To be the advocate for science that the governor described. I started my career as an academic Biomedical Researcher as well as a doctor who treated patients with blood cancers for many years. Given my background, i cant think of anything more critical any topic more important than producing the best research to provide the best data that is needed to develop new treatments for our patients. My formative experience in this regard occurred when i took a year between my second and third years of medical school to participate in the hhmi Research Scholars program at nih, where i studied aids dementia. That experience helped me appreciate the art of generating and analyzing research data, my own data, and it really fostered my love of science. Within a few weeks of starting the job, people would ask how i enjoyed working in the lab, and is the best job of my life. That has turned out to be true, even in hindsight. [laughter] it also fostered my belief in the opportunities for doing good through science and medicine. So not surprisingly, when i left the lab back then, and then finished medical school, and then did all my clinical training, and then became a medical oncologist, well, i quickly became frustrated. Taking care of patients with cancer is an immense privilege, a wonderful thing to do, and i love the practice of medicine, but i also hated that it felt like a recurring nightmare of giving Cancer Patients the same treatments over and over again and watching it fail. You oft remind some of that robot that vacuums the floor. It bumps into the chair, moves away, bumps into the chair, goes back again. It was very frustrating. The drugs didnt really work. It was very tough to be in oncologist back then and it was frankly worse for the patients. Me to the lab. I wanted to do better. I wanted to use science to improve care for patients with cancer. Oncology toinical become a molecular biologist and cancer geneticist in earnest. At the time, that felt like a demotion. I was a clinical fellow at harvard. People would come from all over new england to get my advice on cancer. All of a sudden, you go into a lab and you make offers that wont work for you properly. They bounce around like a mexican jumping being. I had to ask an 18yearold summer student how to get it to work. It was a terrible experience, but i went through it, because at the end, i was a scientist and i could do science that would allow me to treat Cancer Patients. That effort is really what its all about. Our commitment to the search for reliable and rigorous data, so that we can find answers for our patients who are looking for a treatment, a cure, or sometimes just the hope that one is on the horizon. We live in a privileged, extraordinary time of scientific progress, where there has been enormous Transformational Movement in medicine. Ive been particularly lucky in this regard, since i would argue that the progress in Cancer Research has been particularly breathtaking. The last few decades in particular, the progress has been dramatic. Take a disease like malignant melanoma. When i was a fellow at the dfci in 1995, this was the worst cancer imaginable. Metastatic disease was terrible, something we seldom cured that patients rapidly succumb to. Of thousand clinicalndreds of trials that provided no useful information. In 2011, we finally started to have some breakthroughs. I remember it was 2011, because my father died of melanoma in year before these drugs started to work. It was a cruel irony given that i had spent my whole life as a researcher. With a new biological understanding of this disease and the immune response to cancer, we developed several effective therapies that all provided meaningful benefit for patients. Over a five year period back then, fda approved five new melanoma drugs with remarkable activity. Now, what was about the worst cancer imaginable has gone from a nearly 0 long term cure rate to a 60 plus cure rate. The majority of people today who develop metastatic melanoma will be cured of it. They are like jimmy carter. They get treated with brain cancer and then go build habitat for humanity houses later on. That is the kind of progress we have seen against one of the most ghastly cancers imaginable. To be clear, we still have a long way to go in cancer. It is perhaps the leading cause of death in this country and there are too many children dying of cancer. But nonetheless, one has to admit that the progress in this disease, or collection of related diseases, has been remarkable. And it is clear to me, that to make additional progress in cancer, we need more and better research. What i said for cancer is true, i would argue, for all areas of medicine. In fact, i would argue, even more needed in other areas of medicine. Where our progress has not been as good. Just take the as alzheimers, antimicrobial resistance, arthritis, als, and aging. Thats one letter of the alphabet and those are all areas where we need to see more progress. Which brings me back to this session. The title of the session itself, leveraging data to accelerate medical progress captures two of the most Critical Issues we face in the medical Research Community generally, and specifically at the fda. First, what types of data do we need . What are the means whereby we get those data, and in a manner efficient, respectful, values patient privacy and follows the rules. Second, how can we best use these data and their downstream technological advances to speed the development of treatments that make a difference in patient lives . At a time of limited resources, and enormous scientific challenges, we all want to make the most of these precious scientific investments. We want to maximize the payoff for our efforts. This rings especially true when it involves data science, where its crucial that we aggregate data and use cuttingedge analytical techniques to analyze it. Nothing seems more frustrating to me than having a huge data set, knowing the answer is in there somewhere, and not having the appropriate modern Analytical Capabilities to find that answer. Using appropriate analytical techniques, we need to solve these problems. By gathering better quality data we can more effectively make scientific progress, find additional answers, develop new products, and, ultimately, help more people. Few places depend more on highquality data than the fda. It enables us to support scientific innovation and fulfill our unique role to help scientists and developers turn their vision for scientific advancement into reality for patients and consumers. It helps us meet our responsibilities to ensure that these products are safe and effective for their intended use, and highquality data are needed throughout a products lifecycle, not just to get it approved, but to follow it in the real world to make sure the devices continue to work as expected in realworld use. But to fulfill these responsibilities, we must be able to integrate the wealth of available data into effective regulatory decisionmaking. Data itself, while useful, is not necessarily transformative. We must turn it into smart data that is usable to connect cuttingedge scientific discoveries to the realworld products and solutions that make a meaningful difference in peoples lives. At the fda, were working with innovative researchers in a number of key areas, by establishing new linkages between complex data sets and making them available harnessing , real world data, and using novel analytical approaches, all in the name of enhancing innovation and providing better information to those who need it to make medical choices. An example of this worth mentioning is from the center for devices and Radiologic Health cdrh at fda has been working through a Public Private partnership to develop the National Evaluation system for Health Technology or nest that merges several disparate sets of Health Systems data to allow studies of device safety and efficacy in realworld use. For things like postmarket surveillance and label expansion. It is, in my opinion, a good idea given the diversity of project products. Were continuing to Speed Development of Effective Therapeutics by promoting innovative Clinical Trial designs such as platform trials, basket studies, adaptive trials, and pragmatic randomized controlled trials. These are things the fda has provided guidance on how we could consider such data. These designs can be more efficient, and can help lower costs and speed accrual. And were also continuing to use the expedited pathways or such as fast track and breakthrough, accelerated approval, and priority review that congress established for drugs, biologics, and devices to help develop and speed the review of products that treat serious conditions and fill unmet medical needs. Were not abandoning the traditional ways that researchers and fda have been conducting trials. Rather, we want to build on and strengthen that hierarchy, we can use these new forms of evidence as the methodologies improve. And of course, increasingly, we are learning from the input of our patients. The fbi the fda has done a good job of increasing that input. Were also building new structures to encourage and support Multidisciplinary Research collaborations across the fda. A wellknown example is the Oncology Center of excellence at fda, which coordinates cancer activities from disparate parts of the agency to allows for faster and more efficient review of cancer applications, i think that is one of the more famous issues we have taken on, but we have similar initiatives related to Artificial Intelligence and advanced manufacturing. A key technical question to these problems is how to use Cloud Computing and storage at the agency. Weve jumped into Cloud Computing in a big way, already using this technology in innovative ways, allowing sponsors and reviewers to Exchange Messages and datasets in realtime. This is related to it infrastructure and data storage and usage at the fda, which provides some challenges for the agency. Im pleased to say that in just a few weeks well be announcing a new fda plan for modernizing fdas Technology Infrastructure that will allow us to use these data sets more efficiently so that we consider realworld evidence and data sets in a more fast i way across the agent. Agency. So, as you can see, the fda is committed to advancing new approaches for gathering data. This leads me to a final point today, the Critical Role fda plays at a nexus between leveraging data for Speedy Development of new products, while always ensuring the integrity of both the data and the process. Everyone here understands that we are being pushed to approve newer, better, safer, more effective medical products, and to do so more quickly. The key, of course, is to do so while maintaining fdas Gold Standard for safety and effectiveness. This requires striking a balance. And the balancing point must be the health and wellbeing of the patient. Unfortunately, finding this balance and explaining it to the public can at times be problematic. On one hand, its rare to find anyone who is searching for a new treatment for their disease complaining that fda is moving too fast. On the other hand, there are some who believe that faster approvals using some of the new expedited pathways must involve lower standards. I want to state that i do believe anything could be further from the truth. In this regard, we can have it both ways, both faster, more nimble approvals, while at the same time, preserving safety and efficacy for our patients. Possible ishis is in ours changed research. Take another example from cancer. When i started practicing, randomized, blinded placebo drug trials were the standard. Patients hated this, for obvious reasons. They didnt like to go to randomized trials, but we did it because we didnt have any credible alternatives. Over the years we learned a great deal about the biology of cancer and it subsets. In short, we developed a new paradigm. And we came to understand, we did not need placebo controls to make progress in many areas of Cancer Research, and just put out final guidance to that recently saying we would like to minimize use of placebo controls in trials. Places wherell its reasonable like supportive oncology, but it is rare for a therapeutic endpoint. We found we could make progress in cancer using other approaches. And this is good news for patients. No one with pancreatic cancer wants to get randomized to a sugar pill. Its also more efficient. Consider for example some pediatric cancers, there just arent enough patients to effectively use traditional randomized trials. So, we can use smaller trials, with innovative designs and weve seen some enormous successes in cancer using these approaches, with impressive progress in melanoma as i mentioned, but also lung cancer, breast cancer, pediatric leukemia, and many other cancers. The goal is to replicate this success in other disease areas. For example, neurodegen complex andch are not well understood. I brings me back to where i started, and where Research America comes in the critical importance of the need for more Biomedical Research yielding the best data. Agenciesritical to the work. And here let me dwell for a moment on what i mean by good as opposed to bad data. Every day theres new research that offers great promise. But some of this rapid desire for progress comes a risk, the potential for taking a shortcut with the fda, by collecting not good but bad data, and then submitting this bad data to us in support of a medical product. Data can be bad for a few reasons, but two important causes are sloppy, slipshod Data Collection or even data falsification. It can be difficult for the fda to tell these apart, because they differ in terms of intent, that is, if data are bad because of carelessness or because of fraud. In one sense, it doesnt matter that much to the agency. If we use bad data, we can make a decision that harms a patient. Let me specifically comment on the problem of data fraud. When i was in an editor on the journal of clinical investigation, that submission of false data could be a problem. Later, as director of nci, i saw some people mislead us in grant applications. It was at a degree that really surprised me and i had not expected. It is probably not surprising that if someone will use bad data or data manipulation to get their paper published or their grant funded, they will also consider doing that to get a billion dollar medical product approved. We simply cannot tolerate deception of any kind. Now, i do not wish to imply this is rampant. Rare cases. E are i also dont want to imply that its on the upswing. But we do see data fraud at fda, and more than i would have expected prior to coming to the agency. And i would argue that these instances are rare, they are significant because even a few examples can damage Public Confidence in the approval process. Todays modern, nimble, effective, fast fda that everybody requires requires that those who submit applications and data be truthful. That doesnt happen, the whole system breaks down. If someone comes to the fda with data that is inaccurate, or if they submit an application that contains a false claim, it undermines the search for a treatment or cure, violates the public trust, raises costs, exposes people to needless therapies, gives science a bad name, and most importantly, its bad for patients. At the fda, we dont have the resources to check every aspect of every bit of research. We do a lot of checks on data quality and they are vigorous, but at some level, we have to trust the sponsors. Thats how the system works. But we will be vigilant concerning the accuracy of the research we review. And when we do identify data fraud, we will use the full range of our authorities to address this, including civil and criminal penalties. I would argue that good data is we cant enforce our way out of this. It is the product of good culture and this is a place where Research America can clearly be of help by continuing your work to promote integrity to protect patients. Integrity is an area about which we all care deeply. I look forward to working more with this group on the future of this topic. Thank you for the invitation, and i look forward to working in this area more. [applause] cspans campaign 2020 coverage continues monday, when democratic president ial candidate senator Elizabeth Warren gives a speech in new york citys Washington Square park. We will have that live beginning at seven p. M. Eastern at 7 00 eastern. We will have live coverage as President Trump speaks at a Campaign Rally in new mexico. Watch both events live beginning at 7 00 p. M. Eastern on cspan, online at cspan. Org or listen live on these on the free cspan radio app. Campaign 2020. Watch live coverage and make up your own mind. Cspans campaign 2020, your unfiltered view of politics. On newsmakers, neil officer chief policy and executive Vice President of the u. S. Chamber of commerce. Being here. R we have janet with the New York Times and chris with associated press. Chris. Chris lets talk about trade. 40 of the fortune 500 has complained on earning calls and for