1 00:00:00,667 --> 00:00:02,770 So, well, I do applied math, 2 00:00:02,770 --> 00:00:04,294 and this is a peculiar problem 3 00:00:04,294 --> 00:00:06,467 for anyone who does applied math, is that 4 00:00:06,467 --> 00:00:08,400 we are like management consultants. 5 00:00:08,400 --> 00:00:10,346 No one knows what the hell we do. 6 00:00:10,346 --> 00:00:12,620 So I am going to give you some -- attempt today 7 00:00:12,620 --> 00:00:14,913 to try and explain to you what I do. 8 00:00:14,913 --> 00:00:18,234 So, dancing is one of the most human of activities. 9 00:00:18,234 --> 00:00:21,916 We delight at ballet virtuosos and tap dancers 10 00:00:21,916 --> 00:00:23,064 you will see later on. 11 00:00:23,064 --> 00:00:25,754 Now, ballet requires an extraordinary level of expertise 12 00:00:25,754 --> 00:00:28,668 and a high level of skill, 13 00:00:28,668 --> 00:00:31,199 and probably a level of initial suitability 14 00:00:31,199 --> 00:00:33,046 that may well have a genetic component to it. 15 00:00:33,046 --> 00:00:36,439 Now, sadly, neurological disorders such as Parkinson's disease 16 00:00:36,439 --> 00:00:38,526 gradually destroy this extraordinary ability, 17 00:00:38,526 --> 00:00:40,849 as it is doing to my friend Jan Stripling, who was 18 00:00:40,849 --> 00:00:43,816 a virtuoso ballet dancer in his time. 19 00:00:43,816 --> 00:00:46,870 So great progress and treatment has been made over the years. 20 00:00:46,870 --> 00:00:49,814 However, there are 6.3 million people worldwide 21 00:00:49,814 --> 00:00:53,262 who have the disease, and they have to live with 22 00:00:53,262 --> 00:00:55,830 incurable weakness, tremor, rigidity 23 00:00:55,830 --> 00:00:57,687 and the other symptoms that go along with the disease, 24 00:00:57,687 --> 00:01:00,070 so what we need are objective tools 25 00:01:00,070 --> 00:01:03,127 to detect the disease before it's too late. 26 00:01:03,127 --> 00:01:05,681 We need to be able to measure progression objectively, 27 00:01:05,681 --> 00:01:08,854 and ultimately, the only way we're going to know 28 00:01:08,854 --> 00:01:11,046 when we actually have a cure is when we have 29 00:01:11,046 --> 00:01:14,444 an objective measure that can answer that for sure. 30 00:01:14,444 --> 00:01:17,294 But frustratingly, with Parkinson's disease 31 00:01:17,294 --> 00:01:19,647 and other movement disorders, there are no biomarkers, 32 00:01:19,647 --> 00:01:21,876 so there's no simple blood test that you can do, 33 00:01:21,876 --> 00:01:23,678 and the best that we have is like 34 00:01:23,678 --> 00:01:25,919 this 20-minute neurologist test. 35 00:01:25,919 --> 00:01:28,377 You have to go to the clinic to do it. It's very, very costly, 36 00:01:28,377 --> 00:01:31,134 and that means that, outside the clinical trials, 37 00:01:31,134 --> 00:01:33,862 it's just never done. It's never done. 38 00:01:33,862 --> 00:01:36,939 But what if patients could do this test at home? 39 00:01:36,939 --> 00:01:39,037 Now, that would actually save on a difficult trip to the clinic, 40 00:01:39,037 --> 00:01:43,291 and what if patients could do that test themselves, right? 41 00:01:43,291 --> 00:01:45,211 No expensive staff time required. 42 00:01:45,211 --> 00:01:46,629 Takes about $300, by the way, 43 00:01:46,629 --> 00:01:48,622 in the neurologist's clinic to do it. 44 00:01:48,622 --> 00:01:51,303 So what I want to propose to you as an unconventional way 45 00:01:51,303 --> 00:01:52,817 in which we can try to achieve this, 46 00:01:52,817 --> 00:01:54,625 because, you see, in one sense, at least, 47 00:01:54,625 --> 00:01:57,881 we are all virtuosos like my friend Jan Stripling. 48 00:01:57,881 --> 00:02:01,636 So here we have a video of the vibrating vocal folds. 49 00:02:01,636 --> 00:02:04,865 Now, this is healthy and this is somebody making speech sounds, 50 00:02:04,865 --> 00:02:08,329 and we can think of ourselves as vocal ballet dancers, 51 00:02:08,329 --> 00:02:10,543 because we have to coordinate all of these vocal organs 52 00:02:10,543 --> 00:02:12,838 when we make sounds, and we all actually 53 00:02:12,838 --> 00:02:15,134 have the genes for it. FoxP2, for example. 54 00:02:15,134 --> 00:02:17,847 And like ballet, it takes an extraordinary level of training. 55 00:02:17,847 --> 00:02:20,432 I mean, just think how long it takes a child to learn to speak. 56 00:02:20,432 --> 00:02:22,814 From the sound, we can actually track 57 00:02:22,814 --> 00:02:25,095 the vocal fold position as it vibrates, 58 00:02:25,095 --> 00:02:27,638 and just as the limbs are affected in Parkinson's, 59 00:02:27,638 --> 00:02:30,419 so too are the vocal organs. 60 00:02:30,419 --> 00:02:32,299 So on the bottom trace, you can see an example of 61 00:02:32,299 --> 00:02:33,997 irregular vocal fold tremor. 62 00:02:33,997 --> 00:02:35,165 We see all the same symptoms. 63 00:02:35,165 --> 00:02:38,095 We see vocal tremor, weakness and rigidity. 64 00:02:38,095 --> 00:02:40,199 The speech actually becomes quieter and more breathy 65 00:02:40,199 --> 00:02:42,432 after a while, and that's one of the example symptoms of it. 66 00:02:42,432 --> 00:02:45,279 So these vocal effects can actually be quite subtle, 67 00:02:45,279 --> 00:02:48,495 in some cases, but with any digital microphone, 68 00:02:48,495 --> 00:02:51,040 and using precision voice analysis software 69 00:02:51,040 --> 00:02:53,449 in combination with the latest in machine learning, 70 00:02:53,449 --> 00:02:55,027 which is very advanced by now, 71 00:02:55,027 --> 00:02:57,913 we can now quantify exactly where somebody lies 72 00:02:57,913 --> 00:03:00,794 on a continuum between health and disease 73 00:03:00,794 --> 00:03:03,390 using voice signals alone. 74 00:03:03,390 --> 00:03:05,704 So these voice-based tests, how do they stack up against 75 00:03:05,704 --> 00:03:07,854 expert clinical tests? We'll, they're both non-invasive. 76 00:03:07,854 --> 00:03:11,836 The neurologist's test is non-invasive. They both use existing infrastructure. 77 00:03:11,836 --> 00:03:14,840 You don't have to design a whole new set of hospitals to do it. 78 00:03:14,840 --> 00:03:17,142 And they're both accurate. Okay, but in addition, 79 00:03:17,142 --> 00:03:20,469 voice-based tests are non-expert. 80 00:03:20,469 --> 00:03:22,461 That means they can be self-administered. 81 00:03:22,461 --> 00:03:25,041 They're high-speed, take about 30 seconds at most. 82 00:03:25,041 --> 00:03:27,335 They're ultra-low cost, and we all know what happens. 83 00:03:27,335 --> 00:03:29,775 When something becomes ultra-low cost, 84 00:03:29,775 --> 00:03:32,071 it becomes massively scalable. 85 00:03:32,071 --> 00:03:35,746 So here are some amazing goals that I think we can deal with now. 86 00:03:35,746 --> 00:03:38,172 We can reduce logistical difficulties with patients. 87 00:03:38,172 --> 00:03:40,484 No need to go to the clinic for a routine checkup. 88 00:03:40,484 --> 00:03:42,804 We can do high-frequency monitoring to get objective data. 89 00:03:42,804 --> 00:03:46,909 We can perform low-cost mass recruitment for clinical trials, 90 00:03:46,909 --> 00:03:49,024 and we can make population-scale screening 91 00:03:49,024 --> 00:03:50,620 feasible for the first time. 92 00:03:50,620 --> 00:03:52,822 We have the opportunity to start to search 93 00:03:52,822 --> 00:03:56,363 for the early biomarkers of the disease before it's too late. 94 00:03:56,363 --> 00:03:59,121 So, taking the first steps towards this today, 95 00:03:59,121 --> 00:04:01,247 we're launching the Parkinson's Voice Initiative. 96 00:04:01,247 --> 00:04:03,479 With Aculab and PatientsLikeMe, we're aiming 97 00:04:03,479 --> 00:04:05,407 to record a very large number of voices worldwide 98 00:04:05,407 --> 00:04:08,547 to collect enough data to start to tackle these four goals. 99 00:04:08,547 --> 00:04:10,247 We have local numbers accessible to three quarters 100 00:04:10,247 --> 00:04:11,857 of a billion people on the planet. 101 00:04:11,857 --> 00:04:14,934 Anyone healthy or with Parkinson's can call in, cheaply, 102 00:04:14,934 --> 00:04:17,073 and leave recordings, a few cents each, 103 00:04:17,073 --> 00:04:19,263 and I'm really happy to announce that we've already hit 104 00:04:19,263 --> 00:04:22,806 six percent of our target just in eight hours. 105 00:04:22,806 --> 00:04:26,557 Thank you. (Applause) 106 00:04:26,557 --> 00:04:32,877 (Applause) 107 00:04:32,877 --> 00:04:36,452 Tom Rielly: So Max, by taking all these samples of, 108 00:04:36,452 --> 00:04:39,228 let's say, 10,000 people, 109 00:04:39,228 --> 00:04:42,082 you'll be able to tell who's healthy and who's not? 110 00:04:42,082 --> 00:04:43,767 What are you going to get out of those samples? 111 00:04:43,767 --> 00:04:45,597 Max Little: Yeah. Yeah. So what will happen is that, 112 00:04:45,597 --> 00:04:47,254 during the call you have to indicate whether or not 113 00:04:47,254 --> 00:04:48,521 you have the disease or not, you see. TR: Right. 114 00:04:48,521 --> 00:04:51,028 ML: You see, some people may not do it. They may not get through it. 115 00:04:51,028 --> 00:04:53,745 But we'll get a very large sample of data that is collected 116 00:04:53,745 --> 00:04:57,153 from all different circumstances, and it's getting it 117 00:04:57,153 --> 00:04:59,058 in different circumstances that matter because then 118 00:04:59,058 --> 00:05:02,442 we are looking at ironing out the confounding factors, 119 00:05:02,442 --> 00:05:04,603 and looking for the actual markers of the disease. 120 00:05:04,603 --> 00:05:07,100 TR: So you're 86 percent accurate right now? 121 00:05:07,100 --> 00:05:08,294 ML: It's much better than that. 122 00:05:08,294 --> 00:05:10,014 Actually, my student Thanasis, I have to plug him, 123 00:05:10,014 --> 00:05:11,884 because he's done some fantastic work, 124 00:05:11,884 --> 00:05:15,654 and now he has proved that it works over the mobile telephone network as well, 125 00:05:15,654 --> 00:05:19,044 which enables this project, and we're getting 99 percent accuracy. 126 00:05:19,044 --> 00:05:20,620 TR: Ninety-nine. Well, that's an improvement. 127 00:05:20,620 --> 00:05:22,821 So what that means is that people will be able to — 128 00:05:22,821 --> 00:05:24,673 ML: (Laughs) 129 00:05:24,673 --> 00:05:26,579 TR: People will be able to call in from their mobile phones 130 00:05:26,579 --> 00:05:29,651 and do this test, and people with Parkinson's could call in, 131 00:05:29,651 --> 00:05:32,521 record their voice, and then their doctor can check up 132 00:05:32,521 --> 00:05:35,202 on their progress, see where they're doing in this course of the disease. 133 00:05:35,202 --> 00:05:36,172 ML: Absolutely. 134 00:05:36,172 --> 00:05:37,915 TR: Thanks so much. Max Little, everybody. 135 00:05:37,915 --> 00:05:43,072 ML: Thanks, Tom. (Applause)