Thirst Is a Lagging Indicator

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And welcome back to the Tacos and Tech podcast. I'm your host, Neal Bloom. I'm so thrilled to have on longtime friend and founder here in the startup community, Dr. Debbie Chen, founder and CEO of Hydrostasis. Hey Debbie, thanks for being on the pod.

Hey Neal, thanks for having me.

Of course. Feels like it's about time for how long we've known each other. And, uh, I'm excited to converse together, especially coming off a recent fun wearables roundtable we did in person with a whole bunch of different wearable founders. So thanks for joining on here. Do you wanna—

Yeah, that was, that was super fun. I, I love getting together and just like talking shop with hardware people.

Yeah, totally. Hardware people who, you know, there was, I could feel some fun tension in that room. There was like the purists, like FDA only.

Yes.

There was the, oh, there's so many other routes. Beyond to go around FDA. Then there was the, what is the right data? What is the right sensor? You know, like it was, it was like a good, like healthy tension, I felt like.

Yeah. Well, that's, that's where the growth is, right? In the tension.

Totally. I loved it.

Yeah.

Well, why don't you give us a quick high level? What is Hydrostasis?

Yeah, so Hydrostasis builds personalized and real-time actionable hydration monitoring devices. Our first and second product is the Gecko Watch 1 and 2, and we are aiming for to be able to give older adults an opportunity to have preventative action for dehydration mainly. So yeah, super excited to be on and chat more about hydration. Awesome.

I'm excited to chat and just hear the story. From where, where it started to where it's gone. Cuz even hearing you say older adults, I know was not always the original case considering I signed up and got, you know, the one of the first V1s. Uh, yeah, I'm not, I hope I'm not in that older adult population that, that is not, not yet.

Not yet.

But actually it's, it's, you know, younger, older. Yeah.

Hey, every day I'm closer to that. That's for sure.

I'm pretty sure we're in the same age bracket.

Oh, good. So we can use it on our That's always the best way to test as a founder. Well, how'd you get started in this? Because obviously, I'm guessing you weren't born— we were all born before wearables existed of what we think they are today.

I was born before the internet, Neal.

Yeah. So there was a different kind of monitoring that was happening back then. Human monitoring, that's for sure. And did you pass out? That's, that's one way of monitoring, right? Are you sweating? What is the color of your urine right now? You know, hydration monitoring has evolved a little bit, but actually not a ton, I would imagine, which I'm excited to learn kind of the history of that. So take us through it. Like, when did you really get excited to just go down this path of, of, you know, changing the game for health monitoring?

Yeah. Um, so I don't know if you've heard my, you know, previous career, I guess, in amateur Muay Thai fighting. Um, but yeah, so I used to fight in real rings and punch people's faces and they punch me back. So that's really how I started. I, uh, trained, uh, really hard, you know, 6 days a week, sometimes twice a day. And I used to cramp all the time, and I was so super frustrated when my coach would always just tell me to drink more water or eat a banana, right? It's like, okay, I'm already cramping, it's already too late. Like, you know, so I got pretty frustrated there and just trying to figure out my own training and my own hydration. Um, and then so that I didn't do anything with that, right? But then after a few years, I actually had my own health crisis surrounding dehydration. Mm-hmm. Uh, and again, like frustrated that there's a lack of preventative information, right? So then I'm like, man, well, like maybe I should do something about this. Um, so my background is actually in academia. So I, I, you know, did my PhD at Tufts University in, in biomedical engineering. Then came back to UCSD. I did my undergrad at UCSD in biomedical engineering as well. Boston's too cold for me, so I came back to San Diego, did 2 postdocs, first at the medical school at UCSD and then at Scripps Oceanography. So I thought my whole career was going to be academic science. I love science, I love experiments. And then I realized a lot of the things that are in academic science do not see the light of day. Taking nothing away from the amazing science that's happening, I was like, man, I wonder if I could actually do something and in my lifetime make a difference, you know, in like put out a product and see it work. So that's really kind of, you know, self, you know, hope that there was something that I could do for myself. But also just like seeing something, uh, an idea You know, being actually put into the world was, was a driving factor as well.

So you wanted to go from getting physically punched in the face to emotionally as a founder, is what you're saying?

Yes, yes, 100%. So they always say like, oh, founders know how to get punched and get back up. And I'm like, yes, true. Yeah.

You happen to know how to do it in all different sort of ways.

Yeah, it's a really great way for founders to get out of their, you know, whatever it is that they're working on. So I always have to just lay down everything when I get to the gym, go do the punching and the kicking, and then I'm like all refreshed and none of my problems are problems anymore and I head back to work.

So. True.

So How would you— I mean, there's a big jump from being, you know, an academic and advancing research to actually going kind of the entrepreneurial path. Like, when was that even a thought that that was a path that you would change from academia to entrepreneurship?

Yeah. So, I mean, I was so lucky to, you know, meet my very first mentors and your dear friends of Alison Lampertine and Vidya Dhanamani and Sylvia Ma. And those were the 3 first mentors that I've ever met. And man, like, I'm so lucky, right? Because, like, they— the 3 of them basically convinced me that I could do it, which is like, you know, at the time, I don't know if you saw our first pitches, uh, back in, uh, at Astro Days, like, they were rough, you know. And, um, you know, and so I am just very thankful. Actually, before at Astro, I did, um, uh, Hera Labs, uh, from Stella Foundation, and So yeah, just a few of those really sort of got me going and I knew it was an interesting technology to develop, but I didn't know it could be a business. And so that's kind of when I started learning the business side of things.

I think I'm trying to think back when I heard your first pitch. Tell me if I'm right or wrong.

It's okay.

You can forget about that one.

No, no, no. I wanna, 'cause I love rooting it. Do you remember, were you at the event where we had Arlan Hamilton in town? And do you know Arlen?

Do you remember her? I believe so. Yeah. I've seen her in person at least once, and I'm wondering if we're talking about the same event.

It was at, it was like in Little Italy at that coworking space.

Yeah, I was there.

Yeah.

Okay.

That's when I think I saw you give your first pitch, like 2017, '18, '19 timeframe. I don't know. Maybe.

Yeah, probably '18, '19. Yeah.

Yep. There was a group of us who invested in Arlen's fund. And so we said, and she's like, whoa, there was like 20+ people who invested in her fund as a group of San Diegans. So she's like, I'm coming to San Diego and I'm doing a founder pitch day. And I think that's when we met.

Oh, I didn't know that's how that happened. That's so cool. I love that.

Yeah. Well, I'm glad that's how we originally met through Arlan and through obviously Allison, who was my first investor in my first startup as well too.

That's awesome.

What's, I mean, there's a big difference between doing the pitch routes, the pitch scenes versus building a product, building a hardware. Like what were the first steps to be like, hmm, How do I actually put something on the wrist? Or was that even the original idea? Like, what was the original idea to actually measure?

And so after our very first prototypes on the bicep, we moved it to the wrist, which, you know, there's different locations and different, you know, challenges with each location. And so we really had to say, okay, well, if we can show it on the wrist, then we can integrate with the wrist devices, right? So yeah, that's kind of one of the reasons why we moved.

Interesting. We had heard from that wearable roundtable we were talking about Uh, someone talked— one of the early investors in Oura was there— talked about how we had to wait for wearables to actually be cool from like a jewelry perspective for it to actually take on. Did it feel that way even on the wrists? Like, I mean, I've never seen something cool on the bicep, that's for sure. Do you think, uh, we could enter somewhere where, uh, things will be cool besides just rings and wrists?

Yeah, I mean, there's, there's other devices, right? Like the, the earring ones, and there's like the necklace ones and things like that. I think the wearable world is just trying to get people to wear it, right? If you're not wearing it, you're not measuring anything. And, you know, if you're wearing it, it might as well look good, right? So like the Whoop just came out with their sort of high-end version with like the, you know, the high-end, uh, devices, but underneath the sensor is still, you know, the Whoop sensor, but it just looks pretty, right? And then of course Oura looks really nice and looks pretty, so people are going to wear it If it looks good. If it's really ugly, then no one's gonna wear it. So I think that's the, that's the, the reason, uh, towards all of these, um, sort of fashion type of, uh, form factors.

That's true. And there's only so much you can pack into, like sensors-wise, into all these things. Uh, yeah. Which means you have to stack rank what's important versus nice to have. I think the first everyone went for was like step counters. That's what it felt like was like, right? Uh, and then we went to heart rate and now think, obviously it feels like we haven't gotten all the must-haves there yet, right? Blood pressure's still really not measured. Hydration still not really measured. Maybe blood oximeter is measured. I don't know how well, and I don't know how valuable that is. Like, how do you look through all these of what's the necessity versus nice to have? Obviously you're working on something that is yet to be there for a must-have to— in the eyes of Oura, but to you it's much higher in need. So take us through like a little history of, of your data. Why is that the most important, you think?

Yeah, so, um, well, you know, hydration is interesting because I actually believe hydration is the only really actionable biometric that can be monitored on the wrist or the ring at the moment. And I don't want to, you know, sort of naysay everybody else's wearables because they're all great. And I'm huge fans of all of these wearables. What I mean by that is that, you know, like when your heart rate is elevated due to some sort of, you know, AFib or whatever, you can't really control that or do anything to prevent it. Maybe afterwards you can, you know, maybe afterwards you can, you know, take some medicine or sit down or calm down or something like that. Similarly with sleep, you know, we have lots and lots of devices that can do sleep now. And you wake up and you're like, yeah, I didn't sleep well, right? And like, but during your sleep or right before you sleep, maybe you can close the blackout curtains or you can Turn off your devices. But you— there's like really like, how do you, you know, sort of— I don't want to say guarantee, but like do something, right? Like you can't like have better sleep until you had a worse night of sleep, right?

That's right.

Um, and so hydration is interesting because for the first time we can actually get the trends of something happening in your body And then acting on it before the symptom happens. And so I think that's what's interesting. And on top of that, hydration and dehydration in particular actually impact all of these measures, right? They— it impacts your blood oxygen, it impacts your blood heart rate, it impacts your respiratory rate. So Really, like, every single system in the body depends on you being well hydrated. And that's also why, you know, if you go to the clinic or, or the ER, a lot of times the very first thing that you get is a saline bag.

Mm-hmm.

Right? Because we know most likely you're dehydrated. And in order for us to assess what else is wrong, the best way is to get you hydrated so that we can see what else is wrong. Right. So it, it's, it's simultaneously like underreported and also the most, you know, potentially the most reported, right? Is, is, but, but you don't know that it's dehydration. Right. So it, I think it's a very complex problem to tackle. Um, but also, you know, arguably the most important.

Hmm. Yeah, I love the saline piece. Like, imagine if at the same time they also just put a bag of sleep in and just be like, you know what, we're just gonna put you to sleep, drip that in and saline at the same time, and we'll just get that out of the way, you know?

Yeah, yeah. Although the anesthesiologist might say that's what they do.

That's true, that's true. Hopefully that's not used in that many scenarios in the ER. But yes, I hear you.

But you know, a few years ago we had a saline outage there's apparently only 2, I guess, manufacturers or, you know, factories in the US or something like that. And, you know, correct me if I'm wrong, but like something happened with them, with the supply chain, and they were rationing saline. And it's so crazy because you just think like, oh, okay, this is readily available. And so again, if we can do this well at home, right, we don't have to go to the ER and use this as a medical—

Right.

intervention, right?

True.

So that's the, the hope.

Interesting. How much of the research, uh, area that you focused on was related to hydration and, and what have you had to kind of catch up to speed on where the industry's at academically and technology-wise on hydration detection?

You mean my, my PhD and my thesis?

Mm-hmm.

Yeah. So we actually did not study hydration. So the funny thing is that, um, we were studying something else and actually I saw, you know, in my signals that there was this water signal that we are actually seeing as a confound. And so it was funny because my, my PhD was on a, uh, developing an early diagnostic for peripheral neuropathy actually, and using similar technologies. Um, and so my joke at the time was like, oh, wouldn't it be better if we just looked at hydration? And not knowing anything about water or hydration monitoring at the time, this was probably like 2007 or something like that. And I kind of laughed it off because, you know, it was just like, oh, that signal looks much bigger and better than our signal currently. Cuz I'm in the, the depths of my PhD research. Right. Uh, and I did nothing with it. Right. So, uh, it was like 10 years later and, you know, then I started training and realizing that hydration is such a big, uh, you know, indicator that, um, I wanted to do more deep dive. So the technology knowledge and understanding came from my You know, thesis in my research. But when I started Hydration, it was more of a customer perspective, right? Like I needed the, the product myself. So, yeah. Interesting.

Okay. So what have you learned today? Like, why isn't the sensor everywhere? Why isn't it prevalent? Why aren't, why aren't people, you know, one screaming from the rooftops being like, I'm dehydrated, you know, like, where's the disconnect, do you think?

Yeah, so it's interesting, right? Because everybody thinks that I— they know when they need to drink water because, you know, you, you think, oh yeah, I'm, I'm thirsty and I'm gonna drink some water and then it's gonna be fine. And if, if it's not enough, I'll continue being thirsty, right? Uh, that's true of some people and, and mostly younger people. Um, but it's also, uh, first of all, thirst is a lagging indicator, so it only comes on when you're already dehydrated, right? So we're trying to prevent the dehydration symptoms. So thirst is like, okay, you're already dehydrated. Your body is doing that. It, it's fine for normal, healthy young people, and, and that's, that's okay. Um, but when you're older, first of all, the thirst mechanism starts to degrade as you age as well. So you have all these old people saying, I'm not thirsty, right? Um, which they're not lying, and so they're not thirsty, but that doesn't mean that their body doesn't need it. In fact, they actually need it more, right?

Mm-hmm.

Because when, uh, when you get older, the, uh, if, if you have sort of muscle atrophy, for example, muscles hold a lot of the water in your body, um, and your skin gets a little bit thinner, right? And so there's all these like age-related changes, thirst included, where it basically means that you actually need to be more on top of your hydration, and yet you're less because you're, you're not attuned to your thirst. So part of the challenge actually is to educate people on this. Um, and, you know, and, and, you know, I always say, like, if I've pitched to 1,000 people, you know, and those 1,000 people are better hydrated because of my pitch, then I've done my job, right? Um, and so, yeah, I think part of it is education. Part of it is, is really, this is a very challenging and complex problem, um, because it— there's all of these sort of, uh, confounds, right? There's like everything that your body is doing. What are you eating, right? Are you, you know, exercising? Are you a heavy sweater? Um, you know, and, and all of these things are um, you know, impacting your hydration needs, where you live, what is the humidity today. And so other people are saying, oh well, I'll just get on a, a plan, right? And this is how much I drink every day. Well, that doesn't work, especially if you're going through, uh, the heat wave that we just went through, right? Um, and so, you know, we need to understand our bodies and get in tune with our bodies in a different way. And this is one way to sort of Get the information out, uh, so that you can understand your body better.

So it's an awareness one, like, and then build the muscle to even remember. I mean, I felt the difference of needing, being like, I need a drink. I haven't drank in a bit while you're talking about it. Uh, but then it's a, and then how do I improve? Uh, how do I actually change and iterate? That's just for myself and not just go off of 8 ounces, 8 8-ounce glasses.

Yeah. So I always ask people, they're like, okay, 8 glasses. I'm like, well, how big is your cup? Right?

Yeah.

Is it like the 32-ounce Stanley Cup or is it like the little teacups? Like, you know? So yeah.

So what was— take me through kind of your entrepreneurial moment. Like, when did you feel you were a founder in this and what did you actually do to rip the Band-Aid off to kind of go all in?

Oh my gosh. I don't know if there was a moment. It's just been sort of the daily grind, right? You know, I think there was one moment like where I was just very grateful for how big and how small simultaneously my world had gotten. And what I mean by that is like when you're in academia, you're sort of like, okay, I'm the world's expert in this tiny little sliver of science, right? And you are only talking to academics most, most, most of the time, and you feel like you're, you know, really smart or whatever, right? And then you— I moved into business. I'm like, okay, the world is so big and so small and so connected. And so I think on that particular day, I spoke with someone in Paris, India, UK, and the US in the same morning. And I was just like, that's crazy. Now, like, I can go visit all these places and have friends there or something like that, right? And so if, yeah, I didn't have like one breaking moment of like, I've made it as a founder. And I'm hoping that most founders will echo this thing is like, you're constantly learning and you're not ever made it, right? But yeah, I remember that one day where I'm like, wow. Like, I'm talking to all these people, uh, about the thing that I'm building. That's, that was pretty, you know, moving to me.

Yeah. Just the amount of attention span and how much it pushed out everything else of your day and energy and focus. Uh, totally. And hardware-wise, I mean, people love to say hardware is hard, obviously. Thanks. Thanks for pointing that out.

Yeah.

What, what, what were the steps to there? Because what I mean, the biggest thing is obviously getting something to the customer who gives you the feedback to say this is a pain or not so that you can get back and iterate the hardware, right? So how did that go? Like, what was it actually getting hardware out?

Yeah, yeah, that was, that was definitely tough. A lot of hardware companies don't ever launch, right? And so to have launched and sold out twice is a huge, you know, you know, point of pride for us and our team and how hard we've worked. And I think hardware is hard because hardware is not just hardware, right? Hardware, especially in the wearables, it's like hardware and building datasets and firmware and algorithms and apps, right? Like, you could just launch an app and call it a product, right?

Mm-hmm.

You can just launch an algorithm and call it a product. But we kind of had to build all of it. And, you know, it became our moat, which was awesome, you know, and we built a lot of IP surrounding it. But yeah, it's almost building like 3 startups in one, right? You have the hardware and the algorithms and the apps, and then you have to iterate, you know, and prove out, you know, your business model. So it's definitely not, you know, not easy. And I laugh when I see the Jensen Huang video where he's like, I would never do this if I knew how hard it was. I don't think I would not do it, but I definitely didn't know how hard it was.

Thank God we don't know how hard it's gonna be. Yeah, we would never start 100%. You know, ignorance is a little bit of bliss in that regard. But once you start, you're, you become obsessed with the learnings and learn and seeing, you know, what your customer thinks. What were some of the first things that That you learned from the customers once they got it on the wrist that you weren't expecting?

Yeah, well, I'll tell you one fail first and then I'll tell you a couple successes. So one of our very earliest apps, we're testing it, everything is great. Then we send it out to customers and we get some complaints that they're like, we're not actually able to press these buttons. And I'm like, what? We test, I personally test, like the buttons are working. Right? Turns out all of our older adult, you know, users are using extra large font, and the button fell off the page, and they could not press the button. And they were not lying until we finally, you know, were able to figure it out. And so we're like, oh, we need to figure out how to scale this. It's just like stupid early mistakes. But again, if you don't talk to your customers, if you don't figure out what's actually wrong, it wasn't the button's fault, right? Like, we just didn't scale the fonts. So, so that was one, one fail. But yeah, talking to our customers is amazing, especially older customers. You know, any customer service is hard, but, you know, serving older adults is an extra layer of patience and love and care. And in return, they give you so much. Love and care. And it's actually one of my favorite things because my grandmother was my person, my jam. And so like talking to older folks and they always have the best stories. And so I'll go into one customer story. This person is actually not older, probably mid-50s, but we do have some customers that are in their 80s. But you know, he actually told me that his doctor told him that he was going to need dialysis at some point in his life, and he's in his 50s, right? This is like really scary. Dialysis is not fun. And he got a Gecko Watch Gen 2 for his for his for himself for his own Christmas present, and within three months. His blood work, his creatinine levels became normal after using the Gekko Watch for for three months, and he called me, and I was like, "Oh my gosh, this is amazing!" And this is sort of like the first time that you know this this product that came in my head, you know, and and all of these people working on it, and we put it out there and made a bunch of mistakes, and this person said. You changed my entire health trajectory.

Right.

And we didn't see him in the clinic. We didn't see him, you know, like he's not technically sick. Right. And this is what we're trying to do is we're trying to catch people before they have to have some sort of medical intervention. And he's been trying, like he knew his blood work wasn't, wasn't showing, you know, that he was in the right, right path. But he wasn't able to do it. And he was one of those sort of younger older adults that did not have a great sense of thirst and could never, you know, drink enough water for his blood work to show. And so, yeah, that's just one example of something that just really moved me. And it's like, man, if I change just one life, right? Would it have all been worth it? And the answer is yes, of course. In the end, I wanna impact millions of lives, right? But like, man, that story just like makes me so happy. Like I almost cried when he told me. It's like, so yeah, it, it's definitely hard, but definitely worth it.

Incredible. I mean, to get the real feedback loop is huge. You know, it's very easy to put a product out there and know like, Am I doing anything? Am I changing the world? You know, am I affecting— or, you know, are people even looking at it? And are they changing their behavior? Because really what you're doing is, is a device to help people change their behavior, which is huge for, you know, moving people forward. What, what was else? Just let's even step back. You're gathering data, you're able to look at data on people's wrists.

Yeah.

What versus— and seeing real people data versus academic pools, populations pools, like, what was that like seeing actual customer data versus what we told— what has been told about what we know from people's history and specifically around this?

Yeah, I think that it's like a dual-edged sword, because people are going to be doing what they do, you know. So it's great because it's real-world data, people are going to do whatever they do. So we have Weird stuff like, man, the sensor failed. I don't know what happened. And you know, and we get it back, and turns out they were doing some crazy stuff with it, or you know that damaged it or whatever, right? And and then the data on the data side, it just makes it more messy, to be honest. And it's hard because you know you want to have these very validated datasets, right? And of course, that's what clinical studies are for, and that's what you know, validated datasets are for. But if you're trying to launch a product at home, especially in the wellness sector, like, okay, how do you use the user data and what do you actually ingest as ground truth?

Right.

So one of the things that we have decided is that we will offer an opportunity for fluid intake. It's like a log, right? But we actually don't take that log and feed it back into our algorithms as ground truth. And the reason being, it's not that we don't trust people. It's not that people are lying, and they could be. But really honestly, like, as I'm testing myself, I don't remember, you know, like, sometimes I'm just too busy. I drank some water with lunch, and how much, how many units of water was that, right? Like, how many ounces? And Or if I'm on, on a, you know, a run and I'm just drinking, right? Like, I'm not, you know, I come home and then I, you know, can, can actually, you know, have time to input how much I'm drinking, but not in real time, right? So until we get good enough to sort of just, you know, have closed-loop systems where, you know, for example, like CGMs is a good example, right? CGMs. that is for diabetics with an insulin pump is a closed-loop system, right? Something is low, we pump some in, right? Great. That, that you don't have to do anything, right? But on the, on the, you know, wearable side, it's like, it's hard to actually close that loop. And so we're getting one step closer where it's like we actually tell you what to, you know, when to drink and how well hydrated you are. You still have to take that one extra step to actually drink. And we're not asking folks to log more because it just, it's too burdensome. So that's something also we learned is that there are things that are too burdensome, right? And then there are things that we can ask our users to do. And then where is that fine line? You know, and then too much information is, is not good either, right? So a lot of wearables like Here's all the information, data overload, and nobody knows what to do with it. Um, so more data sometimes is not better, especially if you're looking at older adults. Really, we just do one thing and we focus on hydration. How well hydrated are you right now and when do you need to drink? Mm-hmm. So it becomes much simpler when you sort of, you know, just tease out what you're actually trying to do.

How long into the journey did you realize and hyperfocus into the older elder population?

It was a slow multiple pivots. So we actually started off in collegiate sports, got, you know, a little bit of traction there, got some LOIs from some top tier sports teams. And then COVID hit, and there was no more sports. Eventually, sports came back. But then what we found during COVID was there's a lot of movement on remote patient monitoring, especially for older adults. And as we're building, we decided to launch it first direct to consumer because we wanted to gather the datasets. We wanted to sort of own, once again, own all of the pieces, right, to be able to gather the dataset, iterate very quickly, put out, you know, hardware, firmware, algorithms, and keep going with direct customer feedback. We also did try to see if we can go clinical in 2023, and it didn't pan out that way. And so we said, okay, let's just launch direct consumer and see what we can do with the older adults. And it actually has been successful, I think, because folks are looking for solutions outside of healthcare. And so, you know, as we were discussing before, it was sort of like, you know, if, if people take charge of their own health, That's often the best outcome, right? Because you know your body, you know, you know how you feel, how, you know, you have to advocate for yourself and, and your loved ones. And, you know, so in that sense, people are motivated. They, they know, hey, something is wrong, and the current health system as it stands is not helpful to me right now unless I get even sicker. Right. And so people are actually coming to search for a technology like hydrostasis where we can actually help you before you get into the healthcare system. Right. So that's kind of the many different pivots to get to where we were, where we are today.

It's an interesting pivot. I mean, I think you see a lot of people try very specialized ways of thinking like who has the biggest pain And it's usually a customer you think it's like, oh, well, they pay a lot of out-of-pocket. They, you know, like sports. But it's interesting. It's like, but who actually has the potential to do something preventative that completely changes their life? Right?

Yeah.

That's really interesting on the behavior side. I love your example of the CGM, the glucose monitoring piece, which really is just it's a system that the body has already got and fa— and is failing, right? Like when pancreas, you know, dying because of overuse or diabetes around that guard. We don't really have an organ, I guess, that does that for the body for, uh, it's not like your body is failing at determining you need to drink a glass of water. It's like, we're not listening to our own body, you know, of whatever the body designed for that.

Yeah.

Like, so this is truly like training from, from like one-on-one level saying, hey, you're, you must've gotten really good at saying you don't need to drink right now. You don't, you're not listening to that warning in your head. Uh, but there isn't that warning light saying, uh, organ failing because of this, except maybe in the elderly population where organs are starting to fail, um, because of the lack of this. Is that kind of how it's seen to a certain regard? Like this is the extreme piece of where it's happening and that's where—

Yeah.

Therefore, you're intervening?

Yeah. I mean, it's hard, right?

Yeah.

Like you said, there is no organ for hydration. It's your entire body is water, right? So multiple things start happening. And the first sign is executive function impact. And so your cognitive function is declined even at like 2% uh, total body water loss. And at 2%, really, this— you don't really feel it. You have no idea. And sometimes there's a tension headache, right? So then we go reach for the ibuprofen or Tylenol or whatnot. But what if you just like drink a glass of water and see if your, your headache goes away, right? Obviously for migraines and, and other things that it doesn't go away, but like, what's the harm in understanding that hydration comes first, right?

Yep.

So that's kind of where I'm at is like, there's all these things. And now chronic dehydration has been linked to early onset diabetes, and diabetes has been linked to Parkinson's. So we're over here trying to solve Parkinson's, but what if, let's say 20 years ago, we were better hydrated, right? And, and it's like, yeah, these are all very hypothetical, But again, it's like we don't know that unless we put the science to work, right? So I think that's why it's so important is like this is longitudinal data that we're building. And so, you know, long-term health and longevity is, is a big sort of piece of, of, you know, hydration health and what I want to do for, you know, the, the wearables world.

Where do you think, I mean, obviously we're in a moment of advanced interest in, you know, quantified self or personal health data, however, whatever buzzword we've used every 2 to 3 years, right? Um, IoT for the body, right? Whatever it is.

Yeah.

Um, from your perspective of watching and viewing it now for close to 8+ years, one, are we in a bubble around health data? Uh, or are we actually broke through the threshold where it's actually more mainstream? And people have access and are doing the things that are right. So one, I'm just kind of curious in your take on that, and then we'll talk like tech adoption and where we need to go still.

Yeah, um, that's a great question. I think there's different camps. I think the, the people that are really excited about wearables are like, yes, we've figured it out and we are here, right? And then there's still a lot of people that are like, I don't understand why we need to monitor everything in my life, right? And to be honest, I'm kind of in between. Like, I am a wearable founder that doesn't wear 7 different wearables at all times. And the reason why is because I also believe that if we're overmonitored and increasing anxiety, like, that's also not a great way to do it, right? So I do think whatever we do as a monitoring and wearable sort of field, we need to make sure that it is useful and actionable. And what is useful and actionable is obviously subjective. But I think if we— if all we do is increase anxiety, then that means we've failed, right?

Mm-hmm.

And so, yeah, I think depending on your needs, The wearables have, you know, solved many, many, many things, and it's it's it's become so ubiquitous. Everybody has some sort of wearable, and you know people are healthier for it. They you know even the the devices that people say may or may not be super accurate, like people are you know early you know. Our understanding early onset, getting sick, XYZ, you know, AFib, what have you. And so I think we are on the path for sure. There's definitely work to be done, and I do think there's going to be some sort of— I think we're on the explosion side. There will be a shrinking, you know, piece of the timeline. We're not there yet. I think we're still expanding. Um, but once everybody has a whole bunch of information, what next, right? How do we actually sort of curate that to be actually useful? And it'll be interesting how the healthcare system works together with the wellness devices, um, because they are not at our home, they are not when we're healthy, right? And so how do we ingest And and look at the healthy data, right? To predict maybe something is early onset. Let's say you have prediabetes, which by the way is totally reversible, right? If you can input all of these things healthy, you know, eating, drinking water, exercise, and all of the things that you need to do to turn your diagnosis around, that's where the wearables world. Could be very, very helpful. So I think there are examples where that would be a huge success for the wearables, not in the clinic, but then also in the clinic, right? You see a lot of wearables that are being sent home so that the doctors and the nurses that are always understaffed to be able to reach them through a virtual care. So yeah, I'm super excited and really actually very grateful that I'm like in this moment in time in history. It's so exciting with everything that's going on with Oura and Whoop and all the Apple, you know, announcements recently. And so I'm excited to be like a tiny sliver of that and, and see how, you know, we can get hydration into some of these wearables and really reach the people that we wanna reach and, and impact those lives.

Hear, hear to that. Well, I know timing is a huge part of all this and, you know, being around and alive and having product in hand is huge to be a part of this moment, that's for sure. I know one big part that you brought up in the Wearable Roundtable, and again just before we talked here, is kind of the biases in the data and in the hardware. Uh, have we gotten any better there? Like, are we, are we even aware that there's bias out there and we're doing something about it, or it's something people are still kicking the can down the road of within the health data world?

Yeah, it really depends. Depends on how, I guess, each leadership team views it, right? And just to back up for your viewers and listeners, during COVID we relied a lot on the pulse oximeter to triage and decide who was going to stay in the hospital and who was going home. And the studies found that the pulse oximeter did not work well on folks with darker skin. And it was very, very well documented that a lot of folks with darker skin were sent home and they died of COVID and at a higher rate. And so, you know, it was a very sad realization for me. to be like, man, really? You know, and so it made me think like, what datasets are these wearables using to tune their algorithms? So my side quest now is to talk about data equity because, you know, we have all these great tools that ingest the data, right? You know, Claude, ChatGPT, whatever you're using. Um, the, the algorithm and the tool can get better, but the datasets don't get better unless we are providing better datasets. And, you know, just to be clear, women weren't even allowed in clinical trials until 1993. 1993!

That's crazy.

So any sort of therapeutic or safety mandate or whatever it is, like the seat belts, right, were not done with crash test dummies that were of women proportions. They were just a miniaturized man, right? And that actually causes— and you can look up the statistics for, you know, women fatalities and things like that in the car— is elevated. Because of that, and it's unfortunate, but it's true. And so for me, as a person that collects data, right, my goal is to let everybody else know that this is super important, and we are talking about it. I do know that there are some of the top wearables are talking about it, and they are getting better, thankfully. But again, the historical dataset is what it is. So we need to— again, it's an education, you know, piece of it is like when you ask ChatGPT, you know, what is the likelihood X, Y, and Z, like that's the dataset they're using, right? So there still needs to be a human in the loop to understand the history of the datasets that we're using. And I want to make sure that everybody that is collecting data Understands that the data equity piece is so important for the future, you know, algorithms and the future diagnoses that we're making.

It's huge. It's a long road ahead for that, but at least we're talking about it. And now people are ingesting data more readily, more easily. Hopefully they're realizing, and now I can iterate the data that I'm getting, and I can go collect the different data. that I want to get. Uh, that's— I'm still in shock about the '90s piece and women in clinical trials. That's so crazy.

It's crazy. And people don't know about it. People don't talk about it. Yeah, we just kind of take it for granted. Um, yeah, it's, it's like dosages for medications. Like, some medications don't, don't work well for women, and— or maybe, you know, the dosages need to be lowered because then, you know, different metabolism. What— yeah, I mean, there's so many different things that could be, you know, helped with equitable data. And also age as well. So when I'm doing my research, it's really hard to recruit for older adults, um, you know. And so like a lot of times the wearable companies use like college-age white male students, right? Because it's, you know, they get course credit or whatever to volunteer for these studies. Right? And that's also, you know, a problem because when I'm talking about older adults, I need older adult data, right? So yeah.

Really interesting. So where are we— where do we end up eventually? Like, do we get to the point of where we are in the CGM world where you create a fake pancreas, a working pancreas, where you view your— you have a device that looks at your blood sugar and then gives you insulin? Do we have the same? We have a device that looks at your hydration and then gives you saline, uh, to just take the human outta the loop for this? Or, or where do we need to go to help people get actually hydrated at all the times?

I mean, for the wellness sector, I doubt it. Um, I, I think for the clinic, possibly, right? Like if you're in the ICU, for example, right? Um, you can increase flow for saline or decrease flow and things like that. Um, But yeah, I think in general for, for the wellness folks, it really is just understanding your body, what you typically do. Do you fly a lot? In case, you know, then you should probably drink more water because it's extremely dehydrating. Um, and then as we move, you know, uh, towards different applications, you know, um, my view is that hydration monitoring should be everywhere that heart rate and pulse oximetry is, right? So I believe that hydration is actually a vital sign. I think it should be in the hospital stacks. I think it should be at CVS. I think it should be in your Apple Watch and your Oura Ring, you know, uh, in, in any wearables that you wear. Um, hydration is a big piece of the full picture, right? So, um, so that's my goal is to you know, build the technology to be robust enough, uh, to be able to be integrated and, and sort of, you know, disseminate this information and, and the technology so that we can actually make a bigger impact, um, surrounding hydration and, and really understand it more because there's really a lack of understanding, um, of how hydration impacts your entire body and all of the systems that are depending on it.

Maybe. Well, hope with you working on it and many others I know as well as we've met, but you know, you specifically, we're, we're headed there. And like we said, we're in this very special moment where both the customers are demanding it.

Yeah.

And the tech is, you know, the software hopefully is getting easy enough, uh, that we can focus on the hardware part of getting the hardware actually on the people's bodies to a certain regard. Um, And I know you're continuing to work on that. When, when do you think we'll have the device that tells us we ate the best taco we possibly could at that moment? Because that's next, obviously. Hydration first, taco detection next.

Yeah, yeah. Well, unfortunately, tacos usually comes with a margarita, and that's slightly dehydrating. So, but you could also, you know, add in some agua frescas on the side.

Balance out.

Yeah, I don't know. That's, that's a tough one. I haven't thought deeply about the taco side.

Okay, so then where would you go to test it first? Meaning, where's your favorite taco spot?

You know, I, yeah, in San Diego, there's just too many good taco spots. I'll just talk about the one that's, you know, down the street from my, from my house, because that's the one I go to most. And most people probably don't know about it. It's called El Patrón. And I'm in Mira Mesa, so they're, they're great. There's just kind of this neighborhoody place, and every single thing that I get is good. The, the shrimp cocktail comes in this giant, like, you know, giant cup, and so it was really great to get that during the heat, you know, of last week. But yeah, it's just sort of like a mom-and-pop neighborhood place that is just solid, solid food.

So I love it. I don't think I've been mentioned here. Definitely have visited it, but have not been mentioned on the—

oh, you've been—

love a good first-time mention here. Love a good neighborhood spot too, you know. Yeah, a lot of neighborhood spots. We also got a lot of chains and everything in between. You mentioned the shrimp cocktails. Interesting. So is, is, so is the shrimp taco also the thing to get there, or what's the thing?

I've also, yeah, it's just, I, it's interesting because it's like, you know, it's a taco shop and people might be like, oh, you know, I don't know, I don't trust the seafood or something like that. But man, seafood is good. I, I, I've gotten their fish soup as well, is also very good. Ceviche is also very good. So yeah, I enjoy the seafood there.

Okay, I love it. Love good seafood tacos. And what's the right order to get there? El Patrón. And so obviously we'll go and do some taco detection of our own. Yeah, wire ourselves up.

Let me know when you're in my side of town.

You got it. We're here on the Sorrento side. You're on the Mira Mesa side. Yeah, yeah. Other side of the tracks, we love it. But Debbie, thank you so much for, for joining the pod, being a big voice for data equity. Honestly, in this, you're not just out there educating the customer around why you need to actually drink that water, but you're even educating the, the futurists as well who still have work to do in their regard as well in making sure that we're getting the right data. So that we're supporting everyone who is the end user. So I just appreciate what you're doing, uh, and thank you, Debbie.

Thank you so much. I appreciate you, Neal. You do a lot for, for all of us, uh, you know, uh, startup folks here in San Diego and, and beyond. So appreciate your work as well.

Look, if you're successful, we're all going to be successful. You're going to make all of us more healthy, and we know you're just going to work on the next thing after it as well too. So we just got to get out of your way and help Debbie do the thing that she's meant to do, which is this.

Yeah.

So thanks again.

Awesome. Cheers. Thank you so much, Taylor.

Tortillas, round jalapeños. In these modern times, a craft beer and coffee. My coding yoga posse fold the body origami. We be surfing Coronado, eating tacos El Gordo. The tacos standing puesto, lucha libre and sombrero. Gotta shout out to Coast Angels by the ocean, watch the sunset. La Jolla shores, entrepreneurs trying to get funded when San Diego So Startup Week is popping in the summer, Oceanside to Tijuana. SD be full of hustlers, from couch surfing to penthouses right on the beach. Tech leaders who believe stars are within reach. We interviewing founders who be shooting for the moon. #SDTechos with your host Neal Bloom. Come on! Startups get the party, startups get the party started. Startups get the party, startups get the party started. Startups get the party, startups get the party started. You want tech and tacos, tacos and tech, you know we got it, hey! Startups get the party, startups get the party started. Startups get the party, startups get the party started. Startups get the party, startups get the party started. You want tech and tacos, tacos and tech, you know we got it, hey!