WEBVTT - Ep 81 "How close are we to longevity?" 0:00:05.080 --> 0:00:08.559 We know so much about biology nowadays, so why is 0:00:08.600 --> 0:00:12.920 it currently so difficult to figure out how to make 0:00:13.000 --> 0:00:16.680 a person live longer? I mean, we know how to 0:00:16.720 --> 0:00:19.840 do this in worms and often in mice, but why 0:00:19.920 --> 0:00:24.919 is the study of extending lifespans so hard in humans? 0:00:25.600 --> 0:00:28.400 Why are there so few companies studying this? And what 0:00:28.560 --> 0:00:32.360 is the future of longevity research and what would it 0:00:32.400 --> 0:00:39.720 be like to live a much longer life. Welcome to 0:00:39.760 --> 0:00:43.199 Inner Cosmos with me David Eagleman. I'm a neuroscientist and 0:00:43.240 --> 0:00:46.400 an author at Stanford, and in these episodes we sail 0:00:46.560 --> 0:00:50.040 deeply into our three pound universe to uncover some of 0:00:50.080 --> 0:01:04.480 the most surprising aspects of our lives. Today's episode reaches 0:01:04.520 --> 0:01:09.520 beyond neurobiology to our biology more generally and specifically about 0:01:09.560 --> 0:01:13.200 whether we could live a lot longer if we just 0:01:13.360 --> 0:01:17.280 understood which of the billions of tiny molecular signals in 0:01:17.319 --> 0:01:21.560 a cell mattered for the aging process, and which ones 0:01:21.600 --> 0:01:24.639 we could grab a hold of and tweak, and how 0:01:24.800 --> 0:01:28.279 the whole network might shift in a way that keeps 0:01:28.360 --> 0:01:33.479 everything young and optimized. It's often said that the only 0:01:33.520 --> 0:01:38.039 two certainties in life are death and taxes, but it 0:01:38.120 --> 0:01:41.360 turns out the third certainty is that people will put 0:01:41.400 --> 0:01:44.800 in a lot of work to avoid those two things. 0:01:45.360 --> 0:01:49.520 So today's episode is about the endeavor of living longer. 0:01:49.640 --> 0:01:54.200 This is not about immortality, in other words, never dying. Instead, 0:01:54.200 --> 0:02:00.840 this is about longevity, increasing your lifespan. So to introduce 0:02:00.840 --> 0:02:03.800 today's topic, I'm going to read a short story that 0:02:03.840 --> 0:02:07.880 I wrote some years ago and originally read on BBC Radio. 0:02:08.120 --> 0:02:10.640 I have been asked to speak here at the funeral 0:02:11.360 --> 0:02:14.520 of a one hundred and twenty two year old. As 0:02:14.560 --> 0:02:17.000 many of you know, I have been asked to speak 0:02:17.080 --> 0:02:20.680 not only because of my expertise in the history of aging, 0:02:21.200 --> 0:02:25.400 but also because she is a distant relative. She is 0:02:25.480 --> 0:02:31.520 my great great great great granddaughter. Her death is tragic 0:02:31.600 --> 0:02:34.760 to us, not only because she has died so young, 0:02:35.360 --> 0:02:38.359 but because she was haunted her whole life by an 0:02:38.400 --> 0:02:42.359 incurable blood disorder and was well aware that she would 0:02:42.400 --> 0:02:45.639 not have a long life. I have been asked by 0:02:45.639 --> 0:02:49.359 her parents to perhaps ease the tragedy of her young 0:02:49.440 --> 0:02:53.680 death by thinking back to the time when a life 0:02:53.680 --> 0:02:56.799 span of one hundred and twenty two years was not 0:02:56.919 --> 0:03:02.000 considered short but unusually long. At that time, not so 0:03:02.160 --> 0:03:06.200 long ago, it was not typical for people to earn 0:03:06.320 --> 0:03:11.000 multiple PhDs or to be citizens of multiple countries in 0:03:11.080 --> 0:03:16.480 their brief twinklings of a lifetime. They tended to mature faster, 0:03:17.120 --> 0:03:20.359 moving out of the house in their teens or twenties, 0:03:20.800 --> 0:03:24.920 having families of their own by their thirties, retiring in 0:03:25.000 --> 0:03:29.640 their sixties, and dying shortly thereafter, with only enough time 0:03:30.120 --> 0:03:34.480 for one career and one family. All things ran on 0:03:34.720 --> 0:03:40.600 an accelerated schedule. In each generation, they had to relearn politics. 0:03:40.640 --> 0:03:45.560 They had not experienced the patterns before. Everything seemed new, 0:03:45.880 --> 0:03:51.320 every message of progress seemed inspired. Of course, this had 0:03:51.360 --> 0:03:56.200 one advantage. People did not burn with vendettas that belonged 0:03:56.320 --> 0:04:01.440 to distant times. Instead, they died quick, and their children 0:04:01.720 --> 0:04:07.280 held different attitudes. Politics could take sharper turns. We all 0:04:07.360 --> 0:04:10.880 know what it's like to spot a forgotten lover a 0:04:10.960 --> 0:04:15.120 century later, but imagine what it was like to never 0:04:15.200 --> 0:04:20.920 achieve any meaningful temporal distance from your past choices. Everything 0:04:21.000 --> 0:04:25.560 you've done is there at your heels to haunt you. Obviously, 0:04:25.960 --> 0:04:30.880 our mistakes make life educational, but as we know, getting 0:04:31.000 --> 0:04:35.760 second chances allows us to endure it. People with rapid 0:04:35.839 --> 0:04:40.359 life spans felt quite close to their recent ancestors because 0:04:40.400 --> 0:04:44.280 they only had four of them alive at best. We 0:04:44.440 --> 0:04:48.800 typically have five hundred and twelve great great great great 0:04:48.839 --> 0:04:54.240 great grandparents alive, enough to fill a good sized lecture hall. Therefore, 0:04:54.680 --> 0:05:00.440 relationships sink to genetic interest rather than emotional salience based 0:05:00.480 --> 0:05:04.240 on scarcity. For those with only a handful of decades, 0:05:04.600 --> 0:05:08.719 the idea of staying with one partner throughout life was 0:05:08.800 --> 0:05:12.800 something to be devoutly hoped for, and people would declare 0:05:12.839 --> 0:05:16.279 that as part of their wedding vows. In modern times, 0:05:16.640 --> 0:05:20.000 we know of several couples who have celebrated three hundred 0:05:20.080 --> 0:05:24.080 year anniversaries, but it's obviously much more common to enjoy 0:05:24.200 --> 0:05:27.960 dozens of marriages. As we mourn this loss today, we 0:05:28.000 --> 0:05:32.200 should remember that those with a scarcity of years had 0:05:32.240 --> 0:05:37.040 no shortage of one thing novelty. For the rest of us. 0:05:37.560 --> 0:05:42.320 Time speeds up as we grow older. At my age, 0:05:42.360 --> 0:05:47.839 decades pass like summers. We have seen life's patterns many times. 0:05:48.240 --> 0:05:52.480 We have traveled, we have married, we have wrangled, made peace, 0:05:53.080 --> 0:05:59.560 failed friends, impressed strangers, seen new groups rise and dwindle, 0:06:00.160 --> 0:06:04.240 sought new narratives about our abilities and our purpose. But 0:06:04.320 --> 0:06:08.440 in the end, as things become less new, we write 0:06:08.480 --> 0:06:16.320 down fewer memories, unique experiences become increasingly scarce, And so 0:06:16.920 --> 0:06:21.000 as we mourn this life cut short here today we 0:06:21.120 --> 0:06:26.919 can be thankful that for her, at least everything remained novel. 0:06:27.800 --> 0:06:31.760 She did not drown in the ocean of time. Every 0:06:31.839 --> 0:06:36.640 day she continued to find new seashells at the edges 0:06:37.080 --> 0:06:41.039 of its low lying shores. Okay, so that was my 0:06:41.160 --> 0:06:45.120 short story about the social changes that would follow if 0:06:45.160 --> 0:06:48.440 we were to succeed at longevity science. How would that 0:06:48.560 --> 0:06:54.000 change our lives? Our decisions are traditions, how we spend 0:06:54.040 --> 0:06:59.600 our time. But today I want to ask, is longevity possible? 0:07:00.160 --> 0:07:03.200 Where are we in terms of the science. When you 0:07:03.240 --> 0:07:07.159 look at life expectancy at birth, let's say two hundred 0:07:07.240 --> 0:07:10.720 years ago, you find that it was about twenty nine 0:07:10.840 --> 0:07:13.840 years old. At the beginning of the nineteenth century, even 0:07:13.840 --> 0:07:17.000 the healthiest countries in the world had a life expectancy 0:07:17.280 --> 0:07:21.880 no longer than forty years. Now in the twenty first century, 0:07:21.960 --> 0:07:25.960 the world average is seventy three years. That's a huge 0:07:26.000 --> 0:07:29.600 difference in just two hundred years. Is it due to 0:07:29.920 --> 0:07:35.240 miraculous medical advances? Well, not exactly. Largely it's due to 0:07:35.640 --> 0:07:39.880 simple advances like being able to control diarrhea and vomiting 0:07:40.360 --> 0:07:45.200 and having antibiotics, and also on the simple public health 0:07:45.200 --> 0:07:50.640 initiatives like sanitation and clean water and managing sewage. These 0:07:50.680 --> 0:07:54.040 are the steps that have had massive impact in the 0:07:54.320 --> 0:07:59.640 expected lifespan. So we've seen astonishing progress. But keep in 0:07:59.680 --> 0:08:03.679 mind what we're talking about there is the average life span. 0:08:04.200 --> 0:08:08.120 We prevented people from dying young, and that cranked the 0:08:08.240 --> 0:08:12.560 average up and up, But the longest life spans, which 0:08:12.560 --> 0:08:17.880 are influenced by biological aging processes, they haven't really changed. 0:08:18.120 --> 0:08:22.440 People aren't generally growing older. In other words, a thousand 0:08:22.560 --> 0:08:25.320 years ago you could have lived until eighty five, and 0:08:25.400 --> 0:08:29.640 now you can live until eighty five. Despite all our advances, 0:08:30.240 --> 0:08:33.640 there seems to be an upper limit biologically in the 0:08:33.679 --> 0:08:37.120 low one hundreds. So at the moment we haven't yet 0:08:37.200 --> 0:08:42.400 found ways to significantly slow or reverse aging itself. There 0:08:42.400 --> 0:08:45.960 seems to be a biological sealing to human life, and 0:08:46.000 --> 0:08:50.120 this is presumably set by genetics and properties of ourselves 0:08:50.679 --> 0:08:54.760 that limit how long the human body can sustain itself. 0:08:54.880 --> 0:08:58.480 This is despite all the improvements in health and medical care. 0:08:59.080 --> 0:09:02.280 But on the lip side, we're living in a time 0:09:02.320 --> 0:09:05.600 where there are a lot of studies with worms, with mice, 0:09:05.640 --> 0:09:09.800 occasion with dogs or monkeys that seem to indicate there 0:09:09.840 --> 0:09:14.640 may be molecular solutions or at least helpers to the problem. 0:09:14.880 --> 0:09:17.880 If you follow the field or simply scan the news headlines, 0:09:17.920 --> 0:09:23.040 you'll see articles about drugs like rapamycin, or chemicals like restrol, 0:09:23.520 --> 0:09:27.760 or approaches like caloric restriction, and what you'll see is 0:09:27.800 --> 0:09:32.560 that in animal studies these seem to increase lifespan. So 0:09:32.640 --> 0:09:35.760 the question is should you be taking these drugs and 0:09:35.840 --> 0:09:39.319 changing your diet. Do the studies translate over to humans? 0:09:39.960 --> 0:09:42.200 And what dose should you go for or how many 0:09:42.520 --> 0:09:44.160 calories should you restrict? 0:09:45.000 --> 0:09:45.600 Well, these are. 0:09:45.559 --> 0:09:49.040 Questions that short news articles tend to skate over the 0:09:49.080 --> 0:09:52.520 complexity of and so to really understand the big picture, 0:09:53.000 --> 0:09:56.720 we need to talk to experts in the field of longevity, 0:09:57.320 --> 0:09:59.960 and that brings me to Martin borsch Jensen, a research 0:10:00.600 --> 0:10:03.560 who takes the position that if we can really understand 0:10:03.640 --> 0:10:08.640 the biological mechanisms of aging, that gives us our highest 0:10:08.800 --> 0:10:13.680 leverage for alleviating human disease. Martin got his PhD at 0:10:13.679 --> 0:10:17.160 the University of Copenhagen in aging research, then did a 0:10:17.200 --> 0:10:21.720 postdoc at the Buck Institute before becoming a biotech entrepreneur. 0:10:22.040 --> 0:10:25.320 He became the co founder and chief scientific officer at 0:10:25.480 --> 0:10:29.080 Gordian Biotechnology, which is a company that puts the study 0:10:29.080 --> 0:10:33.360 of longevity at the center. So here's my interview with Martin. 0:10:38.080 --> 0:10:41.559 So what is aging biologically? 0:10:42.520 --> 0:10:45.880 That is an unanswered question by the field of aging biology, right, 0:10:45.920 --> 0:10:47.840 So I think that's one of the core things here 0:10:47.920 --> 0:10:51.880 that nobody can tell you, Like, here is exactly how 0:10:51.920 --> 0:10:55.320 this works. You could sort of compare it to like 0:10:55.360 --> 0:10:59.640 what is society or civilization, what is the economy. It's 0:10:59.640 --> 0:11:01.920 sort of the complex thing where we know a lot 0:11:01.960 --> 0:11:07.160 of components and we know some key factors. But let's 0:11:08.280 --> 0:11:11.480 try to do our best here and say aging is 0:11:11.600 --> 0:11:14.960 some set of changes that happen in your body biologically 0:11:15.520 --> 0:11:20.320 that worsen your capacity for your body to restore itself 0:11:20.360 --> 0:11:24.959 to homeostasis is the technical term, but basically, like your 0:11:24.960 --> 0:11:27.480 body is in a certain state, and then the essence 0:11:27.559 --> 0:11:30.120 of life is that when something gets it out of 0:11:30.160 --> 0:11:32.959 that state, it sort of restores itself. Right, So if 0:11:33.000 --> 0:11:35.080 you drink too much, you have a hangover, your liver 0:11:35.160 --> 0:11:37.079 is going to work and so forth, and then you're 0:11:37.080 --> 0:11:39.160 going to be fine again. If you get influenza, you 0:11:39.160 --> 0:11:42.080 have an immune system that's designed to kill all of 0:11:42.120 --> 0:11:44.240 those viruses and then you're going to be fine again. 0:11:44.320 --> 0:11:47.120 And so that's sort of the return to homeostasis. And 0:11:47.160 --> 0:11:49.240 I would say aging is a set of changes that 0:11:49.320 --> 0:11:54.280 happen that lower your ability to like return to homeostasis, 0:11:54.360 --> 0:11:57.880 and then over time that combines with everything that you're 0:11:57.920 --> 0:12:01.080 going through in life to lead to you know, your 0:12:01.200 --> 0:12:04.280 organs failing in different ways and you get weaker, and 0:12:04.320 --> 0:12:06.960 you get slower and like all of those kinds of things. 0:12:07.280 --> 0:12:10.360 So a set of processes that lead to all of 0:12:10.400 --> 0:12:11.120 the bad things. 0:12:11.400 --> 0:12:13.040 And I want to heard you say that if we 0:12:13.040 --> 0:12:16.080 were all twenty eight years old, we wouldn't have all 0:12:16.120 --> 0:12:20.199 these departments in academic research institutes and hospitals and so on, 0:12:20.840 --> 0:12:24.120 because we would just need to address a few things. 0:12:24.760 --> 0:12:27.480 I think you mentioned testicular cancer a few other things, 0:12:27.520 --> 0:12:32.000 but we wouldn't need giant cancer departments MD Anderson and 0:12:32.040 --> 0:12:34.760 so on, because these are all things that come along 0:12:34.920 --> 0:12:36.160 with aging. 0:12:36.679 --> 0:12:39.160 Yeah, Like if you just look at the incident's rate 0:12:39.440 --> 0:12:43.320 of a lot of different diseases, you know, heart failure, 0:12:43.640 --> 0:12:46.000 how many people do you know had a heart attack 0:12:46.160 --> 0:12:49.320 like above age fifty, and how many people you know 0:12:49.400 --> 0:12:51.600 that had a heart attack was like below age fifty 0:12:51.679 --> 0:12:55.840 or below age thirty, right, and probably your anecdotal evidence 0:12:55.840 --> 0:12:59.480 they are sort of aligned with just the stats we have, 0:12:59.600 --> 0:13:01.400 which is, you know, like the rate goes up one 0:13:01.440 --> 0:13:06.000 thousandfold or ten thousandfold or something like that, Right, And so, yeah, 0:13:06.040 --> 0:13:08.720 when you are young, there's just a few things that 0:13:09.200 --> 0:13:11.240 affect you, and when you're old, there's a lot of 0:13:11.240 --> 0:13:14.319 things that affect you. And US healthcare spend is for 0:13:14.559 --> 0:13:19.120 trillion ish and like the majority of that fraction is 0:13:19.160 --> 0:13:22.960 for you know, like people who have age related diseases, 0:13:23.640 --> 0:13:25.760 often multiple age related diseases. 0:13:26.000 --> 0:13:30.080 Now, when people go about trying to research this, you know, 0:13:30.160 --> 0:13:33.000 it's limited in some way by the technologies that we have. 0:13:33.120 --> 0:13:35.440 And so what people have done over let's call it 0:13:35.480 --> 0:13:39.120 the last twenty years, is they look for particular biomarkers. 0:13:39.160 --> 0:13:41.800 So tell us about that and how it's evolved in 0:13:41.840 --> 0:13:45.080 the last couple of decades and what you're doing leading 0:13:45.120 --> 0:13:46.560 to what you're doing at Gordian. 0:13:47.080 --> 0:13:51.240 Yeah. Absolutely, So the field of like, hey, we can 0:13:51.320 --> 0:13:54.880 molecularly sort of study and manipulate aging is really only 0:13:54.920 --> 0:13:58.920 about three decades old. In the early nineties, there were 0:13:58.960 --> 0:14:02.199 some studies where our researchers changed a single gene and 0:14:02.280 --> 0:14:04.760 some worms and it made the worms live twice as long. 0:14:05.080 --> 0:14:07.320 And so before that it's like, well, what is aging 0:14:07.400 --> 0:14:09.120 and can we really change it? And so forth. But 0:14:09.160 --> 0:14:11.920 this shows that there is a way to regulate the 0:14:11.920 --> 0:14:15.040 aging process that's already innate in sort of the way 0:14:15.040 --> 0:14:19.680 our biology functions, and so that's cool. And so in 0:14:19.680 --> 0:14:23.160 a worm, it lives three weeks after you extended the lifespan, right, 0:14:23.200 --> 0:14:25.400 so you can you can do studies where you're just like, 0:14:25.480 --> 0:14:28.040 does it live longer? Is it healthier as you get 0:14:28.040 --> 0:14:31.760 closer and closer to humans? That's sort of impractical, right, Like, 0:14:31.840 --> 0:14:34.920 aging by definition takes a lifetime, and so you don't 0:14:34.960 --> 0:14:37.320 want to do forty year studies all the time. And 0:14:37.400 --> 0:14:39.840 so people have done a couple of things in response 0:14:39.880 --> 0:14:43.280 to that. One is like, find some area of biology 0:14:43.280 --> 0:14:47.080 that like, this seems important. This accumulation of these sinesse 0:14:47.160 --> 0:14:50.320 and cells or these particular changes in your body seems important. 0:14:50.480 --> 0:14:52.560 We're just going to study them and then sort of 0:14:52.640 --> 0:14:55.400 like trust that they are important for the aging process. 0:14:55.680 --> 0:14:58.000 The other thing people have done is try to find. 0:14:59.240 --> 0:15:02.240 They're usually called like aging clocks, and so it's something 0:15:02.280 --> 0:15:05.280 that you could measure that when you look at it 0:15:05.360 --> 0:15:09.200 over time, it changes with age, and so you can 0:15:09.280 --> 0:15:12.720 use whatever the measurement is to tell you sort of 0:15:12.760 --> 0:15:15.960 like how far along is this person? Right, If we 0:15:16.000 --> 0:15:18.520 do an analogy to a company, maybe it's like you 0:15:18.560 --> 0:15:21.120 try to schedule a meeting with someone and whether they 0:15:21.120 --> 0:15:23.160 can take the meeting, and like it's a young startup, 0:15:23.160 --> 0:15:25.600 you can take the meeting in the next forty five minutes, 0:15:25.680 --> 0:15:28.800 and if it's like a giant one hundred thousand person company, 0:15:28.800 --> 0:15:30.040 it's going to take you a month and a half 0:15:30.120 --> 0:15:33.360 to So that's like a marker of the aging of 0:15:34.360 --> 0:15:36.360 you know, in this case the company. So we have those, 0:15:36.480 --> 0:15:40.960 we have multiple of those for sort of human aging. 0:15:41.680 --> 0:15:45.440 We don't yet have one where that when it responds, 0:15:45.640 --> 0:15:49.680 that's actually our aging changing versus it's measuring something that 0:15:49.720 --> 0:15:54.080 happens alongside aging. But it doesn't it doesn't necessarily mean 0:15:54.120 --> 0:15:56.360 you're better off if the number goes down. So that's 0:15:56.360 --> 0:15:58.120 sort of the main limitation here. 0:15:58.000 --> 0:16:01.760 As in I do something so that at this large company, 0:16:02.080 --> 0:16:04.800 I can get a meeting quickly, but it doesn't change 0:16:04.840 --> 0:16:06.760 the age of the company. It's still an old company, 0:16:06.800 --> 0:16:09.000 even though I did some tweak to make the meeting 0:16:09.040 --> 0:16:10.560 happen right, Like you. 0:16:10.520 --> 0:16:13.240 Could set up so that like every calendar in that 0:16:13.360 --> 0:16:17.720 company must auto accept a meeting immediately. However, the company's 0:16:18.120 --> 0:16:21.480 ability to actually act on what happens in the meeting 0:16:21.680 --> 0:16:24.160 is not changed. The amount of bureaucracy is the same. 0:16:24.640 --> 0:16:27.760 And so you could optimize that one all you want, 0:16:27.800 --> 0:16:30.240 but it doesn't really do what you wanted to do. 0:16:30.400 --> 0:16:33.080 So the point here is that even if you do 0:16:33.240 --> 0:16:37.480 something that changes these biomarkers, your cell might be just 0:16:37.520 --> 0:16:41.600 as old and you know, having all the ills of senescence, 0:16:42.040 --> 0:16:43.680 even though you think, hey, I fixed it. 0:16:44.240 --> 0:16:46.160 Yeah. Like, let's say, for example, a lot of these 0:16:46.200 --> 0:16:48.480 are blood tests, right, so they would measure stuff in 0:16:48.520 --> 0:16:51.160 immune cells, primarily because those are the ones circling around 0:16:51.200 --> 0:16:54.400 your blood. And so I imagine if any your immune 0:16:54.400 --> 0:16:56.840 cells will go and then when you have an infection, 0:16:57.000 --> 0:17:00.600 they'll divide and proliferate and create more that's target disinfection 0:17:00.640 --> 0:17:03.920 and so forth. Imagine that what a given aging clock 0:17:04.000 --> 0:17:07.600 measures is actually how many times has this cell divided 0:17:08.000 --> 0:17:12.360 That will tend to go up as you age, but whatever, 0:17:12.600 --> 0:17:17.320 like TikTok tracks that, it's not the whole aging process. 0:17:17.359 --> 0:17:19.160 There's all this other stuff going on in all these 0:17:19.160 --> 0:17:21.200 other organs. And so I think that's the key thing 0:17:21.280 --> 0:17:24.200 that sort of currently we need to address with these 0:17:24.240 --> 0:17:26.840 kinds of aging clocks before we can really reliably use 0:17:26.840 --> 0:17:31.920 them to accelerate the research, is how specific are they 0:17:32.520 --> 0:17:36.640 for predicting the changes that we want to use them for. 0:17:37.400 --> 0:17:40.600 And I know that like everything in biology, you know, 0:17:40.640 --> 0:17:44.200 what we're looking at are these vast networks that bankrupt 0:17:44.200 --> 0:17:48.560 our language. They're so complex, and so what we've been 0:17:48.640 --> 0:17:53.040 doing over the past decades is looking for little places 0:17:53.080 --> 0:17:55.160 in the network where we say, aha, this is maybe 0:17:55.240 --> 0:17:59.240 the sign that we need to read right, But what's 0:17:59.320 --> 0:18:01.439 the what's your approach to this? 0:18:01.440 --> 0:18:04.840 Which I think is very clever. Yeah, absolutely so I 0:18:04.880 --> 0:18:08.240 spent you know, after this sort of existentialist space, I 0:18:08.280 --> 0:18:10.919 went into academic research. I did a PhD at an 0:18:10.920 --> 0:18:14.359 aging institute, and I did postocical research and sort of 0:18:14.359 --> 0:18:18.119 heading on the academic track to be a professor, all 0:18:18.160 --> 0:18:21.040 like trying to figure out how does this work? You know, 0:18:21.040 --> 0:18:23.640 because like one approach to fixing a system, let's say 0:18:23.640 --> 0:18:26.120 a car or whatever is like, okay, well I understand 0:18:26.160 --> 0:18:28.639 what each piece does, and I can see where the 0:18:28.720 --> 0:18:30.639 broken thing is, and then I go in and I 0:18:30.760 --> 0:18:34.240 like fix that broken thing. So that's one approach which 0:18:34.280 --> 0:18:37.639 makes sense if you can like get to an understanding 0:18:37.640 --> 0:18:40.040 in your lifetime, and so if you sort of capitulate 0:18:40.119 --> 0:18:42.199 on that, which is honestly what I did. It's like 0:18:42.240 --> 0:18:44.280 there's so much biology, like we don't even know what 0:18:44.359 --> 0:18:46.959 we don't know yet, right, how do you find a 0:18:47.000 --> 0:18:51.200 solution if you don't have an understanding of the whole. 0:18:51.320 --> 0:18:54.520 And that's why the company I started with my co 0:18:54.560 --> 0:18:57.280 found of Francisco, it's called Gordian after the sort of 0:18:57.359 --> 0:18:59.879 legend of the Gordian nod where you try to untangle 0:18:59.880 --> 0:19:02.639 it but it's so complicated you can't untangle it, and 0:19:02.680 --> 0:19:06.560 then Alexander the then not yet Great, decides to cut 0:19:06.600 --> 0:19:09.960 through it instead and find an elegant solution that questions 0:19:10.000 --> 0:19:13.840 the assumptions. And so the biology version of that for 0:19:13.960 --> 0:19:17.240 Gordian is, you know, I had a knowledge of how 0:19:17.280 --> 0:19:19.719 complex everything was, and I knew that like, yeah, we 0:19:19.800 --> 0:19:22.440 don't actually know what aging is. I can't give you. 0:19:22.720 --> 0:19:25.679 Here's an accelerated version of aging that captures all the 0:19:25.720 --> 0:19:28.840 important parts, because we don't know all the important parts. 0:19:29.240 --> 0:19:33.080 And so if we want to find treatments that work 0:19:33.119 --> 0:19:36.119 for different age related diseases. And this is really important because, 0:19:36.320 --> 0:19:38.479 like we were talking about before, you know, most if 0:19:38.480 --> 0:19:41.240 you just look up like top ten causes of death 0:19:41.280 --> 0:19:44.160 in the US, seven of them, aging is the number 0:19:44.160 --> 0:19:47.240 one risk factor and the eighth one like diabetes. It's 0:19:47.320 --> 0:19:50.320 number two after diet, right, And if you just look 0:19:50.359 --> 0:19:52.159 at like our spend, what are the things that we 0:19:52.240 --> 0:19:54.480 can't cure, what are the things we're worried about, It's 0:19:54.480 --> 0:19:58.200 like not tuberculosis anymore, we did good, but it's all 0:19:58.200 --> 0:20:01.199 these age related diseases. And so so we've put a 0:20:01.200 --> 0:20:03.720 lot of money into trying to treat these diseases and 0:20:03.760 --> 0:20:08.280 find effective medicines, but we haven't succeeded in at scale yet. 0:20:08.560 --> 0:20:12.080 Maybe that's because these diseases, as we talked about before, 0:20:12.520 --> 0:20:15.600 they manifest in old people, and so some of these 0:20:15.600 --> 0:20:19.200 physiological changes that are happening with aging are critical for 0:20:19.280 --> 0:20:23.840 the disease, like being able to manifest and not being 0:20:23.960 --> 0:20:26.359 just like repaired. So if we do all of our 0:20:26.440 --> 0:20:31.359 drudge discovery in organisms that are young Let's say, you know, 0:20:31.440 --> 0:20:34.359 like some model organism in the lab that is young 0:20:34.400 --> 0:20:36.359 and we've sort of engineered it to get the disease. 0:20:36.440 --> 0:20:39.520 Let's take Alzheimer's. People often like have these animals that 0:20:39.600 --> 0:20:43.640 have like expressed the mutant proteins involved in the disease. 0:20:43.920 --> 0:20:46.040 These are mice, for example you're talking about. 0:20:46.119 --> 0:20:49.239 Yeah, exactly, And so we take these mice and we say, oh, 0:20:49.320 --> 0:20:53.200 let's find every mutation that like happens in Alzheimer's patient 0:20:53.240 --> 0:20:54.760 and throw all of them at the mice, and then 0:20:54.800 --> 0:20:57.919 it's going to get Alzheimer's really quickly. But it's not 0:20:57.960 --> 0:21:00.800 really Alzheimer's. It's like one specific dysfunction, and then we 0:21:00.840 --> 0:21:03.160 can fix that. Like we have good drugs to treat 0:21:03.200 --> 0:21:05.480 that in mice. We don't have good drugs to treat 0:21:05.520 --> 0:21:08.760 Alzheimer's in people because it's probably more complicated. 0:21:08.400 --> 0:21:13.119 Because the rest of the adult human has five million 0:21:13.240 --> 0:21:16.560 other biological issues going on at the same time. So 0:21:16.600 --> 0:21:21.080 those mutations in the giant network that's happening, you get 0:21:21.119 --> 0:21:23.719 different results then you do in a mouse who is 0:21:23.800 --> 0:21:26.560 otherwise young and perfect but has these mutations. 0:21:26.920 --> 0:21:30.000 Yeah, that's right. You know, like you get a flat tire, 0:21:30.560 --> 0:21:32.480 you know, driving to work and it's like it's fine, 0:21:32.520 --> 0:21:34.520 I can deal with this, right, but like you get 0:21:34.560 --> 0:21:37.359 a flat tire, like driving to the hospital with your 0:21:37.440 --> 0:21:39.720 kid after you lost your job, it's like you can't. 0:21:39.800 --> 0:21:42.120 You don't have the capacity to deal with this thing anymore. 0:21:42.119 --> 0:21:43.960 That's probably a lot of what happens in these age 0:21:44.000 --> 0:21:46.439 related diseases that like things aren't working as well, so 0:21:46.480 --> 0:21:49.320 you don't have the capacity to compensate for whatever is 0:21:49.359 --> 0:21:52.960 going wrong. Here's where we are. We've studied these diseases. 0:21:53.240 --> 0:21:57.199 We've forced ourselves to like use these simplified models of 0:21:57.280 --> 0:21:59.359 the disease because it's just not we didn't have a 0:21:59.359 --> 0:22:02.800 practical way of trying a lot of things otherwise, and 0:22:02.840 --> 0:22:05.280 then we failed. And so Gordian says, well, what if 0:22:05.320 --> 0:22:09.120 we had a way to go into the most realistic 0:22:09.200 --> 0:22:11.520 environment for the patient. What if we could instead of 0:22:11.600 --> 0:22:14.960 like making this disease in an animal model in this 0:22:15.040 --> 0:22:17.399 accelerated way, what if we could find an animal that 0:22:17.520 --> 0:22:20.280 has the same disease as the human and developed it 0:22:20.760 --> 0:22:23.239 over a long period of time the same way that 0:22:23.480 --> 0:22:26.280 humans do. And then we could test a lot of 0:22:26.320 --> 0:22:30.080 things there. And so for example, we could work with 0:22:30.440 --> 0:22:33.959 you know, for ostereothritis, which is one of the diseases 0:22:34.359 --> 0:22:37.159 that we're working on. A lot of people use have 0:22:37.200 --> 0:22:39.960 these young mice and you do surgical injury and whatever. 0:22:40.640 --> 0:22:44.399 We can find a horse that got ostereothritis from like 0:22:44.480 --> 0:22:48.199 running around and living life, and then we can study 0:22:48.240 --> 0:22:51.760 we can go in and see can we treat the 0:22:51.800 --> 0:22:54.600 osterothritis in this context, and it's much more like a 0:22:54.680 --> 0:22:59.320 human it's like an avatar for the human patient. Now, 0:22:59.640 --> 0:23:02.040 anyone could do that, like anyone can go find a 0:23:02.080 --> 0:23:05.199 whorse somewhere on a farm and then do this study. 0:23:05.320 --> 0:23:08.240 But the way that most studies are done, you have 0:23:08.320 --> 0:23:10.960 these large groups of animals with treatment A and large 0:23:10.960 --> 0:23:12.840 group of animal with treatment B, so that you can 0:23:12.880 --> 0:23:17.080 compare across the biological variability of the individual animals and stuff. 0:23:17.440 --> 0:23:21.560 That's just impractical. It's plausible, but it's like prohibitively expensive 0:23:21.680 --> 0:23:25.280 and like logistically challenging. And so Gordon started with the 0:23:25.320 --> 0:23:27.879 idea that like, we can actually do this if we 0:23:27.960 --> 0:23:31.679 invent a way to test hundreds of treatments in a 0:23:31.680 --> 0:23:34.520 single animal, and so that's the core of the company. 0:23:34.600 --> 0:23:38.199 We can go into the most predictive system for is 0:23:38.240 --> 0:23:41.199 this going to cure disease X and a patient, and 0:23:41.280 --> 0:23:43.080 then we can test a lot of things there, so 0:23:43.119 --> 0:23:45.760 we don't have to be very smart. I try to 0:23:45.760 --> 0:23:47.880 design it so that I can be not very smart 0:23:48.200 --> 0:23:50.760 and still succeed. And so the way we do that 0:23:50.920 --> 0:23:54.439 there's a lot of like cool biotechnology, and we have 0:23:54.560 --> 0:23:58.399 these like re engineered viruses that can deliver therapies to 0:23:58.480 --> 0:24:01.320 individual cells of the organ, and then we can like 0:24:01.680 --> 0:24:05.440 pull those cells out and measure the activity of every 0:24:05.520 --> 0:24:08.480 gene in that cell and then like predict, Okay, what 0:24:08.520 --> 0:24:11.640