WEBVTT 00:00:00.368 --> 00:00:02.505 We have a global health challenge 00:00:02.505 --> 00:00:04.197 in our hands today, 00:00:04.197 --> 00:00:07.257 and that is that the way we currently 00:00:07.257 --> 00:00:10.182 discover and develop new drugs 00:00:10.182 --> 00:00:14.360 is too costly, takes far too long, 00:00:14.360 --> 00:00:18.074 and it fails more often than it succeeds. 00:00:18.074 --> 00:00:21.451 It really just isn't working, and that means 00:00:21.451 --> 00:00:24.498 that patients that badly need new therapies 00:00:24.498 --> 00:00:26.209 are not getting them, 00:00:26.209 --> 00:00:29.707 and diseases are going untreated. 00:00:29.707 --> 00:00:32.790 We seem to be spending more and more money. 00:00:32.790 --> 00:00:36.886 So for every billion dollars we spend in R&D, 00:00:36.886 --> 00:00:40.715 we're getting less drugs approved into the market. 00:00:40.715 --> 00:00:43.932 More money, less drugs. Hmm. NOTE Paragraph 00:00:43.932 --> 00:00:45.852 So what's going on here? 00:00:45.852 --> 00:00:48.447 Well, there's a multitude of factors at play, 00:00:48.447 --> 00:00:50.468 but I think one of the key factors 00:00:50.468 --> 00:00:52.865 is that the tools that we currently have 00:00:52.865 --> 00:00:56.948 available to test whether a drug is going to work, 00:00:56.948 --> 00:00:58.337 whether it has efficacy, 00:00:58.337 --> 00:01:00.103 or whether it's going to be safe 00:01:00.103 --> 00:01:03.655 before we get it into human clinical trials, 00:01:03.655 --> 00:01:05.806 are failing us. They're not predicting 00:01:05.806 --> 00:01:09.034 what's going to happen in humans. 00:01:09.034 --> 00:01:11.757 And we have two main tools available 00:01:11.757 --> 00:01:13.771 at our disposal. 00:01:13.771 --> 00:01:17.812 They are cells in dishes and animal testing. NOTE Paragraph 00:01:17.812 --> 00:01:21.132 Now let's talk about the first one, cells in dishes. 00:01:21.132 --> 00:01:24.285 So, cells are happily functioning in our bodies. 00:01:24.285 --> 00:01:26.340 We take them and rip them out 00:01:26.340 --> 00:01:29.289 of their native environment, throw them in one of these dishes, 00:01:29.289 --> 00:01:30.874 and expect them to work. 00:01:30.874 --> 00:01:33.067 Guess what. They don't. 00:01:33.067 --> 00:01:34.729 They don't like that environment 00:01:34.729 --> 00:01:36.361 because it's nothing like 00:01:36.361 --> 00:01:39.037 what they have in the body. NOTE Paragraph 00:01:39.037 --> 00:01:41.108 What about animal testing? 00:01:41.108 --> 00:01:43.993 Well, animals do and can provide 00:01:43.993 --> 00:01:46.255 extremely useful information. 00:01:46.255 --> 00:01:47.964 They teach us about what happens 00:01:47.964 --> 00:01:50.293 in the complex organism. 00:01:50.293 --> 00:01:53.301 We learn more about the biology itself. 00:01:53.301 --> 00:01:56.199 However, more often than not, 00:01:56.199 --> 00:02:00.415 animal models fail to predict what will happen in humans 00:02:00.415 --> 00:02:03.601 when they're treated with a particular drug. NOTE Paragraph 00:02:03.601 --> 00:02:05.980 So we need better tools. 00:02:05.980 --> 00:02:07.733 We need human cells, 00:02:07.733 --> 00:02:10.483 but we need to find a way to keep them happy 00:02:10.483 --> 00:02:12.074 outside the body. NOTE Paragraph 00:02:12.074 --> 00:02:14.980 Our bodies are dynamic environments. 00:02:14.980 --> 00:02:16.820 We're in constant motion. 00:02:16.820 --> 00:02:19.011 Our cells experience that. 00:02:19.011 --> 00:02:21.820 They're in dynamic environments in our body. 00:02:21.820 --> 00:02:24.575 They're under constant mechanical forces. 00:02:24.575 --> 00:02:27.031 So if we want to make cells happy 00:02:27.031 --> 00:02:28.460 outside our bodies, 00:02:28.460 --> 00:02:30.986 we need to become cell architects. 00:02:30.986 --> 00:02:35.330 We need to design, build and engineer 00:02:35.330 --> 00:02:38.561 a home away from home for the cells. NOTE Paragraph 00:02:38.561 --> 00:02:40.235 And at the Wyss Institute, 00:02:40.235 --> 00:02:42.173 we've done just that. 00:02:42.173 --> 00:02:45.197 We call it an organ-on-a-chip. 00:02:45.197 --> 00:02:46.988 And I have one right here. 00:02:46.988 --> 00:02:49.803 It's beautiful, isn't it? But it's pretty incredible. 00:02:49.803 --> 00:02:54.303 Right here in my hand is a breathing, living 00:02:54.303 --> 00:02:56.961 human lung on a chip. NOTE Paragraph 00:02:56.961 --> 00:02:59.089 And it's not just beautiful. 00:02:59.089 --> 00:03:01.529 It can do a tremendous amount of things. 00:03:01.529 --> 00:03:05.308 We have living cells in that little chip, 00:03:05.308 --> 00:03:07.858 cells that are in a dynamic environment 00:03:07.858 --> 00:03:10.939 interacting with different cell types. 00:03:10.939 --> 00:03:12.578 There's been many people 00:03:12.578 --> 00:03:14.439 trying to grow cells in the lab. 00:03:14.439 --> 00:03:17.595 They've tried many different approaches. 00:03:17.595 --> 00:03:20.222 They've even tried to grow little mini-organs in the lab. 00:03:20.222 --> 00:03:21.771 We're not trying to do that here. 00:03:21.771 --> 00:03:23.897 We're simply trying to recreate 00:03:23.897 --> 00:03:25.474 in this tiny chip 00:03:25.474 --> 00:03:28.491 the smallest functional unit 00:03:28.491 --> 00:03:31.045 that represents the biochemistry, 00:03:31.045 --> 00:03:34.169 the function and the mechanical strain 00:03:34.169 --> 00:03:37.685 that the cells experience in our bodies. 00:03:37.685 --> 00:03:40.717 So how does it work? Let me show you. 00:03:40.717 --> 00:03:43.351 We use techniques from the computer chip 00:03:43.351 --> 00:03:44.984 manufacturing industry 00:03:44.984 --> 00:03:47.181 to make these structures at a scale 00:03:47.181 --> 00:03:50.077 relevant to both the cells and their environment. 00:03:50.077 --> 00:03:52.141 We have three fluidic channels. 00:03:52.141 --> 00:03:55.853 In the center, we have a porous, flexible membrane 00:03:55.853 --> 00:03:57.916 on which we can add human cells 00:03:57.916 --> 00:03:59.260 from, say, our lungs, 00:03:59.260 --> 00:04:01.747 and then underneath, they had capillary cells, 00:04:01.747 --> 00:04:03.535 the cells in our blood vessels. 00:04:03.535 --> 00:04:07.855 And we can then apply mechanical forces to the chip 00:04:07.855 --> 00:04:10.684 that stretch and contract the membrane, 00:04:10.684 --> 00:04:13.781 so the cells experience the same mechanical forces 00:04:13.781 --> 00:04:16.714 that they did when we breathe. 00:04:16.714 --> 00:04:19.874 And they experience them how they did in the body. 00:04:19.874 --> 00:04:22.274 There's air flowing through the top channel, 00:04:22.274 --> 00:04:25.623 and then we flow a liquid that contains nutrients 00:04:25.623 --> 00:04:28.462 through the blood channel. 00:04:28.462 --> 00:04:30.834 Now the chip is really beautiful, 00:04:30.834 --> 00:04:32.931 but what can we do with it? 00:04:32.931 --> 00:04:35.255 We can get incredible functionality 00:04:35.255 --> 00:04:37.006 inside these little chips. 00:04:37.006 --> 00:04:38.512 Let me show you. 00:04:38.512 --> 00:04:41.143 We could, for example, mimic infection, 00:04:41.143 --> 00:04:44.679 where we add bacterial cells into the lung. 00:04:44.679 --> 00:04:47.611 then we can add human white blood cells. 00:04:47.611 --> 00:04:50.202 White blood cells are our body's defense 00:04:50.202 --> 00:04:51.570 against bacterial invaders, 00:04:51.570 --> 00:04:54.739 and when they sense this inflammation due to infection, 00:04:54.739 --> 00:04:57.596 they will enter from the blood into the lung 00:04:57.596 --> 00:04:59.511 and engulf the bacteria. 00:04:59.511 --> 00:05:01.759 Well now you're going to see this happening 00:05:01.759 --> 00:05:05.069 live in an actual human lung on a chip. 00:05:05.069 --> 00:05:08.612 We've labeled the white blood cells so you can see them flowing through, 00:05:08.612 --> 00:05:10.773 and when they detect that infection, 00:05:10.773 --> 00:05:12.170 they begin to stick. 00:05:12.170 --> 00:05:16.057 They stick, and then they try to go into the lung 00:05:16.057 --> 00:05:17.838 side from blood channel. 00:05:17.838 --> 00:05:21.527 And you can see here, we can actually visualize 00:05:21.527 --> 00:05:25.286 a single white blood cell. 00:05:25.286 --> 00:05:27.542 It sticks, it wiggles its way through 00:05:27.542 --> 00:05:29.857 between the cell layers, through the pore, 00:05:29.857 --> 00:05:32.278 comes out on the other side of the membrane, 00:05:32.278 --> 00:05:35.713 and right there, it's going to engulf the bacteria 00:05:35.713 --> 00:05:37.362 labeled in green. 00:05:37.362 --> 00:05:40.366 In that tiny chip, you just witnessed 00:05:40.366 --> 00:05:43.547 one of the most fundamental responses 00:05:43.547 --> 00:05:45.504 our body has to an infection. 00:05:45.504 --> 00:05:49.274 It's the way we respond to -- an immune response. 00:05:49.274 --> 00:05:51.675 It's pretty exciting. NOTE Paragraph 00:05:51.675 --> 00:05:54.018 Now I want to share this picture with you, 00:05:54.018 --> 00:05:56.656 not just because it's so beautiful, 00:05:56.656 --> 00:05:59.992 but because it tells us an enormous amount of information 00:05:59.992 --> 00:06:02.589 about what the cells are doing within the chips. 00:06:02.589 --> 00:06:04.848 It tells us that these cells 00:06:04.848 --> 00:06:07.159 from the small airways in our lungs, 00:06:07.159 --> 00:06:08.910 actually have these hairlike structures 00:06:08.910 --> 00:06:10.918 that you would expect to see in the lung. 00:06:10.918 --> 00:06:12.383 These structures are called cilia, 00:06:12.383 --> 00:06:15.293 and they actually move the mucus out of the lung. 00:06:15.293 --> 00:06:16.832 Yeah. Mucus. Yuck. 00:06:16.832 --> 00:06:19.272 But mucus is actually very important. 00:06:19.272 --> 00:06:21.853 Mucus traps particulates, viruses, 00:06:21.853 --> 00:06:23.312 potential allergens, 00:06:23.312 --> 00:06:24.913 and these little cilia move 00:06:24.913 --> 00:06:27.163 and clear the mucus out. 00:06:27.163 --> 00:06:29.075 When they get damaged, say, 00:06:29.075 --> 00:06:31.494 by cigarette smoke for example, 00:06:31.494 --> 00:06:34.302 they don't work properly, and they can't clear that mucus out. 00:06:34.302 --> 00:06:38.119 And that can lead to diseases such as bronchitis. 00:06:38.119 --> 00:06:40.766 Cilia and the clearance of mucus 00:06:40.766 --> 00:06:45.227 are also involved in awful diseases like cystic fibrosis. 00:06:45.227 --> 00:06:48.777 But now, with the functionality that we get in these chips, 00:06:48.777 --> 00:06:50.601 we can begin to look 00:06:50.601 --> 00:06:53.114 for potential new treatments. NOTE Paragraph 00:06:53.114 --> 00:06:55.066 We didn't stop with the lung on a chip. 00:06:55.066 --> 00:06:56.950 We have a gut on a chip. 00:06:56.950 --> 00:06:58.980 You can see one right here. 00:06:58.980 --> 00:07:02.206 And we've put intestinal human cells 00:07:02.206 --> 00:07:04.111 in a gut on a chip, 00:07:04.111 --> 00:07:06.948 and they're under constant peristaltic motion, 00:07:06.948 --> 00:07:10.139 this trickling flow through the cells, 00:07:10.139 --> 00:07:12.697 and we can mimic many of the functions 00:07:12.697 --> 00:07:14.960 that you actually would expect to see 00:07:14.960 --> 00:07:16.653 in the human intestine. 00:07:16.653 --> 00:07:20.444 Now we can begin to create models of diseases 00:07:20.444 --> 00:07:22.854 such as irritable bowel syndrome. 00:07:22.854 --> 00:07:24.936 This is a disease that affects 00:07:24.936 --> 00:07:26.847 a large number of individuals. 00:07:26.847 --> 00:07:28.621 It's really debilitating, 00:07:28.621 --> 00:07:32.563 and there aren't really many good treatments for it. NOTE Paragraph 00:07:32.563 --> 00:07:34.865 Now we have a whole pipeline 00:07:34.865 --> 00:07:37.144 of different organ chips 00:07:37.144 --> 00:07:40.876 that we are currently working on in our labs. 00:07:40.876 --> 00:07:44.295 Now, the true power of this technology, however, 00:07:44.295 --> 00:07:46.420 really comes from the fact 00:07:46.420 --> 00:07:48.965 that we can fluidically link them. 00:07:48.965 --> 00:07:50.912 There's fluid flowing across these cells, 00:07:50.912 --> 00:07:52.991 so we can begin to interconnect 00:07:52.991 --> 00:07:55.853 multiple different chips together 00:07:55.853 --> 00:08:00.066 to form what we call a virtual human on a chip. 00:08:00.066 --> 00:08:03.075 Now we're really getting excited. 00:08:03.075 --> 00:08:07.170 We're not going to ever recreate a whole human in these chips, 00:08:07.170 --> 00:08:11.339 but what our goal is is to be able to recreate 00:08:11.339 --> 00:08:13.352 sufficient functionality 00:08:13.352 --> 00:08:15.712 so that we can make better predictions 00:08:15.712 --> 00:08:17.926 of what's going to happen in humans. 00:08:17.926 --> 00:08:20.850 For example, now we can begin to explore 00:08:20.850 --> 00:08:24.284 what happens when we put a drug like an aerosol drug. 00:08:24.284 --> 00:08:27.270 Those of you like me who have asthma, when you take your inhaler, 00:08:27.270 --> 00:08:30.196 we can explore how that drug comes into your lungs, 00:08:30.196 --> 00:08:31.822 how it enters the body, 00:08:31.822 --> 00:08:33.576 how it might affect, say, your heart. 00:08:33.576 --> 00:08:35.484 Does it change the beating of your heart? 00:08:35.484 --> 00:08:37.125 Does it have a toxicity? 00:08:37.125 --> 00:08:39.133 Does it get cleared by the liver? 00:08:39.133 --> 00:08:41.285 Is it metabolized in the liver? 00:08:41.285 --> 00:08:43.176 Is it excreted in your kidneys? 00:08:43.176 --> 00:08:45.388 We can begin to study the dynamic 00:08:45.388 --> 00:08:48.013 response of the body to a drug. NOTE Paragraph 00:08:48.028 --> 00:08:49.947 This could really revolutionize 00:08:49.947 --> 00:08:51.596 and be a game changer 00:08:51.596 --> 00:08:54.534 for not only the pharmaceutical industry, 00:08:54.534 --> 00:08:56.907 but a whole host of different industries, 00:08:56.907 --> 00:08:59.307 including the cosmetics industry. 00:08:59.307 --> 00:09:02.189 We can potentially use the skin on a chip 00:09:02.189 --> 00:09:04.150 that we're currently developing in the lab 00:09:04.150 --> 00:09:06.704 to test whether the ingredients in those products 00:09:06.704 --> 00:09:09.987 that you're using are actually safe to put on your skin 00:09:09.987 --> 00:09:12.676 without the need for animal testing. 00:09:12.676 --> 00:09:14.620 We could test the safety 00:09:14.620 --> 00:09:16.873 of chemicals that we are exposed to 00:09:16.873 --> 00:09:18.787 on a daily basis in our environment, 00:09:18.787 --> 00:09:22.518 such as chemicals in regular household cleaners. 00:09:22.518 --> 00:09:25.720 We could also use the organs on chips 00:09:25.720 --> 00:09:28.499 for applications in bioterrorism 00:09:28.499 --> 00:09:31.070 or radiation exposure. 00:09:31.070 --> 00:09:34.420 We could use them to learn more about 00:09:34.420 --> 00:09:37.464 diseases such as ebola 00:09:37.464 --> 00:09:41.356 or other deadly diseases such as SARS. NOTE Paragraph 00:09:41.356 --> 00:09:43.194 Organs on chips could also change 00:09:43.194 --> 00:09:46.568 the way we do clinical trials in the future. 00:09:46.568 --> 00:09:49.155 Right now, the average participant 00:09:49.155 --> 00:09:52.525 in a clinical trial is that: average. 00:09:52.525 --> 00:09:55.851 Tends to be middle aged, tends to be female. 00:09:55.851 --> 00:09:58.323 You won't find many clinical trials 00:09:58.323 --> 00:09:59.838 in which children are involved, 00:09:59.838 --> 00:10:03.385 yet every day, we give children medications, 00:10:03.385 --> 00:10:07.131 and the only safety data we have on that drug 00:10:07.131 --> 00:10:10.205 is one that we obtained from adults. 00:10:10.205 --> 00:10:11.999 Children are not adults. 00:10:11.999 --> 00:10:15.132 They may not respond in the same way adults do. 00:10:15.132 --> 00:10:17.544 There are other things like genetic differences 00:10:17.544 --> 00:10:18.977 in populations 00:10:18.977 --> 00:10:22.083 that may lead to at-risk populations 00:10:22.083 --> 00:10:25.520 that are at risk of having an adverse drug reaction. 00:10:25.520 --> 00:10:28.909 Now imagine if we could take cells from all those different populations, 00:10:28.919 --> 00:10:30.827 put them on chips, 00:10:30.827 --> 00:10:32.791 and create populations on a chip. 00:10:32.791 --> 00:10:34.629 This could really change the way 00:10:34.629 --> 00:10:36.698 we do clinical trials. 00:10:36.698 --> 00:10:39.530 And this is the team and the people that are doing this. 00:10:39.530 --> 00:10:42.787 We have engineers, we have cell biologists, 00:10:42.787 --> 00:10:46.561 we have clinicians, all working together. 00:10:46.561 --> 00:10:48.487 We're really seeing something quite incredible 00:10:48.487 --> 00:10:50.092 at the Wyss Institute. 00:10:50.092 --> 00:10:52.263 It's really a convergence of disciplines, 00:10:52.263 --> 00:10:55.983 where biology is influencing the way we design, 00:10:55.983 --> 00:10:58.645 the way we engineer, the way we build. 00:10:58.645 --> 00:11:00.048 It's pretty exciting. NOTE Paragraph 00:11:00.048 --> 00:11:03.612 We're establishing important industry collaborations 00:11:03.612 --> 00:11:06.985 such as the one we have with a company 00:11:06.985 --> 00:11:10.584 that has expertise in large-scale digital manufacturing. 00:11:10.584 --> 00:11:12.603 They're going to help us make, 00:11:12.603 --> 00:11:14.129 instead of one of these, 00:11:14.129 --> 00:11:15.712 millions of these chips, 00:11:15.712 --> 00:11:17.381 so that we can get them into the hands 00:11:17.381 --> 00:11:20.270 of as many researchers as possible. 00:11:20.270 --> 00:11:24.486 And this is key to the potential of that technology. NOTE Paragraph 00:11:24.486 --> 00:11:27.023 Now let me show you our instrument. 00:11:27.023 --> 00:11:29.012 This is an instrument that our engineers 00:11:29.012 --> 00:11:31.630 are actually prototyping right now in the lab, 00:11:31.630 --> 00:11:33.939 and this instrument is going to give us 00:11:33.939 --> 00:11:36.398 the engineering controls that we're going to require 00:11:36.398 --> 00:11:40.566 in order to link 10 or more organ chips together. 00:11:40.566 --> 00:11:42.795 It does something else that's very important. 00:11:42.795 --> 00:11:45.639 It creates an easy user interface. 00:11:45.639 --> 00:11:48.629 So a cell biologist like me can come in, 00:11:48.629 --> 00:11:50.637 take a chip, put it in a cartridge 00:11:50.637 --> 00:11:52.569 like the prototype you see there, 00:11:52.569 --> 00:11:54.640 put the cartridge into the machine 00:11:54.640 --> 00:11:56.128 just like you would a C.D., 00:11:56.128 --> 00:11:57.260 and away you go. 00:11:57.260 --> 00:12:00.009 Plug and play. Easy. NOTE Paragraph 00:12:00.009 --> 00:12:02.523 Now, let's imagine a little bit 00:12:02.523 --> 00:12:03.902 what the future might look like 00:12:03.902 --> 00:12:06.315 if I could take your stem cells 00:12:06.315 --> 00:12:07.755 and put them on a chip, 00:12:07.755 --> 00:12:10.974 or your stem cells and put them on a chip. 00:12:10.974 --> 00:12:14.475 It would be a personalized chip just for you. NOTE Paragraph 00:12:14.475 --> 00:12:17.683 Now all of us in here are individuals, 00:12:17.683 --> 00:12:20.521 and those individual differences mean 00:12:20.521 --> 00:12:22.963 that we could react very differently 00:12:22.963 --> 00:12:27.210 and sometimes in unpredictable ways to drugs. 00:12:27.210 --> 00:12:31.778 I myself, a couple of years back, had a really bad headache, 00:12:31.778 --> 00:12:34.191 just couldn't shake it, thought, "Well, I'll try something different." 00:12:34.191 --> 00:12:36.326 I took some Advil. Fifteen minutes later, 00:12:36.326 --> 00:12:38.206 I was on my way to the emergency room 00:12:38.206 --> 00:12:40.099 with a full-blown asthma attack. 00:12:40.099 --> 00:12:41.929 Now, obviously it wasn't fatal, 00:12:41.929 --> 00:12:45.102 but unfortunately, some of these 00:12:45.102 --> 00:12:48.711 adverse drug reactions can be fatal. NOTE Paragraph 00:12:48.711 --> 00:12:50.652 So how do we prevent them? 00:12:50.652 --> 00:12:53.232 Well, we could imagine one day 00:12:53.232 --> 00:12:55.575 having Geraldine on a chip, 00:12:55.575 --> 00:12:57.324 having Danielle on a chip, 00:12:57.324 --> 00:12:58.797 having you on a chip. NOTE Paragraph 00:12:58.797 --> 00:13:01.185 Personalized medicine. Thank you. NOTE Paragraph 00:13:01.185 --> 00:13:05.339 (Applause)