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SynchNeuro: How a Neurosurgeon Is Changing Cardiometabolic Care · StartUp Health NOW Podcast

• 0:00
  Welcome back to Startup Health Now, the podcast where we celebrate the entrepreneurs and the innovators who are transforming health. I'm your host, Logan Plaster.
• 0:09
  [piano music] Sometimes health innovation comes from an unlikely source. The most recent addition to our cardiometabolic health moonshot here at Startup Health is a company founded by a neurosurgeon.
• 0:21
  In the cardiometabolic space, we think about things like heart disease and type 2 diabetes, not usually the focus of a surgeon who specializes in implanting neurostimulation devices for people with Parkinson's disease.
• 0:34
  But for years, Dr. Casey Halpern has been researching the connections between the brain and metabolism.
• 0:40
  Specifically, he wanted to help folks with obesity by better understanding the brain signals associated with things like appetite and high and low blood sugar. But what he discovered was way bigger than he expected.
• 0:53
  He figured out a way to monitor glucose continuously using a simple EEG device that sits behind the ear and pulls signals from the brain.
• 1:02
  If their work proves out, they will have created a non-invasive CGM, like the ones worn on the arms of people with type 1 diabetes, that's affordable enough for anyone with type 2 or pre-diabetes to use.
• 1:15
  What that means is that millions of people at risk of developing type 2 diabetes or future heart disease would have access to the glucose data they need to make healthier decisions throughout their day.
• 1:26
  In my interview with Dr.
• 1:27
  Halpern, co-founder of Sync Neuro, we learn about his journey from physician to founder, walk through the details of his new behind-the-ear device, and hear how the rise of GLP-1s means that the time is right for a more accessible way to monitor cardiometabolic health.
• 1:44
  Let's get into it. [upbeat music] Dr. Casey Halpern, thanks for joining me today. Pleasure to be here. Thank you, Logan.
• 1:54
  So you have come up with a truly novel device, um, this over-the-ear EEG-based continuous glucose monitor type device. We're gonna get into all of that. It's really cool. It's really pretty future-forward.
• 2:08
  I work with a lot of founders. Not everyone has really a new take on a medical device. And so this is really exciting. This, this could impact a lot of people.
• 2:17
  But before we get into the product and Sync Neuro, this company that you've started, um, I just wanna get to know you a bit and introduce you to our audience. So, uh, let's take it back.
• 2:29
  I understand for a long time you've been connecting the dots between things like metabolism and the food we eat and the brain.
• 2:36
  So just take us back to kind of where that interest started, if I've sort of characterized that okay. Where that started and kind of your, your journey through, through that kind of academic work.
• 2:48
  Well, Logan, it's a pleasure to be here, and thank you for, for the kind words, and certainly very excited at Sync Neuro to be doing bold, innovative work, uh,
• 2:57
  really trying to bring an exciting neurotechnology to, to many users around the world that need it. Uh, I'm a neurosurgeon. Uh,
• 3:07
  I've been working in the, uh, interaction between the brain and our metabolism since I was really transitioning from college to medical school.
• 3:20
  Uh, I went to the University of Pennsylvania for medical school with-- where there, there was embedded time to do research, and I've always been interested in the obesity epidemic, eating disorders related to obesity, our metabolism, the kind of foods we eat, dangerous urges associated with overeating,
• 3:42
  uh, the association of obesity with metabolic syndrome and diabetes.
• 3:47
  And I suppose the interaction between the brain and our gut and how the brain orchestrates our metabolism has always really been a focus of my research. Uh, after my training, I, uh, I left Penn.
• 4:00
  I went to Stanford University and had a federally funded research laboratory, which exists today, but I, I actually had returned to Penn, uh, where all of this started.
• 4:10
  Um, but it was at Stanford where we made a discovery that we could use brain data. This is electrical data emitted from the brain surface- Mm-hmm...
• 4:21
  all detected using sort of ground truth, uh, tiny little wires that are sitting on the brain surface or, or gently placed into the brain to, uh...
• 4:32
  Well, they're placed for patients that have epilepsy, so we do it for clinical needs. Yeah. But they afford the opportunity to examine and test novel hypotheses, uh, which scientists like me have been doing for years.
• 4:46
  Uh, in this case, we were trying to understand how the brain monitored or tracked our blood sugars.
• 4:54
  Uh, we were particularly interested in understanding why people have the urge to overeat, and does that relate to blood sugar levels.
• 5:02
  And we actually found that indeed, when people are, uh, feeling those urges, blood sugar levels are low. And that might not be surprising, but not something really has been well documented.
• 5:14
  And while that was exciting, what was even more exciting was that we could actually decode brain data to predict those blood sugar values very accurately. Okay. So I formed Sync Neuro-- Sorry.
• 5:26
  Pre-predicting by, by how much? So talk to us about kind of how break-- how much of a breakthrough that predictive element is. Yeah.
• 5:34
  When I, when I use the word prediction, I, I, I mean, uh, using machine learning techniques to- Mm... identify, um, and provide a readout of what the, uh, blood sugar is, and we would--
• 5:49
  To measure the blood sugar, we would actually use continuous data provided from a standard continuous glucose monitor. Mm-hmm. And then, uh, sort of synchronize in time, hence the term Sync Neuro, um- Got it...
• 6:00
  the, the continuous brain data and the continuous glucose monitoring data.And what we found was actually once you decoded, we could do this in an automated fashion using machine learning, once you decoded the brain data, you could actually match the- Okay...
• 6:15
  continuous glucose monitoring data. Okay.
• 6:18
  And e-explain to somebody who's not familiar with EEG or some of these, these, uh, methods you're using why that is exciting or potentially superior to the current gold standard in continuous glucose monitoring. Sure.
• 6:33
  Uh, continuous glucose monitoring is an exciting technology available for people with diabetes, type 1 and type 2.
• 6:40
  It requires a, uh, a device to be placed through the skin, and that little tiny needle, um, it sits under your skin in the interstitial fluid, and it is measuring through a chemical reaction the interstitial glucose levels, which is a proxy for your blood sugar values.
• 7:00
  And it's particularly accurate when you're eating and you have a blood sugar spike, for example, and that's when it's most validated. Um, that technology is a bit invasive. It's expensive. Um,
• 7:13
  for example, they, they do have over-the-counter devices that are available to people now. Um, it's approximately $50 a device, about 100 bucks a month. Okay.
• 7:22
  And, uh, you know, I don't think that that's a scalable technology for the many people with prediabetes that are really trying to understand their bodies better. Mm.
• 7:32
  So the kind of technology we're trying to build is one that can be worn behind the ear discreetly. Um, it's much more affordable to make. It's much more simple technology- Yeah... which is sort of the beauty of it.
• 7:45
  Um- Yeah. Pause on that for a second because when I think about some next gen, over-the-ear brain signal monitor, I think that sounds complicated.
• 7:54
  That sounds like a, a new fangled piece of technology that's gonna be expensive. Why can you do something like that affordably? Yeah. Uh, yeah. So on first glance, this sounds, you know, like science fiction. Um- Yeah...
• 8:06
  and, uh, I would say that actually, um, the sort of the sweet spot of what we're doing is, is that the technology we're building leverages very well-known technology that has been available for many years, decades, um, that we use to study people with epilepsy, uh, people that have seizures.
• 8:25
  They wear a device called EEG- Mm-hmm... electroencephalogram, uh, which typically is worn as a scalp cap, sort of with multiple electrodes all over your scalp. Um, and you can lateralize where seizures are coming from.
• 8:41
  You can even potentially predict when the seizures are gonna happen, and you can actually diagnose epilepsy in this way. Yeah. Um, it turns out we found that when people wear devices like that, um,
• 8:55
  there are many places where you can actually track and decode that, uh, electrical signal from the brain and predict blood sugar levels.
• 9:05
  Um, but it turns out you actually just need the electrode sitting behind the ear- Mm... to do that. And so what we're creating is sort of a miniaturized EEG technology. Yeah.
• 9:15
  Um, EEG is a very sort of straightforward technology to engineer. Uh, it's been around for a very long time. It's fairly well validated. Mm-hmm.
• 9:25
  We now have, uh, dry electrodes and flexible hardware that would allow for people to wear this 24/7 if they so choose very comfortably. Yeah.
• 9:36
  Um, many options for adhesives that could be worn daily, weekly, monthly, uh, with a variety of different options for different skin sensitivities and things like that.
• 9:46
  Also, these adhesives are extremely affordable as well.
• 9:49
  While we don't wanna necessarily build the device based on price, what we're trying to design is a glucose monitor for the masses, the many, many millions of people that are really just trying to understand their metabolism better- Yeah...
• 10:03
  and perhaps have a bit more of a holistic strategy to have those kinds of insights, and that's what the brain does compared to a standard glucose monitor.
• 10:13
  Let, let's talk about the prediabetes part of this and imagine a world where... How many people do you think have prediabetes? Oh, you know, in this country, it's probably about 100 million Americans.
• 10:24
  100 million people, right, and that's just in one country. So y- you know- Yeah... uh, you think globally. So massive issue. No one is treating them. No one is, like, addressing that issue proactively, right?
• 10:37
  It's just something that's just sitting nascent. Um, in a world with an affordable monitor for, uh, blood sugar for these folks, what does life look like? How is life different?
• 10:50
  W-what's that new medical reality for them? Yeah. We are trying to harness the brain's energies to provide insights that people otherwise wouldn't have and to give people more control in their daily life.
• 11:03
  And so people with prediabetes, they're afraid they're gonna develop type 2 diabetes. Yeah. I have prediabetes, for example, and I can't figure out what I need to change in my life to be healthier- Mm...
• 11:15
  and prevent type 2 diabetes later in life and, and treat the problem at hand. Mm. Um, so with a device like this, people are expected to have that type of insight.
• 11:26
  We will be able to provide people with their real-time glucose levels, much like a standard glucose monitor. But I should really clarify that the, the brain is a prediction machine, and the data set is much richer. Mm.
• 11:40
  And you can do so many more things. We're only scratching the surface, the tip of the iceberg- Yeah... as to what we can do with this.
• 11:46
  We have evidence that we can actually anticipate what people's glucose levels may be later in the day. Mm. Maybe even perhaps their sleep quality.
• 11:56
  We're starting to learn that if people have a, a real bad night's sleep, their blood sugar's gonna be really awry the next day. Mm. Mm. Brain actually canPredict approximately what that blood sugar can be- Mm...
• 12:10
  and tell you, for example, maybe via a Bluetooth connected to a smartphone through an app, so Sync Neuro will have its own proprietary app where we will interface with our users, and give you a sense in the morning what your risk factors are and what you could do that day.
• 12:25
  Okay. Guide your lifestyle and, and improve your health every single day. And we're trying to gamify it. We think that's important.
• 12:32
  Um, so we want people to understand what they can do in their day to improve their levels.
• 12:38
  And every day they will have a readout before they go to sleep to try to improve the next day, and more long-term metrics as well.
• 12:49
  [upbeat music] Hey, a quick plug about StartUp Health before we get to the second half of this interview.
• 12:54
  Uh, we have been organizing mission-aligned networks called Health Moonshot Communities in order to level up the world's most ambitious healthcare entrepreneurs.
• 13:04
  We've been doing this work since 2011 and have helped more than 500 companies from more than 30 countries.
• 13:10
  Membership in StartUp Health is open exclusively to founders and CEOs in health tech, biotech, and life sciences who are dedicated to solving the biggest health challenges of our time.
• 13:21
  You can learn more about the benefits of membership, and you can read hundreds of success stories, member testimonials, all at startuphealth.com.
• 13:29
  [upbeat music] Let me just play the devil's advocate, and you can sort of clarify what your vision is. If I wake up and the app tells me, "You had a bad night of sleep-" Yeah...
• 13:41
  therefore your blood sugar's out of whack, and you're gonna be hungry. You should go work out." Like, I'm gonna say, "Okay, you're preaching to the choir. I already know I had a bad night of sleep.
• 13:50
  I already know I should go work out and eat healthier." How is this going to be more granular and more helpful than that? It's all, it's all about timing itself. Okay.
• 14:00
  So, you know, it might very well be that that glucose peak is gonna happen in the morning, so that might be the time when you wanna exercise or avoid a high carbohydrate breakfast, for example. Mm.
• 14:11
  Um, rather if the glucose peak is gonna happen later in the day, um, you might wanna actually have your cardiovascular activity later in the day to try to help offset that. Okay.
• 14:22
  So people will actually be, uh, more prepared for their day to have more control to get ahead of these problems. Mm.
• 14:28
  You know, you know, we're not just trying to replicate in a, in a more affordable fashion what continuous glucose monitors do. We're trying to recreate how people think of their metabolism- Mm...
• 14:40
  and, and give them more control. Yeah. Um, so for example- I would love, I would love to have an app tell me w- the optimal time to work out or- Yeah...
• 14:49
  when to, you know, eat, eat heavier, eat lighter, like anything like that- Yes... um, would be highly, you know, valuable. Yeah. And, you know, people will be able to input into the app the kind of foods they eat.
• 15:01
  The app will then automatically, using machine learning algorithms, be able to decode, uh, combining brain signals and behavior to better understand what, what foods put them at risk, what foods maybe, uh, are, are okay for that individual to eat.
• 15:15
  Mm. You know, there's a, a tendency in our society to, uh, be very rigid in terms of the kinds of foods that cause sugar spikes, for example.
• 15:23
  Avoid donuts, avoid, um, uh, people now say avoiding oatmeal must be done because you'll have a sugar spike because of it, and that very well might be true in certain individuals.
• 15:33
  But in other individuals, they might be pretty resistant to that sugar spike. Mm. Um, so it's very important to personalize this. Okay.
• 15:41
  And what we're finding is that personalized strategies will lead to the best outcome. Okay.
• 15:48
  Moreover, a proactive strategy, so getting ahead of these problems before they happen, not just reacting to the sugar spike after the fact.
• 15:57
  Okay, let's talk about the milestones and kind of where you're at with the company. You talked about an over-the-ear flexible EEG.
• 16:04
  Where are you at in terms of the actual device itself, manufacturing, coming to market, validation, all that? Sure, yeah. Well, we are early stage. You know, we're just transitioning into the seed phase of the company.
• 16:17
  We've raised $3 million of angel money to support where we're getting- or, or where we are today, I should say. Uh, the, the device will be an adhesive sitting on the patch of skin behind your ear, hard to see.
• 16:29
  We have, uh, breadboard prototypes available showing functionality and accurate detections. What we're trying to create are functional prototypes. Uh, we've identified partners on the hardware side to build them.
• 16:42
  We have a fabulous, uh, engineer in the company who's been supporting sort of everything we've been doing today, but we gotta scale this. Mm. We wanna build hundreds of these devices and test them in a, a human study.
• 16:53
  Our computational scientists are telling us that we probably need a large cohort study, something like 500 or 600 patients- Mm... to pair this device. We just need about two weeks of data. Yeah.
• 17:05
  Two weeks of data, our power analyses are suggesting that we can optimize our predictions and, if not be superior, match a standard continuum glu- glucose monitor. Yeah.
• 17:17
  Isn't it interesting, it's, in the world of health innovation that that project, which is so important to the life of Sync Neuro, is both sort of daunting in its size, it's 600 people using it, and yet also if we really think about it, really not that complex.
• 17:33
  600 people just putting this on their ear for two weeks, gathering that data. It's like, it's sort of just like right there- Yeah... um, to be done, right? It's, it's not unimaginable. It is far from unimaginable.
• 17:46
  You know, we intend to do this virtually. Mm. So a virtual clinical trial. We can send people these wearables. It's very easy to do. Yeah. People are really excited about healthcare wearables these days.
• 17:55
  We wanna be an all-in-one. Yeah. You know, we can provide readouts on so many metrics of health that are typically provided, uh, from watches and rings.
• 18:04
  That can be very helpful, by the way, but I don't think everybody wants to wear multiple devices. They want an all-in-one strategy. Mm.
• 18:12
  And glucose monitoring is so critical for health optimizers, not just people with prediabetes. Yeah. So we wanna go beyond the patient population of need as well.
• 18:20
  Uh, we, we think there's lots of early adopters that would be excited to, to try this. Um, the early study of approximately 600 individuals, if done virtually, could take no more than six months, if not faster.
• 18:33
  And-And then we're on, you know, onto getting FDA clearance, and that's, uh, the, the next phase, probably towards the end of this, uh, seed round. How challenging do you think the over-the-ear form factor is?
• 18:45
  Obviously, you need to sort of nail the form such that it is comfortable enough to wear for long periods of time, and it has to be-- it has to look such that people are willing to wear it.
• 18:56
  So how challenging is that piece? You know, certainly there will be people that no matter what you do, no matter how cool it looks or how discreet and slender it is, they wanna-- they won't wanna wear it.
• 19:08
  Um, that's possible.
• 19:10
  What we're learning is that the majority of people with prediabetes, now there's about a hundred million people in this country with prediabetes, but probably only twenty million that have been diagnosed with it. Okay.
• 19:21
  We've done a lot of internal, uh, market research at SyncNeuro. We found that about seventy-five percent of those individuals are scared, and they're eager to have a monitor that's affordable- Mm.
• 19:32
  -painless, and non-invasive that provides personalized data to help them prevent type two diabetes later in life. Yeah. So that's a pretty large market of early adopters. Let's say that's fifteen million Americans.
• 19:43
  Um, you know, our intention is to go beyond that obviously, but, uh, just as an early adopter community, uh, we think that's a really exciting, you know, place to start. It's a great question.
• 19:55
  Question for you, just as, as a founder of this company, you know, you spent a long period of your, your life studying to be a neurosurgeon, doing your, your long residency and practicing as a physician, doing academic research, um, and I'm curious what the-- if there was a moment, if there was a, a, you know, a light bulb moment for you to sort of jump into the fray as a founder, as an entrepreneur, when you probably could have been very comfortable just continuing as a surgeon and as an academic and doing this research.
• 20:28
  Um, was there a moment when kind of the lights came on that, hey, I need to build this company, I need to sort of put myself out there? 'Cause it's a risk. Yeah.
• 20:36
  Probably two moments, um, that I'll share with you, if you don't mind. Um, you know, the first was a dinner with a close friend of mine who, uh, I connected with when I lived in the Bay Area.
• 20:49
  Uh, he was at the time the COO, CFO of Instacart, named Ravi Gupta. And we were sitting at dinner, and I told him, "You know, I love taking care of patients. I'm a neurosurgeon.
• 21:01
  I place deep brain stimulation devices for Parkinson's disease. It's enormously rewarding, highly effective therapy.
• 21:07
  If I'm lucky, and I probably will, you know, have done over a thousand of these, um, in an entire career I can treat thousands of people." And I mentioned this to him, and he said, "Casey, that's unbelievable."
• 21:17
  I'm like, "But Ravi, you know, you impact hundreds of thousands, millions of people with your company at Instacart." And he's like, "Casey, I, I deliver mangoes." And I said to him, "But you deliver millions of mangoes."
• 21:31
  And he said, "It's a different kind of impact, but I see what you mean." And, you know, since that time, I've realized that the kind of reward that I feel every day taking care of patients as a surgeon,
• 21:44
  there is a bit of a ceiling in terms of how many people I could help.
• 21:47
  And if there is a way to use the brain energy and harness brain signals to help people with their-- provide more insight into their health and monitor their health, I could have a similar level of impact, but for millions of people, and change epidem-- health crises and epidemics like diabetes and metabolic syndrome and, and other related health problems.
• 22:08
  You know, the cardiometabolic health space is enormous. Um, but starting here with glucose monitoring because of the, the critical need with people with prediabetes I think could have fabulous impact.
• 22:19
  Um, that-- all of that paired with, you know, I left the Bay Area right when I started the company and returned to Philadelphia. And I at first was questioning myself. You know, I, I wanna start this company.
• 22:30
  I'm living in the Silicon Valley. Why am I moving home back to Philadelphia? And of course, that was to be with family.
• 22:35
  But I, I met with an investor, um, here in Philadelphia, and he never officially invested in our company, but he, he's given us some great advice, and he's out of the space currently.
• 22:45
  And when we sat down to talk, his name was familiar. His name's Howard Ross.
• 22:50
  I learned that in his prior career, now he's in private equity, uh, he invested in early-stage companies, and he realized at that time that he invested in my grandfather's company. No way.
• 23:03
  Which was a life sciences company. His name was Lucas Leone. Um, he started a couple of companies, pretty well-known companies, uh, Beech-Nut Baby Food, Eglin's Best.
• 23:12
  And Howard Ross was w- the first investor in Eglin's Best. [chuckles] And I, I guess I realized, uh, it was in my blood, and, uh, I couldn't ignore it anymore.
• 23:22
  And luckily, you know, my, uh, my chairman at Penn is also really invested in neurotechnology and really interested in how to commercialize it, and my lab seems to be a great place for spitting out a company like this.
• 23:36
  Mm-hmm. And I seem to be the right person to, to take the lead on it. So, so here we go. That's awesome. How would you characterize this moment in time in neurotech? It's an enormously exciting time, you know?
• 23:52
  It see- it seems like it from my angle, so but you're right in the middle of it. So from your, from your side- Yeah...is this an inflection point? Is this a moment right now? Yes, it is, you know,
• 24:03
  for a variety of reasons. You know, there's a variety of new neurotechnologies, invasive technologies, think, you know, deep brain stimulation, Boston Scientific, Medtronic, Neuralink, um,
• 24:17
  incredible research laboratories around the country, around the world.
• 24:21
  Uh, you know, Edward Chang at UCSF, Jamie Henderson at Stanford, uh, Daniel Yoshor at Penn, really trying to develop technologies that sit on the brain surface or inside the brain tissueUsing, you know, brain data to try to deliver therapies and give people insights and more control in their life, sort of the BCI, brain computer interface revolution.
• 24:44
  Mm-hmm. Meanwhile, we have new technologies that are non-invasive, like EEG technologies like Sync Neuro's trying to build. Yeah.
• 24:52
  Uh, trying to understand what we can get from brain data completely externally, and then scale it to the millions of people that could use it. 'Cause BCIs that are invasive really can't be scaled in that way. Sure.
• 25:03
  I know Elon Musk is, is trying to do that. That's obviously very exciting. We'll see where that goes. Mm-hmm.
• 25:09
  But pairing that type of hardware revolution with the software revolution that we're having, thanks to machine learning and AI and the novel deep learning technologies that we're really developing now and starting to see what the potential is, it's an enormously exciting time.
• 25:25
  It couldn't be a better time to try to bring a brain-based wearable to market.
• 25:30
  You know, at first people might think that's a little quirky, a brain-based monitor, but I actually think there's no better time to do it, this neurotech revolution.
• 25:39
  People really wanna learn about their brain more and leverage their brain, which is probably the greatest data source anybody could possibly imagine. Um, and the data that we get's highly personalized and proactive.
• 25:50
  So, so I can't imagine a better time to be doing this. Um, I do think that neurotechnologies are gonna be held to a high bar. Mm. And they really need to make a difference soon.
• 26:05
  You know, I, I don't have a timeline in mind, but I just feel that this excitement and this, this enthusiasm has to be met with some real breakthroughs now or in the next couple of years- Interesting...
• 26:17
  in order to maintain this momentum. Okay. And I think, I, I do think that will happen. So you're saying there, there's an excitement, but there's also an obligation and a pressure to deliver? Yeah.
• 26:27
  And that's why we're- Interesting. Interesting.
• 26:28
  Well, it sounds like you are-- you may be the right type of person at the right time for this kind of technology, and it's exciting to, to see Sync Neuro develop and, uh, it's gonna be amazing to watch over the next year.
• 26:41
  So I appreciate you taking time with me and giving me an update. Logan, this was so fun. Thanks for having me here. All right. KC, uh, wish you all the best. Be well.
• 26:49
  [upbeat music] Thanks for listening to Startup Health NOW. We'll be back again with another episode next week. [upbeat music]