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How Personalized Medicine Works · Stuff You Should Know

0:00
Speaker 1: All right, josh. So the first part of our winter
0:02
Speaker 1: tour is over a lot of fun. But we are
0:07
Speaker 1: going back out this weekend next to Atlanta. While we're
0:11
Speaker 1: not going anywhere, well, we're going down the road ten
0:14
Speaker 1: minutes from my house. Sure, Atlanta, Birmingham. We would still
0:18
Speaker 1: love to see you, and you can still get great seats. Yeah,
0:20
Speaker 1: and this is a brand new show. Unless you were
0:22
Speaker 1: in San Francisco, San Diego, Austin, or Dallas, you ain't
0:25
Speaker 1: seen the show. And it is bringing down the house
0:29
Speaker 1: all over the country eventually probably all over the world. Yes,
0:32
Speaker 1: and you can get tickets. You can just go to
0:34
Speaker 1: s y s K live dot com. It's our square
0:36
Speaker 1: space powered site and they were powering our tour and
0:39
Speaker 1: they were they're powering me on a daily basis. So
0:43
Speaker 1: we will see you guys very soon. Welcome to Stuff
0:47
Speaker 1: you should Know from House Stuff Works dot com. Hey,
0:56
Speaker 1: and welcome to the podcast. I'm Joshua m clark. There's
1:00
Speaker 1: Charles w Wayne, Chucker's Chuck Tran Bryant Chuck Trand I
1:07
Speaker 1: remember that and then that one never even made sense. No,
1:10
Speaker 1: who said that me? Yeah, I don't get it. It
1:13
Speaker 1: doesn't mean anything. That's why I never made sens. And
1:16
Speaker 1: then there's Jerry Chairs, Jerome Rolling, Jair Tran, and Josh Tran. Yeah,
1:23
Speaker 1: the trans I'm excited to record this and then leave
1:26
Speaker 1: because I just quickly on my phone saw that Billy
1:30
Speaker 1: Joel did Ado performance in the commercial break of IT
1:33
Speaker 1: talk show and the video was up. Oh yeah, so
1:36
Speaker 1: I got things to do. Okay, well, let's go personalized medicine. Chuck, huh,
1:41
Speaker 1: So let's take it back. Let's take away back. Okay,
1:45
Speaker 1: let's talk about medicine in general. Right, are we way
1:47
Speaker 1: back machining it or no? No, no, no, all right.
1:50
Speaker 1: So there's this idea that um two best understand how
1:57
Speaker 1: to treat a person, you should understand. Critique said, it's
2:01
Speaker 1: far more important to know what person the disease has
2:04
Speaker 1: than what disease the person has. Boy, that is smart
2:07
Speaker 1: for back then it is you know, and I think
2:10
Speaker 1: that this was the original idea behind medicine, that we
2:13
Speaker 1: we can understand a disease, but when you apply it
2:16
Speaker 1: to a person, it's going to be different than when
2:19
Speaker 1: you apply it to another person. And that is the
2:23
Speaker 1: heart of personalized medicine, is that understanding. Unfortunately, for many
2:29
Speaker 1: hundreds of years. Well actually for a shorter time than that.
2:33
Speaker 1: But in Western medicine, the idea has been that if
2:36
Speaker 1: it works for most people, it will probably work for you,
2:40
Speaker 1: or that's good enough for us. Yeah, it's called a
2:43
Speaker 1: trial and error approach, and that should scare you to death.
2:47
Speaker 1: Well I get it, because until we until the Human
2:52
Speaker 1: Genome Project, we didn't have a lot of choices as
2:55
Speaker 1: a society other than to do our best for the majority.
3:00
Speaker 1: You know. Well, yeah, like that changed everything. It did,
3:04
Speaker 1: but even before that, it was it was like, that
3:06
Speaker 1: was what two thousand, two thousand one, something like that,
3:08
Speaker 1: the Human Genome Project. Yeah, I mean before that, there
3:11
Speaker 1: were some precursors to personalized medicine, like let's look at
3:14
Speaker 1: family histories and stuff like that. Yeah, but even like
3:17
Speaker 1: it's that's not that old. It wasn't until World War
3:20
Speaker 1: Two that people started noticing huh. You know, different people
3:25
Speaker 1: have different reactions to different kinds of medicine. There's actually
3:28
Speaker 1: an anti malarial drug that was given to troops in
3:32
Speaker 1: World War two, American troops, and um, if you're an
3:35
Speaker 1: African American, there's a high likelihood that you might develop
3:39
Speaker 1: anemia after you were given this anti malarial drug. But
3:42
Speaker 1: that wasn't that didn't show among um. White troops and
3:46
Speaker 1: doctors thought, what's behind this? And they went and looked
3:49
Speaker 1: and saw that genetically speaking African Americans were less likely
3:53
Speaker 1: to have a gene active that produces a protective enzyme
3:57
Speaker 1: that keeps you from developing anemia when you're giving this
4:00
Speaker 1: particular anti malarial drug. And that in the middle of
4:03
Speaker 1: the twentieth century, it was the first time we really
4:06
Speaker 1: started in the Western medicine tradition thinking that no, people
4:11
Speaker 1: have different reactions to different types of treatments and can
4:15
Speaker 1: have different experiences with different types of disease. Did they
4:18
Speaker 1: do something about it in that case? I don't know.
4:21
Speaker 1: I was curious. It depends on the time period in
4:23
Speaker 1: this country. Shamefully, they might have said, like, yeah, but
4:27
Speaker 1: who cares. Yeah. At the same time, the Tuskegee Um, yeah, exactly, Yeah,
4:33
Speaker 1: the Tuskegee experiments were going on. We're also infecting people
4:36
Speaker 1: in Guatemala with syphilis. Crazy crazy stuff. Um. So you
4:42
Speaker 1: mentioned Hippocrates, um, more than two thousand years ago. He
4:48
Speaker 1: was pretty advanced for thinking that jerkxes needs bleeding, but
4:54
Speaker 1: uh uh Zeus does not. Zeus never needs a bleeding
4:58
Speaker 1: by that, But it was lightning bowl at the problem exactly.
5:02
Speaker 1: But he was way ahead of his time to be
5:04
Speaker 1: thinking that way back then. Um, some other pioneers since then,
5:08
Speaker 1: I think we talked about these two, Reuben Otenberg and
5:12
Speaker 1: Ludvik hick Thorne job. I don't know that was not
5:17
Speaker 1: good hicktoin uh in nineteen o seven, and I think
5:22
Speaker 1: in our blood episode we might have talked about this.
5:25
Speaker 1: That was such a good episode, it was a really
5:27
Speaker 1: good one. I think, Um, they were the first ones
5:29
Speaker 1: to say, you know what, people have different blood types
5:31
Speaker 1: as it works, so that's why people keep dying. Well,
5:34
Speaker 1: now we're putting this blood into someone that doesn't have
5:37
Speaker 1: the same blood. So that was land Steiner who came
5:39
Speaker 1: up with the idea that way. It wasn't blood types.
5:41
Speaker 1: These two were the ones who first started to match people, like, well,
5:45
Speaker 1: let's match these people. That's the that's yeah, that's a
5:48
Speaker 1: pretty good first example of personalizing medicine on the most
5:53
Speaker 1: basic level, like let's not kill people with blood right uh.
5:58
Speaker 1: And then like I said, um, family histories and such,
6:01
Speaker 1: they finally started saying, hey, you know what, maybe we'll
6:04
Speaker 1: look at your father and your mother and your grandparents,
6:07
Speaker 1: because if they have this disease, you might have it
6:09
Speaker 1: as well. But everything changed when the Human Genome Project
6:13
Speaker 1: came along, and UH, all of a sudden, we found
6:17
Speaker 1: out we could learn a lot more about our predisposition
6:20
Speaker 1: for certain diseases. Yeah, because if you think about it,
6:25
Speaker 1: um are reactions to different diseases, and also the same
6:29
Speaker 1: medicines that treat different diseases. UH, can be traced down
6:35
Speaker 1: to the to the genetic level, to the molecular level,
6:38
Speaker 1: to whether a gene is turned off and expressing a
6:41
Speaker 1: certain kind of protein or enzyme um or whether our
6:45
Speaker 1: genes are going to allow for a tumor that expresses
6:49
Speaker 1: a certain kind of protein that can be tracked. If
6:52
Speaker 1: you conceivably can look at a person's genome sequence, the
6:56
Speaker 1: whole thing, analyze it, and then look it what genes
7:00
Speaker 1: are turned on or off, what proteins are being expressed,
7:03
Speaker 1: that kind of thing, then you if you also know
7:06
Speaker 1: that a certain kind of drug attracts a certain kind
7:10
Speaker 1: of tumor that's associated with that type of genome or
7:13
Speaker 1: genetic sequence, then you can put patient and drug together
7:18
Speaker 1: under its ideal form. Dude, we should stop and just
7:22
Speaker 1: walk away. That's a mic drop statement. I don't think
7:26
Speaker 1: we need anything else. Okay, I'm gonna go watch Billy
7:29
Speaker 1: Jolson do up. All right. So, if you think you
7:33
Speaker 1: go to the doctor and you get personalized medicine, in
7:36
Speaker 1: a sense, you sort of are. But what we're talking
7:38
Speaker 1: about is what Josh has said, which is your own
7:40
Speaker 1: individual biology being the most overriding factor in how you
7:46
Speaker 1: were treated. Your biology, not just you know, you're a
7:50
Speaker 1: human being. Yeah, this works on human beings and horses.
7:54
Speaker 1: And your mom had cancer, your grandma had cancer, so
7:56
Speaker 1: you might have cancer. No, we're talking about looking inside
7:59
Speaker 1: of you to find out what your likelihood to get
8:02
Speaker 1: these things are, and like you said, matching you with
8:04
Speaker 1: the best treatment plan, right, one of those UM one
8:07
Speaker 1: of those courses of study. There's a lot of different
8:09
Speaker 1: things that really kind of fall under personalized medicine UM.
8:13
Speaker 1: But one of those sub fields is called pharmacogenetics, right.
8:18
Speaker 1: And that is again, if you can take a person's
8:21
Speaker 1: genome and then uh analyze it, you can say, well,
8:25
Speaker 1: I see the sequence right here would react very well
8:28
Speaker 1: to this particular drug. That's pharmacogenetics matching the drug to
8:32
Speaker 1: the person, right, yeah, which is the opposite of hey,
8:35
Speaker 1: it works for eight out of ten people, and if
8:37
Speaker 1: you're just one of those, the T S T S
8:41
Speaker 1: and that seriously, that is the basis of western medicine
8:44
Speaker 1: as it stands right now. It's it called it's a
8:46
Speaker 1: trial and error approach. And they don't usually stop at ts. No,
8:51
Speaker 1: they just say like, oh, you survived that round of drugs,
8:54
Speaker 1: but it didn't Let's try something else. Maybe maybe this
8:58
Speaker 1: other one that doesn't work for it tends to work
9:01
Speaker 1: for that might work for you. And then it just
9:04
Speaker 1: goes on and on and on until they finally hit
9:06
Speaker 1: upon that drug hopefully that that doesn't work. I say hopefully,
9:10
Speaker 1: because within that trial and error period a lot of
9:13
Speaker 1: people die. Sometimes that first time, that first trial results
9:18
Speaker 1: in a fatal error, and those are called a d
9:20
Speaker 1: S or adverse drug UM events. There's seven hundred and
9:25
Speaker 1: seventy thousand people in the US alone they either die
9:30
Speaker 1: or are injured by an a d E every year
9:33
Speaker 1: in the US alone, almost a million people, seven hundred
9:38
Speaker 1: and seventy thousand people every year. You give that person
9:41
Speaker 1: a drug and they might die. And the one of
9:44
Speaker 1: the goals of UM of pharmacogenetics is to avoid a
9:49
Speaker 1: d e s so that you can say, before you
9:52
Speaker 1: give anybody a drug, like this won't kill you, Yes, exactly,
9:56
Speaker 1: this won't kill you. We know that because we scanned
9:58
Speaker 1: your geno. We're not guessing here. We know you genetically
10:03
Speaker 1: will not die from this drunk. Yeah, I think we
10:06
Speaker 1: should caveat here when we say things like guessing and
10:09
Speaker 1: like I don't want to paint the medical industry is
10:11
Speaker 1: you know, just throwing darts with a blindfold. They've done
10:16
Speaker 1: They did the best job they could, I think, to
10:18
Speaker 1: treat massive amounts of people in the most efficient way possible.
10:23
Speaker 1: But things are getting better now because of the human
10:27
Speaker 1: biome or the human genome and what we've learned about it.
10:30
Speaker 1: Like when I look about the future of medicine, it
10:32
Speaker 1: is like it's super rosy. Yeah, I agree, you know,
10:37
Speaker 1: like a hundred years from now, it's it's gonna be
10:38
Speaker 1: amazing what we're gonna be doing, maybe like thirty Like
10:42
Speaker 1: we're right there on the cusp right now, where we
10:45
Speaker 1: went through a fairly dark age as far as medicine goes,
10:48
Speaker 1: where we were taking shots in the dark, figuring things
10:51
Speaker 1: out as we went along, and now we are right
10:53
Speaker 1: there at the age where we're about to just take
10:55
Speaker 1: off like a rocket and really understand health and wellness
10:59
Speaker 1: and treatment of disease. All right, well, I feel like
11:02
Speaker 1: we're on the cusp of the message break as well.
11:04
Speaker 1: I think you're right, So, Chuck, I was talking about
11:28
Speaker 1: pharmacod genetics, right, there's actually some examples of pharmacogenetics already
11:34
Speaker 1: taking place. This isn't necessarily in the future, like this
11:37
Speaker 1: is already starting. Yes, I think it started in the nineties, right, yeah,
11:43
Speaker 1: And and we'll get to this later. One of the
11:45
Speaker 1: big reasons that things are cooking now, cooking with gas,
11:49
Speaker 1: as my dad used to say, is because the massive
11:53
Speaker 1: drop in cost for mapping your genome. Yeah, like assive.
12:00
Speaker 1: In fact, i'll go ahead and tease you here and uh,
12:05
Speaker 1: the first time it was done to James Watson in
12:07
Speaker 1: two thousand seven, that was two seven, not even the
12:10
Speaker 1: human genome that was two thousand one. Two thousand seven
12:13
Speaker 1: was four. A time they mapped the person in full
12:17
Speaker 1: cost a million dollars. Now you can get it done
12:22
Speaker 1: a good A good one, not a full You know,
12:24
Speaker 1: you can't map out the entire genome for this amount
12:28
Speaker 1: of money. You can, you can you can sequence it.
12:33
Speaker 1: You can sequence it for that's the caveat less than
12:36
Speaker 1: two dollars, and pretty soon it's going to be about fifty.
12:41
Speaker 1: And then from what I saw in that, I think
12:44
Speaker 1: that was like a Business Insider article, there was a
12:47
Speaker 1: dude who gave this this really interesting lecture. Um. He
12:51
Speaker 1: very strongly asserted that they were pretty confident by thanks
12:58
Speaker 1: to economies of scale, Uh, genome sequencing will cost about
13:03
Speaker 1: a penny. Yeah, they won't. Won't cost a penny, Like
13:07
Speaker 1: you won't pay a penny. I guarantee you that. No, No,
13:10
Speaker 1: but it'll be but it might be like fifty bucks
13:13
Speaker 1: and someone will be makingfit. No. The I think what
13:17
Speaker 1: he was saying was if you take all of the
13:18
Speaker 1: genomes that are sequenced in a year, ultimately that's what
13:22
Speaker 1: it will have cost. It's about a penny each, right,
13:24
Speaker 1: But they it's gonna pop up in in different ways
13:28
Speaker 1: than what you have now. Like this is a pretty
13:31
Speaker 1: common thought that you will pee into your toilet, and
13:34
Speaker 1: your toilet will have a genome sequencer attached to it,
13:37
Speaker 1: and when you pee, your urine will be analyzed for
13:40
Speaker 1: any changes from that morning or the night before or
13:43
Speaker 1: anything like that, so that your baseline health is monitored
13:47
Speaker 1: on a like a several times a day basis. Right,
13:51
Speaker 1: if my toilet starts telling me to cut down on
13:53
Speaker 1: my drinking, then I'm gonna start peeing outside. I imagine
13:56
Speaker 1: that you can probably set it to kind of take
13:58
Speaker 1: it easy on this area, you know that kind of
14:00
Speaker 1: And when I say start being outside, I mean full time.
14:02
Speaker 1: I p outside almost every night, off of my deck.
14:07
Speaker 1: Sometimes you even stand up. Yeah, that's Raymond mcaulay, by
14:11
Speaker 1: the way, he's the bio technology and bio and for
14:15
Speaker 1: Maddox chair Singularity University, what's their mascot, the uh fighting
14:24
Speaker 1: curs wild. So he's a smart guy, and he's the
14:27
Speaker 1: one that is saying that this is just getting cheaper
14:30
Speaker 1: and cheaper. And when you look at the graph in
14:33
Speaker 1: two thousand seven, it took a nose dive in price,
14:36
Speaker 1: Yeah it did. He compared it to Moore's law, where
14:38
Speaker 1: um Moore's law is like the amount of computing power
14:41
Speaker 1: doubles every eighteen months or something like that, twenty four months.
14:46
Speaker 1: They can't remember, um. And it was pointed out that
14:50
Speaker 1: genome sequencing was actually moving in a rate of five
14:53
Speaker 1: to ten times the rate of Moore's law. That's awesome.
14:57
Speaker 1: That is awesome as far as genome sequencing concerned. The
15:00
Speaker 1: problem is computing powers still following Moore's law. And here's
15:05
Speaker 1: the big problem. This is why we're not all getting
15:07
Speaker 1: our genome sequenced right now. Because it might be very
15:11
Speaker 1: cheap to sequence human genome, it's still very expensive because
15:16
Speaker 1: it requires a lot of computing power to analyze that genome. Yeah,
15:21
Speaker 1: that's the main stumbling block is you can't sequence your genome,
15:25
Speaker 1: stick it in a machine and have it say you'll
15:27
Speaker 1: get cancer. Yet. That's the future, but not too far off. No,
15:32
Speaker 1: that's like Gattica. Yeah, but the I mean this guy
15:36
Speaker 1: Macaulay was saying, probably in about ten years they will
15:39
Speaker 1: have machines like that. Yeah, which is what we need.
15:41
Speaker 1: That's the main stumbling block right now is there's so
15:43
Speaker 1: much data that computers can't even keep up. So right
15:46
Speaker 1: now you could conceivably get a decent genome sequenced and
15:50
Speaker 1: analyzed for like fifteen grand, which is not I mean,
15:56
Speaker 1: that's not all the realm of it's not the reach
15:58
Speaker 1: of everybody. You have to be people that, Um, the
16:03
Speaker 1: the the big change will come when all of us
16:09
Speaker 1: get our genome sequence basically for free. And the holy
16:14
Speaker 1: grail in the not too distant future is to not
16:16
Speaker 1: only have a genome sequencer and analyzer in your toilet,
16:22
Speaker 1: but also you'll be wearing like a wearable or have
16:24
Speaker 1: an implanable something, yeah, but or maybe something that's under
16:28
Speaker 1: the skin that is like fitbit, but that's analyzing everything, um,
16:34
Speaker 1: including your hormone levels things like that. So you're not
16:37
Speaker 1: only analyzing your p you're also analyzing your body in
16:40
Speaker 1: a moment to moment basis. And all this stuff is
16:42
Speaker 1: run through an app you have on your phone that
16:46
Speaker 1: is tied in to your health records and other kinds
16:50
Speaker 1: of medical data um that you control and you share
16:55
Speaker 1: with your healthcare provider rather than the opposite. That's another
16:58
Speaker 1: big change coming that we talk sucked about in Will
17:01
Speaker 1: Computers Replace My Doctor episode, that that medical information about
17:05
Speaker 1: the person is going to be wrestled away from healthcare
17:09
Speaker 1: and healthcare providers and insurance companies and placed in the
17:12
Speaker 1: hands of the individual. And that's going to be a
17:14
Speaker 1: huge change that will probably come from this personalized medicine
17:18
Speaker 1: exactly one of the positive changes. All right. So there
17:21
Speaker 1: have been some early stories that have given us all
17:25
Speaker 1: hope for the future when it comes to looking at
17:27
Speaker 1: these biomarkers UM for potential of disease, and one of them,
17:32
Speaker 1: there was a drug called U k A l y
17:35
Speaker 1: d e c O kellidico kalitico I think so UH
17:39
Speaker 1: in two thousand twelve to treat a rare form of
17:42
Speaker 1: cystic fibrosis UM, which is a deadly lung condition. And
17:46
Speaker 1: the FDA here in the U S approved this drug
17:49
Speaker 1: UM basically because they found out certain people have genetic markers,
17:53
Speaker 1: these biomarkers that they wouldn't respond to other drugs treating
17:57
Speaker 1: UH cystic fibrosis. So they said, this is a new
18:00
Speaker 1: drug that will work for you. Success story boom, and
18:04
Speaker 1: this like this is the future of personalized medicine all
18:07
Speaker 1: over the place. Right. It covers about four percent of
18:10
Speaker 1: cystic fibrosis patients. So in the US, it's people that
18:15
Speaker 1: the drug was targeted for, right, because you would think
18:19
Speaker 1: I'm just cynical, but you would think that's so few
18:20
Speaker 1: people that somebody be like, a why bother, I'll bet
18:23
Speaker 1: it costs a bunch of money for the drug, But yes,
18:25
Speaker 1: you're right, UM. And then secondly, it also kind of
18:28
Speaker 1: shows how personalized medicine shifts our understanding of disease to right,
18:33
Speaker 1: the reason these people with cystic fibrosis didn't respond to
18:36
Speaker 1: regular medicine is because their cystic fibrosis was developed because
18:41
Speaker 1: their genes didn't that regulated salt and water movement across
18:45
Speaker 1: the surface of their lungs were mutated and not functioning properly.
18:49
Speaker 1: So this specific drug that targets these four percent of
18:53
Speaker 1: cystic fibrosis patients goes in and messages with that gene. Well,
18:56
Speaker 1: if you do the other ninetent of cystic fibrosis patient,
19:00
Speaker 1: their salt and water um movement is just fine. That's
19:04
Speaker 1: not why they have cystic fibrosis. So it changes your
19:07
Speaker 1: understanding of cystic fibrosis. It's not like you have cystic fibrosis.
19:12
Speaker 1: This is why you have it. This is how your
19:14
Speaker 1: body is showing that you have cystic fibrosis. You have
19:17
Speaker 1: cystic fibrosis, and you can have all these you can
19:20
Speaker 1: have it under these different mechanisms. That's what personalized medicine
19:24
Speaker 1: is changing too. It's changing our understanding of disease itself.
19:28
Speaker 1: Same with cancer, right, certain tumors express certain proteins and
19:32
Speaker 1: although yes, you have an out of control growth that
19:36
Speaker 1: makes a cancer. It really doesn't bear that much of
19:39
Speaker 1: a resemblance to this other kind of cancer. And the
19:42
Speaker 1: more we dig into how people respond differently to cancer
19:46
Speaker 1: treatments and how they can host different kinds of tumors
19:49
Speaker 1: is changing our understanding of cancer. And a lot of
19:51
Speaker 1: people are like, cancer is too big of an umbrella.
19:54
Speaker 1: These are really almost different diseases. Yeah, And I think
19:57
Speaker 1: the Macaulay guys said the hope one day is to
20:01
Speaker 1: stop cancer before it even starts at such a small
20:05
Speaker 1: molecular level with these advanced Uh. I guess like a
20:10
Speaker 1: blood test. Yeah, basically the blood test will be so
20:12
Speaker 1: advanced that let's say, you know you're going to develop
20:16
Speaker 1: cancer in five years, Like we can tell that already,
20:19
Speaker 1: So let's just stop it now before there's a yeah,
20:23
Speaker 1: or before it gets big enough that it's a problem. Yeah, exactly. Uh.
20:27
Speaker 1: If you have type one diabetes, I think it is
20:30
Speaker 1: um good news. There is a new system. It's a
20:35
Speaker 1: basically an artificial pancreas device and they are wearable and
20:41
Speaker 1: the clinical developed by u v A and Harvard Go
20:44
Speaker 1: Cavaliers and Crimson, the Crimson Smarties. That's Harvard. Right, they're
20:53
Speaker 1: not the Crimson Tide too, are they? No, not the Tide,
20:55
Speaker 1: They're just Crimson's the Crimson. I think you guys left
21:00
Speaker 1: part off their Harvard. Well, they do have a mascot,
21:02
Speaker 1: I think, like John Harvard, but it's not like it's
21:05
Speaker 1: just a square of Crimson. I don't know. I think
21:07
Speaker 1: so maybe they're above it. They don't need a Crimson
21:10
Speaker 1: Knights Crimson Knights. No, is that Rutgers. That's Scarlet Knights. Anyway,
21:16
Speaker 1: uv A and Harvard developed this thing together. Uh. And
21:20
Speaker 1: it starts clinical trials in like the next month or two.
21:24
Speaker 1: Uh and for six months, two forty people are gonna
21:26
Speaker 1: wear this thing, this artificial pancreas to tell your body, uh,
21:32
Speaker 1: exactly when you need the optimal level of insulin in
21:36
Speaker 1: your body at all times. Well, and introduces that optimal level.
21:40
Speaker 1: Oh does it? Uh? Huh? How so? So it's like
21:44
Speaker 1: it's monitoring your blood glucost level. Yeah. And you you know,
21:48
Speaker 1: if you have diabetes you have to inject insuline. Yeah,
21:51
Speaker 1: this stuff, say, is connected to report in your chest. Oh.
21:54
Speaker 1: I don't think this one particularly is this is just
21:56
Speaker 1: a wearable monitor. But I think eventually they're gonna have
22:00
Speaker 1: what you're talking about. I guess I'm just getting ahead
22:03
Speaker 1: of the ahead of myself. That's that's actually regulates, not
22:09
Speaker 1: monitors in the future, I think is what you're talking about,
22:12
Speaker 1: or injects like an optimal dose regulating your glucose so
22:17
Speaker 1: you don't have to do it. I think this is
22:19
Speaker 1: just a wearable monitor so you could just like press
22:21
Speaker 1: and say, okay, what kind of how much insulin do
22:24
Speaker 1: I need right now? And it tells you the exact
22:25
Speaker 1: like milligrams, so you still have to like a dope,
22:29
Speaker 1: go and inject it yourself, right, I think so. I
22:33
Speaker 1: don't see how it could be wearable on your arm
22:35
Speaker 1: and also be attached to your body like the insides
22:40
Speaker 1: of your body through like a an ivy. Yeah, I
22:44
Speaker 1: don't think that's what this is. All sounds like there's
22:47
Speaker 1: two different things, but it's still monitoring exactly what your
22:51
Speaker 1: blood glucoast level is. Absolutely and it's your blood loose
22:54
Speaker 1: coast level ergo, it's personalized medicine, that's right. If you
22:59
Speaker 1: have tendus like our buddy Aaron Cooper. Aaron Cooper, he
23:04
Speaker 1: probably didn't hear that. I'll heard it was a ringing.
23:06
Speaker 1: He just hurts. UM. They're working on customizable devices that
23:12
Speaker 1: adjust the audio signal that's unique to your own ear.
23:15
Speaker 1: In other words, hey just put this hearing aid in
23:18
Speaker 1: there that may or may not work for you, right
23:21
Speaker 1: from what I understand it actually so, UM, you know
23:23
Speaker 1: noise canceling headphones, Well, it kind of works like those.
23:28
Speaker 1: I guess it figures out what pitch you're hearing that
23:31
Speaker 1: tonight is that, and it just gets rid of it.
23:34
Speaker 1: I think that's neat. I do too, UM and then check.
23:36
Speaker 1: There's another early example of a good a big win. UM.
23:41
Speaker 1: There's something called herceptin, and the FDA said, yes, go
23:47
Speaker 1: ahead with this. UM. They figured out that this particular
23:51
Speaker 1: drug worked for a specific group of people UM whose
23:56
Speaker 1: tumors expressed a specific protein, and it was a breast
24:00
Speaker 1: cancer UM tumor targeting drug. But like again, it wasn't like, oh,
24:06
Speaker 1: you have breast cancer, here, try um her septin, it'll
24:10
Speaker 1: work for you. It's we we we believe that you
24:14
Speaker 1: have this kind of tumor because it's expressing this kind
24:17
Speaker 1: of protein. So her septin is going to treat this
24:21
Speaker 1: orray for her septin. Yeah, Well, let's take another break
24:24
Speaker 1: and we'll get back and finish up with some of
24:26
Speaker 1: the obstacles in the future. All right, So this all
24:51
Speaker 1: sounds rosy, but there are some obstacles we already talked about.
24:55
Speaker 1: One the previous biggest one was cost. This article itself
24:58
Speaker 1: is m way out of date because it said seventeen
25:04
Speaker 1: thousand dollars a person, and now it's already like two
25:07
Speaker 1: hundred bucks. I think that might be though with the
25:10
Speaker 1: with analysis. Oh really, yeah, I think that's what they're saying. Okay,
25:16
Speaker 1: oh yeah, follow up on the data. Yeah, all right's
25:18
Speaker 1: announced down to fifteen grand, So it's up by two
25:21
Speaker 1: thousand dollars. So it was written a week ago, all right,
25:26
Speaker 1: But the cost of the genome was a previous hurdle.
25:29
Speaker 1: Now that's coming down. Another hurdle is that we mentioned
25:32
Speaker 1: was just processing the data. And then another hurdle is
25:36
Speaker 1: just overstating the impact of this of the findings. Um,
25:41
Speaker 1: just because and it's a slippery slope, Just because you
25:45
Speaker 1: are susceptible to something doesn't mean you're gonna get it. No,
25:49
Speaker 1: And that's actually there's something called the Jolie effect, that
25:53
Speaker 1: Angelina Jolie effect. Oh boy, I've got eight thousand jokes.
25:57
Speaker 1: Have you heard about that now? So do you remember
25:59
Speaker 1: when she did genetic testing and found that, um, she
26:04
Speaker 1: was there was a likelihood that she would develop breast cancer.
26:10
Speaker 1: I think perhaps like her mother may have had breast cancer.
26:13
Speaker 1: I'm not sure, but she was convinced that there was
26:15
Speaker 1: a good chance she's going to get breast cancer. So
26:17
Speaker 1: she went ahead and had a double mestectomy without breast cancer,
26:21
Speaker 1: no tumors, no nothing. She just preventatively had mossectomies. Angelina
26:26
Speaker 1: Jolie did yes, and it created what's called this Angelina
26:31
Speaker 1: Jolie effect. And Christina applegated something like that too. Well,
26:34
Speaker 1: she had breast cancer. Angelina Jolie didn't have breast cancer,
26:39
Speaker 1: believed that she would conceivably get breast cancer, so it
26:42
Speaker 1: just had her breasts removed and the right um and
26:45
Speaker 1: it created what's called this Angelina Jolie effect, which is
26:48
Speaker 1: this idea that UM, the more we know about our bodies,
26:52
Speaker 1: the more UM focused on all the things that could
26:57
Speaker 1: conceivably go wrong, hype pathetically could go wrong, that we
27:02
Speaker 1: may take radical steps like like prophylactic surgery. Basically, you know,
27:08
Speaker 1: to prevent something that may or may not even happen.
27:10
Speaker 1: And this is a big concern among bioethicists about this
27:14
Speaker 1: kind of understanding that will come from personalized medicine is
27:18
Speaker 1: are we gonna all become obsessed with our health? Well?
27:21
Speaker 1: I think people that already are. This will just be
27:24
Speaker 1: the next step of that. Yeah, But I could see
27:27
Speaker 1: if it could bring more people into the full I'm
27:29
Speaker 1: sure there's a lot of people who don't think about
27:30
Speaker 1: their health just because they don't have that kind of awareness.
27:33
Speaker 1: But if it was in their face, like, hey, buddy,
27:35
Speaker 1: here's your genome, Look at this crazy stuff that could
27:38
Speaker 1: happen to you. Do you may start thinking about it
27:41
Speaker 1: even if you weren't predisposed to it before. But you
27:44
Speaker 1: would have to go get that done to begin with.
27:46
Speaker 1: Well that's another question too. So right now, if getting
27:50
Speaker 1: your genome done costs seventeen grand right, um, should that
27:56
Speaker 1: be just the providence of the rich or that a
28:00
Speaker 1: human right to know what your genome says? If anybody
28:05
Speaker 1: can know what their genome says, should everybody? I predict
28:08
Speaker 1: that the answer will ultimately be yes to that, then
28:12
Speaker 1: there's a right, and the government will probably fund a
28:15
Speaker 1: program for every American get to get their genome sequence years.
28:21
Speaker 1: Another big problem is the f d A is just overtaxed,
28:25
Speaker 1: you know, it's it's a rapidly moving field and they
28:29
Speaker 1: just can't keep up at this point, which you know,
28:32
Speaker 1: because there are a lot of new things that come
28:33
Speaker 1: along with new drugs, new devices that the FDA has
28:36
Speaker 1: a test. Well, not just that the understanding of it
28:40
Speaker 1: as well, Like they used to have this open database
28:43
Speaker 1: from the Human Genome Project to where all of these
28:46
Speaker 1: anonymous subjects, genes or genomes were just sitting out there
28:50
Speaker 1: for anybody to go and data mine, right, and then
28:53
Speaker 1: somebody proved that you can actually find you can d
28:57
Speaker 1: anonymize these people because again this is their genome and
29:02
Speaker 1: figure out whose genome you're looking at specifically, And the
29:06
Speaker 1: FDA had to shut it down, but they shut it
29:08
Speaker 1: down after somebody proved that this could already be done.
29:11
Speaker 1: So they're they're having to react rather than being able
29:14
Speaker 1: to keep up with the changes in the field. And
29:16
Speaker 1: that's one of the other huge slippery slopes in the
29:19
Speaker 1: future is um Well, a couple of things. How insurance
29:23
Speaker 1: companies deal with this um A. Can they deny someone
29:28
Speaker 1: based on a biomarker um right, now there's legislation that
29:33
Speaker 1: has been signed into law that says no, you cannot.
29:37
Speaker 1: It's called biological discrimination, which is profoundly insightful or foresightful
29:43
Speaker 1: for the government. Sure, I'm really surprised by that one. Uh.
29:46
Speaker 1: And you know what, Canada is the only G seven
29:48
Speaker 1: country that doesn't have this protection biological discrimination, and it's
29:55
Speaker 1: a big deal. There's a lot of people that are
29:57
Speaker 1: going like, why are we the only one where Canada? Uh?
30:01
Speaker 1: Predict Trudeau will change that. Well, there's a big push
30:05
Speaker 1: to for UM. And it's funny when they voted in
30:08
Speaker 1: the what was the act called uh them Genetic Information
30:16
Speaker 1: Non Discrimination Act of two right um. It passed by
30:20
Speaker 1: a vote of to nothing in the Senate and four
30:25
Speaker 1: fourteen to one in the House. Who is the one?
30:28
Speaker 1: It was Ron Paul of all people. Huh. I'd be
30:32
Speaker 1: interested to know what his his thinking was. I've got
30:34
Speaker 1: it because I was I thought the same thing. Here's
30:36
Speaker 1: his thinking, because it doesn't make sense that he's because
30:39
Speaker 1: he's pretty obsessed with the government staying out of your bills.
30:42
Speaker 1: He said, uniform federal mandates are a clumsy and ineffective
30:45
Speaker 1: way to deal with problems such as employers, and one
30:48
Speaker 1: of the rubs is either you'll be denied insurance or
30:50
Speaker 1: maybe you won't get hired for a job or promoted
30:53
Speaker 1: if they know that you might, you know, keep the
30:55
Speaker 1: buckets soon. That guy can't push a broom. He's got
30:57
Speaker 1: a defect on his G four eight gene. But it
31:01
Speaker 1: says right here in his experience, and he can push
31:03
Speaker 1: your broom genetics. He said, uniform federal mandates are clumsy
31:07
Speaker 1: and ineffective way to deal with problems such as employers
31:10
Speaker 1: making hiring decisions on the basis of the potential employees
31:13
Speaker 1: genetic profile. Imposing federal mandates on private businesses merely raises
31:17
Speaker 1: the cost of doing business and thus reduces the overall
31:20
Speaker 1: employment opportunities for all citizens. Huh. Yeah, I see what
31:25
Speaker 1: he's saying, but I don't know. It's kind of surprised.
31:27
Speaker 1: It seems like something you'd want to protect, um, but
31:30
Speaker 1: it passed by the widest of margins regardless. Yeah, that
31:34
Speaker 1: might be a record. No, I'm sure there's been unanimals
31:38
Speaker 1: one of the I would like to know what those were,
31:41
Speaker 1: you know, like honoring girl Scouts on Patriot Day or something. Now,
31:44
Speaker 1: there was one person's like no, No, that was Bernie Sanders.
31:47
Speaker 1: I choked on a on a tagalong once, never buying
31:52
Speaker 1: them again. Um, there's another obstacle, Chuck, and it is
31:55
Speaker 1: gathering the information, like yeah, to get this understanding of
32:01
Speaker 1: you know, what kind of genes lead to certain kinds
32:04
Speaker 1: of diseases so that we can treat people in an
32:06
Speaker 1: individual basis when we stumble across that same genome and
32:10
Speaker 1: a person later, you have to under you have to
32:13
Speaker 1: have a big database of genes. So where do you
32:15
Speaker 1: get it? Twenty three and me, that's apparently where you
32:18
Speaker 1: go get it. It sounds like forever twenty one, like
32:21
Speaker 1: a mall store and me. Uh yeah. They are a
32:25
Speaker 1: company now and the leading company I think for the
32:28
Speaker 1: personal genome test market, and how they're making their money
32:33
Speaker 1: now is not by selling these test kits which is
32:36
Speaker 1: ninety nine bucks, which supposedly they were selling at a loss, right,
32:40
Speaker 1: so they could eventually have this database that they could
32:42
Speaker 1: then sell to whoever, not whoever, but namely like form
32:47
Speaker 1: of companies and people doing research. So the twenty three
32:51
Speaker 1: and me amassed a database if I think about eight
32:54
Speaker 1: hundred thousand people, six hundred thousand people who took the
32:58
Speaker 1: twenty three and me test and paid ninety nine looks
33:00
Speaker 1: for it, agreed to donate their DNA, their gene, their
33:04
Speaker 1: genome research to research. Right. So twenty three and Me said,
33:08
Speaker 1: thanks a lot, guys. Now we have six hundred thousand
33:11
Speaker 1: individuals genomes just sitting there waiting to be analyzed. And
33:15
Speaker 1: very recently they closed to deal with a company called
33:17
Speaker 1: gene Tech. Gene Tech paid twenty three and Me sixty
33:21
Speaker 1: million dollars just to analyze three thousand people with Parkinson's genomes.
33:27
Speaker 1: That's why they were selling the kids at a loss, Yes,
33:30
Speaker 1: because they knew the big payoff was in something else entirely. Yeah,
33:33
Speaker 1: and um, they're they're from what I read in the
33:36
Speaker 1: UM A M I T. Technology Review article. Um, the
33:42
Speaker 1: twenty three and me. You shouldn't paint them, And I
33:43
Speaker 1: don't mean to paint them as nefarious or anything like that.
33:46
Speaker 1: But there's a guy named um Charles Seife who writes
33:51
Speaker 1: for Scientific American. In two thousand thirteen, he called the
33:53
Speaker 1: idea of a private company amassing a private database of
33:59
Speaker 1: human genomes yeah terrifying. Yeah, I mean it definitely is
34:03
Speaker 1: like the stuff of science fiction movies. I couldn't decide
34:06
Speaker 1: whether or not it was bad or not. I think
34:09
Speaker 1: what people are most concerned about is like, well, what
34:12
Speaker 1: happens in the future, or what if it becomes just
34:14
Speaker 1: like Facebook, where they have the rights to sell your
34:16
Speaker 1: personal information to whoever wants. It's exactly what it is.
34:19
Speaker 1: So Facebook data minds your behavior that you get to
34:23
Speaker 1: use their application for free. Twenty three and Me analyzed
34:26
Speaker 1: your d n A and sent you some stuff back
34:29
Speaker 1: for bucks, and their data mining your genes. It's the
34:35
Speaker 1: same thing as Facebook. It's just instead of behavior, they're
34:38
Speaker 1: analyzing genes, their data mining or amassing a database of
34:41
Speaker 1: it for sale. But right now they're saying, but yeah,
34:43
Speaker 1: we're selling it to researchers who are out to make
34:45
Speaker 1: medicines to make people better. Yeah, and that's you can't
34:48
Speaker 1: really argue with that. It's just the potential for it.
34:50
Speaker 1: Can you can understand how somebody could make it. It
34:52
Speaker 1: could could be made very uncomfortable by that. Yeah. The
34:55
Speaker 1: evil overlord, son of the current head of twenty three
34:59
Speaker 1: and me is one will do it well. The founders.
35:02
Speaker 1: The founder used to be married to Sergey Brynn of
35:04
Speaker 1: um of Google. Yeah. I think they since split up,
35:08
Speaker 1: but she still is the founder, and I believe the
35:11
Speaker 1: person who's running twenty three and me hopefully she subscribes
35:15
Speaker 1: to that Don't Be Evil thing too. Seriously, if you
35:18
Speaker 1: want to know more about personalized medicine, we should probably
35:21
Speaker 1: revisit this every six months, I think, Chuck. Um, you
35:25
Speaker 1: can type those words into the search bar at how
35:27
Speaker 1: stuff works dot com. You should also check out these
35:30
Speaker 1: um awesome episodes. Your limbs torn off? Now, what can
35:34
Speaker 1: can your grandfather's diet shorten your own life? Um? And yeah, blood,
35:40
Speaker 1: that was a good one. And then, um, will computers
35:43
Speaker 1: replace my doctor? If this episode floated your boat, you
35:46
Speaker 1: will love this too. And I said float your boat,
35:49
Speaker 1: which means it's time for listener mail. That means it's
35:53
Speaker 1: almost time for Billy Joel doo wop. I'm gonna call
35:57
Speaker 1: this Satanic Panic Movies. Hey, guys, my wife Jody and
36:01
Speaker 1: I just listened to the episode on Satanic Panic and
36:03
Speaker 1: we loved it and reminisced about our childhoods. We were
36:06
Speaker 1: both children of the eighties and uh, she remembers all
36:08
Speaker 1: the daytime talk shows about Satanic panic. We both had
36:11
Speaker 1: no idea it was taken so seriously by so many people.
36:14
Speaker 1: For me, I always assumed that stuff was just legend.
36:16
Speaker 1: Although there was a Devil's Drive Street in my own
36:19
Speaker 1: town growing up that kept all its ten year old
36:21
Speaker 1: spooked into our teenage years. Uh and it was a
36:24
Speaker 1: rite of passage when you finally got your license to
36:26
Speaker 1: drive down that street. Mostly, I remember Satanism through movies
36:30
Speaker 1: and pop culture, though given your pinchamp for cinema were
36:34
Speaker 1: cinema tangents, we were both expecting to hear more on
36:38
Speaker 1: that topic in this episode. Agreed. Here's my top ten
36:42
Speaker 1: list of mainstream eighties satanic Bannock movies. Number ten, drag Net,
36:47
Speaker 1: number nine, The Golden Child. He said this one does
36:50
Speaker 1: not hold up well. I'm supposed to hear that they
36:53
Speaker 1: didn't hold up well. Number eight Children in the Corn uh. Seven,
36:57
Speaker 1: Witches of Eastwick, Eastwick six, Every popular horror movie in
37:01
Speaker 1: the eighties right thirteenth Night around Elm Street elloween. I
37:03
Speaker 1: take issue with that Man's not samar in Elm Street
37:06
Speaker 1: by the third enth is certainly not see pans are
37:08
Speaker 1: just creepy killer guys. Slash your boots come one. Number five,
37:13
Speaker 1: The Burbs, Yeah, number four, The Evil Dead Series, No.
37:18
Speaker 1: Number three, Indiana Jones and the Temple of Doom ritual sacrifice.
37:22
Speaker 1: Not give him that. Yeah, I'm not satanas. I think
37:25
Speaker 1: he's just broadened Number two, Poultergeist. No, no, not even close.
37:31
Speaker 1: Number one. I don't think he asked which ones are
37:33
Speaker 1: you gonna say? Don't belong Number one young Sherlock Holmes.
37:37
Speaker 1: I love that movie, but I don't remember much about it.
37:40
Speaker 1: Oh yeah, there was a whole It was very It
37:42
Speaker 1: was more like Indiana Jones and the templeo Toom was
37:46
Speaker 1: like a ancient egypt worshiping Victorian cult. That was cool.
37:51
Speaker 1: I saw it like in the last year or so. Really,
37:54
Speaker 1: I remember enjoying it when I was red. Where did
37:56
Speaker 1: that guy go? No idea, I was wondering that myself. Uh.
38:00
Speaker 1: Thanks for an amazingly delightful and consistently entertaining podcast. Guys.
38:03
Speaker 1: We came out to your Boston show and absolutely loved it.
38:06
Speaker 1: Happy New Year. That is from Brian Gladstein of Framing
38:10
Speaker 1: m Massachusetts. Thanks Brian, thank you for half of that
38:13
Speaker 1: list you send as well. We appreciate it. If you
38:16
Speaker 1: want to get in touch with us, send us a
38:18
Speaker 1: list that we may or may not trash. You can
38:20
Speaker 1: tweet to us at s Y s K podcast. You
38:23
Speaker 1: can join us on Facebook dot com slash stuff you
38:25
Speaker 1: Should Know. You can send us an email to Stuff
38:27
Speaker 1: Podcast to how stuff Works dot com and has always
38:30
Speaker 1: joined us at our home on the web, Stuff you
38:32
Speaker 1: Should Know dot com. For more on this and thousands
38:39
Speaker 1: of other topics, is it how stuff Works dot com