Editors' Note: This is the transcript of the podcast we published last week on Invitae (NYSE:NVTA). We hope you enjoy.
Daniel Shvartsman: Welcome to the Razor's Edge. I'm Daniel Shvartsman. I'm joined by Seeking Alpha author Akram's Razor on this show. Each episode we take an investing idea or theme that Akram has been looking at for his personal investing as well as the Seeking Alpha marketplace service he runs, also called The Razor's Edge. We look at the ideas themselves, stress test them, try to figure out where they might go right or wrong, talk about what's been going on, and talk about the research and analysis that led to this take.
The idea to share some current investing ideas here into consideration, but also get the ins and outs of deep fundamental market research today. This week's topic has a lot behind it. The ticker symbol is NVTA. The stock is Invitae. Akram released a short case on the company on Seeking Alpha on October 11th, that went long in terms of breaking down why the genetic testing company was more like a WeWork than an Amazon. In other words, the company has had prodigious revenue growth, but it's come at a cost of increasingly negative cash flows and limited competitive advantage, in Akram's view. Was a thoroughly researched short case and as is often the case it's attracted a lot of attention, both positive and negative.
On today's Razor's Edge, we're going to talk about what brought Akram to this case, what investors are missing, and some of the reactions since he went public on Invitae. We're also joined by a colleague of Akram's, James who can add some insight on this topic based on research he's done on the stock as well.
Before we begin a quick disclaimer and disclosure; The Razor's Edge is a podcast on Seeking Alpha's The Investing Edge channel. The views discussed belong to either Akram, James in this case, or me respectively, and nothing on this podcast should be taken as investment advice. We'll disclose any positions in any stocks discussed at the end of the podcast, though upfront I can say I have no positions in any of the stocks we plan to discuss, Akram is short Invitae and long Myriad Genetics, and James is short, Invitae. We're recording this on the morning of November 4th.
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All right, guys. Good morning. Welcome.
Akram Razor: Good morning.
James: Good morning. Thanks.
DS: So let's just go really basic, why Invitae? What brought -- why does your radar get on this stock? Where did they come up?
AR: That's definitely an interesting part of the story. I guess the starting point was, there was people shorting Myriad. So I follow the Southern Investigative Reporter. And they've done a couple short pieces on that. And I kind of have taken a look at it briefly, which caused me to take a brief look at Invitae, and that was probably like, May or June. And then Ilumina missed big time on earnings, and I've traded Ilumina several times of the year. I've never traded any of these other stocks in terms of that. But it kind of got me interested in the space. And I guess what kind of, I mean, like, I think I had pinged James on it a couple times being like this is like this is worth looking into, but like neither of us had really gotten that excited about it.
And then there was a report that came out by a short seller, recommending the stock is an amazing long idea, which I read, because I know the short seller and his work. Once I read that, I was like, I need to look at this company a little closer. And then just the typical process, like pulling up their filings, seeing exactly what's going on financially, and I was just like, wow, this is just an incinerator. What are they doing? Why is -- like, what's the business model?
And that brought me to, there's an author on Seeking Alpha who had published a lot on this over the years, capital markets, laboratories and read their work, and they made these Amazon compares where, obviously, that's where you get a little bit of a heightened radar, when a laboratory diagnostic company is being compared to Amazon, which I mean, I don't know also if you know -- and I had like a brief experience with Theranos in 2000 it was say like, early 2014, like back when it was like -- I was picking on the Decacorns then, my favorite, like when I used to write my market commentary and I'd have a little bit of fun with it.
At the time, the two I was having fun with were Zenefits and Theranos. But I mean in Theranos' case, like I was just curious as far as what like -- I mean, it was a private company, $10 billion, obviously a lot of hype. I was like, wow, do I short Quest and LabCorp, right? I mean, I can't make -- I can't invest in Theranos. But if this company is so revolutionary like it, there's this pretty simple thesis out there in the public markets where I mean, if they're going to stick a lab in a box, I should go short Quest Diagnostics and LabCorp.
And I have, on the medical side, an extensive network of friends and family. So I ended up doing just one call with someone who'd been at Quest and in the laboratory diagnostic space, pretty senior for about 20 years. And like, I mean, it was like a 30 minute conversation. I felt stupid by the time it was over. It was just like, he's like, are you an idiot, you can't stick a Lab-in-a-Box. It was like -- it was literally like that, after like being very polite for a little while. So that type of stuff kind of intrigued me. And Theranos ended up being Theranos. I never really did much more with it after that. And then Wall Street Journal came after it, and it became this cautionary tale. I don't know if James -- did you follow Theranos very closely, I don't even know if we really discussed that?
J: No, I had heard from some VC friends who were very skeptical of it all the way through. But I wasn't that close to the name myself.
AR: Yeah, I mean, neither of us I would say, I would characterize myself as close to it. But I mean, I did take the time to literally be like, hey, do I short these stocks because of Theranos, right? It was like an investment idea at the time.
So yeah, I mean, I guess that's what started it, right. I mean, like Theranos had this -- and then the message was just kind of just like affordable blood testing for all, a social cause being compared more to, like technology differentiating companies and I mean, Elizabeth Holmes like to associate herself when she talked about things, when she compared herself to the Google Founders and Facebook and like, I mean, if you saw the documentaries like here we were at, in Brazil, and this is where we -- who was sitting there, and the Google guys, and the Amazon and Facebook, and we are the stars of the show, right?
And if you look at Invitae, I mean, like on the surface, it's like there's a social enterprise element to it, right? Where it's just like, we have a mission, and this mission is to make genetic testing affordable for all. I mean, like, they don't care, they don't describe themselves as like a laboratory diagnostics company, right?
DS: Well, they --
AR: That was a genetic information company. Go ahead.
DS: Yeah. I mean, if you look, I have got their 10-K open, their last one and it's -- our goal is to aggregate a majority of the world's genetic information into a comprehensive network that enables sharing of data among network participants to improve healthcare and clinical outcomes. So it's this.
AR: Yeah, so what does that mean?
DS: Right. You know, it is this very -- it is very big mission, right. It is very big.
AR: Yeah, I mean, James, obviously has some views on this. Like, I mean, what do you think of that part?
J: Well, I think that really comes down to the crux of the investment case here, which is, just because something sounds good as a sound bite doesn't mean that it actually makes sense in business. And so the idea of accumulating the world's genetic information, you would argue, seems like if you could do that would allow you to capture rents on that database. But there are very real issues with that. Namely the company has said that they won't do that. And then when they're pressed about how -- whether or not they will do that, they kind of seem to give non answers what I can tell.
So that's one of the questions right that that I think would be very helpful for the company to lay out there, very specifically, which is, if we gather all this data up, and specifically what data is being gathered? Are they -- is that data, they've also released to a common database, like they say they have been doing, is there additional data that they're not releasing?
AR: Well, I mean, the data that they're sharing with the common database is the variant of unknown significance data, right? So I mean, that's what they're contributing to Clinvar. We don't really know. But like, I mean, I'll be honest, like if I was to go in and have hereditary cancer test, I would have never thought once about, like, who the lab doing the test is or ask the oncologist anything, but like literally now knowing this business, I mean like, make sure you're not using Invitae, because I have no clue what they're going to do with that data.
Like my DNA is a product for them to figure out somewhere down the road just to do something with it, I mean, it's so -- like James just said, it's very bizarrely unclear, which is decidedly convenient when you're running a business model like this.
DS: So step back for a second. So the thesis -- the company's thesis is that they're providing genetic tests. And then they're aggregating that, they provide it at -- arguments are they providing it for below the cost that they actually have to pay to their providers to actually deliver the test but low cost testing that they can then -- if we're going to use the Silicon Valley jargon, that they get the flywheel of more genetic data and improve, they get a lot of volume, and eventually, that's both going to give them scale to lower the costs, but then also they're aggregating this huge genetic database, which as you kind of point out, Akram, they're going to have to do something with to make it reasonable, which raises concerns in of itself. But the idea is that eventually they'll get scale from offering at cost that will allow them to become a profitable business, I think. That's how I understood the company's take and the company's argument.
AR: I mean, like James just said the company hasn't explained that. So if you look at this company's history, this isn't like a startup, number one, right. So this company was founded in 2009. They've been at this for a decade, okay. Initially, they were kind of rare disease focused, right?
Like where they're deriving the revenue, if they were to actually describe themselves accurately, they would be like, we do hereditary cancer testing far cheaper than Myriad, right? And I mean, like, I think that's an important thing to look at this. I mean, there are sources of revenue, which is generally speaking what has attracted people to the stock, it's not science, right. It's not like you've developed a test or you're like Foundation Medicine and you've got this companion diagnostic clinical trials and you are about to do something where you're going to earn a high margin, because you've developed something nobody else has. That's typically, what people get excited about in science and biotechnology, right?
You get rewarded for R&D, okay. These guys have approached the market that Myriad discovered the BRCA mutation in 1994, okay. That's like what the indication of hereditary cancer right? I understand cancer, 90% of it is not hereditary. So you're looking -- when you talk hereditary, there's a less than 10% chance that it's something hereditary. That's helpful from a clinical standpoint, as far as your treatment for cancer diagnosis, whether it's early or late stage or whatnot.
So this company came into this space in the sense that Myriad had a monopoly on this gene, right? They started doing their first BRCA testing lab kit was like 1996. They had the patent on that gene till 2013 when the Supreme Court struck it down, right. So these guys entered this space, essentially, from that standpoint as a competitor against Myriad. And once that space kind of opened up in hereditary cancer testing, I mean like, well, you can't patent these genes, right? Which is great for competition, but what's the flip side of it?
If I make a major discovery on gene X correlates to disease Y, right? And I can't patent it and I'm running like a test that kind of identifies that historically, kind of tough to build a very profitable business around it. So when we go back to like what you were saying about like this whole genetic information and whatnot, the most interesting thing about this business is look at the rest of the landscape. Nobody's selling the story, like Myriad's still the revenue leader in hereditary cancer testing.
The other space the company is in deriving revenue from is reproductive health, carrier screening, non-invasive prenatal screens. And that's the most crowded market ever. It's got Ilumina and Sequenom, which is owned by LabCorp, like pretty much, they control the IP there. And then there's like a half a dozen other competitors owned by large companies.
So like, in hereditary cancer, you've got Myriad. And then you kind of have this like at a huge, huge, huge discount to Myriad prices, Invitae, right? I mean, like now they're running what, $99 tests, okay? So you look at it and you can sit here we can just, like figuring out what they want to do data wise and the fact that it's Vegas kind of important. It's also important in the context of -- well, there's a whole industry here, right? I mean, this is at least what -- we got some heat when we cautioned this like, some of this has attracted obviously a lot of retail investors by using the Amazon compare. And, in the initial thesis it was like a cautionary mention at the end, like that the laboratory diagnostic space doesn't need another Theranos.
And at least in Theranos' case, what they were selling to investors was we're building a better mousetrap essentially, right? Like we've got -- we've engineered something that's going to change the way we are able to do testing. And that's not the story here. The story here, I mean, if you go back to the founder in 2016, there's a couple of interviews with him. And he literally says like, we're providing the same test that everyone else is providing, we're just making them more affordable. That was that's their initial story, right.
So I mean, you do kind of run into something like that, which is where, like some people may think it like, you know, oh, it's very, self-serving or opportunistic to compare this to WeWork. It is, exactly like WeWork from a business standpoint. Like you can't get around that fact. And I think the Amazon like -- and this is not like some guy writing a really bullish Seeking Alpha article and using hyperbole, the management sticks to compares. I mean, they -- literally they have a slide in their investor deck, what we can learn from Amazon, and they make statements like our competitors -- what did they say, James, is like the competitors margin is our opportunity or
J: Yeah, something that effect. Yeah, you've heard a lot of ground there, Akram. I think the important aspect of what you've said and the commonality among all those points is that the management team has made some very high level statements about the promise of this industry and the promise of their company. And they could really answer a lot of these questions if they wanted to, right? They could say, okay, here is our revenue breakdown from cancer or nips [ph], kind of other panels, which don't have necessarily the clinical efficacy.
Or they could say, here's our -- here's what we're getting from the various cost cutting or network effects or economies of scale that we promised. And here's how this is going to develop, but they don't they just say, trust us, it's all going to work out. And the way that it's not [ph] going to work out is that it worked out for Amazon. So it's there's not much transparency, there's a lot of just kind of big picture verbiage I would say.
AR: Yeah. I mean, 100% and like, I mean, you get the Amazon story, Daniel, right. I mean, if you look at it, people like, if you look, well, come on, Amazon was losing money. No, Amazon was improving operating cash flow from literally from day one. I mean, people forget, like, you make money selling DVDs and books online, particularly if you don't pay your suppliers for 100 days, right? I mean, like, where was Amazon after a decade? It was already a behemoth, right?
So when you look at it, Amazon had someone else, i.e., their suppliers funding their growth. It's free, cheap capital. This company went and IPOed in 2015, at $16 a share, had like 25 million shares outstanding. They're at 100 now, four years later, right? I mean, it's like, they keep going back to the well. So if you're an investor and you're looking at it from a return on investment on money, you're giving them. I mean, you have a serious problem. And if you look at it, and you say, hey, I'm going to compare myself to Amazon. Well, Amazon had a cost structure that attacked this cost structure of brick and mortar, okay?
They benefited from so many things. We didn't have sales taxes, if you were paying on Amazon as a consumer. They benefited from the fact that they went into markets with huge existing volume already, books and DVDs. They didn't have to convince people to buy X, Y and Z. They were already huge volume markets. I mean, I'm sorry, but like hereditary cancer testing. It's not something people get excited about to go online or buy as a gift for a friend.
I mean, like, we get the DTC space, and even that has already slowed down drastically, and that's Ancestry. And if Ancestry slowed down at like 30 million tests, right, like, you really think people are going to be super excited as individual consumers to be like, I really need to figure out whether I have a history of cancer right now. I mean
J: Well, and more importantly, more importantly, I think there's a healthy amount of skepticism in the medical community whether or not these tests are useful, right? Like the issue with any test is, if you find something, an indicator of a disease. Does that help you catch the disease? Does it help you catch it earlier than existing testing or physical exams, or other ways of seeing the diseases there? And then can you do anything about it?
So, I think one of the issues here is even if you were to send your saliva [ph] sample out, and you came back with saying indication that you might have liver cancer potentially. A, you wouldn't know, if that were real, because it's really just a correlation at this point. There's not enough data. B, even if you knew, it was real, there's really not much to do except worry about it. And so you have a lot of additional burdens on the patient and the healthcare system in terms of emotional and financial burdens, without any clear benefit.
And so I think within -- as I'm saying, within breast cancer, that there is a clear benefit in terms of efficacy and outcomes. But for the rest of the space, it's really not clear. And that's why, if you look at the treatment protocols for most of the commercial payers, they don't pay for all these tests, because the research doesn't demonstrate that they should.
DS: So one of the things I'm -- as we're throwing around these comparisons. I'm thinking about the -- there's a notion in Silicon Valley and sort of abroad, the market, the idea of tech, tech as a category is becoming less and less meaningful, because companies are adopting online models or tech models to different verticals. And what I think about with Theranos and Invitae, specifically, healthcare is a very complicated sector, both in terms of the way payers work and we can get into Medicare in a little bit, but the way the payment system works.
And I'm not talking even about what might or might not happen in the future with changes to insurance. But just -- that's, I think, always been fairly -- you have to really work through it. And the articles for example, there's looking at the different reimbursement codes and that sort of thing. Like, it's more than you have to do to figure out, well, are they going to buy this software tool or not?
And then also, Theranos is a problem, because they were actually -- there were issues of fraud around people, things that were supposed to help people's health. And so I guess I'm just kind of, I guess, I wanted to hear a little bit more about like, because -- a lot of the response.
AR: Well, I mean, look -- let's, I mean, if you think about Theranos, where really was the fraud. The fraud like, I mean, if you read the indictment, what she's really on the hook for the biggest time is misleading investors, okay. I mean, that's the biggest part.
Yes, correct, like at the end, there was issues with the lab testing and they were getting inaccurate results because by the time she did that deal with Walgreens, and clearly they were at a point where they were desperate for showing meaningful revenue, because they need to raise more cash, right? Because they still haven't made the Edison work, right? They're trying to engineer a problem. They're working on it.
She didn't set out to commit fraud, right? She set out to build -- to stick a Lab-in-a-Box, right? But she had bigger aspirations. She wanted to take -- that she wanted to aggregate your data. She wanted to stick it in this cloud called Yoda, right? I mean, if you look today, you still have people who defend -- I mean, what's his name?
DS: Yeah.
AR: Tim Draper has really defended her. And what does he defend her on the point, and his point is that look, she had this vision to give you a movie of your health, i.e. like look, I get my blood work once a month, and that goes into a cloud, right? And my physician can track it. And I'm building a historical picture of a trend, by having more real time information on my blood work, cholesterol, everything right? So that creates preventative medicine in their view, right? Like your ability to have an earlier and more accurate versus a snapshot, right?
So he's like, look, she had that and was great and I genuinely have discussed this with James. I believe if she had IPOed this company and the company had started out as like, hey, she's got this Edison and this finger stick. It would have been just like binary tech play, right? She either makes it or she doesn't. And people would have debated that and thought that out there would been the believers. And then there would have been the skeptics, but she would have had plenty of time, as she gauged how that was working, okay?
To find something that generates revenue, which investors are willing to pay for, like with her inflated market cap on the Edison optimism, where she could just do regular lab testing like Quest and like LabCorp, but she would obviously do it at a lower price, right? But she would sell you the story that I'm going to stick this in the cloud, and you're going to pay a subscription fee, right? And that subscription fee to that cloud, Yoda, where all your information is and your general practitioner can access it and whatnot, that's the business. That's where I make money.
Of course, what's the problem with that business? And that business is -- well, I mean, that you're going to be like, well, you're losing a lot of money per test, doing your tests at a lower price than Quest and LabCorp or whatever to provide this back end service, why can't they do that, right? I mean, like, that becomes the same thing because you're going to need the same infrastructure. That's where she ran into issues. She's collecting data and she doesn't have the lab infrastructure to do it at the scale that these guys are doing.
If she'd been like these DTC companies, 23AndMe ancestry, she could have actually struck a deal, which is like, I'll be the cloud and I'll outsource the testing to them. And I will take a loss on the tests, because my investors are going to subsidize it, right? I mean, there was -- there would have been many Ways, but of course, she was also trying to kill their businesses. So it didn't work, right, with her engineering. but like, I mean, the bottom-line is, is if you look at it, like, it's something where you had a potential business model in that sense, where we would be asking the same questions that you'd ask about in detail, right? Like what are you doing that's different?
If you look at them today, Quest and LabCorp, they've entered into direct-to-consumer testing. I can go online and order my own tests and schedule the appointment and go pick them up, right? I'd like it's really, like, it's something where I don't even need to go through my medical practitioner if I want to get tested. And I don't know, to the degree I mean, I've discussed this with other people in the medical community on the testing side and I'm just, why isn't there a VIP service like, if I'm an extremely wealthy individual, where they come to my house, do the work, store in a cloud. And there's access to my blood work, on let's say -- but we don't have to do a monthly but let's say every three months, right?
These -- I mean like these are obviously options. So when you look at something like that and you see what went wrong with this company, her biggest mistake was being private. It's like -- because with her turtlenecks and Steve Jobs and Stanford dropout, I mean, the benefit of doubt, she would have gotten, if you look at the benefit of doubt, for example, that this company, Invitae has gotten. I mean, their CEO says one thing, and then he does the other three months later and nobody has cared like, at all. No one's asking questions. I mean, I don't know if you -- have you watched the CNBC, the Invitae interview with him on CNBC, Daniel?
DS: No. No, I haven't pulled that up.
AR: If you watch that, you would not understand what the company does. It's like we are the company the key opinion leaders turn to and this -- like, he does not say I'm a laboratory diagnostics genetic testing company, who derives primarily its revenue from doing these types of tests. And we're doing them at a significant discount to a competitor, who has had a monopoly in the space for ages. And we're using that to generate volume and we're hoping to parlay that into other sectors. And this is like -- this is our business model. Because to be -- to tell you the truth, if you look at this closely, I don't think they figured it out. They are trying to figure it out as they go along and that's part of the problem here.
DS: Isn't -- you said, if Theranos that they could have arguably sold tests below costs, but then put the -- like, isn't that essentially what the Invitae has? They haven't maybe laid out that vision but they're essentially selling below cost to get into -- like they could build that into the cloud sort of approach like?
AR: Okay. No, let's not make that mistake, okay? I'm saying that Theranos, if they wanted to, okay, and wanted to pivot for a story to sell, that sells well, when you're dressed like Steve Jobs, and you dropped out of Stanford, and you're a unique character and you're -- you've got a Board that has these people on it. And you've convinced Tim Draper and Larry Ellison to invest in you and whatnot, right? When you've dressed something like that, and you've ticked all those boxes, okay, you could just be like, hey, I'm going to do the same blood work everyone else is doing, I'm going to do it cheaper. So come to me. And how I'm going to make money off of it down the road, is I'm going to store that data, and it's going to give you a real time picture.
Now if you were to compare this on genetic information, my DNA isn't constantly changing, right? So if I'm doing -- if my focus is hereditary screening, i.e., what's been passed on to me, and what does that indicate?
What is the usefulness of that sitting there, right? Number one. And number two, in her case, it would be like, well, you still need to build the lab infrastructure to do the tests. You're going to have to do huge volume. So any business that -- like I mean, if you listen to the CEO, he literally sits on conference calls. And he's like, we hope to do half a million tests this year and reach a million people next year, and on our way to billions across the world. Well, what kind of infrastructure, you need Amazon infrastructure for that, right? I mean, how many geneticists do you need, genetic counselors? The industry doesn't even have the employees. I mean, we were discussing this, like, how big is that industry James.
J: It's well smaller than then I thought it was. I think it's in the thousands of genetic counselors. I forget it, 10,000 or 15,000.
AR: So you're going to need lab technicians, genetic counselors, you're going to need the physical footprint. You're going to need logistics. I mean have you looked -- like part of the thing that like -- we found kind of interesting is just look at Quest Diagnostics. I mean, there was a $100 price target slapped on this thing. That's the market cap of Quest, okay? They have 3,500 trucks like 26 planes, 6,000 patient access points, right? They have infrastructure to test everybody.
The internet bull on this stock, he's been close to management. He's done a lot of write ups on it. One of his write ups was just recently, and I read it and he's like, I visited the company and the CEO told me that they're actually paying for the trucks to go to FedEx, to pick up the samples and bring them back instead of waiting for FedEx to bring them to the lab. And he's like, I've never seen a company who cares about the customer so much. And I am like -- I mean, sorry, logistics are part of his business. Collecting the samples and the turnaround time and what the infrastructure you need to do it, right?
Like that's not something of like, hey, I really care about my customer. It's something you have to do and unfortunately, Quest and LabCorp are sitting there with huge economies of scale and scope and infrastructure and the same machines available to them, and the lab technicians and the geneticists and everything to flip this switch on, and they're not flipping it on. Why?
DS: Right.
AR: It doesn't make money, because the volume isn't significant enough and the cost isn't at that point. So when this company talks about driving down costs, no, they're not driving down costs. Everyone else has a lower cost per test already established, because they have higher volumes in the space, right? If you look at it Myriad's cost per sample is in the $140, $150 range. If you look across all these other labs, who are doing the stuff and the testing on the reproductive health they're all far lower, right?
So this is a last person in the space coming and trying to get to the volume, trying to get to the economies of scale and trying to drive it down, right? But they still are subject to the same cost infrastructure limits. It's not amazon.com. They haven't eliminated the blockbuster employees sitting, that when they're competing against in DVDs like a Netflix or an Amazon or whatnot, they haven't eliminated the huge physical retail footprint that a Barnes & Noble needed, right? Like, they still have the same limitations, from a cost standpoint. They're relying on Ilumina machines, consumables, Agilent, Read [ph] everybody -- like it's the vials from, what's the company that sells the vials?
J: OraSure
AR: OraSure, right, like you're buying the same stuff from the same people. So it's when you look at it from that standpoint, like if they were to sell you a story about data or whatever, it's like, well, everybody else can sell us a story about data. Why are they selling it to us?
J: It's an interesting dynamic here, because when there was the rebuttal by this bullish commentator/endorsed analyst of the company, there was a comment that, hey, it's not just the raw data, it's not just the genetic information that is useful, because genetic information in and of itself doesn't tell you enough about the disease. And I think that's a partial indictment of the whole process. But more importantly, what the analyst said is, what the company does is they take that information and they combine it with a patient's medical record. That includes all of their scans, their CTs, their MRIs, all their historical blood tests, all their physical exams, and then it takes that data. And if you get enough of that data, then you can start running effectively very large statistical relationships and figure out, okay, which genetic mutations might be associated with which diseases.
The problem with that is, as far as we know, that's not what's happening. And yet the company, again, they've kind of endorsed this, this guy is an analyst of record, the company hasn't come out and said that. But that's not what's happening. Because if it is what is happening, I think they're serious privacy concerns. So I think it's very different, if you as patients and [indiscernible] into 23AndMe, you might sign a paper, some paperwork somewhere, but if they're actually signing away the rights to all their medical records. Again, I don't believe they are, but again, this is what would need to happen in order for this data to be proprietary and useful. Then I would imagine the consumers are not aware of that.
And so you kind of have this catch 22, if you're getting the data, whatever, this guy refers to it as the golden data, whatever it is, if you're getting that data, such that it's useful, you're probably in violation of some privacy laws, whether or not you are in terms of you're covered legally, I think just patients don't understand that's what's happening. And if you're not getting that data, then there's a very real question as to what exactly is the use of just this genetic information without putting it into -- in context without kind of correlating it to these other disease markers?
And again, this is a question that could -- that's very answerable by the company as far as we know, has decided not to answer.
J: I mean, look, there's also two elements of that, right. If you remember also, in his rebuttal, he pointed out to a subscription model, right ,where he was even saying that this should be looked at from a dollar-based retention standpoint like a SaaS company. So I mean, again, if he's saying this, it's something that well was spoon fed to him, okay? And that's part of the element here, when you're dealing with something like this, and you look at that, it's like, all right, so like, I go in, I do a test for cancer, but you know, a BRCA screen. And you're saying -- are you essentially saying that, in year one, you generated revenue off of the actual testing, but then in year two, and year three, supposedly, my DNA is something that just sits there, and they can find ways to make money off of, by farming it for some sort of data that they can sell to pharma.
And it's tenuous at best to even understand how that model would work, because if you look at the rest of the industry, you just have to assume, they're all idiots. I mean, how many tests has Myriad done? I mean, look, when you go back to this thesis, Daniel, one of the most important things here is, when I put this on, this company was bigger than Myriad, literally in enterprise value, it was bigger than a company with $850 million in revenue, 20 years of testing. They've done 6 million tests through some -- to that effect I think it is at this point.
They have a database that they've made a trade secret since 2004, as far as variant data. They have four times the employees of Invitae. I mean, if you were to look at this company from there -- one notable institutional bull in the space, like this bull doesn't own any Myriad, okay. And they have a genetic spawn, and they did like kind of throw like a little bit of a shade at this thesis when it came out. And I mean, I can imagine they got a lot of questions because they own a lot of the stock and they were like, these are the companies leading in AI.
And then they like -- they listed Invitae like two other names. And then they put in their tweet, which was almost essentially directed, not my gen [ph], which I mean, for someone like me, I just -- I didn't even really spend much time getting into the AI nonsense. But if you look at Myriad how many people with machine learning backgrounds and data scientists do they employ, plenty.
You could just go on LinkedIn, look at it, and draw your conclusion. But they're not out running around saying, hey, we got AI, we're doing stuff. We're literally running machine learning models on your DNA. We're figuring out better ways, a secret sauce. Like who would advertise that? If you actually have made the data a trade secret, and you refuse to share it and they've gotten a lot of heat for it, literally the whole industry had to band together to contribute data freely to Clinvar, because Myriad won't share, because they're like, hey, fine, you took away our patent, but who cares about that. Our ability to interpret this is better than everybody else at this juncture.
So again, you look at it, at something like that, and you're just like, well, there's companies who've been doing this for decades. And you're just supposed to assume that like data science is completely irrelevant to them. But the company that acquired an AI startup in July, by September is a leader in this space. I mean what, you know.
DS: Solet me -- so there are a few directions to go here. But let's quickly touch on Myriad. It's -- you're using it as a payer here, as I think you mentioned, it's -- short sellers have kind of had their eyes on it. Somebody like Southern Investigative Reporting Foundation has reported about it. Why are you comfortable with that as the other side of this trade given the fact that they've also come under fire?
AR: I mean, I don't know James, you want to tackle this? I'm obviously a lot more bullish on Myriad then most people. I would say, like, I can't really get my head around the short thesis, and I can't get my head around the short thesis in a relative context. I mean, if you've looked at the space there are some companies with some pretty crazy valuations. Myriad is not a hard business to understand. They have a cash cow in hereditary cancer. They've used that to diversify into companion diagnostics, into carrier screening, now into these pharmaco-genetic tests, psychotropic like for depression, which is a very controversial area.
A lot of a lot of volatility around Myriad lately, let's say the last six months, has been tied to this gene site division, and the way the FDA wants to treat these tests, where I get a DNA test that like tells me, I'm more tolerant for Zoloft over Prozac. And no science has shown any clinical efficacy yet, and it's a controversial area, because there's obviously some doctors, and they've been doing -- they've been running clinical studies to try to get this approved. And they missed the primary endpoints on it. But there's also an argument that in depression, which is like opioids, a national crisis, essentially speaking, and it's not going to get better, that there's nothing, and something is better than nothing. I mean, two-thirds of antidepressants are prescribed by general practitioners. Not -- you're not talking about the psychiatry side here. These are not experts on these drugs or on mental health.
And the argument is that maybe you give them something that starts this out with a little bit more direction, however little incremental it is. Now when the stock got hammered in the summer, on its last earnings, was because they said the FDA is pushing back on them on the labeling. And then recently, there was another genetic psychotropic-related test company where the FDA allowed them to resume sending the test information, but to the doctors. So the patient just gets this, like here's what your genetics say, but nothing about the drugs. But the doctor actually gets the drug indications. And then that doctor can see that and that doctor can use that as part -- like as a helpful part of his treatment.
But again, you go back to -- they haven't been able to show scientifically and it's hotly debated. I mean, there was just recently something in -- two Harvard doctors had published something in one of the big journals on mental health, same thing with oncology, like outside of BRCA, like there was a recent paper basically like these other genes are like no better than a placebo.
So this is part of the problem in the space but I mean, I haven't -- I don't have the numbers in front of me. I mean, James do you remember off the top of your head, but I mean, I think it's like $850 million in revenue and like $150 million in EBITDA, something like that against a company with -- that did what, like $144 million in revenue last year and lost what $100 million.
J: Yeah, but larger now.
DS: Yeah, $850 million, trailing 12 months revenue, looks like EBITDA of over $100 million at least.
AR: Yeah. So like, you can look at that, I mean, and this is something when you look at stocks, I mean I was long, some Pinterest against the Snapchat short. And I thought about closing it before earnings. And the reason I thought about closing it is that you know, Snap is $16 billion and Pinterest is 15 billion and Twitter after its 35% decline is 18.2 billion AV. Yeah, Twitter's growing slower than the other two. But it's like three to four times the revenue base. And you got to kind of adjust for that, when you get to that point.
And you're like, this is a company that is in the advertising space, and it's doing -- it's going to do whatever issues its got, it's going to do 3.5 times what this is going to do and their enterprise values are a hair apart. So when you -- like this wasn't -- this is a case where if you would look at an Invitae, you'd be like, this has got to be like a quarter a fifth of the size of like, even if you are a believer and you're willing to buy into the speculation of a Myriad.
And then the other problem you have with it is that they're interrelated. All the revenue growth that is coming for Invitae is coming because Myriad hasn't come down in pricing. They've been fighting this price decline, because they've had the luxury to fight it as the leader in the space and they're extracting a premium for their testing, because they -- like there's a compelling argument, at least from their end, that based on the data we have in the history, our tests can more accurately predict what you have, as far as a likelihood of a hereditary cancer and indication reliably.
And it's ironic, and we were discussing this when we were working on this, like this company throw shade at who -- I mean, they throw shade at the DTC companies. Like they literally just gave a scientific presentation at this Houston Cancer Conference with Genetics or whatever, just like two weeks ago, where they were like, here's 23andMe's tests, okay, and this is what's wrong with it. Like 23AndMe gives you a BRCA test, that only is designed to detect three variants. Basically, if you're not an Ashkenazi Jew, it's useless.
But it's literally a report that is bundled in with the ancestry, with the health with the 50, 60, 70 reports, you get for $100 okay. It's not like you're going into buy this or you're going to your doctor and you're like, okay, I had breast cancer, I'm worried about a potential recurrence. Let's see family history. Do I need to get a mastectomy early because I have this mutation and that's a good preventative measure, et cetera, et cetera. They're not looking at 23AndMe. Like, it's -- you're competing in the clinical grade medical diagnostics market. But here's this company attacking the DTC companies who are not really their competitors.
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Breaking Down The Invitae Short (Podcast Transcript) - Seeking Alpha
