Editor's Note: In this Medscape One-on-One interview, Eric Topol, MD, speaks with the Icahn Institute's Eric Schadt, PhD, about how he turns math into medicine, and how he hopes to hasten clinical research and the search for cures as he zips along on snowboards and superbikes.
Starting Down a Math Path
Eric J. Topol, MD: Hello. I'm Eric Topol, Editor-in-Chief of Medscape. I have Eric Schadt with me for a Medscape One-on-One interview. Eric is the director of the Icahn Institute for Genomics and Multiscale Biology at Mount Sinai in New York City.
Eric, you have a remarkable background in mathematics. How do you go from mathematics to what you are doing now?
Eric E. Schadt, PhD: I started in pure mathematics, which is drilling deep in math for the sake of math. It's about as detached as you can imagine from applied math. But once I achieved PhD candidacy in pure math (I studied computer science and applied math as an undergraduate), I started thinking more about how math could be applied. I was hearing a lot about the sequencing of the human genome and other technologies that were coming in biology that might demand a more quantitative mathematical approach. I started going to seminars about where biology was headed and got bitten by the "Let's understand living systems at a deeper level" bug, and then made the jump from pure math into an applied math biology program.
Dr Topol: What's impure math?
Dr Schadt: Mathematics on its own is quite a beautiful discipline, and the kinds of relationships you can explore in a logic-driven way don't necessarily have an easy tie-in to the physical space. Impure math is how we take what we know about mathematics and apply it to real physical problems. I have turned that corner and now I think that maybe I wouldn't ever have been one of the greatest pure mathematicians. But I can be a greater applied mathematician and take that mindshare and help apply it to the real world.
Dr Topol: That makes a lot of sense. Eric Lander also has a background in math. So a couple of noted people in genomics have come through that path.
Dr Schadt: Indeed. In fact, my advisor, Ken Lange, was a pure-math guy, and he was in that wave with Eric Lander and [Robert] Elston.
Linking Academia and Industry
Dr Topol: It is an interesting connection. Speaking of connections, you have had a very interesting background. You did some time in a startup called Rosetta Inpharmatics [that was acquired by Merck] and at Pacific Biosciences. You have taken the unusual path of having gone from academia to life-science industry startups and then back into academics. What is it like to live on both sides of the experience?
Dr Schadt: After my PhD program, the attraction to a company like Roche [where Schadt was a senior research scientist] and then ultimately the startup company, Rosetta, was the focus in scale of resources to tackle a new area of biology—this high-dimensional, multiscaled view, with technologies that could look at the entire system and all genes at once, and the money that was required for that focus. The biology community back then wasn't necessarily sold on where that technology was going. The National Institutes of Health (NIH) weren't funding these technologies on a large scale at that point because they were unproven. Industry was an avenue, because they bet heavily on this technology and they were dumping serious amounts of money.
So I went into it just wanting access to the technology and to apply it to real biology, and that was successful. We achieved pretty good success in showing how we can use Affymetrix GeneChip® technology to better understand such diseases as asthma and cardiovascular disease. What I learned at Roche was that there is a line here at the academic industry divide, and not many people want to ride that line. But if you can master riding that line, it's a good existence—a good way to benefit from what a company has to offer and from what an academic institution has to offer. You can minimize the weaknesses of both by maximizing the strengths of both. I learned through my career how to play that game and became comfortable living in that gray zone.
Dr Topol: It's not very common. It looks like you have done it really well.
Dr Schadt: I don't know that I have any special skills. When I was at Roche and Rosetta, it wasn't just about needing to meet the demands of a company, especially a startup. As you know, those are intense efforts. But I had to maintain my academic identity by publishing papers and being involved in academic research that would lead to publications on a scale that would be respected by the academic community. So it was a little harder than if you lived in either world independently. In my experience, it was well worth the effort because of the opportunity to gain the advantages of each. I had an appetite on both sides to blur that line.
Life in the Fast Lane
Dr Topol: That's only one aspect of the unusual path that you have taken. Another that is interesting to me is that before you even finished high school, you went into the Air Force.
Dr Schadt: My great escape from rural Michigan was going into the military. I had lots of energy and wanted to explore the world. I didn't come from a wealthy background. I was impoverished, so that was an avenue to get out into the real world and start exploring what it could be. It was very physical. I went into the Air Force pararescue program, which is a very elite physical program. I was injured during the training; that washed out my military career and led to my exposure to the academic side.
Dr Topol: You have had a few accidents. Earlier this year, you were in a snowboarding accident.
Dr Schadt: I try to maintain some physical activity. [I was with my] sons on some big hills, going extremely fast on a day when the conditions weren't ideal. I caught some air and had a bad landing. I hit really hard—broke my clavicle in five places as well as four ribs, and I had a collapsed lung and a concussion. All I could think about was traumatic brain injury and hoped I didn't succumb to that kind of damage.
Dr Topol: But, knowing you, that won't hold you back from speed.
Dr Schadt: No. In fact, [my sons and I] will be going to the New York Safety Track in upstate New York this weekend on my BMW S1000RR, trying to go 200+ miles per hour on the track with a bike.
Dr Topol: So you have a real need for this.
Dr Schadt: The speed is addicting. When I am thinking about science problems and solving very hard problems, it consumes me. The snowboarding and riding super bikes is one of the few ways I have to completely detach. Your survival depends on you focusing. It's one of the few things I can do that allows me to tune everything else out.
Dr Topol: Having had accidents doesn't hold you back?
Dr Schadt: It doesn't hold me back. But as I get older, I don't want to have a catastrophic injury that debilitates me for the rest of my life.
Dr Topol: Are there safer ways to get an adrenaline rush besides going 200+ miles per hour?
Dr Schadt: No, but that's why we do it on the New York Safety Track and not on the open road.
Thinking Too Deeply to Pick Out Clothes
Dr Topol: You also have a distinct, iconic look: Even in the middle of winter, you might be seen wearing cargo shorts. What's going on with that?
Dr Schadt: It might be a carryover from the military. I didn't enjoy very much about the military, but the one thing that was easy was the dress because it was a uniform. You didn't have to think about what you were going to wear every day. When I got out of the military and went into pure math, it drove me so deep into determining how smart I was and whether I could solve these really hard problems. It caused a transformation in my mind about how deeply and how hard I could think, and I wanted to tune out everything else. I didn't want to think about looking in the closet and deciding what to wear, or what color I wanted the shirt to be. It slowly morphed towards being back in graduate school and wearing T-shirts and shorts every day.
Dr Topol: You have upgraded.
Dr Schadt: I upgraded (to polo shirts) once I got into the commercial world, because they didn't like the T-shirts. But it stuck. It's easy. It's low-energy. I don't have to think about it, and over time people thought it was kind of cool. It's not that I equate myself with Steve Jobs or Mark Zuckerberg, but there seems to be that theme that some people enjoy not having to think about what they wear.
Lured to the East Coast
Dr Topol: When you were recruited to the Icahn Institute, did you meet with Carl Icahn? How were you lured here?
Dr Schadt: The East Coast was not my top place to live. I was sitting in sunny Palo Alto, California, with Pacific Biosciences and really enjoying the transformational technology that I was doing there. They were being very supportive in allowing me to build a research program outside of Pacific Biosciences to exploit the technology and solve big problems of disease. In effect, I was trying to do in Palo Alto what I'm doing here: form an institute in collaboration with Pacific Biosciences, and build out this big data analytics center and have it hooked up to a school such as Stanford or University of California San Francisco. We tried to raise the necessary money—we needed on the order of $100 million to build out that kind of thing and hire the right kind of people—but it was during the great recession.
Dr Topol: It was kind of a tough time to do that.
Dr Schadt: As we were having trouble raising that kind of money in the Bay Area, I cast my net further. I ran into Carl Icahn at Mount Sinai, and they were looking to make this kind of investment. Initially I tried to convince them that it would be cool to have a Mount Sinai Institute in Palo Alto.
Dr Topol: You couldn't make the sale on that one?
Dr Schadt: I couldn't make the sale. I still didn't want to move to the East Coast, but I finally made a visit to Mount Sinai and was amazingly impressed—not just with Carl Icahn willing to make a big investment, but with the leadership at Mount Sinai. They took a very long-range view of where medicine was going, that information was going to be king, and what we had to do to become competitive and survive in 5-10 years' time.
They were thinking progressively, and it convinced me that this was a place where the kind of vision that I had could happen.
Dr Topol: That's terrific. You have hired many interesting people outside of medicine, like [data scientist] Jeff Hammerbacher, formerly of Facebook. You have a different idea of how to build something like this—not the traditional way at all.
Dr Schadt: The problem is how to leverage the digital universe of information to build more predictive models; to point at patients at Mount Sinai as they walk through the doors of the medical center, and to better diagnose and treat—or even prevent—disease in those individuals. That's not the classic medical doctor or classic biology researcher; that's somebody who thinks about big-scale data, information, machine learning, and deep learning. I brought in Jeff Hammerbacher, who is a pretty amazing guy. He was the founding chief data scientist at Facebook and then he formed Cloudera, which has been an amazing success in bringing Hadoop®-style computing to the masses. We need to be able to build that Internet-scale architecture in medical settings as the scale of data grows, and then have all the right analytical minds on the data to build the models that can be translated more clinically.
It's not enough to have the smart modelers building the sophisticated model. You need a way to translate that, to get that into the hands of physicians, to get that into the hands of the consumers—the patients—and to enable them to better understand what might be going on in the system. We have built out and hired at least 250 people in the past 3 years. It's been pretty crazy to move at that scale.
Dr Topol: That's good for unemployment here in New York City.
Dr Schadt: It has been good for the economy and job creation, but probably half of that is aimed toward big data analytics and predictive modeling.
An Appetite for Big Data
Dr Topol: You have taken big data to mobile medicine in your recent creation of an asthma app with Apple. You were at the Worldwide Developers Conference recently. Did you have an idea that you'd get into the whole mobile device world as well?
Dr Schadt: I don't know that initially I was oriented in that direction. We have always looked at disease as a more holistic problem. We need to pull in as many dimensions as we can and integrate them to build these models of phenotypes. Seeing the kind of work that you were driving with wireless devices, and seeing the revolution coming that would enable a whole new scale of phenotyping of individuals—not just in snapshots, like when you go to the doctor's office, but longitudinally over time—it was very natural for us to want to jump on that bandwagon and use it as another avenue to create larger-scale phenotypic data collected longitudinally that we could integrate with the molecular data.
Dr Topol: That's fantastic. You are revolutionizing medical research. It's a whole new way to collect data. Could you ever ingest enough data? Is your appetite for data as big as it gets?
Dr Schadt: It's among as big as it gets, and it's a frustration to many because we never want to accept the boiled-down—even with the imaging folks—where we want to start to integrate the imaging with the molecular data. We didn't want to accept the principal component reductions that they would do to come up with main basis vectors for interpreting structural feature information in the brain. We wanted the voxel or pixel level of information, to start from scratch. It is somewhat of a natural bent to want to work at the lowest level and then work your way up to the highest level.
Although, I think we will run into technology limits eventually as single-cell sequencing comes into play and we start sequencing more routinely whole genomes. Your genome won't be sequenced once; it will be sequenced several times a week to monitor what's going on in your system. At that level, the data will be too vast and it will cost too much money to store, so we will have to think about how to get smarter and reduce that dimensionality. I'm starting to see the limits, at least.
Dr Topol: We certainly have been big on hoarding data and short on processing it and making what counts out of it. Another thing that you have been big on—I know you worked a lot with Stephen Friend—is the open data and open science movement, and I think that is part and parcel of this theme. What's your philosophy on that?
Dr Schadt: That came out of the pharmaceutical experience that Stephen and I had. We were part of a startup, Rosetta Inpharmatics that Stephen founded. I was chief scientist and we were acquired by Merck, which was kind of fun in the beginning because we had a 5-year run during which they invested very heavily and we were running technologies and big disease groups, trying to figure out the biology of disease. But the problem was that they wanted to hoard that information; they didn't want to share it broadly. They didn't want to see the models that we were building used broadly. They wanted to maintain a competitive advantage with the data, and what Stephen and I were thinking the whole time was that we need to push to make biology more competitive in the pharmaceutical space because that's going to help everybody. It's going to benefit the pharmaceutical industry by making better bets because they would have better models that are refined by the communities. It's going to benefit the communities to have access to more information to build better models.
Sage Bionetworks [founded by Friend and Schadt] was born out of the desire to make biology competitive and offer platforms that would enable broad sharing of data, with the appropriate rules and incentives to make people want to be able to participate in that. If we want to take biology and medicine to the next level, to get to where they are in physics, climatology, or quantitative finance where models rule the day, and where knowledge and understanding are organized in these models, we as biologists and medical researchers have to be hosting these models in an open way that enables everybody to pound on them, to evaluate their efficacy, to compete them against one another, and to refine them and evolve them in dynamic, adaptive ways. That has to happen or we don't achieve all of the vision of precision medicine and the impact that those data can have on real lives.
Selling Your Ideas
Dr Topol: That is very important. What you have been doing with others to lead that whole movement is fantastic. The last thing I want to discuss is how unusual it is for a data geek (meaning that in the most affectionate way) to be able to connect with the media and tell your story to the lay public. You have been doing that for a while and are very good at it. I remember seeing a great story in Esquire.[1] It was a profile about how you would get on planes and link to supercomputers and do all kinds of analyses. Are you still doing that? Tell us what that experience has been like and whether you think that also is important to try to advance the field.
Dr Schadt: What I've learned through the company path is that selling your ideas, selling where you want to go to the individuals who control the purse strings, is really critical. A company like Merck, for example, wasn't really designed to think about systems biology and mathematical modeling and all of that, and to sell them on the idea, we had to boil it down and simplify it, come up with certain visualizations and animations and so on, to help convey very complicated material to people who didn't quite get it. If they did get it, it would enable you. There is a lot of environmental context that drove the desire to do that.
Pacific Biosciences solidified that. Stephen Turner, who founded the company, is one of the most brilliant guys I have ever met in my life. He taught me a lot, including the importance of thinking more visually in communicating complex material through visualizations and sophisticated animations. I have always viewed that as important. Going to the media is selling what you're doing more broadly. We're all funded through government research and we depend on people trusting in the kind of research studies we run and participating in those. They are ultimately the ones we serve in the medical centers. So we have to take seriously the role of how to educate, and expose what is happening, to help people understand where everything is going, what the technologies are, the potential of those technologies if applied appropriately, and what is needed to get to the point where they can be applied appropriately. The thought has always been that if we can sell that more generally, we are going to have a better system.
Advice for the Next Biomedical Generation
Dr Topol: In closing, there are a lot of young people out there in biomedicine, and they are trying to figure out what they are going to do in their careers. What advice do you have for them?
Dr Schadt: My advice has several lines. If you're still in school, take as much quantitative reasoning and computing as you can. All of biology and medicine is going more purely to an information-driven science. If you want to be a master in that universe, you need to know how to think statistically, how to approach problems computationally, and understand how big data are stored and accessed. You don't need to be a deep expert, but having an awareness of different groups and what roles they play enables you to better manage and form the right teams.
The other [piece of advice] is about the business and academic divide. Go into it wanting to solve the biggest, hardest problems, and don't be constrained by where you think resources need to come from. Don't think that you need to maintain this pure idea that it needs to be in an academic arena funded by the NIH.
There is a big appetite now, especially with NIH funding at a more steady level, to partner with companies that can provide lots of resources, and you have to work out the terms and how the intellectual property is going to work out. All of that is important, but don't shy away from it; embrace it, and get on the mission to solve the problems that matter. Have that kind of impact, and if you want to have a greater impact, it's going to depend on how you can connect the dots—not just within your academic center, but within companies and technology centers.
Form all of the collaborations with different device makers (eg, Apple, Google); these guys are going to be the powerhouses and play very influential roles in the future of medicine. How we can tie it all together demands a new way of thinking about an academic existence being more connected.
Dr Topol: You are right on target about medicine getting datafied. Some of these big tech titans are now into medicine more than ever before.
Eric, thanks so much for letting the Medscape audience learn about your philosophy. It is one-of-a-kind, and you are one of the most interesting people in medicine today.
