In this seventh episode, Nathan Price, Professor & Associate Director of the Institute for Systems Biology, explains the concept and aspiration of 'scientific wellness'. He predicts that it will become the dominant paradigm of 21st century healthcare. He explains ‘personal, dense, dynamic data clouds’ will enable both peak wellness and disease avoidance. Possibilities that China may leapfrog the United States.
Lee: Hello, Nathan. Welcome to the seventh episode of the Hyper Wellbeing podcast.
Nathan: Lee, it’s great to be with you.
Lee: Appreciate it. The last time I saw you was at Hyper Wellbeing 2016 where you gave a keynote. That was greatly appreciated.
Nathan: It was a great meeting. Thanks for organizing.
Lee: Nathan, can you do a favor and jump in and just provide a quick synopsis of what systems biology is?
Nathan: Sure. Systems biology is essentially an approach that attempts to be holistic and quantitative. It’s holistic in the sense that you’re trying to understand the integration of multiple biological components and how they work together as a system to create phenotypes. It’s build on essentially to molecular biology that was mostly about trying to understand what individual parts do. Then the quantitative aspect is you’re trying to understand that whole system from making quantitative measurements, this is OMICS data and things like that, and then quantitative computational modeling. We try to then put it all back together. That’s essentially systems biology.
Lee: Putting it back together, can you explain that computational part? I just want to make sure that everyone can get that.
Nathan: Sure. We’ll take a simple example. Let’s take the process of metabolism in the body, maybe not so simple. If you look at the …
Lee: Yeah. Metabolism is a simple part in the body, Nathan, right?
Nathan: Yeah, exactly.
Lee: A simple part.
Nathan: Yeah. I did my whole PhD studying a tiny quarter of it, so it’s funny. It’s funny, [inaudible 00:02:41].
Lee: Yeah, some of the systems biology charts for metabolism are just absolutely ridiculous to look at. They’re 400 pieces and not just the high level simplified version.
Nathan: Yes, yes, exactly. In essence, if you’re doing molecular biology, you’re figuring out what does an enzyme do. You figure out that this enzyme takes a glucose molecule and phosphorylates or whatever it is that a particular enzyme does. In systems biology approach then putting it all together is essentially building those big complex maps that you’ve seen so that you start saying, “All right, we figured out through molecular biology and biochemistry what each of these enzymes does.” In systems biology, you’re putting that all together creating a map and then you’re building computational simulations of metabolism.
Nathan: You ask questions like, for this network, given what it’s eating, how much ATP can it make, does it have all the components necessary to make the amino acids, does it have the ability, how much redox flux can you deal with in this network, and so forth. Essentially, in systems biology, you’re trying to answer a question about how all those pieces interact as a whole. Then in systems biology, maybe you’re modeling a metabolic network. Then you ask another question which is, how is that metabolic network regulated? Then, you build a model of gene regulation that interfaces with that metabolic model and so forth. That’s one of the things that you do in systems biology, is just to try to ask that question of, how do all these pieces interact, how do they work together, and then how do they predict a phenotype or a trait that you care about.
Lee: Hey, Nathan, that’s super interesting. When you were describing there, I was like, hey, that’s what I would have studied if I could go back in time and begin all over again. I’m envious that that’s what you have been doing. It just seems absolutely fascinating.
Nathan: It’s really a fascinating area. I really love working in systems biology.
Lee: Yeah, it seems more of an engineering, computer science discipline, than what I would have normally associate with biology from my school days.
Nathan: Yeah. There’s certainly an element of that. My training actually is in engineering. My PhD is in bioengineering from UCSD where I work with Bernhard Palsson who’s also an engineer. There are different flavors of systems biology certainly. My path end did come more from the engineering side. We do think about how to take a system, take it apart, try to understand how the components interact together, get blueprint diagrams for how that system operates and often [crosstalk 00:05:34].
Lee: It’s just like fixing a car. It’s just like the blueprint to get for the car, wiring diagrams you get for cars.
Nathan: Yeah. There are some interesting comparisons back to that. Of course, there’s also significant differences because you’re dealing with an evolved system and you know the rules behind it are sometimes opaque. It just becomes [crosstalk 00:05:56].
Lee: Just complexity that you like?
Nathan: Complexity is fascinating. I don’t like to end a complexity. I think you try to deal with complexity and then at the other side, you try to get to the level of insight or simplicity and so forth. I think a lot of science, of course, is about trying to take these complex observations that we see around us and trying to see beyond the details, try to see something where we can make a simplification, where we learn something deep about a system. I think that’s what we’re always striving for. At a first pass, yeah, you just embrace the complexity and then you hope to be able to pull things out that are actionable. Actionable simplicity, I like to call this. I go from complexity to actionable simplicity, try to mine insights out of the data.
Lee: Well, appreciated for that. It reminds a little bit of good artists who say, “At the beginning, everything expands and gets messier. Then, as you get insight and develop your skills, you begin to simplify and sometimes the most simple thing was derived from the greatest complexity.” You mentioned the word redox, would you be so kind to just briefly introduce redox?
Nathan: Redox is basically just reduction and oxidation. Reduction and oxidation states in metabolites is one of the dominant transformations that has to be undertaken by metabolism. That’s what I was referring to. This is the point of things like NADH and NADPH and things like this which are really redox potential carriers in your cells.
Lee: You introduced in one of your papers – I think you did or someone at ISB – the term personal, dense, dynamic data clouds. Can you introduce the term please.
Nathan: Yes. This is a term that Lee Hood and I introduced in our Nature Biotechnology paper from last year. Basically, the notion is to generate data that’s personal, s it’s specific to every individual. Dense, meaning we make lots of measurements. Dynamic, those measurements are over time. The notion between having personal, dense, dynamic data clouds is that in essence what it’s going to give us is a broad view of what’s happening in a person’s body over time so that we can derive two things from it. One is to quantify wellness so that we can quantify health state, doesn’t have to be well but like a person where they’re at. You quantify that state.
Nathan: Then, second is to look for over time the transitions. One of our big dreams is to try to understand the early warning signs for all the major human diseases. We can figure out ways to predict them and prevent them. We believe that’s only possible really by generating these personal, dense, dynamic data clouds. That’s a big goal, of course.
Lee: What constitutes a data cloud? What type of data?
Nathan: It can vary, as long as it’s dense and dynamic. For us, what’s typically and what we’ve done so far is you have your genome as a baseline and then we have multiple time points where we measure proteomes, metabolomes, clinical labs, wearable devices data, microbiomes, those kind of data. You can expand that as well with immunosequencing, with epigenetics. Essentially, you’re trying to get a large amount of integrated data coupled with knowledge of what’s happening to a person and their health state, clinical data, and so forth.
Lee: Okay. It’s quite a mouthful, personal, dense, dynamic data clouds.
Nathan: It is. Dense phenotyping is the simpler version we’re moving to, as I think some of the field is as well.
Lee: This deep phenotyping, it will be used for two categories. First is quantifying wellness and the second is demystifying disease.
Nathan: Yeah. The quantification of wellness we’re very interested in. In fact, there was a quote I really like. I was on a panel a few years ago with “Denny” Ausiello who is actually the Chief of Medicine for Mass General at Harvard Medical School. He said something that really stuck with me. He said, “Healthcare is the only industry that doesn’t study its own gold standard, which is wellness.” I really resonated with that. It was right on, went with what we’re talking about. I love to hear it from someone who is in the position that he is in and with the gravitas that he has in the medical field, because it’s really true.
Nathan: As a community, there’s huge amount of research dollars that are spent on disease, that makes a lot of sense but we don’t have much at all that had gone into the quantified scientific study of wellness, the gold standard of the body and how it works. That’s really what we’re pushing on that front. We want to quantify wellness. We want to understand that state. The reason we really want to understand it deeply molecularly is because we want to be able to see and understand when the system starts to depart from a wellness state for each individual. Then, that leads to the second big point, this demystifying disease, which is really about identifying the early disease transition.
Nathan: Because what we believe, and actually in some diseases, it’s clearly true and we can start talking about that, which is that early stage disease can be quite easy to treat and reverse and late stage can be nearly impossible or we can’t do it today. The desire to understand that wellness state, understand the early transitions and be able to stop disease before it really starts is central to what we’re really interested in developing.
Lee: I’m smiling here because I would love it if we had like four hours together. I love to spend an afternoon with you and pick your brains over so many things.
Nathan: One of these days, we’ll get together.
Lee: Yeah, it’s just pulling me in. I’d really love some of a significant amount of your time at some point in the future. I’ll plot evil ways how I might be able to achieve that.
Nathan: Sounds good.
Healthcare is the only industry that doesn’t study its own gold standard, which is wellness.Dennis Ausiello
Lee: Anyway, if we look at healthcare, orthodox healthcare, at my event in 2016, you said and I think you were quoting the New England Journal of Medicine and your assertion. I quote, you said, “You can attribute by 30% of a person’s lifetime health outcome back to their genetics, about 60% of someone’s lifetime health refers back to their behavior and environment”. Choices that are easily modifiable, so our choices are part of behavior and environment, sorry, and “only 10% of a person’s lifetime health can be attributed back to the healthcare system.” That’s a stunning statement that only 10% of a person’s lifetime health can be attributed to the healthcare system.
Nathan: Yeah, it really is. I am just taking that data straight from 2007 New England Journal of Medicine paper that goes into the details of how they did that estimate. If you think about it, our interactions with the healthcare system is currently constituted are pretty sparse. You said, “Well actually, maybe this is our … ” Anyway, you don’t necessarily go to the doctor all the time. Some people are good about going in for their yearly checkup. A lot of people …
Lee: I haven’t been to a general physician in 17 years and that was for a checkup. I don’t know why I would go.
Nathan: That’s what I was going to allude to, but then I thought that was on this recording, that was our preconversation.
Lee: Yeah, yeah, it was. We can bring up here. I don’t know why you would go to a doctor. I’m quite confused.
Nathan: See? That’s the issue. Because of that, that I think is a huge driver for 90% of a person’s lifetime health really comes back to their genetics and even more importantly lifestyle and environment. Then, healthcare gets involved at certain really key moments. It plays a very important role. That 10% is important, clearly when you really have a terrible illness and you’re in healthcare system. But it doesn’t drive as much of your lifetime health as these other factors. We’ve really wanted to say, “Well, let’s focus on the 90%, understand more about what we can understand molecularly, so genetics plus blood measures and things of that nature coupled with lifestyle and environment.” That’s really a big element of the goals of scientific wellness.
Lee: I saw a paper. The title from memory was Personal Choices are the Leading Cause of Death.
Nathan: Yeah, personal choices that we make are … That’s the other [crosstalk 00:16:00].
Lee: Yeah, it was valid paper. It is in the 21st century. Personal choices are the leading cause of death in the 21st century. It’s not bacteria. It’s not viruses.
Nathan: Right. The greatest predictor of death, of course, is birth. We do care about what happens in between, living our life, having full rich life that is enabled by health, and that allows us to do the things that we really want to do in our time here. These things have a big focus. Just trying to empower people with knowledge to make simple choices that will help them have a lifetime of health rather and avoid unnecessary disease.
Lee: My grandmother worked in public health. It was quite clear from listening to her and also reading that public health had significant and even significant is understatement, achievements during the 20th century against infectious diseases had huge wins. Going back to her day, people really were at mercy of a lot of things which no longer are. I feel quite privileged. But now, in the 21st century, we don’t worry as much about bacterial and viral infections. Today, it’s really lifestyle which accounts for, say, 80% of disease. Would you agree with that?
Nathan: Yeah. There’s been a huge shift from infectious disease as being the dominant killers to chronic disease. That is right at the heart of this transition between the way that we thought about 20th century medicine and the way that we should think about 21st century medicine. It’s a very different set of problems. If you think about the success we had against infectious disease, it’s really stunning. All of the diseases that were feared by our ancestors, not so distant ancestors, we take it for granted that we’re not going to have that.
Lee: Yeah, even just a few generations actually.
Nathan: Just a few generations. My grandma actually suffered from polio. She had polio. That was back in the time. The polio vaccine came out shortly thereafter. If she’s born slightly later, she never gets that because the polio vaccine came out and it would have been done away with. Those successes were dramatic. What we think is the 21st century medicine is going to be really driven by more of an approach, the kind of things we’re talking about here in scientific wellness and what Lee Hood calls P4 medicine – predictive, preventive, personalized and participatory. We see that as being the heart of a 21st century medicine that will be tailored to tackle more of this 90% and focused more on the elimination of the chronic diseases, just like we did with the infectious disease in the last century.
Lee: Let’s just jump on to then and run with it. You mentioned the term scientific wellness, could you introduce that, Nathan, please?
Nathan: Yeah. The notion between scientific or quantitative wellness is an essence to generate these personal, dense, dynamic data clouds and use them as a way to quantify the healthy state for an individual and also across a population. In addition to just sort of that we feel well is a monitoring of different systems in the body to see that they are functioning properly. Then scientific wellness, some are paradoxically perhaps but I hope I can convince overseers of this is that scientific wellness is actually the key to understanding disease. Because if you have this quantitative understanding of wellness and these dynamic trajectories, then you can see how individuals start to transition away for wellness.
Nathan: You can see then the earliest transition states to disease. We start to see the individual path that people take into a disease state. I think that the signal to noise ratio is going to be much better when we see those individual trajectories than when we look at all late stage disease after many, many things that happened, not only the initial insult but all of the bodies trying to compensate for it. Most of our data now is at late stage disease. A focus on scientific wellness will give us a ton of information about all the early transition states. We think that’s going to be really essential.
Lee: Let me slow that down just a touch, just to make sure everybody listening can follow along. Maybe everybody does and maybe I’m just over concerned. You mentioned about the signal to noise ratio and let me clarify. What you’re saying is people first have to notice that they are sick, that they have symptoms. Then go to the doctor and then realize, say, they’ve got stage four pancreatic cancer. By the time you begin taking measurements then, that’s definitely very unfortunate for them and it’s unfortunate usually economically too because you have to spend so much on late stage.
Lee: What you’re saying at the data level is the data is quite dirty, maybe because it became corrupted by the body trying to respond in a defense type fashion to processes that have taken place. Whereas a data would have been much clearer to separate out much earlier and that’s the disease transition. This is what you’re saying, right?
Nathan: Yes, that’s in essence what I’m saying is that if you have dynamics, what we see is that early on, there’s usually a small number of perturbations to the system. We track a lot these values that diverge away from normal. Early on, you see usually a relatively small number of things that do that and a sense to get bigger and bigger and bigger as you get closer and closer to diagnosis.
Lee: It becomes harder to decode and decipher the order and the sequence in what’s going on because so much is actually now going on.
Nathan: Exactly. More and more process have been affected. At the end then, and we do a lot of these analyses. It’s very conventional thing to do in science. You take OMICS data. I’ll use myself as an example. We have a grant to study Alzheimer’s disease. We study Alzheimer’s disease. We actually study the brains of people who have Alzheimer’s and those that don’t. When we do that after a person has died, no one’s given you a piece of their brain before then. We get these signals, but they’re very late stage. We can say, okay, what was different in this Alzheimer’s brain from the person that didn’t get Alzheimer’s? It’s very messy signal at that point. Because, for one, you’re getting postmortem tissue. I should clarify, we don’t actually get tissue. We just analyze data from people who do this. We don’t actually get [crosstalk 00:23:32].
Lee: Nobody is posting you new brain slices.
Nathan: No, no, not me. We get data from this. When we look at these data, but there hundreds of genes that have changed, tons of proteins, micro or anything you look at. There is massive numbers of changes. Some of that is informative but it doesn’t tell us what we really want to know. What we really want to know is what was happening in the bodies of these people 20, 30 years before and what was happening in the body of the person that went on to get Alzheimer’s that wasn’t happening in the body of the person that didn’t. What we really, really want to know is if we had seen those early signs for the person who later was going to transition in Alzheimer’s. Could we have stopped it? That’s what we want to do for many disease.
Nathan: I’ll give you another example, one that’s already well worked out. Alzheimer’s is a tough problem. Let’s take diabetes. Diabetes is a very familiar case. I want to just point to it as an example. We understand pretty well the mechanisms behind diabetes. We actually have a clinically defined group called prediabetes. In prediabetes, essentially is monitoring for a health and a system. You’re looking at your ability to regulate glucose. If you start to develop insulin resistance, then this is a sign that you might transition to diabetes.
Nathan: Now, if you’re prediabetic as I used to be, then you, your insulin resistance, you can watch this tick up. The intervention for reversing that, for type 2 diabetes, prediabetes for insulin resistance is pretty simple. You lower your sugar intake, exercise more, just monitor a number of different factors and you can back out of it, pretty simple. Now, if you get to late stage diabetes, you have very serious complications. You can read all the horrible symptoms; you could lose a limb at the very extreme. It’s horrible. You got to end up taking insulin shots all the time and so forth. You end up having all of these issues if you let it go to that very late stage.
Nathan: I think it’s a beautiful example of how if you’re monitoring for something simple like your insulin resistance and you watch it tick up, you can back out of that disease, no problem if you do it early enough and if you’re paying attention to it. Once it gets late, it’s hard and it’s laden with complications. What we want to do is figure out for how many diseases is that true. We think for the chronic diseases that that will be true for most of them, that there will be a way to define a pre-disease state, probably with ways that we can intervene that are relatively simple, relatively straightforward, relatively safe, and just trying to reduce the need to get into that really late stage situation.
Lee: Well, I think type 2 diabetes is a great example. From what I’ve been looking at, most people could spot it coming, say, a decade away, maybe even longer with simple measurements.
Nathan: Yes, yes.
Lee: If you look at the cost of diabetes economically and you look at the cost to the individual, I mean collectively, I mean to society, it is massive unnecessary suffering taking place. That’s what really alarmed me that there is something wrong with healthcare when I realized that millions are walking into diabetes unnecessarily so and are very late stage when they’re being informed. Then, a separate issue, they’re getting quite bad information typically on what lifestyle changes to make and very few doctors are telling their I want to say patients or clients, I’m not sure which to pick. Patient seems very paternal just for diabetes. The patient, “come in young man”.
Lee: By the time you go to the doctor, it’s late stage and then this information they give, they don’t say, “Hey, you’ve got a choice, that you could alter it with lifestyle.” They don’t mention that you can reverse diabetes, whereas I know you can because I’ve done it. I know other people who’ve done it. In the past two years, especially likes of Virta Health coming up more and more awareness of it, that you can reverse it. It’s not a progressive disease.
Nathan: Yes. This we could into all kinds of other issues in terms of health and populations because behavior change is challenging for people. Data alone does not change behavior. That’s been pretty well established. That’s one of the reasons we work a lot with health coaches to try to help individuals achieve behavior modification. From a larger societal point of view, it’s also true that just the environment and how we construct it makes a huge difference. People who have really studied this see this all the time because if you say …
Nathan: In some cases, from a societal level, it’s not surprising that we have a diabetes epidemic. We create foods that induce diabetes. We market them heavily. We try to make them as a society and in portions of society we work to make them as addictive as possible, et cetera, et cetera. Then, we turn around as a society and say, “Oh, wow, we have a diabetes problem. We need to emphasize more late stage healthcare, which also cost a fortune.” We have this skyrocketing healthcare costs. We feed them as a society a lot of these problems on the frontend. You could see this as other societies go through Westernization and processed foods become more ubiquitous and things like this. You could just watch this. The time series is I’m sure you’ve seen on diabetes in our country and worldwide is staggering.
Nathan: The level of which that’s going up has been unbelievable. At some level, people have some understanding of what’s happening. I think it’s a little different when you make the measurements in your own body, it certainly made a difference for me when I just watch it tick up over time. I’m like, “Wow, I’m on a path I don’t want to be on.” I think that is useful to then tie back. There’s all kinds of other issues which maybe beyond what we want to get into today on just the social ramifications and how societies really have to think about how you construct an environment in order to have a big impact on public health.
Lee: Yeah. It concerns me greatly how we organize ourselves at a societal level. I’ve got grave concerns there. Unfortunately, I do feel them in a position to greatly influence that. I decided I would aim at the individual level and hope that this macrocosm would end up reflecting the microcosm.
Nathan: Yeah. I think that that makes a big difference. There’s been other studies that I’ve looked at, health is contagious so to speak. In other words, your health is influenced by your friends [crosstalk 00:31:31].
Lee: Yeah, it’s average of your five best friends type of thing.
Nathan: Yeah, exactly. You becoming healthy will probably help other people around you. That’s a …
Lee: Let us put to this way. There’s a lot more people walking to the blood test lab where I live than there used to be. People used to only go in there when they were sick. It’s spreading like a “virus”. Hey, go in there before you get sick and be super happy that it’s very cheap, where I’m living. Here’s how to interpret the data. Here’s my spreadsheet. When you were talking about environment, food deserts come straight to mind because some parts of the States I’ve been in, you can walk and you will find nothing healthy. The book comes to mind …
Nathan: Yes, a huge issue.
Nathan: I have not read it.
Lee: Yeah, yeah, yeah. I’ll need to send you a link because Robert …
Nathan: I have to check it out.
Lee: … Lustig has that Sugar the Bitter Truth, the highly trafficked lecture he gave on sugar.
Nathan: Yes, yes. I’m familiar with Robert and what he’s doing.
Lee: Yeah, this Hacking the American Mind is on my reading list. Anyway, in terms of doing a quick calculation on insulin, on type 2 diabetes coming, the most simple one I can think of is just the homeostatic model assessment (HOMA). All you need is your insulin. That costs me 12 euros. Your glucose which is … Well, you can measure it for free at home, or pay two euros or whatever. So you’re only talking, at least where I’m living, 12 euros, put into a HOMA calculator and you get something somewhat reasonable coming back, at least it’s better than just measuring your fasting blood glucose. I don’t find fasting blood glucose a great … I just feel very uncomfortable using that only to predict or to get gauge on insulin resistance.
Nathan: Yeah, I agree.
Lee: Okay. You mentioned scientific wellness and we spoke of that. Then you wanted to somehow … I’ll use the word bootstrap, this scientific wellness concept and you created something I guess with Leroy Hood called the 100 Pioneers. Can you tell me about the 100 Pioneers?
Nathan: Yes. We had been talking about some of these ideas conceptually for a while. We wanted to figure out a way to get traction and really move this ahead. We watched [sic: launched] early 2014 something called the Pioneer 100 Project. Essentially, what we did was just recruit 100, ended up being 108 people, mostly from the Seattle region but some from few other places as well into a program where we were going to prototype what we thought what we could learn from generating all these data. It was a feasibility study in essence to see could we collect all these data that we build systems to try to find some insights and would it be meaningful to people.
Nathan: That was our real thesis. Because a big leap that we had to make was in scientific wellness, this concept was we thought that the key to generating these longitudinal, dense dynamic data clouds for being able to see those early transition states. The really key was, is there enough information in them now so that they are meaningful to people now? So that there’s a reason for someone to go through this program that’s in the present and not only in the future. When we did the Pioneer 100, we got all these individuals together and it ended up being just a wonderful experience. We did monthly events where we walked them through and do education. What is a microbiome? What are these blood measures, so forth? That was fun and informational element to it.
Nathan: Then people came through and every three months, over a nine-month period, they got their blood drawn and we would measure. We did whole genome sequencing on everybody. Then at those three-time points, we did proteome out of the blood, metabolome out of the blood, clinical labs about 150 different clinical labs, out of the blood. We did microbiome from feces. Then they had to wear wearable devices, Fitbits and things like that. All that data together, was really fascinating.
Nathan: I think one of my fears back then was maybe we’ll make all these measures. It’s going to be scientifically interesting, but maybe there’s really not very much to tell anybody. That was probably my number one fear when we are first setting up the studies. Maybe there won’t be anything to say. What was really surprising to me was that in fact for every single person that came through, there was something pretty interesting that we could tell them that they weren’t aware of from these said measures. For a number of people, it turned out to be a hugely impactful in their health.
Nathan: A number then said this was the best health experience they ever had even though this was not a healthcare study, just a research study. Even still, working with coach and there was a physician that interfaced with people as they went to the program, had an effect with them. There was some interesting things. One person, just to give an example, this was someone who actually had concierge medicine on both coasts by virtue, their job. He had developed arthritic-like symptoms in his knees and ankles. This was causing him a lot of problems. He couldn’t hike in the mountains with his family anymore, which is something he really loved to do.
Nathan: He was having these issues. He came in our program and we did this 360-degree view all these data and something pretty simple jumped out, which was that the ferritin levels with iron essentially in his blood was really high. We looked in his genome and he had the genes that gave the highest risk for disease known as hemochromatosis. We gave that information back to him, to his physician, back in the healthcare system. He got diagnosed, in fact, with hemochromatosis. What’s fascinating is that hemochromatosis is, it’s mainline can lead to liver dysfunction and ultimately death. You could die from hemochromatosis.
Nathan: One of the lesser known side effects is that that iron can actually catalyze cartilage breakdown in some people. In his case, basically, he got treated for hemochromatosis. Those aren’t aware of this, treatment for hemochromatosis is dead simple. Donate blood once a month. Physicians have a fancy name for it, therapeutic phlebotomy like in everything in medicine. Basically, give blood once a month. Get rid of that. Getting rid of the blood gets rid the excess iron. Brought his levels back to normal, and the cartilage issues in his knees and ankles subsided. He was able to get back to hiking with his family. We thought that was really meaningful.
Nathan: Again, it’s a very simple example of because he was empowered with knowledge, he can make a very simple choice, in his case, donating blood and eliminate a disease. He was one of the two. We had a second person who also had the genes that gave the highest risk for hemochromatosis. She is a woman. She’s premenopause. For obvious reasons, she would not have manifested this but tells her that, okay, no need to be alarmed. You got these genes that gives you a high risk for hemochromatosis, just monitor your ferritin levels. If they ever go up, donate blood. She’s empowered with knowledge to eliminate the disease trajectory from her future, completely doesn’t have to exist for her.
Nathan: If she doesn’t know it and she just go on along in her life, there’s a good chance she will develop hemochromatosis. With the knowledge and this very simple decisions, she can eliminate that disease trajectory completely from her future. That’s the kind of thing we’re talking about.
Lee: Ferritin, I measure periodically and it’s only 5.60 euro. I mentioned prices only because it’s so insane if you can access at such cost not to check such things or for example GGT which I find a great marker. You’re speaking of two people of what was called the pioneer 100 study, right?
Lee: When was that study done?
Nathan: That study was done in 2014. It ran from I think it was April through December of that year, when people are actually through. Then, of course, we did a lot of data analysis subsequent. That was the genesis of that.
Lee: Then, you’ve also got something the 100K, 100,000 Wellness Project. How does the 100,000 Wellness Project fit in? Did that come afterwards? It’s obviously vastly more people. Have you had 100,000 people? Has is it completed? What is this 100K Wellness Project? Where does it fit? How did it come about? What’s the mission? Where is it?
Nathan: We announced the 100K Wellness Project as basically an aspirational project. We actually announced that in 2013. The 100 Pioneer was meant to be essentially a pilot because we said, all right, we thought at an approximation that if we had 100,000 individuals that we could learn a huge amount about transition states to all the major human diseases at that scale. That was the aspiration that we set out to do. That vision actually came first and then we did the Pioneer 100 which was a size that was feasible for us to take on. So far, we have about 5,000 people who have come through this program.
Nathan: We have dense, dynamic data clouds on that, through our partnership with Arivale, the spin-out company. We’re building out things that are related to this project in different ways. We’ve also affiliated with Providence St. Joseph Health, which is a 50-hospital system in the West United States. Lee Hood has become their chief science officer now. Basically, there, we’re generating dense, dynamic data clouds in a number of different populations. 1,000 people in Providence have signed up to go through scientific wellness program.
Nathan: Then, we also are doing dense, dynamic data clouds for certain populations relevant to different diseases such as Alzheimer’s disease, and multiple sclerosis, and breast cancer, and a number of others. What we’re doing is populating out towards that 100,000 with a combination of people who are going through a wellness program as well as people who are in different disease categories. We are filling that out in various ways. We’re also partnering with a group out in China. Lee Hood is going to co-chair what’s being called the International Human Phenomics Organization. We were all just in China last month.
Nathan: China, it turns out, has really gotten invested in this whole vision. In fact, China is investing $3 billion into a project, very much a version of what we had announced in our version of the 100K Wellness Project. That will be part of this International Human Phenomics Organization. So there’s increasing interest in this and the 100K is the encompassing vision of where we’re going in terms of recruiting individuals into … Well, in terms of generating data clouds that we think are necessary for understanding those disease transitions.
Lee: I can’t help but be shocked and think that why is the state not doing this. It would seem very pertinent upon the state as a civic duty and a collective duty to be doing this, not a private enterprise.
Nathan: Yeah. We really thought that as well. We tried, of course, to get the government interested in funding this project at the beginning. We’re not successful at doing that here, interesting, right? Sort of interesting, the Chinese government is massively interested in this. Like I said, they just committed $3 billion, pretty stunning amount. Actually, I think perfectly in line because this can … You’re talking about something, that investment is roughly on the scale of what the U.S. put into the human genome project. This feels equally important, probably much more health impactful. Well, I don’t know, the genome is hugely impactful in the long run. But this would accelerate that to a huge degree.
Nathan: There is sort of a version of this in the U.S., of course. There’s the All of Us Program. Although the All of Us Program is very genomics focused, it’s very centered on trying to have a million people. I hope that project is successful. I’m rooting for it. But it feels like… I think they could have gotten a lot farther if they had done a smaller number of people with deep phenotyping as opposed to limited phenotyping over so many, many people.
Lee: Yeah. I saw the NIH project. It was an NIH project, the All of Us. It seemed to have the right philosophy …
Nathan: That’s NIH project, yeah.
Lee: … behind it, the philosophy we’ve spoken of. It just felt a little … for want of a better way of putting it, a touch late to the game, like running behind the ball type thing.
Nathan: Yeah. Well, there are certainly other efforts that were earlier. We had tried to pitch ours to them, I don’t know, a year, year-and-a-half or so before the All of Us Program. I forget when it was exactly. I think it’s a noble endeavor, you know I’m excited about. I just think from my standpoint though, I think they fixated too much, I don’t know, maybe it was for political reasons. I don’t know. I feel like they fixated too much on wanting to have a million people. Because I think as soon as you commit to a million, you divide the resources that you’ve got to a million people. Pretty soon, you’re doing genomics.
Nathan: But genomics on a million people is already very expensive, even at current prices that are getting, of course, better and better. Then, you have some limited clinical data. I actually feel like a lot of the field as a whole really is missing the boat right now to some degree in the sense that I feel like there’s so much interest in genomics plus clinical outcomes and phenotypes. I love that word. We use outcome from that all the time. But as you add to that, you’re essentially getting variants that have smaller and smaller effect sizes and you’re increasing your statistical power to see them.
Nathan: While I think that’s useful, I think for the same investment, taking those genomics and putting them in the context of this personal, dense, dynamic data clouds with deep phenotyping, I just think you can learn so much more. In fact, we had a very interesting interaction recently. We have these 5,000 data clouds and someone asked from the genomics world “Well, how many more do you need so you can start deriving insights?” We just looked at them dumbfounded because you’re like, “Uhm, well, we could derive … ” I’m like, “We can take that current data that we have and derive insights from it for 20 years without any problem.”
Nathan: There are so many questions we can ask and answer. The data clouds are enormously rich. You can analyze these data sets for long time. It’s a very paradigm than this notion of pushing out genomics which is at first approximation one kind of analysis, of course there is some variance to that. It’s one kind of analysis trying to figure out what are these increasingly small variants to get effect sizes, to get to clinical significance. There is some transition, of course, because as you have enough, you can start thinking about network effects and combinations and things like that.
Nathan: Although combinations need to be refined in that space to keep your combinatorics down because brute force combinatorics in genomics is impossible even if we had every person on the planet sequenced, those combinatorics get really big really fast. Anyway, I don’t want to get too much into that. Just the notion is from smaller numbers of these dense, dynamic data clouds, you can learn qualitatively things and a massive amount that you just never get from genomics plus clinic. The data clouds fill in all the intermediate information that we think is going to be actionable. We call this the manifestation of genetic risk in the body.
Nathan: You can take variants that we already have. You can get all the molecular correlates in the data clouds and then starts telling you what is different about people who are in high risk from all these different diseases. It gives you clues into a path towards prevention. That’s mining them like crazy right now. I think that going to be really interesting.
Lee: I appreciate that. On other people doing it front, leaving the state aside, it sounds very much also like Project Baseline from Google’s Verily, would you agree?
Nathan: Yes, to the extent that they don’t speak about it publicly terribly much. Yeah, it certainly similar to that. I remember it actually in the early days after we had launched our effort and then there was a press release from Project Baseline, I remember a lot of people came to us and was almost like, “Oh, are you guys going to quit now? Google is going to do everything.”
Lee: Yeah, go home.
Nathan: Which I’m very happy we didn’t do. Yeah, go home like, “Oh, Google has so much more money than you. There’s no point to do what you’re doing.” It was odd reaction from people [crosstalk 00:50:41].
Lee: Give up your day job Nathan.
Nathan: Yeah, exactly. That’s why we kept flagging along, thankfully. Project baseline in the extent that they’re trying to quantify these 10,000 people I think they said and establish baselines for it. I love all that in the sense that it’s very aligned with where we’re going and the kind of thing that we think should happen in the future of medicine. Our effort, as much effort as we put into this, if you compare it to the size of healthcare, are still pinprick small. I’m very happy to see our efforts move forward. I want to see a Project Baseline move forward. You mentioned China’s iCarbonX, which is very similar to what we’re talking about.
Lee: I mentioned it to you by email.
Nathan: Oh, you haven’t mentioned it here. Sorry about that.
Lee: I’ve been tracking iCarbonX for a long time. iCarbonX from what I saw, seemed more of a clone of Human Longevity Incorporated.
Nathan: Yup, there’s Human Longevity, Craig Venter’s effort. There’s what Mike Snyder is doing down at Stanford. I’m in general just a big fan of all these efforts, because I want to see healthcare move in a way that embraces wellness more deeply. I want to see us as humanity really generate as many of these personal, dense, dynamic data clouds as we need to understand how to predict and prevent disease. I want to cross that bridge. I would be very sad if we were the only effort. It would mean that no one else is buying into this vision at all. I think there’s lots of different places that are buying into their own variants of this vision. We want to see that become the future of healthcare. We need more and more people to push that. I’m excited about all those kinds of efforts.
Lee: We might find that China leapfrogs the U.S. on a healthcare front.
Nathan: I think there are some reasons to believe that. The U.S. remains very strong and a very strong set of research innovations. We’ve got a lot of that. In terms of this embracing of certainly some of these concepts that we’ve talked about, scientific wellness, deep phenotyping, and so forth, China seems to embrace it more so than the U.S. We do have a lot of these private enterprises as we’ve talked about here in the U.S. as well as in China. Publicly, China has embraced it more I would say. I think this $3 billion human phenome project is going to be a huge leap in that direction. The All of Us Program I would like to see move more towards deep phenotyping.
Nathan: They say that they want to do that. It’s part of their cohort. I’d love to see that accelerated. I think China is moving aggressively. When we were in Shanghai this last month, it’s very impressive. We went through one of the most impressive hospitals I’ve ever seen, in Jiahui. They’ve got this phenome project which was overwhelmingly impressive, at least in the scale of the ambitions of it to start with. I think there’s a lot that they’re pushing forward. The number of patients they have to deal with is incredible. But there’s also a lot of asymmetry still in China in terms of the big cities, I think, are really rolling forward really fast. They’ve got a lot of the rest of the population that they need to worry about as well.
Lee: Would the 2025 vision, China’s 2025 vision, they’re definitely aiming to race ahead. For example, on the iCarbonX front, Tencent, they invested $155 million on Series A into iCarbonX.
Nathan: ICarbonX has raised a huge amount of money, yeah.
Lee: China also doesn’t have the same “privacy” issues around genomic data et cetera.
Nathan: That’s right. There are certain reasons why Chinese companies will be actually I think less burdened by regulations then in the United States. People can argue positive, negative of that. I think that’s the real difference.
Lee: If you just look at independently as a race into the future, one is encumbered with privacy regulation. The other thing is America is getting increasingly uncompetitive because employers are paying so much for healthcare. Their employees are getting sicker and sicker and healthcare costs are going more and more up. Employees are not seeing that because it’s coming prior to their paycheck. They’re not so aware that, hey, this is what’s making China cheaper, that the workforce is not as sick.
Nathan: Yeah, it’s a huge issue. It gets us back to some of the societal issues which is we need to embrace a culture of wellness much more so than we have. Typical lifestyle and culture really drives a lot of health. There has already started to be revolutions in this way, communities that are becoming healthier and …
Lee: Can you name one?
Nathan: Well, I would say pretty broadly the West Coast. It’s a big ship to turn. I think food companies are actually coming around on this somewhat too. I think they’re worried about as people learn about the negative health impacts of packing sugar into so many things, I think there are some worry that that would ultimately be viewed like cigarettes back in the day.
Lee: I think the processed food industry will be seen as a Big Tobacco. Definitely, large food manufacturers are certainly looking at reformulating their formulas and strategies and embracing or trying to embrace this zeitgeist …
Nathan: Yeah, and a lot of them …
Lee: … because you know the …
Nathan: Yeah, a lot of them will talk about this. They understand that a lot of their consumers are turning much more towards health. They want food that reflects that manner.
Lee: Anyway, two important questions I’ve got for you. Let me fire two of them at you. My second guest, Joseph Antoun, he was pushing the biggest cause of disease is aging. Aging is the disease if we can call it that. If you can solve aging or let us age more gracefully, then you don’t need to worry about downstream diseases. When you talk, you always from what I’ve heard so far speak of just diseases and catching specific diseases and knowing the disease states ahead of time before people are manifesting symptoms. I’m wondering, why are you not mentioning aging?
Nathan: Yeah, that’s certainly an oversight on my part. We’re very interested in aging, we actually have a paper on aging that we’re going to be submitting within two weeks. We’ve mapped out across all the data clouds, all the elements that we see for healthy aging. We have developed a biological age calculation from the multiomic data which we’ll release here shortly. We’ve delved in to see across this broad well of data what is different for people as they age as related to a number of different health metrics. We are actually very interested in aging. I did speak a lot about disease, I guess I got into that track.
Nathan: In essence, I actually don’t want to end there. We end up talking a lot about disease because in the science world, we have a vast amount of information and data about disease for the reasons I’ve mentioned at the beginning. There hasn’t been a big focus on studying wellness quantitatively and so forth. What I really want to get to is more deeply understanding health and healthy aging is a huge part of that. One of the things, for example, and the human genome, I feel like it’s been very mis-sold to the public in some ways because of this focus in the research world that you were just pushing or just alluding to. Because I think that the general person on the street, when they hear the genome, I feel like there’s this mental issue that it’s like a crystal ball that’s going to tell you how you’re going to die. Everyone’s like, “Oh, don’t get your genomes. They’re going to scare you.”
Lee: Yeah. You might as well not change your lifestyle and habits. It’s pre-determined at birth where the stars were type of thing.
Nathan: Yeah, and don’t find out anything about your genome because all that is going to do is scare you and tell you all the different ways you’re going to die.
Lee: It’s like a tarot reading.
Nathan: Yeah. I think that’s just a very wrong perception, because your genome isn’t about your death. Your genome is about life, life processes. A good example is there’s a tribe of Native Americans here, just outside of the Seattle region. They were subject to have a paper. Anyway, it is brought up all the time. This population has diabetes genes, high risk for diabetes. Well, in fact, those genes are not diabetes genes. Those genes are genes that were well adapted to the lifestyle that they lived out here throughout the course of their history. The notion there is that those are genes that are adapted well to a certain environment. It’s about the life process.
Nathan: They only become “diabetes genes” when you cross them with a Western diet. Those genes are particularly maladapted to a Western diet scenario. We talked a lot about trying to understand the manifestation of genetic risk in the body and studying disease, we do that because that’s the wealth of data that’s available today. But in the long run, I actually don’t think that the study of what we’re talking about should be so driven to disease. It actually is a very key concept that we talked about for scientific wellness, which is to try to quantify wellness that incorporates the notion of aging, should make that more explicit.
Nathan: From that standpoint, you’re looking at these disease transitions. But at the end of the day, I actually do believe in … If you think about this to a farther future, that we might not even deal so much with the concept of disease the way that we do now. The short one we absolutely have to, because that’s where we’re at. But in the long run, I think if you really understand that well state and you’re just trying to correct deviations from it, that that whole science should be much more focused on how well are your body’s systems really operating and trying to hone them and correct them.
Nathan: If you’re doing that in the long run, whereas we think into the far future, maybe that gets us into a place where we’re actually not all that focused on disease at all. That’s not a immediate future, but that’s where I think this ultimately could go. Thank you for that question. I appreciate that, because I think that talking about avoiding disease more than I want to in terms of really where I think this should ultimately go.
Lee: It reminds me that on Institute of Functional Medicine slide pack that you delivered, you put that you’re aiming to help with the democratization of healthcare. It was a bullet point. Can you explain what you were meaning by democratization of healthcare?
Nathan: Sure. One of the things that we want to be very mindful of is we don’t want this personalized or precision medicine approach to be just for the rich. There are certain elements that are like in early adapters and so forth, people that will spend disposable income on these things. That’s probably inevitable. But ultimately, what you want is to be able derive insights that benefit everyone. There’s a number of different ways that that can play out. One is trying to push and this is already happening, that the various assays and so forth get cheaper and cheaper. Second, we think that a focus ultimately on a wellness centric healthcare could be done in a way that would dramatically reduce healthcare cost from all the spending on late stage disease.
Lee: You are working alongside Leroy Hood. Now, Leroy or Lee as you shorten it to …
Nathan: Lee greatly prefers Lee.
Lee: He invented the automatic … Does he? I don’t know. I’ve never spoken with him. I’ll note for the future. He invented the automatic DNA sequencer. The Human Genome Project wouldn’t have been possible without that. It was him I believe who came out with the term scientific wellness, am I correct?
Nathan: Yeah, certainly came out of him.
Lee: Do I attribute that to Lee Hood alone?
Nathan: Yeah. Lee or Lee and me, I mean basically those are our efforts.
Lee: Lee and me, okay, I’m unsure. We’ll give dual credit then.
Nathan: Lee is the …
Lee: Lee is …
Nathan: Lee is the face of this thing, yeah.
Lee: We’ll put him as lead author, how’s that?
Lee: We’ll put you as co-author. Well, he said, “The scientific wellness industry will be worth more by market capitalization than today’s disease care industry.” In other words, orthodox healthcare is only a sick care industry. It’s focused on the sick, which is all good. But that’s where the focus is, is on disease. Once you get sick, that’s where it puts its focus on, and say, 97% of its money. As I was saying, he said that scientific wellness will be worth more by market cap than today’s orthodox healthcare industry. Do you share that point of view?
Nathan: Yes, I do actually share that point of view. I think it might take a little longer than Lee thinks. He’s probably earning quite a bit discussion. Directionally, we’re both big believers that scientific wellness will be the dominant paradigm for 21st century medicine. I think there’s a question of how long that will take. The current healthcare industry has huge inertia to it obviously. For all of our talk about trying to get to something that’s not driven by just disease, this heavy disease focus, the fact of the matter is in our current healthcare system, that’s the massive focus.
Nathan: For chronic disease in the 21st century, yes, we believe that it needs to become more wellness centric for the reasons we talked about in the beginning. This shift from infectious disease to chronic disease, the desire to move upstream, and the data clouds that we and others are generating are going to be the substrates for letting that happen. Ultimately, we very much believe that 21st century medicine will be about the evolution from this late stage disease care to more and more towards earlier wellness care. Then ultimately, more healthcare resources will go into that and become bigger over time. Directionally, yeah, we’re very aligned with that so. That’s where we think the future is headed.
Lee: I notice we’re running out of time here. Let me try and cut it down to, I hope, two questions. With today’s healthcare, I heard that the hospital charges $20,000 per hour for chopping the feet off diabetics. The hospital only gets $200 per hour for giving lifestyle advice. So it’s very hard to see how the incentives can move within that system so as to prevent. What do you think?
Nathan: Yeah. This is a huge issue. It get really to the heart of the matter because we have to make just being realistic in terms of what is going to happen in the world. We have to get economic incentives aligned. As you get into this space, I’m sure you found alarming to the degree to which economic and health incentives are not always aligned. There is some push on this. There’s, of course, the movement towards value-based payments. That is one step that I think can be beneficial, has its own complexities. That is at least a start. The flip side is that they’re going to be disruptive forces, I believe, in medicine.
Nathan: You’re going to start to have systems that are embracing this new view of 21st century medicine. Ultimately, we have to let the marketplace become competitive so that those places can … So alternate views can move forward. We start having competition of innovation in the marketplace. In healthcare, for obvious reasons because there’s such important safety concerns it’s a very highly regulated space. Well, a lot of that is very necessary, very good, there’s going to be a period of transformations that will become very apparent that are highly needed. We have to make sure that regulations that are in place for safety are held.
scientific wellness will be the dominant paradigm for 21st century medicineNathan Price
Nathan: But those that are just there to protect the status quo or to disincentivize innovation from heavy lobbying and things like that, maybe some of those need to be loosened. We’re already starting to see some innovation actually that I think is very good. One innovation, this isn’t directly related to this but I’ll just point this out, is with Scott Gottlieb, the chairman of the FDA, has made I think a very important move in the genomics space. For a long time, genomics was being evaluated the same way that we’ve done things in the past. What it was is that every single time you found a variant or a combination or some polygenic score or whatever it is and you wanted to, say, be able to tell someone about it, that you had to go through its own independent regulatory process and it take a couple of years. 23andMe had to go through this. They got one down. My favorite tweet from that was, they’re like, “1 down, 2,999,999 to go.” It’s like, okay, we’re not going to be able to work through this ever [crosstalk 01:10:57].
Lee: That’s pretty funny.
Nathan: Yeah, which is a pretty funny one. What they’ve done at the FDA now, which I just love, is they said, “Okay, we have an important issue which is the safety of people and the validity of genetic information that goes to them.” 100%, that’s important. Then, they said, “Okay, but maybe we can solve that without this kind of ludicrously slow process.” Which is that now, they’re highlighting a set of companies. The companies come through and then they get vetted on their process, what evidence they use, how they’re presenting it, and so forth. They can do that as a program, as a package. See, I love that.
Nathan: Because then, what that does is that says, okay, we’re not going to put regulations in place that are irrational, that are blocking the entire future of that field and all the good it can do. Instead, we’re going to safeguard against charlatans, we’re going to safeguard against people that don’t know what they’re doing by having regulations in place that review the processes of how it’s going, how they evaluate evidence. Then those are subject to periodic review. I love that. That’s the kind of innovation that I think we need on a regulatory side, is where we look at the fundamental safety issue that has to be preserved and we have to maintain which is vital.
Nathan: But then, ask the question, can we set things up in a way that achieves that but also allows there to be innovation and progress? I thought that was a beautiful example of that. I think that’s what’s going to have to happen in the wellness centric healthcare space as well which is to try to think about creative ways to get those economic and health incentives aligned, because that’s what’s really going to drive benefits for most people.
Lee: Nathan, trying to wrap this up here, you had said at my event, trying to remember what the quote was in fact. It was, you said, here is … I found it. “Humanity is about to cross from ignorance into knowledge on many, many fronts because we’ve never actually measured our bodies as an integrated system in much detail before.” Picking up in that, I find it absolutely crazy that we’ve not being measuring our bodies and taking lots of data, data being blood samples, data being genomics, data being stool tests, et cetera, and measuring people over time who are not sick. My parents both, deep breath, unfortunately died of cancer.
Lee: I lament greatly that they were not measured from a healthy state and yes, into cancer and towards death. Because that would have at least allowed them to contribute something back to humanity in a way they died in vain in that regard. I greatly lament that they were not measured from health to disease, to progression through disease, because data is a key to deciphering that. Instead, they had basic measurements once sick and hey, here’s your dose of chemo. Do you agree with that?
Nathan: I very much agree with that. Because what we really want to know, of course, is can we intervene, can we stop these things. Especially now, what we can couple … Actually, we have a proposal in on this right now, see if it gets funded, working with Jim Heath, here at the Institute for Systems Biology, but basically trying to couple these data clouds and reach for the much more immune specific information and coupling that to immune therapies. Because what you should be able to do is a pretty comprehensive monitoring. In this case, we’re focusing in on recurrence to be … We have a focused population.
Nathan: You should be able to take these things like the data clouds once the trajectories design an amino therapy. In this way, you can eliminate a lot of cancers if something like this works. I think that we want to do that. Another thing we’re doing and this is true with Tom Brown, who’s the head at the Swedish Cancer Institute here in Seattle, is we’ve also launched a Breast Cancer Survivorship Program. We’re doing exactly this. We’re taking people who have gotten a breast cancer diagnosis and we are monitoring them with this dense, dynamic data clouds from the point of diagnosis through their chemotherapy.
Nathan: Then, what we’re trying to do is even when people survive the cancer, very thankful they survive, because chemotherapy hit so much of your body, just decimates different elements of your body, it takes a long time to get back to health. We’re actually monitoring this entire process to try to figure out ways that we can enhance the return to wellness, the return to health for, in this case, women who are coming through breast cancer. We’ve had breast cancer in my family and it’s a big personal issue. It’s a big issue for many of us. It is something where we think mapping that, so we’re going to be looking at early stage.
Nathan: We have a number of examples that people would come to the program where we can see potential early warning signs for cancers or trying to work those out. We want to understand what’s happening during the course of therapy and we want to see what’s happening for the return to wellness, because we’re having more and more cancer survivors thankfully. We’re very interested in that whole process. At the very least as you say is you go through this, we can really learn from it. Hopefully, we can make I think these kind of approaches from humans, with dense, dynamic data clouds, we’re going to be able to work out just a ton related to both health and disease. I think it’s going to be really, really meaningful in the long run.
Lee: I see we’re over our allotted time.
Lee: Just let me make it one last simple question, Nathan. I’ll save the simple, simple one for last. I think that we’re going to end up with two industries. We’re going to have the orthodox healthcare of today. It is likely to stay focused on acute care and the traditional stuff, the vaccines, et cetera, injuries. But we’ll have a new separate industry adjacent in addition which will be far more build upon engineering data science principles which will focus on prediction, prevention, and optimization. I don’t see the current orthodox healthcare transitioning over there although there will be overlap yet to be determined.
Lee: Do you foresee something similar or do you think the orthodox healthcare will somehow transition? Because for me, orthodox healthcare is built upon a principle that there will be people involved. It’s a person-centric, healthcare professionals, doctors. It’s not very machine and device-centric. It keeps people in the middle. That is just not where the future is going. Its very device and software-centric and software and devices scale. For example, when you talk about people and the biology and looking a all their systems, I’m 100% sure we’re going to be running people’s biology in the cloud, as in running an avatar, biological avatars of them in the cloud.
Lee: They’ll resync with that once a year. It’s predicting what’s going to take place with that person over the next 6-month or the next 12-month. You do the odd test and it resyncs again. The question is, do you believe they’ll be two industries yourself? Where do you stand in that position?
Nathan: I think that’s a great question. I think there’s a lot still up in the air. I do think that a lot of the innovation will have to come from outside the current healthcare industry. I think most huge innovations virtually all was happened that way. It will be very interesting to see if healthcare systems can adapt and change sufficiently to be the beneficiaries of that revolution. I do have some hopes on that. If I look at the Providence St. Joseph Health System, they brought in Lee Hood and ISB. Scientific wellness is a part of their five-year strategic plan and wanting to disrupt themselves. I see, you know what, Rod Hochman who’s been I think really a visionary leader there.
Nathan: I think there are some signs that at least certain healthcare systems are open to this. I think there is really a question of just given the scale and scope of all that they’re doing and just how much that can be absorbed. I do absolutely think that there will be a remaking of a very different kind of approach on healthcare and that that will in essence arise mostly from outside the healthcare system. It will be a question of how much partnership, how much deep integration there is with the current healthcare system. I think that’s really in part up to the leadership of current healthcare systems. It’s extremely hard challenge because almost always being innovations come from small new startup endeavors that grow as opposed to radical shifts of big organizations. I think that’s probably going to be true [inaudible 01:21:11].
Lee: I’m apologetic. We’re over the time with you. I highly appreciate you sparing your time graciously with us today.
Nathan: Well, it’s great to be with you, Lee. I appreciate and it’s great to talk to you.
Lee: I hope to catch up and hopefully, we’ll get an update of this 100K Wellness Project.
Nathan: Sounds good. We’ll talk soon.
Lee: Thank you very much, Nathan.