1 00:00:00,368 --> 00:00:02,505 We have a global health challenge 2 00:00:02,505 --> 00:00:04,197 in our hands today, 3 00:00:04,197 --> 00:00:07,257 and that is that the way we currently 4 00:00:07,257 --> 00:00:10,182 discover and develop new drugs 5 00:00:10,182 --> 00:00:14,360 is too costly, takes far too long, 6 00:00:14,360 --> 00:00:18,074 and it fails more often than it succeeds. 7 00:00:18,074 --> 00:00:21,451 It really just isn't working, and that means 8 00:00:21,451 --> 00:00:24,498 that patients that badly need new therapies 9 00:00:24,498 --> 00:00:26,209 are not getting them, 10 00:00:26,209 --> 00:00:29,707 and diseases are going untreated. 11 00:00:29,707 --> 00:00:32,790 We seem to be spending more and more money. 12 00:00:32,790 --> 00:00:36,886 So for every billion dollars we spend in R&D, 13 00:00:36,886 --> 00:00:40,715 we're getting less drugs approved into the market. 14 00:00:40,715 --> 00:00:43,932 More money, less drugs. Hmm. 15 00:00:43,932 --> 00:00:45,852 So what's going on here? 16 00:00:45,852 --> 00:00:48,447 Well, there's a multitude of factors at play, 17 00:00:48,447 --> 00:00:50,468 but I think one of the key factors 18 00:00:50,468 --> 00:00:52,865 is that the tools that we currently have 19 00:00:52,865 --> 00:00:56,948 available to test whether a drug is going to work, 20 00:00:56,948 --> 00:00:58,337 whether it has efficacy, 21 00:00:58,337 --> 00:01:00,103 or whether it's going to be safe 22 00:01:00,103 --> 00:01:03,655 before we get it into human clinical trials, 23 00:01:03,655 --> 00:01:05,806 are failing us. They're not predicting 24 00:01:05,806 --> 00:01:09,034 what's going to happen in humans. 25 00:01:09,034 --> 00:01:11,757 And we have two main tools available 26 00:01:11,757 --> 00:01:13,771 at our disposal. 27 00:01:13,771 --> 00:01:17,812 They are cells in dishes and animal testing. 28 00:01:17,812 --> 00:01:21,132 Now let's talk about the first one, cells in dishes. 29 00:01:21,132 --> 00:01:24,285 So, cells are happily functioning in our bodies. 30 00:01:24,285 --> 00:01:26,340 We take them and rip them out 31 00:01:26,340 --> 00:01:29,289 of their native environment, throw them in one of these dishes, 32 00:01:29,289 --> 00:01:30,874 and expect them to work. 33 00:01:30,874 --> 00:01:33,067 Guess what. They don't. 34 00:01:33,067 --> 00:01:34,729 They don't like that environment 35 00:01:34,729 --> 00:01:36,361 because it's nothing like 36 00:01:36,361 --> 00:01:39,037 what they have in the body. 37 00:01:39,037 --> 00:01:41,108 What about animal testing? 38 00:01:41,108 --> 00:01:43,993 Well, animals do and can provide 39 00:01:43,993 --> 00:01:46,255 extremely useful information. 40 00:01:46,255 --> 00:01:47,964 They teach us about what happens 41 00:01:47,964 --> 00:01:50,293 in the complex organism. 42 00:01:50,293 --> 00:01:53,301 We learn more about the biology itself. 43 00:01:53,301 --> 00:01:56,199 However, more often than not, 44 00:01:56,199 --> 00:02:00,415 animal models fail to predict what will happen in humans 45 00:02:00,415 --> 00:02:03,601 when they're treated with a particular drug. 46 00:02:03,601 --> 00:02:05,980 So we need better tools. 47 00:02:05,980 --> 00:02:07,733 We need human cells, 48 00:02:07,733 --> 00:02:10,483 but we need to find a way to keep them happy 49 00:02:10,483 --> 00:02:12,074 outside the body. 50 00:02:12,074 --> 00:02:14,980 Our bodies are dynamic environments. 51 00:02:14,980 --> 00:02:16,820 We're in constant motion. 52 00:02:16,820 --> 00:02:19,011 Our cells experience that. 53 00:02:19,011 --> 00:02:21,820 They're in dynamic environments in our body. 54 00:02:21,820 --> 00:02:24,575 They're under constant mechanical forces. 55 00:02:24,575 --> 00:02:27,031 So if we want to make cells happy 56 00:02:27,031 --> 00:02:28,460 outside our bodies, 57 00:02:28,460 --> 00:02:30,986 we need to become cell architects. 58 00:02:30,986 --> 00:02:35,330 We need to design, build and engineer 59 00:02:35,330 --> 00:02:38,561 a home away from home for the cells. 60 00:02:38,561 --> 00:02:40,235 And at the Wyss Institute, 61 00:02:40,235 --> 00:02:42,173 we've done just that. 62 00:02:42,173 --> 00:02:45,197 We call it an organ-on-a-chip. 63 00:02:45,197 --> 00:02:46,988 And I have one right here. 64 00:02:46,988 --> 00:02:49,803 It's beautiful, isn't it? But it's pretty incredible. 65 00:02:49,803 --> 00:02:54,303 Right here in my hand is a breathing, living 66 00:02:54,303 --> 00:02:56,961 human lung on a chip. 67 00:02:56,961 --> 00:02:59,089 And it's not just beautiful. 68 00:02:59,089 --> 00:03:01,529 It can do a tremendous amount of things. 69 00:03:01,529 --> 00:03:05,308 We have living cells in that little chip, 70 00:03:05,308 --> 00:03:07,858 cells that are in a dynamic environment 71 00:03:07,858 --> 00:03:10,939 interacting with different cell types. 72 00:03:10,939 --> 00:03:12,578 There's been many people 73 00:03:12,578 --> 00:03:14,439 trying to grow cells in the lab. 74 00:03:14,439 --> 00:03:17,595 They've tried many different approaches. 75 00:03:17,595 --> 00:03:20,222 They've even tried to grow little mini-organs in the lab. 76 00:03:20,222 --> 00:03:21,771 We're not trying to do that here. 77 00:03:21,771 --> 00:03:23,897 We're simply trying to recreate 78 00:03:23,897 --> 00:03:25,474 in this tiny chip 79 00:03:25,474 --> 00:03:28,491 the smallest functional unit 80 00:03:28,491 --> 00:03:31,045 that represents the biochemistry, 81 00:03:31,045 --> 00:03:34,169 the function and the mechanical strain 82 00:03:34,169 --> 00:03:37,685 that the cells experience in our bodies. 83 00:03:37,685 --> 00:03:40,717 So how does it work? Let me show you. 84 00:03:40,717 --> 00:03:43,351 We use techniques from the computer chip 85 00:03:43,351 --> 00:03:44,984 manufacturing industry 86 00:03:44,984 --> 00:03:47,181 to make these structures at a scale 87 00:03:47,181 --> 00:03:50,077 relevant to both the cells and their environment. 88 00:03:50,077 --> 00:03:52,141 We have three fluidic channels. 89 00:03:52,141 --> 00:03:55,853 In the center, we have a porous, flexible membrane 90 00:03:55,853 --> 00:03:57,916 on which we can add human cells 91 00:03:57,916 --> 00:03:59,260 from, say, our lungs, 92 00:03:59,260 --> 00:04:01,747 and then underneath, they had capillary cells, 93 00:04:01,747 --> 00:04:03,535 the cells in our blood vessels. 94 00:04:03,535 --> 00:04:07,855 And we can then apply mechanical forces to the chip 95 00:04:07,855 --> 00:04:10,684 that stretch and contract the membrane, 96 00:04:10,684 --> 00:04:13,781 so the cells experience the same mechanical forces 97 00:04:13,781 --> 00:04:16,714 that they did when we breathe. 98 00:04:16,714 --> 00:04:19,874 And they experience them how they did in the body. 99 00:04:19,874 --> 00:04:22,274 There's air flowing through the top channel, 100 00:04:22,274 --> 00:04:25,623 and then we flow a liquid that contains nutrients 101 00:04:25,623 --> 00:04:28,462 through the blood channel. 102 00:04:28,462 --> 00:04:30,834 Now the chip is really beautiful, 103 00:04:30,834 --> 00:04:32,931 but what can we do with it? 104 00:04:32,931 --> 00:04:35,255 We can get incredible functionality 105 00:04:35,255 --> 00:04:37,006 inside these little chips. 106 00:04:37,006 --> 00:04:38,512 Let me show you. 107 00:04:38,512 --> 00:04:41,143 We could, for example, mimic infection, 108 00:04:41,143 --> 00:04:44,679 where we add bacterial cells into the lung. 109 00:04:44,679 --> 00:04:47,611 then we can add human white blood cells. 110 00:04:47,611 --> 00:04:50,202 White blood cells are our body's defense 111 00:04:50,202 --> 00:04:51,570 against bacterial invaders, 112 00:04:51,570 --> 00:04:54,739 and when they sense this inflammation due to infection, 113 00:04:54,739 --> 00:04:57,596 they will enter from the blood into the lung 114 00:04:57,596 --> 00:04:59,511 and engulf the bacteria. 115 00:04:59,511 --> 00:05:01,759 Well now you're going to see this happening 116 00:05:01,759 --> 00:05:05,069 live in an actual human lung on a chip. 117 00:05:05,069 --> 00:05:08,612 We've labeled the white blood cells so you can see them flowing through, 118 00:05:08,612 --> 00:05:10,773 and when they detect that infection, 119 00:05:10,773 --> 00:05:12,170 they begin to stick. 120 00:05:12,170 --> 00:05:16,057 They stick, and then they try to go into the lung 121 00:05:16,057 --> 00:05:17,838 side from blood channel. 122 00:05:17,838 --> 00:05:21,527 And you can see here, we can actually visualize 123 00:05:21,527 --> 00:05:25,286 a single white blood cell. 124 00:05:25,286 --> 00:05:27,542 It sticks, it wiggles its way through 125 00:05:27,542 --> 00:05:29,857 between the cell layers, through the pore, 126 00:05:29,857 --> 00:05:32,278 comes out on the other side of the membrane, 127 00:05:32,278 --> 00:05:35,713 and right there, it's going to engulf the bacteria 128 00:05:35,713 --> 00:05:37,362 labeled in green. 129 00:05:37,362 --> 00:05:40,366 In that tiny chip, you just witnessed 130 00:05:40,366 --> 00:05:43,547 one of the most fundamental responses 131 00:05:43,547 --> 00:05:45,504 our body has to an infection. 132 00:05:45,504 --> 00:05:49,274 It's the way we respond to -- an immune response. 133 00:05:49,274 --> 00:05:51,675 It's pretty exciting. 134 00:05:51,675 --> 00:05:54,018 Now I want to share this picture with you, 135 00:05:54,018 --> 00:05:56,656 not just because it's so beautiful, 136 00:05:56,656 --> 00:05:59,992 but because it tells us an enormous amount of information 137 00:05:59,992 --> 00:06:02,589 about what the cells are doing within the chips. 138 00:06:02,589 --> 00:06:04,848 It tells us that these cells 139 00:06:04,848 --> 00:06:07,159 from the small airways in our lungs, 140 00:06:07,159 --> 00:06:08,910 actually have these hairlike structures 141 00:06:08,910 --> 00:06:10,918 that you would expect to see in the lung. 142 00:06:10,918 --> 00:06:12,383 These structures are called cilia, 143 00:06:12,383 --> 00:06:15,293 and they actually move the mucus out of the lung. 144 00:06:15,293 --> 00:06:16,832 Yeah. Mucus. Yuck. 145 00:06:16,832 --> 00:06:19,272 But mucus is actually very important. 146 00:06:19,272 --> 00:06:21,853 Mucus traps particulates, viruses, 147 00:06:21,853 --> 00:06:23,312 potential allergens, 148 00:06:23,312 --> 00:06:24,913 and these little cilia move 149 00:06:24,913 --> 00:06:27,163 and clear the mucus out. 150 00:06:27,163 --> 00:06:29,075 When they get damaged, say, 151 00:06:29,075 --> 00:06:31,494 by cigarette smoke for example, 152 00:06:31,494 --> 00:06:34,302 they don't work properly, and they can't clear that mucus out. 153 00:06:34,302 --> 00:06:38,119 And that can lead to diseases such as bronchitis. 154 00:06:38,119 --> 00:06:40,766 Cilia and the clearance of mucus 155 00:06:40,766 --> 00:06:45,227 are also involved in awful diseases like cystic fibrosis. 156 00:06:45,227 --> 00:06:48,777 But now, with the functionality that we get in these chips, 157 00:06:48,777 --> 00:06:50,601 we can begin to look 158 00:06:50,601 --> 00:06:53,114 for potential new treatments. 159 00:06:53,114 --> 00:06:55,066 We didn't stop with the lung on a chip. 160 00:06:55,066 --> 00:06:56,950 We have a gut on a chip. 161 00:06:56,950 --> 00:06:58,980 You can see one right here. 162 00:06:58,980 --> 00:07:02,206 And we've put intestinal human cells 163 00:07:02,206 --> 00:07:04,111 in a gut on a chip, 164 00:07:04,111 --> 00:07:06,948 and they're under constant peristaltic motion, 165 00:07:06,948 --> 00:07:10,139 this trickling flow through the cells, 166 00:07:10,139 --> 00:07:12,697 and we can mimic many of the functions 167 00:07:12,697 --> 00:07:14,960 that you actually would expect to see 168 00:07:14,960 --> 00:07:16,653 in the human intestine. 169 00:07:16,653 --> 00:07:20,444 Now we can begin to create models of diseases 170 00:07:20,444 --> 00:07:22,854 such as irritable bowel syndrome. 171 00:07:22,854 --> 00:07:24,936 This is a disease that affects 172 00:07:24,936 --> 00:07:26,847 a large number of individuals. 173 00:07:26,847 --> 00:07:28,621 It's really debilitating, 174 00:07:28,621 --> 00:07:32,563 and there aren't really many good treatments for it. 175 00:07:32,563 --> 00:07:34,865 Now we have a whole pipeline 176 00:07:34,865 --> 00:07:37,144 of different organ chips 177 00:07:37,144 --> 00:07:40,876 that we are currently working on in our labs. 178 00:07:40,876 --> 00:07:44,295 Now, the true power of this technology, however, 179 00:07:44,295 --> 00:07:46,420 really comes from the fact 180 00:07:46,420 --> 00:07:48,965 that we can fluidically link them. 181 00:07:48,965 --> 00:07:50,912 There's fluid flowing across these cells, 182 00:07:50,912 --> 00:07:52,991 so we can begin to interconnect 183 00:07:52,991 --> 00:07:55,853 multiple different chips together 184 00:07:55,853 --> 00:08:00,066 to form what we call a virtual human on a chip. 185 00:08:00,066 --> 00:08:03,075 Now we're really getting excited. 186 00:08:03,075 --> 00:08:07,170 We're not going to ever recreate a whole human in these chips, 187 00:08:07,170 --> 00:08:11,339 but what our goal is is to be able to recreate 188 00:08:11,339 --> 00:08:13,352 sufficient functionality 189 00:08:13,352 --> 00:08:15,712 so that we can make better predictions 190 00:08:15,712 --> 00:08:17,926 of what's going to happen in humans. 191 00:08:17,926 --> 00:08:20,850 For example, now we can begin to explore 192 00:08:20,850 --> 00:08:24,284 what happens when we put a drug like an aerosol drug. 193 00:08:24,284 --> 00:08:27,270 Those of you like me who have asthma, when you take your inhaler, 194 00:08:27,270 --> 00:08:30,196 we can explore how that drug comes into your lungs, 195 00:08:30,196 --> 00:08:31,822 how it enters the body, 196 00:08:31,822 --> 00:08:33,576 how it might affect, say, your heart. 197 00:08:33,576 --> 00:08:35,484 Does it change the beating of your heart? 198 00:08:35,484 --> 00:08:37,125 Does it have a toxicity? 199 00:08:37,125 --> 00:08:39,133 Does it get cleared by the liver? 200 00:08:39,133 --> 00:08:41,285 Is it metabolized in the liver? 201 00:08:41,285 --> 00:08:43,176 Is it excreted in your kidneys? 202 00:08:43,176 --> 00:08:45,388 We can begin to study the dynamic 203 00:08:45,388 --> 00:08:48,013 response of the body to a drug. 204 00:08:48,028 --> 00:08:49,947 This could really revolutionize 205 00:08:49,947 --> 00:08:51,596 and be a game changer 206 00:08:51,596 --> 00:08:54,534 for not only the pharmaceutical industry, 207 00:08:54,534 --> 00:08:56,907 but a whole host of different industries, 208 00:08:56,907 --> 00:08:59,307 including the cosmetics industry. 209 00:08:59,307 --> 00:09:02,189 We can potentially use the skin on a chip 210 00:09:02,189 --> 00:09:04,150 that we're currently developing in the lab 211 00:09:04,150 --> 00:09:06,704 to test whether the ingredients in those products 212 00:09:06,704 --> 00:09:09,987 that you're using are actually safe to put on your skin 213 00:09:09,987 --> 00:09:12,676 without the need for animal testing. 214 00:09:12,676 --> 00:09:14,620 We could test the safety 215 00:09:14,620 --> 00:09:16,873 of chemicals that we are exposed to 216 00:09:16,873 --> 00:09:18,787 on a daily basis in our environment, 217 00:09:18,787 --> 00:09:22,518 such as chemicals in regular household cleaners. 218 00:09:22,518 --> 00:09:25,720 We could also use the organs on chips 219 00:09:25,720 --> 00:09:28,499 for applications in bioterrorism 220 00:09:28,499 --> 00:09:31,070 or radiation exposure. 221 00:09:31,070 --> 00:09:34,420 We could use them to learn more about 222 00:09:34,420 --> 00:09:37,464 diseases such as ebola 223 00:09:37,464 --> 00:09:41,356 or other deadly diseases such as SARS. 224 00:09:41,356 --> 00:09:43,194 Organs on chips could also change 225 00:09:43,194 --> 00:09:46,568 the way we do clinical trials in the future. 226 00:09:46,568 --> 00:09:49,155 Right now, the average participant 227 00:09:49,155 --> 00:09:52,525 in a clinical trial is that: average. 228 00:09:52,525 --> 00:09:55,851 Tends to be middle aged, tends to be female. 229 00:09:55,851 --> 00:09:58,323 You won't find many clinical trials 230 00:09:58,323 --> 00:09:59,838 in which children are involved, 231 00:09:59,838 --> 00:10:03,385 yet every day, we give children medications, 232 00:10:03,385 --> 00:10:07,131 and the only safety data we have on that drug 233 00:10:07,131 --> 00:10:10,205 is one that we obtained from adults. 234 00:10:10,205 --> 00:10:11,999 Children are not adults. 235 00:10:11,999 --> 00:10:15,132 They may not respond in the same way adults do. 236 00:10:15,132 --> 00:10:17,544 There are other things like genetic differences 237 00:10:17,544 --> 00:10:18,977 in populations 238 00:10:18,977 --> 00:10:22,083 that may lead to at-risk populations 239 00:10:22,083 --> 00:10:25,520 that are at risk of having an adverse drug reaction. 240 00:10:25,520 --> 00:10:28,909 Now imagine if we could take cells from all those different populations, 241 00:10:28,919 --> 00:10:30,827 put them on chips, 242 00:10:30,827 --> 00:10:32,791 and create populations on a chip. 243 00:10:32,791 --> 00:10:34,629 This could really change the way 244 00:10:34,629 --> 00:10:36,698 we do clinical trials. 245 00:10:36,698 --> 00:10:39,530 And this is the team and the people that are doing this. 246 00:10:39,530 --> 00:10:42,787 We have engineers, we have cell biologists, 247 00:10:42,787 --> 00:10:46,561 we have clinicians, all working together. 248 00:10:46,561 --> 00:10:48,487 We're really seeing something quite incredible 249 00:10:48,487 --> 00:10:50,092 at the Wyss Institute. 250 00:10:50,092 --> 00:10:52,263 It's really a convergence of disciplines, 251 00:10:52,263 --> 00:10:55,983 where biology is influencing the way we design, 252 00:10:55,983 --> 00:10:58,645 the way we engineer, the way we build. 253 00:10:58,645 --> 00:11:00,048 It's pretty exciting. 254 00:11:00,048 --> 00:11:03,612 We're establishing important industry collaborations 255 00:11:03,612 --> 00:11:06,985 such as the one we have with a company 256 00:11:06,985 --> 00:11:10,584 that has expertise in large-scale digital manufacturing. 257 00:11:10,584 --> 00:11:12,603 They're going to help us make, 258 00:11:12,603 --> 00:11:14,129 instead of one of these, 259 00:11:14,129 --> 00:11:15,712 millions of these chips, 260 00:11:15,712 --> 00:11:17,381 so that we can get them into the hands 261 00:11:17,381 --> 00:11:20,270 of as many researchers as possible. 262 00:11:20,270 --> 00:11:24,486 And this is key to the potential of that technology. 263 00:11:24,486 --> 00:11:27,023 Now let me show you our instrument. 264 00:11:27,023 --> 00:11:29,012 This is an instrument that our engineers 265 00:11:29,012 --> 00:11:31,630 are actually prototyping right now in the lab, 266 00:11:31,630 --> 00:11:33,939 and this instrument is going to give us 267 00:11:33,939 --> 00:11:36,398 the engineering controls that we're going to require 268 00:11:36,398 --> 00:11:40,566 in order to link 10 or more organ chips together. 269 00:11:40,566 --> 00:11:42,795 It does something else that's very important. 270 00:11:42,795 --> 00:11:45,639 It creates an easy user interface. 271 00:11:45,639 --> 00:11:48,629 So a cell biologist like me can come in, 272 00:11:48,629 --> 00:11:50,637 take a chip, put it in a cartridge 273 00:11:50,637 --> 00:11:52,569 like the prototype you see there, 274 00:11:52,569 --> 00:11:54,640 put the cartridge into the machine 275 00:11:54,640 --> 00:11:56,128 just like you would a C.D., 276 00:11:56,128 --> 00:11:57,260 and away you go. 277 00:11:57,260 --> 00:12:00,009 Plug and play. Easy. 278 00:12:00,009 --> 00:12:02,523 Now, let's imagine a little bit 279 00:12:02,523 --> 00:12:03,902 what the future might look like 280 00:12:03,902 --> 00:12:06,315 if I could take your stem cells 281 00:12:06,315 --> 00:12:07,755 and put them on a chip, 282 00:12:07,755 --> 00:12:10,974 or your stem cells and put them on a chip. 283 00:12:10,974 --> 00:12:14,475 It would be a personalized chip just for you. 284 00:12:14,475 --> 00:12:17,683 Now all of us in here are individuals, 285 00:12:17,683 --> 00:12:20,521 and those individual differences mean 286 00:12:20,521 --> 00:12:22,963 that we could react very differently 287 00:12:22,963 --> 00:12:27,210 and sometimes in unpredictable ways to drugs. 288 00:12:27,210 --> 00:12:31,778 I myself, a couple of years back, had a really bad headache, 289 00:12:31,778 --> 00:12:34,191 just couldn't shake it, thought, "Well, I'll try something different." 290 00:12:34,191 --> 00:12:36,326 I took some Advil. Fifteen minutes later, 291 00:12:36,326 --> 00:12:38,206 I was on my way to the emergency room 292 00:12:38,206 --> 00:12:40,099 with a full-blown asthma attack. 293 00:12:40,099 --> 00:12:41,929 Now, obviously it wasn't fatal, 294 00:12:41,929 --> 00:12:45,102 but unfortunately, some of these 295 00:12:45,102 --> 00:12:48,711 adverse drug reactions can be fatal. 296 00:12:48,711 --> 00:12:50,652 So how do we prevent them? 297 00:12:50,652 --> 00:12:53,232 Well, we could imagine one day 298 00:12:53,232 --> 00:12:55,575 having Geraldine on a chip, 299 00:12:55,575 --> 00:12:57,324 having Danielle on a chip, 300 00:12:57,324 --> 00:12:58,797 having you on a chip. 301 00:12:58,797 --> 00:13:01,185 Personalized medicine. Thank you. 302 00:13:01,185 --> 00:13:05,339 (Applause)