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Anantha P. Chandrakasan, Chair of J-Clinic, talks to Opening Doors about his hopes for the newest MIT\/Community Jameel partnership<\/strong><\/p>\nAnantha P. Chandrakasan, Dean of the <\/em>MIT School of Engineering<\/em><\/a> and the Vannevar Bush Professor of Electrical Engineering and Computer Science, is the recently appointed Chair of the Abdul Latif Jameel Clinic for Machine Learning in Health (<\/em>J-Clinic<\/em><\/a>). \u00a0Over the next few years, Anantha and the J-Clinic team will be pushing forward the boundaries of global healthcare research to deliver real-world impacts in disease prevention, diagnostics, and drug discovery and development.<\/em><\/p>\n \u00a0<\/em>Opening Doors spoke to Anantha about the latest partnership between MIT and <\/em>Community Jameel<\/em>, and how he plans to maximize its impact in the coming years.<\/em><\/p>\n Q: W<\/strong>hen you first heard about the proposals for J-Clinic, what was your initial reaction?<\/strong><\/p>\n AC: \u00a0I first discussed it with Mohammed Jameel<\/a> in September 2017. \u00a0Straightaway, I was excited by the opportunities of combining global healthcare with some of the leading-edge AI research at MIT to enable new ideas to emerge.<\/p>\n We already had people working on machine learning at MIT, and others on healthcare, and there was some work at the intersection of the two. \u00a0I saw J-Clinic as an opportunity to bring that intersection together and make a truly global impact with our work in this crucial field.<\/p>\n Q: How heavily involved was MIT in these fields before the creation of J-Clinic?<\/strong><\/p>\n AC: \u00a0We were already involved in research around AI and healthcare, linked to our proximity to Boston\u2019s world-leading healthcare cluster. \u00a0We have the Institute for Medical Engineering and Science (IMES) here at MIT, the Computer Science and Artificial Intelligence Laboratory (CSAIL<\/a>), and many more departments, centers and labs at MIT. \u00a0In fact, when we were defining our \u2018Quest for Intelligence\u2019<\/a> initiative, we found there were 200-plus principal investigators at MIT working on AI related topics, including healthcare-related research.<\/p>\n J-Clinic is a way to encourage collaboration between them all, because the innovation we\u2019re seeking is only going to happen if we bring together researchers working on machine learning and AI with those working on healthcare technologies.<\/p>\n We also need to foster close connections with the hospitals and with the industry players and innovators that can help to commercialize some of these ideas. \u00a0Collaboration and innovation have little value in isolation.\u00a0 There is a whole ecosystem that needs to come together to make sure innovation is translated into impact, and that\u2019s what makes J-Clinic so exciting.\u00a0 J-Clinic can be the catalyst for this new type of collaboration.<\/p>\n Q: What has been the current impact of AI in healthcare, and how much further is there to go?<\/strong><\/p>\n AC: \u00a0It\u2019s still in the very early stages.\u00a0 The idea of AI, and particularly machine learning, has recently re-emerged because of advances in image recognition technology, the exponential growth in the power of computing\/GPUs, and the availability of huge amounts of data.<\/p>\n Early breast cancer detection has been one of the successes so far \u2013 in fact, one of our faculty colleagues, Regina Barzilay, has done some pioneering work on the use of machine learning for breast cancer detection. \u00a0But overall, AI in healthcare is still a very new field.<\/p>\n <\/p>\n What really excites me about this whole area is the potential for these new technologies to have an impact far beyond big hospitals in big towns and cities. It could transform healthcare in a wide range of settings worldwide, including rural facilities and emerging markets.\u00a0<\/p>\n Q: Are we talking about a fundamental revolution in healthcare, or is it just a case of improving current practices?<\/strong><\/p>\n AC: \u00a0A bit of both. \u00a0Certainly, it will streamline and make much more personalized healthcare possible. \u00a0We will be able to track an individual\u2019s data, understand it in relation to the wider population, and customize treatments more individually. \u00a0That\u2019s a very exciting opportunity.<\/p>\n But ultimately, I\u2019d love to see this technology looking at the prevention of diseases. \u00a0These are the more futuristic opportunities. \u00a0Perhaps we\u2019ll be able to detect tumors even before radiologists can see them on a mammogram \u2013 that\u2019s the kind of ambition we\u2019re working towards. \u00a0The first achievement is likely to be detection, then better treatment, then personalized treatment, and finally disease prevention. \u00a0That\u2019s our ultimate goal.<\/p>\n Q: \u00a0Using AI and machine learning for disease prevention sounds like science fiction. \u00a0Is it realistic?<\/strong><\/p>\n AC: \u00a0Not for every disease, but I believe we can certainly make progress on several different fronts, enabled by the kind of unique collaboration that J-Clinic can provide.<\/p>\n One of the biggest challenges is around access to data, because today very little of the data that\u2019s collected is actually used. \u00a0There is bound to be hidden knowledge buried in that data, we just can\u2019t access it. \u00a0In time, I believe there will be advances that allow us to access a lot more of the data that\u2019s collected.<\/p>\n Q: \u00a0How quickly might we see some practical results from J-Clinic?<\/strong><\/p>\n AC: \u00a0It\u2019s hard to say. \u00a0There have been a lot of innovations recently, but there need to be many more to get to where we want to be. \u00a0So it will be a combination of both long term and short term results.\u00a0 This is reflected in the way J-Clinic is set up. \u00a0Some of the funding is going to target the long-term, more basic research that has a longer time horizon. Other funding will target solutions that are closer to commercialization and look at how we can help to accelerate these ideas from the lab to impact, working with MIT\u2019s Deshpande Center for Technological Innovation.<\/p>\n Q: \u00a0How did you decide on J-Clinic\u2019s three stated areas of focus \u2013 preventative medicine, diagnostic tests, and drug discovery and development?<\/strong><\/p>\n AC: \u00a0We looked to see where we could make the biggest impact. With diagnosis, for example, I\u2019m thrilled that J-Clinic will not just target the hospitals with the best facilities. \u00a0We want to do diagnosis in rural settings, like India, for example, where they may not have access to mammograms or there may not be a single doctor for an entire village. \u00a0The promise of bringing AI technology to healthcare environments that may not have the kind of resources enjoyed by the developed world is incredibly exciting.<\/p>\n In preventative and more personalized medicine, it\u2019s exciting to consider being able to target and create drugs for a particular person. \u00a0At the moment, it\u2019s a completely open playing field. \u00a0And we can also use machine learning to guide the process of drug discovery, creating drugs that target very specifically-defined groups of people.<\/p>\n Q: \u00a0What are your ambitions for J-Clinic over the next five or 10 years?<\/strong><\/p>\n AC: \u00a0In the short term, we\u2019ll look to develop new algorithms and have an immediate impact with some of our ongoing work on detection, diagnosis, and drug discovery.\u00a0 I\u2019d like to explore how we can make partnerships with both hospitals and industry, particularly with regards to deploying our ideas, and we also want to spin out our research and create start-ups to help drive the next generation of healthcare innovation.<\/p>\n As a personal goal, I\u2019d like to take this technology to all parts of the world. \u00a0Our researchers love to solve these kinds of problems, and I\u2019m very keen to encourage them to find the solutions needed to move this technology forward worldwide.<\/p>\n Set against those ambitions, though, is the reality that getting access to data will be our biggest challenge. \u00a0It is something we will have to solve. \u00a0The better access to data we have, the better our prediction and treatment approaches are going to be.<\/p>\n Finally, some of our research has to be focused on the ethical use of these technologies. \u00a0Those questions are not scientific, but they are equally important if we want to successfully deploy our research.<\/p>\n Q: \u00a0Could AI and machine learning close the gaps between the quality of healthcare people can access in different parts of the world?<\/strong><\/p>\n AC: \u00a0Yes, I believe so. \u00a0That\u2019s a big part of it. \u00a0You can certainly envisage a situation where machine learning acts as the first step in deciding who, in a rural community, should go to a bigger hospital in the nearby town, for example. \u00a0But there is a lot to do before that. \u00a0What new kinds of devices will we need to take these new systems out into the real world? \u00a0What innovations and algorithms will we need to develop to make best use of the data we have? \u00a0And can we work with governments to subsidize some of the equipment healthcare workers will need?<\/p>\n <\/p>\n Q: \u00a0How pleased are you with the strength of J-Clinic\u2019s leadership team?<\/strong><\/p>\n AC: \u00a0I\u2019m thrilled. \u00a0Having two MacArthur fellows as the co-leads, covering machine learning and health from different perspectives, is something to be very excited about. \u00a0\u00a0Professor James J. Collins<\/a> is the leader of synthetic biology, and Professor Regina Barizlay<\/a>, is the leader of machine learning for health.\u00a0 Then there\u2019s Institute Professor Phillip A. Sharp<\/a>, a Nobel laureate who has advanced basic science and brought his innovations into the commercial world, giving us expertise in research and entrepreneurship. \u00a0All these people are experts in their field, and all of them also have extensive experience working with the healthcare industry itself. \u00a0\u00a0<\/p>\n Q: \u00a0Finally, J-Clinic is the fourth MIT collaboration with Community Jameel. How important has the MIT\/Community Jameel partnership been over the last few years?<\/strong><\/p>\n AC: \u00a0It\u2019s been absolutely instrumental. \u00a0Our students want to make an impact on the world. \u00a0So when you look at the Poverty Action Lab (J-PAL<\/a>), the Water and Food Systems Lab (J-WAFS<\/a>) and the World Education Lab (J-WEL<\/a>), these are the kinds of deep and important problems our students want to address through their research. \u00a0J-Clinic<\/a> fits perfectly into this environment.<\/p>\n These programs have been absolutely game-changing.\u00a0 I\u2019m particularly excited about the opportunity for the programs to interconnect and amplify each other\u2019s impact over the coming years. \u00a0It\u2019s a great opportunity for J-Clinic. \u00a0We hope to partner with the other J-Labs in very specific ways in both the short and long term.<\/p>\n The partnership with Community Jameel has provided us with much-needed resources to facilitate this valuable work. \u00a0But more importantly, it\u2019s enabled us to develop a research framework in which our students thrive, creating connectivity that can help to make a practical, real-world impact.<\/p>\n![\"\"](\"https:\/\/media.alj.com\/app\/uploads\/2019\/01\/Chasing-cancer.jpg\")
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