Michael Snyder: Insights from medicine’s most-measured man

Transcript

Russ Altman (00:03): This is Stanford Engineering's, The Future of Everything, and I'm your host, Russ Altman. Today, Professor Mike Snyder, from Stanford University, will tell us how he uses wearables and constant monitoring of his physiology to detect small changes that may indicate disease, often before any symptoms are obvious to him or his doctors. It's the future of big, personalized data.

(00:28): There are many things we can measure about human physiology. When we go to the doctor, they can measure our blood, our urine, even our poop for disease. That happens once a year, once every couple of years. We can wear smart watches that measure our heart rate or our oxygen, and we may or may not pay attention to that. But what if we were measuring this stuff constantly, wearables all the time, regular measurement of our blood and other body fluids? What would we be able to learn? Well, Mike Snyder of Stanford University is one of the most measured people in the world.

(01:02): He's collected gigabytes and gigabytes of data about his own physiology over the last several years, and he started to learn some things. In fact, he's learned enough things that he got a hundred other people to do this kind of intense monitoring and he reported in a paper that at least 50 of them, about half, found major medical problems using one or other of these technologies to monitor both their baseline and then changes. So Mike, you're one of the most measured people in the world, and what I mean by that is you've made the most measurements of yourself over the last few years of pretty much anybody. How did this all get started and what's the scientific kind of goal for making all these measurements, which we'll talk about in a second?

Mike Snyder (01:47): Sure. Well, it started a long time ago. Believe it or not, our claim to fame is studying biological systems by collecting big data around them. People used to study genes one at a time and our shtick was let's go in and study all the genes involved in a process, and then proteins, RNA. And then, basically we always wanted to apply it to medicine and then I moved to Stanford, as you probably know, 13 years ago, and it was a great opportunity to do that. We could just start taking some of these approaches we invented and things like that and start getting big data around people and, of course, I thought I'd start with myself.

Russ Altman (02:24): Yeah, I guess the consent issues there are more straightforward, you just have to agree. Okay, just for people who haven't, so this is often called the quantified person or the measured person so give us a sense, first of all, for just what's the basic data that you collect? Where does it come from? I know it involves some wearables but also some biological samples so just take us through the kind of data that you collect and then we'll go through why and what are we learning.

Mike Snyder (02:53): Yeah, sure. It started with omics data. What I mean by that is, for those you don't know, it's like sequencing your genome. That was brand new when we started this, just a few genomes had been sequenced. We just sequenced mine as part of this but we do much, much deeper than that. We always thought genomics is a part of the picture. In fact, I'm going to back up a little bit and just say we envision health as a thousand piece jigsaw puzzle, and the way they measure it today is by collecting about five of those pieces. They're key pieces, mind you, don't get me wrong, but it's not like getting 800 pieces where you have a much clearer picture. And so, what we're trying to do is by collecting this data get that clearer picture.

(03:31): We start with these omics data, meaning your genome, as I said, then all these molecular measurements out of blood. So we'll take common blood draw like you normally do in a doctor's office but we'll just dive deeper on it. We'll measure all your RNA as much as we can, your proteins, your metabolites, your lipids. And then, to be honest, we measure your poop, your microbiome, some of you know that's super important for your health. And then later, as actually the fitness trackers came out, we said, "Well, these are pretty good health monitors, let's try those too." And we put them on the Apple watch and Exists and, son of a gun, those were pretty powerful for measuring health. At the end of the day, we're doing deep clinical testing, these omics I mentioned, which is all the proteins, lipids, and such, and then wearables, and we do questionnaires, stress questionnaires, things like that. Then we do some advanced tests as well.

Russ Altman (04:23): So tell me a little bit about the wearables because I've been at a meeting with you a couple of times where you come in with a lot of stuff hanging on your, if you don't mind me saying, hanging off your body. So go through some of the details of what you're actually measuring.

Mike Snyder (04:37): Yeah, sure. I am pretty wired up so here are my four smart watches, I think you can see.

Russ Altman (04:43): Four smart watches for those who are listening, yes.

Russ Altman (04:46): Yeah, so it's a garment, a Fitbit, and Apple, and then of course my company, we can talk about that if you like, which is a bit higher resolution and lets us measure a little bit more. And so, we have that. I have a continuous glucose. So they'll measure, by the way, heart rate, heart rate variability. They're all pretty good for that, but then skin temperature, some do, some don't, some are accurate, some aren't. Blood oxygen and blood pressure, I would argue none are perfectly accurate but the deltas are good and that's key to this whole business, looking for ...

Russ Altman (05:18): When you say delta, you mean the changes over time might be more accurate than the absolute measurements?

Mike Snyder (05:23): Correct, yeah. Thanks for clarifying. Yeah, absolutely. And that's true, we can see changes even with a, sorry, I almost said crappy, but a crappy device.

Russ Altman (05:35): It's okay, this is YouTube, and radio, and podcasting.

Mike Snyder (05:38): Yeah, you can pick up these shifts pretty easily, and that's the thing about continuous monitors, that's why we like wearables. They track you 24/7, 365 days a year, as long as you keep them charged, and they're just perfect for picking up these shifts. And, I mean, we can get into this if you like but it's how I first discovered my Lyme disease, was because my blood oxygen dropped and my heart rate went up. With the latter I detected with a smartwatch and the former with something called a pulse ox set.

Russ Altman (06:07): Okay. Well, since you mentioned it, let's go right into that because it sounds like a great example. Before that, the reason you have four is because you want to make sure that the data is good? I just want to make sure we understand what the reason for four is. Some of those are redundant measurements but it gives you better accuracy when you can average them or stuff like that?

Mike Snyder (06:24): Well, it's more that they're different resolutions. We're trying to figure out what is the optimal resolution, and the battery drain is a bit of an issue so you want to get the optimal resolution without draining battery because if you drain it fast, people miss data, which isn't so good either. So there is that aspect, but they also measure different things. Some do measure skin temperature, some don't. The blood pressure very few measure and blood oxygen, same thing, so they're measuring different things in a different sensitivities. And so, at the end of the day, we'll get to this too but I got Lyme and I had all devices on. We haven't figured it out yet but I'll figure out which one's going to be most sensitive.

Speaker 1 (07:02): Okay, so let's talk a little bit about Lyme disease. For people who don't think about Lyme disease, it's actually a very difficult diagnosis to make for physicians because it's a tick-borne illness. So people go out into the country, they take a hike, a little innocuous tick, or seemingly innocuous, affixes to their legs and if it's on there long enough and it takes a meal of blood basically from you, then it can transmit this Lyme disease bacteria, which has very insidious symptoms. There is a rash, but then all kinds of things can happen over months and years, and very often are missed by physicians. So tell me what happened in this case of this Lyme disease, I guess, discovery.

Mike Snyder (07:41): Yes. Well, my case is pretty easy to pin down. I spent one day helping my brother put up fences in rural Massachusetts where 55% of ticks are Lyme infested. And two weeks later I'm flying to Norway, and I measure myself all the time as you can tell, including my blood oxygen, and your blood oxygen normally drops on flights. This is actually not very well known. It's known to pilots but very few other people, including flight attendants. It's why you get tired on airlines, by the way, your blood oxygen drops and you get tired. So anyway, my blood oxygen dropped abnormally low, I mean much, much lower. It was 90 median value instead of 96 for that [inaudible 00:08:20].

Russ Altman (08:20): Right, right, okay.

Mike Snyder (08:21): And my heart rate went up, which I saw on my smartwatch. I later learned my skin temperature from my smartwatch also went up but I didn't notice that at the time, that was more subtle. And, when I landed it didn't come back to normal and so it was all pre-symptomatically, no symptoms. I had no bullseye prior to this.

Russ Altman (08:40): Bullseye is the name of the rash that they have for Lyme disease.

Mike Snyder (08:42): Yeah, from Lyme. That's what a lot of people get, not everyone, and I didn't see it anyway. And so, in the end I did get a fever off and on, I knew something was up. Because of the timing, it was two weeks later, I did go to a physician in Norway. I warned him it might be Lyme. He draws blood, sees my immune cells.

Russ Altman (09:02): Wow.

Mike Snyder (09:02): Yeah, he sees my immune cells are up, says, "Mike, you got a bacterial infection, you should take penicillin." And of course my response was, "No, I should have doxycycline." It got a little tense for a few moments there. He did give in but he was very reluctant. My wife is my witness, she speaks Norwegian so that's why I brought her along.

Russ Altman (09:21): Gotcha.

Mike Snyder (09:23): Anyway, he did speak English so it wasn't a problem in the end. But anyway, so he did give me doxycycline. I was going to go above the Arctic Circle and I did not want to be sick so I took it. It cleared it up right away, you do take it two weeks. When I got back I got tested and, sure enough, I was Lyme positive, something called an antibody test. I had the antibodies but I even had some antigens left, the proteins that are left over from the Lyme. It's a well controlled experiment. Just so happens, not randomly, but I gave blood before I left, three days, and I was negative so I had actually acquired, it became what's called sero-positive during that time.

Russ Altman (09:58): This is a really great story because I'm imagining this is the vision of the future that you have, is that there's a constant monitoring, that you can pick up subtle differences that might not have been appreciated before without these measurements. And then, even if you didn't know about Lyme disease, you showed up to a doctor who at least after a couple of tries probably would have figured out what's going on, even if you hadn't given him the big clue. Did you remember a tick at all?

Mike Snyder (10:25): Well, I did have a tick that had not embedded because I checked myself when I came back from this fence putting up episode, and so I don't know that that was the culprit. It's unlikely to be so maybe it was a hidden one. I don't have much hair but maybe it was somehow buried in there. Who knows? And I'm not sure he would have figured it out, to be honest. You're only there for a very short period. He didn't know it was Lyme, he said, "All right."

Russ Altman (10:55): It's probably not very common in Norway.

Mike Snyder (10:58): Yeah, it's not unheard of but it's not super common. I warned him ahead of time though because of the timing, the two weeks. I said, "Look, this could be Lyme, just to give you a heads up." So when I was in there he was primed but he still wasn't ready to go that way. Anyway, I'm not sure it would have come out that way so I do think this is the future. I think, you've heard me rail on medicine before, perhaps, but I think physicians ... And there's nothing ill about it, it's just they only have 15 minutes to spend with you and you have a lot more time to spend with yourself thinking about these things, and so you do have to take your diagnosis into your own hand to some extent.

Russ Altman (11:37): Yeah. Good, so let me ask you about that. Two questions. First of all, is one of the things that you're measuring when you check your blood on a regular basis, would you have discovered the Lyme antibodies through the normal course of this research where you're taking blood samples all the time and doing these measurements? Or is that not one of the things that you routinely check?

Mike Snyder (11:58): It's not one of the things we routinely check. Now, we do check something called CRP, C-reactive protein, which is a sign of infection, could be viral, could be bacterial, could be other things. We do check things but we don't normally check routinely for Lyme, but I actually think wearables are going be the way of the future. Just to continue the story further, we had two years of data on me and I went back and looked at the data and there were four times I was measured by this protein called CRP. One was the Lyme time, two were viral infections, and there was a fourth time, asymptomatic, but I had just as high of this protein, this measurement, as the other times, suggesting I had been ill. And every single time my smartwatch showed I had a high resting heart rate and high skin temperature, every single time.

(12:48): It was retrospectively but every single time we could see it went up before symptoms appeared because they'd record when the symptoms appeared. Basically, that gave us impetus to say, "Hey, we can detect when you're ill before you know it with a smartwatch." And so, we wrote an algorithm, we called it Change of Heart. We thought that was kind of cute. And then, we basically showed it worked on me and it worked on three other people, one of whom got sick twice. Every single time before they recorded symptoms this resting heart rate went up. And so, we think it's a very, very sensitive measure and this was all published in 2017, and then we kept perfecting the algorithm. By the way, it didn't work well for skin temperature because I don't think everyone keeps their watch tight on the wrist. It works for me but it doesn't work for some others. So we basically were improving the algorithms, building a cloud-based infrastructure and then along comes COVID.

Russ Altman (13:43): Yeah, so about that. What is the infrastructure you have for monitoring? You get a lot of data and it sounds like you're very interested in this. This is your life, this is your research, so you're sitting on the plane looking at your oxygen and looking at your heart rate. But I'm imagining that ... What's the vision for the future about how involved an individual would have to be in monitoring this data versus having AI or some other software do all the work so that you can just live your life and not worry about it? Because, right now, it sounds like you're very involved in watching all of this data.

Mike Snyder (14:19): Oh, yeah. I'm a geek and there's a few other people like me out there, but the average person doesn't want to do all this stuff so where it's going to go, I think, is that it's like your car. Your car has a ton of sensors on it. A race car has 400 sensors on it. They don't have 400 dashes, dials on the screen, they distill the data back. Just like your car has a few gauges, gas, a check engine light it's called. It's phenomenal, [inaudible 00:14:46] the thing.

Russ Altman (14:46): Yeah, that's the one we all fear. Check engine, that's the bad one.

Mike Snyder (14:50): So anyway, we have that and that's just typically the main thing.

Russ Altman (14:53): Check body, we're going to have a check body light.

Mike Snyder (14:54): You got it, and that's exactly right. I think that's what we're going to be seeing in the future, and that's how it should run. And so, we built, believe it or not, that system for COVID now, and that's where I was going to go with this, that we can actually detect COVID in advance of symptoms. Retrospectively, it's four days but we built this real time alerting system, meaning we'll follow your background. This is how it's going to be. Follow a person's baseline and look for that jump up, a signal that's abnormal. And resting heart rate turns out to be way, way better than, say, temperature that we're measuring now. Like COVID, half the people don't get a fever, but they all have their heart rate jump up.

Russ Altman (15:32): Can you distinguish it from other viruses?

Mike Snyder (15:35): No, not yet. I hope we might be able to but I honestly don't know. It's not just specifically for viruses, our alerting system, it's a general stress, meaning workplace stress is the number one trigger of, we call them red alerts. It'll give you a red alert if you have one of these abnormal signals, but right now you have to click on it. Soon we'll tell you automatically, you don't have to click. But right now you click on it once a day and you'll see if you got a red day or a green day. Red days could be stress. It also turns out if you run a marathon, some people may know this, your heart rate will be up for a few days after that. That's a red alert. Things like that. So some of it's very easy to contextualize. Some of it, if you're just sitting around and you're not really stressed and somehow you're getting a red alert, something's up. You're either mentally or physically stressed, potentially from a virus.

Russ Altman (16:25): This is The Future of Everything, with Russ Altman. More next with Mike Snyder.

(16:30): Welcome back to The Future of Everything. I'm Russ Altman and I'm speaking with Mike Snyder from Stanford University. In the last segment, Mike told us about how he's doing constant monitoring with wearables and with tests of his physiology. In this segment, he'll tell us about an exciting series of experiments he did with COVID on himself, of course, and he'll also tell us about how he can make measurements from a single drop of blood. That may sound familiar. Mike is aware of that. He'll tell us why this is different. Welcome back to The Future of Everything. I'm your host, Russ Altman, and I'm speaking with Mike Snyder from Stanford University. In the last segment, we talked about this exciting idea of having all these wearables, all of these blood and other bodily fluid samples, to do a real full court press on understanding the state of your physiology, really day-to-day, hour to hour. So Mike, you were telling us about COVID, and I don't think we finished that story. I think you had a personal experience with COVID. So tell me, how did all of these sensors and stuff perform in the setting of COVID?

Mike Snyder (17:34): Yeah, so we have this real time detection system that we've been using and people have been using, it even picks up asymptomatic cases, by the way.

Russ Altman (17:41): Wow.

Mike Snyder (17:42): I do want to warn you, it only works 80% of the time, we have more perfection to do. But it did work for me personally, which is I woke up one morning a little bit congested. Is it allergies? Am I getting something? I honestly didn't know. I still felt pretty good so I did an antigen test and it came out negative. I looked at my smartwatch alerting system and it came out positive. It said red alert. I was due to fly to New York City that day so what did I do? I got on the plane because I listened to my antigen test and not my smartwatch. Wouldn't you know it, the next morning in order to go to the meeting, you have to do a COVID test. Sure enough, I'm bright positive, and so I had to spend a whole week in New York City stuck in a little hotel room, all because I listened to this antigen test.

(18:29): And so, the bottom line is that we think it's more sensitive. It's not as specific, meaning I didn't know I had COVID. That's a drawback, but it is more sensitive than an antigen test. I think it works because, again, we're following you 24/7 and two beats per minute is enough to get a red alert, you can easily see that.

Russ Altman (18:48): And the other great point is that even if it's not COVID, it's not clear that the other people want to be in a meeting with you, even if you have a common cold so I could see the ... And one quick thing before we go onto the next topic. You showed us that you are actually literally wearing four watches right now.

Mike Snyder (19:06): I am. Yep. Here they are.

Russ Altman (19:07): Is anybody working on the single watch solution? Because obviously, in the real world nobody's going to wear four watches.

Mike Snyder (19:13): Yeah, no, they're all converging too, right? They're all starting to measure. More get higher and higher resolution. From our standpoint as a researcher, it's hard to get the data from some of these companies, and so it's one of the reasons we founded our own watch, but there will just be one. Maybe they'll all converge on the same sort of high resolution measuring SBO-2, something called galvanic stress response.

Russ Altman (19:35): Yes. Is there a move to get open standards so that they could all use the same interface to represent the data in the same way? This is asking a lot for competing companies to cooperate, but sometimes they do this. Is there any move in that direction?

Mike Snyder (19:50): Well, I think so. They're all using kind of common devices, PPGs and things like this, so I don't think it's that hard to convert them into common standards, to be honest. And they have a common sharing system like health kit, things like that for collecting all the data. So I think we'll get there. Which one? Oh, win. I'm not going to predict. It's hard to say.

Russ Altman (20:10): Okay. So I want to do a switch to a ... Recently, there was a report out of your lab of sampling a drop of blood and getting a whole bunch of useful information. And forgive me, Mike, but I've heard this story before, it's been in the news. Tell me what you guys have done and is this the same as we've heard about in the context of Theranos, or is this very different?

Mike Snyder (20:31): Well, the concept's the same but the execution's different. Yeah, so obviously our shtick is collecting a lot of data from blood and we've been thinking about this. We spent six years working on this, this is not a fly by night operation, trying to figure out what is the right collection method, getting very fixed volumes turns out to be important. And finding things where the molecules in your blood will be stable and making sure they don't degrade. Because in our system what you do is you do a little prick. So, I guess, to rewind here, yeah, you do a little prick, you take a tiny little droplet.

Russ Altman (21:03): I'm surprised that you're not wearing a black turtleneck. Forgive me.

Mike Snyder (21:09): Well, that's not quite my style. I probably wear the same color pants but everything else isn't quite like that.

Russ Altman (21:14): Okay, I interrupted, I apologize.

Mike Snyder (21:17): No, no worries. And so, you take, for those of you who are geeks, 10 microliters of blood, sometimes 20. It depends from your either fingertip or these days we do it from your shoulder. And the nice thing is you collect this at home so you don't have to go to a doctor's office. We want to transform the whole system, meaning no more going to a doctor where there's a lot of sick people, giving a lot of blood for which they use a tiny little bit to measure things and then give you a report back on something that they compare to everybody else, which isn't the way to do this stuff.

(21:49): So what we're trying to do is collect these little droplets at home. When you're in a native environment, you literally mail it in, FedEx it in, and we've set it up in a way that we think most things are pretty stable. And then, we do our deep data dive where we measure in the lab all your metabolites, lipids, some key molecules called cytokines and proteins, things like that. Then we can actually develop a report and send it back. In the lab we're measuring about 2,200 things, so 2,200 analytes. Many of them are very, very key, including some glucose control molecules are called insulin, something called incretin. This is a big deal because we think we can dissect diabetes into its subtypes with this kind of measurement system.

Russ Altman (22:31): So I'm going to guess that among those 2,000 things some of them are normally clinically measured, things that we normally get with the blood samples that we give, but it must be that many of the things you're measuring are kind of new to measure in a clinical situation. So how do you get clinical validation that these are useful? Do you go through the FDA and get kind of approvals or how does it work when you're measuring new things that nobody has ever measured before?

Mike Snyder (22:58): Yeah, great question. This is a research project as we run it in the lab but it does have a lot of high value molecules. Things like cortisol, you probably have heard about, that's an indicator of stress. These molecules called cytokines, which are stimulators of the immune system. Some of these glucose related molecules, control molecules, some of them are normally measured in the clinic but some aren't that could be pretty valuable, so we are seeing a lot of what other people do. By the way, we're not doing everything. We don't get glucose or LDL, which is pretty important, because it kind of swamps out the system, so you do get them by your standard measures but we'll see a lot more. And we think that gives a clearer picture. A lot of these molecules we're seeing, believe it or not, are up on the FDA website.

(23:41): Some of these are molecules involved in depression or some of your amino acids and things like that that are pretty important to know about, actually. We think what it'll do, they're not FDA approved but I think they will fit into medicine at some point. They'll have to go through the usual rigorous vetting and such, and then I think they will. But right now they can be done under research and they can give you sort of a wellness indicator. We've actually spun off companies who do this sort of stuff. One's called YOLOv, that's actually measuring 650 analytes, and another's called Rhythm, that's actually measuring key analytes, we think, for long COVID. So we're trying to get useful information out of this that the medical system right now doesn't capture and it's the same concept, getting a much, much clearer picture of your health by measuring more things.

Russ Altman (24:33): How is the accuracy of those measurements compared to the old fashioned, gold standard ways of measuring them?

Mike Snyder (24:39): Yeah, it's pretty good. Some analytes aren't as good, meaning because they'll break down or what have you, but many of them are just as good. We do it with a technique called mass spectrometry, which is different from immuno assays, and that has pretty good control, meaning you can see things with a pretty reproducible measurement so it's pretty good. Now, a lot of the things people measure, like we mentioned this protein before, CRP, that thing jumps up a hundred fold when you're ill so you don't have to worry about being 15% off, if that's the case.

Russ Altman (25:14): I see. So the tolerances and how much precision you need is actually different for all 2,000 of these. And so, some measurements, if they're a little noisy, it's acceptable and other ones you really have to nail exactly right, I guess.

Mike Snyder (25:27): Right. But I think the key to all of this, and this is a big concept for us, it's not just collecting big data, it's the longitudinal aspect.

Russ Altman (25:34): Yes.

Mike Snyder (25:34): So being able to see these shifts was key for my Lyme, it was key for COVID, it's key for everything. Know your baseline so you see the shifts. We don't do that enough in medicine. Even when we collect the data, nobody goes back to look at the old points, and this came out from one of the people we were measuring. He was perfectly normal on one of his liver enzymes but at the low end, very constant. And then he actually, for one of his visits, he's part of this measuring group we're doing, he jumped up twice as much but was still in the normal range. Nobody saying anything to him. And so, he came to me ...

Russ Altman (26:06): But for him it was high. For him it was very high.

Mike Snyder (26:09): He came to me and he said, "Mike, what's going on here? I'm up double." And I looked at this and said, "Go get another measurement." It was a week later. So he did and, sure enough, then he shot out a range. So he was on this bad trajectory and then he actually took ... Ironically, he changed his diet and actually it solved the problem. I'm not saying that'll happen for everybody but it did in his case. But it was all about the trajectory, and that's been true, by the way, in one of the other ... So we've spun off a medical version, sorry if this sounds like a plug on this but a medical version that our company, Qubio, does that actually does whole body MRI, which medicine doesn't terribly like, as well as sort of a medically relevant version of what we're trying to do. And, same thing, we've caught people with these longitudinal measurements that are shifting away, and we caught early pancreatic cancer by longitudinal measurements. It's almost never found, but we could see it because of this increased, if you will ...

Russ Altman (27:04): Fascinating. So I guess the final question because this is very exciting and it looks like it's coming to all of us soon. You talked about the importance because of battery and stuff, of getting the right sampling frequency for your wearables. What's the right sampling frequency for these micro-fluidic micro samples that you're doing? Is this the kind of thing you imagine doing every day, every week, every month? It sounds like we really need to learn the rate at which these molecules change in order to catch the things we want to catch.

Mike Snyder (27:34): Yeah, so the answer is I don't know but we're starting quarterly, which is not a bad way because if cancer happens it can go pretty quickly. That seemed like a reasonable place to start, but I also think it's going to depend on what you're at risk for. If you're at risk for diabetes in some of these metabolic things, maybe you do want to get them measured a lot more frequently than if you're at risk for other things. You'd probably want to get those measured more frequently. Like inflammatory diseases, maybe get the cytokines and some of these other inflammatory markers measured more often. So I think it's going to come down to your particular situation but I could see a world where in the future, the Mike Snyder world is that you have a mirror set up.

(28:14): First thing in the morning you're wearing your wearables, it trans, by Bluetooth, over into your mirrors and tells you green lights on all these things, and maybe some yellow lights or red lights on a few things that you need to work on or keep an eye on. And then, you have a finger prick sampling, either that gives you instant read back for a few analytes but for other things you'll mail in and get back a report. It won't make doctors go away, don't get me wrong, it's only going to help physicians if they have this background data to be able to give you better diagnosis of what's going on with your health and if something's popping up.

Russ Altman (28:51): Thanks to Mike Snyder. That was the future of big, personalized data. You've been listening to The Future of Everything with Russ Altman. You can follow me at RB Altman, and you can follow Stanford Engineering at Stanford ENG.