:19,560
Speaker 5: did their own math, which was like, well, these GLP

713
00:36:19,600 --> 00:36:22,480
Speaker 5: one drugs cost one thousand dollars a month, and if

714
00:36:22,480 --> 00:36:24,280
Speaker 5: you multiply, if you have a forty year old patient,

715
00:36:24,360 --> 00:36:27,240
Speaker 5: you multiply that by forty years, Well, really a GLP

716
00:36:27,320 --> 00:36:28,799
Speaker 5: one drugs, you know it's going to cost you four

717
00:36:28,840 --> 00:36:32,359
Speaker 5: hundred and eighty thousand dollars. So obviously you know we're

718
00:36:32,400 --> 00:36:35,840
Speaker 5: coming in at fourteen fifteen thousand, where obviously the option

719
00:36:35,960 --> 00:36:38,000
Speaker 5: we're not going to be really affected by this. And

720
00:36:38,400 --> 00:36:42,080
Speaker 5: you know, to take that into consideration, you say, why

721
00:36:42,120 --> 00:36:44,560
Speaker 5: would people be taking this for forty years? Right? Like,

722
00:36:44,680 --> 00:36:47,320
Speaker 5: why would if they if someone you know, seventy percent

723
00:36:47,320 --> 00:36:49,840
Speaker 5: of sleep apne is caused by obesity, If you have

724
00:36:49,920 --> 00:36:52,719
Speaker 5: someone that's taking it and they take it for let's

725
00:36:52,719 --> 00:36:56,160
Speaker 5: say sixteen months and they go from being obese to

726
00:36:56,280 --> 00:36:59,320
Speaker 5: having a normal body weight, and then in all likelihood

727
00:36:59,320 --> 00:37:02,160
Speaker 5: at least for like seventy percent of them, the obstructive

728
00:37:02,160 --> 00:37:05,160
Speaker 5: sleep abne goes away. I mean you have to just

729
00:37:05,320 --> 00:37:08,239
Speaker 5: kind of the total addressable market for a company like

730
00:37:08,280 --> 00:37:10,720
Speaker 5: res med or for the c PAFT industry in general,

731
00:37:11,120 --> 00:37:14,440
Speaker 5: it is going to shrink, right, It's kind of and

732
00:37:14,600 --> 00:37:16,880
Speaker 5: even you know, and then when people say that you

733
00:37:16,880 --> 00:37:19,240
Speaker 5: know this is a fad or you know this won't

734
00:37:19,239 --> 00:37:21,640
Speaker 5: work again, you look at like like when was the

735
00:37:21,719 --> 00:37:24,960
Speaker 5: last fad weight loss drug that had Intuitive Surgical talking

736
00:37:25,000 --> 00:37:28,279
Speaker 5: about on the earnings call? Right, Like Intuitive Surgical they're

737
00:37:28,320 --> 00:37:29,960
Speaker 5: not ready to speak to it, but they mentioned it

738
00:37:30,000 --> 00:37:31,840
Speaker 5: on the earnings call. And then you have another company.

739
00:37:32,160 --> 00:37:34,600
Speaker 5: I think this was my favorite one, right, and it

740
00:37:34,640 --> 00:37:37,719
Speaker 5: wasn't even because of anything the company did or said.

741
00:37:37,800 --> 00:37:41,600
Speaker 5: It was just because I'm reading the prepared remarks and

742
00:37:42,840 --> 00:37:46,160
Speaker 5: the exact text was basically, you know, the company is

743
00:37:46,200 --> 00:37:49,600
Speaker 5: called Teleflex, and it essentially it's a company that makes

744
00:37:49,640 --> 00:37:52,400
Speaker 5: devices for sleeve. But sleeve gets direct to me like

745
00:37:52,440 --> 00:37:56,320
Speaker 5: the bariatric surgery weight loss surgery. You get the sleeve

746
00:37:57,000 --> 00:38:01,920
Speaker 5: and the thing is, you know, sleep gas tractomy. I

747
00:38:01,920 --> 00:38:04,759
Speaker 5: think the average weight loss over seventy two weeks is

748
00:38:04,800 --> 00:38:09,000
Speaker 5: like twenty six or twenty seven percent, And with Munjaro

749
00:38:09,280 --> 00:38:11,640
Speaker 5: it's a little bit closer to depending on the dose,

750
00:38:11,719 --> 00:38:15,360
Speaker 5: between like seventeen and nineteen percent. But Lily's new drug,

751
00:38:15,640 --> 00:38:18,920
Speaker 5: the triple agonist red true Tide, is showing like twenty

752
00:38:18,960 --> 00:38:22,320
Speaker 5: four to twenty five percent. Right, So in the prepared remarks,

753
00:38:22,320 --> 00:38:25,360
Speaker 5: they're basically saying, we did see an effect from GLP

754
00:38:25,480 --> 00:38:31,040
Speaker 5: ones on the demand for bariatric surgery, which affected the

755
00:38:31,040 --> 00:38:35,839
Speaker 5: demand for our device, the Titan stapler. Wait, so if

756
00:38:35,880 --> 00:38:38,040
Speaker 5: I ask you, Tracy, if you want to lose weight,

757
00:38:38,080 --> 00:38:43,920
Speaker 5: would you rather take or get Titan staples? Like? Like,

758
00:38:43,920 --> 00:38:46,920
Speaker 5: like you want to go with the Titan stapler? I

759
00:38:46,960 --> 00:38:47,360
Speaker 5: don't think so.

760
00:38:47,800 --> 00:38:50,360
Speaker 1: Why didn't they call it like suft staple or a

761
00:38:50,400 --> 00:38:54,240
Speaker 1: gentle staple? Titan is just a terrible name for any

762
00:38:54,280 --> 00:38:58,360
Speaker 1: surgical procedure. Okay, Wait, So one of the reasons talking

763
00:38:58,400 --> 00:39:00,759
Speaker 1: about this is fun is because it is kind of

764
00:39:00,840 --> 00:39:05,600
Speaker 1: a giant thought experiment of what a world of fewer

765
00:39:05,640 --> 00:39:10,160
Speaker 1: obese people would actually mean. How far can you take it? James,

766
00:39:10,200 --> 00:39:14,000
Speaker 1: like to, what's your most interesting sort of second order

767
00:39:14,440 --> 00:39:18,920
Speaker 1: trade idea based on a widely available weight loss drug.

768
00:39:20,200 --> 00:39:22,160
Speaker 5: Well, I think that you know, if I'm going to

769
00:39:22,200 --> 00:39:24,080
Speaker 5: stretch this as you know, as far as it can go,

770
00:39:24,280 --> 00:39:26,080
Speaker 5: the first thing is stretching it as far as it

771
00:39:26,080 --> 00:39:29,520
Speaker 5: can go gets pretty stretched because I mean, the direct

772
00:39:29,600 --> 00:39:31,239
Speaker 5: medical costs this year from obessie, they're going to be

773
00:39:31,280 --> 00:39:34,200
Speaker 5: three hundred and seventy billion dollars. The indirect costs are

774
00:39:34,200 --> 00:39:37,440
Speaker 5: going to be over a trillion. McKinsey in twenty twelve,

775
00:39:37,440 --> 00:39:39,560
Speaker 5: when the OBCD rate was like I want to say,

776
00:39:39,600 --> 00:39:43,000
Speaker 5: seven or eight percent lower, they estimated that OBESD results

777
00:39:43,040 --> 00:39:47,440
Speaker 5: in an annual global an annual global economic impact that

778
00:39:47,600 --> 00:39:50,800
Speaker 5: is equivalent to two point eight percent of the global GDP.

779
00:39:51,600 --> 00:39:54,319
Speaker 5: So you think about like productivity six days, you know,

780
00:39:54,400 --> 00:39:59,160
Speaker 5: workers comp injury, I mean life insurance, health insurance, workers

781
00:39:59,200 --> 00:40:02,160
Speaker 5: comp insurance. It something like that. When you have a

782
00:40:02,320 --> 00:40:04,760
Speaker 5: when you have a literal disease state that is affecting

783
00:40:04,840 --> 00:40:07,759
Speaker 5: forty two percent of your population, it's kind of hard

784
00:40:07,840 --> 00:40:09,719
Speaker 5: not to stretch this far, you know, like like if

785
00:40:09,719 --> 00:40:13,200
Speaker 5: that gets fixed. But in terms of the one that

786
00:40:13,200 --> 00:40:15,680
Speaker 5: I would share on a podcast to be entertaining, I

787
00:40:15,719 --> 00:40:19,719
Speaker 5: would say, like match group or bumble as along. If

788
00:40:19,760 --> 00:40:22,880
Speaker 5: you look into like just general, everyone feels.

789
00:40:23,320 --> 00:40:26,640
Speaker 4: Themselves and so they get to advertise them that's in

790
00:40:26,680 --> 00:40:28,759
Speaker 4: a product in the dating marketplace.

791
00:40:29,480 --> 00:40:32,720
Speaker 5: And you know what's interesting about this, you know, match group.

792
00:40:32,840 --> 00:40:35,279
Speaker 5: I already think that the fundamentals look good here, but

793
00:40:36,200 --> 00:40:38,279
Speaker 5: you know, if we're going to like stretch it super far,

794
00:40:38,400 --> 00:40:40,319
Speaker 5: you look at like match groups last earnings and like

795
00:40:40,719 --> 00:40:43,440
Speaker 5: payers were flat or decreased a little bit for tender,

796
00:40:43,920 --> 00:40:47,600
Speaker 5: but they increase significantly for hinge. And if you look

797
00:40:47,600 --> 00:40:50,440
Speaker 5: at like there are like, you know, social sciences studies

798
00:40:50,440 --> 00:40:53,520
Speaker 5: about like the effects of obesity on like your how

799
00:40:53,560 --> 00:40:55,400
Speaker 5: happy you are and how satisfied you are with your

800
00:40:55,480 --> 00:40:58,080
Speaker 5: dating life and stuff, And I think, I don't want

801
00:40:58,080 --> 00:41:01,040
Speaker 5: to butcher the results or something, but it was basically

802
00:41:01,640 --> 00:41:05,840
Speaker 5: across genders, right, like if you are female or male,

803
00:41:06,480 --> 00:41:10,200
Speaker 5: the effect of losing ten or twenty pounds on your

804
00:41:10,280 --> 00:41:13,120
Speaker 5: average you know, satisfaction with your dating life and with

805
00:41:13,360 --> 00:41:15,399
Speaker 5: just generally how happy you are. It's a lot more

806
00:41:15,440 --> 00:41:20,040
Speaker 5: significant in females. So you know, maybe if you want

807
00:41:20,040 --> 00:41:22,200
Speaker 5: to like be super early and stretch it super far.

808
00:41:22,320 --> 00:41:24,680
Speaker 5: Maybe the reason that like hinge is getting more popular

809
00:41:24,719 --> 00:41:27,560
Speaker 5: than tendered. Maybe it's because it's easier to lose weight.

810
00:41:27,600 --> 00:41:30,040
Speaker 5: I don't I would not say that in like an

811
00:41:30,040 --> 00:41:36,080
Speaker 5: authoritative way, but you know, I just say, yeah, that's

812
00:41:36,120 --> 00:41:39,960
Speaker 5: that's the thing. I'm going to get quoted a like, No,

813
00:41:40,400 --> 00:41:43,120
Speaker 5: this is a crazy guy thinks that, like match group

814
00:41:43,200 --> 00:41:45,040
Speaker 5: is going to moon because of you know, No, I

815
00:41:45,040 --> 00:41:46,759
Speaker 5: guess I just say I get, I get how the

816
00:41:46,800 --> 00:41:50,560
Speaker 5: internet works, though this is I know, I know it's funny.

817
00:41:50,560 --> 00:41:52,680
Speaker 4: I keep reading through conference calls after you mentioned them.

818
00:41:52,719 --> 00:41:54,840
Speaker 4: I'm looking at the res mid one and did you

819
00:41:54,880 --> 00:41:58,160
Speaker 4: look at Titan State, But they're talking about They're like, well,

820
00:41:58,320 --> 00:42:01,040
Speaker 4: they're like because clearly this is a source of anxiety

821
00:42:01,080 --> 00:42:03,319
Speaker 4: for them. So they're like, oh, well, like uptake and

822
00:42:03,400 --> 00:42:05,640
Speaker 4: like endherance is not really that good. And then a

823
00:42:05,760 --> 00:42:08,319
Speaker 4: very funny thing they say, because Biden had that mark

824
00:42:08,360 --> 00:42:10,760
Speaker 4: on his face is our biggest side effect is President

825
00:42:10,760 --> 00:42:12,680
Speaker 4: Biden had a little mark on his face and he

826
00:42:12,800 --> 00:42:15,000
Speaker 4: was asked about it and it was from his CEPAP.

827
00:42:15,520 --> 00:42:15,759
Speaker 5: Look.

828
00:42:15,760 --> 00:42:17,440
Speaker 4: I think it's a good long road to play out here.

829
00:42:17,480 --> 00:42:20,479
Speaker 4: I think it's frankly good marketing. So President Biden, because

830
00:42:20,520 --> 00:42:22,200
Speaker 4: he had to put a device on his face for

831
00:42:22,280 --> 00:42:23,640
Speaker 4: his sleep problems.

832
00:42:23,719 --> 00:42:26,399
Speaker 5: The company is setting it market, did we just I mean,

833
00:42:27,320 --> 00:42:30,360
Speaker 5: I saw I saw a photo of Justin Trudeau at Imax,

834
00:42:30,840 --> 00:42:32,240
Speaker 5: so maybe I should get long Imax.

835
00:42:32,719 --> 00:42:35,839
Speaker 4: You know, it seems like a big deal, like just

836
00:42:36,120 --> 00:42:38,640
Speaker 4: zooming out. It seems like a big deal. Even if

837
00:42:38,640 --> 00:42:40,239
Speaker 4: we like set aside what it's going to do to

838
00:42:40,239 --> 00:42:42,560
Speaker 4: PEPSI or what it's going to do to like freedom

839
00:42:42,600 --> 00:42:44,239
Speaker 4: lay or that's the same, you know, what it's going

840
00:42:44,280 --> 00:42:47,359
Speaker 4: to do to all these consumer companies, you know, health insurance.

841
00:42:47,640 --> 00:42:52,960
Speaker 4: You mentioned that like obesity plus obesity related diseases are huge,

842
00:42:53,239 --> 00:42:54,799
Speaker 4: and so if they were to go down and you

843
00:42:54,840 --> 00:42:56,879
Speaker 4: see maybe you see some of that in the sort

844
00:42:56,880 --> 00:42:59,480
Speaker 4: of weak stock price of res med anxiety about this?

845
00:43:00,040 --> 00:43:02,799
Speaker 4: What does it mean just like for like health insurers

846
00:43:03,040 --> 00:43:06,719
Speaker 4: and also just like healthcare utilization in general, Like you know,

847
00:43:06,880 --> 00:43:09,520
Speaker 4: generally we think of like healthcare as like a line

848
00:43:09,560 --> 00:43:12,319
Speaker 4: that only goes up that if you're a healthcare professional,

849
00:43:12,360 --> 00:43:15,920
Speaker 4: you're like gonna do very probably likely very well guaranteed demand.

850
00:43:16,360 --> 00:43:18,000
Speaker 4: What is the effect on just sort of like the

851
00:43:18,040 --> 00:43:21,080
Speaker 4: broader healthcare institutional healthcare industry.

852
00:43:22,040 --> 00:43:24,239
Speaker 5: Since you've already got documents search slouded up, why don't

853
00:43:24,239 --> 00:43:28,520
Speaker 5: you check out Insparity. The ticker is a NSP.

854
00:43:28,960 --> 00:43:29,839
Speaker 2: This is a fun guy.

855
00:43:30,320 --> 00:43:32,840
Speaker 4: I was like just hearing different names and then I

856
00:43:32,840 --> 00:43:34,200
Speaker 4: look at looked them up during the answer.

857
00:43:34,200 --> 00:43:34,799
Speaker 2: But yeah, keep going.

858
00:43:34,880 --> 00:43:38,640
Speaker 5: Welcome to my life during earning season. Document search is

859
00:43:38,680 --> 00:43:42,600
Speaker 5: my favorite feature. But you know, if you look at Inspirity,

860
00:43:42,880 --> 00:43:45,560
Speaker 5: you can kind of see. I don't want to misquote anyone,

861
00:43:45,680 --> 00:43:47,440
Speaker 5: so I'll just put it up very quickly.

862
00:43:48,120 --> 00:43:49,440
Speaker 3: Look at the share price.

863
00:43:49,840 --> 00:43:53,360
Speaker 4: Hey, this is the company offers recruiting, employment screen and

864
00:43:53,400 --> 00:43:54,600
Speaker 4: retirement business insurance.

865
00:43:54,640 --> 00:43:56,040
Speaker 2: Yeah, what is this company?

866
00:43:56,160 --> 00:43:57,720
Speaker 1: It's down about sixteen percent.

867
00:43:57,800 --> 00:43:59,920
Speaker 2: That's what matters. I can't figure out what they do

868
00:44:00,040 --> 00:44:01,080
Speaker 2: and what their connection is here.

869
00:44:01,120 --> 00:44:01,600
Speaker 5: So we're going to.

870
00:44:01,680 --> 00:44:05,520
Speaker 1: Find out human resources and business optimizations.

871
00:44:05,600 --> 00:44:09,160
Speaker 2: No, no, no, yeah, but I don't so what's the here.

872
00:44:09,280 --> 00:44:11,319
Speaker 5: So here's the deal, right. They also offer you know,

873
00:44:11,400 --> 00:44:14,880
Speaker 5: employed benefit administration, which you know, like like health and

874
00:44:15,400 --> 00:44:18,000
Speaker 5: so if you want to boil it down to two things, like,

875
00:44:18,040 --> 00:44:20,279
Speaker 5: Insparity got hit on the fact that like people want

876
00:44:20,280 --> 00:44:22,239
Speaker 5: these drugs because they don't want to be fat and

877
00:44:22,320 --> 00:44:25,760
Speaker 5: the drugs make them not fat, and Insparity apparently thinks

878
00:44:25,800 --> 00:44:28,160
Speaker 5: that you know, that is a fad. They were saying

879
00:44:28,200 --> 00:44:30,200
Speaker 5: something that was like, oh, you know, the effects are

880
00:44:30,239 --> 00:44:32,719
Speaker 5: going to wane because of the side effects. And when

881
00:44:32,760 --> 00:44:35,400
Speaker 5: you think about it, like these drugs were originally developed

882
00:44:35,400 --> 00:44:37,040
Speaker 5: for type two diabetes, and it's like, oh, you know,

883
00:44:37,360 --> 00:44:39,360
Speaker 5: there's never been a drug before that was developed for

884
00:44:39,440 --> 00:44:41,080
Speaker 5: one thing and then ended up being really good for

885
00:44:41,080 --> 00:44:43,360
Speaker 5: the other, you know, just like Tracy said with Viagra.

886
00:44:43,920 --> 00:44:46,880
Speaker 5: And basically they said, you know, large claim activity accounted

887
00:44:46,880 --> 00:44:49,360
Speaker 5: for approximately seventy five percent of the higher costs with

888
00:44:49,440 --> 00:44:53,160
Speaker 5: claims over seven hundred and fifty thousand dollars, and the

889
00:44:53,200 --> 00:44:56,600
Speaker 5: remaining twenty five percent is related to higher than expected

890
00:44:56,640 --> 00:44:59,759
Speaker 5: pharmacy costs. As for higher pharmacy costs, we experienced an

891
00:44:59,800 --> 00:45:03,120
Speaker 5: in increase and utilization of the specialty drugs, including a

892
00:45:03,200 --> 00:45:05,600
Speaker 5: significant step up in the use of diabetes and weight

893
00:45:05,640 --> 00:45:08,880
Speaker 5: loss drugs. And then they talk about behavioral health drugs

894
00:45:08,880 --> 00:45:12,880
Speaker 5: to behavioral health drugs too, which is probably you know,

895
00:45:12,920 --> 00:45:15,000
Speaker 5: I mean, I don't know, that's a whole different conversation

896
00:45:15,080 --> 00:45:17,359
Speaker 5: with COVID and behavioral health drugs. And you know, like

897
00:45:17,600 --> 00:45:20,880
Speaker 5: how people have emotionally reacted to the last three years.

898
00:45:20,920 --> 00:45:23,800
Speaker 5: But when you look at it, for insparity. It's probably

899
00:45:23,840 --> 00:45:26,319
Speaker 5: bad right now because you know, as long as these

900
00:45:26,360 --> 00:45:29,879
Speaker 5: companies have a duopoly on these drugs, the cost will

901
00:45:29,920 --> 00:45:32,600
Speaker 5: probably be hot. But that can only last for so long.

902
00:45:32,680 --> 00:45:36,600
Speaker 5: You know that eventually there will be competition. Eventually the

903
00:45:36,600 --> 00:45:39,279
Speaker 5: cost will go down. Eventually it'll be like Biagra, where

904
00:45:39,320 --> 00:45:41,040
Speaker 5: it goes from you know, eighty eight dollars pill to

905
00:45:41,600 --> 00:45:44,279
Speaker 5: whatever two dollars a pill. Maybe it was bad quarter

906
00:45:44,360 --> 00:45:46,839
Speaker 5: for insparity. Maybe that continues for a little bit while

907
00:45:46,840 --> 00:45:48,880
Speaker 5: they're still expensive, and then eventually it'll get better. But

908
00:45:48,920 --> 00:45:51,400
Speaker 5: when you think of it from let's say Signa or

909
00:45:52,239 --> 00:45:54,920
Speaker 5: United Healthcare Signa on their earnings called they said, you know,

910
00:45:55,000 --> 00:45:57,840
Speaker 5: GLP ones are definitely top of mind for many of

911
00:45:57,880 --> 00:46:01,319
Speaker 5: our clients. There's been a meaningful upticking utils station. And

912
00:46:02,920 --> 00:46:07,000
Speaker 5: essentially what they said was, you know, there's a continued

913
00:46:07,040 --> 00:46:10,160
Speaker 5: interest in behavioral solutions. You know, these insurance companies they

914
00:46:10,160 --> 00:46:11,960
Speaker 5: will like pay for you to get a gym membership,

915
00:46:12,040 --> 00:46:14,319
Speaker 5: or they'll pay for you to get a meal plan

916
00:46:14,440 --> 00:46:17,760
Speaker 5: or something, and the success rates of those things are dismal,

917
00:46:18,400 --> 00:46:22,120
Speaker 5: like absolutely awful, right and you know it doesn't work.

918
00:46:22,440 --> 00:46:26,480
Speaker 5: And insurance companies are stakeholders in global health, right, and

919
00:46:26,760 --> 00:46:29,719
Speaker 5: they're really good and anticipating how much it's going to

920
00:46:29,800 --> 00:46:31,759
Speaker 5: cost and making sure, you know that they make more

921
00:46:31,800 --> 00:46:36,080
Speaker 5: money than what it's going to cost. But as an epidemic,

922
00:46:36,320 --> 00:46:39,360
Speaker 5: this is still like a relatively new thing. The obesity

923
00:46:39,440 --> 00:46:42,759
Speaker 5: rate has never been forty two percent before, and so

924
00:46:42,840 --> 00:46:45,879
Speaker 5: what do how can we really accurately model what that's

925
00:46:45,880 --> 00:46:48,520
Speaker 5: going to look like in fifty years? I mean, you know,

926
00:46:48,640 --> 00:46:51,160
Speaker 5: maybe if it continues the way that it's going unobated,

927
00:46:51,320 --> 00:46:55,440
Speaker 5: I think that ultimately, you know, health insurance that it's

928
00:46:55,440 --> 00:46:57,640
Speaker 5: going to be a significant hit. So what you're seeing

929
00:46:57,760 --> 00:47:02,080
Speaker 5: is these drug drug companies essentially going on these data campaigns,

930
00:47:02,120 --> 00:47:03,759
Speaker 5: which is, you know, we're going to show you not

931
00:47:03,920 --> 00:47:06,120
Speaker 5: just that it results in weight loss. We're going to

932
00:47:06,160 --> 00:47:09,240
Speaker 5: do a study and a clinical trial on every single

933
00:47:09,239 --> 00:47:11,920
Speaker 5: one of the beneficial effects of losing weight. Right, We're

934
00:47:11,960 --> 00:47:16,279
Speaker 5: going to say, oh, obstructive sleep, at hyper lipidemia, hypertension,

935
00:47:16,360 --> 00:47:20,480
Speaker 5: heart disease, type two diabetes, knee replacements, all of this stuff.

936
00:47:20,520 --> 00:47:24,600
Speaker 5: And then eventually it is for Signa or for United Healthcare,

937
00:47:24,640 --> 00:47:27,560
Speaker 5: it is going to be They're they're going to do

938
00:47:27,560 --> 00:47:30,000
Speaker 5: what insurance companies do. They're going to negotiate. They're going

939
00:47:30,080 --> 00:47:32,160
Speaker 5: to push down the price. They're gonna you know, they're

940
00:47:32,200 --> 00:47:34,960
Speaker 5: gonna there's going to be pushback. There's going to be

941
00:47:36,000 --> 00:47:38,720
Speaker 5: what cut gets covered and what doesn't, especially after Munjara

942
00:47:38,760 --> 00:47:41,279
Speaker 5: gets approved for OBCD. But at the end of the day,

943
00:47:41,920 --> 00:47:45,319
Speaker 5: the thing is they are basically going to have to

944
00:47:45,600 --> 00:47:48,319
Speaker 5: do a cost benefit analysis, and there is no way

945
00:47:48,320 --> 00:47:50,879
Speaker 5: in my mind, I think really even if they were

946
00:47:50,880 --> 00:47:53,479
Speaker 5: paying one hundred and fifty percent of what Lily's charging

947
00:47:53,480 --> 00:47:55,799
Speaker 5: and didn't negotiate at all, over the course of the

948
00:47:55,800 --> 00:47:59,000
Speaker 5: next twenty or thirty years, they would probably make money.

949
00:47:59,320 --> 00:48:03,120
Speaker 5: Like they would probably be a better situation than it

950
00:48:03,160 --> 00:48:05,440
Speaker 5: would be without it, you know, not to get too

951
00:48:05,760 --> 00:48:10,680
Speaker 5: like insanely off the rails. But again, it's a podcast, so.

952
00:48:10,400 --> 00:48:12,920
Speaker 1: This thing is experiment, So let's do it.

953
00:48:13,040 --> 00:48:15,839
Speaker 5: Let's entertain some people. Right, why shouldn't the government pay

954
00:48:15,880 --> 00:48:16,120
Speaker 5: for this?

955
00:48:17,000 --> 00:48:20,480
Speaker 4: Well, you mentioned that the Inflation Reduction Act is going

956
00:48:20,520 --> 00:48:22,479
Speaker 4: to reduce the cost. This should be Biden's re election.

957
00:48:22,640 --> 00:48:24,359
Speaker 4: He's like, hey, I signed the bill that's given.

958
00:48:26,360 --> 00:48:31,600
Speaker 5: Yeah, let's look, let's look at this. Right. We just

959
00:48:31,640 --> 00:48:34,040
Speaker 5: had like the biggest public health experiment ever. You know,

960
00:48:34,080 --> 00:48:36,799
Speaker 5: we had COVID. Right, Like, how many does anyone know

961
00:48:36,800 --> 00:48:38,560
Speaker 5: off the top of their head how many people COVID?

962
00:48:38,680 --> 00:48:42,160
Speaker 5: I don't, that's not a fact that I have handy,

963
00:48:42,560 --> 00:48:46,719
Speaker 5: but right, but and how many people? What was the

964
00:48:46,800 --> 00:48:51,320
Speaker 5: all cause mortality of like COVID in like annually during

965
00:48:51,360 --> 00:48:55,320
Speaker 5: like the peak of the epidemic. It was probably high.

966
00:48:55,480 --> 00:48:58,240
Speaker 5: But what I'll tell you is it probably was similar

967
00:48:58,320 --> 00:49:00,319
Speaker 5: to how many people are going to dive over city

968
00:49:00,360 --> 00:49:03,000
Speaker 5: this year. You know, I don't want to like speak

969
00:49:03,040 --> 00:49:05,480
Speaker 5: without facts in front of me, but I would say,

970
00:49:05,560 --> 00:49:08,040
Speaker 5: you know, if if someone wants to go look that

971
00:49:08,200 --> 00:49:11,840
Speaker 5: up and you know, whether it's how many people divebcity

972
00:49:11,920 --> 00:49:13,799
Speaker 5: this year or how many and five years, I would

973
00:49:13,840 --> 00:49:18,600
Speaker 5: say that they are probably comparable public health crises. And

974
00:49:18,840 --> 00:49:21,480
Speaker 5: also in terms of the impact on the economy. Obviously,

975
00:49:21,480 --> 00:49:24,480
Speaker 5: nothing can rival shutting down the entire economy and you know,

976
00:49:24,560 --> 00:49:28,239
Speaker 5: having a lockdown. But if you look at it from

977
00:49:28,239 --> 00:49:31,279
Speaker 5: a cube versus chronic perspective, you know, if obesity is

978
00:49:31,280 --> 00:49:33,480
Speaker 5: going to cost us a trillion dollars this year in

979
00:49:33,480 --> 00:49:36,680
Speaker 5: indirect costs, and we're running it a trillion dollars a year,

980
00:49:37,400 --> 00:49:40,279
Speaker 5: I mean over the next ten years, like what it

981
00:49:40,400 --> 00:49:43,200
Speaker 5: just seems like something where it let's say that you know,

982
00:49:43,280 --> 00:49:45,880
Speaker 5: Lily and Novo and all the other companies that eventually

983
00:49:45,960 --> 00:49:49,520
Speaker 5: join the FRAY that they're effective in proving that the

984
00:49:49,600 --> 00:49:54,759
Speaker 5: side effects are moderate and that the overall benefit is sustained,

985
00:49:54,800 --> 00:49:57,680
Speaker 5: and it's good. Why would the government not cover it? Right? Like,

986
00:49:57,840 --> 00:50:00,839
Speaker 5: if they're if they'll cover COVID vaccine, should probably cover

987
00:50:00,880 --> 00:50:03,120
Speaker 5: this too, especially if it has a twenty percent production

988
00:50:03,320 --> 00:50:04,239
Speaker 5: like heart attacks.

989
00:50:04,320 --> 00:50:08,680
Speaker 1: I mean, well, I would never overestimate America's ability to

990
00:50:08,719 --> 00:50:11,000
Speaker 1: make bad decisions when it comes to public health care.

991
00:50:11,160 --> 00:50:12,520
Speaker 5: But that's a good point.

992
00:50:13,200 --> 00:50:17,719
Speaker 1: But James, that was a really fun conversation. Absolutely a

993
00:50:17,760 --> 00:50:19,840
Speaker 1: blast to have you on and go through the transcript

994
00:50:19,920 --> 00:50:21,839
Speaker 1: sort of in real time while we're talking to you.

995
00:50:22,120 --> 00:50:22,680
Speaker 3: That was great.

996
00:50:23,760 --> 00:50:26,839
Speaker 5: Absolutely, And you know, if you want to learn more,

997
00:50:27,080 --> 00:50:29,680
Speaker 5: you know, I've been writing about this since June on

998
00:50:30,000 --> 00:50:33,200
Speaker 5: is suctriniresearch dot com. I go pretty deep into these

999
00:50:33,239 --> 00:50:37,160
Speaker 5: I did want on a yeah, oh you you read it,

1000
00:50:37,200 --> 00:50:38,640
Speaker 5: Come on, we do a little.

1001
00:50:39,120 --> 00:50:40,600
Speaker 1: There's much believe it or not.

1002
00:50:40,640 --> 00:50:42,279
Speaker 2: There is something that I read it.

1003
00:50:42,200 --> 00:50:44,400
Speaker 4: On the subway this morning while coming in. I do

1004
00:50:44,520 --> 00:50:45,560
Speaker 4: real prep for this job.

1005
00:50:46,120 --> 00:50:48,120
Speaker 5: I send it to you like twelve hours beforehand, and

1006
00:50:48,200 --> 00:50:50,360
Speaker 5: I know it's like, you know, twenty pages long, so

1007
00:50:50,960 --> 00:50:51,799
Speaker 5: I would have forgived you.

1008
00:50:53,080 --> 00:50:54,799
Speaker 1: All right, well, James, thanks so much for coming on

1009
00:50:54,840 --> 00:50:55,960
Speaker 1: all thoughts. Appreciate it.

1010
00:50:56,640 --> 00:50:57,879
Speaker 5: Thank you so much for having me guys.

1011
00:50:58,000 --> 00:50:59,040
Speaker 2: Thanks James, that was a blast.

1012
00:51:12,080 --> 00:51:14,480
Speaker 1: All right, well, Joe, I for one look forward to

1013
00:51:14,560 --> 00:51:18,880
Speaker 1: the spelt future of publicly funded weight loss drugs.

1014
00:51:19,120 --> 00:51:21,160
Speaker 4: I mean, I totally like, why not if all the

1015
00:51:21,239 --> 00:51:25,120
Speaker 4: things seem to be true about this what many people

1016
00:51:25,160 --> 00:51:27,920
Speaker 4: seem to believe. And you know, it's like James is

1017
00:51:27,960 --> 00:51:29,840
Speaker 4: like totally right, Like you see a lot of people

1018
00:51:29,840 --> 00:51:32,359
Speaker 4: like poking there, like there must be some catch here, right,

1019
00:51:32,560 --> 00:51:34,520
Speaker 4: there must be just gonna melt your insides or it's

1020
00:51:34,520 --> 00:51:37,200
Speaker 4: gonna do something. Maybe one day, you never know, but

1021
00:51:38,040 --> 00:51:40,400
Speaker 4: right now, anything I read about the side effects never

1022
00:51:40,480 --> 00:51:41,919
Speaker 4: seemed like that compelling or anything.

1023
00:51:41,960 --> 00:51:43,760
Speaker 2: And he just point out the classic drugs for a while,

1024
00:51:44,120 --> 00:51:44,640
Speaker 2: it kind.

1025
00:51:44,520 --> 00:51:47,680
Speaker 4: Of feels like potentially like a legit miracle drug, right,

1026
00:51:47,800 --> 00:51:48,720
Speaker 4: Like it's kind of wild.

1027
00:51:48,760 --> 00:51:50,600
Speaker 1: Well, I think he makes an excellent point about the

1028
00:51:50,640 --> 00:51:52,719
Speaker 1: trade offs, right, and at some point it might be

1029
00:51:52,800 --> 00:51:55,520
Speaker 1: cheaper for an insurance company to just provide this drug

1030
00:51:55,760 --> 00:51:59,120
Speaker 1: rather than treat someone for diabetes or heart problems or

1031
00:51:59,160 --> 00:52:02,320
Speaker 1: sleep apnea or whatever else for the rest of their lives.

1032
00:52:02,520 --> 00:52:04,520
Speaker 1: The other thing I was thinking throughout all of that,

1033
00:52:04,560 --> 00:52:07,520
Speaker 1: you know, I initially came into the conversation thinking like,

1034
00:52:07,600 --> 00:52:12,040
Speaker 1: oh wow, if everyone's consuming less, yeah, maybe that's deflationary.

1035
00:52:12,280 --> 00:52:15,440
Speaker 1: But now I'm going back to that price over volume

1036
00:52:15,680 --> 00:52:19,080
Speaker 1: oh theme. And James brought it up as well, which is, well,

1037
00:52:19,160 --> 00:52:22,440
Speaker 1: if you're Wendy's and people just aren't buying as many cheeseburgers,

1038
00:52:22,480 --> 00:52:25,280
Speaker 1: then maybe you just raise your prices to offset it.

1039
00:52:25,320 --> 00:52:27,960
Speaker 4: Could be the I am cures. I mean, there's all

1040
00:52:28,040 --> 00:52:30,279
Speaker 4: kinds of like other things that we could get into. Yeah,

1041
00:52:30,320 --> 00:52:32,760
Speaker 4: and so another thing, and I saw someone on Twitter

1042
00:52:32,800 --> 00:52:36,160
Speaker 4: say this, They're like, well, well, the snack companies put

1043
00:52:36,239 --> 00:52:38,040
Speaker 4: even more salt.

1044
00:52:37,840 --> 00:52:39,759
Speaker 2: And other addicting type of.

1045
00:52:39,719 --> 00:52:43,800
Speaker 4: Like ingredients to counter setting the people who aren't taking

1046
00:52:44,480 --> 00:52:46,759
Speaker 4: the drugs buy even more in the future, Like they're

1047
00:52:46,800 --> 00:52:48,439
Speaker 4: not going to give up without a fight if there's

1048
00:52:48,440 --> 00:52:51,200
Speaker 4: some drug that causes people, you know, like everyone's gonna

1049
00:52:51,239 --> 00:52:53,399
Speaker 4: like try to like find some way. We didn't talk

1050
00:52:53,400 --> 00:52:56,600
Speaker 4: about gyms really, but I wonder like, like one way

1051
00:52:56,600 --> 00:52:58,400
Speaker 4: of thinking is maybe it's bad for gyms. But on

1052
00:52:58,440 --> 00:53:00,680
Speaker 4: the other hand, like if maybe one to show off,

1053
00:53:00,840 --> 00:53:03,360
Speaker 4: that's exactly right. If you feel more confident, then maybe,

1054
00:53:03,400 --> 00:53:05,000
Speaker 4: like you know what, I'm ready to I don't mind

1055
00:53:05,040 --> 00:53:07,520
Speaker 4: being seen at the gym. All kinds of interesting questions,

1056
00:53:07,520 --> 00:53:09,680
Speaker 4: Like I like the idea of like, you know, Madge

1057
00:53:09,760 --> 00:53:12,600
Speaker 4: or Hinge is a bye or is like a winner here?

1058
00:53:12,680 --> 00:53:15,640
Speaker 4: So that was a very fun thought insperiment, and it

1059
00:53:15,680 --> 00:53:17,840
Speaker 4: was fun in the context that he knew so many details,

1060
00:53:17,840 --> 00:53:19,279
Speaker 4: so it was like also kind of real nudges.

1061
00:53:19,440 --> 00:53:21,640
Speaker 1: Yeah, and I'm going to spend I think the next

1062
00:53:21,760 --> 00:53:23,960
Speaker 1: like two hours or so just going through some of

1063
00:53:23,960 --> 00:53:26,440
Speaker 1: the Earnings transcripts and saying what people are saying about this,

1064
00:53:26,440 --> 00:53:29,920
Speaker 1: because I hadn't realized that people were already actually talking

1065
00:53:29,960 --> 00:53:30,359
Speaker 1: about it.

1066
00:53:30,600 --> 00:53:33,120
Speaker 4: Well, so I think the reason I didn't realize it

1067
00:53:33,160 --> 00:53:35,600
Speaker 4: is because I was searching azimbic. It's just like the

1068
00:53:35,640 --> 00:53:39,360
Speaker 4: thing all searching. You just search GLP and then tons

1069
00:53:39,440 --> 00:53:41,560
Speaker 4: come up, and so it's really interesting. I mean, it's

1070
00:53:41,560 --> 00:53:43,719
Speaker 4: a huge focus on a lot of these calls just

1071
00:53:43,760 --> 00:53:44,480
Speaker 4: from looking it up.

1072
00:53:44,560 --> 00:53:47,200
Speaker 1: All right, well, fun conversation. Shall we leave it there,

1073
00:53:47,280 --> 00:53:50,000
Speaker 1: Let's leave it there? Okay, this has been another episode

1074
00:53:50,040 --> 00:53:52,879
Speaker 1: of the All Thoughts podcast. I'm Tracy Alloway. You can

1075
00:53:52,880 --> 00:53:54,920
Speaker 1: follow me on Twitter at Tracy Alloway.

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Speaker 4: And I'm Jill Wisenthal. You can follow me on Twitter

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00:53:58,239 --> 00:54:01,360
Speaker 4: at The Stalwart. You can follow Hello James Van Galen

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00:54:01,800 --> 00:54:05,640
Speaker 4: on Twitter at sutrini seven. Also check out his research.

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00:54:06,040 --> 00:54:09,680
Speaker 4: Follow our producers Carmen Rodriguez at Carman Arman and dash

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00:54:09,719 --> 00:54:12,800
Speaker 4: O Bennett at dashbot and all of the Bloomberg podcasts

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Speaker 4: can be found under the handle at podcasts. And for

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Speaker 4: more odd Loots content, go to Bloomberg dot com slash

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Speaker 4: odd Lots where we have a transcript.

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Speaker 2: Blog in a newsletter and we don't have.

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Speaker 4: A pharmaceutical channel and there maybe we've got to add

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Speaker 4: a medicine and health one. But check out the discord,

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Speaker 4: one of my favorite places to hang out on the internet.

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Speaker 4: Other odd Lots listeners are there talking twenty four to seven,

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Speaker 4: Discord dot g slash on.

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Speaker 1: And if you enjoy odd Lots, if you like listening

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Speaker 1: to these types of conversations imagining a world without obesity,

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Speaker 1: then do leave us a positive review on your favorite

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Speaker 1: podcast platform.

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Speaker 3: Thanks for listening. In a