 Our next speaker is someone that I have the most personal vignette about. Phil Schaap is a Nobel laureate of physiology or medicine and an institute professor of the Koch Institute for Integrated Cancer Research at MIT. Phil Schaap was the first director of the McGovern Institute for Brain Research at MIT. And his assistant director of the Institute for Administration at that time was a woman named Gail Wolf, whose name is now Gail Luchin. She's my wife. Please welcome and introducing and greeting Phil Schaap. Thanks, Ken. It's I have several reasons to thank you. She saved my life many times, many times. So it's an honor to be invited to make comments today on the 10th anniversary of NIVIV. It's a momentous moment. May you prosper, grow, and may you continue to help the health and well-being of the country. What I'm going to talk about today is what we've called at MIT the Third Revolution, which is the convergence of life science, physical science, and engineering in advancing health care. And we have produced a white paper that was released a year ago. And you can find it on the web about this. Convergence of physical science, engineering, and advancing health care is really what NIVIV is about. It's some of the things that Francis has commented about. And what I'm going to try to do is to give you some feeling as to how I think about this in terms of its future impact on biomedical research and health care. Well, convergence is the merging of distinct technologies into a unified whole. And that is an important word, merging. It is not bringing individuals together. It is bringing disciplines together in ways that the toolkits and the expertise of different disciplines are welcome into the same field of life science. And the problems of life science are owned equally well by engineers and physicists and computationalists as they are by biologists and physicians. And what we expect out of this is new pathways to new insights and discoveries and new opportunities to impact on the health of people around the world. Now we've called this the Third Revolution, which is this integration at a molecular level in specifics is what's new, I think, with engineering, physical science, and mathematical science. But by calling it the Third Revolution, we've essentially said we see two previous revolutions, unless talk about those for a moment. The first revolution being the discovery by Watson and Crick of the structure of DNA mid-century. And the second revolution is that, which as Francis had just talked about in part. And that is genomics. And the third revolution, I think, is something that is post-genomics and that it is something that over the decades, not tomorrow, over the decades, we will continue to see flourish and become an increasingly important part of what the country does in health care and what NIH is involved in, in terms of supporting research. Let's look back over the last 50 to 60 years since the first revolution, the discovery of the structure of DNA. I've made the argument in a number of lectures as you get to get to be an old man like I am now. You're asked to give more philosophical talks. And I've made the argument in many of those cases that life science is really a very young science. And we can really, in an important way, consider Watson and Crick actually the Newton of life science. Meaning that they provided to us by the discovery of the structure of DNA and the recognition that the information in the structure was the information for the creation of new cells and new organisms. The mechanism by which we can see the universality of life all the way from plants to any organism. We now see them as having a relationship through a common evolution and through a common use of DNA as their genetic material. Now, the reason that is important is that if you look back and think about it, well, Newton lived 200 years before the discovery of the structure of DNA. And that makes life science a very young science, a science that we're still having remarkable discoveries in of a very fundamental nature, unfolding the ways life systems work. But if you carry forward from that time in the 50s through the decoding of DNA, the understanding how information flows into the cells, we come to mid 1970s with the establishment of the biotech industry and the first synthetic biology. It's really interesting to think back. And in mid 70s, mankind attained the ability to synthesize organisms by taking and making novel genes and introducing those genes into cells. And so we've developed in the mid 70s the most rudimentary activity in terms of the synthesis of organisms, a whole new way of synthetic biology. And when I was part of this in the 1978 in creation of Biogen, I looked to the chemistry department at MIT to be the sort of future of taking this genetic information and making new organisms. And I have to say that as I look back over the 30 or 40 years since then, it's been the engineers who've taken on that task and not the chemists in this country. So if we look forward now, we see the genomic revolution in 2003, which Francis so beautifully described as being so important and providing us was just an enormous set of opportunities to impact on human health and disease. And now we're looking at forward and saying, well, what's coming? How is all this going to be integrated into something that translates into a greater impact? And I would comment on this in terms of looking at a national academy report, which I was able to co-chair with Tom Connelly from DuPont in the new biology of the 21st century in this white paper that I've commented on earlier. I want to think back to Susan Hockfield at MIT as been a very articulate proponent of what the third revolution is. I've taken this maybe not verbatim, but in terms of theme from her comments about this. Physicists gave engineers the electron and they created the IT revolution. And biologists gave engineers the gene and together they will create the future. And I think there's a lot of literal truth in this, that when we look at the revolution going on in IT now, it is a product of the integration of the science of the physics, this translation of the engineers, the engineering science that created the IT revolution, which is at least more than the biological revolution right now. And biologists have given the gene that will work with engineers and others to create the future. And what will this mean in terms of economic impact? Francis made the case of the importance of research support by NIH and it has been incredibly valuable in creating both increased health and increased economic impact in jobs across the country. But we're now at about 18% of GDP being invested in healthcare. And we've got some of the best healthcare outcomes in the world. But if you look forward with the aging population, increasing demand, what we see is increasing pressure on the system to provide healthcare of the most high quality and impactful that we can. And yet we can't move from a point of 18% GDP in healthcare to 25%, to 30%. So to do this, we're going to have to increase the quality of healthcare in an innovation network where we do it at a sustainable cost. And there again, I think convergence is part of the answer to making that happen. And that's why I think this is such an important part of what NID is doing and what the country and NIH is doing. So personalized healthcare in science and engineering, personalized you've heard effective, more effective treatment. This is one way to improve the efficacy of medicine at lower costs, accessibility, information, technology, providing information, both to the research scientist and the physician, but as well to the patient. And informing the patient about healthcare in a very substantive way, and affordability a more informed consumer and patient participation in keeping themselves healthy and in fact engaging the healthcare community in a more effective way. And this integration is the best chance, I believe we have, to actually impact on healthcare, improve its quality and do that at a sustainable cost. I've taken this slide from a presentation of Denny Osiello, who is the head of medicine at MGH. And this outlines the amount of information we're now integrating into both discovery research, predictive models on the left, as well as actionable clinical insights. We anticipate and our research programs being supported by NIH of spanning an individual patient from genotype, cellular, personal diets, physiological information, including microbiome, form of genetics, clinical responses, healthcare history, medical records. And all this is going to be integrated, has to be integrated, to actually think about what clinical and medical developments you want to do as a pharmaceutical company, as a healthcare share provider, as a research scientist in the laboratory. And that is an enormous amount of information. And the thing to keep in mind, and I don't think we've actually engaged this enough in the community, is that the patient is going to also have that information and is going to use it to demand and want certain types of healthcare. And we're going to have to integrate all of that in the next decade. So why we've talked about these revolutions in life science, there's been equal more or other revolutions, or even greater revolutions in engineering. And I think that's what complements what we're talking about in terms of healthcare and life science in terms of convergence. You know the information technology revolution in which everyone is walking around warred to the world and each other are remarkable, powerful activity. Storage and processing of large databases and increasing use of those large databases and how to search them, how to analyze them, how to get patterns out of them, how to visualize them is something that engineers have been doing over the last decades to achieve number one. Synthesis of composites at nanoscales, nanotechnology, a revolutionary technology and will be revolutionary in healthcare. Micro fabrication, we've seen several examples of that in the comments made today, in micro being able to fabricate devices that isolate single cells and in fact even will isolate components of single cells in highly parallel ways so you can collect enormous amount of information and bring it to a problem. Sensitive and quantitative measurement devices including imaging and we've heard fantastic examples today. This is the toolkit of engineers, major it and control technology and I'm really interested in this question dynamics. Life scientists typically think of steady state. We very seldom can analyze a problem in dynamics. Engineers analyze problems in dynamics all the time. It's called a differential equation. So the engineer's toolkit is information theory which we are just beginning to scratch the surface out in life science but life science is an informational science. That's what Watson and Crick taught us. DNA information, the flow of information in systems and how information flows through different evolution over time scales. Modeling of complex systems. Engineers don't need to understand how a system works. In many cases they can achieve what their ends are by just modeling and quantitatively measuring how a system responds and then tweaking it to make it respond. Quantitative characterization of complex systems, kinetics of complex systems. How do they undergo dynamic change? And synthesis of new complex systems in synthetic biology as a most proximal example but will be more complex in the future as we use multi-cellular systems and try to control organs in vitro, assays in vitro. All of that is tool kits that come with an engineer. So at MIT we've been working on this convergence and we're at an infant step in it in the establishment of the Koch Institute which is a combination of 12 engineers and 12 cancer biologists all together in the same building in which on every floor there are three or four engineers and three or four cancer biologists. For example, you've heard earlier today Sangeeta Bhatia in her organ culture of liver. Sangeeta is across the hall from me. I see her all the time in Kakwee Collaborate in some examples. But this is just a small part of what's going on at MIT and many other institutes across the country. A third of MIT engineers now have life science as part of their activities and that is the youngest group at MIT and some of the most dynamic and you've heard an earlier example today from Francis. So let's look a little bit about what MIT is doing and I apologize at the beginning to being so provincial, but it's where I live and it's what I know. So one of the things that's going on in the Koch Institute is this question of systems. How do we model and understand how a cell responds when you inhibit one pathway or when you stimulate one pathway, not in its primary pathway, you determine the initial pathway, but how do others pathways undergo change in response to that and feedback and feed forward systems and come to a new dynamic equilibrium? It requires enormous amount of measurements. This is Doug Loffenberger in biological engineering at MIT and Richard Heinz and Michael Yaffe and you have combined enormous multi-component observations to mass spec, other techniques of measuring, hundreds of different modified proteins, proteins changing in quantity, RNA changing in quantity, and then modeling all that in a complex set of equations and you see at the bottom DT rate of change with time and that's something that has to be modeled into these systems because if you have a system at equilibrium, it's a dead system. Life is a non-equilibrium process and we've never come to grips with that in terms of our science to date. We've never had the tools built in a real sense, but it is part of how we have to understand in time life systems. And in micro fabrication you heard several examples at MIT, I mean by Dr. Pettigrew and Francis. This is a specific example from Scott Mellon-Mellis at MIT supported in part by NCI and in part by NID. What he's measuring is changes in the weight of cells by having a lever seen up at the top there in which cells cycle through a channel and the vibrations of that lever will change slightly depending on the weight of the cell as it passes at the tip of the lever. And it's a very, very sensitive. 0.01% change in the mass of a cell can be detected. Now the next step that he's achieved that, the next step is to put a restriction channel in that restriction site in that channel where he can then look not only at the weight of a cell but what the deformability of the cell, what the microstructure within the cell means about how membranes can change in the cell. And this is all a single cell. You can do thousands of cells in an hour and it'll be scalable in the future to even higher levels of resolution. Engineering cell biology at a single cell level as Francis commented, an important step forward in terms of what we can do. Moving to a more therapeutic activity, we've seen drug development over the last 50 to 100 years creating drugs that are specific but in many cases not quite specific enough. But there's a lot more information around the cell than just the simple hydrophobic pocket at the catalytic site in which the drug then engages. The cell with the cell surface and many properties of that cell that have information in them that you can use to target a drug to a cell to achieve more therapeutic output. You don't have to recreate the cell. You can just package the cell and you can modularize pharmaceuticals by using the same package and multiple drugs within the package. It's a revolutionary concept in how pharmaceuticals can be developed. In this case, it is Bob Langer using nanoparticles that have been fabricated to carry a drug, in this case, taxile or taxicuring, to prostate cancer cells. It was initially funded by NIBIB and NCI and then the Koch Institute at MIT funded it and then Bob's funded out and 207 in venture capital raised $100 million and is developing this as a therapeutic. This is translation. This is impact on economics. This is impact on health. And now, where are they at in this? Well, what they've achieved by very good engineering in making these nanoparticles 20 nanometers in diameter, modifying their surface, keeping them in solution, circulating in the blood for hours. Note 40 hours in human blood serum, circulating this nanoparticle, allowing it to move out of the bloodstream into the vicinity of cells and being taken up by its targeting activity on the surface to prostate cancer cells. Well, it's very early. There's a paper was published in Science Translation, but this is technology at a nanoscale impacting on therapeutic impact. For many other examples of this, this is just what I'm familiar with and I think is very important. Now, as Francis said, we've seen an explosion in the definition of human genes that cause disease. And we need a genomic technology to actually exploit that information in a very direct way to impact on healthcare. And there might be some ways of doing that that are different than what we think about in terms of creating a small drug to target a specific protein in which we do pharmacology as we do now. And this is SIRNA technology. It's a discovery about 10 years old. It was supported by basic research support out of NIH. It has revolutionized how we analyze genes and cells. It has totally changed how cell biology is practiced. And what it means is that you can introduce a small synthetic piece of RNA into cells and silence a gene from which those genomic sequences are made as complementary RNA in this small RNA. And if you think about what that means is that right now we're doing small drug pharmaceutical development, targeting proteins in the cytoplasm and conventional therapeutics. We're using antibodies to target proteins on the surface. We use therapeutic proteins like interferon and depot to stimulate cells. In many ways, all of those are gene-specific. We target a product from a specific gene. We can target a product from a specific gene with SIRNA. So what's the issue? We should be able to cure all those 400 or 1,000 or 5,000 mutations that Francis has commented on. Well, the challenge is this and that is delivery. How do you take a RNA that is very non-membrane-like hydrophobic, hydrophilic, philic, lack solution and move it through the bloodstream into the vicinity of a cell, into the surface of a cell, release into the cell cytoplasm and function in the mechanism by which it functions from an endogenous machine. And this is called delivery viruses do this. They deliver their nucleic acid to cells. Biologists have been studying how viruses do it over the last 50 years. Engineers are going to solve this problem for us. And when they solve this problem, we will be able to take anything we do in a test tube and direct it to a cell. Now, one solution to that problem that I illustrate here is a lipid nanoparticle in which we take lipids, which have been designed for this purpose, modifications of the surface SIRNA in the middle and use it systemically to deliver in the bloodstream to silence the activity of the gene within a cell. Now, I've debated as to whether I should show you the next slide because I have a conflict of interest, an enormous conflict of interest. I have Francis sitting in front of me and he's allowed to pull me off the podium but I'll do it anyhow. And as I said, I think this is a new way of doing medicine and let me just illustrate that. When we do drug development now with small molecule drugs, we actually go back every time we develop a drug back to the first step in that process and then proceed along through clinical trials to the end. It's not, it's a linear process. It's a process that was established 50 to 70 years ago and it hasn't changed. What this activity of using nano to target is modularization. This phone has been created by a process in which we didn't go back to Bell and reinvent the telephone. We have modular pieces that we assemble to make a phone. So if we can turn pharmaceuticals in the modular, we've changed how drug development is developed. So where are we at? Well, this just shows you an example from a company that I have all conflicts of interest with. I founded it, I'm on the board of it. I'm director of the scientific advisory board. But that just, this is, so take it with a grain of salt. I'm not recommending that you do anything. But what I show you here is a proof of principle in humans. This is PCSK9 which Francis introduced you to earlier today as being an incredibly important target for controlling cholesterol, LDL in the blood. It is being targeted by numerous other mechanisms. But this is a trial in human volunteers. Let me say that again, human volunteers. It means that the risk in this pharmaceutical treatment has been accepted for human volunteer testing. That's taking a lot of risk out of it. And then what you see is circulating PCSK9 because as Francis commented on, it's a very good circulating marker for the level of activity of that protein which is expressed in the liver. And you see at the highest dose, 0.4 weeks per kg, that the level of this circulating protein decreases to 30% and persists over a month. Now, you heard, knockout of this protein is reduces LDL. I won't talk about that. All I want to show you is that you can deliver these SIRNAs in a patient and see pharmaceutical activity. So then let me finish, make a couple of other comments. This is something that's anticipated from the Dr. Pettigrew and Francis Collins comments, implantable chips that can control drug delivery. And do real-time assays in vivo. This is under development. It'll be read out by imaging, as you've heard earlier, by other means and time. It's another way of monitoring a patient and understanding what's going on in real time. And this is very remarkably important. One of the big challenges in cancer as we go to precision cancer treatment is understanding what the genetic mutations are in the tumor cells in a patient. And the way we have to do that now is to biopsy a patient by using a needle, recovering the material, and then assaying it. And patients tend to object if you want to biopsy them every day. But if you're actually developing a cancer therapy, you need to know something about what's happening in that patient as we treat them with these drugs in combinations of drugs. And this work, CTC Microchips by Medetoner and Dan Haber at M&GH, again supported by NIBI, has really opened in a new level of technology the ability to isolate circulating tumor cells and recover them in real time and be able to identify mutations in those cells that can correlate with therapy. A very important advance in personalizing cancer care. It's still under development. It's a highly anticipated advance in cancer research and cancer care comes out of the integration of engineering and life science and the application of translation to a real world problem. So let me leave you as what should society expect from increasing investment in convergence? Better informed and engaged patients out of IT integrated into this activity. More complete understanding of normal and disease conditions as we understand how to analyze in highly parallel ways quantitative measurements of the status of a patient, the status of a cell, the status of a sub component of the cell by imaging. More quantitative models for current knowledge integrating what we now know into a modeling so that we can predict what might happen and then advance our understanding. More real time and highly parallel data collection which I just commented new compositions and systems to control and treat disease. And at the end of the day, I think this offers us the best chance for more effective healthcare at sustainable cost. Thank you. Congratulations for introducing us to the third revolution of healthcare science. Since you've worked in the academy as well as in the industry and also one of the pioneers in the field, how do you think we could control the healthcare cost? There is so much of divergence. As a scientist, I guess we should not be thinking about in terms of economy but economy which supports the science. So if you look at the surgical practice, in one center it will cost $400 for the same surgical practice maybe 4,000 in other place. So there are issues that could be handled. So although we are not interested in how these things are handled, but for science, I guess we have to look at it. Is there any way we could do to interfere or make it more useful? So the first thing I would say is we're not going, it'll be independent of our choice. Society is going to control healthcare costs. So we're going to have to work within that on the next. Second, I do think that we have to consider in very substantive ways as we lead our science, our community as NIH in terms of how we can create the right environment to be as innovative as possible to achieve as higher quality healthcare as possible as individuals. I at my bench doing research, I want to solve this problem. I select the problem, I want to solve the problem. I'll give everything I can to solve that problem. But within the broader envelope of how we support our healthcare, talk about our healthcare, we have to contribute in my opinion to societal problems and solve societal issues. And it's interesting when you do that, it feeds back into the health system and the science and shapes how it works. Something flying around you. So based upon your interest in technology and talking about trying to change the drug discovery process, what do you think the prospects are for actually removing animals from the drug discovery process and replacing with these based human based functional systems and other technologies that you're developing? I think the science that you heard today it will continue to develop. So that we can with higher throughput, more accuracy move some of the activities that we now engage with animals into laboratories. But we will always need animals at some stage in drug development and in science because the physiology of these systems are just too complex to model now. It may be over decades, we will be able to do it but we can't do medicine or drug discovery without the engagement of animals now. But we will remove them over time in many different activities and that will be good. The basic premise of your talk seem to have been that we scientists are in control in putting the technologies forward and ultimately having success. The issue that I have with this premise is that it leaves, it removed the FDA and the regulatory aspects out of the equation. And I think that actually the driving force for all of these technologies to ultimately be successful lies with Congress and with society more than with science, with our scientists. Could you comment on that? Well, there's always been a tension between science and society. You saw Galileo mentioned early on. And there is this always this tension between FDA approval of drugs, cost reimbursement, what technology is going to be used. I think we need to provide the best opportunities we can with our science and engineering to solve these problems. And I personally feel, I don't know if, I grew up in Kentucky, I'm from a farm country in Kentucky and I keep my roots back there and I keep in contact. The citizens in this country love science, they support science and they want the products of science. They understand jobs comes out of science and better healthcare. And they will ultimately speak through their Congress about that as long as we're open and educational in terms of keeping them engaged and making them understand we're honest about what we know and what we don't know. I agree with you, we've created a field of science. It is being incorporated and advanced in many different countries in the world. I don't consider that a negative. I consider it an elevation of our science and an elevation of the livelihood of the people who are involved there. But if we want to stay preeminent in this field and continue to have the ability to create new products, and I've talked about healthcare here, but I can make the same conversation about energy and materials and environment, if we want to have a highest quality of life we can, we're going to have to invest in this and it's a competitive world out there. There's nothing, the oceans don't protect us anymore in technology, the world is struck as you well know.