Where does your story begin, and when did you decide that science was a passion that you wanted to pursue?
Dr. Hood's Childhood and Beginning
I was born in Missoula, Montana. I went to the early grades there and then went to high school and middle school in a really small town called Shelby, Montana. It was a school that had about 146 kids and three of the best teachers I ever had.
I did well in science and kind of intuitively knew that I wanted to do something in science. I’d initially thought about biology and that got started when my youngest brother, who was six years younger than I was, was born with down syndrome. This was back before we knew about chromosomes or anything like that, and I remember being really puzzled why he was the way he was. The doctors couldn’t answer these questions, and it was really intriguing.
My grandfather built and managed a geology camp in southwestern Montana, in the Bitterroot Mountains, and this was a summer camp for geologists from Harvard and Yale and Princeton and Columbia. I worked there for three years, and it was terrific, since it was the first time that I had ever met scientists, coming from a small town in Montana. Then they began to give me a sense of what science was, and what was really exciting was that my junior year I actually took a course with the kids and the course was doing geologic mapping of an interesting feature. So I mapped an oil incline in Wyoming, and I used that, actually, as a project for what was then called the Westinghouse Science Talent Search .
I ended up being part of the final 40 that got to go back to Washington, and that was an enormously interesting experience, because one, I had never been out of state until then, so it was getting on the train and going all the way to Washington DC, it was really an incredible experience. And then number two, getting to Washington and meeting all of these kids who were super bright, and for the most part had gone to schools where they really had much more preparation than I had, a lot of prep school kids that went to this kind of thing. You know, it made me realize, in Shelby I was the best student, but here, I was one of 40 that certainly wasn’t anywhere near the best student. So that was a sobering kind of experience.
And what happened my junior year, when I started thinking about schools, I had really thought in terms of keeping kind of towards liberal arts schools and so forth, so I thought about Carleton, which was my first choice and there were a lot of reasons why I liked it. I looked at Harvard, that was a possibility, and my high school chemistry teacher, who was one of these really great three teachers, really had two important roles in my life. One is that he started at that time, trying to persuade me about Caltech, and I had never heard of Caltech, so I read about it, and I came back to him and said, “Look, the advanced math test has all sorts of mathematics that we’ve never had at Shelby.” And his attitude was, “Ah, you’ll do fine, just go take the test.” Well, a big part of the test was calculus and we’d never had calculus. Anyway, it actually took a lot to convince me since I wasn’t actually sure that I wanted to go necessarily to a technical school.
But the other thing that he did that was interesting was that my senior year, he asked since he didn’t know much biology, if I would help him teach sophomore biologists, and I said that I would do it if I could teach out of Scientific American. So I would select an article, and I gave maybe 10 lectures in that course. One of the articles that I selected...Let me say, that after being at a geology camp for three years and getting to the Westinghouse finals, I really was thinking very seriously about geology at that time. But in this class, I remember, this was 1956, reading an article out of Scientific American about the structure of DNA, and that really convinced me that biology was where I wanted to go. And you know, I think that I understood maybe 1 % of what was in that article. I taught it, so I learned more than the students did, anyway, but it really convinced me that biology was really incredibly...If all the information for constructing a human could be digitally encoded, that was really incredible, we had no idea at that time. I mean the structure of DNA had just been done in 1953, so we knew what the structure was and we knew about replication, mutation, all of those things. But we didn’t know about genes or messenger DNA or any of those other things, so that really convinced me that I wanted to go into biology.
Dr. Hood's College Experience
Anyway, I took the advanced math test, and it was really hard. I think I figured out a little bit about calculus in the course of doing the test, but I am convinced that I had one of the lowest scores in mathematics of any of the undergraduates that were admitted to Caltech. And I went there, and again, my roommate for the first month was this incredible guy who had come from a prep school, and he was in third-year math at Caltech, he’d had all sorts of physics, and he said, “You’re really going to have a hard time here.” And the interesting thing was that he flunked out the first month, and he flunked out because he played bridge 20 hours a day and never went to class. Anyway, I was busy as a bee and working away, and I did fine. But when I finished Caltech—I think in part of my brother and in part my fascination with DNA, Caltech was great in fundamental biology but it had no higher organism biology, it had no human biology whatsoever—I decided I would go to medical school and pick up all of human biology and then go into the PhD afterwards.
Graduate School
So I only applied to two medical schools—Harvard and Hopkins—and got in[to] both, but I decided to go to Hopkins because they had a program called 3-2 where if you wanted to go to medical and not pursue a traditional course, you could get through in about two and a half years by going straight through all the summers. And you did all the clerkships and everything, so I did full medical student panoply and it was great, and I loved it, and I actually loved being the doctor in the clerkships and everything. But you know, I was really much more enamored for research, and what Hopkins did for me was it got me excited about all the things I’m doing now. So I got very interested in immunology and interested in cancer, I got interested in neurodegeneration and those are all things that I ended up pursuing later in my career.
So when I finished, I decided what I really wanted to do was molecular immunology, because in medical school I’d read a lot about kind of frontiers in immunology and a big question that which really fascinated me [wa]s, how could a human make so many different kinds of antibodies to protect yourself against the whole world of, universe of pathogens and all of that? And I read about this work done by a person at NIH, and formerly Mike Potter, and by a person who was at NIH and actually went to Caltech on studying...Well, Mike Potter developed a system whereby you could use mineral oil to actually induce myeloma tumors in mice, and those tumors were of plasma cells, so the tumors made large quantities of one type of antibody molecule, and I decided what would really be cool would be to study that system and then determine the protein sequence of these proteins to see if the variability could give you insights into mechanisms and diversity and how these things evolved.
Caltech
And so I looked at a bunch of different schools and went to Caltech, because [they] agreed to let me work on that project, and he said what’s really great about that project is that almost noone is interested in this so it was what he called a Saturday afternoon project, so he said, “You’ll be able to do it easily.” So I went and got started, but quickly we saw and generated these tumors and proteins and I learned how to do protein sequencing—which in those days was really hard and exhausting kind of procedure—and got a lot of data, and then immediately that data became fascinating, because it did give us insights and set constraints on how you thought about how diversification could occur and all of that kind of thing. So I was really fortunate because as a second-year student, I got to go to Berkeley and UCSD and Harvard and give lectures on what I had done as a grad student. So it really put me in this fastlane for doing exciting things, and this was the really the most exciting area—immunology— during that 10 year period or so.
So at the end of my graduate work and things like that, I decided to go to NIH because it was Vietnam War and everything like that. So I got to be in the medical clerkship group there, and I had an independent lab and got to do research and so I worked in this area of molecular immunology. And then from there, I went back to Caltech, because...my PhD advisor, and I had really a challenging relationship [with him] because he wasn’t very interested in graduate students and didn’t really spend much time, but I would say that he’s the guy who had the biggest impact on my career because his mantra was 1) Always practice biology at the leading edge because that’s where it’s exciting and fun, absolutely agree with that, did that. And 2) If you really want to change your field, invent a new technology that lets you explore completely new dimensions of dataspace and so forth.
So anyway, I decided that when I went to my next job, I would have my lab do technology development and since I knew a lot about protein chemistry and knew exactly the kinds of things that we needed to do to really improve protein sequencing, and number two, I would really like to carry on in molecular immunology which was really what I did at NIH. So I went to six different schools and visited, and it seemed to me the only one where I could do both of those things effectively was Caltech. So I ended up going back there and getting on the faculty and starting as an assistant professor in 1970, and Caltech was really terrific for me in many ways. Immediately, I began recruiting grad students and postdocs to do the technology side of things and to do the immunology side of things. So by the end of 10 years, we really advanced to the point where on the technology side, we had really come a long way on the protein sequencer, and in fact, in the next year or so, we kind of had the most advanced sequencer that had every been developed; it was 200 times more sensitive than the prior instruments, and it was faster and had a higher repetitive yield so you could see what it was really. And then we had started work on automating DNA synthesis, we’d started to automating peptide synthesis, and we were just beginning to think about how to automate DNA sequencing. So in ‘78 or ‘79…
You guys can ask questions, you know?...
So I went to the president of Caltech and said, “Look, we’re developing these four instruments and a couple are pretty far along, I’d like to take them out and commercialize them.” Because my philosophy then was [that] society pays for scientists to really have a lot of fun, so your obligation is that if you get useful things, you should bring them back to society, and a great way to do it is to start a company to do that sort of thing. And the president of Caltech said, “The role of an academic institution is scholarship and education. It isn’t commercialization.” And I looked at differently. I said, “I think all scientists have an obligation to transfer knowledge to society where it’s useful, and I think that the best way to do that is transferring inventions that are relatively complete to companies, and then when they make them, they make them available to all of science.” And he said, “Well, if you want to do that, then you’re on your own.”
So I went out in the next year and a half to 19 companies, including Beckman, three times to Beckman, and all times they said no, they weren’t really interested. So actually I was really surprised because these instruments were really going to change biology and how these people couldn’t see it, and I’ll tell you later about the big mistake I made going out, but what happened was that Bill Bowes who was a venture capitalist in San Francisco called me and said, “I hear that you’re unsuccessfully shopping this idea around. I’ll give you 2 or 3 million dollars, and let’s start a company together.” And I thought, gee, this is terrific, so I went to [what the heck is this name], and told him about this opportunity, and he said that “Under no circumstances will Caltech accept venture capital money because it’s dirty money.” So we had a really big argument about whether it was dirty or not. What happened that’s interesting was that after six months, I finally bored him down to the point where he said, “Okay. You’ve convinced me that this is the only way to commercialize these instruments.” And we were just getting ready to sign a document to start the company, which was Applied Biosystems, which was probably one of the most successful molecular instrumentation companies ever. But what happened is, I gave a lecture at Caltech trustees just as we were about to sign that document, and it turns out that Arnold Beckman was then chair of the trustees and a major donor to Caltech, and my lecture was on these four instruments and how they were going to change the course of biology. So he came up to me and said, “This is unbelieveable. This is really exciting, and it’s just what Beckman Instruments needs,” and I said, “Well, I went to your SPINCO division three different times and the last time they said, ‘We understand what you’re trying to sell and we aren’t interested. Don’t come back.’” And he said, “That’s impossible!” So he flew up the next morning. And what’s interesting was that those guys actually ended up lying. They said, “Lee misled us on what these products were, because he wanted to start a private company and make a lot of money.” So Arnold Beckman came back furious with me, to the president. So I wrote up a whole history of exactly what had happened and gave it to the president and said, “Look, let Arnold read this.” Well, the president actually was a wimp and never did give it to Arnold, but that ended up getting settled after a few years of fussing back and forth. And in the meantime, we signed the document and we started Applied Biosystems.
But the two really interesting lessons I learned is 1) If you have really new innovating ideas—and all of those four instruments was really innovative and new—you don’t want to give them to an old company. Because what they’ll almost certainly do is that 1) Only put a fraction of their effort into doing anything, because they’ve got other things to do. And even more importantly, they won’t be able to hire the talent you need to really do the final element, the instruments. So, it was really lucky that those 19 companies that turned me down. But the other thing I learned is, in the case of all those companies, I went to middle-level managers. And middle-level managers are really good at profit and loss and figuring out how you can maximize opportunities in the next quarter; they aren’t really interested in the future. You need to go to the top, like Arnold. I mean, Arnold, in a second, saw the long-term implications. If I had gone to him first, he’d have agreed and forced Applied Biosystems to agree, and it would have been a disaster—I mean, forced Caltech to agree—it would have been a disaster because Applied Biosystems hired some of the best engineers and technologists that were available at the time. And they were, because we had designed the gas-liquid phase protein sequencer so well, they were in the black within six months, because it didn’t take much to put out a robust instrument that worked really well. And they went on to produce the other three instruments. So the company’s whole mission was producing the four instruments, and they did an absolutely magnificent job.
So coming back to Caltech, you know the downside of developing all of these instruments is my lab really started to grow, and in that regard, the chairman actually came to my office, and in 1973, after I’d only been there three years, and said he wanted to argue on the strongest possible terms that I give up all of this engineering and technology development, and I said “Nope, won’t do it, it’s going well.” And 25 years later, I asked him why he would say that. And he said, “I said it because the senior biologist at Caltech felt it was really inappropriate to have engineering in biology, and they wanted me to move you to engineering, at least I didn’t do that. And they felt uncomfortable that you were doing these two different big things, molecular immunology and technology, you had a very big lab.” So those were agitations that I realize were...I mean, Caltech is an ideal place—incredible students, incredible faculty—but I was beginning to feel that maybe this wasn’t the best place for me to stay. So, I did stay another...Well, I stayed up until ‘92, but increasingly I got pressured out of technology development, and in the mid-80s I started pressing the Human Genome Project, which we’ll talk about in just a few moments. And almost all of the senior scientists at Caltech were really against the Human Genome Project, and in fact Caltech missed out on that movement totally and it really hurt biology at Caltech.
And so...Well, what happened because we were developing the automatic sequencer was in 1985, I got asked to attend the first meeting ever held on the Human Genome Project, and they invited 12 of us to come and pass judgement on whether this was a good or bad idea. And this was sponsored by the old chair, my chair of biology, [Robert Stevens], who had then become a chancellor at Santa Cruz, so he went there, and we had this debate. The 12 of us came to two really interesting conclusions. 1) It was technically possible, though it was really difficult, in fact, it was about a year later when we had the first prototype of the automated DNA sequencer. And 2) We realized that were split 6 to 6 on whether we thought that it was a good idea, and the 6 against it were really, really against it, because big science is bad; it would take money from small science, and we didn’t want to change the culture. When I went out to the scientific community in ‘85, ‘86, and ‘87, I started pushing these ideas. I would say initially that about 80% of the biologists were utterly opposed to the Genome Project. And the institution that was most opposed was the NIH. And if it hadn’t been for the Department of Energy and their commitment to the Genome Project, it would have been delayed at least five years, if not longer. But anyway, a national academy committee was convened in ‘88 and it came to the conclusion that the Genome Project should be done, and NIH immediately switched and decided since it was going to happen, they better get on the bandwagon, and they played a major role in doing it. And so it got started in ‘90 and finished, more or less, in 2003. From my point of view, the reason why it was so important was two things:
You know, I’d been thinking about complexity in biology really since the beginning of my career. And what I’d realized when I first came to Caltech was 1) We didn’t have a way to talk about complexity and that later became systems biology, and 2) We didn’t have a lot of the technologies we needed to make the measurements to attack complexity. That was the four instruments, and others that we’ll talk about in a moment. So when the genome was done, it first of all defined all the genes or most of the genes in the human genome, so for the first time you could think about a global holistic systems approach to biological experiments in humans, and come to understand their systems much more effectively than ever before. And the second thing it did which was really important, which is really the heart of what we’re doing now, is that it gave us access to genetic variability in humans, identifying what it was, so that we could correlate it with phenotype, either normal phenotype or disease phenotype, and that’s turned out to be a very, very important tool. So, the automated sequencer got me really involved in the genome project and that was a monumental change in how I thought about a lot of different things, and one of the things that was really interesting about developing the automated sequencer, was that we started in about ‘78 or so with a really bright young biologist who knew a little bit of engineering. And he worked really hard on it for three years and got nowhere. And I realized that one person couldn’t do this. So in ‘82 I got together a really good engineer, a really good chemist, a terrific computer scientist, and I was the molecular biologist...And within a week of the time that we started talking, we came up with a complete conceptualization what you had to do, and then it took about three years to create the first proof of principle and everything. But the key ideas were using little capillaries, so you had very narrow gels, using four-color chemistry so you could color-code the four bases, using lasers to identify colors, and all this straightforward kind of things that we know about now but it required an enormous amount; for example, we had to invent incredible chemistry for coupling dyes to primers, which did the sequencing and all that, and chemistry was...And that’s where the biologist failed, he just didn't know the chemistry that was so critical. And the other thing, putting together these four people to invent this sequencer made me realize, if you are going to practice leading edge biology, you don’t—and I experienced this myself—get very far before you realize you need new technologies to explore new areas of dataspace. I realized that biology should drive the technology, and that you should have an environment where the technology could create the analytic tools to analyze all the data. And if you can have biology drive technology drive analytics, then you can actually change how you view biology, so it’s a complete circle.
So I went to a different president...in about ‘88 or so, and said, “Look, I have a great new idea, I’d like to start a new biology department at Caltech that is (and I called it biotechnology) cross-disciplinary.” So the chemists and the engineers really loved the idea. The physicists were indifferent as much as I could tell. But the biologists were really threatened by it, and they vetoed it, so they really didn’t want it to happen. So Bill Gates made it possible in ‘92 for me to move to the University of Washington and set up the first cross-disciplinary department that was absolutely, spectacularly successful. And the dean who hired me, was just a terrific dean, [he] promised that if I built for the first four years, this cross disciplinary department, in the fifth year he’d give me another floor and I could begin to build systems biology on top of that. So it was absolutely an ideal environment. So we went there and this department was utterly spectacular, so two of its people invented the first key techniques in the newly emerging field of proteomics. A third person developed the two key algorithms for all of the Human Genome Project, one which lets you assemble DNA fragments, and another which lets you assess the quality of the sequence data generated. A [fourth] developed a brand new type of multidimensional high-speed cell sorter that was fantastic, and then there we developed our fifth instrument, which was using inkjet technology to create a DNA synthesizer that allowed you to synthesize DNA really rapidly, and it actually allowed you to create DNA arrays very rapidly too. And with that machine, I created a company called Rosetta, again commercializing it, and Rosetta became very computational, so it ended up selling the invention to Agilent, which is the method that Agilent uses today to synthesize enormous amounts of DNA and DNA arrays and things like that.
But what happened in the midst of all of this success, serendipity reared its ugly head because just at the beginning of the fifth year, the dean who hired me died in an avalanche in the Himalayas. So a new dean came in who only had done outcomes research, he knew nothing about science, and I knew from day one that I was really going to have trouble with him. And he was a boy scout type that really expected people to kaotao to him and I have never kaotaoed to anybody. So we clashed from day 1, and I stayed there a couple of years and tried, but then, in 2000, I resigned. And actually I brought a lot of key people from the cross-disciplinary department to create the first Institute for Systems Biology, which you are in now, and it was independent, it was nonprofit. It didn’t have a dean telling me what to do and stuff like that. But it was really hard, because I had just come out about the time that the depression of 2002 and 2003 in tech occurred, so all of my rich friends who I was sure would donate to this new school—really, after you’ve lost 20 to 30 percent of your portfolio, you’re not really interested in donating money to anybody—so, it was very hard to get started, but we did, and we’ve been really successful.
But what was really interesting is that from day 1, especially in my lab, we’ve been interested in taking these systems approaches—global, holistic, multidimensional—to think about human disease. And over the next two or three years we defined two really important concepts for disease, and that is systems medicine, and that is nothing more than applying systems approaches to disease, and then the idea of thinking about healthcare that should be predictive and preventive and personalized and participatory, 4P healthcare was really key. And the most critical “P” that most people sell short is the participatory. You’re not going to get health care to work until you get patients really engaged, we can talk more about that in a little while.
So basically what happened is, a big part of how the institute is taking on really big problems and then creating strategic partnerships and the resources to solve them. And one really interesting strategic partnership that we had in 2007 through 2013 or so was one with the state of Luxembourg. What had happened was that I had a good friend at Pricewaterhouse Coopers who said, “Look, I know the ministry of finance in Luxembourg. And I’d like to introduce you to him, because he has some really interesting ideas on how to change the economy of Luxembourg, and he needs your help.” So I met him over the phone, and then I flew out and talked to him. We got along fabulously, and he was a guy; he was by far the most powerful single individual in the whole government. And what he wanted to do he could get done, which was great!
So what he had decided was that he wanted to transform the economy of Luxembourg from a 90% dependence on financial services to bring in biotech and healthcare. And so he said, “Would you like to write a proposal to help us do this?” And I said, “Oh, absolutely!” So we wrote a proposal and what we offered to do was 1) Set up at the newly minted University of Luxembourg—and at this time it was four years old, so, they had a biology department by nobody who knew anything about modern biology or disease or anything. So what I offered to do was to set up at the University of Luxembourg a Center for Systems Biomedicine, which really is what we do in Seattle, and what we guaranteed we’d do was identify the director, help recruit the faculty, and what was really powerful was that we took 11 senior postdoctoral fellows they hired and we trained them for two to three to four years at ISB, and they went with a commitment to go back for three years and transfer everything they’d learned. So this institute was up and running within three or four years of its creation, and it is now one of the absolute leading centers of systems biomedicine in the EU. So we were very successful in that. The second thing we did was to set up an international network. And what we’d asked for from Luxembourg, was [that] we had a whole series of technologies and strategies that we’d been trying to develop, but we really had trouble at NIH getting it funded, because NIH kept saying, “No, you have to do more.” And the point with these things is, you got half a proof for principle before you can do more, and that costs money and...So, we went to Luxembourg and said, “Look, we have about 10 technologies and strategies we’d like to develop, and we’d like to ask you for 100 million dollars over the five year period.” And they gave it to us without a question.
So we were able to develop all of these fantastic technologies and strategies—I could go through and tell you about them, but, we won’t do that here—and what was interesting about this strategic partnership was that it ended in 2013, and it placed us at an incredible tipping point in medicine, because for the first time, we could do a lot of things people could never before. So I was trying to think of how we could apply these things to a program which we could introduce to the healthcare system. So what we came up with was interesting. So, let me just say, P4 medicine is really different from contemporary medicine, and in five important ways.
1) It is proactive rather than reactive. 2) It focuses on the individual and not on populations like traditional medicine does. 3) It is committed to wellness as well as disease, and what P4 medicine had said was that healthcare should be two major considerations: wellness (optimizing it) and disease (dealing with it). And society, even today, put 96, 97 % of its resources into the disease and almost none into wellness. And the [4th] thing, of course, was that we were starting to think about these technologies and what they could do, and we realized that human beings are really incredibly complicated creatures. So what you need to be able to do was measure in a 360 degree survey many different features of every single individual human being. And we called these personal dense dynamic data clouds and I’ll say a word more about that in just a moment. And then the final thing that was the most controversial, was that we said, “The way that you do clinical trials is fatally flawed.” And that is, you take 20,000 individuals and you give them a cancer drug or a placebo, and you extract the data, but you know, 1) each individual is unique genetically, and 2) they’re unique environmentally. So it means you’re averaging disparate objects, and we know from mathematics that when you do that, you enormously increase the noise of the signal. So we argued, “We’ll take 20,000 individuals, each with their data cloud, and we’ll stratify them according to each of their unique data clouds, ” for example, as whether you respond to a drug or you don’t respond to a drug. And what’s interesting about that approach is that if you take the 10 top drugs selling in the U.S. today, the responders to those vary from 1 in 4 to 1 in 25. So 85% of the drugs are wasted. They expose the individual to cross reactivities, they cost lots, it’s horrible. So what we can do with the data cloud is that we can immediately separate the responders from the non-responders, and the cool thing about is that Genentech showed us with a drug called Herceptin. If you can identify the responders; they took 46 responders to Herceptin into the FDA and got the drug approved for 46 patients. And that’s what everyone’s going to do in the future because we’ll be able to stratify from the very beginning responders and non-responders. And in fact your initial clinical trial should be probably 30 or 40 individuals, because that is more than enough to separate the responders, the non-responders and everything. And we are in the midst of persuading Pharma companies...And Genentech is intrigued with this sort of idea, so we’ll be doing some things with them.
Anyway, what I decided to do then was, look, I’ll persuade 100—it turned out 108—of my friends to undergo an analysis with these dense dynamic data clouds of a period of a year. And the idea was that we do the genome sequence, and from bloods and urines we did clinical chemistries and proteins and metabolites. We did the gut microbiome every three months. We did fitbit...And the idea was that you can integrate and analyze that data, and for each individual point to a series of actionable possibilities, which if acted upon, would either improve wellness or let them avoid disease. And in that year-long study we proved just unequivocally, that works beautifully. But the other thing that was really key about our study was, we brought the actionable possibilities to the pioneers, as we call them, with coaches. The wellness coaches were trained number one in psychology. We started the project by the coach talking to each pioneer and asking them, what are your real health objectives. And let me say, if I asked you that, it would take at least an hour for you to figure it out. I mean, you guys are all young and immortal and can never imagine getting old or having any problems. Our audience was, you know, average, middle-aged, and somewhat different in this regard.
But these were trained psychologists who could explain the actionable possibility to the individual and persuade in the context with their health objectives to carry out the actionable possibility. And we got 70% compliance, actually, which was—I would’ve guessed 5 to 10 %—but we did very well. And the data turned out to be spectacular and they gave us new insights into how healthcare industries are going to operate in the future, including Pharma—actually, it just came out in a paper with Nature Biotech, in the August issue, in fact, we have the cover of that issue, so you can look at that, or I could send you a PDF if you’re interested. But the second thing we did as a consequence of the success of Arivale, the vast majority of the pioneers really wanted to go on after it had ended in the first year. And I’ll just say paranthetically, at the very beginning when we were thinking about the study, I went to NIH and had a nice discussion with Francis Collins, who was the director of NIH, and asked him if he would consider supporting a study such as this, and he said nope, they had no interest whatsoever. And in fact a year before Obama had announced precision medicine, we had already defined it, in terms of these personal dense dynamic data clouds, what it should be, it’s very different from what NIH is doing right now.
So anyway, we started a company—again, saying that we should bring this to everybody—called Arivale, which brings to the consumer scientific wellness and that started in mid-2015, and now today they’ve got more than 3,000 customers, which is 30 times as much data as we analyzed in the original case and everything, so that is quite the exciting venture. And I would say, we really have proven that scientific wellness works very well, and the enormous challenge now is to bring the cost of assays down so it’s affordable by poor as well as by middle-class and the other classes. And the assays’ costs are coming down...so in a few years, we should be in pretty good shape and we are pushing new technologies to do that even faster. So what happened in the beginning of 2016 was, Rod Hoffman, who’s the CEO of Providence-St. Joseph’s—which is an enormous nonprofit healthcare system centered here in Seattle—came to me and said, “I’d like to make ISB the research arm of Providence, and we’d like you to become its chief science officer.”
So we debated that, and agreed [that] this was a great way to bring P4 medicine to the healthcare system, and it’s really opened up a lot of very exciting possibilities. So one, I immediately decided, what we would do is choose from Providence’s strengths 7 projects that we called translational pillars, which would be effectively a very new kind of clinical trial. And what we would use on those are dense dynamic data clouds for all the reasons we talked about. And what we would use on it were relevant to these new technologies and strategies that we’d developed from all the Luxembourg money and everything, so it gave us a really unique chance to introduce some of these things to the healthcare system.
So, we found in the Providence system really good clinicians, scientists that could head each of these projects, really terrific. So we’ve had great support, and in fact, Providence put in the money to fund the first two clinical trials. So the first one is on scientific wellness, and what they’re going to do is put a thousand of their employees through the Arivale program for three years, and compare them with a thousand randomly selected employees, and we will assess over that time 1) improved health, improved wellness and 2) how much cost-saving doing scientific wellness creates in the system, and it’s going to enormous for lots of different reasons. And what we will be able to do then is go to the payers and persuade them that they should pay for scientific wellness, because in the end it will save money. And I’m actually trying to persuade Providence to become a payer themselves and take advantage of all the money that’s saved rather than giving it out to a third-party payer and everything. And they’re thinking about it, anyway.
So the second clinical trial is really an exciting one. So for personal reasons, I am really interested in Alzheimer’s disease. And it turns out, in thinking about Alzheimer’s disease, it’s utterly clear [that] no single drug or even two drugs is going to touch it. It is a disease that is going to require multiple parameters and their adjustments. So we have a collaborator at UCLA that actually asked the simple systems question, “How can you optimize synaptic communication between nerves?” And from that, he devised a 36-point regimen which includes supplements and vitamins and drugs and exercise and a variety of other kinds of things that he’s tried on 125 people and had some remarkable transitions from early Alzheimer’s back to normal individuals. So we’re going to do a clinical trial with proper controls, using the dense dynamic data clouds and these new technologies to carry this out, and the hope is, within a 3-year period, we will have really good quantitative blood biomarkers that can signal the earliest stage of Alzheimer’s. And then we’ll have this multiparameter analysis that can immediately reverse people back to normal. And you know, as one example of cost savings, Alzheimer’s today costs society 260 billion a year, so suppose we could successfully carve away 10 percent, 20 percent, 30 percent of Alzheimer’s, you could have enormous cost savings with nothing else. And we can do that with other chronic diseases as well.
The second thing we plan to do...We plan to create a center for systems translational medicine that is the interface between the Providence system and ISB, and there we’ll house a lot of interesting things. For example, we’re beginning to think about how to create, in Providence, a scientific wellness clinic that can do something really unique that Arivale can’t touch at all. So Arivale’s the commercial company that brings genomics and other things to consumers. And what commercial companies can’t do is bring to their customers any actionable possibilities that relate to disease, or the FDA will shut you down, just like they shut down 23andMe just about 5 years ago or so. So we have for all these 3,000 pioneers, probably more disease actionabilities than we do wellness actionabilities that can’t be used. So what I’m going to do is set up—in the Providence system scattered throughout—wellness clinics that can take these people in and we’ll have the coaches and we’ll have the physicians to give them the actionable possibilities. And with many cases, it’ll be warning, in other cases, there’ll be things they really have to do almost immediately. And we’ve persuaded a physician to work here at Swedish and we’re going to actually set up the first health clinic and figure out how to do it and begin doing all these things. Providence has five other clinics in the Southern region in Northern California and Southern California, and once we’ve learned how to do the scientific wellness clinic at Swedish, then we can go to those and bring them the chance to enormously enrich their wellness possibilities. And of course the thing you have to be really careful of is, people don’t want to be told what to do and people are really threatened by things they don’t know, so it’s not an easy task to make those kinds of changes.
Katherine: I was going to ask—Do you think that’s something that has changed from when you first started your career to now, about people’s acceptance of new technology? And when people resist it, why do you think that is?
Hood: So, I don’t think it’s changed very much because I think what is a normal part of most scientists and certainly most physicians, is a reluctance to give up things that you’ve always practiced your entire life, and things that you’ve learned early in your career. For example, I went to seven different high-ranked medical schools, trying to persuade them to do a fraction of the things that we’re talking about doing with Providence, and I never got anywhere. And the big issue was always the silos that existed there, and very powerful individuals that were threatened either because they thought that we wanted to take their science away, or threatened because they thought it’d take resources they felt were their own from them. And in academia, powerful people can veto things even if most people feel it’s good. And I tried to do the same for medical education, we’re doing some really radical changes in medical education, and I could never get any medical school to even think about that. And I finally came to the conclusion that the only medical school you could use to transform education is a new medical school where the people aren’t set in their ways. So the University of Washington is starting a brand-new medical school in Spokane this fall, and what I’ve persuaded them to do is put their 60 medical students into the Arivale program for the four years they go through, and we’re working with them to redesign a curriculum that will go with their learning to use their own data and come up with their own actionable possibilities. It’s really going to be quite an exciting kind of endeavor.
So the wellness clinics are a second thing that we’re going to do. A third thing we’re going to do is, I’m going to set up a technology platform at ISB that will have the capacity for executing the dense dynamic data clouds that Arivale has. Now, four projects that Arivale does not have interest in—and we’re actually going to import their extremely powerful analytic tools, the computational analytic tools for data integration and modeling and all that kind of thing, and we’re just negotiating the kinds of terms for doing that now. And finally, as I indicated, we are really thinking about how to revolutionize education and bring P4 and scientific wellness to health care professionals, and especially physicians to start with, to patients. We’ve also done a lot of K-12 education, so we’re working with senior kids taking both health courses and biology courses and we’ve created this series of four systems modules to teach them all about systems biology, and these modules are now in all states; they’re in 27 different countries, and more than a million kids have gone through learning the hands-on science these modules teach. And we’re going to do exactly the same for P4 medicine, we’re just in the process of starting that.
So, that’s my career. I still think that it’s the most exciting part of my career right now, we’re doing so many exciting things that are really going to change healthcare and how people think about necessities of life, and I want everyone to think [that] optimizing wellness is a big necessity of life.
Will: A common theme throughout your life is that you continue to work on new projects, what do you think motivates you?
Hood: I want to be excited by what I’m doing. And you know when you work on a thing for a while, you really define it really well, and then it becomes very mechanical, carrying through and finishing all the details. I would really rather go on to something brand new and let other people finish out the details. And another thing my mentor always said was, “There are librarians who fill out all the details and dot the i’s and cross the t’s, and there are the pioneers that take you to new places.” And he said, “You always want to be a pioneer.” And in fact, I had a good friend who was an industrialist and a famous art collector in Pasadena called Norton Simon, and he once said to me something that was really interesting.
He said, “If you plot the career of a typical person, where the y-axis is the level of success, and the x-axis is time, a lot of people are really bell-shaped curves. They go up to a maximum and they gradually fade away.” And he said, “You never need to be on the downside, if just before you get to the top, you switch and do something completely new and different...What that does for you is, it makes you more insecure again. You have to go out and learn, you work hard, you’re enthusiastic, and then you just have another curve like that.” So I’m all for having multiple up-curves and never getting caught on the down-curve. And I think that you should think about the same kind of thing. I’ve changed every 10-15 years in major ways—look, it’s all biology, but what I thought about what I did changed completely in each case.
Katherine: So you have a background in both genetics and in clinical trials and testing medicine—
Hood: Well, another thing that I didn’t tell you was that I have a pretty good engineering background, too. Because in high school, my father was a superb electrical engineer in Montana, he did really interesting things, but every summer he’d teach big courses, and he wanted me to come down and take the courses. So circuit design, systems theory, all these kinds of things. And that totally changed the way I thought about biology, from a much more engineering point of view, and that’s why I really think that bioengineering is a terrific major to have as an undergraduate, if you’re really interested in the kinds of things that I talked about here.
Katherine: We’re working on CRSPR CAS9 where we’re using bioengineering to kind of change the genetics of something. Do you feel that there are benefits or drawbacks to trying to cure genetic disease by changing the genome of a human before they’re born, or do you think it is—do you like doing the clinical trials with medications and wellness as a way to kind of treat that?
Hood: So I think you need both. I think you really do need both. I mean, if you’re going to change germ cells, which means you change the gene and every cell in the body, you really have to be careful that you know what you’re doing. And see, I think it’s probably fine to do that for diseases where we unequivocally know it’s one gene and we know what it is and what we have to change, but you 1) have to be sure that’s all you change and 2) we have to be sure there isn’t something we don’t know about lurking there, and when you change this, you’ll really screw the individual up. And see, I think that’s the thing that people really have to be very careful about. Now, the great way to do it is to look at defects that come from organs where you have access to stem cells. So for example, your hematopoietic system, your red blood system, all is derived from hematopoietic stem cells. And you can easily get them from an individual, and you can easily do CRSPR modifications...So for something like thalassemia, where we know the gene—it’s the beta hemoglobin gene, position 6, you can change the valine to a glutamic acid back to a glutamine, you know—that is something we’re already working on. But changing the sperm cell, where you do everything, is a much bigger risk if you do anything a) you don’t know about or there is another aspect to the disease you don’t know about. So I think you just have to be really careful that you have total understanding.
Now, there are bioethics people that would argue [that] we should never change the germline, and I don’t believe that all, because I think that if we can change the germline and really improve people—and there are other people who are worried that the improvements, maybe we’ll have a super-race and an ordinary race—you know, I think to do that, we’d really have to change complex traits that do with consciousness or how we think and things like that. That isn’t going to happen for many lifetimes, I mean, we don’t even know how to think about consciousness, it’s a holy grail that not even systems thinking—you can do many things, but you can’t even begin to even think about how to change it in a positive way. So, I think the things that we’d focus on would be very immediate, and we have to be certain that the technology has zero artifacts and I don’t think that we’re quite there yet in that regard, either. So we have to be careful. And in the meantime, we should go ahead with the kind of things that I talked about with therapies and drugs, and the most important is to get the early transitions and reverse them, they’re easy. And we’ll learn how to do that in the next 15 years, 20 years, and I think that we can take out most of the bad chronic diseases. Cancer, I think we can take, Cardiovascular, I think we can take, Nerve-degenerative, I think we can deal with Diabetes, those kinds of things.
Lauren: You talked about developing curriculum for K-12. How young does that go, is it normally targeted for high school students?
Hood: No, we work for K-12, all the way, on the initial set of studies that we did, and we created courses that were inquiry-hands-on; we created resource centers where the teachers could get the things they needed to do the experiments with students; it was enormously successful. Now, with something like P4 medicine, you have to have a little more background. I actually think we can get down there—I bet middle school kids would really be excited—but what we’re doing now is, in each case, we take teachers and students to help develop the modules so we’re sure they work well, and we’re very careful that the modules help fill in the requirements that teachers need at the end of their course. If you just do things independently, they won’t do them, because they’ll say, “My students won’t do well on the tests,” so we make sure that they’re all fully integrated and everything, and that’s why they’ve been so widely accepted across the country.
Lauren: So you go clear down, even to elementary school?
We do elementary school, yeah. We did initially, and it really changed Seattle School District, and we got really terrific teachers that were committed to this kind of thing, but in the end, it’s slowly faded away, and it’s faded away because new leadership comes in, they have no idea what’s happening, they don’t—I mean, to make it permanent, we’d have to spend all our time with the Seattle School District, and we go back and give them refreshers from time to time, but we just don’t have time to. And we’ve tried to get to the administrators and teach them what a valuable thing they have, and that’s been very useful, but the trouble is, administrators and teachers frankly really turn over, so unless you really keep them up-to-date on everything, things started to diffuse away. So what you really need to do is get these things officially in the curriculum books that they use and everything, and we’re trying to do that, but that’s a big job.
Lauren: So with that, do you think that things with common core standards and stuff put roadblocks [for] people teaching science, since they’re not things like computational biology or systems biology?
Hood: No, but you can get around all those, if you know them and understand them well. And all teachers are willing to admit that they’d love to enlarge the understanding of things. So no, in fact, we’ve played a very active role in Washington State in setting the standards of all the different levels, so we’ve really tried to tour things towards getting things more science.
Michael: You’ve done a lot of work and contributed a lot to the scientific field over your entire life, and I wondered if that cut into your personal life.
Hood: What I can say is, my two kids, who are now 48 and 50, are incredibly successful and incredibly well-balanced, and we always had a good time as a family. As a family, we always did camping; I did a lot of technical climbing—my son is a much better technical climber than I am now—and so I think that as a family, I traveled a lot and was away a lot, but when we played, we really played intensely, and we did terrific things together. And I think the measure of how good a parent you are is what kind of kids you’ve raised. And I think that my wife and I raised really spectacular kids. I mean, successful as people as well as successful as professionals. My son is a professor at the University of Alaska in Juneau in environmental engineering and studies how the melting of the glaciers is changing the ecology and chemistry of the sea, and it’s really a fascinating topic. And my daughter, a couple of years ago, started her own law firm on discrimination and so she attacks big companies that discriminate against poor individual people and she’s really great at it, she’s been extremely successful, and so she’s very excited about things. And they both have kids—they unfortunately have 5 granddaughters and for me and no grandsons, but I wouldn’t trade a grandson now for any of the granddaughters, they’re really terrific and again, they’re really great kids learning to do lots of things and are very involved in things. And I spend a lot of time going back and forth between Juneau and Los Angeles, where my daughter is, to see the kids every other month, that kind of thing.
But do I regret being away as much as I was? I really do in some ways. For example, I really do miss events for the kids that I would have liked to see, but on the other hand, I couldn’t have done what I did if I had a lot more time with being at home and things like that. So it’s a decision that you guys will all have to make; you’ll have to decide what fraction of yourself you put into your profession as opposed as into your family, and I would argue, where you can make the choice, less important is that you do intensely family things as well as professional things, and they’ll remember. Our kids all remember the great times. For example, we used to go to Aspen for about 20 years, 6 weeks every summer, because I wrote a whole series of books. And the kids grew up in Aspen, they learned to fish, they learned to play tennis, I mean Aspen is...and they have their fondest memories of the things we did together, hiking, they learned to appreciate classical music—Aspen has wonderful classical music, a summer festival and everything—so they had really great times.
So I think that you can work out balances, but the thing is to do things that stretch your kids’ minds and bodies, make them learn new things and do things. Go on hikes. You know, my daughter, for a while, was a couch potato, but she quickly migrated out of necessity. And she turned out to be a terrific athlete, superb swimmer, superb at volleyball, she was great at gymnastics. And what’s interesting was that she’d get very good at each of these things, and then she’d quit because she felt that people had too many expectations of her and she didn’t want to people to have expectations, especially her father and mother. So we learned to keep hands-off. I suspect that some of you have gone through some of those kinds of relationships. So overall, I can’t complain. If I had it to do over, I would spend somewhat more time with family.