1 00:00:14,440 --> 00:00:16,960 Speaker 1: Welcome to tech Stuff. This is the story, and today 2 00:00:17,040 --> 00:00:21,320 Speaker 1: I'm here with Cara Price. Hey os Hey, Cara. This 3 00:00:21,360 --> 00:00:24,239 Speaker 1: week's story is one that is quite personal to me, 4 00:00:24,560 --> 00:00:26,119 Speaker 1: and it has to do with the technology that we 5 00:00:26,280 --> 00:00:28,360 Speaker 1: use to detect and treat cancer. 6 00:00:29,640 --> 00:00:31,880 Speaker 2: You know, I think cancer is unfortunately one of those 7 00:00:31,920 --> 00:00:35,199 Speaker 2: things that many people have confronted. Even if you have 8 00:00:35,240 --> 00:00:38,600 Speaker 2: never received a cancer diagnosis, many people have watched loved 9 00:00:38,600 --> 00:00:40,200 Speaker 2: ones struggle to overcome the disease. 10 00:00:40,880 --> 00:00:44,839 Speaker 1: That's right, and my parents separated when I was very 11 00:00:44,920 --> 00:00:47,760 Speaker 1: very young one. In fact, my parents are sort lived 12 00:00:47,760 --> 00:00:51,199 Speaker 1: in different countries, so I was often shuttling around between 13 00:00:51,240 --> 00:00:55,240 Speaker 1: them in the company of a nanny who was essentially 14 00:00:55,760 --> 00:01:01,120 Speaker 1: a third parent, and she unfortunately got with breast cancer 15 00:01:01,200 --> 00:01:05,399 Speaker 1: that was detected too late. She had a double mistectomy, 16 00:01:06,120 --> 00:01:11,160 Speaker 1: but the cancer already metastasized and she died. And it's 17 00:01:11,200 --> 00:01:13,600 Speaker 1: one of the great sadnesses of my life. 18 00:01:13,600 --> 00:01:16,320 Speaker 2: In fact, I'm sorry to hear that, you know, it's 19 00:01:16,560 --> 00:01:19,959 Speaker 2: unfortunately an all too common story. 20 00:01:20,800 --> 00:01:24,880 Speaker 1: Absolutely. So I got connected with this guy called Andre 21 00:01:25,040 --> 00:01:28,600 Speaker 1: Zor a few months ago, and he's a biochemist and 22 00:01:28,680 --> 00:01:31,400 Speaker 1: also the co founder of a company called Loomis cell 23 00:01:31,920 --> 00:01:36,280 Speaker 1: which is a company that's changing how cancer surgeries are performed. 24 00:01:36,319 --> 00:01:38,320 Speaker 1: So I was pretty intrigued. 25 00:01:38,920 --> 00:01:42,479 Speaker 2: So can you just explain to me what is wrong 26 00:01:42,520 --> 00:01:44,760 Speaker 2: with the way that surgeries are being done now? 27 00:01:45,080 --> 00:01:49,200 Speaker 1: Well, I was pretty surprised to hear from andre that 28 00:01:49,320 --> 00:01:55,000 Speaker 1: cancer surgery isn't as precise as perhaps we might imagine 29 00:01:55,120 --> 00:01:57,720 Speaker 1: or hope. He says that there's actually a fair amount 30 00:01:57,720 --> 00:02:00,840 Speaker 1: of art to the science of detecting and then removing 31 00:02:00,920 --> 00:02:02,200 Speaker 1: tumors in surgery. 32 00:02:03,080 --> 00:02:05,800 Speaker 3: I think it's one of those dirty secrets in medicine 33 00:02:05,800 --> 00:02:11,600 Speaker 3: that people don't really realize. Cancer surgery is extraordinarily imprecise, 34 00:02:12,320 --> 00:02:16,239 Speaker 3: and even the best surgeons in the world will miss 35 00:02:16,280 --> 00:02:22,880 Speaker 3: cancer because, contrary to common perception, cancer cells are really 36 00:02:23,000 --> 00:02:23,520 Speaker 3: not that. 37 00:02:23,560 --> 00:02:25,280 Speaker 4: Different from normal tissue. 38 00:02:25,320 --> 00:02:29,440 Speaker 3: It's very difficult to tell in real time during a surgery, 39 00:02:29,480 --> 00:02:32,640 Speaker 3: with everything going on, where does the tumorand and the 40 00:02:32,680 --> 00:02:34,120 Speaker 3: healthy tissue start. 41 00:02:34,560 --> 00:02:37,600 Speaker 1: In fact, Andrei told me that the best cancer surgeons 42 00:02:38,320 --> 00:02:41,920 Speaker 1: are considered the best because they're so good at detecting 43 00:02:42,400 --> 00:02:46,440 Speaker 1: where the cancerous tissue ends and where the healthy tissue begins. 44 00:02:46,800 --> 00:02:50,440 Speaker 1: This is through a process called palpating, which is basically 45 00:02:50,880 --> 00:02:55,360 Speaker 1: a fancy way of saying feeling out by touch, the 46 00:02:55,400 --> 00:02:58,240 Speaker 1: difference between healthy cells and cancerus cells. 47 00:02:58,760 --> 00:03:01,560 Speaker 3: I've been there, and I've tried, and I can't feel 48 00:03:01,600 --> 00:03:06,440 Speaker 3: a damn thing. It's not something that the untrained fingers 49 00:03:06,480 --> 00:03:09,240 Speaker 3: are able to detect. But all of the world's best 50 00:03:09,240 --> 00:03:13,080 Speaker 3: surgeons is able to tell whether there's cancer left behind 51 00:03:13,080 --> 00:03:16,360 Speaker 3: by pile paiding around where the primary tumor was and 52 00:03:16,440 --> 00:03:18,840 Speaker 3: deciding in real time whether more tissue needs to be 53 00:03:18,880 --> 00:03:24,960 Speaker 3: taken out or not. But most cancer surgeries are imperfect, 54 00:03:25,200 --> 00:03:28,680 Speaker 3: and on average, if we look at all cancer surgeries, 55 00:03:29,160 --> 00:03:31,960 Speaker 3: thirty to forty percent of the time, thirty to forty 56 00:03:31,960 --> 00:03:34,760 Speaker 3: percent of the time there will be cancer left behind, 57 00:03:35,120 --> 00:03:36,800 Speaker 3: not on purpose, unintentionally. 58 00:03:37,040 --> 00:03:38,760 Speaker 2: That seems like a high percentage. 59 00:03:39,040 --> 00:03:41,040 Speaker 1: Yeah, I mean, of course, is not to say that 60 00:03:41,120 --> 00:03:45,240 Speaker 1: cancer surgery is ineffective. Alongside drugs, these procedures have saved 61 00:03:45,280 --> 00:03:48,440 Speaker 1: millions of lives in the past few decades. Andrew thinks 62 00:03:48,440 --> 00:03:51,400 Speaker 1: we can do better and save more lives, and so 63 00:03:51,480 --> 00:03:54,480 Speaker 1: he set out to solve this problem, and his company 64 00:03:54,520 --> 00:03:59,920 Speaker 1: has now created a technology to more precisely detect cancerous tissue. 65 00:04:00,320 --> 00:04:03,240 Speaker 1: It's called Loomis cell, and so far it's being used 66 00:04:03,280 --> 00:04:06,560 Speaker 1: to treat breast cancer patients. But Andre doesn't want to 67 00:04:06,600 --> 00:04:08,760 Speaker 1: stop at just one type of cancer. He wants to 68 00:04:08,760 --> 00:04:11,960 Speaker 1: treat them all, and he has a deeply personal reason 69 00:04:12,000 --> 00:04:15,160 Speaker 1: to do so. He told me that he watched one 70 00:04:15,200 --> 00:04:17,400 Speaker 1: of the women who he loved most in his life, 71 00:04:17,680 --> 00:04:21,080 Speaker 1: a woman he grew up with, suffer from an unsuccessful 72 00:04:21,200 --> 00:04:25,640 Speaker 1: avarian cancer treatment. Andre tells it best, So here's the 73 00:04:25,680 --> 00:04:34,720 Speaker 1: rest of our conversation. And I've lived through the tragedy 74 00:04:34,720 --> 00:04:38,840 Speaker 1: of an unsuccessful cancer treatment, and so of you, and 75 00:04:38,880 --> 00:04:40,200 Speaker 1: I'm wondering if you could tell that story. 76 00:04:40,839 --> 00:04:44,120 Speaker 3: It was one of those incredibly sad stories that her 77 00:04:44,200 --> 00:04:48,120 Speaker 3: cancer was called relatively late. It was a varian cancer, 78 00:04:48,560 --> 00:04:51,760 Speaker 3: and he was a varian cancer that had metastasized to. 79 00:04:52,279 --> 00:04:54,200 Speaker 4: What we call the peroneal cavity. 80 00:04:54,240 --> 00:04:57,359 Speaker 3: That is the cavity where all the reproductive organs of 81 00:04:57,400 --> 00:04:59,960 Speaker 3: the women are, as well as several other Bible ord 82 00:05:00,480 --> 00:05:05,720 Speaker 3: And there is really no way to identify where cancer 83 00:05:05,880 --> 00:05:11,960 Speaker 3: has metastasized in the peritoneal cavity other than palpating around 84 00:05:12,000 --> 00:05:16,080 Speaker 3: and trying to figure out where the cancer is. And unfortunately, 85 00:05:16,880 --> 00:05:19,159 Speaker 3: more often than not, they failed. The vast majority of 86 00:05:19,200 --> 00:05:21,159 Speaker 3: times they failed. 87 00:05:22,080 --> 00:05:24,360 Speaker 1: What was the name of the friend that you lost. 88 00:05:24,720 --> 00:05:25,680 Speaker 4: Her name was Monica. 89 00:05:26,200 --> 00:05:28,880 Speaker 1: If I remember from our last conversation, though, you really 90 00:05:28,880 --> 00:05:32,200 Speaker 1: lived through the journey with Monic current and you may 91 00:05:32,200 --> 00:05:34,040 Speaker 1: have promised to her, I think before she passed away. 92 00:05:34,839 --> 00:05:37,400 Speaker 3: Yeah, it was one of these things that you never forget, 93 00:05:37,480 --> 00:05:38,960 Speaker 3: you know, we went through this journey together. 94 00:05:39,080 --> 00:05:40,920 Speaker 4: She was in Mexico at the time I was here 95 00:05:40,920 --> 00:05:42,520 Speaker 4: in Boston, and so. 96 00:05:42,640 --> 00:05:45,240 Speaker 3: Because I was privileged to work with a lot of 97 00:05:45,680 --> 00:05:48,480 Speaker 3: top physicians in the field, I was able to put 98 00:05:48,480 --> 00:05:51,520 Speaker 3: her in contact with some of the best doctors in 99 00:05:51,560 --> 00:05:54,600 Speaker 3: the varian cancer and you know, the incredible team at 100 00:05:54,640 --> 00:05:57,560 Speaker 3: MD Anderson was able to extend her life by almost 101 00:05:57,640 --> 00:06:00,799 Speaker 3: nine months, which is unheard of or a stage four 102 00:06:00,880 --> 00:06:04,360 Speaker 3: over a cancer patient. She had just had a baby, Emilia, 103 00:06:04,440 --> 00:06:08,640 Speaker 3: who unfortunately grew up not knowing his mom. Her doctor, 104 00:06:08,720 --> 00:06:11,160 Speaker 3: David at m D Anderson said, look, we're at the 105 00:06:11,240 --> 00:06:14,200 Speaker 3: end of the line here, We're done here, and she 106 00:06:14,279 --> 00:06:16,239 Speaker 3: needs to find peace on the fact that she fought 107 00:06:16,320 --> 00:06:18,479 Speaker 3: with all her will, but it's time for her to 108 00:06:18,560 --> 00:06:21,719 Speaker 3: let go. And so I flew to Mexico City and 109 00:06:21,920 --> 00:06:24,480 Speaker 3: the whole family was there and we're talking, and you know, 110 00:06:24,720 --> 00:06:26,960 Speaker 3: she was making jokes, and then at some point we 111 00:06:26,960 --> 00:06:30,000 Speaker 3: were left alone and she said, I don't understand the 112 00:06:30,040 --> 00:06:33,960 Speaker 3: why why aren't we doing better? Why is in the 113 00:06:34,000 --> 00:06:37,120 Speaker 3: field doing something that will give women like me who 114 00:06:37,400 --> 00:06:40,960 Speaker 3: just gave birth to beautiful, healthy baby, the opportunity to 115 00:06:41,120 --> 00:06:44,800 Speaker 3: leave longer to do something with our lives. Why why 116 00:06:44,800 --> 00:06:48,400 Speaker 3: aren't you doing more? And I said, well, you know, 117 00:06:48,880 --> 00:06:51,560 Speaker 3: it's a combination of factors where she's like, look, I 118 00:06:51,560 --> 00:06:55,080 Speaker 3: don't want to hear you have to promise me, and 119 00:06:55,120 --> 00:06:58,800 Speaker 3: I did that you're going to do everything in your power, 120 00:06:58,880 --> 00:07:01,599 Speaker 3: everything you can to make sure this doesn't ever happen 121 00:07:01,640 --> 00:07:06,640 Speaker 3: again to another woman. That when a woman gets diagnosed 122 00:07:06,640 --> 00:07:09,159 Speaker 3: with a variant cancer, breast cancer, correctal cancer, whatever it 123 00:07:09,200 --> 00:07:12,480 Speaker 3: may be, and they tell her that she needs to 124 00:07:12,520 --> 00:07:15,080 Speaker 3: go to surgery, that they're not going to tell her 125 00:07:15,160 --> 00:07:16,800 Speaker 3: at the end of the surgery what they told me, 126 00:07:16,920 --> 00:07:19,320 Speaker 3: which is there's some cancer left behind and you have 127 00:07:19,400 --> 00:07:22,800 Speaker 3: weeks to leave. You have to promise me that you're 128 00:07:22,800 --> 00:07:24,360 Speaker 3: going to do everything in your power and you're not 129 00:07:24,360 --> 00:07:27,400 Speaker 3: going to rest until you have figured out a solution 130 00:07:27,480 --> 00:07:31,480 Speaker 3: to this. And I did. I, you know, held her 131 00:07:31,520 --> 00:07:33,000 Speaker 3: hand in mind, and I said, I promise you. 132 00:07:33,040 --> 00:07:33,600 Speaker 4: I will do that. 133 00:07:34,360 --> 00:07:37,480 Speaker 3: She passed away a few weeks later. We didn't discuss 134 00:07:37,520 --> 00:07:40,680 Speaker 3: this ever again, and you know, it was kind of 135 00:07:40,680 --> 00:07:42,160 Speaker 3: stuck in the back of my mind for a couple 136 00:07:42,240 --> 00:07:43,720 Speaker 3: of years. So I was like, Okay, well I made 137 00:07:43,720 --> 00:07:47,480 Speaker 3: this promise. And then you know, I met my co 138 00:07:47,560 --> 00:07:50,520 Speaker 3: founder David. He had just lost his wife to breast cancer, 139 00:07:50,600 --> 00:07:54,160 Speaker 3: and I saw the opportunity to partner up with. 140 00:07:54,080 --> 00:07:58,040 Speaker 4: Somebody who was as heart and as deeply. 141 00:07:58,040 --> 00:08:01,040 Speaker 3: Moved by the fact that we can do better by 142 00:08:01,040 --> 00:08:04,320 Speaker 3: these women, that we can't do better by their families, 143 00:08:04,400 --> 00:08:06,559 Speaker 3: and you know, we have the power to do something 144 00:08:06,600 --> 00:08:07,120 Speaker 3: to change it. 145 00:08:07,840 --> 00:08:10,200 Speaker 4: And so that's how a fifteen year journey started. 146 00:08:10,520 --> 00:08:14,440 Speaker 1: Fifteen years almost to the date. Let's talk about what 147 00:08:14,640 --> 00:08:16,960 Speaker 1: is loumicell, What does it do, how does it work. 148 00:08:17,560 --> 00:08:20,760 Speaker 3: What we know is that if you catch cancer early, 149 00:08:21,120 --> 00:08:24,320 Speaker 3: surgery can be curative if you get all the cancer 150 00:08:24,320 --> 00:08:31,840 Speaker 3: cells out, But most cancer surgeries are imperfect. When you 151 00:08:31,920 --> 00:08:34,839 Speaker 3: do a breast conserving surgery, the problem is that thirty 152 00:08:34,840 --> 00:08:38,679 Speaker 3: to forty percent of the time, the surgeon will inadvertently 153 00:08:38,800 --> 00:08:43,080 Speaker 3: leave cancer cells behind. So what loomicell does, for the 154 00:08:43,120 --> 00:08:48,319 Speaker 3: first time in history is it gives the surgeons a guideline, 155 00:08:48,640 --> 00:08:52,480 Speaker 3: a signal where they are able to identify in real 156 00:08:52,559 --> 00:08:56,760 Speaker 3: time during the surgery whether there are cancer cells left 157 00:08:56,800 --> 00:09:02,040 Speaker 3: behind or not. How well, you get a Nobel Price 158 00:09:02,280 --> 00:09:04,439 Speaker 3: winner and you get a couple of really smart people 159 00:09:04,440 --> 00:09:07,200 Speaker 3: from MIT, and you define the problem. And that's what 160 00:09:07,240 --> 00:09:09,959 Speaker 3: people from MIT do. They go and solve problems, right, 161 00:09:10,320 --> 00:09:13,080 Speaker 3: And so in this case, Munjigu Weendi, Jorge Ferreer and 162 00:09:13,200 --> 00:09:16,079 Speaker 3: David Leif they sort of joined me in this journey 163 00:09:16,120 --> 00:09:17,959 Speaker 3: and said, all right, well, we need something that is 164 00:09:18,000 --> 00:09:22,640 Speaker 3: extraordinarily safe, inexpensive that can be injected before surgery and 165 00:09:22,760 --> 00:09:28,040 Speaker 3: will give surgeons the ability to make cancer cells illuminate, 166 00:09:28,280 --> 00:09:30,400 Speaker 3: be fluorescent under normal light. 167 00:09:30,480 --> 00:09:31,840 Speaker 4: Only it's purple light. 168 00:09:32,120 --> 00:09:34,760 Speaker 3: And so the surgeon will switch off the big lamp 169 00:09:34,760 --> 00:09:36,560 Speaker 3: that you see on the ceiling on the operating room, 170 00:09:37,040 --> 00:09:40,480 Speaker 3: and the device that we use has purple light coming 171 00:09:40,600 --> 00:09:42,920 Speaker 3: out of it, and when it hits the cells that 172 00:09:43,000 --> 00:09:46,720 Speaker 3: are cancers, those cells fluores back and can be detected 173 00:09:46,760 --> 00:09:49,160 Speaker 3: and displayed on the screen so the surgeon can take 174 00:09:49,200 --> 00:09:52,280 Speaker 3: action immediately. The way it works at the molecular level 175 00:09:52,559 --> 00:09:56,600 Speaker 3: is proteins have a function, and if you can tailor 176 00:09:56,760 --> 00:10:00,840 Speaker 3: protein function you can make some real magic happen. And 177 00:10:00,880 --> 00:10:03,360 Speaker 3: so what we do is we take advantage of a 178 00:10:03,480 --> 00:10:09,160 Speaker 3: protein that is abundant in cancer cells. It's a protein 179 00:10:09,200 --> 00:10:13,280 Speaker 3: that cancer cells use to cut tissue that is surrounding 180 00:10:13,320 --> 00:10:16,280 Speaker 3: the tumor. One of the most important features of cancer 181 00:10:16,640 --> 00:10:19,560 Speaker 3: is that it destroys its environment so that it can grow. 182 00:10:20,040 --> 00:10:21,960 Speaker 4: Otherwise it just doesn't grow right. 183 00:10:22,480 --> 00:10:26,319 Speaker 3: And so we detect that protein by providing it something 184 00:10:26,440 --> 00:10:31,240 Speaker 3: too cut. And when it cuts that substrate that we provide, 185 00:10:31,760 --> 00:10:33,920 Speaker 3: that's when light happens. Think about one of those little 186 00:10:33,920 --> 00:10:36,280 Speaker 3: sticks that you use, a glow stick, right that when 187 00:10:36,280 --> 00:10:39,360 Speaker 3: you crack it, it emits light. Well, the same but 188 00:10:39,400 --> 00:10:41,800 Speaker 3: at a molecular level. When you crack this little mini 189 00:10:41,800 --> 00:10:44,480 Speaker 3: glow stick, and the only way to crack it is 190 00:10:44,480 --> 00:10:47,760 Speaker 3: by a protein that is primarily expressed in cancer cells, 191 00:10:48,040 --> 00:10:50,200 Speaker 3: it gives you a luminous signal. 192 00:10:50,360 --> 00:10:55,040 Speaker 1: So you're injecting a substance into the patients, which you 193 00:10:55,160 --> 00:10:59,479 Speaker 1: know that the cancer will destroy. When it destroys the substance, 194 00:11:00,040 --> 00:11:03,200 Speaker 1: it emits this light, which is visible under purple light. 195 00:11:03,559 --> 00:11:08,400 Speaker 1: Correct well, and where are you on delivering on that promise? 196 00:11:09,360 --> 00:11:13,280 Speaker 3: So we were incredibly fortunate that the FDA approved this 197 00:11:13,480 --> 00:11:18,200 Speaker 3: product last year. Hospitals started using it in the first 198 00:11:18,280 --> 00:11:21,120 Speaker 3: quarter of this year, and it's being used now at 199 00:11:21,160 --> 00:11:22,920 Speaker 3: several hospitals across the US. 200 00:11:23,080 --> 00:11:25,000 Speaker 4: Stanford was the first adopter. 201 00:11:25,760 --> 00:11:29,719 Speaker 3: There are three surgeons at Stanford that are essentially doing 202 00:11:29,760 --> 00:11:32,840 Speaker 3: every single cancer surgery that they do using the Loomi 203 00:11:32,880 --> 00:11:34,240 Speaker 3: cell technology. 204 00:11:33,800 --> 00:11:36,080 Speaker 1: Breast cancer surgery or beyond breast cancer. 205 00:11:36,040 --> 00:11:36,680 Speaker 4: Breast cancer. 206 00:11:36,720 --> 00:11:40,800 Speaker 3: At this point, of course, the journey will continue for 207 00:11:40,840 --> 00:11:42,959 Speaker 3: a long time because I'm not going to rest until 208 00:11:43,040 --> 00:11:44,880 Speaker 3: we are successful in a varian cancer. 209 00:11:45,040 --> 00:11:45,760 Speaker 4: Ovarian cancer. 210 00:11:45,840 --> 00:11:49,720 Speaker 3: Unfortunately, in the list of difficult cancers to treat, ovarian 211 00:11:49,760 --> 00:11:51,679 Speaker 3: cancer is kind of at the top of one of 212 00:11:51,720 --> 00:11:53,960 Speaker 3: the hardest ones to treat, right up there next to 213 00:11:54,040 --> 00:11:56,600 Speaker 3: brain cancer and so on. And so right now there's 214 00:11:56,640 --> 00:12:01,480 Speaker 3: trials on going on sophageal called recto prostate cancer and 215 00:12:01,520 --> 00:12:05,000 Speaker 3: so on, and eventually we will get two complicated things 216 00:12:05,080 --> 00:12:08,760 Speaker 3: like brain cancer and varian cancer. But to know that 217 00:12:08,920 --> 00:12:13,599 Speaker 3: patients are going in big academic cancer centers like Stanford 218 00:12:13,640 --> 00:12:17,480 Speaker 3: and relatively small regional hospitals like Baker in Florida, and 219 00:12:17,640 --> 00:12:20,360 Speaker 3: patients are going in there and they're leaving the surgery 220 00:12:20,440 --> 00:12:23,120 Speaker 3: room and the doctor is saying we got it all. 221 00:12:23,840 --> 00:12:26,360 Speaker 3: And when they say we got it all, before they 222 00:12:26,360 --> 00:12:29,000 Speaker 3: had a seventy percent certainty that they got it all 223 00:12:29,600 --> 00:12:31,840 Speaker 3: based on our clinical data. Now they have like a 224 00:12:31,920 --> 00:12:33,040 Speaker 3: ninety eight percent. 225 00:12:32,760 --> 00:12:35,120 Speaker 4: Certainty that they did in fact get it on. 226 00:12:35,760 --> 00:12:38,040 Speaker 1: What did it feel like to watch the technology being 227 00:12:38,080 --> 00:12:39,200 Speaker 1: deployed for the first time? 228 00:12:39,600 --> 00:12:43,600 Speaker 3: You know, you can never get over the loss, especially 229 00:12:43,679 --> 00:12:46,800 Speaker 3: the loss of somebody as incredible, as beautiful, as full 230 00:12:46,840 --> 00:12:49,839 Speaker 3: of energy and love and life as Monica was. There's 231 00:12:49,920 --> 00:12:53,760 Speaker 3: nothing that will ever substitute for having her around. There's 232 00:12:53,960 --> 00:12:57,880 Speaker 3: nothing that will fill that hole. But to fulfill a 233 00:12:57,960 --> 00:13:01,360 Speaker 3: promise that it's made under those conditions is one of 234 00:13:01,440 --> 00:13:04,120 Speaker 3: the most gratifying things that you can do in life, right, 235 00:13:04,160 --> 00:13:07,480 Speaker 3: because it's not an empty promise. This is not going 236 00:13:07,559 --> 00:13:10,240 Speaker 3: to benefit hurt, It's not going to benefit me. It's 237 00:13:10,280 --> 00:13:13,040 Speaker 3: going to benefit hopefully millions of people. 238 00:13:12,720 --> 00:13:15,680 Speaker 4: Who who get the news that they have cancer and 239 00:13:15,720 --> 00:13:18,320 Speaker 4: that they need to have surgery. That is unique. 240 00:13:18,400 --> 00:13:21,120 Speaker 3: And while it doesn't make up for the loss of 241 00:13:21,160 --> 00:13:24,480 Speaker 3: somebody that you love, the fact that you got fifteen 242 00:13:24,600 --> 00:13:29,560 Speaker 3: years worth of disappointments and failure and restarts and falling 243 00:13:29,600 --> 00:13:31,760 Speaker 3: down having to get up again, because you have this 244 00:13:32,000 --> 00:13:35,040 Speaker 3: energy that is propelled by the problems that you made. 245 00:13:35,720 --> 00:13:38,880 Speaker 3: I don't think that there's any other motivation that is 246 00:13:38,920 --> 00:13:41,080 Speaker 3: as strong as that. It is that kind of energy 247 00:13:41,160 --> 00:13:44,120 Speaker 3: that's like I can't quit. I don't have the right 248 00:13:44,200 --> 00:13:45,240 Speaker 3: to quit ever. 249 00:13:45,800 --> 00:13:48,360 Speaker 1: Zooming out a little bit to the wider field of 250 00:13:48,480 --> 00:13:51,880 Speaker 1: technology and cancer, I mean, you laid it out, I 251 00:13:51,960 --> 00:13:59,199 Speaker 1: think very well. Which is better detection allows for earlier intervention? Obviously? 252 00:13:59,600 --> 00:14:02,120 Speaker 1: You know nowadays in the US, one and eight women 253 00:14:02,160 --> 00:14:04,280 Speaker 1: are expected to be diagnosed with breast cancer at some 254 00:14:04,280 --> 00:14:06,920 Speaker 1: point in their lives, but the mortality rate has been 255 00:14:06,960 --> 00:14:10,240 Speaker 1: in steady decline. Where are we on the bigger picture 256 00:14:10,480 --> 00:14:13,720 Speaker 1: of beating cancer? I mean where there was an article 257 00:14:13,720 --> 00:14:15,120 Speaker 1: in the New York And not too long ago about 258 00:14:15,120 --> 00:14:19,119 Speaker 1: how detection is getting better but doesn't necessarily mean better outcomes. 259 00:14:19,320 --> 00:14:23,479 Speaker 1: There's a lot of excitement around you know, AI, personalized drugs. 260 00:14:23,600 --> 00:14:25,200 Speaker 1: You know, taking a step back, what is the state 261 00:14:25,280 --> 00:14:28,600 Speaker 1: of the nation, of the wider field of technology's ability 262 00:14:28,640 --> 00:14:29,880 Speaker 1: to kill cancer? 263 00:14:31,040 --> 00:14:33,160 Speaker 4: You're right to take a wider view, right, We're going 264 00:14:33,240 --> 00:14:34,360 Speaker 4: to live longer. 265 00:14:34,640 --> 00:14:39,520 Speaker 3: And most mechanical things we will be able to fix, 266 00:14:39,880 --> 00:14:42,920 Speaker 3: including the heart, which at the end is a mechanical pump. 267 00:14:43,240 --> 00:14:46,320 Speaker 3: So cancer is the ultimate frontier if we continue to 268 00:14:46,360 --> 00:14:50,040 Speaker 3: improve our health as a society or be sitting the 269 00:14:50,160 --> 00:14:53,040 Speaker 3: US notwithstanding because that's a problem. But you know, if 270 00:14:53,080 --> 00:14:54,480 Speaker 3: you look at the rest of the world, people are 271 00:14:54,520 --> 00:14:59,240 Speaker 3: living longer and longer, and cancer is becoming the primary 272 00:14:59,280 --> 00:15:02,160 Speaker 3: cause of death, and so at some point we have 273 00:15:02,280 --> 00:15:06,240 Speaker 3: to address this in a much more efficient manner than 274 00:15:06,280 --> 00:15:10,320 Speaker 3: we are today. We have some wonderful drugs, and I'm 275 00:15:10,360 --> 00:15:13,320 Speaker 3: not against drugs at all. In fact, some cancers there's 276 00:15:13,320 --> 00:15:15,720 Speaker 3: nothing you can do surgery wise, and you have to 277 00:15:15,800 --> 00:15:19,880 Speaker 3: use drugs. So we are making significant advances and eventually 278 00:15:19,920 --> 00:15:23,040 Speaker 3: we will find drugs that are highly specific that are 279 00:15:23,080 --> 00:15:25,880 Speaker 3: going to be able to target cancer cells in ways 280 00:15:25,920 --> 00:15:30,680 Speaker 3: that we couldn't imagine ten years ago without the side 281 00:15:30,680 --> 00:15:34,040 Speaker 3: effects that we used to have with raw chemotherapy. But 282 00:15:34,160 --> 00:15:37,800 Speaker 3: I believe and I think most physicians will agree that 283 00:15:37,920 --> 00:15:42,320 Speaker 3: surgery will remain the front line way to deal with 284 00:15:42,400 --> 00:15:45,480 Speaker 3: cancer for the simple fact that if you have to 285 00:15:45,560 --> 00:15:49,360 Speaker 3: kill cancer cells, it's better to kill less cells, and 286 00:15:49,400 --> 00:15:51,600 Speaker 3: the more you can get out of the body, the 287 00:15:51,720 --> 00:15:54,240 Speaker 3: less cells you have to kill later on. And if 288 00:15:54,240 --> 00:15:56,960 Speaker 3: you can ensure that you didn't leave any cells in 289 00:15:56,960 --> 00:15:59,760 Speaker 3: the primary tumor site, then you're going to be better off. 290 00:16:00,000 --> 00:16:04,120 Speaker 3: And there's no question about that. So my prediction is 291 00:16:05,360 --> 00:16:09,800 Speaker 3: we will see cancer quote unquote end within our lifetimes. 292 00:16:10,760 --> 00:16:11,600 Speaker 1: That's a big prediction. 293 00:16:12,480 --> 00:16:13,880 Speaker 4: I think it's going to happen. 294 00:16:13,920 --> 00:16:16,720 Speaker 3: I think our understanding of biology, the biology of cancer 295 00:16:17,280 --> 00:16:19,560 Speaker 3: over the next forty years is going to get us 296 00:16:19,600 --> 00:16:21,520 Speaker 3: to the point where we can address cancer very very 297 00:16:21,520 --> 00:16:26,200 Speaker 3: effectively through a combination of surgery and incredibly targeted therapies. 298 00:16:26,560 --> 00:16:28,280 Speaker 1: How big a role do you think lo Miiselle could 299 00:16:28,280 --> 00:16:28,680 Speaker 1: play in that. 300 00:16:29,200 --> 00:16:31,200 Speaker 3: I think lou Miisell will become the center of care 301 00:16:31,240 --> 00:16:35,240 Speaker 3: for cancer surgery for all cancers. I do believe that 302 00:16:36,000 --> 00:16:38,680 Speaker 3: we do. In the US, we do about a million 303 00:16:38,720 --> 00:16:42,440 Speaker 3: to two million cancer surgeries every single year. That's across 304 00:16:42,480 --> 00:16:45,040 Speaker 3: all cancers. Breast cancer is one of the highest ones, 305 00:16:45,040 --> 00:16:48,440 Speaker 3: with three hundred thousand surgeries a year. I would say 306 00:16:48,480 --> 00:16:51,320 Speaker 3: that this year we're probably going to do a couple 307 00:16:51,360 --> 00:16:55,120 Speaker 3: of thousand surgeries, and then that is going. 308 00:16:54,960 --> 00:16:59,400 Speaker 4: To grow pretty quickly from there. So right now we. 309 00:16:59,480 --> 00:17:04,080 Speaker 3: Are in either full use or testing at about a 310 00:17:04,119 --> 00:17:07,800 Speaker 3: dozen hospitals in the US. We expect to be in 311 00:17:07,880 --> 00:17:10,560 Speaker 3: about twenty to thirty hospitals by the end of the year, 312 00:17:11,200 --> 00:17:13,600 Speaker 3: and the projection for the following years to be at. 313 00:17:13,480 --> 00:17:16,199 Speaker 4: About one hundred health centers across the United States. 314 00:17:16,680 --> 00:17:19,359 Speaker 1: And if lou Misselle doesn't become the standard of care 315 00:17:19,880 --> 00:17:22,880 Speaker 1: for cancer surgery, why will that be What would have happened, 316 00:17:22,920 --> 00:17:23,240 Speaker 1: would have. 317 00:17:23,200 --> 00:17:26,440 Speaker 3: Gone wrong, because somebody will come up with a better 318 00:17:26,440 --> 00:17:27,800 Speaker 3: solution and that will. 319 00:17:27,640 --> 00:17:30,320 Speaker 4: Be a happy day. Technology is only as good as 320 00:17:30,359 --> 00:17:35,640 Speaker 4: technology is good. Right. We all used to use AOL At. 321 00:17:35,480 --> 00:17:38,639 Speaker 3: One point, I still have a Yahue email account, and 322 00:17:38,680 --> 00:17:40,439 Speaker 3: I may be one of the only ones left. And 323 00:17:40,480 --> 00:17:43,359 Speaker 3: then technology got better and everybody moved to something else, 324 00:17:43,800 --> 00:17:45,679 Speaker 3: and that's entirely fine. 325 00:17:45,840 --> 00:17:50,680 Speaker 4: That's what we want. We want to create ever rising bars. 326 00:17:50,320 --> 00:17:52,760 Speaker 3: So that people get over them. We don't create barriers 327 00:17:52,800 --> 00:17:54,879 Speaker 3: so that people can't get over them. We create barriers 328 00:17:54,880 --> 00:17:56,840 Speaker 3: so that stronger will. 329 00:17:56,560 --> 00:18:05,080 Speaker 1: Prevail after the break. How Andrea is working to improve 330 00:18:05,240 --> 00:18:07,919 Speaker 1: another industry, our food system. 331 00:18:08,320 --> 00:18:19,200 Speaker 5: Stay with us. 332 00:18:20,520 --> 00:18:22,600 Speaker 1: I'd have to know a bit more about you and 333 00:18:22,880 --> 00:18:25,240 Speaker 1: what brought you to the field of biotechnology. 334 00:18:25,720 --> 00:18:28,359 Speaker 3: You know, I grew up in Mexico City, not really 335 00:18:28,400 --> 00:18:30,359 Speaker 3: knowing what I wanted to do. 336 00:18:30,440 --> 00:18:31,040 Speaker 4: With my life. 337 00:18:31,160 --> 00:18:33,760 Speaker 3: I always thought I wanted to be a doctor. I 338 00:18:33,840 --> 00:18:37,560 Speaker 3: had the opportunity, after finishing college in Mexico to come 339 00:18:37,600 --> 00:18:39,960 Speaker 3: to Boston and become. 340 00:18:39,680 --> 00:18:42,200 Speaker 4: A part of M I. T. And Harvard, which. 341 00:18:42,600 --> 00:18:46,520 Speaker 3: Opened up an entire new universe of of what could 342 00:18:46,560 --> 00:18:50,159 Speaker 3: be done with biology. Very early on, I got interested 343 00:18:50,359 --> 00:18:54,240 Speaker 3: in a very specialized field, which is how proteins, which 344 00:18:54,280 --> 00:18:57,399 Speaker 3: of course are the building blocks of nature, how their 345 00:18:58,160 --> 00:19:03,119 Speaker 3: structure relates to their funk. And it opened up a 346 00:19:03,520 --> 00:19:06,199 Speaker 3: brand new universe to me that I was just not 347 00:19:06,320 --> 00:19:09,840 Speaker 3: aware of that. You know, all these little, tiny, microscopic 348 00:19:09,920 --> 00:19:13,240 Speaker 3: machines regulate everything that happens in nature in an incredibly 349 00:19:13,280 --> 00:19:16,760 Speaker 3: powerful way. And so the more I learned about that 350 00:19:16,880 --> 00:19:19,720 Speaker 3: microscopic biological world, the more. 351 00:19:19,560 --> 00:19:20,480 Speaker 4: I wanted to know. 352 00:19:21,280 --> 00:19:23,640 Speaker 3: And then, of course, you know, I learned that they 353 00:19:23,640 --> 00:19:26,199 Speaker 3: could be used to cure disease, which is what I 354 00:19:26,200 --> 00:19:28,960 Speaker 3: wanted to do all my life. You know, growing up 355 00:19:29,640 --> 00:19:33,679 Speaker 3: in a lower middle class household, my mom was teacher, 356 00:19:33,760 --> 00:19:36,520 Speaker 3: my dad worked in construction. You know, you're kind of 357 00:19:36,560 --> 00:19:38,200 Speaker 3: wondering what am I going to do with my life, 358 00:19:38,240 --> 00:19:41,640 Speaker 3: And there was always this desire to try to help 359 00:19:41,680 --> 00:19:44,720 Speaker 3: other people, and I really didn't know how, and so 360 00:19:44,920 --> 00:19:47,800 Speaker 3: this universe that opened up before my eyes gave me 361 00:19:47,840 --> 00:19:50,600 Speaker 3: an opportunity to say, if I can figure out some 362 00:19:50,680 --> 00:19:54,880 Speaker 3: of this very unique processes that happen in our bodies 363 00:19:54,920 --> 00:19:58,480 Speaker 3: at a microscopic level, I could help cure disease. I 364 00:19:58,520 --> 00:20:02,159 Speaker 3: could help make a better life for people. And that 365 00:20:02,400 --> 00:20:03,679 Speaker 3: was just incredible. 366 00:20:04,160 --> 00:20:09,120 Speaker 1: When green Light Biosciences, your other company, was publicly listed, 367 00:20:10,000 --> 00:20:12,359 Speaker 1: you talked about having two missions in life. One was 368 00:20:12,880 --> 00:20:16,400 Speaker 1: quote the ability to provide solutions for healthcare, which we've discussed. 369 00:20:17,200 --> 00:20:21,440 Speaker 1: The other was to grow food sustainably and cleanly, which 370 00:20:21,440 --> 00:20:25,280 Speaker 1: we haven't discussed yet. This also begins with a personal story. 371 00:20:25,960 --> 00:20:29,959 Speaker 3: Yeah, and that personal story is a lot cuter because 372 00:20:30,240 --> 00:20:33,240 Speaker 3: of course nobody died, but it also involves My favorite 373 00:20:33,240 --> 00:20:36,040 Speaker 3: person in the world was my son Alex. And Alex 374 00:20:36,080 --> 00:20:38,320 Speaker 3: had something that you know, I think a lot of 375 00:20:38,359 --> 00:20:41,600 Speaker 3: parents will relate to, which was Alex didn't need a 376 00:20:41,640 --> 00:20:46,159 Speaker 3: lot and he was super thin and losing weight, and 377 00:20:46,320 --> 00:20:48,680 Speaker 3: a lot of the things that we would feed him 378 00:20:48,920 --> 00:20:51,639 Speaker 3: would make him sick, and we were just like racking 379 00:20:51,640 --> 00:20:53,320 Speaker 3: our brain trying to figure out what the hell was 380 00:20:53,359 --> 00:20:55,400 Speaker 3: going on. Like one of the only things he would 381 00:20:55,400 --> 00:20:58,120 Speaker 3: eat was bananas. He would eat bananas all day long. 382 00:20:58,160 --> 00:21:00,680 Speaker 3: And I remember my mom being like, let me bananas 383 00:21:00,800 --> 00:21:03,159 Speaker 3: is you know, when have you ever seen a you know, 384 00:21:03,240 --> 00:21:06,040 Speaker 3: a sickly gorilla and only it is bananas. 385 00:21:06,480 --> 00:21:09,600 Speaker 4: They don't only eat bananas or whatever. But you know, 386 00:21:09,680 --> 00:21:11,640 Speaker 4: it made sense because bananas are protected. 387 00:21:11,680 --> 00:21:14,760 Speaker 3: They have this incredibly strong peel that protects them from 388 00:21:15,600 --> 00:21:18,600 Speaker 3: basically everything that is outside. And so one of the 389 00:21:18,600 --> 00:21:21,200 Speaker 3: things that would make Alex really sick, for example, would 390 00:21:21,200 --> 00:21:24,879 Speaker 3: be strawberries, and we couldn't figure out why. My wife, 391 00:21:24,920 --> 00:21:28,600 Speaker 3: who is not a scientist, eventually figure it out that 392 00:21:28,640 --> 00:21:32,560 Speaker 3: it wasn't the strawberry itself, or the salary or the 393 00:21:32,600 --> 00:21:38,360 Speaker 3: carrot or whatever, it was whatever chemical leftovers where on 394 00:21:38,400 --> 00:21:42,800 Speaker 3: that particular food. Chemical synthetic pesticides were the. 395 00:21:42,720 --> 00:21:43,439 Speaker 4: Biggest s culprit. 396 00:21:43,520 --> 00:21:47,280 Speaker 3: There were others, like some of the colorings would make 397 00:21:47,320 --> 00:21:51,040 Speaker 3: him fairly anxious, but what would make him really sick 398 00:21:51,720 --> 00:21:56,200 Speaker 3: would be And we later identified a class of insecticides 399 00:21:56,760 --> 00:21:59,160 Speaker 3: called organo phosphates. 400 00:22:00,160 --> 00:22:00,720 Speaker 4: Of phosphates. 401 00:22:00,760 --> 00:22:04,160 Speaker 3: If you google or akin of phosphates, they're nerve agents. 402 00:22:04,760 --> 00:22:08,440 Speaker 3: Most famous or kind of phosphate of all times sarrying gas. 403 00:22:09,240 --> 00:22:12,920 Speaker 3: So here's human wisdom in full display for you. We 404 00:22:13,000 --> 00:22:16,399 Speaker 3: take a nerve agent that was used to kill people, 405 00:22:16,560 --> 00:22:20,639 Speaker 3: millions of people, okay, and we chemically modify it, and 406 00:22:20,720 --> 00:22:23,159 Speaker 3: we to solve it in water and dilute. 407 00:22:22,760 --> 00:22:25,480 Speaker 4: It down, and then we spray it on. 408 00:22:25,480 --> 00:22:27,360 Speaker 3: The same foods that we're going to feed our kids. 409 00:22:27,640 --> 00:22:31,359 Speaker 3: And so what I discovered is that we use thousands 410 00:22:31,359 --> 00:22:35,480 Speaker 3: of chemicals, none of which are particularly safe or specific 411 00:22:36,160 --> 00:22:39,440 Speaker 3: or bio degradeable or clean, and that if we don't 412 00:22:39,520 --> 00:22:41,240 Speaker 3: use them, by the way, we would lose seventy to 413 00:22:41,280 --> 00:22:43,520 Speaker 3: eighty percent of our food. So it's all like we 414 00:22:43,600 --> 00:22:46,680 Speaker 3: have an option. So a lot of people will tell you, ah, 415 00:22:46,760 --> 00:22:49,200 Speaker 3: it just short, all should just go organic. 416 00:22:49,640 --> 00:22:53,160 Speaker 4: Okay, Well, then we're going to need another eight planets to. 417 00:22:53,160 --> 00:22:55,200 Speaker 3: Feed the soon to be ten billion people that we 418 00:22:55,240 --> 00:22:58,200 Speaker 3: have on this planet, and there's no room for that. 419 00:22:58,440 --> 00:23:00,480 Speaker 4: In fact, thirty to twenty. 420 00:23:00,280 --> 00:23:03,840 Speaker 3: Percent of our food gets destroyed on the farm before 421 00:23:03,880 --> 00:23:07,280 Speaker 3: we have an ability to harvest it. That's an insane number. 422 00:23:07,280 --> 00:23:10,760 Speaker 3: It's billions of metric tons of food that get destroyed 423 00:23:10,760 --> 00:23:13,920 Speaker 3: by pests because we cannot control them with the chemicals we. 424 00:23:13,880 --> 00:23:15,440 Speaker 1: Have, because they've become resistant. 425 00:23:15,840 --> 00:23:17,879 Speaker 3: Because most of the bogs have become resistant to the 426 00:23:17,960 --> 00:23:23,000 Speaker 3: chemicals we have, and so there came another impossible idea, right, 427 00:23:23,040 --> 00:23:25,879 Speaker 3: which is, okay, well, let's replace those chemicals with something 428 00:23:25,920 --> 00:23:28,280 Speaker 3: that is here's a list of stuff that we have 429 00:23:28,359 --> 00:23:31,919 Speaker 3: to come up with. First of all, cheap, because you know, 430 00:23:32,040 --> 00:23:35,680 Speaker 3: farmers are the engine or society. They already don't make 431 00:23:35,800 --> 00:23:38,159 Speaker 3: enough money. We can't give them something that's going to 432 00:23:38,200 --> 00:23:39,840 Speaker 3: be three times the price of what they're paying today. 433 00:23:39,840 --> 00:23:41,560 Speaker 3: That's just not going to work. So it's got to 434 00:23:41,600 --> 00:23:45,520 Speaker 3: be inexpensive. It's got to be potent, because they're not 435 00:23:45,560 --> 00:23:47,520 Speaker 3: going to sacrifice their yield. In fact, it has to 436 00:23:47,560 --> 00:23:50,600 Speaker 3: be more potent than the chemicals they're using today so 437 00:23:50,640 --> 00:23:52,359 Speaker 3: that they can recover more of their food. 438 00:23:52,920 --> 00:23:55,359 Speaker 4: But it has to be one hundred percent safe. 439 00:23:55,960 --> 00:23:59,560 Speaker 3: It cannot affect the environment, It can't affect beneficial insects, 440 00:23:59,840 --> 00:24:04,119 Speaker 3: can't affect pollinators, it cannot affect obviously human health, and 441 00:24:04,160 --> 00:24:08,359 Speaker 3: it cannot accumulate in our food because otherwise it'll end 442 00:24:08,440 --> 00:24:09,200 Speaker 3: up in our kids. 443 00:24:09,440 --> 00:24:11,720 Speaker 4: And so, you know, that's the list of things that 444 00:24:11,760 --> 00:24:12,680 Speaker 4: we had to come up with. 445 00:24:13,280 --> 00:24:15,440 Speaker 3: And it's kind of interesting when you put a list 446 00:24:15,640 --> 00:24:20,240 Speaker 3: of features that is that impossible you eliminate a lot 447 00:24:20,240 --> 00:24:23,400 Speaker 3: of things really really quickly, and the only thing that 448 00:24:23,800 --> 00:24:27,320 Speaker 3: was left was this wonder molecule called right on nucleic 449 00:24:27,359 --> 00:24:31,639 Speaker 3: acid RNA. And so it turned out that RNA was 450 00:24:32,160 --> 00:24:34,560 Speaker 3: at that point we thought would be, and now we 451 00:24:34,640 --> 00:24:37,520 Speaker 3: have proved that it is the solution to a lot 452 00:24:37,560 --> 00:24:38,280 Speaker 3: of those problems. 453 00:24:38,960 --> 00:24:43,639 Speaker 1: RNA has become famous since the COVID pandemic as something 454 00:24:43,680 --> 00:24:49,040 Speaker 1: that you can inject to in a sense, change the 455 00:24:49,160 --> 00:24:52,199 Speaker 1: DNA of an organism, in our case humans. Is that 456 00:24:52,280 --> 00:24:53,639 Speaker 1: is that a fair assessment? 457 00:24:53,880 --> 00:24:58,680 Speaker 4: Incorrect? Okay? The messenger on a Vaccines do not change 458 00:24:58,760 --> 00:24:59,840 Speaker 4: the DNA. First. 459 00:25:00,600 --> 00:25:03,440 Speaker 3: Now, RNA acts in two ways, right the way in 460 00:25:03,440 --> 00:25:05,840 Speaker 3: which we all know, which is the way we learn 461 00:25:05,920 --> 00:25:11,040 Speaker 3: in high school, which is our DNA gets transcribed into RNA, 462 00:25:11,440 --> 00:25:15,320 Speaker 3: So the RNA is a faithful copy of the DNA. 463 00:25:16,200 --> 00:25:19,800 Speaker 3: That RNA then gets read by a ribosome and it 464 00:25:19,840 --> 00:25:24,040 Speaker 3: gets translated into a protein. That's the machinery of the body. 465 00:25:24,160 --> 00:25:28,520 Speaker 3: DNA goes to RNA, RNA goes to proteins. That's what 466 00:25:28,560 --> 00:25:31,040 Speaker 3: we learn in high school. What we didn't learn in 467 00:25:31,080 --> 00:25:34,400 Speaker 3: high school is that there's another function of RNA, which 468 00:25:34,440 --> 00:25:38,680 Speaker 3: is a function of interference, and that means that there 469 00:25:38,720 --> 00:25:43,720 Speaker 3: are RNAs, they're called small interfering RNAs whose job is 470 00:25:43,840 --> 00:25:48,200 Speaker 3: actually to silence down some of the messenger RNAs that 471 00:25:48,240 --> 00:25:53,119 Speaker 3: are not needed. So why is that, Well, imagine that 472 00:25:53,480 --> 00:25:56,359 Speaker 3: your body says I have too much of this messenger RNA, 473 00:25:56,480 --> 00:25:57,280 Speaker 3: that I don't need it. 474 00:25:57,359 --> 00:25:58,280 Speaker 4: I don't need more. 475 00:25:58,119 --> 00:26:02,359 Speaker 3: Insulin or more growth RM or more cortisol or whatever it. 476 00:26:02,320 --> 00:26:03,880 Speaker 4: Is that your body is producing at the time. 477 00:26:04,200 --> 00:26:06,360 Speaker 3: And so what your body does is then it produces 478 00:26:06,400 --> 00:26:10,720 Speaker 3: this small interfering RNase to suppress the excess messenger RNA 479 00:26:10,840 --> 00:26:13,000 Speaker 3: that is out there so that you don't end up 480 00:26:13,040 --> 00:26:14,679 Speaker 3: with an overproduction of a protein. 481 00:26:15,440 --> 00:26:18,400 Speaker 4: So now you can take that tool that is natural. 482 00:26:18,600 --> 00:26:21,520 Speaker 4: It's nature. We're using nature. We're not using something artificial. 483 00:26:21,560 --> 00:26:22,960 Speaker 4: This is a natural pathway. 484 00:26:23,640 --> 00:26:26,280 Speaker 3: But what you're doing, instead of saying we're just going 485 00:26:26,320 --> 00:26:29,680 Speaker 3: to suppress the excess messenger in a you can say 486 00:26:29,680 --> 00:26:32,560 Speaker 3: I'm going to suppress all of the messenger RNA that 487 00:26:32,680 --> 00:26:35,639 Speaker 3: leads to the production of something that is vital to 488 00:26:36,040 --> 00:26:41,240 Speaker 3: a fungi or a weed or an insect. Now, the 489 00:26:41,280 --> 00:26:46,480 Speaker 3: best part about this is it won't work on vertebrates. 490 00:26:47,600 --> 00:26:51,679 Speaker 3: It won't work on fish, birds, humans, cats, dogs. So 491 00:26:51,760 --> 00:26:55,119 Speaker 3: because we have this built in protection, it is quite 492 00:26:55,160 --> 00:26:59,240 Speaker 3: literally impossible for our products to have any impact on 493 00:26:59,320 --> 00:27:02,080 Speaker 3: human health or the health of a whole bunch of organisms. 494 00:27:02,400 --> 00:27:04,440 Speaker 4: The best part, however. 495 00:27:04,160 --> 00:27:07,480 Speaker 3: Is that you can finally tune the sequence of that 496 00:27:07,640 --> 00:27:10,800 Speaker 3: RNA to only affect the pest that you're interested in 497 00:27:10,800 --> 00:27:14,920 Speaker 3: affecting and nothing else, and you can be extraordinarily specific 498 00:27:15,240 --> 00:27:15,920 Speaker 3: in that sense. 499 00:27:16,240 --> 00:27:17,320 Speaker 4: Let me give you an example. 500 00:27:18,040 --> 00:27:21,200 Speaker 3: Our very first product is an insecticide against something called 501 00:27:21,200 --> 00:27:22,840 Speaker 3: the Colorado potato beetle. 502 00:27:23,040 --> 00:27:23,959 Speaker 4: It's just a beetle. 503 00:27:24,080 --> 00:27:27,480 Speaker 3: It's about yay, big, has big stripes on its back. 504 00:27:27,720 --> 00:27:30,159 Speaker 3: Another beetle that you should be very familiar with is 505 00:27:30,160 --> 00:27:32,720 Speaker 3: the lady bog. The ladybug is in fact a beetle, 506 00:27:32,760 --> 00:27:36,200 Speaker 3: and it is very closely related to the Colorado potato beetle. 507 00:27:36,520 --> 00:27:37,720 Speaker 4: They are like first cousins. 508 00:27:38,119 --> 00:27:41,520 Speaker 3: If you apply any chemical synthetic pesticide that will kill 509 00:27:41,520 --> 00:27:46,560 Speaker 3: the Colorado potato beetle, you will likely destroy the ladybug. 510 00:27:46,119 --> 00:27:48,240 Speaker 4: Colonies that are in your field or in your. 511 00:27:48,480 --> 00:27:51,760 Speaker 3: Surrounding areas and so on. Okay, because they're so closely 512 00:27:51,800 --> 00:27:55,720 Speaker 3: related that anything chemical that will impact the potato beetle 513 00:27:55,760 --> 00:27:59,360 Speaker 3: will impact the lady Our product is designed to affect 514 00:27:59,840 --> 00:28:03,600 Speaker 3: the Colorado potato beetle without having any impact whatsoever on 515 00:28:03,640 --> 00:28:06,399 Speaker 3: the ladybog, even though they share like ninety five percent 516 00:28:06,440 --> 00:28:09,640 Speaker 3: of their genes. We can tailor we can fine tune 517 00:28:09,720 --> 00:28:14,199 Speaker 3: our RNA to kill one and not have any impact whatsoever. 518 00:28:13,760 --> 00:28:16,439 Speaker 4: On the other one. And not only the ladybug is faired. 519 00:28:16,600 --> 00:28:20,919 Speaker 3: Honey Bees, butterflies, earthworms, et cetera, et cetera are not 520 00:28:21,040 --> 00:28:24,960 Speaker 3: affected by this RNA because this RNA specific to the 521 00:28:25,040 --> 00:28:26,960 Speaker 3: gene that exists in the potato. 522 00:28:26,560 --> 00:28:29,200 Speaker 1: Beet And where's it being used today? 523 00:28:29,240 --> 00:28:32,960 Speaker 3: This product right now, it's the number one selling product 524 00:28:33,040 --> 00:28:35,800 Speaker 3: in potatoes in the US, and so it's approved in 525 00:28:35,840 --> 00:28:39,720 Speaker 3: the US. It's now its sales have now surpassed the 526 00:28:39,800 --> 00:28:43,000 Speaker 3: sales of all of the leaning chemical pesticides in potato 527 00:28:43,000 --> 00:28:45,920 Speaker 3: fields treating the Colorado potato beet So in two years 528 00:28:46,400 --> 00:28:49,160 Speaker 3: we became the market lead and we're incredibly happy with 529 00:28:49,240 --> 00:28:49,960 Speaker 3: its performance. 530 00:28:50,120 --> 00:28:52,840 Speaker 1: Now, you said a moment ago that is not GMO, 531 00:28:52,920 --> 00:28:55,480 Speaker 1: But there have been some criticisms that in a sense, 532 00:28:55,560 --> 00:29:01,080 Speaker 1: my releasing this biological agent and effecting the internal mechanism 533 00:29:01,080 --> 00:29:04,080 Speaker 1: of these insects that you're in essense to playing god 534 00:29:04,200 --> 00:29:06,840 Speaker 1: or intervening in nature in a way that's kind of 535 00:29:06,840 --> 00:29:10,200 Speaker 1: could have unpredictable consequences. How do you respond to some 536 00:29:10,240 --> 00:29:11,520 Speaker 1: of those criticisms. 537 00:29:11,760 --> 00:29:14,560 Speaker 3: I love that question because like, oh, you're playing God. No, no, no, 538 00:29:14,760 --> 00:29:18,200 Speaker 3: We've been playing god for one hundred years. Agriculture is 539 00:29:18,240 --> 00:29:20,280 Speaker 3: not the natural state of planet Earth. 540 00:29:20,360 --> 00:29:21,600 Speaker 4: It's a human invention. 541 00:29:22,240 --> 00:29:27,640 Speaker 3: Look, we scientific community have the responsibility to be extraordinarily 542 00:29:27,680 --> 00:29:31,400 Speaker 3: transparent about the mechanism of action, about the testing that's 543 00:29:31,400 --> 00:29:33,600 Speaker 3: been done, about how we've done it, about why we 544 00:29:33,680 --> 00:29:38,200 Speaker 3: feel so strongly that our products are safe and effective 545 00:29:38,240 --> 00:29:41,360 Speaker 3: and better for society and for nature than the products 546 00:29:41,360 --> 00:29:44,080 Speaker 3: that we're replacing. So, if we're going to sustain ten 547 00:29:44,160 --> 00:29:47,280 Speaker 3: billion people on this planet, we need industrial agriculture. It's 548 00:29:47,320 --> 00:29:50,080 Speaker 3: no way around it. And if we're going to do that, 549 00:29:50,280 --> 00:29:54,040 Speaker 3: it's much better to spray something that is highly targeted, 550 00:29:54,280 --> 00:29:58,080 Speaker 3: that is safe, that is a natural pathway, that is bithgradable, 551 00:29:58,280 --> 00:30:01,600 Speaker 3: that does not accumulate raise some chemical that is derived 552 00:30:01,640 --> 00:30:04,960 Speaker 3: from oil that is going to drill a hole or 553 00:30:05,400 --> 00:30:08,360 Speaker 3: destroy the brain of every insect that it comes in 554 00:30:08,400 --> 00:30:11,959 Speaker 3: contact with. If I had my choice, I would move 555 00:30:12,000 --> 00:30:14,080 Speaker 3: to a different planet, and I would keep the population 556 00:30:14,280 --> 00:30:15,760 Speaker 3: low and we would all leave off the land. 557 00:30:15,880 --> 00:30:17,480 Speaker 4: Okay, that's not a choice we have. 558 00:30:17,840 --> 00:30:21,040 Speaker 3: And we have a responsibility to another nine billion humans 559 00:30:21,360 --> 00:30:26,080 Speaker 3: to provide them with clean, inexpensive, sustainably grown food. That's 560 00:30:26,160 --> 00:30:28,840 Speaker 3: the state of reality. I love people who argue that 561 00:30:29,160 --> 00:30:33,080 Speaker 3: society's gone wrong. Okay, great, we know all right. It's 562 00:30:33,120 --> 00:30:35,600 Speaker 3: not our responsibility to bitch and wine about it. It's our 563 00:30:35,640 --> 00:30:36,840 Speaker 3: responsibility to fix it. 564 00:30:37,360 --> 00:30:40,640 Speaker 1: We like bold predictions on this show. You have one 565 00:30:40,720 --> 00:30:45,600 Speaker 1: very bold prediction earlier about effectively curing cancer within our lifetimes. 566 00:30:45,880 --> 00:30:49,600 Speaker 1: What's your bold prediction for where this RNA technology might 567 00:30:49,680 --> 00:30:50,800 Speaker 1: lead us within our lifetimes? 568 00:30:51,240 --> 00:30:53,160 Speaker 3: Well, I think green Light is going to have dozens 569 00:30:53,160 --> 00:30:54,320 Speaker 3: of products in the market. 570 00:30:54,760 --> 00:30:58,520 Speaker 6: I think that we will provide tools to farmers in 571 00:30:58,640 --> 00:31:03,240 Speaker 6: every continent, will allow them to add more tools to 572 00:31:03,400 --> 00:31:07,120 Speaker 6: their toolkit to deal with destructive bests. 573 00:31:08,280 --> 00:31:13,800 Speaker 4: What I can't tell you is if other companies will follow. 574 00:31:13,480 --> 00:31:16,760 Speaker 3: Suit and come up with other biological solutions that are 575 00:31:16,920 --> 00:31:18,360 Speaker 3: as good as effective. 576 00:31:17,960 --> 00:31:19,200 Speaker 4: As ours are. 577 00:31:20,320 --> 00:31:25,200 Speaker 3: My hope is they will, because farmers need them. Chemicals 578 00:31:26,000 --> 00:31:28,440 Speaker 3: are on their way out, whether we like it or not. 579 00:31:28,640 --> 00:31:31,240 Speaker 3: They are just not working anymore. 580 00:31:31,880 --> 00:31:35,040 Speaker 1: You opened this conversation talking about growing up in a 581 00:31:35,040 --> 00:31:39,600 Speaker 1: middle class house in Mexico and with Monica got very sick. 582 00:31:39,680 --> 00:31:41,000 Speaker 1: She said to you know, we didn't send you to 583 00:31:41,320 --> 00:31:44,600 Speaker 1: Boston for no reason. What do you think that your 584 00:31:45,080 --> 00:31:48,040 Speaker 1: global perspective? I mean, the fact that you grew up 585 00:31:48,160 --> 00:31:51,920 Speaker 1: in Mexico brings you as a technologist. 586 00:31:52,760 --> 00:31:55,040 Speaker 3: Yeah, it's really interesting and it's hard not to get 587 00:31:55,080 --> 00:31:56,040 Speaker 3: political about this. 588 00:31:56,160 --> 00:31:58,760 Speaker 4: But disease knows no boundaries. 589 00:31:59,400 --> 00:32:03,520 Speaker 3: Disease in any form, whether it's human disease, plant disease, 590 00:32:03,600 --> 00:32:07,400 Speaker 3: crop disease, animal disease doesn't care about the lines that 591 00:32:07,440 --> 00:32:09,840 Speaker 3: we humans have artificially painted on maps. 592 00:32:11,120 --> 00:32:14,440 Speaker 4: They don't care about what rays you are. Cancer affects 593 00:32:14,480 --> 00:32:18,520 Speaker 4: every race more or less equally. They don't care whether 594 00:32:18,560 --> 00:32:22,600 Speaker 4: you were born in the US or not. It's global. 595 00:32:23,040 --> 00:32:27,800 Speaker 3: We are fighting global battles, and we are increasingly using 596 00:32:28,320 --> 00:32:32,760 Speaker 3: local armies. Can't find a global battle using local armies. 597 00:32:32,840 --> 00:32:33,800 Speaker 4: You need to be global. 598 00:32:34,640 --> 00:32:37,480 Speaker 3: You need to make the tools that you have affordable 599 00:32:37,480 --> 00:32:41,360 Speaker 3: and accessible in the US to everybody. It is the 600 00:32:41,520 --> 00:32:43,520 Speaker 3: right thing to do. It is the only way in 601 00:32:43,520 --> 00:32:47,160 Speaker 3: which you can achieve global equilibrium. We have people from 602 00:32:47,200 --> 00:32:49,480 Speaker 3: one hundred countries working at Greenland, and we're only three 603 00:32:49,560 --> 00:32:50,160 Speaker 3: hundred people. 604 00:32:50,640 --> 00:32:53,640 Speaker 4: Science is not Science is global. 605 00:32:53,880 --> 00:32:57,640 Speaker 3: No matter what religion you are or what political system 606 00:32:57,680 --> 00:33:00,640 Speaker 3: you subscribe to, it is our responsibility to think globally 607 00:33:00,680 --> 00:33:03,600 Speaker 3: because these global problems affect us all. And so my 608 00:33:03,840 --> 00:33:06,800 Speaker 3: mission has always been from day one to make all 609 00:33:06,840 --> 00:33:09,400 Speaker 3: these solutions, whether it's in cancer, whether it's in our 610 00:33:09,440 --> 00:33:11,000 Speaker 3: ability to grow food global. 611 00:33:11,840 --> 00:33:14,640 Speaker 4: Andrew, thank you, thanks my pleasure, Thank you so much. 612 00:33:31,120 --> 00:33:34,040 Speaker 1: For tech Stuff. I'm as Valoshian and I'm Kara Price. 613 00:33:34,520 --> 00:33:37,640 Speaker 2: This episode was produced by Eliza Dennis and Adriana Tapia. 614 00:33:38,160 --> 00:33:41,800 Speaker 2: It was executive produced by me Ozwaaloshan and Kate Osborne 615 00:33:41,800 --> 00:33:46,000 Speaker 2: for Kaleidoscope and Katrina Norvell for iHeart Podcasts. Jack Insley 616 00:33:46,040 --> 00:33:48,480 Speaker 2: mixed this episode and Kyle Murdoch wrote our theme song. 617 00:33:48,880 --> 00:33:51,560 Speaker 1: Join us on Friday for the Weekend Tech when Karen 618 00:33:51,600 --> 00:33:53,800 Speaker 1: and I will run through the tech headlines you may 619 00:33:53,840 --> 00:33:54,320 Speaker 1: have missed. 620 00:33:54,680 --> 00:33:57,080 Speaker 2: Please rate, review, and reach out to us at tech 621 00:33:57,080 --> 00:34:09,680 Speaker 2: Stuff podcast at gmail dot com.