This blog post was written as an unedited response to Zara Stone’s inquiry about Q Bio for her article in The Information.

We’ve never thought of ourselves as just an elective whole-body MRI company. We believe that using single modalities to comprehensively assess health risk and disease in the human body is primitive and error prone. Companies use millions of data points to forecast the weather and target ads and other content at us. Why do we limit our models of human health and pathology to single modality measurements at a point in time? 

Q Bio is a deep technology company operating at the intersection of AI/ML, Physics and Biology, focused on making holistic clinical digital twins a reality because we think they have a huge number of applications in healthcare. We do use MRI to analyze an individual’s anatomy in our prototype digital twin platform, which has been running out of a Redwood City pilot site for early adopters. But anatomical information is just one piece of the puzzle. We also gather genetics, medical/family history, lifestyle, vitals and comprehensive biochemistry adding up to about 3 billion data points taken in less than 60 minutes resulting in the most comprehensive model of human physiology built from clinical quality data ever assembled. Our algorithms then can intelligently summarize the most salient existential risks for an individual in a way that doesn’t overload a clinician and makes it easy to track changes in a person’s risk over time.

We use MRI because it is currently the only FDA approved technology we have to probe anatomy with reasonably good resolution and without ionizing radiation. MRI is optimized for acute symptomatic diagnosis (meaning the doctor already has an idea of what they are looking for), so it doesn’t have to be reproducible, it is more artistic photography than a scientific tool (since it is optimized for and limited by human interpretation). Because it is slow, expensive, and relatively subjective, it is often reserved as the last stop in medicine when a doctor is trying to diagnose a patient for a wide variety of possible indications. So you have to be very careful how you use MRI in proactive ways responsibly and we have spent a lot of time designing our protocol to focus on the most prevalent existential threats in the population using multiple dimensions and modalities for each risk. 

This has enabled clinicians to easily correlate multiple pieces of data to find really nasty, bad things very early, where each individual piece of data by itself may not be too alarming or lack specificity, but together they are very concerning. The large number of physicians that trust and use our platform is a testament to that. At the same time, a key part of our R&D since our founding has been developing a superior modality to MRI that addresses its shortcomings for analyzing human anatomy and we have successfully done that.

Given the potential of magnetic resonance to yield information beyond what even an MRI takes qualitative pictures of, we have built hardware and software technology to give a complete picture of what magnetic resonance can tell us about the body, down to the most fundamental physics. Today, this yields faster scans on cheaper hardware, as well as a wealth of information which could not be measured by today’s MRI technology. We’re looking forward to sharing more about this technology in the future, because it is really the key to making the Gemini platform available to everyone, and has a lot of other exciting applications.

This lede is admittedly a tease, but we can’t help feeling hopeful as vaccinations continue to roll-out and we return back to the office here at Q Bio.  When we first closed down our offices and our Q Center to go into shelter-in-place on March 11, 2020, we also started researching the early clinical tests and data available to determine what we could do to help our employees, our members, and our community.  In addition to quickly procuring personal protective equipment (PPE) and at-home RT-PCR saliva tests for active monitoring and safety, we also researched serological SARS-CoV-2 antibody titer test options. 

When we re-opened our service in May 2020 with all new safety and hygiene policies in place, we also offered these new tests to members as part of our Q Exam. At that time, antibody tests early in the pandemic helped members confirm whether that “really bad cold” they had in late February really was COVID or not, and whether they already potentially had antibodies from COVID exposure.  Our goal, as always, is to provide clinically-relevant data to our members and their chosen care providers to empower them to make informed decisions and have peace of mind. 

Today, as we see more and more members who have been vaccinated coming back into our center, the information value of this antibody test is no longer as relevant. We are seeing presence of antibody titers due to either past infection or a positive result from vaccination, and “false positives” or “false negatives” depending on how different people have reacted to the vaccine. The test was meant for confirming the presence of antibodies from having had an active case of SARS-CoV-2. The test was not meant for confirming whether vaccination is effective. The amazing science behind mRNA stimulates production of protein spikes that prepare the body to fight the virus, but it does not necessarily mean that the body will have a full immune response to actual SARS-CoV-2 virus. In short, we are not testing for protein spikes production or overall immune response and this is confusing and anxiety-inducing. More importantly, the information from this test also doesn’t change recommended behavior and is not recommended by CDC to assess immunity.

The best recommendation: get vaccinated.

So it is a sign of our hopeful times that, as of today, April 19, 2021, — almost a year to the date when we first started sourcing and procuring tests, — we are happy to retire the blood COVID antibody titer test. To all our members and Q Bio friends here in California, with vaccines now available for everyone ages 16 and older, if you haven’t already, go check out myturn.ca.gov and get your shot!

In the beginning of high school in Athens, Greece (my hometown), I had to decide which path I should focus on, which was easy. I had always been good at mathematics, physics, chemistry, and biology — I didn’t need to study a lot, and could easily grasp the ideas. But in history and literature, I would spend hours studying to achieve a high score. The last year of high school, after taking the National Exams, I was required to rank the schools based on my preference. That was one of the hardest decisions for me; all the good students were selecting either Medicine or Engineering. I knew I couldn’t be a Medical Doctor, as I’m scared of blood, and Electrical or Mechanical Engineering was not very interesting to me.

A new school, the School of Applied Mathematics and Physics, had been founded a few years earlier within the National Technical University of Athens. It was not a typical engineering school, but was rather teaching an array of basic scientific fields and their applications. Against the advice of many teachers, who insisted there would be no clear career path after such a program, I proceeded and put it on my list. I graduated with a Masters of Engineering in Applied Mathematics and Physics. During the fourth year of my studies, I took an introductory course in medical physics, and this was the “aha” moment. 

So Much More Than Pictures

I left Greece in 2009 to come to the US to pursue PhD studies in biomedical engineering, and I immediately joined an MRI lab. Since then, medical images have been my focus. I strongly believe that images are more than pictures; they are the shades of gray which uniquely describe the underlying biology. After completing my PhD, I joined MD Anderson Cancer Center (MDACC) and worked on radiomics/radiogenomics for brain tumors. During my first days at MDACC I realized that the clinical evaluation to determine treatment effectiveness of lesions or tumors is primarily based on the use of a pair of calipers across the vertical and horizontal axes in order to determine whether the lesion is growing or not. I struggled with the fact that it was so myopic; to me, we were only looking at the top of the iceberg. Since lesions, tumors, and organs in general have multiple dimensions — structural, functional, and phenotypic features that characterize them, all of which are non-invasively captured by medical imaging, I knew we needed to leverage that data and find the unique links to the underlying biology. At MDACC, I focused on radiomics, hoping to develop models that would lead to individualized therapies.

After speaking with Jeff Kaditz, Thomas Witzel, and the Q Bio team, I realized there was an opportunity to work on something even bigger: what if we offered the whole-body scan and image-derived data to everyone? As Lead Image Processing Engineer, I’m excited to see not only cancer patients benefiting from this technology, but everyone. I was hesitant to leave academia, because I mistakenly thought that in industry research was defined by marketing goals. This is not true at Q Bio, whose mission is to make proactive, individualized, accessible healthcare available to everyone. I’m excited to work on this mission. Last but not least, I’m excited to interact with a multidisciplinary team and learn every day.

In the recent episode of Hyper Wellbeing podcast, our Founder/CEO Jeff Kaditz begins with coronavirus chat. He goes on to explain that most medical knowledge today is probably incorrect or heavily biased. That there’s almost nothing a doctor does that couldn’t have been done 200 years ago in terms of the information.

He presents his vision to run ‘search engines for the body’ and turn healthcare into hard science. Key topics: Multiscale Digital Models of Human Biology; Turning Health into a Hard Science; Quantified Health, Wellness and Aging

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Full transcript (lightly edited for clarity) follows:

Lee ​​S. Dryburgh: Hello and welcome to the Quantified Health, Wellness and Aging Podcast. Today we have our twelfth guest Jeff Kaditz, the CEO of Q Bio. Welcome, Jeff.

Jeff Kaditz: Hi, Lee. How are you doing?

Lee: Well, do you have 20 minutes? This is meant to be a one in a 100 year event taking place at the moment. I don’t mean this podcast [laughter], I mean this pandemic. Let’s just put it this way, I actually went to bed last night and knew we had a podcast today and then I only remembered when the alarm for it went one hour ago and that was because somehow my mind went back to yesterday and I got the days mixed up. I’ve been rolling out of bed straight into looking at coronavirus, COVID-19 and working way later than I normally do and going back to bed on it again. So, it’s been tough. You?

Jeff: I’ve been isolated for the last two weeks in the Tetons in Wyoming so it all feels a little bit like watching a science fiction movie play out. It’s terrifying and it’s fascinating at the same time.

Lee: The last few days I’ve been going from, well, it first hit me a week ago last Tuesday when a friend texted me and said hey, a group of her friends have it. I’m in a country bordering northern Italy. When I heard the details of some people in the group in their twenties like struggling to breathe, losing consciousness, finding it hell, a head that feels it’s going to explode, labored breathing. I’m like damn, that doesn’t sound like flu to me. The last thing I’d remembered was seeing Trump on TV saying hey, it’s a flu and there is 15 cases and by April it’ll be gone.

So that night I started looking and then I was like hang on, this looks back-of the-envelope calculations like you’re going to have half a million to 1.2 million dead in the States alone. Then I calculated the shortness of ventilators, beds and I was just perplexed at the disparity between my calculations and television and I just went on it full time. Now, 10 days later, over 10 days later, I swing between a panic and a relaxness. I’ve eventually got the maths together to know why there’s such a wide variation, but even then it’s quite extreme because you have like Elon Musk now, saying hey, no need for panic, be calm, indicating it’s not such a big thing.

And then you’ve got David Sinclair, Mark Hyman and others backed with the kind of figures I had. But luckily in the last few hours I’m back to I would say a 0.6 case fatality rate which is way better than the one to three I had 10 days ago. But there’s just so much surrounding this and its an economic toll also. It’s not just a human toll. When I look at the economic toll, that’s harder to begin to work out because it depends upon the human toll, but we’re not going back to life the way it was in any case.

Jeff: No, I think about that a lot. One of the interesting things I’ve been thinking about is I’ve been kind of reading more and more about the flu, the Spanish flu in 1918, and I’ve wondered how the world is much smaller now and there’s a lot more information and information travels a lot faster than it used to then. I’m wondering if there were short-lived cultural changes that happened after 1918 that eventually were lost because we didn’t have the internet which some say is in a sense a backup of society’s memory. And I’m wondering if there’s going to be changes that are much longer lived now simply because in 20 years, people are going to go search and see the panic that was caused in videos and news from today. Whereas, 20 years after 1918 that could have easily been lost if you were born after it. And so it’s interesting to see, I’m interested to see how sticky some of these changes are and if the internet has an effect on that.

Lee: Yeah. And I could never have imagined how quick society can change. I went to the supermarket yesterday and I’m designated a time because earlier is for the elderly. And then around the supermarket aisles people are scared of each other and not looking forward to meeting another in passing and trying to force a meter between them. And then there are barriers up at the cash registers and the clerks have masks on. But the funny thing was we all avoided each other going around the supermarket. But then when we go to pay there was only one cashier on one checkout. So people didn’t know what to do because if you didn’t step forward and crunch against the next person, well, somebody would step in front of you who didn’t care so you’d never get served. It became this petri dish.

People just crammed together and it was just ridiculous how much we avoided each other, went according to a schedule, and then got smashed together waiting ages on a queue. It’s a bit like when Donald Trump began saying that hey, the flights from Europe are going to be canceled and then there was panic at the airports and it was six hours to get your bags and up to two hours to clear. So people were waiting eight to 10 hours, I’m told, crammed together. So it’s very hard to do sense making at the moment. And with the job I do, I spend my life making sense or attempting to make sense and this has just thrown a curve ball into it that I’m not appreciating because life was quite good the way I had it. I thought I had the vectors worked out. So yeah, and I don’t think any of the clients I serve, they’re going to go back to business as usual.

And what’s kind of disappointing to me is I still am seeing these messaging and streams and announcements that probably were pre-buffered on social media, but doesn’t fit the zeitgeist. It doesn’t fit the time. I don’t want to know about your smartwatch that can detect if I’m falling in love or have to have glowing skin at the moment. It’s just not where attention is and I don’t think it’s going to be here when we come back. I think something has fundamentally changed in it. How big a change will depend upon the economic aftershocks, but before the huge economic aftershocks we’ve got this human toll over the next couple of months where let’s say half the American population is likely to get it, but we don’t even know how much of the population has it at the moment. That’s what’s throwing the maths off by so many factors.

Jeff: Yeah, I think that’s a lot of the source of panic is just the uncertainty and not having that information. Clearly if you look at the numbers from South Korea or at least what’s reported they were so aggressive so early. They have the information, they can make decisions based on the information, and we’re in a situation where we don’t have the information so everybody’s, we have to take the most dire precautions because lack of information is what’s driving that.

Lee: I did see that Everlywell had announced a home test, but the PCR kind. It’s uncomfortable where you need to swab right the back of your nose and then you need to use a postal service. I saw another company I tweeted it on Hyper Wellbeing. I forget the name and if they’re FDA approved then it will be a home testing without needing to insert things to the back of your nose and use the postal system because you want to get tested, not because you have symptoms. But to know if it has passed you by. For example, a month ago my girlfriend and I were like this is a really weird flu we’ve got. We were both perplexed by it. We didn’t even think of corona virus. Four days later like the flu back again. Just a bizarre flu and even now I’m like I don’t know. It was just kind of odd and everybody kind of seemed sick.

But we don’t know if that was regular influenza. We didn’t have a cough or high fever but you want to know if you’ve had it to know if you’ve got antibodies. Now like South Korea as you mentioned, they were on top of it more than anyone else. And if you take their data then you have a case fatality rate of 0.6 which is good. It’s still diabolical if you assume half of California will get it in the following two months.

Jeff: Yeah.

Lee: So we have to hope the case fatalities are actually 0.2, but you see the Lancet report and so on putting out huge numbers. You saw the WHO putting out something in the 1% to 3% [3.4] range. I’ll put these links in the show notes. And I got frustrated checking online at the stats because I know in Slovenia the stats are higher.

So I don’t see how we can go about business for the next two months, Jeff. Look at the exponential growth rate. The good news is it’ll have an exponential decline because you only meet roughly the same people each day in your family units and circles. You run into people who have been pre-infected so it has an exponential decline on the other side and we should be good by August. But the next few months I don’t know how you go about business and I don’t know how you get any business messaging out that people will listen to over the next two months?

Jeff: I think, well, there’s then the question of reinfection rate in the community. I think there’s a lot of, it seems like unless we have a really solid treatment or a very clear vaccine, really we won’t be behind this until one of those things happen.

Lee: There are a couple of promising off-label drugs so they’re now off patent. In fact, Elon Musk has been tweeting about them – they do look promising. In terms of a vaccine I was on the phone to a CEO of a company. I won’t name it and he said they have a vaccine. They just need it approved. And I said, hey, but what about the cytokine storm. That was never solved for MERS and SARS. He said no, we’ve solved it. I’ll say it was an Israeli venture. In terms of corona virus, how do you see it impacting your business? I know you’re in the midst of it, but surely you must instantly notice it. Hey look, people are probably not really attuned hearing about a wellness package at the moment, I would presume.

Jeff: It actually hasn’t affected us too much. I think the biggest thing we’ve been focusing on is making sure we update and double check and triple check our procedures for making sure that as people come through, everything is sterilized. I think given, in some ways I could imagine given our initial customer base, you can imagine an increasing demand for people who want more visibility and understanding of what’s going on in their bodies.

Lee: Please, for the sake of the audience, could you give an introduction to Q Bio?

Jeff: Yeah. So I think we’re trying to step back and start from first principles and think about how would you design a primary care system with the technology we have and knowing what we know now, if you could do it from scratch. And when we did that, one of the first things we felt was important is that if you want to have value-based care or be making data-driven decisions in healthcare there’s a fundamental capability that’s missing which is more or less you need to have some kind of analytics platform for measuring change in the human body.

And this is very important, I think, because if you look at the way diagnostics have been done historically, there is some fundamental assumptions about statistical distributions. Specifically that human health is roughly a normal distribution and I think it’s actually much more of a long tail distribution. So the idea that I can take a population reference or that was typically actually done by taking a thousand white males and they’re probably middle aged and establishing that as a reference and then applying that to everyone to determine whether or not they have some biomarker that’s high or low or if they’re at high risk for a single disease.

It’s silly because we all have unique genetics and even people who have the same genetics like twins diverge over time. That’s one reason I think it’s somewhat flawed. But the other is really that what’s much more likely to be common is the rate of changes across people when they’re developing a disease versus the absolute measurement at a single point in time of a specific biomarker. I think it’s also a little bit crazy that we try and reduce complicated diseases like cardiovascular disease to a single variable measured a single point in time based on one of these population references. Of course our diagnostics have terrible specificity, right?

In this era what other business can you think of? Can you imagine if Facebook tried to predict which ads you were going to click on or how to customize your newsfeed based on a single variable? Or if Google gives you search results based on a single variable to predict relevance. That would never happen. And so the idea of using multivariate information about the human body and then how those things are changing is really just applying a kind of modern information theory in data science to understanding human health. So going back to where we started we said okay, well what that means if we want to be able to build this analytics platform for the body there’s a few things that are required. We need to cover the major, the most salient features of the body. What is that? That’s genetic information, chemical information and structural information, right? It needs to be noninvasive. It needs to be fast, and we need to be able to make it cheap.

The last thing that’s very important is that it needs to be reproducible. The set of measurements that we take needs to be reproducible and the reason that’s critical is if it’s not reproducible, if I can’t reproducibly measure a quantity that’s under experimental control, I can’t measure what’s changing in it. I think there’s a ton of information that’s actually collected in the healthcare system today that is subjective observation. Or there’s even lab tests that are not as reproducible as you’d like if you come from a background, let’s say in experimental physics. So like I said, these properties are very important. It’s noninvasive, cheap, fast, and reproducible. And if you can do that, if you can make this, you can kind of think of this as a physical of the future where if I can gather genetic, chemical and structural information in a way that has these four properties, I can then actually track what’s changing, right?

And there’s all kinds of benefits to this. Specifically, it sets us up to build a healthcare system that actually gets better and more efficient over time. Because you can’t make data-driven decisions. You can’t be self-optimizing unless you are understanding how your interventions affect a system. And that’s true in a single individual and it’s also true at a population level. And that’s why this isn’t really a revolutionary idea. I mean measuring changes in a system to be able to forecast future measurements in that system is effectively the scientific method to some degree. If we look at almost every modern scientific discipline, they were all revolutionized when an instrument was developed or instruments that allowed us to cheaply measure the system that was being studied. Astronomy was revolutionized by the telescope. Biology was revolutionized by the microscope. Weather was revolutionized by the thermometer. And then we have all these other sensors now, but at the end of the day what ends up happening when we want to take something that is an art or a kind of a soft science and make it a hard science is really the transformation of it becoming an information science.

Because when we can reproducibly measure a system and then we can go back after we got that data and develop algorithms that try and predict the next measurement, well if it doesn’t agree we say okay, our models don’t actually describe the dynamics of the system we have to come up with a new model. But if it starts to agree we start to think hey, we understand actually the dynamics of the system. We can forecast changes to the system, we can test hypotheticals. And I actually think ultimately that’s where we’re going to get to with the human body. If you take what we’re proposing out into the future we’ll get to a point where we have this virtual kind of model of each one of our health that we can test hypotheticals for. I think this could be a boon for not only personalized diagnostics but personalized therapeutics.

Lee: That was very eloquent. We should be applying systems theory to healthcare as a system as in you need to measure every component and see how it affects the totality, recursively.

Jeff: Well, I think initially as we’re learning, if we can measure things reproducibly cheaply and quickly and non-invasively, then it makes sense to measure more. But I actually think that what ends up happening, and this is a little bit like indexing a web page, right? I actually think of the platform for healthcare in the future is a lot like a search engine for your body and the physical is like indexing a web page or it’s like a web crawler. A web crawler doesn’t actually copy a whole web page. It actually extracts the most salient features. And depending on the web page, some features might be more salient than others and I actually think it’s going to be the same way for people eventually. I think eventually the physical that we get in order to optimize for outcomes and cost will be tailored to our individual risks and previous measurements that were taken. So you can imagine you show up to a place… I think it would imagine like a car wash for your body. You go in, you say, “Hey, I’m here for my checkup.” It might’ve been a year ago, it might’ve been a few months ago, depending on your risks. The set of measurements to be  taken are quickly computated saying, “Here’s the optimal set of measurements that we take to understand and forecast Jeff’s health risks for the next year and help us determine if he needs to see a doctor or he doesn’t. And he should just come back next year.”

And if you think about the efficiencies that would be gained, you could almost think of this as a triage layer in front of the existing primary care system. Because one thing that is common across the entire globe is that the number of doctors per capita is going down. And all the attempts to say AI this, AI that are really attempts to displace highly skilled labor or effectively doctors time. And I don’t think that’s going to happen soon.

And I actually think we have enough doctors. So the problem isn’t doctors need to spend more time with patients, it’s that doctors need to make sure they’re spending time with the patients that need it. Effectively, I would think of this system that I’m suggesting, that is a triage system, as actually being like a load balancer for highly skilled labor in the primary care system. We don’t have to automatically determine if you’re sick, we just have to automatically determine if you need to see a doctor. And that’s very different because if you can scan a thousand people, with these comprehensive set of metrics, and only a thousand of them need to talk to a doctor that year, effectively that doctor is caring for 10,000 people. And I think that’s the way to think about one of the major gains in efficiencies is it’s a better use of highly skilled labor in a time when we have an increasingly scarce amount of that labor.

Lee: Brad Perkins, the first guest I ever had, he said that he believes the future healthcare will require a new breed of clinicians. More data scientists. There would be more akin to being data scientists. Would you agree with that?

Jeff: No, actually I wouldn’t. I think it’s a fundamental transformation, right? When the Internet became available, it was like the world’s largest library. We didn’t need new people using the internet. We needed new tools to help us find what we were looking for in the library. Because the Dewey Decimal System wasn’t going to work for the Internet. It just doesn’t scale.

Lee: Would traditional clinicians have the training?

Jeff: Well, I think with the right tools, they don’t need training. I mean, I think that’s part of one of the elegant things about what Google is. You don’t need to be taught how to use Google very much. You just ask a question, you say, “This is what I’m looking for,” and you get better at using it and it gets better at answering your questions. I actually think that the amount of information that we’re talking about in the healthcare system is exactly why I actually think the ultimate clinical decision support tool for the future, not only for population health management but for individual patient care, is going to be a search engine. As a doctor, I should just be able to go to Jeff’s dashboard and I should say, “Hey, tell me about Jeff’s respiratory system.” And the system should just summarize all the most relevant information about Jeff’s respiratory system for me.

I think we need new tools to help doctors sift through this information and find the most relevant bits based on the questions that they have. We don’t need necessarily new doctors. The same way that there are data scientists and there are analysts. I think that there could be the people that build these tools might very well be people that have medical or biological backgrounds and computer science backgrounds. But fundamentally, ultimately what technology should do is not require more data science background from a doctor. What it really should do is liberate the doctor to actually just focus on making clinical decisions and care of a person. Technology should minimize the technical requirements for a doctor or technical background, not enhance it.

Lee: I don’t know if you saw a statement I made which was, “The future I see is computer science moving to health and wellness, which is a converse of the trend that most people seem to be focused on with digital health and so on, which is digitization of present healthcare.” Would you agree?

Jeff: I mean, I don’t know if it’s too philosophical, but in general, I think what we’re going to see is there’s very big venture capital companies that are built on the idea that software is eating the world. And I think that fundamentally that’s going to be true for everything. Information, you can call it computer science, having a degree in computer science. I think there’s two parts to what is traditionally called computer science. There’s information theory and then there’s programming. Computer science is actually, in my mind, more information theory than it is programming. It’s just kind of like the tools that we use to study information. But I think that’s true everywhere. And I think that there’s, especially as we start to get into quantum information systems, the line between information and physical reality is going to continue to get blurry and that’s why software can eat the world.

Lee: I saw back in 2005 and especially when it hit the end of 2007 and then with the release of the iPhone. I said that a computer manufacturer, Apple, and a search engine company, Google, will encroach the telecom space. Now telecoms was a hardware industry, which had been my industry and people laughed. Now it’s fairly obvious that software ate telecoms. And I don’t think the software and the Internet has actually had much impact upon healthcare. And if you agree with that premise, then surely you would agree the software and the Internet or networking, has not hit healthcare. When it does hit healthcare, you’re not left with the same healthcare afterwards.

Jeff: I would agree. And in some ways there’s good reason for it. There’s a lot of dogma in healthcare, right? I mean, just think about the kind of quote unquote annual checkup or the physical. There’s almost nothing that a doctor does when you go visit them that couldn’t have been done over 200 years ago in terms of the information. Sometimes there are labs, but there’s a lot of times they don’t even do that. So I think that’s a long time to have very little change. And I think it’s especially bad in the United States. I think there is in some ways doctors have to operate in a constant state of fear, right? The do no harm thing is really, I think, a fear and honestly the liability issues in the United States I think actually exacerbate this.

There is a kind of an unreasonable standard for doctors… if people come to someone and say, “Am I sick or not?” It’s almost never that binary, right? It’s never that black and white, sick or not. It’s “Well, here’s the statistics,” right? But not everybody understands that. So doctors are in a very tough position to give people kind of absolute certainty when that really is not something that exists. And I think because of that, any change that they make to what they’re clinically taught actually puts them at risk of losing their ability to practice medicine. And so the funny thing about all this is it’s very heavy regulated for good reason because people’s lives are at risk, but that really does slow down change. And if you want something to get better and cheaper, that requires a fundamental change. You need to have a system that can introspect itself, learn from mistakes and then improve.

But healthcare is not really set up to do that for a number of reasons. And I think there is a very delicate challenge in trying to figure out how… And that’s something that we think a lot about is how do you create more opportunities for self optimization in learning without creating increased risks to the individuals. Because at the end of the day, I would almost argue that clinical studies are just, as an idea, are somewhat flawed, right? One thing that I was talking to you about earlier is that I don’t think human health is really a normal distribution. I think it’s a long tail. What even makes it more complicated is I would argue that it’s based on non stationary patterns, right? Which means that what it means to be sick and healthy is changing depending on the environment, technology, what we eat, our behaviors.

Just take the average age, height and weight of a baby 50 years ago and apply it. If you’d apply that today, every baby is in the 90th something percentile. So our nutrition is getting better. So, that means that the problem with these fixed in time studies and then applying it forever into the future to me is fundamentally flawed. What we really need to do is take the approach of how do we measure more about all of us and continually learn and update the system from everything we know. Because in theory, the more people that have lived, the better we should be at understanding what’s going on in our bodies.

Lee: Yeah, each life that lives and dies makes a contribution by having lived.

Jeff: Well, and I would argue that that should be the case. About four or five years ago, I gave a podcast and I talked about how the first thing that would be useful… And I think there’s a lot of missing information in existing healthcare system because it is mostly subjective information versus kind of objective measurements about our biology. Is data donorship. If people could go to the DMV and opt to be a data donor instead of just an organ donor, the power of that is you have the… If you donate kind of the history or the evolution of your biology and how it changed over your life, it can benefit every person that’s ever going to be born after you. Whereas if I donate an organ, I could save one or two people’s life maybe. And so-

Lee: I fully agree and especially-

Jeff: … there’s a compounding effect.

Lee: I mentioned this with Nathan Price, that my father suffered cancer many times and ultimately died from it.

Jeff: Sorry to hear that.

Lee: And it was such a shame… I appreciate that. It’s such a shame that he wasn’t able to donate that data, pre chemo, post chemo, chemo again, no chemo and so forth. There was no recording of those variables and their interrelations and their changes over time as his life underwent those changes and then ultimately led to a final decline.

Jeff: I mean that brings up I think another great thing about this approach of let’s take a step back and how do we build a analytics platform for the body that can measure what’s changing? This isn’t just about potentially understanding changes that are the precursors to serious disease. There’s a whole host of other scenarios we’re having to understand, and measuring these changes are valuable, right? Before, if you’ve ever been injured or had a serious traumatic orthopedic injury, if a doctor or a set of surgeons has a understanding of what your anatomy and chemistry were like before they do surgery, they have a better chance of actually measuring how close they got to restoring you to your pre-injury status. And that’s not just actually anatomically that’s potentially chemically because I’ve had a number of orthopedic surgeries where I know that my inflammation in my body has gone up because of severely damaged joints. And so there’s chemical information after surgery, not just anatomical.

You can imagine being rushed… Recently my girlfriend’s brother was rushed to the hospital after falling in a ski accident and it wasn’t a very bad fall, but when he stood up he had severe abdominal pains. They rushed him to the hospital and they did a full CT scan. They found that he had an enlarged spleen. They assumed that he might be going into sepsis. They cut him open from his sternum to his belly button, untangled his intestines looking for holes, didn’t find anything, closed him back up, he was in and out of the hospital for two months. All kinds of complications, hundreds of thousand dollars in medical bills. And it turns out he just has a slightly larger than average spleen.

So, doctors not being able to see what has changed recently in a person forces them to conclude that when you’re symptomatic, or have an issue and time is of the essence, that your latest symptoms are correlated to anything that they think is abnormal. The problem is that if you believe in this long tail and everybody’s a little bit different, there is no normal, right? Doctors, in medical school, they’re shown here’s a female anatomy, here’s a male anatomy. And if it deviates from that a little bit, especially in an emergency, they have to be safe. You hear doctors talk about, “I operated because I had to be sure.”

Well another way they could be sure is to see that nothing has changed since this horrible accident and know that, no, you just have a slightly larger than average spleen and this wasn’t because you have a leak in your intestine.

Lee: So I have to ask the question why was this not possible before? Why is it suddenly possible now?

Jeff: Let me answer that in one second because I think there’s another point… This is a specific kind of information. I’m talking about surgical. Another reason I think it’s very important to measure change is how many times in the current healthcare system are people prescribed drugs for the rest of their life based on a single lab result? I don’t think we have good information on this, but I’m really interested in knowing how do we know when we get prescribed one of these drugs that it’s not only it’s having the effect that intended, but it’s not having other effects? And the reason this is particularly important, and why if it was standard that we took these snapshots about people on an annual basis and we could understand this better, is that drug developers, when they develop drugs… And I learned this not too long ago. If they develop a drug, a statin, that’s just supposed to adjust your cholesterol, when they do the clinical study to see how the drug works, what they do is they only measure your cholesterol and there’s a really interesting reason why. It’s because they don’t want to know what else it’s changing because if they find that it changes other things and has measurable side effects, they would have to report it. That’s very scary to me.

Because that makes me want to know every time I get prescribed something, I don’t just want to know it’s doing what it’s supposed to. I want to make sure it’s not doing things that it’s not supposed to.

And so I think that’s another specific use case of just the simple ability of measuring what’s changing over time allows doctors to actually know, just like we do AB testing on websites and apps. It’s like, why can’t a doctor actually measure the impact of an intervention they’re having, whether it’s drugs, exercise, whatever they’re prescribing. Surgery. Why don’t they have the tools to measure the impact that they’re having? Why is it they just prescribed something and assume it’s fixed if you don’t complain?

Lee: I hear the logic.

Jeff: Getting back to your question about why wasn’t this possible. I think there’s a lot of things that have happened in the last decade, but to me the thing that I started paying attention to is… And I think this is the general trend, is I would say we’re entering the age of the digitization of biology.  And to me what that really means is you can look at all these different technologies that we’re developing and the trend really, whether it’s genomics, transcriptomics, proteomics, epigenetics, metabolomics, microbiomics, then there’s kind of you can call it radiomics if you want to talk about morphology. The general trend in most of these kind of areas is that the price of measuring one thing is approaching the price of measuring everything.

Early on even look at 23andMe, they looked at a few snips. Now the cost of transporting a sample to a lab is a dominant cost for a shallow whole genome sequence. And so you might as well sequence the whole thing if you’re going to take the sample to the lab. And I think that shotgun proteomics, shotgun metabolomics, all of these things, they’re not there yet, but what they have in common is the approach to gathering information is measure everything in the sample, then use software to ask questions. Whereas assays historically were, let’s find a reagent that interacts with some chemical or some protein that we want to measure. Then we use some sensor based on whether it’s some kind of light it maybe gives off and the intensity of that light tells us kind of the concentration.

So the assays before were actually, the query was baked into the assay, right? In a digitization, you’re actually taking a physical object and extracting all the information in it so you can ask questions later. And so the query becomes software, not the actual physical process of gathering information.

And that is the trend that’s allowing us to gather information. That is the trend that’s allowing us to start to do this. I think that, in a lot of these areas, if you look at genetics for example, that’s just the tip of the iceberg. Its price performance has beaten Moore’s law in the last decade or so. I think that’s going to continue, in all the kinds of things that we can measure about the human body.

It’s very clear, you can kind of look at the horizon and say, well, at some point it’s going to be feasible and cheap to just measure everything about the human body on some regular interval. When that happens, healthcare will truly become a pure information science.

Lee: It logically stacks up, and you would imagine it would have to happen, because it logically stacks up. Everything stacks against it not happening.

Jeff: Yeah, to me, it’s an inevitability. It’s a matter of assuming human civilization exists, at least. I think at some point it will be a necessity. But I think it’s a matter of when, not if, to be perfectly honest.

Lee: Yeah, I don’t think I could agree with you any more. It’s because I very much agree with your train of thoughts, is why I put my life on hold in 2015 to focus on what I do, focus on, which very much is in accordance with what you say. But the road there may be complicated, and that takes me back to what I was going to ask you. Each chronic disease is approximately a trillion-dollar industry. There’s a lot of entrenched positions.

For example, you mention that you dispense statins based off some cholesterol measures. By the way, cholesterol is very dynamic.

Jeff: Sure.

Lee: It changes roughly every four days. Yeah, I can change the profiles and the sub-bands of it through diet alone. Which is kind of shocking. You wonder why people get dispensed drugs on a test once a year. The amount of stress, if I recently had an infection, it’s also different. It’s a dynamic system, and actually I perform a lot better with high cholesterol, and my other markers are better with high cholesterol. I just make sure it’s not damaged cholesterol.

You might consider myself cynical here, but I don’t take the position it’s cynical. Doctors have been coerced … Unknowingly, I would say. It’s become a collective thing, into using stupid markers simply to dispense drugs. If cholesterol is this, I put you on a statin. Without much investigation. Don’t you see that healthcare today has incentives just to dispense drugs, and they don’t actually want to do any real testing.

Jeff: I don’t blame doctors, to be perfectly honest. I think that there’s a matter of liability. I think there’s this problem of doctors not wanting to ever go outside of norms… It’s the saying, no one ever got fired for buying IBM, which might not be true anymore, but I think I heard it when I was younger.

Lee: We know what you mean.

Jeff: But I think it’s a similar thing. Would you risk your livelihood on something that wasn’t widely accepted? If a doctor goes based on a massively widely accepted clinical study of here’s best practices, they’re not risking anything, and who can blame them? But I think there’s a bigger question here, which I think you kind of brought up. It’s that until we have the ability to comprehensively measure changes in the human body, so that we can actually study the impact of certain things, and how biomarkers are related … I should also add that if you want to do this, you also need to make this measuring process fast, right? Because when people say, “Oh, I went and got this measured yesterday,” and next week you’re going to get this measured and say, “I measure everything once a year.” I don’t think that’s the same.

Because again, going back to it with my background in experimental physics. If I want to characterize a system at a point in time, I need to take a snapshot of it. Otherwise I lose the ability to correlate the relationships between those measurements, which is part of the thing that gives me the power of prediction, right? I have to say that most clinical things that I read, because we don’t have the tools right now to study the human body the way we would most other physical systems, I have a hard time relying on them, too much.

I think that I would go as far as saying that most of medical knowledge that we have today is probably incorrect, and it’s probably heavily biased. Again, I don’t think that’s anybody’s fault. But I think there’s a lot of evidence in that. We look at a clinical study and how hard it is to reproduce the results of a clinical study, right? Or just look at how quickly a decade ago we’d believe one thing is the problem, and then a decade later it’s another thing. It’s just not that systematic, right?

Again, and I can go into all these reasons why I think that’s true. But there’s just I think overwhelming evidence that we just know a lot less than we think we do.

Lee: I more than fully concur. I know that is the case.

Jeff: I think fundamentally if you come at our approach to solving this problem from a scientific perspective, I’d say, let’s just assume we know nothing. Let’s start from that. We have the tools, and I’m not saying we should completely act that way. But we should in some ways have a little bit more humility about our ability to understand the human body. We understand almost every part of our universe better than we understand what’s going on in our own bodies.

Lee: And the oceans.

Jeff: Yeah. Well, another very complex, dynamic system. I think our approach is really just to be a little bit humble and say, “Look, we don’t really know.” We have some ideas, but why not approach this in a way that we can have a lot more confidence in what we do and what we don’t know? One of my co-founders does a lot of research, Mike Snyder. Dr. Mike Snyder, the chair of genetics at Stanford. There’s a lot of evidence that even just type 2 diabetes is actually lots of different diseases. We lump these things together into this ontology, but we really haven’t had the tools to measure and study human metabolism, the way you would as a true scientist, enough to understand these things.

I think our approaches really need to be a little more humble and say, “Hey, what is the way, if we want to actually start pinning things down, how would you approach this?”

Lee: It’s the same with Alzheimer’s. It’s not one disease, and you see because of the dogma of amyloid plaques, you see the situation we now are in with Alzheimer’s where it’s predicted, continuing the way we are, that half of all millennials will end up with such a degenerative cognitive decline.

Jeff: Yeah. Again, going back to my background in physics, the amyloid plaques to some degree are a macroscopic phenomenon, right? Especially if you can see it with something like MRI at a millimeter resolution. The processes that lead to that are happening at a billionth or a millionth of a meter. Part of this idea of let’s measure more about the body isn’t just, measure more. Let’s take multi-scale measurements. In a lot of physics, you want to understand things happening at different length and different time scales. I think we need to apply that same kind of thinking to the body. We can measure things about our chemistry on the billionth of a meter. We can measure things about cellular organization, which is a millionth of a meter. We can measure things about the structure of our body on the thousandth of a meter.

But it’s correlating across all these different length scales that actually helps us understand processes. Just because of the way the human body is built, if I can see something happening at a millimeter scale, it means that there’s a lot of things that have to be happening at a billionth or a millionth of a meter scale. It’s triangulating between all of these things that can actually really help us understand processes. Once you understand that, you can say, “Okay, well there’s lots of different processes that could be happening at a millionth or a billionth of a meter that could look the same at a thousandth of a meter.”

I think that’s, again, going back to why something like Alzheimer’s could actually be the result of many different underlying physical processes that are going awry, but we think of it as one disease because at a macroscopic level that’s what it looks like.

Lee: Talking physically, do you subscribe to the notion, if you keep the mitochondria healthy, you keep the tissue healthy. You keep the tissue healthy, you keep the organs healthy. You keep the organs healthy, you keep the body healthy.

Jeff: I don’t have formal background… I’ve read a lot about biology, but I don’t like to speculate too much on microbiology because of that. I will say that, again, going back to kind of the fundamentals, and I think physics obviously underpins a lot of the chemistry, and ultimately what happens in biology. I do think that the human body fundamentally, or maybe it’s just a property of life, is an entropy-fighting system. The act of aging, in my mind, is just when our body slows down its replication and loses the ability to keep up with entropy.

I see no reason that, let’s say if we had unlimited energy. I see no reason why we shouldn’t be able to stay as young as we want indefinitely, because it really is just a matter of being able to combat entropy. Whether or not the majority of the entropy is accumulating in a mitochondria or something else, at the end of the day, it’s just managing disorder. We are constantly battling our bodies’ desire to be pulled into disorder, but given enough energy we should be able to keep its order.

Lee: Are you aware of David Sinclair’s information theory of aging?

Jeff: No, but I know David. I sat on a panel with David, and I’m a big fan of him, and so I could imagine what his information theory of aging is. But I’m not familiar with it.

Lee: Yeah, he believes that the epigenome becomes corrupted over time. But he believes that the cell somehow has a backup somewhere, and you can revert the epigenome back, back to a previous state of methylation, and literally roll back time, biologically. In fact, there was a paper where they did this with the eyes of a mouse.

Jeff: That makes a lot of sense to me, but the way I have thought about it actually is from the perspective, again, going more back to kind of information theory and complexity theory, is … One of the problems that I had a decade or more ago when everybody said that once we decode the human genome healthcare would be solved, is that when I thought about the amount of information contained in the human genome, versus the amount of information it takes to express our biological state, there’s about a 10^20 difference in terms of the number of bits required to describe it.

When I tried to reason about, well where does this extra complexity come from? To me what it meant is that the act of living our lives … There’s more information that’s actually accumulated, or chaos that’s incorporated depending on how you look at it, in the act of living our lives than there is actually in our genome. I think the epigenome, or methylation, is potentially one of these sources of their accumulations of complexity and actually information. In some ways it has a history of everything that our body has been exposed to.

I think that one makes a lot of intuitive sense to me, based on this idea. But that’s also why I think that measuring changes is so critical to understanding our current health and potential future health. I think our genes are very useful in understanding our risks and what might be the best way to influence our trajectory. But just as a thought experiment, for example. Let’s say an alien civilization came down to us, and said, “I have two technologies that are going to appear magical to you, and you can choose which one you want. I can tell you what the entire human genome means, and decode it for you, or I can give you the ability to take a snapshot of a person’s biological state instantaneously and non-invasively, into pure digital information. Which one would you prefer?”

The answer to me is actually to take the snapshot. Part of the reason is that I think by understanding, if you can take those measurements, and measure in the evolution of, let’s say a human. You can actually infer and decode … That’s the way you would actually end up having to decode the genome anyways, right? Not only is I think it more immediately useful for understanding somebody’s health, but I also think that it actually inevitably is the tool that you need to have in order to decode the genome for the most part.

Lee: What do you mean by, we’ve not decoded the genome? Just because that might not be immediately evident to most people.

Jeff: We can sequence it. Well, and we can even debate that. Again, I’m not an expert in genetics, but one of the issues that I currently have with genetics technology is the idea of a reference genome. Again, as a physicist I would much prefer if all sequencing was de novo. At least, until we perfect kind of the high throughput stuff. But in terms of reproducibility and not being dependent on other kind of so-called references which may or may not be relevant to everybody.

When I say decode, I mean it’s one thing to sequence a genome, and let’s just assume we can do that accurately. It’s another thing to know what it all means. We’re not even close to that. But my point is that even if we had that, I don’t know that it’s immediately more useful than our ability to instantaneously take a snapshot of our biology, cheaply and non-invasively.

Lee: I understand. What you’re saying, in technical terms overall, is we don’t know shit today.

Jeff: In technical terms, yeah. I think that sounds, again, a little bit like doctors have failed us, or clinical research has failed us. I don’t think that’s necessarily what it is, I just think that if you go back even 20 or 30 years, the tools that were available to actually study biology were not that much different than a psychologist had. It was very much just based on look, feel, and description of symptoms.

Lee: Yeah, but you’re talking of an order of magnitudes way ahead. You can’t even comprehend the present to where you’re pointing to.

Jeff: Yeah, all I’m saying is that I just think that it’s necessarily we say we don’t know shit, it’s like, well … You know, yeah.

Lee: I meant humanity has a … Yeah.

Jeff: I think we have a lot to learn, and the other thing I think that’s very difficult about the human body again, is there’s a notion of different levels of chaos in a system. There’s class one and class two. For example, predicting the weather, it’s a class one chaotic system. That just means that our predictions about it don’t influence its outcome. Humans are much more complicated in that sense, because my predictions, potentially if I tell you you’re at risk for a heart attack and you should adjust your diet, your life, and then you never have a heart attack, you can never prove that it was because of the things that I told you to do.

Lee: No, and 40% of people who leave the doctor, no matter what they do, if they take the pill or don’t take the pill, would get better anyway.

Jeff: Yeah. I mean, again, this just goes back to, I think we have to treat each human and their bodies and their health like a unique system, and come up with a way of practicing healthcare that treats each person as unique. If we do, I think it actually scales much better, because all this talk about precision medicine and personalized medicine, at the end of the day really the reason that’s important is because healthcare is such a long-tail phenomenon. We need to personalize it to scale prevention. The same way Google has to personalize search results to get the most relevance.

I think the end goal shouldn’t be personalized medicine or precision medicine. The end goal should be getting to more proactive or preventative medicine. The way you do that at scale is that it has to be personalized.

Lee: Going to be interesting how … You speak of interfacing with doctors and providing them with a tool. But actually what you’re doing is, you’re enabling a marketplace, so that people can go ahead and purchase anti-aging therapeutics and procedures, or compounds and so forth. What you’re doing is enabling a marketplace with that data. I mean, that’s what has to happen.

Jeff: I think you could, and I think that that’s a possible future. I think it’s super important that one of the most important parts of this is how we protect this data and how people control it … I feel extremely strongly that this data should be owned and controlled by an individual. That if a person wants to share to this person, either on a continuous basis, on an anonymized continuous basis with academics, so they continually research, or upon their death. I think that almost has to be written into, I think, our fundamental constitution that people own and control information about their body.

Lee: Yeah.

Jeff: The idea of a marketplace I think would be okay, as long as we establish this … I do think there’s a whole economy where you could imagine people being able to deliver on demand, if I have access to this information about your body, I could synthesize a drug specifically targeted to help you, and then ship it to you. And that’s definitely a good thing if you can do it in a way that protects the safety of the individual. I mean, that would obviously be great economically if you could do that safely.

Lee: Or the ultimate nutraceutical. Rather than a drug.

Jeff: Especially given the current situation, I think there’s actually other really interesting applications. If you built this dataset and it was somewhat standardized, you could imagine, without having to share personal identifying information, the CDC actually having access to population level analytics of changes in the population.

Imagine if you were doing this as a standard. Let’s think about the Flint, Michigan case. If you were doing this and you had these car washes for your body and everybody went, and in 20 minutes everything could be measured about the body. And they went home and they just got an alert if they needed to talk to a doctor.

Imagine that was the reality. Well, in Flint, Michigan on any given day, let’s say it’s a Wednesday, X people would get this done. You could easily imagine just very simple alerting systems or database triggers for the most part. If you saw, from Wednesday to Thursday, all of a sudden everybody that came in had increased lead in their body, your immediate response would be, “Okay, well something changed in the environment. What happened?” It wouldn’t be two years later when people were finding that their kids had disabilities and they had long term exposure to lead.

You would actually be able to say, “Okay, something in the environment’s changing because we’re seeing increased toxins at this specific point in time.”

Lee: Absolutely.

Jeff: Because, at the end of the day, as people we’re out, we’re effectively environmental sensors going around picking up things. You can imagine ways that this could be used to benefit population health and give early warning signs. And also prevent corporations or tyrannical governments from doing things to our environment unbeknownst to us because we’d get notification.

That’s the specific case of Flint, Michigan of lead being put into the water. But, you could also imagine in the outbreak of a novel disease. If some doctors started to see some percentage of people start to have these aggressive flu-like symptoms, you immediately could say, “Well, are we seeing this anywhere else in the world in the population?” And you could triage much more effectively. Even if we didn’t have a test for that specific thing yet, we would be measuring a statistical change in the symptoms that were reported earlier on.

Lee: It makes the present situation seem even more ridiculous. I mean with coronavirus.

Jeff: It’s like people talk about how expensive it might be to do this, and I actually think that what we’re doing right now could be a commodity in just a couple of years and only take 20 minutes what we do in 60 minutes. What is the cost of an uncontrolled pandemic when the economy shuts down for a year or more? What is the cost of all of the procedures or drugs that we give to people that were unnecessary because doctors didn’t have enough prior information to know that the thing that they were about to do wouldn’t change anything?

Lee: I know you’ve got a hard stop, so can I just give you a few quick questions? Feel free to rapid fire answer them. You mentioned a physical, but then people’s minds will look at Forward or Parsley Health. Do you want to quickly differentiate yourself from that type of category?

Jeff: Sure. I actually think we’re very complimentary. If you look at the amount of information that they gather versus actually a standard visit to a doctor, it’s actually not that different. What they really provide is access to a doctor, whether it’s 24 hours a day via chat or you can show up whenever you want. And they all have primary care doctors. They are a care provider. We are much more focused on giving better information and making it easier for care providers to understand what’s changing in an individual. So, we actually have a number of existing people who use our platforms that are also customers of Forward and Parsley.

So, we’re very complimentary. But, their philosophy is, and we can talk about AI and all these other things, but I think their philosophy really is the key to preventative care is people need more access to doctors. I think our feeling is that the key to preventative care really is making sure that people who need to talk to doctors get access to doctors because, given just the number of doctors in the world, it’s impossible for doctors to spend four hours with 2000 people a year.

So, what that really means to us is rather than increasing the amount of time a doctor spends with each individual, it’s how do you shift the distribution so that doctors can spend the right amount of time with every individual. They only spend time with the people that need it. So, a doctor might spend four hours a year with a person that they see, but they only see 10% of the people they actually care for, right? So, I think that’s the fundamental difference of our approach, but I think it’s actually complimentary because they have great doctors and they provide a lot of in-person interaction. That’s not where we’re focused.

Lee: But you’re not targeting sick people.

Jeff: There’s different use cases for our platform. There are people who have chronic conditions. There are people who are recovering from chronic conditions. We have professional athletes who want to use this to optimize their performance and diet and training. We have people who are about to start taking a drug that might have some nasty side effects and they want to make sure that they can track how that drug is affecting them. There are people who are about to have a major surgery and they want to understand if they’re fully recovered, and their musculature and their symmetry has come back, and their inflammation markers are returned to normal after their surgery.

Lee: So you really are the physical of the future as per the website claim.

Jeff: I think what we offer really is the simplest way ever. You can almost think of it as like GPS for your health. It’s the simplest way ever to understand where you are and what’s changing in your body.

And I do think that there’s a future where when we get sick we always know why we got sick. It’s not a mystery. And then it’s just a matter of how we fix it. But how do we enable the ability for us to provide that kind of visibility is we’ve made it cheap enough and fast enough so that – and noninvasive – so that an individual can, on some regular interval, even if it’s in a limited group right now, can measure what’s changing. So in the same time it would take you to go to the dentist, we can measure everything about your body rather than just look at your gums.

Lee: So, can you tell me what kind of price points you have, where the locations are? And I think we’ll finish off there.

Jeff: So, we opened our first location in March last year in Redwood City, and we didn’t really do any promotion of that, we just kind of opened it up to see what would happen and let it grow organically. And it quickly filled up. The initial audience is very much people maybe are going to us instead of Mayo Clinic, which… They can spend $25,000 and fly to Minnesota and spend two days there or they can go down the street, spend an hour, we actually measure more, we aggregate your medical history, do genetics, chemical-structural analysis, and then we make it really easy to see what’s changing, and we automatically surface the most salient changes to you and your doctor in a shareable dashboard. And that is why I think Parsley customers and Forward customers actually were complimentary is they’re effectively concierge practices, and we just give a next level of understanding what’s changing your body to those customers.

Our price point right now is, for aggregation of your medical history for a year and one exam a year, it’s $3,495 and that’s primarily because we’re volume constrained. We’re capacity constrained. We’re going to be opening more facilities and we expect to actually drive this price down to be well under a thousand dollars in just a couple of years. And, that’s when I think it starts to get interesting to work with payers and other systems for specific demographics that are high risk. And, I think, then we’ll continue to drive the price down and then it will open it up to even more people. Because, I think when we get to sub $500 and 20 minutes to measure everything more accurately than we are right now, I think it starts to really look like the physical of the future.

Lee: I know I have to let you go, but if I can just keep you for a few more seconds, and feel free to answer me very rapidly. Two questions, and I promise to leave it there. How do you differentiate yourselves with Human Longevity with their Nucleus service? And second, do you think that following coronavirus there will be more impetus to come to Q Bio since it’s those who are in less than optimal condition, i.e. high insulin resistance, who are predominantly suffering the worst and have by far the greatest mortality are those who are in a sick condition?

Jeff: Sure. So, I’ll start with the first one. I think the biggest difference … I’m, in general, actually a fan of Human Longevity. I think what you get from them is much more of a research project. There’s a lot of things that they measure that don’t really cut our bar for clinical information value or reproducibility. So, we’ve chosen to focus on things that, if we’re going to charge people for it, we want to make sure we’re maximizing the clinical information value per unit time per dollar that they spent. So, we want to measure more, faster, cheaper information that a doctor can use. Human Longevity is doing whole genome sequencing, metabolomics, proteomics, and some other things that it’s not clear what their value is yet. And I would even argue that because they can’t be reproducibly measured, their longitudinal value is questionable. But, if you want to have the latest cutting edge set of measurements and we don’t know what they mean, and you’re willing to pay more and spend four or five hours going through this, then that’s good.

I think what we’re really focused on is how do we do something that can be done at a population scale, is completely noninvasive so you don’t expose to any radiation, and I know HLI uses a CT scanner which involves radiation… Something that we do has to be noninvasive enough that you could do it on a child eventually or a pregnant woman, and fast enough and cheap enough as well. So, that’s where we’re really focused. And, we have technology that allows us to measure much more, as far as clinical information is concerned, at a cheaper price faster than they can. And, we’re also focused on the tools that allow a doctor to find the most information or the most important information fast because we expect to continue to measure more cheaper and faster, which means the doctor’s tools actually need to get smarter in terms of surfacing the most relevant things about your health to them.

But again, their background really is much more of a research institute and trying to decode the human genome. We do a much more focused panel of 157 genes that have very widespread clinical acceptance to understand what they mean. It’s not to say that there aren’t going to be more in the future. We’ll add them as we think it’s appropriate. We just don’t want to charge people for information that their doctors can’t use and that they can’t use right now. If we’re to have a research biomarker in our protocol, we don’t charge somebody for it or we wouldn’t because we want to study it, and because it’s just not ready for prime time. And that’s why we do studies.

But, as far as the latter, I think that’s an open question if we’re getting into the coronavirus. It certainly hasn’t affected us yet too much, but we’re also not everywhere. We’re in the process of opening a number of locations around the country where we have wait-lists, but I don’t know that we have enough data to know. But, it’s certainly an interesting question. But again, I think that if you take a step back and think about really what we’ve built in trying to build the first platform that was really optimized for measuring clinical changes in the human body, it goes beyond just finding disease. It goes for understanding how doctors, when they intervene, if it was successful or not. Or, if they prescribe you a drug, if it’s having any negative side effects. It’s just this fundamental idea of can I understand how my behavior or a doctor’s interventions change me and affect my health trajectory?

So, I think that that is much bigger than just early identifying location of disease. It’s much more holistically helping us understand and how we manage our bodies and health.

Lee: And corona, do you think it will be a driver of people getting more proactive instead of passive?

Jeff: I think it’s hard to say. To some degree I would be surprised if it was. But, I also know that there’s a lot of people that have told me that they expect it to be creating a huge surge in demand. But, I think it remains to be seen. I think that it depends. It really depends on how scared people are. And I think the other aspect of it is how actionable the information we could provide is. Ultimately, I think as far as coronavirus is concerned, if their fear is related to coronavirus, the only thing that’s going to dissuade them is a test for the coronavirus.

Lee: But you want to protect yourself against future pandemics, and they’re coming up more and more.

Jeff: Look, one of the first customers and people I built this platform for was me after a health incident that I had, and I spent a bunch of months in a hospital bed in 2008. And the way I look at it is this, when it comes to our platform, 100% of us at some point in our life will get severely sick or hurt. The question is when that day happens, what tools will doctors have to understand what has changed recently so that they can correlate those changes and identify what the problem is. And, that’s actually when time’s of the essence. And that’s part of the human condition. 100% of us are going to face this issue.

So, I really look at this as preparing for something that’s absolutely inevitable and wanting to make sure doctors can quickly figure out when time is really of the essence. If you figure out what’s wrong in weeks versus months, that could be a massive difference in outcomes. So, when you think about it from that perspective, if there’s a new pandemic and we don’t even know how to identify or test for it, if we know what changes it causes in your body, sure, it’s great if I can just go back in for my routine physical and say, “Hey, are the changes that have occurred in my body consistent with symptoms or issues that people are reporting that have confirmed to have this virus?” So, it’s an indirect way to identify, and I think that that is a potentially useful thing.

Lee: Jeff, it’s been absolutely fantastic talking with you. I greatly appreciate you sharing your vision, or the Q Bio vision. I don’t want to keep you any longer. I feel guilty enough how it is. I greatly appreciate, and I super hope you’re going to be back.

Jeff: It was a lot of fun. I’m looking forward to doing it again. Take care.

The phrase, “the art of medicine,” has bothered me for many years. With technology already at the forefront of medical discovery, and improving everything else in our daily lives, why do people still die from treatable conditions? Why haven’t we applied the same scientific principles that have led us to understand the evolution of the cosmos, weather patterns, particle physics, or planetary motion to the human body? 

When Life Gives You Lemons…

I recall standing in my office in San Francisco years ago, waiting for an update to a mobile analytics platform my team had built, the second largest of its kind in the world at the time, with hundreds of millions of active users all on their cell phones, all over the world. It became clear to me that for the first time in human history we could begin to measure and quantify human behavior. At that moment I felt I was witnessing the transformation of sociology from an art, left to academics, to an information science.

I’d finished early on a dual degree program in Computer Science and Physics, mostly because I had been told it was impossible (the single best way to get my attention), and had consequently spent my post-college years starting tech companies that solved problems ranging from network security to consumer lending, punctuated by chunks of time off to recharge by skiing in remote places. The master plan, despite my father’s insistence on an MBA, was to move to Wyoming and spend the rest of my life chasing winter, but something I could never have imagined derailed those plans. 

In June 2008, I was clipped by a car while training for an Ironman. The impact dislocated and shattered my left hip and cracked my pelvis. I also tore muscles off of my right elbow, and a quadricep off my right knee. I had massive internal bleeding, could only move my left arm, and spent much of the year bedridden. At one point I was told I had advanced avascular necrosis in my hip and if I didn’t get a replacement I would lose my leg. I was able to avoid a hip replacement, but still required major surgery after dealing with months of conflicting diagnoses, and struggled to get hospitals to share information about my body, which delayed my recovery. 

On top of this health crisis, the driver who hit me was uninsured, and my insurance company refused to pay for the critical care I needed, pending an investigation. The financial crisis of 2008 compounded these problems, and I was forced to sell my house and everything else I owned in order to cover the hospital bills. In three short months, once in great health and financially secure, I found myself unsure of everything: I didn’t know if I’d be able to walk again, let alone live the life I imagined, and I was broke. 

 What I did have, however, was a front row seat to the complexities of both the finance and healthcare systems, and the better part of a year in a hospital bed to consider how some foundational concepts in both needed to change. My reimagining of the lending industry ultimately led to the creation of Affirm but rethinking healthcare presented a more interesting, complex problem. As an athlete, dedicated to my own health, I found it bizarre that not one doctor could determine what had changed in my body due to the accident, and efficiently assess my condition and treatment plan. But as a scientist, I wondered why there wasn’t a tool with which to comprehensively know the state of our health on a regular basis — not just when we’re sick or confined to a hospital bed, but all the time, and perhaps even before small problems become big ones. 

Building the Q Bio Platform

In 2015, Q Bio was born, and we set about to first consider these key principles:

1. Why We Measure, What We Measure, and How

Every person reading this will get sick or injured; it’s inevitable. Our concern should be making sure when this time comes that our doctors have the best tools/information available to determine the cause of the issue, when time is of the essence. The most valuable thing to know at this time is simply what has most recently and significantly changed. This isn’t screening, this is preparing for something inescapable, and we call it “health monitoring”. With this in mind, we designed first platform able to comprehensively measure and identify clinical changes in human biology, associated with common causes of death. In less time than it takes for an average dental visit, Q Bio measures thousands of genetic, biochemical, and anatomical biomarkers. Our platform then continuously aggregates and analyzes a person’s medical history, looking for relationships between past or recent health events and changes in a person’s body that may increase risk. Ensuring this process is non-invasive and fast is critical so that it can be done regularly and reproducibly. We believe this is the physical exam of the future.

2. Clinical Value and Actionability 

A research team including Dr. Michael Snyder, one of Q Bio’s founders, studied a group of more than 100 patients for up to eight years, measuring data on them every quarter. During the study, the researchers discovered more than 67 potentially serious health issues, which would not have been discovered as early, if at all, without this level of data analysis over time.

It’s simple but true: every human body is different, and even genetic twins make decisions over the course of their lives that make their risk profiles diverge. The best way to know if there is an issue emerging in your body is to compare you to you. Most diseases are accelerating processes, so assessing health risk on an individual level based on what is changing and how fast will yield insights about the progression of disease far better than comparing single measurements about you today with outdated, unrepresentative population references. 

At Q Bio, we believe firmly that this tool can dramatically affect the outcomes of your healthcare decisions for the rest of your life. 

In order to make sure there is clinical value in the Q Exam, we consider every biomarker we measure with two specific characteristics in mind:

• How well it can be reproducibly measured
• Existing clinical evidence relating a biomarker to specific health issues 

While we are excited about all the research going into the discovery of new biomarkers and tools to measure them, many of them do not sufficiently satisfy these criteria, which we think are critical in order to make information actionable for clinicians and increase confidence in clinical decision making. So we have focused on making better use of existing biomarkers to make sure we are providing immediate actionable value to our users and partners, while continuously evaluating and integrating the latest biomarkers into the Q Exam as they are ready for clinical use. 

Actionability is an important characteristic of clinical information, but there is a difference between actionability and clinical intervention. Having actionable information also means knowing when the best course of action is to do nothing. Too often in our health care system do we intervene with drugs or procedures due to a lack of good information and then do limited follow-up to gauge if that intervention not only had its intended effects, but to make sure it didn’t have any unintended side-effects.  

3. Empowering Doctors with More Information Requires New Tools

An important part of our mission is to build technology that makes doctors more effective, so that they can spend more time with their patients who need it most. 

Today, a single physician can see about 2,000 patients a year and has an average of 15 minutes to spend with each, a significant amount of which is spent logging opinions into an EHR. Highly skilled labor is an increasingly scarce in today’s healthcare system, and this is an ineffective use of their time. If we want preventive healthcare to be available to a growing population, we either need to make more doctors, faster, or doctors need to spend less time with each patient on average. In other words, we need to give doctors the tools so that they can focus more time on people who need it most, and less with those who don’t. 

To this end, we designed the first platform able to quickly sift through vast amounts of information and surface the most relevant clinical chemical and anatomical changes in a person’s body broken down by the major subsystems, weighted by their genetic, medical history and lifestyle risks. This removes the obligation to pore through EHRs, which are designed for billing and administration, not to help a doctor understand the dynamic factors impacting someone’s health. Allowing doctors to quickly find emerging issues and identify individuals who have no major immediate risks saves time. 

4. Empowering Individuals

The rise of wearables, smart scales, etc. is driven by the underlying desire of people to have better access to and control over information about their bodies. Ironically, the vast majority of this information isn’t clinical quality and cannot be easily used by healthcare professionals in their decision making. Q Bio is the obvious next step in empowering people, not just with more information, but better information, with actual clinical utility so that it can be incorporated into their care. For the first time ever, Q Bio gives people complete control over this information and with whom they share it, making slow, painful processes like second opinions, or re-testing things of the past. 

That’s what we are all about at Q Bio. There is growing evidence that a data-centric approach to healthcare will lead to better outcomes. We have the technology to comprehensively measure the human body, tracking clinically relevant and measurable biomarkers for individuals. We have built the software that, with today’s computing power, can analyze the data, and see trends over time, and give that information to individuals and their physicians in an actionable way, as defined by a higher standard.

The Paradigm Shift

We can change medicine from art to science. We can empower doctors to take better care of more people and give patients the efficiency and privacy they need. We can build a healthcare system that does far more than screen for disease and react to problems once they’re existential. It’s a fundamental transformation of medicine that we can and must make. 

That’s why we built the foundation for the Science of Medicine; the first platform ever designed to comprehensively and efficiently monitor changes in human health.

Jeff Kaditz, Q Bio CEO and Founder

I’m excited to share that I’ve joined Q Bio as VP of Radiomics. My journey here has been a long time coming. Even before entering college, I had decided that I wanted to focus on radiomics. I thrived on solving problems since I was a boy, but I was really bad at playing computer games. I could never win! And often I ended up just hacking my computer. My mother always thought that my computer was broken because I was modifying it so much. When I first heard about the ability to view the inside of humans with computed tomography, I built a viewer for MRI images on my computer… and I was hooked.

And so I oriented my education in that direction. After I landed my first job in a fMRI lab during my first year of college, MRI machines became literally everything to me. Some 15 years later, after completing my PhD at MIT, I became the head physicist at one of the best MRI research laboratories in the world, the Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital. I got to solve problems that are meaningful to me and to take care of a family of 8 human MRI machines. This involves, besides QA, technical diagnosis of problems and pulse sequence developments. I also supported and collaborated with several hundred users of the center. My computer science side has not retired, so sometimes I find myself debugging Linux kernels, chasing down BIOS bugs, programming FPGAs, …on top of soldering custom equipment I developed.

My work interests focused on two areas. One is the optimization of clinical MRI procedures and to translate new MRI techniques into the clinic faster, which will ultimately allow for better diagnostic quality as well as increased patient comfort. MRI has been incredibly important for modern medicine and it’s a prominent tool in diagnostic medicine and biomedical research. But it’s also been expensive, time-consuming, with poor reproducibility and as such, only used in acute circumstances.

As a tool, MRI captures chemical and physical data, in addition to generating detailed spatial images. And importantly, it does not expose the human body to any radiation as with other more invasive imaging technologies. There is an opportunity to think about focusing this technology on health and not just on sickness. What is possible when we use it for preventive care? What will a whole body scanner of the future be like? In many aspects, today’s MRI machines are still confined by the basic principles set over 30 years ago. With modern computers and appropriate generalized algorithms and low-cost multi-modality sensors, many of these principles are no longer valid and the hardware can now be rethought. It was time for me to get a bigger garage.

When I met Jeff and the Q Bio team, I saw that they shared the same passion and conviction in making whole-body scanning part of the standard physical. They are also already up and running with a rapidly growing service that has helped individuals and their clinicians gain valuable insights about their health and their bodies. The team has already caught early diseases that have significantly changed the health outcomes of individuals — actually saving lives. Real-world impact and the potential to build and learn together with an interdisciplinary team. I decided this was where I wanted to build that garage.

At Q Bio, I’ll be leading a team to help the larger interdisciplinary Q Bio team to make cutting-edge morphological measurements over time a reality. Together with clinicians, software engineers, and bioinformatics analysts, we work on MRI physics, hardware debugging, sequence programming, advanced reconstruction, auto-segmentation, C++, Linux… and in between, enjoy some hands-on building and playing with magnets and novel sensors.

Our mission at Q Bio is to make it easy for individuals and clinicians to measure the most important changes in the body to help identify disease at its earliest and most treatable stages. If interested in this mission, please reach out. I’m hiring!

I’ve jumped in to the deep end again. And it’s one of my favorite times of building and scaling a business. The early team of less than 20 have worked with the founder to prove early concept and solved some of the hardest technical product problems. Early adopters are returning as users and word of mouth is driving real demand. The early glimmer of an idea has been substantiated and now lives and exists at the core of the company. Yet there are still many unknowns and so much to be figured out. But there’s a team here willing to work together to solve hard problems and actively learn together. This stage of a company — early and at an inflection point in building visibility, brand, usage, membership, and becoming a full-fledged business with lasting social impact is incredibly exciting. One of my favorite times to jump into start-up trenches.

So here I am at Q Bio. I was incredibly inspired by my early conversations with Jeff, Garry, and their early investors and board. Their vision and mission: treatable diseases no longer take lives, and every generation is healthier than the last. That’s a big and dynamic peak I’m motivated to scale. I’m honored to be able to join them on this mission.

Before joining, I had the rare privilege of being able to take 7 months off. In that time, reading, talking with friends and family, traveling, playing with new ideas, I have always come back to what makes it worthwhile to work. For those of us lucky enough, our time is the most precious resource we have. And this is amplified for me with 3 children at home who can always use more of my time. The mommy guilt is real. Yet I like to work hard on hard work and so where and how has to be meaningful if I’m away from home. Improvements in education, the environment, and health care have always been the 3 areas I felt would make the most difference in my children’s life and future.

The team at Q Bio is solving for truly actionable and hard science. They take their mission seriously. And what’s really inspired me to make the jump to Q is a set of core beliefs and how they are approaching building a solution that aligns with where I believe health care is going / needs to go. The team here believes that…

.…Prevention is better than the best treatment

This seems perhaps obvious. Those of us who try to exercise, eat healthy have absorbed this belief from a young age. I do this for my kids as it’s required for vaccinations, well-baby / well-child check-ups, and there’s a given schedule. My oldest, however, is already aging out of this schedule. It’s crazy that there’s a gap starting with older teens and young adults where we no longer have annual check-ups and only reactively go see doctors. For women it’s a bit better with ob-gyn check-ups, but the last time my husband and I had a comprehensive exam was in Taiwan over 4 years ago where there are more affordable and welcoming options. As Jeff Kaditz, Q Bio’s CEO/founder likes to point out, seeing our dentists regularly is the only model of regular, ongoing check-ups we do for our health. It’s not just anecdotally important, but lifestyle and prevention as medicine represents at least a 40% opportunity to improve population health.

…System biology that brings affordable, non-invasive radiomics side-by-side with clinical biometrics will revolutionize our understanding of the body.

To tackle this, Q Bio is looking beyond targeted treatment populations. Instead, the team takes a system biology approach and focuses on known markers and actionable insights for a broad and overall healthy population not worried about immediate disease treatment. The focus is on preventive medicine. As it turns out, all of us have something that may be “off” at any given time that does not require intervention. Or many of us manage and have under control some health concern, but don’t really have a full known treatment available. I have allergies that come and go without any clear understanding of what triggers them. There’s much that medicine still does not understand in terms of what a spectrum of health looks like. The approach of studying just single parts — whether genomics, microbiology, or focus on specific tissues or metabolic systems — feels like the parable of the blind men and the elephant. The conversations around inflammation and what it really reflects; or the recent unfortunate failures in Alzheimer medication trials because, as it turns out, there are larger systemic dependencies that a single path of treatment can not solve; these are all examples of where having interdisciplinary and holistic data would help us better understand our bodies. At Q, the specific focus has been to bring non-invasive, repeatable, and comprehensive radiomics together with known biometrics (i.e. data from genetics, blood, urine…) to provide a full picture of individual health.

…Actionable, individual changes in your own health over time is better than single point in comparison to population average for health baseline

And they are looking at this over time. The goal is to provide a big data, longitudinal view of health. The underlying thesis being individual risk factors are better indicator of health than comparisons to larger population averages. For those who are quantified health geeks, this goes beyond sleep trackers, FitBits, Apple Health, to look at known and actionable clinical markers. Note that this is not about research level omics, but replicable and known markers. And the goal is to catch any potential for disease early so that the focus can be on prevention and to not drive individuals to overtreatment, but instead early engagement before reactive treatment required. Interestingly, Q Bio to date has found that in about 21% of visits, clinically significant high risk factors affecting mortality and still at an early stage were found that informed clinical decision for early intervention or additional diagnostic evaluation. This represents significant cost savings in healthcare and, more importantly, better individual health outcomes. All a result of tracking early and personal baselines for individuals.

…Individuals should have access to and control over information about their health and bodies.

Finally, the team is committed to putting members first and engage with an individual’s chosen community of care providers, no matter who or where. This means focusing on privacy from day one and having high controls in place on how we collect data. I have not met many start-ups that have IRBs in place from the get go. And from a data ownership standpoint, so much of healthcare can be frustratingly truncated or locked within a system. To get second opinions, to move, to change providers often means a loss of your health history. And many companies in this space keep information they gather over individual health as proprietary. I really like the trust that Q is building with members by committing to provide full access, portability, and control over their health information. This is about truly empowering members.

At Q, we are building the physical of the future.

For any of you who’d like to jump in as well, please reach out @clarissa_shen! Come take control of your health and join us on this mission to make every generation healthier than the last.

We are entering a new era of data-driven health monitoring. In addition to conventional approaches, we can now determine genome sequences, collect data about thousands of molecules (RNA, protein, metabolites, lipids), perform advanced imaging, and continuously monitor physiology.

Importantly, we can follow people over time, during periods of disease and health. In today’s Nature Medicine article, my scientific colleagues and I describe the results of a research project called Integrative Personal Omics Profiling (iPOP) that illustrates the value of using advanced technologies to carefully follow 109 people for about three years (many for four or more years) and how this can be applied to manage health. This study uncovered 49 clinically significant health findings — plus 17 more if hypertension is included. Some of these findings were very consequential — early detection of lymphoma, two precancerous conditions, and two serious heart conditions. There were a variety of disease risks identified (e.g. for cancer, cardiovascular disease) and early signs of disease (e.g. diabetes) that were actionable.

The ability to focus on early intervention and prevention represents significant cost savings in healthcare and, more importantly, better individual health outcomes.

One of the core beliefs of this approach is that tracking individual changes over time is better than examining population averages alone in identifying clinically actionable, early health interventions. This study confirms that belief. Population health data inherently looks at averages and may miss early signs of disease progression in an otherwise asymptomatic individual.

Existing medical knowledge is biased and there is a need to de-conflate the measurement of our biology from the analysis of our health. Tracking a well-defined set of biomarkers longitudinally offers the clinical advantage of detection at the earliest stages of disease where an intervention may be more likely to succeed in reducing long term morbidity and mortality.

Developing the Physical of the Future

While presenting the iPOP project over the years and all over the world, many people have asked how they can get access to these technologies to follow their own health. Consequently, Jeff Kaditz, Garry Choy, and I have spun off a derivative of iPOP called a Quantitative exam (or “Q” for short) which is offered by Q under an institutional review board (IRB) approved protocol. The Q protocol brings together many of the health-related features of iPOP and adds whole body MRI (magnetic resonance imaging). We began piloting the Q protocol in 2017 and have since expanded to include select partners, and interest is high.

The Q protocol has already shown promise that goes beyond iPOP by generating additional data around known and actionable set of biomarkers that includes non-invasive, whole-body, comprehensive imaging data.
This has allowed the team to not just track personalized, longitudinal changes…

…but to track these changes at depth across specific biomarkers.

By utilizing a multiomics approach similar to iPOP but further incorporating biometrics and non-invasive radiomics, to date Q has found information for at least one previously unknown health-related condition in 97% of member visits; this information is valuable for ongoing preventative monitoring. It is also further evidence that comparing against population averages does not really reveal much about the line between health and sickness. Given the healthy population served, the large majority of members did not have follow-up care required. However, in 21% of those first visits, the Q protocol uncovered clinically significant findings that were both high risk for affecting mortality and at an early stage informing clinical decision for early intervention or additional diagnostic evaluation. The ability to focus on early intervention and prevention represents significant cost savings in healthcare and, more importantly, better individual health outcomes. To quote one Q member: “Nobody has ever told me so much about me.”

We are optimistic that longitudinal deep profiling, accompanied by powerful data integration and analysis, will ultimately help improve healthcare. Individuals and their healthcare providers will obtain a clearer picture of disease risk and evolving health status. As one Q referring physician and member recently shared, “Q does a great job leveraging advanced biomedical science and technology to assist primary care providers to provide more informed, precise, proactive care plans to their individual patients. Q brings the ‘possible’ in the future of medicine to the actual care delivery in the clinic, now.”

We share this excitement and believe that future emphasis may be increasingly focused on keeping people healthy through predicting disease risk and catching disease early to avoid adverse health outcomes. We hope that precision medicine will become an integral part of healthcare and available for all.

by Michael Snyder, Ph.D.
Stanford W. Ascherman Professor and Chair, Department of Genetics Director, Center for Genomics and Personalized Medicine