This Week in Startups - Building a blood-testing startup in 2023 with Vital CEO Vasu Nadella | E1801

Episode Date: September 4, 2023

This Week in Startups is brought to you by… Lemon.io - Hire pre-vetted remote developers, get 15% off your first 4 weeks of developer time at https://Lemon.io/twist OpenPhone. Create business phone numbers for you and your team that work through an app on your smartphone or desktop. TWiST listeners can get an extra 20% off any plan for your first 6 months at openphone.com/twist LinkedIn Jobs. A business is only as strong as its people, and every hire matters. Go to LinkedIn.com/TWIST to post your first job for free. Terms and conditions apply. * Today’s show: Vital Biosciences CEO Vasu Nadella joins Jason to discuss exactly how Vital’s “VitalOne” conducts 50+ blood tests with a small sample of blood (9:16), building investor trust in the wake of past industry failures (18:45), creating accessible care (40:35), and much more! * Time stamps: (0:00) Vital Biosciences CEO and Co-Founder Vasu Nadella joins Jason (1:18) Theranos’ background and what prompted Vasu to pursuit (7:56) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist (9:16) Vasu demos how the VitalOne works, lessons learned on Vital’s journey (18:45) Scaling the company, raising a war chest, building trust in the product, benchmarking and governance for labs (27:36) OpenPhone - Get 20% off your first six months at https://openphone.com/twist (29:07) State of lab robotics, paths for incorporating AI into Vital’s technology, benefits of converging technologies (39:16) LinkedIn Jobs - Post your first job for free at https://linkedin.com/twist (40:35) Creating accessible modern lab testing (45:38) Consumer behavior and the outcome of consumers controlling spend * Check out Vital Bio: https://vitalbio.com FOLLOW Vasu: https://twitter.com/vasunadella * Read LAUNCH Fund 4 Deal Memo: https://www.launch.co/four Apply for Funding: https://www.launch.co/apply Buy ANGEL: https://www.angelthebook.com Great recent interviews: Steve Huffman, Brian Chesky, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland, PrayingForExits, Jenny Lefcourt Check out Jason’s suite of newsletters: https://substack.com/@calacanis * Follow Jason: Twitter: https://twitter.com/jason Instagram: https://www.instagram.com/jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis * Follow TWiST: Substack: https://twistartups.substack.com Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin * Subscribe to the Founder University Podcast: https://www.founder.university/podcast

I think going back to the beginning of your conversation, it's like, where does this, you know, converge with some of the stuff that's coming out now? Yeah. And we get really excited about that, right? If you have the ability to get diagnostics everywhere, what can you build? What do you enable? What can you build on top of that? You know, if you've got the ability to interrogate your body, measure these things all the

time, more frequently, you can plug them into knowledge systems. That's a totally new way to think about, you know, care delivery that just could not have existed until both our hardware existed and some of this AI that you're talking. talking about has existed. So you want to play in that world for sure. This weekend startups is brought to you by lemon.io. Need to speed up your product development without draining your budget. Hire vetted engineers from Europe at lemon.io. Go to lemon.io slash quiz to get 15% off for the first four weeks. Open phone brings your team's business calls, texts, and contacts into one delightful app that works anywhere. Get 20%

percent off your first six months at openphone.com slash twist and LinkedIn jobs. A business is only as strong as its people and every hire matters. Post your first job for free at LinkedIn.com slash twist. All right, listen, Theranos was one of the biggest stories in the history of technology and startups. We had John Kerry Rue on this very podcast right after we broke the story. We were one of the first people to have them on because I knew it was a scam from day one. I figured that out. And then we had them on after the book came out. Those two episodes, some of the most popular and most watch episodes of this week in startups. And there's a reason why this captured everybody's attention. And it was because even though like Elizabeth Holmes was this odd character, fake voice, styling herself

after Steve Jobs and all the lab secrecy, the fake tests, the lawsuits, the backstabbing, all this craziness, all the hundreds of millions of dollars invested and them going to jail for 10 years. It was an incredibly powerful idea. It's one of the best ideas that any of us ever heard. Whatever if you get a bunch of tests done with a small amount of blood. I literally, I'm doing this executive, you know, health coaching thing right now with a startup and they drew my blood. They did no less than 10 vows of my blood to do all these different tests. And It's a painful experience and I'm a tough guy and I don't mind it, but it is a pain in the neck. And then when I, my God, when I have to take my wife or my kids to get blood drawn,

some people will skip these blood tests because they don't like having blood drawn. So if you could do what Elizabeth Holmes, brilliant idea and horrible criminal execution, if you could take that idea and do it without horrible, horrible execution, I think it changes health care forever. And that's the big idea that today's found. who's on the program is going to try to do. And it's an idea that's been out there for 100 years. But I think there is a chance that he's going to succeed.

Vasu, Nadella is the CEO and co-founder of Vital Bioscience's. Welcome to the program, Vasu. Thanks for having me on, Jason. I got it correct, right? VASU is VASU. Yeah, perfect. Perfect. Okay, they have it.

Okay, so you heard my introduction there. And you seem like you're, pretty young. You graduated from college, uh, when? 2014, 2012? I actually didn't finish, so I started in 2012 and I left in 2014. Okay, great. So you and Elizabeth Holmes have something in common. You're both dropouts. I think that's the, hopefully the last, well, and then we're both working in blood testing. Yeah. Yeah. But how did you get drawn to blood testing? Yeah, you know, I think it's a space that I've spent a lot of time thinking about. And, you know, my friends will tell you this. Other investors I spend time with will tell you this. I've been fascinated with

a bunch of companies in this space, whether they're tests for doing things like sepsis detection, at home testing for cancer patients. I've just been enamored with the idea. And I think it comes from having a lot of chronic disease in the family, like seeing my mom, I have to spend a lot of weekends in the lab waiting for results. That's sort of dread that everyone feels when they're waiting for an important lab result that takes days, feeling disempowered, right? Because you're waiting for the physician to call you. And if you don't hear anything, do you just kind of assume you're okay or do you assume you got forgotten? And then a lot of doctors in the family, too, and you kind of hear it on both sides where, you know, they're frustrated that patients don't get

their lab tests. Like you said, it is just a very broken system. But kind of, you know, we get to build in this amazing world, all of this new technology. And I think one of the big things you wonder is everyone kind of agrees that health care sucks. Everyone agrees that we spend too much on administration, that we burn doctors out, that we treat sickness instead of avoiding sickness, and there's a ton of people that fundamentally just don't have access. And so, like, why hasn't there been this sort of like software moment in healthcare? Right.

Why does, why do costs keep going up? Why do you not get really kind of more efficient systems? And so my view on this has always been that you're fundamentally delimited by physical connection there, right? You have to go to the physician. You have to go somewhere, get your blood drawn. Things have to get shipped across the country. And in that world, it's really hard to drive software efficiencies.

So we like to think about this, you know, and we think about vital, not as a blood testing startup. We think about ourselves as a care delivery startup and we're building devices to make care more accessible, ubiquitous, you know, available, empowering. But if you think about all of these things that people are working on, right, they're trying to solve all those problems, whether it's going to your local CVS, going to a minute clinic, and having a really high quality primary care visit, whether it's like telehealth,

I can do more than, you know, just tell you if you have the flu and send a simple prescription over, or like crazy big ideas. Like, we're going to build AI doctors that totally replace the need to ever talk to a real doctor. All of that stuff is going to be rate limited with the current infrastructure on diagnostics.

It just likely won't happen, right? If you have to go take your blood somewhere, ship it across the country, wait days, you're fundamentally not going to enable all this software and all these really great innovations to really have the impact they could have. So that's what we're tackling. We're addressing that.

And I think the first instantiation of that is what you're seeing. It's a vital one. It's a system that lets you get all of your blood tests in 20 minutes at the doctor's office with a small volume of blood. Yeah, that's a quick control house. So let's talk about the, and we'll show the machine here for those of you who are watching at home, if you're listening, will sports cast it. If not, just go search for this week and startups on YouTube. And you can find the video real quick. but how much blood are we talking about here because obviously Elizabeth Holmes

you know held that tiny vial and was on the cover of a magazine and it was going to be like literally a drop of blood which to me seemed laughable that you could actually use that for that many tests so how much blood are we talking about here and then how many tests she was talking about 200 tests or something crazy you just said I think 40 or 50 tests is you know what you think you can do off of what a vial of blood yeah so we're using two different different types of blood, right? The total sample volume we're using about is about 600 micoliter so for context, one of those tubes Jason that was probably drawn from you is 10 milliliters. So we're using less than one tenth of that sample. Oh, wow. And we can run the full gambit.

And so that 600 micololiter is split between two different anticoagulants for two different types of tests. Drops are not, you know, scientific units of measure. They're not standard units, right? So to contextualize, she was trying to do stuff on roughly 100 to 150 microliters. That's what she was calling a drop. So if you take that, and again, it's not a real unit of measure, but 600 micoleters is about six to 10 drops depending on what we're talking about. Imagine this. You got an idea for a tech startup.

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get 15% off the first four weeks what a deal so stop burning money hire developer smarter and visit lemon dot io slash twist easy peasy lemon squeasy at lemon dot io slash twist so let's take a look at this demo here you have a machine and hilariously you know they wouldn't show the edison machine to people. You have a slick looking machine as well, which makes this an incredible parallel. When people come to your office specifically investors, and they see that you're building blood testing and that you have a machine. What's the general reaction? We love doing demos, and we like love to put on a full show where we, like, we did demos in a hotel room a couple weeks ago. We put a camera inside the machine so people have like full custody of their

blood as it was going in and they knew they could watch the blood get tested. Yeah, I think it's one of these things that the bar has just gotten so much higher. And so we get to put ourselves into their shoes and say, like, how do we make sure they feel really comfortable with the technology here? Yeah. So we spend a lot of time before the demo, walking them through how the tech works. And then we spent a bunch of time, yeah, like running the demo, they get their results. And often we tell them what tests we're going to run so they can go, you know, get their

test at Lab Corp request before they fly over to see us. And we compare. and often we're really, really close, right? Because that's the point of a system that can meet the gold standard of lab testing. Right, so here's a beautiful machine with an LED on the front or LCD, whatever, some kind of display. And so the person just picks, I guess, what they're ordering or picks who sample this is and drops it in and the rest of this history. Yeah, exactly. So here, what you're seeing, I have two videos.

So what you're going to see here is a user walk-up. They're going to select the patient. So bi-directional connectivity to EMRs is how we're designing the whole system. They open the drawer. They drop in two tubes. Electronic medical records, EMR, right? Yeah. And these tubes can be microtainers or vacutainers.

So microtainers are a small ones. We've ever done a mail-in test. Those are those tubes. That's how we do the smaller samples. And they put in what's called a disc pack and a support pack. So I'll just kind of walk through what's going on. In the disc pack, or three microfluidic disks. And in the support pack are reagents, mostly about water in this case, or buffer.

and eight disposable tips. So each disk is a different type of test. One of the really big challenges in the space is how do you combine three very different modalities of testing, immunocassays versus hematology, for example, into a single platform. And so we've got this relatively breakthrough, you know, microfluidics platform that lets us use a disk to do these tests, and each disc is designed around that type of test. And on each disc are these freeze-dried reagents, these little liobedes. we like to call them like the same technology behind Dippin Dots, if you will. And that support back, and I told you there's tips and regents.

So just to orient you, this is inside the system. The left-hand side is going to be the drawer coming in, and then you're going to see the discs get moved and the samples on the bottom left here. Right. So what's happening inside the system to run these three very different modalities of tests in parallel is we're actually have three subsystems inside, kind of like three mini DVD players. Each disc gets loaded while we're mixing. and decapping that blood.

So the user never gets exposed to blood. Everything gets done inside the system. There's no pre-analytical error from a poorly mixed sample, for example. We want this to be super easy to use. And yeah, we load up blood. We load up buffer into each disc. Depending on the type of tests, it's going to be EDTA blood, depending on other types of tests, with lithium heparin blood.

And as we load up these disks, they start spinning. So you can see the bottom one spinning there, the one on the left-hand side spinning. I mean, you were right. It looks like it's a CD player that's been opened up or if you had a glass CD player like viewing jail, they have plastic ones where you can see on the inside. It looks like that.

Yeah, we want to do like a limited edition version of the system with clear covers in case people want to watch it, do stuff. I was just going to show what's going on. So on these disks are these channels. I know it's white on white, so let me know if it's hard to see. And these channels, you load up blood and buffer in the center and then you just modulate the acceleration and deceleration of this disk.

And that's what lets you, you know, run. with really high precision and accuracy, all the fluidic kind of processes that you might expect, metering, diluting, aliquotting. And by the time it gets to the end, it mixes with these reagents, as low reagent bees, you can see at the end there. Wow. And that's how we run these tests in parallel. And then I assume the machine cleans itself.

It has some sort of way to make sure that my blood sample and the next persons do not cross-contamined each other, yeah? Yeah, so these are all disposable, right? and we all recycle plastic. So this all comes back out in the tray, and then the user just disposes of this tray. Got it. But you also had those, I guess, you know, eye droppers, essentially,

yeah, the tips. So those are also replaced each time? Those are also replaced, yeah. Got it. So, and it can do that in 20 minutes. The machine's going to cost $50, $150,000. What do you think it would wind up costing? Or do you just give them the machine and charge per test?

We're going to do, yeah, like this is a pretty standard. model and lab testing where people have a minimum volume that they go for. And then based on that minimum volume, will either totally discount the price of the instrument or they'll have a price based on that. This is going to be, you know, there's an opportunity here to be faster, better, cheaper, right? Today, a lot of lab testing, all the demand gets originated by the physician, but it's folks like Laborp Request who, you know, tend to absorb those economics. They're the ones running those tests or the ones that insurance companies pay once they run those tests. So by bringing this to the doctor's office, we actually in a name.

able physicians to run these procedures and bill for them. And that's a huge unlock for them because they can now build for this stuff or absorb those costs if they're in some sort of value-based care arrangement where they're covering the cost of a lab test. So it's designed to be in a doctor's office, not in, yeah, phlebotomist, I guess, is a term, or a lab corp office or something like that. Yeah, we're designed this to sit in every doctor's office, but also what we call all these alternative sites of care. So today, skilled nursing facilities are another good example where there's a lot of Blood draws that they don't have a lab on site to send it out. It's a really painful process in an environment that could really use some of these diagnostics

would enable kind of new applications of telehealth and stuff like that. Pharmacies are another good example. So we think 20 minutes to get your results or as opposed to what's typically multiple days. And so when we when we look at this, what have you figured out here in terms of testing blood quickly that Lab Corpse, which is an investor in your company, I understand. Yeah, LaGrofts and Elizabeth Holmes and Sunny Bawani

didn't figure out. But what have you figured out here? There's a bunch of things. I think there's very specific things that we've figured out from a technology perspective. And then there's some meta lessons that I think have led to success so far.

The specific set of bets that we made are really based around our deep intentionality, but where we place complexity in the system. So a lot of people, people who attempted stuff, Theranos included. But, you know, as you study Theranos, you realize there's actually a half dozen other dead bodies in the space for zombie companies that have raised $100, $200 million as well. And what a lot of these guys got wrong was they

really counted, they placed complexity in the wrong part of the stack. So the good example of this is if you rely on an electrometrical component, like a pipetting head or a gantry, to do everything, to drive all the accuracy and precision that you need to run these tests, over time they'll fail. And actually over time, it's really hard to integrate new tests because you're relying on this system that's actually relatively brittle. And so what we did differently was place all that complexity to drive accuracy and precision into a microfluidic platform. This is disposed of every single time.

So as long as we know how to make this stuff, which, you know, thanks to the many, many DVDs that have been made, you have a whole supply chain here, a lot of know-how and how to mold thin plastic disks, we can leverage that learning and make something that's easily dispose and is going to perform the same way every single time as opposed to something that will drift over the years that you're using it, for example. So that's just one example. I think the meta lessons that we took away from this was just being hyper paranoid at the outset of where the complexity that you're, you know, the decisions you're making

about the architecture of the system lead to from a durability perspective, reliability perspective, and accuracy perspective. There's like a set of lessons there. And then the other is really think about building and platforms. I think people in software do this all the time, like this notion of microservices and really thinking about how to platformize your technology. We did that with our tech as well, where we thought about how do you like make the incremental test much easier than the first test that you built.

And you don't get a lot of credit from investors for this, right? But actually think it's the right way to build some of these harder companies. You need the N plus one to challenge to be easier. And so we spent a lot of time building platform or approaches where, for example, we have a lot of IP around our immunosay that lets us take off-the-shelf antibodies, get them to perform a lot better than their advertised kinetics, because we have a way to take them and get them to fit into our paradigm of a microfluidic, a bowl, assay that sits on a disc that can run in 20 minutes of a small sample. And so when we need to build another test, we can go a lot faster than a traditional company does because we've got this approach, this sort of computational methods around it,

design of experiments around it that let us put that onto our system a lot faster. So going slower, making sure you got a strong foundation, that the accuracy is there, and that, you know, scaling will happen if you have the right platform built, which is the reason probably you raised a war chest of $48 million. Was that one round out of the gate you raised that, or is that in total for the company? No, that's in total. So that's over several rounds. I think the simplest way to put this is like you have to sharpen your axe before you start chopping down trees.

And you will never converge on a on a time scale that makes sense for venture cost of capital. If you if every new asset in our case or any new thing and any kind of deep tech company is a totally new challenge. Like you just never really scale fast enough. Well, and that is I guess you started in 2019, 2020 sometimes. So you've been out of for three or four years. Yeah. Just over four years old. but the product's not in market yet.

So you had to have very patient investors and then hit some sort of milestones that you explained to them made you worthy of future investment, correct? Yeah. And you have to like any company like this, you have to break this down into like, you know, here are the incremental steps that de-risk the company over time. In the beginning, a lot of them are technical, right? Like, can we do this many tests at once? So the first demo of the system that you saw was actually like using another company's pipetting robot. and our subsystems inside it. And then it turned, or actually even before that, it was my co-founder

pretending to be the robot by just showing that you could run these things in parallel. And so you have to kind of set these markers yourself, convince investors that they're meaningful, convince investors that you paid down a lot of risk as it results in being able to do those things. And then, yeah, go raise to hit that next milestone. So we're finally at the stage now where I think we're going to raise another round of capital soon. And that's really going to orient us to fund all the way through to commercial through the FDA.

So we'll pay down the regular. risk and getting to some of that early commercial risk. And you want to have this in market or in testing in 2024, correct? Yeah, we'll be in clinical studies, uh, it's where it's like the back half of 2024 and then in market in 2025. Amazing. Uh, and then, uh, how long does the FDA take to clear this and does the history of what happened with thereinose impact you?

In other words, but in your discussions with them, are they like, yeah, that was, like a very unique one-off and we understand like you're not that and they're kind of rooting for you or is it just like they're like we can't and in fairness I guess they did do their job they're the heroes of the there are no story so I guess they're just telling you like hey we got a process follow the process and everything's good what's the interaction like there post-theranos all of our interactions at the FDA have actually been super positive they've brought kind of more people than they needed to they've spent a lot more time helping us understand what they'd want to see. What's awesome is when you want to follow the rules, the rules are actually really,

really kind of obvious and they're available for you to look at. So you can look at guidelines. You can look at, in our case, predicate instruments and see how they prove to the FDA, they're meeting this performance bar and basically show the tell the FDA, hey, I'm going to do the same thing that this other company did. Are you good with that? Are there any new risks that you're seeing as a result of our use case or our instrument? Here's what we're seeing. Here's what we'll test. So we're doing all that work now. We're talking to the FDA, getting a ton of clarity there. But 80 to 90% of it, you can do before we talk to the FDA just by looking at, you know, how they approved, or sorry, cleared other devices. Yeah.

I mean, it's interesting in our industry where people want to ask for, you know, beg for forgiveness instead of asking for permission. Totally. This is fine if you're doing SaaS software. It's totally fine if you'd like to make, you know, an electric go-kart that you're the only person driving. But at a certain point, when the public touches things, the playbooks are. there. So if you're making NFTs or some cryptocurrency for you and your friends, that's fine. If you want to sell 100 million of it, you probably want to look at the SEC's rules. Yeah. It might be security. Yeah. Just maybe if they expected it to go up in value, yada, yada,

how we test here. And it's, I think for certain people who are entrepreneurs, I think they have taken the approach of, well, Airbnb broke the rules or this company broke the rules or Uber broke the rules, whoever, DoorDash put in and out burger on the thing. Putting in an out

burger on a door dash or, you know, a postmates app without their permission, going there and picking up and delivering it, I could send my assistant

to go pick up in and out burgers for everybody. It is no harm no foul. Yeah. Blood test, cryptocurrency, people's savings,

you know what you're doing's wrong, you know, in those cases if you're bending the rules, huh? I totally agree. I think, you know,

there, there's never a perfect system. Like in our space, you could argue that there could have been a lot more innovation if this was an easier process or the bar was lower. But you're totally right. Are you talking about people's health, people's, you know, well-being? And that bar should be at the right level to make sure everyone's safe. I think we've always invited that bar. And, you know, what's awesome is the FDA at positive reaction. They want to help us through this. And we've been having more conversations with them as we make more progress and want to show them more stuff. So yeah, it's been

good so far. I mean, the thing that I took from our first part of a conversation here is that you said, you told people to get their blood test done before going to yours and then comparing the results. Yeah. And, you know, there's a famous individual Jean-Louis Gassier, and

he worked for Steve Jobs. He ran Apple in France, I believe. Yeah, I read his blog. Yeah, it's cool. You read his blog post, right? And there was this famous Theranos trouble, a first person account, where he and his Monday note essentially said, you know, he started emailing Elizabeth and other people who he knew at Phaeranos and their investors like,

hey, I got to test at Stanford. I'm an old dude who, you know, like my blood test matter. And yeah, what did he test again? It was hematurcrit and platelets, I think. Yeah, I can't remember. Yeah, and it was just completely off. Yeah. So platelets is one that's notorious for the different.

between capillary, which is from a finger stick or, you know, from a shoulder versus Venus, platelets is notorious for dropping because your blood, you know, tends to not want to leave your body. And so you clawed and you coagulate and your platelets drop as a result of that. So, yeah, it makes sense that the method that they had didn't work for platelets at all. Ematicrit, you know, that one typically isn't as off, but it doesn't look like it was that bad. There was really platelets was a really bad one. Yeah, and so how do you look at your benchmarking now? And is it true that all lab tests have significant variability or non, you know, or significant

or maybe even more than significant variability? And should we all be getting our blood tested from two different labs and comparing them? No, that's probably overkill. That's overkill. The things that every single test has a different kind of bar, right? So some tests have very, very tight ranges. And being outside of that range can mean life or death. Other tests have very wide ranges.

And so between all this, like the clinical chemistry community and a whole bunch of other groups have come out with, you know, what are guidelines? And so Clea is one of the big groups that governs this stuff, governs labs. And they have their own guidelines for the total allowable error that you should be getting on an instrument. We can use those guidelines and be like, cool, we're going to hit that bar. It's the highest bar that's out there. And so all of our tests are designed to fall within the total lawable error based on a lot of these guidelines.

Where those guidelines don't exist were for a handful of tests, they haven't developed them yet, you go and look at predicate instruments. And typically those predicate instruments are developed around some philosophy. Like you're going to use this test to diagnose X or prevent Y. And therefore, they'll come up with that and defend that to the FDA. And that sort of becomes the gold standard. And you fit into that paradigm. So you have two paths, right?

And these things converge really quickly. like what isn't a guideline eventually becomes a guideline and it's pretty standard. What we've done, I think that no one else has really done in this space is just put our data up on our website so you can go look at it. Vidalbio.com slash data. We ask for your email so we can bug you later if you're a potential customer that we can get feedback from. But other than that, it's all we ask for.

And we want you to see our data. We want you to see where we're not performing yet on some tests that we're going to tighten up over the next couple weeks and we'll update our data set as a result of that. And all that data is coming off of real samples comparing to gold standard lab instruments that are out there, typically a Roche instrument or Sismex instrument. Are you still using your personal phone number for your startup? It's 2023. It's time to stop. It is a huge mistake that founders make.

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we see robotics in the world, you know, people building cars in factories or we have an investment in CafeX, you know, moving coffee cups around to make perfect. you know, Boba and coffees and, you know, foam and ice, and it's just incredible to watch. But it's been advancing. Labrobot, laboratory robots is a distinct subset of robotics. And you were saying, hey, you did an interesting thing where you had your co-founder doing it manually with the understanding, hey, robots are going to do this. What is the state of robotics in these laboratories? Is it, it seems like that's such a constrained, narrow use of robotics. Has it essentially been perfected and reliable? And you can, you can,

can very quickly and easily program a robot to do what is necessary, or is there still a lot of iteration that still needs to occur in laboratory robotics? I think it's massively sophisticated. If you go to some of these trade shows, a lot of the vendors that are robotics or automation companies, like really big companies, you may have heard of like Festo or T-Can or Hamilton, they sell a lot, right? And there's startups, too, like OpenTrons that did really well through COVID scaling their robotic lines.

I think it's, I think like almost every major lab, right, in North America has probably some of the most sophisticated robotics you've seen. And they've vertically integrated in a lot of ways too. Like the coming that sells you the machine also, you know, typically now offers an automation solution. It's a good, it's a good marker for what's different than, you know, 10 years ago or 20 years ago that makes a lot of this stuff possible. Like, you can go on Amazon today and for $100 by a relatively sophisticated 3D printer that's

got pretty good precision, right? And because of things like that, you can now have instruments that, you know, sit on your counter and also do blood tests using the same similar type of supply chain. So it's a lot of, a lot of things like that. Those little gears that move the, what I call the eyedropper around, that is a descendant of all of those 3D printer hackers, you know, making little ornaments or trinkets in their 3D printers over the holidays. If you look at our platform, we are taking advantage of supply chain and know-how from the billions of DVDs and Blu-rays that were made from advancements in gantries, from advancements in cell phone technology. Like the image sensor that we use is a cell phone image sensor, cell phone lens, right?

You bring the cost down. You can bring the size down. You get a lot of this stuff kind of more off the shelf. And then on the other side, like maybe less, you know, obvious to consumers, but like nanoparticle technology, quantum dot technology, a lot of that stuff is cheaper too. And that's how you can make these assays more sensitive and more sophisticated in a format that fits under microfluidic and you could have before. So I think a lot of this stuff is now just now possible. It is really interesting what happened because of the video game, you know, GPUs and cell phone technology. I mean, cell phone technology is now impacting desktop computer technology.

The convergence is incredible. The cameras on your phone are more sophisticated than your desktop cameras. camera. So now, like laptops and desktops are kind of borrowing from those advances. AI hasn't come up yet in our discussion because what you're doing is trying to be incredibly precise. You're not asking some AI to figure things out for you. Is there some AI angle here that will eventually emerge or is what you're doing just incredibly finite and precise that you don't want AI getting in there and guessing and making its best guess, as it were. As impressive as the guesses can be in AI.

Yeah. Look, a lot of the DNA of the team comes from AI and optics and machine learning. So we are not afraid of that stuff. We use a lot of those techniques on the kind of the design side of things to speed up progress. But as far as the instrument goes, there's a ton of computer vision. We aren't using, you know, what you may see in like a Tesla for self-driving where it's learning all the time. those things tend to be tougher with the FDA, right? You want to understand how those algorithms work.

Most of the time, we can't explain how, like, a really large LLM works yet. Like, it's like cutting out stuff to be able to explain that stuff. So we want... I mean, that's, I mean, say more about that. Like, you have these, you know, tensors set up and it's making its best guess. And then you ask Sam or, you know, Greg, whoever, like, hey, how does this actually work? And it's like, yeah, well, we trained it and then stuff comes out. And, okay, but how does it work?

Totally. And he's like... Yeah, yeah. It's a borderline philosophy at this point. Like, it is a very, very hard problem. Yeah, explainability, I think, is a massive problem in AI. The FDA actually has a ton of guidance around systems that are built around this type of thing in particular on the AI side. We have enough with the FDA to deal with, and we have a pretty clear path with the standard of feature diagnostic pathway.

So we're staying out of that lane. We don't need it. You know, we can do the old school computer vision stuff and get really far with it. And we can explain it and understand it and tune it in ways that we fully get. That being said, I think going back to the beginning of our conversation, it's like, where does this, you know, converge with some of the stuff that's coming out now? Yeah. And we get really excited about that, right? If you have the ability to get diagnostics everywhere, what can you build?

What do you enable? What can you build on top of that? You know, if you've got the ability to interrogate your body, measure these things all the time, more frequently, and you can plug them into knowledge systems, that's a totally new way to think about, you know, care delivery. That just could not have existed until both our hardware existed. and some of this AI that you're talking about has existed. So we want to play in that world for sure. I was just reading somebody had taken one of these, you know, MRI type scans, pre-nova, whatever.

And they had like a nodule or something on their thyroid, something like, you know, not super concerning. But then this person was going back every year. And then they had like three years and the nodule had grown a little bit. And the person went to Stanford or Harvard or whatever and said, hey, how many people do you know who are in like the first two years of a nodule growing and cancer on a thyroid? And they're like, well, we don't have any patients like that.

We have no data. And he's like, I'll be your first. Yeah. And now like you think about how reactive medicine is and healthcare as opposed to, you know, maybe thinking about these things in real time. We're recording our sleep and our heart rate. But man, we could be actually knowing what's happening. in the body in real time or close to real time. And listen, yearly scans is real time as far as

the answer goes. Forget about if this became a daily thing where your body was on the daily basis giving blood or a weekly. I mean, it seems like science fiction, but a weekly blood draw and understanding the changes in it could revolutionize medicine. It's a space we're excited to work in. I think, you know, the current state of lab testing is like living in a world where you take a picture with your phone and then you have to wait a week to see what the picture was. Like that's kind of the world that you live in today, right? And today we can order a pizza and it's like here in 15 to 20 minutes. Why is lab testing not like that?

So we're totally excited about that. I think a lot of what we have built and designed with the Vital One is to enable a platform that can one day go in the home. So a lot of the IP that we have is how do you use cell phone technologies and really cheap technologies that have kind of scaled with the economies of, you know, those types of supply chains. They're like at the limit, I think, of vital as this company that is really trying to build something like a systems biologist for everyone. Like, can we give you the ability to measure and understand yourself and then plug that into

these systems that keep you healthy, right? Rather than treat sickness, to your point of like, you know, you kind of wait until this is either a tumor or it's not, that we're worried about it or not. how do you get to a place where there's a system kind of monitoring you, keeping healthy? And like, less so even for us, like, that's what we want for our loved ones. Like, that's the anxiety that we have to have with our parents or grandparents. Well, and imagine when these systems start converging. And that's the thing.

You know, I am in a very, very privileged position to have incredible founders like yourself on this program. And, you know, you look at Prinovo and they're over here, you know, making the skins. And then what you're doing. And there are people who are making models of the heart. and people who are doing stuff with the brain. And then there's the quantified self. You know, there's whoop and Apple watches and sleep and ate sleep. And then there's nutrition and there's gut biome.

And nobody's taking all of this into a Manhattan project-like project where if we had but a thousand, you know, people commit to doing whatever, quarterly, monthly blood tests, pre-novost scans. And we said, hey, let's hire. And this would be something that a university could do. they said, hey, you know what, let's put a team on this to take the pronovostan, to take your blood test, to take all these other quantified self things, put it together. Right. And then let's see where the path with these, what do they call the long studies that people do?

Longitudinal. Yeah, longitudinal studies and say, let's do one of these, but with these new tools. And the new tools are sitting there. They're waiting for somebody to, you know, know everybody's glucose level combined with, you know, other, you know, real time glucose and everything. And we might figure some things out. And that's where AI could come in and start looking at the results and saying, hey, you know, heart rate variability. You know, there's just so many different concepts here. Yeah, this is one of the things I was excited about.

Like, I thought Verily was working on something like this. I think maybe they shut it down or they were doing something in this vein. You know, combine that with, you know, full genome sequencing, all the other stuff happening in that world. Yeah, no, totally. I hope someone works on that. I think we're going to try to do our best from our angle on the long diagnostic side. But the end state vision we want to build is what you're describing. Like this systems biologists that's keeping you healthy.

To do that, you have to learn from a bunch of data that today does not exist. Creating a job and finding qualified candidates. It's so time-consuming. Don't I know it? I'm trying to add five positions right now because things are going so well at the launch fund. But you know what? I have a secret weapon and I'm going to share it with you. Lincoln Jobs.

They're about to hit a billion users over at LinkedIn. So just think about all the insanely qualified people that are there looking for work. You just go post your role on LinkedIn and you will be 100% certain that you got access to the most qualified candidates. And guess what? First one's on us. That's right. First drinks on us. Go to LinkedIn.com slash twist and post your first job for free.

You got nothing to lose. And that will give you that purple ring on your profile. You see that? Everybody's got the purple ring now. that means everybody in your network knows you're hiring, they click on it, and you'll get those friends of friends, right? Those are the really high quality leads that you want applying to your job because there's someone in your network who can vet them. So I did that for launch and I do it for inside and we found so many amazing people at our company. When you think LinkedIn jobs,

I want you to think better candidates faster. Let me say that one more time, better candidates faster. LinkedIn jobs will help you find the qualified candidates you want to talk to faster. Post your job for free at LinkedIn.com slash twist. That's LinkedIn. dot com slash twist to post your job for free terms and conditions to apply. You know what it's like is like you have all these mutants with this like superpowers around the world and there's no professor X saying like, hey, let's get all the mutants together and put them on the same team. And let's see what these crazy mutants, you know, can they save the world, right?

And where's the Avengers or X-Men of the space? They're all fighting different battles alone. And what the Justice League taught us or the X-Men taught us is when you work together as a team, you might be able to go further. And that's really like, somebody out there who's listening to this has got, you know, an extra couple of billion dollars laying around.

And, you know, there's a few people going after that one. No, I think it's going to happen. But look, I don't think the hardware is there yet. Like, you know, to your point, for Nuvo is still like a $2,000 thing. Yeah. We're working on the lab testing side. This stuff has to come down the cost curve in order to enable that future. It's another

one of those ideas. I think you said this at the beginning of our call, right? It's another kind of extremely the obvious thing that's just super hard, but hopefully it gets easier with the stuff like this. Yeah, I feel like we're at a certain tipping point here with what happened with the cell phone revolution, what happened with accumulating the world Zeta online and the sensors, robotics, AI, all of this is in like a crescendo. And, you know, there's somebody who needs to be the conductor of this, you know, and there's no conductor, but it is a crescendo and all of this music is coming together.

and you know what happens in the next decade I think is going to be truly truly mind-blowing because I don't think people understand the how quickly stuff is compounding right and you get to see it yeah and when you see it up close and personal I think it's something that Tim Urban talks about a lot is you know exponential is just super hard for humans to comprehend exponential change yeah I think the only people who really know what this is like are the super wealthy that have really, really like high-end concierge doctors who do get this type of care, right? They're being constantly monitored.

They get every single test under the sun. And, you know, they tend to be healthier and they tend to live longer as a result of that. It's interesting. I literally am now moving into this myself. And I am working with a company called Fount.com. Yeah. If you know them. And this is like a world-class theme of performance and longevity folks.

And I literally just did my own. onboarding today. I did my blood tests last week. And I am in the process of just saying, you know what? I like to drive a Model Y. Some people like to drive the Model X. It's a $50,000 car versus $150,000 car, right? If you get it loaded. Yeah. I don't mind flying coach, you know, for certain flights. I'd rather put my money into like maybe making myself optimally perform. And I this like found out bio is not cheap, but it's also not absurdly expensive. A coal plunge, infrared sauna, nutritionist, you know, it sounds crazy to invest $25,000 a year. I understand if you were a firefighter or a teacher to spend $25,000 on your health,

sounds crazy. But like we're talking about, the stuff, the people who do spend the 25K or 50K on their healthy year, and I know people spending 250, you know, Peter Atia is not cheap. My understanding is that's like a quarter million dollars a year or a half million dollars a year to be his patient. That's what I heard. that's coming down the price curve. And with services like Foundup Bio, Pronova, all this stuff, I think it's eventually going to be $2,500 a year.

Yeah. And that's really... Super accessible is going to be the key. And then hopefully the lessons, you know, are open sourced, right? Like, you're a founder. You listen to This Week in startups when you're in high school,

you told me before this made me feel old. Yeah, that's right. But that was 10 years ago? I guess. A little bit more than 10, but yeah. Because I've been doing it for 13 or 14, so you must have been listening in the first year or two of the pod. Yeah.

But founder advice used to be this like hidden resource. And then this weekend startups, Y Combinator, you know, Fred Wilson, Bill Gurley blogging. Now it's become like, oh yeah, the playbooks are out there. There's a lot of knowledge. I think that's going to happen in healthcare.

You know, like the knowledge is going to be released into the wild. and people will be able to optimize even and take control of your health care, right? Like, there's a, there's a massive, like, category, to your point about how this wasn't even a thing, right? Like, start a podcast, startup advice. Like, there's a whole category, I think, in consumer electronics and broadly, like, even healthcare

that has not been built yet, like, per new vital, where I think we're all like the kind of first, first members in this, but there, I think this stuff will look very, very different the way, you know, 2008 didn't, you know, felt very different. Yes. does today and everything it looks looks and feels so much more different than it did even 15 years ago yeah i think it's going to be the same thing 15 years from from today in health care consumer health care and then probably consumer driven health care consumers need to take control of

this huh that's you think that's a key piece to it if consumers are in control of their spend and if they have options to buy stuff and maybe route around their doctor make some decisions for themselves because the doctor patient relationship seems like so broken to me. Like I go when something's hurting as opposed to I'm doing research online and I I would love to just have a service where I could pay by the minute to just talk to three doctors

simultaneously ask three of them the same question. And yeah, but like I could just say, hey, I'm thinking about doing this tart cherry juice. I've been looking at tart cherry juice and, you know, it's supposed to be great for,

there's all these studies on tart cherry juice. I'll just leave it at that. You can do your own research. I mean, and then there's people, who make it, who make it like cold pressed and then it's like incredibly good for inflammation, antioxidants, all this stuff. So I'm down the rabbit hole on this.

I'd like to talk to three people about that. How do we talk to them? How do I pay somebody $100 to have a conversation for 20 minutes about cherry juice? I don't. It doesn't exist except for podcasts. Tim Ferriss or Huberman or whoever, Joe Rogan, you know? There's something really interesting about what you said. I think all these models are looking like they're going to be successful.

I know it's still early days. All of them kind of started with the patient experience first. first. And they focused on nailing that. And then they solved for physicians. It's like this sort of second category, making it make sense economically and motivating them, making sure the incentives lined up, right, giving them, giving them an opportunity to contribute to this. And then it was like insurance was last, right? And so you've got direct primary care, one medical, all this stuff. Insurance is a last kind of consideration there, even though they ultimately have to be the ones who pay for this. You solve for all these other things.

I think that's going to be a trend. And, you know, at the end of the day with with making lab testing more accessible. We know that we're going to work with physicians who care about the patient experience before we work with physicians who don't. And physicians who don't are the dying breed here, right? They're the folks who are probably later in their career and they're not going to be around much longer because of how much of care is moving to this value-based care model where you have to worry about this stuff and you have to consider it and you have to think about how you design your care delivery experience around making sure that patient gets healthier or stays healthy. in order to meet, you know, your incentives line up.

Yeah, I think I totally agree with you. Yeah. The one thing I think is people understanding the cost because we, um, part of consumerism, when we think about capitalism and consumer and consumer behavior is there's a cost curve, right? And you have people who are like, I'm going to buy a Tesla first, right? I'm going to be the first person up the hell. I'm going to overpay for it.

I'll get the roads through. They get the group of people who will take the model S. And then eventually it just, you know, makes its way down. But if you don't understand the cost, and the cost has been obscurified and it's opaque, and I'm paying a copay, and then there's no menu. Like, there's no menu when you go to the doctor. I go, they tell me $25. I don't know what I'm paying $25 for it.

It's like, oh, that's your visit. Okay, but what is everything else cost? Yeah. And that's where it could become very powerful. And then if you could shop, like, when I got my meniscus, I supposedly tore my meniscus. They opened me up. Oh, geez. Meniscus in my knee wasn't actually torn.

And they're like, yeah, we just cleaned a little crop, but it wasn't. I'm like, how much of that cost? Or like, oh, $26,000 in New York, you know, 15 years ago. Yeah. And I got it done. And I'm like, that's expensive. That's expensive. I'm like, what is it normally?

And then like people are getting meniscus surgery for 6,000 or 2,000. And you know who actually price compares and looks at outputs? You know what category of surgery? Plastic. Exactly. Yeah. People go to Mexico. People go to Korea.

People go to Turkey. They go all different places. So if you want to get your nose done or you're trying to get augmentation or getting your teeth done, because that's not covered, you find the best person at the best price. And that's why tourism has carried out. And then there are people going to South Korea, specifically women, who are getting better outcomes at incredible prices. And it's created a category called surgery tourism or something or plastic surgery tourism. Medical tourism. that's it, you got it.

And that's what we need in the United States. Yeah, the market around this stuff. You know, I think like the big thing here is hospitals, maybe I shouldn't say it that way, but the you want to go to people and you kind of want to know what they stand for, right? You want to go to mail and be like, I'm going to pay top coin and it's going to be so expensive, but it's going to be the best care, right? This monument to medicine is going to give me the absolute best care. And then you want the opportunity to go somewhere else.

and be like, I know I'm going to pay $100. It's going to be just what I need. But it's going to get the job done. Like, I don't think we have that. There's a total lack of transparency right now. What you describe is what, you know, marketers do and product people do naturally. Right. Hey, you could stay at the Amman Hotel.

It's 1,500 to 2,500 a night. Yeah. But you don't leave the resort. It's so good. You just want to stay there for three days and spend $6,000 staying in a resort and you never leave. Yeah. And then other people are like, you know what? I'm staying at an onsen in Japan. I'm paying $100 a night. I'm doing an Airbnb.

I'm staying at this, you know, whatever. When I go to Japan, I don't, I mean, I have stayed at the Amman, but, you know, I like to stay in an apartment, you know, like so I have in Naseco, like an apartment place. I can get an apartment and, you know, have my own, you know, whatever, kitchen. So people can then make those choices and it's because of competition, price, value. And some people like value, right? There's brands that are based on value. the W Hotel was one, Pip, there's a new one called Citizen M.

I stayed out in Miami. Have you seen Citizen M hotels? I haven't, no. Citizen M hotels. It's like the new W. Your room is tiny. It's super cheap. Like 150, 250 bucks cheap

in the hottest neighborhood in Miami. That's pretty good. Come downstairs. You can stay in Brickle for 200 bucks a night. Now your room is tiny. It doesn't, you know, have like, you're not going to hang out in your room.

Who's going to Miami? me to hang out of their room. You want to be on the shit. You want to be out. And then they have a great floor with like a cafeteria type set up with desks and co-working. Yeah. Brilliant, right?

And I stay there. I'm not cost conscious. I can stay wherever I want. I like the vibes. Yeah. I got to look into this. I'm a founder, Jason. So I'm staying like like, like Kinta holiday and express.

No, that. There's a whole category of like what we're talking about value. So like Ace Hotel in New York. I stay at a place called Ace Hotel in New York. $200, $300 a night. Got a cool downstairs vibe. It's in like the 20s, like Broadway and 28th or something. Yeah, 24th.

It's super hip. I go downstairs. I get recognized. So, all internet people. There's a cool restaurant. Yeah. So great.

And so I'm just the master of like the value. Yeah. Mint. Like, you know, I don't fly private. I could afford to fly private once in a while if I wanted to. I take JetBlue Mint.

Have you ever taken Jet Blu Mint? Like on the business class tip? Oh. Yeah. That's worth when you get your next round. Canadians are stuck with their Canada. It's brutal. Yeah.

Are you based in Canada? No, you're not based on Canada. Yeah, we're out of Toronto. We're at a couple of warehouses in Mississauga, which is just outside of Toronto. Are you based out of Toronto because you couldn't get visas to the U.S. and it was too hard? No, no, nothing like that. Yeah. No, I'm dealing with a lot of founders who can't get into the U.S. right now.

and then your insane prime minister and everybody up there is like if you get kicked out of the U.S., your H1BVs is no good, we'll take you for 10 years. Yeah. America is killing itself. These great entrepreneurs who want to come here for funding, go to YC, go to launch, accelerator, whatever.

They're like, ah, can't get in. I'm going to go to, I'll put my company in Toronto, Vancouver. Yeah, if you've got any biochemists, hardware engineers, firmware engineers, they're listening. Hit us up. You're in Toronto, you said? We're in Toronto, yeah, we're hiring.

I mean, what a city. I mean, poof, great. Great coffee, too. A little expensive. It's got an expensive, Toronto. Yeah, you're America. Your dollar goes a lot. Well, I think it's the,

what's expensive there is housing, yeah? Housing is expensive, but, you know, it's getting better. It's getting better. It's getting better. Listen, continued success. Cannot wait in 2025 to absolutely use your machine and get my blood done more regularly

and continue success. You guys are hiring. I understand. yeah? Yes, sir. Definitely. Where can they go to find out more? Firmware engineers.

VitalBio.com slash career. So if you're biochemist, firm or engineer, we're hiring just generally across software as well. So yeah. firmware engineer. That's a legit position. We need to do the firmware on this machine.

Legit. All right, listen, we'll see you all next time on this week starts. Bye-bye.