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What’s more important? Lifespan or Health Span? – Michael Geer

Episode Summary

Michael Geer is co-founder and CSO (Chief Strategy Officer) of Humanity Health, a London-based startup that’s building an iPhone app and subscription service designed to help users slow or reverse their rate of aging. Geer’s co-founder Pete Ward has described the app as like “Waze for maximizing healthspan,” that is, their predicted years of healthy functioning. This week Harry grills Geer on the app’s features, the startup’s business model, and the argument for better integration of clinical and digital data into consumers’ everyday health decisions.

The Humanity iPhone app, which is currently being beta-tested by users in the UK, is designed to track various types of health-related data for free, such as exercise levels. At various premium subscription levels, users will be able to track biomarkers in their blood samples and even track the levels of methylation in their DNA. The app’s machine learning algorithms pull together all of this data to produce what the company calls an “H Score.” The big idea is to show well users are doing at slowing their aging—compared to others who have similar profiles or have taken similar actions—and to advise users on what else they could be doing to increase their H Score and their healthspan.

Harry interviews Geer about the startup’s origin story, the app’s features, Humanity Health’s business model, and the argument for better integration of clinical and digital data into consumers’ everyday health decisions.

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Harry Glorikian: On Star Trek the Vulcans have a saying: Live long and prosper. The “AND prosper” part is important, because nobody wants to live a long life, if it comes at the expense of their health and prosperity.

In fact, there’s a growing notion in the healthcare industry what you should really be trying to optimize isn’t your lifespan but your “healthspan,” meaning, the number of years of healthy functioning you can look forward to. 

And that’s the main idea behind a new smartphone app and subscription service being developed by startup based in London called Humanity Health. The company came out of stealth mode in the UK last fall.  It’s testing its iPhone app on beta users in the UK now and will soon open up to users in the US.

The way Humanity’s CEO and co-founder Michael Geer explains it, we can’t affect our chronological age, but we can affect our biological age, if we take the right steps to stay fit and prevent disease. The Humanity app is designed to track various types of health-related data for free, such as exercise levels. At various premium subscription levels users will be able to track biomarkers in their blood samples and even track the levels of methylation in their DNA.

The app’s machine learning algorithms pull together all of this data to produce what the company calls an “H Score.” The big idea is to show how well users are doing at slowing their aging, compared to others who have similar profiles or have taken similar actions, and to advise users on what else they could be doing to increase their H Score and their healthspan.

It’s intriguing stuff. But the jury is still out on whether Geer and his colleagues can scale up a premium health-tech service to millions of customers. That’s one of the questions I covered in my interview with Geer, which we’ll go to right into now.

Harry Glorikian: Michael, welcome to the show.

Michael Geer: Thanks, Harry. Yeah, excited to be on here.

Harry Glorikian: So. Let’s start off like I mean, before we get into the details on the company or what you’re doing there at Humanity, your background is more tech than it is health. So what did you do in the past and what sort of prepared you for starting a health tech company?

Michael Geer: Yeah, for sure. Yeah, so I guess I started off as a failed astronaut, I did aerospace and space. I’ll get there eventually, pay my way in as many of us will end up doing. But yes, then because of that obsession, ended up over in Moscow and ended up starting one of the, you know, being on the founding team of one of the biggest dating sites in the world, Badoo. When I left Badoo, which is around 2010, Those two years right after that, that I had a couple of people close to me got late stage cancer.

And so sitting there in my late 20s feeling invincible, as you do in your late 20s, and you had this success but couldn’t do anything for these two people, felt completely helpless. And so what I guess started searching for at that point was, it started with a specific journey, which was, OK, why are people finding out, you know, late stage about cancer like these? These were two people that were living in cities, they’re middle class. There was no reason why they didn’t have access to medicine or health care. And they were still, you know, finding out stage four in both cases. And so I started going down that rabbit hole. And I guess my engineering background is probably what has led me through my life, whatever, you know, job or business I started. And so just like, OK, why aren’t we screening everybody for cancer? Then the next step was, you know, the main answer was too many false positives in the tests that we screened everybody. Will send people towards a bunch of procedures. They don’t need to kill more people than we save kind of thing.

Michael Geer: And so I had reached out to, being a founder, you start just you know, if you want to learn about something, you just reach out to the top person in that space. I reached out to George Church, he was actually the first person that I asked about genetics. Yeah, he was kind enough to meet with me, answer all my stupid questions. And so it went. I wasn’t planning to start a health tech company. This was more personal, like I need to learn more about this because I don’t want to feel so helpless, because unfortunately, I think this will probably happen, continue to happen. And just on a personal note, my uncle just passed away from cancer a couple of days ago. So it continues to happen.

Harry Glorikian: Sorry.

Michael Geer: Thank you. But I think there is a difference between then and now, as I do have a lot more optimism, because, you know, there’s things like, you know, Grail and companies like that that are really kind of pushing the envelope on early detection. But anyway, getting back to your question, so when I started to believe that we could actually start a company in the space and get into health tech was when I was in so many rooms with all these great scientists, these stem cell researchers, immunologists, people out in the Valley when I moved out there, and they … you know, there’s so many breakthroughs that happen in science and so much known knowns that you’re sitting around in these rooms with the scientists and they’re like, yeah, of course, that’s the way it is. And you’re like, OK, tell me more. And you can see that they’ve done the experiments. They have the data. It shows that that’s the way it is. It’s just these aren’t the same people that know how to get to a million people. You know, the distribution path is quite simple on that side, is you need to get it to a pharma company or something like that, then they have the way to get it to all the doctors and then the doctors can distribute it to people.

Michael Geer: And so what I started to see in the preventive space, and that’s when I dragged in Pete, my co-founder, which we can talk more about, was that there was just a ton of stuff that we already knew in science that we could actually bring out to people on the preventive side, both monitoring their health and also, you know, help directing them and, you know, guiding them and what they can do, that there needed to be more people on the consumer tech side actually bringing that out to the millions of people through that distribution path, because really the pharma-doctor path doesn’t actually work as well or really at all right now for preventive measures.

Harry Glorikian: Well, it’s that, you know, that whole system is not necessarily designed for paying for prevention, it’s paying for, you know, fixing something that’s wrong.

Michael Geer: Yeah, I mean, it’s that I mean, that’s definitely that probably the top one. It’s also, it’s just the system of indications. And then when you have an indication, then you can market to it, like the whole distribution pattern is based on, you need to have a very finite target. And preventive stuff isn’t as finite.

Harry Glorikian: Yeah, yeah. I mean, there are some things that we can clearly, you know, we know what the marker is and we can see the disease that it causes. So you try to get ahead of it. But some of the areas that you guys are looking at, you know, is still, I want to say a work in progress, you know, there’s no, say, defined marker for aging, per se, right, that I know of. What convinced Peter to join, because I think he was someone he was somewhere else, right?

Michael Geer: Yeah, so and then we should go back to the markers for aging because this is a fun conversation I always have with folks. Yeah. Yeah. So with Peter, he was similar. He didn’t want to be an astronaut. He wanted to be an entrepreneur his whole life. So he succeeded and in his very first love. But he was at the beginning of the social networking boom, had an amazing website that called WAYN. It basically allowed you to connect with people around the world, which we kind of take for granted now. And so he had gone on that path and was just, you know, we had met each other in London, had really respected each other. I had actually jumped on and worked with him at WAYN for a couple of years, for a few months. And so we figured out we could, you know, work well together. And so really, he was I would like to say that he was the top of my list. I think he was my list when I wanted to found something new. It was it was like, no, I need I need Pete to come in on this with me. And, you know, we have the same consumer tech side, but he has just a lot of skills with team building and, you know, investment and stuff. That’s just that’s not my usual daily focus. So it makes for a good team. And but it was also important that he believed me and believed in the science. And so that was that was kind of that first process. We actually went on a bunch of what we called at the time, like science fantasy camps. One of them was, Illumina has a program called, or they did, I’m not sure if they still do, “Understand Your Genome.”

Harry Glorikian: Yep. I’ve done it.

Michael Geer: And so we went to this one was in Boston. And so it was like we went there. We actually I think we generally picked up a couple of our future science advisors and that one trip alone. And so, yeah. So after, and again, it’s this kind of process and that’s what we hope humanity will be able to do in a faster process, is get that message out that there is a difference in the rates that we age and that our bodies lose function and we can do something about it. And I think those kind of two years of traveling around on and off with Pete was kind of the very hands on version of what we hope to do at a bigger scale with Humanity. And so once he came around and became a believer like me completely, then then we started looking at what we could actually build.

Harry Glorikian: So tell me, what is Humanity, the company offering to people? What is the, call it the product, or the subscription? Right. Walk me through what it is. And maybe at some point you can sort of also go through what the app is, that sort of pulls all this together so that the person can see their information.

Michael Geer: Yep. Yeah. So our main focus with Humanity is to extend people’s health span, which basically means, you know, increase your, as much as possible, healthy years. So wherever you’re starting from, just keep you either at that level or make you healthier and make sure that that continues as long as possible. Health span, probably a quick way for people to think of it, and biological age, we can get deeper into that, is the idea that, you know, you can have a very unhealthy, you know, 75-year-old or you can have a really healthy, you know, fairly fully functional 75-year-old. And so you want to be that fully functional 75-year-old. And the same thing for the 40-year-old and the 50-year-old. And so our focus is basically to allow people to start to see what actions they can take on a daily basis to basically extend their health span. So basically, we put it in the app as you know, reducing your biological age, which is just a measure of your kind of probability of disease and a measure of your current function of your body. And so the idea is to have all that working in the background, the collection of all that data, the running it through the predictive models, but really to the user just nudges and kind of information that guides them towards doing more the actions on a daily basis that they need to do to, you know, increase their health span.

Harry Glorikian: So how does that differ from, say, I mean, you know, there are all these other, there’s obviously the Apple Watch, right, get up, walk around, breathe, all that good stuff. Then there’s things like the WHOOP band, which, you know, sort of gives you things like stress scores. And, you know, supposedly you could be able to tell whether you had alcohol the night before or not because it, you know, disrupts sleep patterns. And so how does what you guys are putting together, you know, make a difference? I mean, I remember seeing something about taking blood regularly. What are the components that you guys have put together to sort of build a full package?

Michael Geer: Yeah, I think, and what we saw in the space, the questions that Pete and I started asking when we were kind of submerging ourselves in the science, was, OK once we fully believed in this idea that people age at different rates, there’s a thing called a biological age, which is just kind of a coined term of describing that loss of function. Then we started asking very product kind of consumer tech questions like, OK, first of all, can we measure it? And second, very importantly, can we measure it for a low enough price that we could actually bring this to direct to consumer? Because, I mean, we talk about this kind of off camera. But one of the reasons we know each other here is because through Christine, who runs Evidation Health and I for years would always be tagging along to different conferences when I was running the tech companies.

Harry Glorikian: Right

 Michael Geer:And seeing people go through this trouble in those first years. And what me and Christine saw kind of falling by the wayside is all these very motivated people who come into the space. And the next thing you know, all they could talk about is we’re trying to get this deal with this insurance company. That was kind of like the never-ending kind of cycle of optimism and then kind of loss of optimism.

Michael Geer: And so we basically started with, OK, can we measure it and can we do it cheaply enough? And so then we basically, I guess and the reason, the fact that we started at that basic kind of science level, I think, is different than a lot of people started. So like Fitbit would start with, can we measure this particular action, right. Or WHOOP would start with, you know, can we can we help athletes know how much they’ve recovered and how much with exercise the next day. We started much more on the side of, can we just measure people’s function and loss of function in their body and then evolve from once we figured that we could do that and cheaply enough, the idea evolved to, OK, once we do that really well, we just give this feedback loop of are you know, are you becoming younger or are you becoming older in the loss of function since then, we could also monitor all the actions that we’re taking and start to basically change the weightings of the points that they’re getting from those actions and start to actually guide people towards changing this first main thing, which is, you know, is their biological age going up or down?

Harry Glorikian: So when you’re doing one of these blood tests, what are you measuring in a blood test? Right. I could show you the laundry list of stuff that my doctor orders for me. Right. Which, you know, if you don’t know what they are, it’s basically gobbledygook. But just curious.

Michael Geer: Yeah. And I think that’s, I mean, we try to stay out of the weeds presenting this to the user base, but I think talking to investors and talking to other people in the space, the inside baseball on this is, this overconcentration on like moving one marker? It’s kind of also based on what we started with, talking about clinical trials. Clinical trials and those kind of research studies are based on trying to see if one thing affects this other thing. And so you end up with this kind of conglomeration of, you know, cholesterol is bad for you. So whenever we see cholesterol outside of the norm, then we just need to concentrate on getting that one marker down. But I think most people have kind of, most doctors, and I think definitely all scientists now, have come to the understanding that all these things are kind of homeostasis of, and representative of, homeostasis in the body. And so you can’t just concentrate on one marker moved one way or the other. That’s one thing. So, OK, great. Mike, you know, don’t look at one marker. So you look at all the markers. Yeah.

Michael Geer: So what you end up doing is you need to have a longitudinal data set which has future health outcomes. So, basically that you can see the future. Right. And so, you know, and so the examples of this is like UK Biobank, Estonian Biobank, Framingham in Massachusetts, you got Jackson Heart Study. And so, you know, the future health outcomes. And then luckily, in many cases, you have past markers that have biomarkers that have been taken. And this, you know, example, the clinical markers, the analytes in the blood. And so really what ends up happening at this point, although one of our SABs has kind of taken this to the next level, is a lot of times you end up with the common panels. So your lipid panel, your full blood count, that sort of stuff, you end up with, those are the markers that you want to grab, because those are markers you can compare to that longitudinal data that has the health outcomes. So you can do your models. Kristen Fortney, just give a shout out to one of our SABs, has a company BioAge. She took it to the next level because a lot of these bio banks actually have stored samples. And so she would take the samples off the shelf and measure a lot more analytes. The reason why the first part is actually very useful is those analytes end up being very cheap and the same thing.

Harry Glorikian: Right.

Michael Geer: So you kind of actually want to keep on that level. You want to you want to say, hey, I want that $5 panel, that $8 panel and put them together. And then that’s going to give me a predictive model. And so if I can get to that point, which we can, then that’s better than, you know, the $1,000.

Harry Glorikian: No, no. I mean, but, you know, like I was talking to Joel Dudley from Tempus and they’re trying to basically off of one sample, do every, you know, thing you can do on it and storing that because they know that over time like that, data set is going to have more and more value that that will be created. Right. So it’s sort of what do I do today versus what should I be doing to get ready for tomorrow?

Michael Geer: So there’s two things there. And, you know, there’s great people like Mike Snyder out at Stanford in the precision medicine kind of personalized medicine space. Right. And the stuff that they’re doing is super valuable. They’re basically, yeah, they’re getting every marker on everything and they’re like highly phenotyping, as they say, kind of people. The thing is, when you do then go to bring that to the masses, you do need to go through a process of basically whittling it down to what are the markers we can actually collect at any time, because that that kind of limits your ability to actually bring the service to a user. Right.

Harry Glorikian: So there’s a basic subscription and then I think a premium subscription. I mean, there’s, trying to figure it out from reading a bunch of stuff which isn’t clear, necessarily clear on the website.

Michael Geer: Coming out of stealth, we’re still in closed beta. So, yeah, we’re still a little bit stealthy.

Harry Glorikian: So what’s going to be the offering and what is somebody’s get for what? I guess.

Michael Geer: Yeah. So I mean, like anything, these things will iterate. But right now, so we brought in 70 alpha users, fully paid alpha users in the UK, which is not actually traditional. Usually you bring in people for free. But we wanted to see if people were willing to pay different prices to get the service. 

Harry Glorikian: I want to pause the interview right here because just as Michael was explaining the company’s pricing model, out Internet connection dropped. I followed up with him later and got the details by email.

Michael explained that the company is currently testing different price points for its different subscription levels with its test customers in the UK.  Some of the tracking features will be available for free. For an entry-level subscription fee, customers will get insight into their biological age and what actions are working for people like them. The company is currently testing a price of around $30 per year. And one level up from that, customers will be able to send in blood samples for clinical tests of common biomarkers like lipid levels, for a fee of around $100 per quarter. And for an even higher fee of around $300 per quarter, the company will analyze customers’ DNA methylation, which is thought to be one indicator of aging.

Michael wrote to me, quote, “Pete and I have built freemium applications with millions of subscribers in multiple past projects and really love its ability to deliver more good to more people globally,” unquote. Okay, back to the interview.

Michael Geer: And then all data comes into different predictive models that we have and then we have a composite, kinda master model and the accuracy, you know, as you combine those models becomes higher and higher. Our goal, though, is definitely to make the digital side as predictive as possible, which I think I mean, we can either get into it or not. But the frequency of measurements, you know, all this kind of stuff plays into how predictive a model can be and obviously your data set with the future outcomes. And so we think there’s no kind of mathematical or science reason why the digital biomarkers can’t be highly predictive.

Harry Glorikian: Well, I mean, there’s always stuff you can’t see that’s inside. Right. That’s happening at a different level. I mean, if you look at all the work that’s happening with, you know, the Oura ring or now that, you know, there was something on the Apple Watch. Seeing certain physiological changes ahead of time, you can sort of predict what’s going to happen. If you could actually, like you said, Grail and you know, some of the other companies out there like Garden, they’re looking at blood where you can see, you know, very small changes that might predict some future state. But, so look….

Michael Geer: On that point, I think the future is definitely, … From consumer tech, it’s all funnels. And so my mind is always thinking funnels, you know, but in the medical space, you would call it triaging or, you know. So I think the future is definitely that you start off with a digital, you detect something. It might not be clear exactly what it is. You then you then get bumped up to your GP or your you know, your family doctor or, you know, you go through kind of a telemedicine, go through PWN into your Grail test, if they think that that’s like the next step. All that’s built out. And honestly, I think you’re 2021 is going to be quite a year for, like, all that stuff to finally come to fruition at least in its first kind of prototype form of that that whole funnel of health that make sure that we’re much more protected than we are.

Harry Glorikian: Yeah. I mean look, so, you know, we can both agree that the medical establishment, which, you know, I have a, I’m trying to have my feet in both spaces because they’re colliding, as you know, definitely would say, look, if you’re more active, it’s you know, you’re going to be healthier than when you’re less active. Right. Couch potato versus somebody that at least goes for a walk eating unprocessed foods, right, is healthier than eating a lot of, like, snacks. Funny, because my son said to me, oh, my, I hate so many Cheetos last night. I feel like I have a rock in my… So clearly not a good thing to do. Right. Meditation can reduce stress. I keep trying to impress on them that they should pick this up as a habit. Not when you’re older, like I am. Right. And that decent sleep every day makes a huge difference, because of recovery and so forth. I’m sure the medical establishment would say, like, look, if you can track these things and make yourself better, that’s probably good. And then, OK, if you can look at bloodwork and DNA genotyping and methylation, even better. Right. Which is Ventner’s old company, Longevity, is a company that’s trying to do a lot of that stuff. What is Humanity adding to this equation? What is the argument that distills all this data down to what you’re calling, I believe it’s an H Score.

Michael Geer: Yep, yep. So the. So there’s kind of two things missing at the moment, and they exist in different pieces, in different places. The first is on the holistic actual connecting your biomarkers with these longitudinal data sets that have the future health outcomes. Like the real predictive. So it’s it sounds a little inside baseball, but a lot of these systems are actually built on a different paradigm. And a lot of the systems are actually built on a bunch of cobbled together meta-studies of clinical trials. Which, as people that kind of focus on the on the space, you know, everything goes to zero. It’s like a statics course. It’s like everything kind of just evens out. And so a lot of the stuff is based on kind of picking and choosing which kind of meta studies you believe in, which then dictates what means you’re being healthier and what means you’re not. And so the thing that me and Pete wanted to make sure is that this thing is really built on real data because you could just as easily, you know, just say, OK, what do you what are you doing? OK, here is the US (or) WHO or some organization says that this is healthy. So this is what this is what your score is going to be. But we have the data. So why don’t we actually be sure about it and actually build it on these models? So that’s one piece. 

Michael Geer: The Humanity Score is the ability for giving points based on we’re seeing those actions actually play out in that biological age. And so, again, it’s not this is not this based on what people recommend generally, because as you well know, like as we grew up over the years, you know, recommendations have changed wildly. So and that’s not to say that they weren’t based on the best kind of knowledge at the time. You know, maybe, sometimes not. But so the recommendations shouldn’t be the basis of knowing what actions I should take. But the last piece of that is, like all of us are different. And I think everybody, all doctors and definitely scientists can agree on that. And so being able to actually say this action and these combination of actions, that’s the important part. The combination of actions. The Humanity Score allows us to dynamically, you know, change the score based on what we see in your biological age result. And so I’ll give you one example. This is an example. So if you didn’t sleep very well last night and you ate badly the day before 2:00 and then you got up early and you went for a 5K run, what you over time, what you see and a lot of these kind of longitudinal data is that you’re actually being less healthy going out for that 5K run. You’re actually, you’re stressing your body too far. And I mean, this is the you know, this is what it seems the data saying. And so you can’t just single out actions and just say, hey, you should run more. Hey, you should do this more, because the combination of those actions is very vital to whether it’s healthy or not, so that the Humanity Score allows us to kind of put all those together to help them know if they’re heading in the right direction. And so a single score that pulls together all these things to give you. One anecdote also is a lot of the people that we see now coming into the app or a bunch of them, if they’re very healthy, a lot of times for some of them, that means the high intensity training like, you know, five mornings a week. But these same people then go to their desk and they sit there without moving for the next the next eight hours. Right.

Harry Glorikian: That would be me. That would definitely be me.

Michael Geer: Some people, maybe my co-founders as well. And so what’s and but we know this constant touchstone where you can basically see what is the next action I can do to increase my score. And then you have this one score. It just is much better from a user motivation side than if you go into, I won’t name any particular company, but if you go into their app and you need to go to your HRV chart and you need to go to your steps chart and you need to go to that, it’s like great, a lot of data, but it’s not really guiding me in the direction I need to go.

Harry Glorikian: Yeah, I mean, there’s a couple of companies, right, that have tried to come up with this sort of aggregated score. It’s funny because I know some of these and I know like couples, literally husband and wife will be almost competing on which score was better. Right. So let’s you know, we’re talking about an awful lot of data coming from a lot of different sources. And so what do you guys, how does machine learning play a role here? You know, what are you guys doing in a sense? And, you know, when I talk about A.I., I think it’s just like, OK, here’s my toolbox and I’ve got all these tools. And depending on what I’m trying to fix or what I’m trying to work on, I’m going to pull out this wrench or a hammer, I think. But it’s part of the same toolbox. So how are you guys approaching this? Of course, without giving away the secret sauce of what are you guys doing? What patterns do you hope to detect and what predictions are you hoping to provide for users?

Michael Geer: Yeah, I mean, our aim is really on the one side that biological age, make it as predictive as possible. But as we go forward, I think the thing that we can do that that hasn’t been done before is we are actually trying to score the actions in combination of actions that you are taking, not the user base, but you are taking. And so then, of course, across the database of all users, we can match you with people like you. So on all the attributes, not just not just your blood biomarkers or digital markers, but also your activity rates and other things. And we can start to actually learn across that, you know, bio twin or whatever you want to call it, of Harry, we can start to feed back to you, OK, you might want to try this action. You might want to do more of this action because it seems to be working on all your bio twins within the user base.

Harry Glorikian: This is Harry again. Our Internet connection cut out one more time while Michael was explaining how the app will track users’ eating habits and nutrition. The basic idea is just that the app won’t be counting every meal or every calorie.

Michael Geer: The focus will not be on trying to make sure that you tell us every single kind of vegetable portion that you that you give us. We’re trying to be as agnostic as possible to the data we’re taking in. And so if you are tracking that in quite detail in another app, you know, we’re looking to hook in through APIs and through Apple Health with as many of those kind of apps so that your data doesn’t replace. The biggest things that we’ll be capturing is kind of the type of your diet, the frequency of your diet and kind of the time window. And those will be the main things that we come up in in the beginning. That’s..

Harry Glorikian:How do you make that less burdensome to the you know, because I think to myself I’m like, crap, I’m spending so much time, like trying to track everything that 

Michael Geer: I mean, that’s the thing. Right. And that’s where Pete and I, my background is in. The good news is that a lot of this stuff is already quite well connected to most of the stuff we’re collecting on you is automated. So you just go about your day and, you know, the data comes in. And so it’s coming through your wearable right now, most of it. So we’re building on iOS first, so all of that stuff’s coming into your Apple Health. We pull it out of HealthKit and then you don’t have to do anything as a user. You basically just see your points racking up and you can get guidance on what you can do to increase your score more. And we’ll look to do that on everything that we’re tracking, not just nutrition, but, you know, not just activity, but each thing that we start to expand and kind of we want to collect as much of your lifestyle actions as possible so that the model can learn from it and become more accurate.

Harry Glorikian: So let’s jump back for a second. Right. So. You’re using all these older, you know, the Framingham heart study, et cetera, to build some sort of model that shows that with certain marker changes, biological age changes versus chronological age. But then is the assumption that you have to actually change some of those — that you might be able to change that biological age?

Michael Geer: Yeah, I mean, that’s a that’s exactly it. You basically have a, and this isn’t new its just been built on I would say better data. 

Harry Glorikian: Oh, no, it’s not, it’s definitely not new.

Michael Geer: Certainly, you know, what I touch on is kind of the example of like the old ways. It’s probably just more like the version one or two. And this is like the version three with cholesterol. You know that the reason why that became such a focus is because so many people that came in with heart attacks and when they started doing, you know, you know, bigger research studies as they saw that they had high cholesterol, it was like, you know, the person that was always in the room when the money got stolen kind of thing. Right. And so this is this is just expanding upon, that is you’re looking at as many markers as you have in these longitudinal data sets and you’re able to come up with a weighted probability of all the all the future diseases that ended up happening in that dataset, whether it be Framingham or NHANES or UK Biobank.

Harry Glorikian: So is there, is there any data that, you know that that and maybe you guys are starting to generate it, but you know where this health monitoring service can change morbidity and mortality across killers like, you know, cardiovascular, metabolic, et cetera?

Michael Geer: Yeah, the there’s a lot of examples of it. There’s I think the what we try to always do is keep it like the most highly accepted ones when we talk to talk to people about it. I think there’s a lot of newer work that that’s been very specific, but there’s just a ton of work that actually led to all those recommendations that we ended up with anyway. Right. They would do kind of these is more controlled studies where, you know, this group would do this amount of exercise in this group wouldn’t. And they tried to control for all the factors within those two groups. And so there’s a there’s a ton of kind of peer reviewed research studies that basically show that these different interventions actually did change the future health outcomes, whether, you know, reduce the occurrence of cancer or reduce the occurrence of heart attack. And so all these things have very much been proven. I think that thing, the new thing or the other thing that we’re trying to really bring is not changing any of that. What we’re trying to do is bring to consumers the ability to track it very closely, very accurately, and get that combinatorial, you know, of those actions. And so you could actually see like the like the example I was giving earlier, like better sleep plus the diet. Plus this amount of exercise is the perfect kind of optimal for you to really increase your health span. And that’s the difference. I wouldn’t say it’s a difference in the accepted …. we never actually go into a room and kind of even like more traditional kind of, you know, on the on the medicine side, and no one really, as you said at all, these concepts are accepted already fully. It’s more how do we actually deliver that to consumers at scale? And I think that’s what we’re that’s what we’re trying to tackle.

Harry Glorikian: Yeah, that’s what I was going to go to next, which is, you know, you and Peter have like a lot of experience on digital products and services used by hundreds of millions of people. Right. Do you feel like Humanity is scalable in the same way?

Michael Geer: Yeah, and I think I think part of that is, is you start with the, I think I have a slide in one of my old presentations. I’ll give it at conferences. The you know, you’ve got to, if you want a mainstream application that reaches hundreds of millions of people, you need to focus on a kind of a mainstream need for lack of a better word. You might say that Badoo, I would say Badoo kind of allowed you, the dating site that I that I started and the founding team, the you know, it allows you to meet new people. That was a tag line. But some would say, OK, it’s sex. And so the sex sells, sex sells. So if you build something, you’re probably going to get people to use it. And I think health is another one of those. Right. And I think that’s. That makes us very optimistic that we can we can do it as long as we have the right team around us.

Harry Glorikian: And that was going to be my next question. So. Right. So what evidence do you have the consumers are, you know, really motivated and of course, there’s, look, you know, helping Evidation and, you know, talking to Christine, there’s always a group of people, right, that that are incredibly motivated to do these things. But now are you’re talking about a large mass of people. You’re saying you’ve got to collect this data. It’ll get better if you have a wearable. You know, you’ve got to take this blood work every three months. And how do you keep them going over time? Like, how do we know that they’re motivated?

Michael Geer: I think the thing that captures a lot of people’s attention and captured me and Pete’s attention and captures users’ attention, and it sounds too simple to be true, but the actual focus on aging is very motivating. Just to give you a couple of anecdotes from our alpha users, you know, one of them, one of them saw her rate of aging and very soon after moved to another country where she could live in a place where she could go hiking a lot. We you know, we saw another person. We actually heard this a couple of times from users where they basically when they got their first rate of aging, they basically went for a run right afterward. Actually, this is the thing that’s realistically going to make them younger. But the fact is that seeing your rate of aging as it kind of cuts through all the more nebulous stuff, when people say be healthier, you can say be healthier to a room of 10 people and they probably have, you know, 10 or eight different ideas of what that means. Right.

Harry Glorikian: There was a video, I think that somebody created that, you know, you could put your picture in there and it would actually age you. And I think for a lot of younger people, it freaked them out, right, because they never think about it. And then to see yourself, maybe you guys need to add that as a part of the service. If you continue down this route, you could look like this.

Michael Geer: And we will, because I think I think the other thing the other thing that you realize when you, there’s things that need to be very strict and serious. Right. And there’s but in that slide, the data that you present to the user, you know, the anything you present to the user that’s about their health needs to be dead on. Right. But the way that you capture their attention and the way that you motivate them to do things outside of that first rule, you know, we need to use all the all the tricks that people all the kind of methods that people, you know, say are bad with Facebook or some other service. Like I think we all kind of agree, like it would be so much better if those methods were used to actually make us healthier and happier, right

Harry Glorikian: No, no. I mean, you know, we always found that gamification and reward systems and all those things that sort of motivate people to do things that they’re critical to call it, changing a bad habit, right, and trying to motivate, you know, people to be healthier, I mean, I’m sure that there are physicians that are listening to this going, I can’t get my patient to do what I need them to do. What are you guys talking about? But I think that some of these technologies and some of these interactivity of just nudging someone. You know, it does get them to think about things.

Michael Geer: I think the, so the example that I always give is so when you come from the outside, let’s say Pete and I are coming from the outside here. We’re consumer tech folks. We there’s never been a popular or, you know, mass scale product that didn’t have feedback loops. And so when you go to and this isn’t a criticism of the of the doctors, but it’s just kind of a, you shouldn’t expect something unless you have that feedback loop. So if you if you put a photo up on Facebook and no one likes it or comments on it, like how many more photos do you think that person is going to post on Facebook? None, right? It’s you’ve got to have that feedback loop of, I did something and now I see the reaction. Right. And so when you go to a doctor like once a year and your doctor kind of looks at your chart and you’re kind of like, you’re ranging a little bit out of norm, but you’re not doing anything critical. And they’re like, you need to be healthier, you need to exercise more. And you’re like and you probably leave that meeting with the doctor like semi-motivated or at least thinking about it. And then but what happens the next day? Like what happens if you go for a run and then what do you look at getting another blood test? You’re not getting any kind of real feedback. And so getting the feedback loops really tight is you can’t expect the motivation without it. And so that’s kind of table stakes. And I think a lot of times people start to espouse that people are never going to be motivated. But it’s the system needs to just be you know, it needs to be a better kind of loop created.

Harry Glorikian: So how does how does a patient take this and then interact with their physician or the medical establishment or so forth?

Michael Geer: Yeah, I mean, that’s one of the one of the things we thought really deeply about is so when you’re making something like this and anybody that is making any app or any kind of service that collects any biomarkers knows that you will come across things that, you know, need more attention or they seem like they need more attention. Right. And so one of the things that we already do is we do a kind of physician oversight on top of the blood markers before they come back into the system. And we basically triage people out to their GP and make sure that they can, you know, hand those results to the GP. We do that whole system to make sure that anything that looks like it might be further out of the norm is actually brought to the user’s attention and they know the next step they should take. I think that can be done at an even more seamless level telemedicine and different things, you see this with, you know, genetic testing already in the consumer spaces, some of the better companies will set you up. So Color. This was even years ago when I did Color for the first time, which does, you know, cancer genetic markers. You know, that part of their service is you got a genetic counseling session. And I think that’s what we touched on earlier about the kind of like funnel of preventative. And then when something might be detected, even, you know, that handoff.

Harry Glorikian: Yeah. I mean, this thing here, it’ll take my measurement for free. Yeah, exactly. But, you know, then it has the subscription service where there’s a machine learning algorithm which will say something is wrong and then it’ll elevated to a physician if, you know, if it’s completely out of line. So I totally understand the process. But, so, what’s the long-term vision? Is it a consumer product? Is it something where you’re you know, you’ve got industry partnerships with either health care providers or insurers or drug developers? What’s the plan?

Michael Geer: Yeah, I think when we, when people that kind of did services that got to a larger level, the method that’s in we’ll use this on Humanity because it’s worked for us so far is you start direct to consumer. You get that. Products. You want that that direct interchange with the consumer. Right. You then the next step is, it’s a very easy step is to be to see or then other people that have connection with a lot of people then distribute your products directly to those other people. I think the bigger, bigger vision is where we got to kind of with AnchorFree, which is the consumer VPN that I that I help run out in the valley, which had 700 million people. As you start to actually try to lift and kind of effect the market as a as a whole set with the consumer vendors, we basically started refusing to allow any government agencies or anything to see our servers and we started to affect policy on a kind of a larger level and different countries in the sense of humanity. We want to be super open and collaborative. And so, you know, our model is, is consumer subscription model. We don’t want to be, we don’t we don’t have a need to lock down IP. We don’t have a need to you know, we’re just doing a consumer. Then we’re going to get IP, then we’re going to have a license, licensing kind of model. Our mission is to have that kind of that subscription model bring as much value into the free portion so that it’s as radically inclusive as possible and then preserving the privacy of that data, allow modeling on that data that can help raise all ships. And in the research space, it and that’s yeah, that’s kind of the five-year plan and probably that’s the 15-year plan. But, you know, you see what happens as you go.

Harry Glorikian: Awesome. Well, it was great to catch up with you and talk to you. Appreciate the time. I’m super curious to see how this evolution comes out and. You know, maybe one of these days we can hop on and, you know, if there’s anonymized data, I’d love to see what you guys are seeing, always super interesting. So uh excellent I actually look forward to it.

Michael Geer: Thanks, Harry.

Harry Glorikian: That’s it for this week’s show. We’ve made more than 50 episodes of MoneyBall Medicine, and you can find all of them at glorikian dot com forward-slash podcast. You can follow me on Twitter at hglorikian. If you like the show, please do us a favor and leave a rating and review at Apple Podcasts. Thanks, and we’ll be back soon with our next interview.


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