Latest / Core Memory / The New Era of Consumer DNA Tests

Transcript

The New Era of Consumer DNA Tests · Core Memory

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you feel comfy i feel ready to go ready yeah all right i think
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we're we're locked
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in we're good um yeah okay all right uh yeah if there's nothing
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else i could tell
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SPEAKER_00: you let's get started we'll go into it um all right
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SPEAKER_00: Kyan Sadegi.
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SPEAKER_00: Sadegi.
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SPEAKER_00: Sadegi.
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SPEAKER_00: Kyan Sadegi.
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SPEAKER_00: Okay, I want to do it over again.
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SPEAKER_00: Okay, do it.
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SPEAKER_00: I prepared for this.
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I listened to other videos where people said it,
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but I knew,
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I was like,
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did they say it right?
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SPEAKER_00: Yeah, it's hard.
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SPEAKER_00: It's hard.
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SPEAKER_00: It's a hard name.
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SPEAKER_00: I was worried.
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SPEAKER_00: Okay.
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SPEAKER_00: Kian Sadegi.
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SPEAKER_00: Sadegi, yes, that's correct.
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SPEAKER_00: Thank you for rolling in here.
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SPEAKER_00: You are the co-founder and CEO of Nucleus.
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SPEAKER_00: Founder, CEO.
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SPEAKER_00: Just founder.
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SPEAKER_00: Just founder.
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SPEAKER_00: There's actually no co-founders.
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SPEAKER_00: It's important to make that distinction.
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SPEAKER_00: Yeah, I mean, I think it is.
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SPEAKER_00: No, no, it is.
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SPEAKER_00: It's good.
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SPEAKER_00: All right,
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SPEAKER_00: I'm just going to do a little,
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SPEAKER_00: I'm just going to introduce people to you just a little bit.
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SPEAKER_00: Okay.
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SPEAKER_00: And then we'll jump in.
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SPEAKER_00: So Nucleus,
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SPEAKER_00: We're going to get into it pretty deep,
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but it's a new type of DNA testing and there's lots of ins and
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outs to it.
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SPEAKER_00: You went to the University of Pennsylvania.
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SPEAKER_00: Briefly.
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SPEAKER_00: You are a dropout.
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SPEAKER_00: You're a TEAL fellow.
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SPEAKER_00: Correct.
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SPEAKER_00: So fallen into that camp.
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SPEAKER_00: I think the company started in 2021.
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SPEAKER_00: Yes.
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SPEAKER_00: It was incorporated, yes.
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SPEAKER_00: And then you've been rolling out new services.
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SPEAKER_00: You have a service,
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SPEAKER_00: if I remember right,
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SPEAKER_00: the one that you really first started getting attention for was
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SPEAKER_00: was around measuring people's IQ.
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Yeah,
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we do an adult DNA testing,
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which includes traits like IQ all the way to diseases as well.
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SPEAKER_00: Right.
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SPEAKER_02: And then just in the last month, I think, launched Nucleus Embryo.
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SPEAKER_02: Yeah.
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SPEAKER_02: So we have basically three main products.
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SPEAKER_02: One is the DNA health product, Nucleus Health, you can think of it as.
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SPEAKER_02: Another is a genetic matching.
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SPEAKER_02: So you can see if you're a match with your partner,
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SPEAKER_02: basically if your care is for the same rare hereditary marker.
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SPEAKER_02: And then now we have Nucleus Embryo.
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So one of the things that's really unique about us as a
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business is we go the entire stack.
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SPEAKER_02: Right.
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SPEAKER_02: So we do basically,
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SPEAKER_02: you know,
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SPEAKER_02: sequencing analysis from adults now all the way to embryos,
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which I think really violates a lot of the underlying
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assumptions of what it means
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SPEAKER_02: to be a genetics company today.
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SPEAKER_00: And we're going to get into all this.
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SPEAKER_00: I just wanted to cover some of the bases.
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SPEAKER_00: Are we live though?
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SPEAKER_00: Yeah, we're live.
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SPEAKER_00: We're going.
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SPEAKER_00: We're going, man.
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SPEAKER_00: I have to.
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SPEAKER_00: Oh,
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SPEAKER_00: and before we get too much farther,
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I just have to say that this podcast was made possible by the
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good people at E1
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SPEAKER_00: Ventures.
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SPEAKER_00: We'll give them.
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SPEAKER_00: Little applause.
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SPEAKER_00: Okay.
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SPEAKER_00: What do all these buttons do is the question now.
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SPEAKER_00: Because if that one does that.
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SPEAKER_00: We got good sounds, but I try not to go too wild with the soundboard.
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SPEAKER_00: That was just a little love for the people helping us along.
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SPEAKER_00: Okay.
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SPEAKER_00: So the note, that was just the intro.
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SPEAKER_00: Now we'll get into the good stuff.
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SPEAKER_00: I mean, I don't think this is like...
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SPEAKER_00: Meant to be as radical as it sounds.
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I guess you're,
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I would say,
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a lively and semi-controversial figure,
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I think.
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SPEAKER_00: Depends who you ask.
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SPEAKER_00: In this realm, yeah.
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SPEAKER_00: I mean,
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SPEAKER_00: you guys,
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SPEAKER_00: you made a big play at one point as 23andMe was going through financial
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SPEAKER_00: difficulties.
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SPEAKER_00: That's a whole nother story.
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SPEAKER_00: That could be another podcast.
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SPEAKER_00: Which I want to get into.
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SPEAKER_00: There's some people who gripe online
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SPEAKER_00: You're not alone in this.
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Companies like Orchid get these gripes about eugenics and
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things like that with these DNA tests.
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And then there's some people when you launched the IQ test that
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were grumbly about
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SPEAKER_00: like,
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SPEAKER_00: can we trust the science and all this?
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SPEAKER_00: And then beyond all that, you're just like, you're a good marketer.
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SPEAKER_00: You're active on Twitter.
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SPEAKER_00: Yeah, like I said, lively, I think, is fair.
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SPEAKER_00: I think that's fair.
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SPEAKER_00: Okay.
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SPEAKER_00: So I want to cover the company's technology.
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SPEAKER_00: I do want to do a little bit on your backstory first.
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SPEAKER_00: I think you're of Persian-Iranian descent.
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SPEAKER_00: Correct.
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SPEAKER_00: And your father...
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immigrated to the united states yeah my dad um my mom and my
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dad both actually are
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from iran um post the 79 revolution they had to leave iran my
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dad specifically he
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actually had to escape iran so he spoke badly against the
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government i like to joke
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you know like father like son and um they basically tried to
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kill him so he had to
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SPEAKER_02: escape eventually ended up in um
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And,
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you know,
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he sort of has this kind of proverbial kind of classic American
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dream story.
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SPEAKER_02: He's flipping hamburgers at McDonald's.
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He eventually becomes a doctor,
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goes to Harvard Medical School,
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becomes an ophthalmologist.
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SPEAKER_02: And, you know, my mother has a similar story.
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SPEAKER_02: She had to leave Iran.
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She eventually became,
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like,
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she could speak,
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I think,
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four different languages fluently.
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SPEAKER_02: She ended up meeting my dad in Canada, I think, actually.
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And I like to say for my mother,
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you know,
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she has three PhDs,
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me,
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my brother and my sister.
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SPEAKER_02: You know, she's world-class, world-class what she does.
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And I think my parents sort of gave me this backdrop of kind of
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the determination
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SPEAKER_02: of an immigrant family,
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SPEAKER_02: households with the kind of opportunity of America,
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SPEAKER_02: which is,
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SPEAKER_02: you know,
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SPEAKER_02: the breeding ground for many,
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SPEAKER_02: many different founders.
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SPEAKER_00: Did you grow up in Boston or Canada?
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SPEAKER_00: In Brooklyn.
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SPEAKER_00: I grew up in Brooklyn.
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SPEAKER_02: Yeah, yeah.
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SPEAKER_02: Okay.
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Actually,
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in part,
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people ask me,
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well,
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why is Nucleus in New York City a lot?
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SPEAKER_02: And one of the very just pragmatic reasons is that I'm from New York.
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SPEAKER_02: Okay.
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SPEAKER_02: You know, so...
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yeah when i grew up i just grew up with a ton all most of my
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best friends were
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persian i played tennis with all these i just i was like a
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pretty competitive
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tennis player which happened to be like i grew up in texas a
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bunch of the best
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people in the state were were a bunch of persian kids who who i
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hung out with like
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at school and then at tennis and and yeah it was like a big
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part of my life i kind
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SPEAKER_00: of
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SPEAKER_00: the families are always so warm and feed you lots.
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SPEAKER_00: Yeah.
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SPEAKER_00: And I just got, I got totally embraced into that, that community.
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SPEAKER_00: It was really cool.
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SPEAKER_00: Um, and then, okay, so you're, you're at UPenn.
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SPEAKER_00: I think you're studying computational biology.
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SPEAKER_00: I was studying comp bio even before Penn.
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SPEAKER_02: So I,
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SPEAKER_02: you know,
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SPEAKER_02: unfortunately my cousin,
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SPEAKER_02: she,
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SPEAKER_02: she went to sleep one day and she,
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SPEAKER_02: she didn't wake up.
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SPEAKER_02: Uh, so she died in her sleep.
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SPEAKER_00: I read about the story.
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SPEAKER_00: Yeah.
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SPEAKER_02: Um, and,
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you know,
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I asked my dad at the time,
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you know,
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my dad was obviously a physician.
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SPEAKER_02: I said, like, you know, how does this happen?
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SPEAKER_02: He said, oh, you know, bad genetics.
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SPEAKER_02: And I was like, what the hell does that mean?
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And that got me very interested in thinking of disease as like
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a problem to be solved.
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I think I intuitively recognized that if there's like one
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15-year-old that suddenly
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SPEAKER_02: dies in her sleep and another 15-year-old that doesn't,
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SPEAKER_02: there's something like wrong here that's like a problem to be solved.
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SPEAKER_02: And that actually,
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SPEAKER_02: I think,
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SPEAKER_02: eventually informed me,
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SPEAKER_02: you know,
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SPEAKER_02: decades later,
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SPEAKER_02: I guess,
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SPEAKER_02: what we're doing now.
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SPEAKER_02: But
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I started becoming very curious with CRISPR specifically,
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like gene editing technology,
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right?
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It's a device that you can actually use it to engineer a
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genetic material.
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And so I joined one of the first do-it-yourself gene editing
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laboratories in high school.
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And this is really kind of notable timing because now the same
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journalist that
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SPEAKER_02: covered that story.
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So I was in this do-it-yourself gene editing laboratory and we
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were engineering
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SPEAKER_02: yeast to make them illuminated.
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SPEAKER_02: We added bacteria to make them.
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SPEAKER_02: This is in Brooklyn?
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this is in brooklyn this is a warehouse in brooklyn this is
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like og hacker like
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weird like biohacker though not like necessarily classical
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programming hacker and
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there was a journalist there and the journalist was covering
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this sort of diy like
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crisper movement and then she ended up writing a story about
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just like this 17 year
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old you know engineering things like what the hell is this kid
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doing here anyways
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and then now like you know almost 10 years later she's writing
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this another story
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on us but about nucleus embryo this is the wall street journal
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what's her name name
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SPEAKER_00: is amy marcus okay okay she's like a she's a
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SPEAKER_00: She's a health bioreporter.
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SPEAKER_02: Yeah, health bioreporter.
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SPEAKER_02: And so to me,
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SPEAKER_02: it's kind of a weird,
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SPEAKER_02: crazy kind of long-term timeline thing because you can see how different
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SPEAKER_02: technologies and different interests are eventually going to converge.
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Because I started off not on the programmatic side,
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but on the actual wet lab.
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SPEAKER_02: It's much messier than the computer.
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SPEAKER_02: And I,
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SPEAKER_02: in part,
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went toward combining atoms and bits together because I found
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the wet laboratory to
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SPEAKER_02: not be very iterable.
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SPEAKER_02: So my mind,
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I felt like it was always very imaginative and can kind of
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create anything in my
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SPEAKER_02: mind,
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SPEAKER_02: but then bring it into the physical plane via pipette I struggled with.
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SPEAKER_02: On the computer,
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SPEAKER_02: it was much more of like kind of an immediate instantiation of my logic,
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SPEAKER_02: where logic can lead to creation much faster.
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And now I feel like I'm almost coming around again in the
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journey by being like,
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SPEAKER_02: wait a second,
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SPEAKER_02: these technologies,
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and this is sort of a meta point that we can talk about later
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on in the pod,
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SPEAKER_02: but the sequencing,
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SPEAKER_02: analyzing,
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SPEAKER_02: editing stack,
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SPEAKER_02: it's almost in a weird way a culmination of all my experiences.
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SPEAKER_00: Yeah, and you're 25?
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SPEAKER_00: 25, yeah.
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SPEAKER_00: 25, so it's funny.
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SPEAKER_00: I'm old enough to have,
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SPEAKER_00: like,
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SPEAKER_00: I mean,
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SPEAKER_00: I,
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SPEAKER_00: like,
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SPEAKER_00: lived through the birth of DIY Bio,
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SPEAKER_00: and,
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SPEAKER_00: you know,
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SPEAKER_00: it's kind of funny,
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SPEAKER_00: because when the genome,
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SPEAKER_00: when we first did the whole genome around,
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SPEAKER_00: what,
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SPEAKER_00: 2000,
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SPEAKER_00: 2001-ish,
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SPEAKER_00: you know,
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SPEAKER_00: everyone thought there would be this immediate kind of revolution,
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SPEAKER_00: and then I,
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SPEAKER_00: yeah,
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SPEAKER_00: I guess about 15 years,
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years past in the DIY biorevolution really started to kick off
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from Stanford and
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SPEAKER_00: some other places.
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SPEAKER_00: And once again, it felt like, oh, okay, we've turned biology into code.
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And we have done some of that,
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but it always goes slower than people think.
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So you didn't have the feeling because you're so young that
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you'd kind of missed
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SPEAKER_00: that wave already.
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SPEAKER_02: Yeah, no, I think...
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One thing that has always been very true with me is I just
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follow my curiosity very much.
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SPEAKER_02: And it led to gene editing.
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SPEAKER_02: And I was like, well, I really like this, but it's not very iterable.
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SPEAKER_02: So now let me go study kind of the intersection of bits and atoms.
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SPEAKER_02: Let me go do computational biology at Penn.
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And then that led me to be in genetics class one day where I
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literally the
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SPEAKER_02: professor brought up the decrease in cost of sequence in a human genome.
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SPEAKER_02: I'm sure a lot of your listeners are familiar with this chart.
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Basically,
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it shows that it used to be a billion dollars to read a human
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genome.
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SPEAKER_02: And then now, at the time in 2020, it was $1,000.
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SPEAKER_02: And I literally remember going in class thinking,
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SPEAKER_02: OK,
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SPEAKER_02: well,
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SPEAKER_02: obviously,
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SPEAKER_02: this price didn't converge on zero.
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SPEAKER_02: Obviously, there's going to be an exponential proliferation of this data.
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SPEAKER_02: Obviously, someone needs to build the application layer for DNA.
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And with that in mind,
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I turned to my classmate,
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and I said,
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this is crazy.
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SPEAKER_02: The world's going to look different 10 years from now.
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SPEAKER_02: And they said to me, OK, well, is this going to be on the midterm?
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SPEAKER_02: I said, OK, I got the fuck out of here.
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SPEAKER_02: I was like, I got to get out of here, man.
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SPEAKER_02: So this is not for me.
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SPEAKER_02: And so I left.
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SPEAKER_02: I moved back into Brooklyn.
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SPEAKER_02: There's this whole story down.
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SPEAKER_02: I don't know how I should get into it.
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SPEAKER_02: But I actually lied to my parents.
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SPEAKER_02: Sorry, mom, dad.
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SPEAKER_02: I told them, because the immigrants are wrong.
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SPEAKER_02: You don't leave your pen from an immigrant.
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SPEAKER_00: Unless you want to get killed.
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SPEAKER_02: You know, so I was like, oh, I work with a professor at Penn.
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SPEAKER_02: There's no professor at Penn.
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SPEAKER_02: I was grinding in my bedroom for a year.
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SPEAKER_02: I filled in 18 subject notebooks,
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SPEAKER_02: basically the underpinning,
10:18
almost like the intellectual foundation for building this sort
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of application layer
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SPEAKER_02: that combines all these different genetic analyses together.
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SPEAKER_02: And that eventually led to Nucleus.
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SPEAKER_02: And, you know, my parents said to me, we're kicking out of the home.
10:28
SPEAKER_02: And I said, okay, well, that's not going to-
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SPEAKER_02: were kicking out of the home.
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SPEAKER_00: Oh, kicking you out.
10:30
Yeah,
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because it's been like a year and they're like,
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what,
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like,
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what are you even doing?
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SPEAKER_00: Oh, so you were actually living at home while you were doing this?
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SPEAKER_02: Oh my God, yeah, in my bedroom.
10:36
SPEAKER_00: So what, you would like fake going to meetings?
10:38
SPEAKER_00: I would, yeah, I mean, they don't know, it was COVID too.
10:41
SPEAKER_02: So it's kind of like,
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SPEAKER_02: I'd like go into the,
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SPEAKER_02: I'd like also,
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it's really funny because I'd pull up like the DNA ATCG on my
10:47
computer and I would
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SPEAKER_02: like show my family that,
10:48
SPEAKER_02: I'd be like,
10:49
SPEAKER_02: look how cool this is.
10:50
SPEAKER_02: And they'd be like, wow, that's crazy.
10:51
SPEAKER_02: Like the DNA on your computer?
10:52
SPEAKER_02: I'm like, yeah, right?
10:53
SPEAKER_02: Like this lab is some really cool lab.
10:56
SPEAKER_02: And it was, it was in front of your projects, you know?
10:59
SPEAKER_02: And that's the thing though,
11:00
which is like one of the hardest things I think people maybe
11:02
sometimes miss about
11:03
SPEAKER_02: starting a company like Nucleus is like,
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SPEAKER_02: you know,
11:05
SPEAKER_02: you need to have not only exceptional investigativeness,
11:07
SPEAKER_02: but then exceptional enterprisingness.
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And usually those are kind of very paradoxical characteristics
11:13
that don't exist in someone.
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SPEAKER_02: And I think the thing is that when you're under such intense pressure,
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SPEAKER_02: you're able to push yourself to the nth degree in both.
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SPEAKER_02: I feel like I can oscillate between both as needed.
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SPEAKER_02: Right now, I'm probably more on the enterprising side of my life.
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SPEAKER_02: But if I ever needed to, I could go back in the investigative side.
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SPEAKER_02: But during that year of COVID, it was isolating.
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SPEAKER_02: It was lonely.
11:33
SPEAKER_02: It was brutal.
11:34
SPEAKER_02: It was freaking hard.
11:35
SPEAKER_01: Yeah.
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But,
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you know,
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now,
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you know,
11:37
you have the fruits of your labor show eventually.
11:39
SPEAKER_00: Because you were in those notebooks, you were feeling it was what?
11:42
SPEAKER_00: What were you like?
11:43
You were you were trying to you were trying to devise a
11:46
software platform.
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SPEAKER_02: The thing I was thinking about is,
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SPEAKER_02: OK,
11:48
SPEAKER_02: how do you basically I was thinking,
11:50
how do you like if you were going to and this is very related
11:53
to the embryo launch,
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SPEAKER_02: too.
11:54
It's like if you're going to build software that could accept
11:56
any kind of DNA file.
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SPEAKER_02: Because DNA testing technology has gone through many evolutions.
12:02
SPEAKER_02: And the thing I realized was,
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SPEAKER_02: well,
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SPEAKER_02: actually,
12:05
SPEAKER_02: the kind of testing is basically becoming,
12:07
SPEAKER_02: if not already,
12:08
SPEAKER_02: a commodity.
12:09
SPEAKER_02: In other words,
12:10
everything from collecting the human sampler and the embryo
12:13
sample to generation of
12:15
SPEAKER_02: the raw DNA file is becoming commoditized.
12:17
SPEAKER_02: So the true value lies after the atoms have been translated into bits.
12:23
SPEAKER_02: And then so it's all at that point,
12:24
SPEAKER_02: you can almost think of DNA naively as like a text file,
12:28
SPEAKER_02: right?
12:28
SPEAKER_02: It's like, how do you build software that analyzes a text file?
12:31
SPEAKER_02: And that was the profound realization I had,
12:32
which is the reason why this company today could have been
12:35
started in a bedroom and
12:36
not in a literal wet lab is because suddenly genetics is
12:40
actually a computational
12:41
SPEAKER_02: science.
12:42
SPEAKER_02: And that is something that I think at the time it was obvious to me
12:45
SPEAKER_02: retrospectively,
12:45
SPEAKER_02: as I see how other companies have kind of built out their technologies,
12:49
SPEAKER_02: that actually wasn't obvious.
12:50
SPEAKER_00: So this was kind of what I was asking earlier.
12:53
SPEAKER_00: If you're in my seat, somebody's covered this stuff for a long time.
12:57
SPEAKER_00: People have been...
12:59
like i said telling me this is a computational problem this is
13:02
all software now for
13:04
yeah 10 12 15 years and and what it just it's just taken longer
13:09
um you know
13:10
obviously people have been working on that you've got drew andy
13:13
at stanford george
13:13
church does so much stuff like this but you you you just felt
13:17
like there were
13:18
SPEAKER_00: obviously opportunities people had missed or or
13:21
SPEAKER_02: I think a lot of things.
13:22
SPEAKER_02: I think one that people forget that even when 23 got started in 2006,
13:25
SPEAKER_02: the cost of being a human genome was $10 million a sample.
13:28
SPEAKER_02: So in my mind,
13:28
SPEAKER_02: any sequencing company that had existed,
13:31
SPEAKER_02: even in 2010,
13:32
SPEAKER_02: 2015,
13:32
SPEAKER_02: it was way too expensive.
13:34
SPEAKER_02: When I started Nucleus in 2021,
13:36
SPEAKER_02: around a year later,
13:38
SPEAKER_02: I went to set up the initial infrastructure.
13:40
SPEAKER_02: I was quoted a price of like $2,000 per genome.
13:44
And then literally two months later,
13:45
it dropped down to whatever,
13:46
200 bucks from Illumina.
13:48
SPEAKER_02: And I started thinking,
13:49
SPEAKER_02: well,
13:49
SPEAKER_02: you know,
13:50
SPEAKER_02: like,
13:51
SPEAKER_02: you know,
13:51
whatever people have told me is basically complete bullshit
13:53
because the sequencing
13:54
SPEAKER_02: has been way,
13:54
SPEAKER_02: way,
13:55
SPEAKER_02: way,
13:55
SPEAKER_02: way too expensive.
13:56
I mean,
13:56
the fact that 23andMe was still the company after 20 years,
14:01
right?
14:01
SPEAKER_02: Since 2006, there's been 7,000 ride sharing companies.
14:04
SPEAKER_02: There's been a million social media companies.
14:06
SPEAKER_02: You know, there's been bazillion crypto companies.
14:08
SPEAKER_02: Where are the genetics companies?
14:09
If you go and say,
14:10
okay,
14:10
name another genetics company,
14:11
people cannot think of one.
14:13
SPEAKER_02: And then it's actually related to a lot of the embryo launch we just did,
14:16
SPEAKER_02: too,
14:16
SPEAKER_02: because if you think about embryo,
14:17
SPEAKER_02: nucleus embryo,
14:18
SPEAKER_02: it's software.
14:19
SPEAKER_02: We're the application layer.
14:20
SPEAKER_02: We don't do the testing.
14:22
We actually don't really,
14:22
you know,
14:23
we're partners with general prediction.
14:25
We recommend people do genomic prediction to do the testing for
14:28
their embryos.
14:29
SPEAKER_02: But fundamentally, we're an application layer.
14:30
SPEAKER_02: We're embryo selection software.
14:32
SPEAKER_02: And I think it's the greatest manifestation of this idea,
14:34
SPEAKER_02: which is us saying,
14:36
SPEAKER_02: how do you know that genetics is now computational science?
14:38
SPEAKER_02: Well,
14:39
we have a product in production that literally takes in raw DNA
14:43
files from another
14:44
SPEAKER_02: laboratory,
14:45
SPEAKER_02: and that we analyze and give results to the patient.
14:47
SPEAKER_02: That's how you know, I think, that we're finally actually there.
14:49
And in part,
14:50
that's because the sequencing cost is actually now a couple
14:52
hundred bucks.
14:53
SPEAKER_02: It's not thousands of dollars.
14:54
SPEAKER_02: It's not tens of thousands of dollars.
14:56
SPEAKER_02: And also,
14:56
I think there's a way you have to tell this story that a lot of
14:58
sequencing
14:59
SPEAKER_02: companies historically missed.
15:00
SPEAKER_02: Even some of the people you mentioned,
15:02
SPEAKER_02: they've thrown their hat in the ring and started companies before.
15:05
SPEAKER_02: They didn't tell the right story to consumers.
15:07
And that's something that I think 23andMe,
15:09
you know,
15:09
actually did successfully.
15:11
SPEAKER_02: It lost a lot of credit for that in the last, you know, several years.
15:13
But they actually told the compelling story about why it
15:15
matters to do genetic tests.
15:17
SPEAKER_02: But of course, it was about genealogy.
15:18
And so now the kind of scope of what it means to be a genetics
15:21
company is expanding.
15:23
SPEAKER_02: That's how I think about it.
15:24
SPEAKER_00: Okay.
15:24
SPEAKER_00: I have...
15:26
I'm going to fast forward for a second and then I'm going to
15:27
come back because I do
15:29
SPEAKER_00: want to still ask about sort of that,
15:30
SPEAKER_00: the Teal Fellowship and making this leap.
15:33
SPEAKER_00: But I want to hit this point.
15:35
SPEAKER_00: So the 23andMe,
15:37
SPEAKER_00: I mean,
15:37
SPEAKER_00: I think a lot of people listening to this will probably know this,
15:40
SPEAKER_00: but,
15:40
SPEAKER_00: you know,
15:41
they only ever partly because of the cost issue you're talking
15:45
about were testing
15:46
one percent of your dna this this small sample and and and to
15:50
your point you know i
15:52
some of the ancestry information was pretty interesting but
15:55
when you start digging
15:56
a little deeper into the medical stuff i always found it like
15:59
kind of unfulfilling
16:00
and maybe you know for some people that's a good thing it just
16:03
means your dna is
16:04
SPEAKER_00: Not that interesting.
16:04
SPEAKER_00: But,
16:05
SPEAKER_00: you know,
16:05
so now we've moved to this new era where you can do whole
16:08
genome sequencing and go
16:09
SPEAKER_00: over the whole thing.
16:10
I actually did...
16:11
I did a story with Illumina,
16:13
I want to say about a decade ago.
16:15
They used to have a program where you could pay quite a bit of
16:18
money to...
16:20
have your whole genome sequenced,
16:21
and they would pair you with the doctor.
16:24
SPEAKER_00: And so I actually went through that process for stories.
16:27
SPEAKER_00: I've had my whole genome sequenced for a long time.
16:29
SPEAKER_00: And you can do it again, right?
16:30
SPEAKER_00: Don't you have the nucleus DNA kit somewhere?
16:32
SPEAKER_00: Yes, I do.
16:34
SPEAKER_00: So I've been bad.
16:35
SPEAKER_00: I got this months ago, and you've been texting me until I do it.
16:40
SPEAKER_02: That's my job.
16:41
SPEAKER_00: You can tell me if it's so old that if it still looks like this or not.
16:44
SPEAKER_00: Let's see.
16:46
SPEAKER_00: Oh, well, I'm going to wrap the whole kit.
16:49
SPEAKER_00: Okay, here we go.
16:50
SPEAKER_00: Will this still work?
16:51
SPEAKER_00: I think this is like five or six months.
16:53
SPEAKER_00: I think this will still work, yes.
16:55
SPEAKER_00: Okay.
16:55
SPEAKER_02: DNA is a very stable molecule.
16:56
SPEAKER_02: Should I keep going or?
16:58
SPEAKER_02: I mean, it seems like your sample is in there, so.
17:00
SPEAKER_02: It seems like you collected your sample already.
17:02
SPEAKER_00: No, no, no, I haven't.
17:03
SPEAKER_00: Oh, you haven't?
17:03
SPEAKER_00: I haven't.
17:04
SPEAKER_02: Okay.
17:04
SPEAKER_02: Oh, this is a recollect kit.
17:05
SPEAKER_02: That's why.
17:05
SPEAKER_02: Yeah, yeah, yeah.
17:06
SPEAKER_02: Oh, yeah, because you messed up the first time.
17:07
SPEAKER_02: All right.
17:08
SPEAKER_02: So then you just swab and, you know, it's so easy.
17:10
SPEAKER_02: Just take your swab and just swab your cheeks.
17:13
SPEAKER_00: I was telling you, I chew on these nicotine mints all the time.
17:18
SPEAKER_00: I think I did try to do this once before.
17:20
SPEAKER_00: I think it messed up.
17:20
SPEAKER_02: You know, the kit is usually more beautiful than this.
17:23
SPEAKER_02: So has it changed?
17:24
SPEAKER_02: No, no.
17:24
SPEAKER_02: This is a recollect.
17:25
SPEAKER_02: So we sent you, you know, not as nice, I have to say.
17:27
If it's a recollect,
17:28
we're like,
17:28
okay,
17:29
we'll send you a new one,
17:29
but you won't get the nice kit.
17:31
SPEAKER_00: I apologize for that.
17:34
SPEAKER_00: And so, okay, so you can test your whole genome.
17:38
SPEAKER_00: It's been cool.
17:38
SPEAKER_00: So when I did that test, I had this doctor, Brad Pitay, in San Diego.
17:44
SPEAKER_00: He kind of partnered with Illumina, and it was really cool.
17:47
SPEAKER_00: I mean, you can bring up your whole genetic code.
17:49
SPEAKER_00: There were, when I was
17:51
looking at this a lot there are all these open source
17:53
applications where you can
17:54
like go hunt around for things you're interested in it was
17:57
awesome and then every
17:57
now and then he'll call me and whatever something updates in
18:01
the software and he's
18:02
like oh just so you know you know you might want to keep an eye
18:04
out for this or
18:05
that if I do if I do your test today I know you have these
18:10
different product lines
18:12
SPEAKER_00: but
18:13
SPEAKER_00: Okay.
18:14
I mean,
18:15
I find this fascinating,
18:15
because to your point,
18:17
23andMe was this huge hit,
18:19
it felt like.
18:20
SPEAKER_00: Did very well for a while.
18:21
Really captured,
18:23
everybody knows that brand,
18:25
but it was this very limited test.
18:26
SPEAKER_00: So in some ways, you guys have just rebooted this idea.
18:31
SPEAKER_00: I know there's more to it,
18:32
SPEAKER_00: but in some ways,
18:32
SPEAKER_00: you've just rebooted this idea for a whole genome sequence era.
18:36
SPEAKER_00: I think...
18:37
SPEAKER_02: So the way of thinking about the genetics industry is the following.
18:42
There are consumer genetics businesses,
18:43
which historically have been kind of gimmicks.
18:45
SPEAKER_02: People always talk about 23,
18:46
but obviously Ancestry is actually the largest genetic testing
18:49
company in the
18:49
SPEAKER_02: world.
18:50
SPEAKER_02: And they do genealogy, obviously it's called Ancestry.
18:52
SPEAKER_02: So that's kind of one division.
18:53
Then there's kind of clinical genetics companies that do like
18:55
hereditary breast
18:56
SPEAKER_02: cancer screening,
18:57
SPEAKER_02: for example,
18:57
SPEAKER_02: like Myriad Genetics.
18:59
SPEAKER_02: Then there's preconception testing,
19:00
SPEAKER_02: right,
19:00
to see basically if you and your significant other are at risk
19:03
of passing down a
19:04
SPEAKER_02: serious genetic condition to your child,
19:05
SPEAKER_02: which is a company like Natera.
19:07
SPEAKER_02: Natera is like a $20 billion company, actually.
19:08
SPEAKER_02: They do other things, but it's a $20 billion company.
19:11
SPEAKER_02: Then there's pharmacogenomics,
19:12
SPEAKER_02: where basically your DNA can affect your thousand different drugs,
19:15
SPEAKER_02: right?
19:16
SPEAKER_02: And then there's also IVF testing companies,
19:18
SPEAKER_02: right,
19:18
which look at basically your embryos and give you information
19:21
to your embryos.
19:21
SPEAKER_02: Orkid, we put a whole video out with them.
19:23
SPEAKER_02: Noir's cool.
19:24
SPEAKER_02: Yeah.
19:24
SPEAKER_02: Genetic prediction, there's many of them.
19:26
And what we do is we combine all these companies,
19:29
all these applications into one.
19:31
Because the fundamental realization of a company like Nucleus
19:33
is the application
19:35
SPEAKER_02: layer is king,
19:35
SPEAKER_02: the software layer is king,
19:37
and there's really no actual difference between analyzing an
19:40
embryo DNA file and an
19:42
SPEAKER_02: adult DNA file.
19:42
SPEAKER_02: It looks the same.
19:43
SPEAKER_02: Similarly,
19:44
when you analyze for genealogy or you analyze for breast cancer
19:47
or schizophrenia or
19:48
SPEAKER_02: pharmacogenomics,
19:48
SPEAKER_02: again,
19:49
SPEAKER_02: once you have the whole genome,
19:51
there's no reason why there should be six different companies
19:53
focusing on six
19:54
SPEAKER_02: different applications.
19:55
SPEAKER_02: Historically,
19:55
that made sense because it was almost like the old analogy
19:58
where there's a fence
19:59
SPEAKER_02: set up for a long loss problem,
20:00
SPEAKER_02: right?
20:01
SPEAKER_02: In other words,
20:02
there were so many fences set up because the underlying
20:04
assumption of these
20:05
SPEAKER_02: businesses was that you couldn't read the whole genome.
20:07
SPEAKER_02: So think of your DNA as like a thousand page book, right?
20:10
SPEAKER_02: You could maybe read a page of the book.
20:12
SPEAKER_02: And so, you know,
20:12
SPEAKER_02: Different companies said,
20:13
SPEAKER_02: okay,
20:13
SPEAKER_02: we'll each focus on different pages,
20:15
SPEAKER_02: and then those old companies actually became very successful.
20:17
SPEAKER_02: Us, we're collapsing that model.
20:18
SPEAKER_02: We're saying, actually, every application can exist in Nucleus.
20:22
SPEAKER_02: We're building the health and reproductive stack.
20:24
SPEAKER_02: And moreover, there's no such thing as a genetics company.
20:27
SPEAKER_02: And that we can talk about, too.
20:28
SPEAKER_02: Because the thing that people forget,
20:29
SPEAKER_02: too,
20:29
SPEAKER_02: about 23andMe is they'll sometimes say,
20:31
SPEAKER_02: oh,
20:31
SPEAKER_02: 23andMe is a one-time test.
20:32
SPEAKER_02: The ethos of a business of 23andMe, it was an offshoot of Google.
20:36
SPEAKER_02: 23andMe's first investor was Google.
20:38
SPEAKER_02: It was part of the kind of Web 2.0 movement.
20:40
SPEAKER_02: where the idea was similar to Google or Facebook's model,
20:43
SPEAKER_02: which is collect a lot of data and then sell that to a third party.
20:46
SPEAKER_02: In other words, the customer wasn't the customer.
20:49
23andMe could have been the most successful consumer health
20:52
business ever.
20:53
SPEAKER_02: They could have been, right?
20:54
SPEAKER_02: I mean, they kind of predicated the longevity movement
20:56
and they had more reach and distribution than any other
20:59
longevity kind of consumer
21:01
SPEAKER_02: health startup.
21:02
SPEAKER_02: The reason why they didn't do that is because that wasn't their business.
21:04
SPEAKER_02: People sometimes will conflate to the fact that genetics is one time,
21:08
SPEAKER_02: that's why it's not a good business.
21:10
SPEAKER_02: Genetics actually,
21:11
SPEAKER_02: I would argue one,
21:11
I'd argue it's actually something that is increasingly valuable
21:15
year over year.
21:15
SPEAKER_02: But even barring that point,
21:17
the reason why 2030 didn't create recurring value for the
21:20
consumer is because they
21:22
SPEAKER_02: were trying to serve the pharma company.
21:23
right it was the google model is the facebook model the
21:25
customers and the customer
21:27
and that collapsed yes and that collapsed in itself because
21:29
23me data is so
21:31
fundamentally limited it's actually not all that good for
21:33
making drugs and so if
21:34
SPEAKER_02: 23me had said actually the dna is the foundation to build a real-time
21:37
consumer-centric quantified health platform where you take
21:40
someone's genetics their
21:41
blood their mris their wearables and we integrate all that
21:44
together they would be
21:45
SPEAKER_02: worth you know 100x they would have got inquired for 100x and they did
21:49
SPEAKER_02: And so from that perspective,
21:50
SPEAKER_02: too,
21:50
you start realizing DNA is one of many tools to build this
21:53
consumer health stack,
21:55
SPEAKER_02: and moreover,
21:55
SPEAKER_02: DNA as the only lab test that's generational in nature,
21:59
SPEAKER_02: right?
21:59
SPEAKER_02: And that's what's so interesting.
22:00
SPEAKER_02: You know,
22:00
SPEAKER_02: you take a blood test in mom,
22:01
SPEAKER_02: you're not going to use that to make insights into your future child,
22:03
SPEAKER_02: obviously,
22:04
SPEAKER_02: right?
22:04
SPEAKER_02: But genetics is literally what you pass down to your child, right?
22:07
SPEAKER_02: It's literally you're a function of your mom and your dad.
22:09
SPEAKER_02: And so in that way,
22:10
SPEAKER_02: too,
22:10
SPEAKER_02: you start realizing this idea that,
22:12
SPEAKER_02: you know,
22:12
SPEAKER_02: we call it generational health and nucleus,
22:14
SPEAKER_02: that
22:15
SPEAKER_02: when you do a genetic test,
22:16
SPEAKER_02: you're actually also doing genetic tests for your child,
22:20
SPEAKER_02: but also for your mother,
22:21
SPEAKER_02: for your brother,
22:22
SPEAKER_02: for your sister.
22:22
SPEAKER_02: In other words,
22:23
SPEAKER_02: there's a familial nature to the diagnostic test that simply speaking,
22:26
SPEAKER_02: for whatever reason,
22:27
SPEAKER_02: no one has taken advantage of.
22:29
SPEAKER_00: Well,
22:29
SPEAKER_00: because I think sometimes if you did do 23andMe,
22:33
SPEAKER_00: it felt unfulfilling because unless you had something horrendous,
22:37
SPEAKER_00: like the BRCA gene or something,
22:39
SPEAKER_00: there were only like three or four things where it was like,
22:42
SPEAKER_00: you really should...
22:44
SPEAKER_00: go check this out.
22:44
Otherwise,
22:45
it's kind of like,
22:45
oh,
22:46
you might be like kind of predisposed to this or that.
22:49
SPEAKER_00: And it was sort of like, well, what am I supposed to do with that?
22:51
SPEAKER_02: And that's in part because the technology was so limited.
22:53
SPEAKER_02: So let me give you an example.
22:54
SPEAKER_02: So now you would expect around 90% of Nucleus customers,
22:58
they find out that they're actually carrier for a genetic
23:00
marker they didn't know.
23:01
SPEAKER_02: That's pretty crazy.
23:02
I mean,
23:03
basically,
23:03
like for me,
23:03
for example,
23:04
I'm a carrier for cystic fibrosis.
23:06
SPEAKER_02: I had no idea.
23:07
SPEAKER_02: Obviously, it's not in my family because it's a recessive condition.
23:10
SPEAKER_02: What do you do with that?
23:10
Well,
23:11
I mean,
23:11
now the key is every single time I go on a date with anyone,
23:14
I'm not even kidding.
23:15
SPEAKER_02: I'm like, hey, I mean, I don't want my kid to have cystic fibrosis.
23:19
SPEAKER_02: The worst thing that could happen,
23:20
SPEAKER_02: and it still happens,
23:20
SPEAKER_02: is millions of babies of genetic conditions where you date someone,
23:24
SPEAKER_02: you get married,
23:24
SPEAKER_02: you fall in love,
23:25
SPEAKER_02: and you simply don't swab your cheeks.
23:26
And then God forbid your son or daughter has a very serious
23:29
debilitating disease
23:30
SPEAKER_02: that just invisibly was passed down.
23:33
SPEAKER_02: I mean, so what do you do?
23:34
SPEAKER_02: I mean,
23:35
SPEAKER_02: literally,
23:35
SPEAKER_02: if you and your significant other,
23:37
SPEAKER_02: in my case,
23:37
SPEAKER_02: if my girlfriend was also a care for cystic fibrosis,
23:40
SPEAKER_02: I would do nucleus embryo.
23:41
SPEAKER_02: So now we think about that.
23:42
SPEAKER_02: Now we create the stack.
23:44
SPEAKER_00: Wait, let's stop for one second.
23:45
I saw you do an Instagram date with,
23:49
with a woman and you guys went to this longevity.
23:52
SPEAKER_00: Yeah.
23:53
SPEAKER_00: You had some, uh, what did you go into?
23:55
SPEAKER_00: It was like slot.
23:56
SPEAKER_00: It was a lymph, lymph, lymph, lymphatic drainage.
24:01
SPEAKER_00: You guys were getting along.
24:02
SPEAKER_00: Um, she was very nice.
24:03
SPEAKER_00: She was very nice.
24:04
SPEAKER_00: Yeah.
24:04
You guys were having,
24:05
she was fully into the whole,
24:07
so you go into this,
24:08
this video is great.
24:09
SPEAKER_00: People should go look at it.
24:11
SPEAKER_00: Um,
24:12
SPEAKER_00: And you're very clear.
24:13
It's like,
24:13
we're going to have this date,
24:14
but at the end,
24:15
we're going to do our test.
24:16
SPEAKER_00: And if we're not a match, this whole thing is over.
24:20
SPEAKER_00: And you guys are kind of getting along.
24:23
SPEAKER_00: I mean, you're both very nice to each other.
24:24
SPEAKER_00: It seemed like you were enjoying the lymphatic drainage.
24:27
SPEAKER_00: and having a good time.
24:28
SPEAKER_00: And then you do the test at the end.
24:30
SPEAKER_00: You're not a match.
24:32
SPEAKER_00: I was trying to pause the screen.
24:37
SPEAKER_00: Or maybe it's her medical information.
24:39
SPEAKER_00: We can't talk about it.
24:40
SPEAKER_00: It is her medical information.
24:41
SPEAKER_00: But vaguely,
24:42
SPEAKER_00: she had...
24:43
SPEAKER_02: Basically,
24:43
SPEAKER_02: yeah,
24:43
SPEAKER_02: there was a risk of the child having a serious condition.
24:47
SPEAKER_02: I'm not going to specify what it was.
24:48
SPEAKER_02: But I think that it's funny.
24:50
SPEAKER_02: And then you guys just call it off and you hug her and send her on her
24:55
SPEAKER_02: It might seem like sci-fi and creepy maybe even almost,
24:58
SPEAKER_02: but this is done in certain communities.
25:00
SPEAKER_02: The Ashkenazi Jewish community,
25:01
SPEAKER_02: for example,
25:02
they will only matchmake based off of people are not the same
25:04
carrier for the same
25:05
SPEAKER_02: condition.
25:05
SPEAKER_02: I think- Because they have like canavans and all kinds of- Yeah,
25:08
SPEAKER_02: there's all sorts of different carriers for things.
25:10
SPEAKER_02: But the thing is that what's interesting about this is like,
25:13
when you're dating someone,
25:14
presumably you're getting as much information as you can.
25:18
SPEAKER_02: Let's be real,
25:19
SPEAKER_02: you're looking at their Instagram,
25:20
SPEAKER_02: you're looking at their parents,
25:21
SPEAKER_02: you're looking at their job,
25:22
SPEAKER_02: their career,
25:23
SPEAKER_02: their this.
25:23
SPEAKER_02: You're looking at everything.
25:24
SPEAKER_02: I mean, it's your significant other, right?
25:25
SPEAKER_02: This might be the most important decision,
25:26
SPEAKER_02: probably is the most important person decision of your entire life.
25:29
SPEAKER_02: There's no reason why
25:30
I think it's a very reasonable question to be like,
25:32
well,
25:32
is our DNA compatible?
25:33
SPEAKER_02: Are we a genetic match?
25:34
SPEAKER_02: I think it's just a very reasonable question.
25:36
SPEAKER_02: You don't want to have a child with a serious condition.
25:38
SPEAKER_02: A swab could save your future child's life.
25:40
SPEAKER_02: I mean, you're probably going to swab your cheeks.
25:42
And so in this case,
25:42
I think it was interesting because it was actually an organic
25:45
date.
25:45
SPEAKER_02: It was all real.
25:46
SPEAKER_02: And we didn't actually know.
25:48
you know,
25:48
on the one hand,
25:49
I think,
25:50
you know,
25:50
Aurora,
25:51
she was sort of the girl in the video.
25:52
SPEAKER_02: I think she was like disappointing that we weren't in genetic match,
25:54
SPEAKER_02: but also I think in a way it's ultimately really informative.
25:57
SPEAKER_02: Like, I don't know.
25:58
SPEAKER_02: I felt like in a really way empowering,
25:59
SPEAKER_02: like imagine like,
26:00
SPEAKER_02: you know,
26:00
SPEAKER_02: you fall in love and then,
26:02
SPEAKER_02: you know,
26:02
SPEAKER_02: you're going to have kids and you can do nucleus embryo,
26:04
SPEAKER_02: so it's fine,
26:05
SPEAKER_02: right?
26:05
SPEAKER_02: You can always do that and you can pick the embryo without the condition.
26:07
SPEAKER_02: And again,
26:07
SPEAKER_02: that's why it's like,
26:08
SPEAKER_02: sometimes people are like,
26:08
SPEAKER_02: oh,
26:09
SPEAKER_02: I don't want to do it because what if we're not in genetic match?
26:10
SPEAKER_00: But if you love her, that's fine.
26:13
SPEAKER_02: You can then do IVF and you can pick the baby without the condition.
26:16
SPEAKER_02: But at the beginning phase before you're like, okay, who should I date?
26:19
I mean,
26:20
I think it's pretty reasonable to say,
26:21
hey,
26:21
you know,
26:21
you should swab your cheeks.
26:22
SPEAKER_02: Yeah.
26:23
SPEAKER_02: And how like, okay, because it's all percentages, right?
26:25
SPEAKER_02: I mean.
26:26
SPEAKER_02: In this case, it wouldn't be.
26:27
SPEAKER_02: In this case, it would be.
26:28
SPEAKER_02: So genetics is different.
26:30
SPEAKER_02: There's different kinds of genetics.
26:31
SPEAKER_02: So one is like kind of what people might know,
26:33
SPEAKER_02: like where,
26:34
SPEAKER_02: you know,
26:34
someone falls in some sort of like in the symptoms or something
26:37
radioactive
26:37
SPEAKER_02: material,
26:38
SPEAKER_02: they get some mutation and then like they have some trait.
26:40
That's a model of like what's called monogenic conditions or
26:43
conditions where,
26:43
SPEAKER_02: you know,
26:44
SPEAKER_02: I know you know this,
26:44
SPEAKER_02: where there's like a bad
26:45
SPEAKER_02: marker and you get a disease.
26:46
SPEAKER_02: Single gene.
26:47
SPEAKER_02: Yeah, single gene.
26:48
SPEAKER_02: Like a BRCA variant, for example.
26:49
Even BRCA though is probabilistic in nature,
26:51
but basically it's high penetrant.
26:52
SPEAKER_02: So you'd expect to get this condition, right?
26:55
SPEAKER_02: And so a lot of,
26:55
SPEAKER_02: or not a lot,
26:57
SPEAKER_02: a portion of the rare genetic conditions are,
27:00
SPEAKER_02: you can imagine,
27:00
SPEAKER_02: more deterministic in nature.
27:02
SPEAKER_02: Then it gets to common conditions,
27:04
SPEAKER_02: like things like heart disease,
27:05
SPEAKER_02: things like schizophrenia,
27:06
SPEAKER_02: like Parkinson's,
27:07
SPEAKER_02: for example,
27:08
SPEAKER_02: different cancers,
27:09
SPEAKER_02: where it's more probabilistic in nature.
27:11
SPEAKER_02: where it's like,
27:11
SPEAKER_02: hey,
27:12
SPEAKER_02: a typical woman has a 13% chance of breast cancer,
27:15
SPEAKER_02: you have a 25% chance,
27:17
SPEAKER_02: or apply that across schizophrenia or anything else.
27:19
SPEAKER_02: And in the kind of genetic matching we do right now,
27:24
SPEAKER_02: it's very much in this camp,
27:25
SPEAKER_02: which is like the more deterministic camp,
27:26
SPEAKER_02: so it's very kind of cut and dry,
27:28
SPEAKER_02: right?
27:30
SPEAKER_02: But I do want to just emphasize this point again.
27:32
SPEAKER_02: you know,
27:32
SPEAKER_02: if you are not a genetic magic thing or another,
27:34
SPEAKER_02: that is the beginning of the story of having healthy children.
27:36
That is not the end of the relationship because then what do
27:39
you do,
27:39
right?
27:39
And this is kind of the beauty of the kind of health and
27:41
reproductive stack that we're building.
27:42
SPEAKER_02: This is sort of the,
27:43
SPEAKER_02: you know,
27:43
really unique things about nuclease and the fact that we do
27:45
adult tests and we also
27:46
SPEAKER_02: do now embryo analysis as well,
27:48
SPEAKER_02: which is,
27:48
SPEAKER_02: hey,
27:49
SPEAKER_02: you guys are both carriers for cystic fibrosis.
27:51
SPEAKER_02: We're going to make sure that when you go do IVF,
27:54
SPEAKER_02: we're going to pick a baby without cystic fibrosis,
27:56
SPEAKER_02: right?
27:56
SPEAKER_02: And maybe even beyond without cystic fibrosis,
27:58
SPEAKER_02: they won't even necessarily need to be a carrier for cystic fibrosis.
28:01
We can go even one step beyond because now all of a sudden
28:03
there's this idea of
28:04
SPEAKER_02: generational health where you literally from your bloodline,
28:06
SPEAKER_02: so to speak,
28:07
SPEAKER_02: are getting rid of a bad marker.
28:09
I mean,
28:09
I don't think there's a family that wouldn't say,
28:11
okay,
28:12
well,
28:12
obviously why not?
28:13
SPEAKER_02: Especially if you're going to do IVF, why not?
28:16
SPEAKER_00: Okay, so...
28:18
SPEAKER_00: Let's dig into that for a second.
28:20
SPEAKER_00: And I don't mean this to be super combative.
28:22
SPEAKER_00: Before you came on,
28:23
SPEAKER_00: I was just like asking some friends,
28:24
SPEAKER_00: you know,
28:24
SPEAKER_00: and so because you're talking about being quite general purpose.
28:27
If I look at someone like Orchid,
28:29
you know,
28:29
they've got,
28:31
they have their own labs,
28:32
right?
28:32
SPEAKER_00: And they're doing, I went to an IVF clinic.
28:35
SPEAKER_00: I mean, they've got this partnership.
28:37
SPEAKER_00: There's an embryologist there, Pamela.
28:39
SPEAKER_00: We did a video with her.
28:40
SPEAKER_00: I mean, she's amazing at her job, just selecting these cells.
28:43
SPEAKER_00: There's a lot of stuff that goes into it, right?
28:46
SPEAKER_00: And so you could argue, okay,
28:48
SPEAKER_00: Well, if I'm doing the IVF part, ORCID pays so much attention to this.
28:53
SPEAKER_00: They've done all this science.
28:54
SPEAKER_00: They've got these relationships with the IVF clinic.
28:58
SPEAKER_00: You know, they're really putting so much focus and attention into this.
29:03
Some of my biotech friends were like,
29:05
well,
29:05
nucleus,
29:06
you know,
29:06
they don't have their own lab.
29:07
SPEAKER_00: This is all software.
29:09
SPEAKER_00: And...
29:10
um yeah i mean i i think they were presenting this as as a ding
29:13
right that that um
29:15
the level of science is is different with a company like orchid
29:19
versus you guys and
29:20
and maybe this is kind of where you're at or maybe not yeah i
29:23
was just and i know i
29:24
appreciate i've seen you on reddit i mean you you take all
29:28
questions and and you
29:29
know seems like you're you're um totally good addressing things
29:34
like this yeah
29:34
SPEAKER_02: absolutely um
29:37
There are companies like the ones you mentioned that are
29:39
focused on the testing of
29:41
SPEAKER_02: the embryos,
29:41
SPEAKER_02: right?
29:42
SPEAKER_02: And there's many of them, right?
29:43
SPEAKER_02: Genetic Predictions, our partners.
29:46
SPEAKER_02: We focus on the analysis.
29:47
SPEAKER_02: It's not that it's analysis is better than the testing.
29:51
SPEAKER_02: I mean,
29:51
SPEAKER_02: the testing,
29:51
SPEAKER_02: the function of the testing in the context of like,
29:54
SPEAKER_02: you know,
29:54
SPEAKER_02: laboratory is to principally generate a raw DNA file.
29:58
SPEAKER_02: That raw DNA file is analyzed.
30:00
SPEAKER_02: The value exists in the application layer.
30:03
It's not that the lab testing is more important than the lab
30:06
analysis or the
30:06
SPEAKER_02: analysis is more important than the testing.
30:08
SPEAKER_02: It's about what do you want to focus on.
30:10
SPEAKER_02: We focus on the analysis.
30:11
SPEAKER_02: We focus on the software.
30:13
SPEAKER_02: We are the only selection software.
30:14
SPEAKER_02: We're the only genetic optimization software.
30:16
SPEAKER_02: We provide analysis on everything.
30:18
So from our perspective,
30:19
we're actually complementary to these companies that you
30:21
mentioned.
30:22
SPEAKER_02: We're actually not competitive with them.
30:23
SPEAKER_02: We want people, more and more people to do IVF.
30:26
SPEAKER_02: We want people to get access to the raw files.
30:30
And then at that point,
30:31
people can actually genetically optimize their babies on
30:33
nucleus.
30:34
SPEAKER_02: And I think that's interesting because for us,
30:36
SPEAKER_02: there's a couple of things that we do fundamentally differently.
30:38
SPEAKER_02: One is we don't put an arbitrary line in the sand and saying,
30:41
SPEAKER_02: hey,
30:42
SPEAKER_02: you can get diseases,
30:43
SPEAKER_02: but you can't get traits.
30:44
SPEAKER_02: We believe in genetic optimization.
30:46
We believe if couples want access to height or IQ or hair color
30:49
or eye color,
30:51
SPEAKER_02: or alcohol dependency, they should have access to that.
30:54
SPEAKER_02: Another thing is we really believe in the consumer deciding.
30:58
So this is a different approach than some of the companies that
31:00
focus on the
31:01
SPEAKER_02: testing,
31:02
which is we really see it not as the doctor's choice to make
31:05
the decision.
31:06
SPEAKER_02: If you go to an IVF clinic today,
31:08
SPEAKER_02: generally speaking,
31:09
SPEAKER_02: the doctor's the one that's picking the embryo.
31:12
we see it as very similar to our model in the context of adult
31:16
populations as well,
31:17
SPEAKER_02: which is this idea of participatory medicine.
31:19
So just take a step back here to kind of understand the kind of
31:23
ideological
31:23
SPEAKER_02: framework,
31:23
SPEAKER_02: which is,
31:24
SPEAKER_02: you know,
31:25
SPEAKER_02: Dr.
31:25
SPEAKER_02: Lee Roy Hood is a very famous scientist.
31:26
He said that,
31:27
you know,
31:27
the best medical system is one that follows these four P
31:30
structure.
31:30
SPEAKER_02: So one that's personalized, that's predictive, um,
31:34
SPEAKER_02: And that's participatory.
31:36
SPEAKER_02: And one more, I think I'm missing a predictive maybe.
31:39
And basically he described a system that at the beginning can
31:45
prevent conditions
31:46
SPEAKER_02: that can predict conditions before they happen,
31:48
SPEAKER_02: effectively switching from a sick care system.
31:50
SPEAKER_02: to a true preventative system.
31:52
SPEAKER_02: And part of that is actually the consumer being in the driver's seat.
31:55
SPEAKER_02: It's actually not the physician.
31:56
SPEAKER_02: So the physician historically has been,
31:57
SPEAKER_02: I would argue,
31:58
SPEAKER_02: somewhat of a gatekeeper,
31:59
SPEAKER_02: somewhat of a blocker.
32:00
SPEAKER_02: And you can see already in the kind of upstream in the adult land,
32:03
SPEAKER_02: in the adult testing and longevity land,
32:05
SPEAKER_02: led by someone like Brian Johnson,
32:06
SPEAKER_02: which is like,
32:07
SPEAKER_02: I am actually the agent of my own healthcare.
32:10
SPEAKER_02: We are taking that principle now and applying to the embryonic context.
32:13
SPEAKER_02: By being software, it's not a disadvantage, it's actually an advantage.
32:17
SPEAKER_02: Because now anyone from any IVF clinic,
32:20
SPEAKER_02: no matter what company they use,
32:21
SPEAKER_02: can actually take their files,
32:23
SPEAKER_02: bring it to our software,
32:24
SPEAKER_02: and then they can literally get insight on every disease,
32:27
SPEAKER_02: every trait.
32:28
SPEAKER_02: We are not beholden by the, frankly, more conservative.
32:33
SPEAKER_02: And I would argue,
32:34
SPEAKER_02: and I think you would actually see this in the IVF clinics today,
32:37
SPEAKER_02: they often will conflate science for politics.
32:40
SPEAKER_02: They'll say, hey, you can't get analysis on your baby's height.
32:45
SPEAKER_02: Why?
32:46
SPEAKER_02: That's the single greatest polygenic model we have today is for height.
32:50
You go to an IVF clinic and the doctor will say,
32:52
no,
32:52
no,
32:52
you can't decide off of that.
32:53
SPEAKER_02: So suddenly we're not just kind of philosophically different in that,
32:57
SPEAKER_02: hey,
32:57
we're approaching from a software layer because we actually
33:00
want everyone to have
33:01
SPEAKER_02: access to it.
33:02
SPEAKER_02: Once you're a lab test, you're fundamentally limited.
33:04
SPEAKER_02: For us, it's like, well, you can go do your lab testing anywhere.
33:07
SPEAKER_02: You can generate the raw files.
33:08
SPEAKER_02: You can bring it to us.
33:09
SPEAKER_02: Now what happens?
33:10
SPEAKER_02: One, you're in the driver's seat.
33:12
SPEAKER_02: Not your physician.
33:12
SPEAKER_02: Very important to us.
33:14
SPEAKER_02: Two, you have access to everything.
33:15
Everything from schizophrenia and alcohol dependence to your
33:18
baby's eye color.
33:19
SPEAKER_02: It's not for us to say,
33:20
SPEAKER_02: and in our opinion,
33:21
it's not for the physician to say what you shouldn't and
33:23
shouldn't optimize for.
33:24
SPEAKER_02: And then three, by combining our might.
33:26
SPEAKER_02: Because to be clear, we do adult testing and analysis.
33:31
SPEAKER_02: We operate many laboratories.
33:32
SPEAKER_02: Nucleus is actually an informatics laboratory.
33:35
We're actually one of the only clinical grade whole genome
33:37
informatics laboratories
33:38
SPEAKER_02: in the entire country.
33:40
SPEAKER_02: So there's two laboratories we use.
33:41
SPEAKER_02: There's the wet lab and there's the dry lab.
33:42
SPEAKER_02: We own and we operate our dry lab informatics laboratory.
33:45
SPEAKER_02: So it's not exactly even correct to say we're not a lab.
33:47
SPEAKER_02: We are a lab.
33:48
SPEAKER_02: On the wet lab side of things,
33:49
SPEAKER_02: we also,
33:50
SPEAKER_02: as you know from the swab you have,
33:51
SPEAKER_02: we also do that testing as well.
33:52
SPEAKER_02: So we're very familiar with the kind of testing.
33:54
And the thing we've realized over time is that the testing,
33:57
it's not what's interesting.
33:59
SPEAKER_02: I mean, the testing, I mean, you saw the cost curve.
34:01
SPEAKER_00: It was a billion dollars.
34:02
SPEAKER_00: Now it's $100.
34:02
SPEAKER_02: You know what's going to happen in the next five years, Ashley?
34:05
SPEAKER_02: That's going to be nothing.
34:06
SPEAKER_02: Everything is going to be moved to this software layer.
34:09
SPEAKER_02: So it's not about science.
34:11
SPEAKER_02: It's about the fundamental alpha for the
34:14
SPEAKER_02: consumer in terms of access,
34:15
SPEAKER_02: in terms of the breadth and depth of analyses,
34:18
SPEAKER_02: it exists in the application layer.
34:20
SPEAKER_02: And on that last point,
34:21
SPEAKER_02: which is because we do test adults,
34:23
we can actually make the IVF process much cheaper and much more
34:27
effective and
34:28
SPEAKER_02: targeted for parents.
34:29
SPEAKER_02: Why?
34:30
SPEAKER_02: Well,
34:31
SPEAKER_02: The reality is that if you have like a human embryo,
34:34
SPEAKER_02: the fundamental thing is where does the embryo come from?
34:36
SPEAKER_02: It comes from mom and dad, right?
34:37
We offer some of the cheapest clinical grade whole genome
34:40
testing in the United States.
34:41
So we can very effectively sequence mom and dad and then inform
34:44
the parents on the
34:45
specific markers they need to watch out on and then run a
34:48
cheaper genetic test at
34:49
SPEAKER_02: the embryonic level.
34:50
So suddenly now we've actually made genetic testing not
34:53
something for the super
34:54
SPEAKER_02: rich,
34:54
SPEAKER_02: not something for the creme de la creme of Silicon Valley,
34:57
SPEAKER_02: but something that anyone anywhere can access.
34:59
SPEAKER_02: And so that's kind of the last thing,
35:00
which is by leveraging our strengths in adult testing and kind
35:03
of going full stack
35:04
SPEAKER_02: now,
35:04
SPEAKER_02: we can also make it cheaper and accessible,
35:06
SPEAKER_02: not just patient-empowered and not just giving someone the full stack of
35:09
SPEAKER_02: information.
35:09
SPEAKER_02: You guys partner with Illumina?
35:12
We have partnered with Illumina,
35:13
and now we partner with Genomic Prediction.
35:15
SPEAKER_02: So in a way, it's actually very similar if you think about it.
35:18
People don't think about us in the adult testing context as
35:21
being an application
35:22
SPEAKER_02: layer,
35:22
SPEAKER_02: but functionally speaking,
35:23
SPEAKER_02: we are.
35:24
And that actually goes back to,
35:25
I'm not sure if you know this,
35:26
but there was a...
35:27
SPEAKER_02: There was a company way back when it was called Impute.me.
35:29
SPEAKER_02: It was run by our chief scientist.
35:30
Impute.me was a software service where you could actually take
35:33
a raw 23.me file and
35:35
SPEAKER_02: upload to Impute.me.
35:36
SPEAKER_02: And so that was one of the times Lasse and I,
35:38
SPEAKER_02: the founder of Impute.me,
35:40
SPEAKER_02: he and I became very close.
35:41
SPEAKER_02: I was actually emailing him under a pseudonym.
35:42
SPEAKER_02: There's a whole story.
35:44
SPEAKER_02: I was asking very technical questions under a pseudonym.
35:46
SPEAKER_02: Because you didn't want him to know you were younger.
35:49
SPEAKER_00: I don't even know.
35:49
SPEAKER_00: I think so.
35:50
SPEAKER_02: I didn't want him to look me up.
35:51
SPEAKER_02: So I was like, my name is Bob, who's the worst pseudonym ever.
35:53
This is my biggest regret during that year is I should have
35:56
thought of a better pseudonym.
35:56
SPEAKER_02: I could have gone crazy.
35:58
SPEAKER_02: Bob?
35:58
SPEAKER_02: Come on, Keon.
35:59
SPEAKER_02: What the hell?
36:00
SPEAKER_02: So I was emailing to Bob, and the thing that I think Lasse...
36:03
SPEAKER_02: was so,
36:04
SPEAKER_02: so intelligent for realizing,
36:06
SPEAKER_02: and maybe,
36:07
SPEAKER_02: you know,
36:07
SPEAKER_02: the best,
36:07
SPEAKER_02: you often realize this,
36:08
SPEAKER_02: like the best like insights kind of are accidents almost.
36:11
SPEAKER_02: Like you're almost going through the idea maze and you're like,
36:13
SPEAKER_02: oh,
36:13
SPEAKER_02: let me just do this next obvious thing.
36:15
SPEAKER_02: And the thing I realized,
36:16
SPEAKER_02: this was now almost,
36:17
SPEAKER_02: you know,
36:17
SPEAKER_02: Impute Me had existed like,
36:19
SPEAKER_02: you know,
36:20
SPEAKER_02: 10 years ago,
36:20
SPEAKER_02: 10 plus years ago.
36:21
SPEAKER_02: is that actually the 23andMe customers,
36:24
SPEAKER_02: they could take their raw file and bring it to ImputeMe.
36:27
SPEAKER_02: And so from Lasse's perspective,
36:29
SPEAKER_02: and Nucleus now owns,
36:30
SPEAKER_02: we actually acquired ImputeMe,
36:32
SPEAKER_02: and so it sort of kind of informs our fundamental way that we see this.
36:35
And also me in my bedroom,
36:36
again,
36:36
I told you,
36:36
it was always a software problem for me.
36:37
SPEAKER_02: This is always a software problem.
36:39
SPEAKER_02: It's not a lab testing problem.
36:40
SPEAKER_02: Was that,
36:40
SPEAKER_02: wait a second,
36:41
you can actually apply that same logic of 23andMe to ImputeMe
36:45
to now embryos for
36:45
SPEAKER_02: Nucleus.
36:46
SPEAKER_02: And the thing was,
36:48
SPEAKER_02: at the same time,
36:49
SPEAKER_02: in parallel,
36:49
SPEAKER_02: as we started talking genomic prediction,
36:51
SPEAKER_02: and I said,
36:51
SPEAKER_02: hey,
36:51
SPEAKER_02: why don't we,
36:52
SPEAKER_02: for the first time ever,
36:53
SPEAKER_02: build this stack together?
36:54
SPEAKER_02: And so I think it's sort of this beautiful thing that,
36:58
SPEAKER_02: to say what you said earlier,
36:59
SPEAKER_02: which is like,
36:59
SPEAKER_02: you know,
37:00
SPEAKER_02: oh,
37:00
SPEAKER_02: genetics is computational science.
37:01
SPEAKER_02: People have been saying that for two decades.
37:03
SPEAKER_02: it's here.
37:03
SPEAKER_00: It's live, it's in production.
37:06
SPEAKER_00: I hope so.
37:06
So when I got my whole genome,
37:08
I got the file and yeah,
37:10
for better or worse.
37:11
SPEAKER_00: And what'd you do with the file?
37:12
SPEAKER_00: It probably went around and uploaded.
37:13
SPEAKER_02: No, no, I uploaded.
37:14
SPEAKER_00: Yeah, you uploaded, right?
37:15
SPEAKER_00: Exactly.
37:16
SPEAKER_02: But that's a great example, right?
37:17
SPEAKER_02: Because you have the file, you realize, wait a second,
37:19
SPEAKER_02: The test is cool, but the function of the test is the analysis.
37:23
SPEAKER_00: Well, it's cool because you could hop to Ancestry.
37:26
SPEAKER_00: Yeah, exactly.
37:27
SPEAKER_00: There's a couple other.
37:28
SPEAKER_00: There was a lot.
37:29
SPEAKER_00: Prometheus was my one.
37:30
SPEAKER_00: MyHeritage, I think it's another one.
37:31
SPEAKER_00: MyHeritage, yeah.
37:33
SPEAKER_00: It's interesting because 23andMe,
37:34
SPEAKER_00: I felt like it did really well in the U.S.,
37:37
SPEAKER_00: but if you start uploading to these other sites,
37:40
SPEAKER_00: you get connections with people from other parts of the world.
37:42
SPEAKER_00: Yeah.
37:44
SPEAKER_00: And yeah, so I've been doing that for a long time and better.
37:46
SPEAKER_00: Where's my DNA?
37:47
SPEAKER_00: I'm just giving up on that.
37:51
SPEAKER_00: Ashley, though, think about this.
37:52
SPEAKER_00: Now think about from what you were doing.
37:54
SPEAKER_00: How long ago was this?
37:55
SPEAKER_00: I mean, I've been doing, I've been uploading that, yeah, for a decade.
37:57
So for a decade now,
37:59
we're taking that and saying,
38:00
hey,
38:00
why not for embryos?
38:01
SPEAKER_00: Yeah.
38:02
SPEAKER_02: I mean, think about that.
38:02
It is a natural continuation of an already existing phenomenon
38:07
that exists in the
38:07
SPEAKER_02: adult DNA land,
38:08
SPEAKER_02: which is the alpha is not in the generation of the file.
38:10
SPEAKER_02: The alpha is in the analysis.
38:12
SPEAKER_00: That makes sense.
38:13
SPEAKER_00: I mean, we might as well get into this.
38:15
SPEAKER_00: I don't think we're going to crack any new ground.
38:18
SPEAKER_00: But,
38:18
SPEAKER_00: you know,
38:18
SPEAKER_00: clearly every time you post,
38:20
SPEAKER_00: every time Nora from Orchid posts,
38:23
SPEAKER_00: you know,
38:23
SPEAKER_00: when we did our video...
38:25
SPEAKER_00: Get all the eugenics stuff.
38:27
SPEAKER_00: So there are like there's two bits of this, right?
38:29
So one is like health and I have a lot of trouble with the
38:33
critics on that one.
38:35
I feel like this is coming from a place where they don't really
38:37
understand what's going on.
38:38
SPEAKER_00: So, you know, to me,
38:41
SPEAKER_00: If you're looking at these embryos and one has,
38:44
SPEAKER_00: you know,
38:44
SPEAKER_00: a chance of having this monogenetic,
38:48
SPEAKER_00: horrible,
38:48
SPEAKER_00: debilitating disease,
38:49
SPEAKER_00: and you can not do that,
38:51
SPEAKER_00: to me that seems obvious,
38:52
SPEAKER_00: then the next step people,
38:54
SPEAKER_00: even some people grumble about that,
38:56
SPEAKER_00: but then the next step is like,
38:57
SPEAKER_00: oh,
38:58
SPEAKER_00: okay,
38:58
SPEAKER_00: now we're doing eye color,
38:59
SPEAKER_00: now we're doing height,
39:00
SPEAKER_00: and then...
39:02
SPEAKER_00: You know,
39:04
SPEAKER_00: again,
39:04
I don't think we're going to break new ground here because this
39:06
is like a long
39:06
SPEAKER_00: running debate.
39:07
I think people fear that then suddenly you end up with like all
39:13
the kids look the
39:14
SPEAKER_00: same because there's like some trend.
39:16
SPEAKER_00: I think people will want different things and stuff like that.
39:19
SPEAKER_00: But I mean...
39:22
The biggest thing I've been noticing as a reporter who covers
39:25
this stuff that I
39:25
don't think the public is aware of is whether it's ORCID or you
39:29
guys or other...
39:32
SPEAKER_00: This moment has arrived in 2025 in a pretty big way.
39:36
SPEAKER_00: This is not going away.
39:37
SPEAKER_00: We're going to get better and better data.
39:39
SPEAKER_00: There's going to be more choices to be made.
39:42
SPEAKER_00: I don't think most people are sort of... To me, it feels like...
39:47
SPEAKER_00: The stuff we talked about,
39:48
SPEAKER_00: the things that I've been covering for 20 years,
39:50
SPEAKER_00: to your point,
39:50
SPEAKER_00: are here.
39:51
SPEAKER_00: I don't think most people are paying attention to this.
39:53
SPEAKER_00: So how is this going to play out, man?
39:55
SPEAKER_00: Because there is going to be a backlash.
39:59
SPEAKER_00: Every time I talk to people,
40:00
SPEAKER_00: they just say,
40:01
SPEAKER_00: well,
40:02
SPEAKER_00: okay,
40:02
SPEAKER_00: then we need ethicists and this is medical.
40:05
SPEAKER_00: People take this stuff very seriously.
40:06
SPEAKER_00: In my experience, tech always kind of like outpaces regulatory issues.
40:13
SPEAKER_00: Like if society wants this, society's going to push it forward fast.
40:18
SPEAKER_00: And so I don't know.
40:20
SPEAKER_00: I mean, yeah, like tell me.
40:22
SPEAKER_00: I have a lot of thoughts.
40:23
SPEAKER_00: Yeah.
40:23
SPEAKER_00: Okay.
40:24
SPEAKER_00: So tell me some of your thoughts and then tell me,
40:26
SPEAKER_00: tell me what like five or 10 years from now looks like.
40:31
First things first is,
40:33
you know,
40:35
all the time in,
40:36
in the longevity movement,
40:39
SPEAKER_02: People will say, I'm gonna optimize my health.
40:41
SPEAKER_02: Nobody bats an eye.
40:42
SPEAKER_02: I'm gonna optimize my life.
40:43
SPEAKER_02: No one bats an eye, right?
40:44
SPEAKER_02: And when people talk about longevity,
40:47
SPEAKER_02: and this is related to embryos,
40:48
SPEAKER_02: it's inextricable,
40:49
SPEAKER_02: and I'll explain why.
40:50
When people talk about longevity,
40:51
they don't just mean I want the absence of disease,
40:54
right?
40:55
SPEAKER_02: We all know that.
40:55
SPEAKER_02: People want peak performance.
40:57
SPEAKER_02: They want to thrive.
40:57
SPEAKER_02: They don't just want not Alzheimer's, right?
40:59
SPEAKER_02: They want to be in the best possible shape.
41:01
SPEAKER_02: In other words- Yeah, like if an adult could be taller-
41:04
SPEAKER_00: Lots of people would choose that instantly.
41:07
SPEAKER_00: Exactly.
41:08
And so there's really this false line in the sand between
41:12
diseases and traits.
41:12
SPEAKER_02: In other words, there actually is no difference.
41:14
SPEAKER_02: And you know, this isn't like a philosophical point.
41:17
SPEAKER_02: This is actually almost like a genetic point.
41:18
SPEAKER_02: And what do I mean by this?
41:19
SPEAKER_02: What I mean is that like,
41:20
SPEAKER_02: If you actually look genetically,
41:21
what you find is that the extreme enough version of any trait
41:24
is a disease.
41:25
So we tend to think of a trait as a disease as like a very
41:27
sharp distance,
41:28
SPEAKER_02: but it's actually not.
41:29
SPEAKER_02: Let me give you some examples.
41:30
SPEAKER_02: Height, right?
41:31
SPEAKER_02: The extreme end of height is Morphin's syndrome.
41:33
SPEAKER_02: It's a disease.
41:34
SPEAKER_02: The other end is dwarfism.
41:35
SPEAKER_02: It's a disease.
41:36
SPEAKER_02: IQ.
41:37
SPEAKER_02: One end is autism, right?
41:38
The other end can be some sort of,
41:40
you know,
41:40
you literally are incapacitated.
41:43
In other words,
41:43
there's kind of a much more inextricability of diseases and
41:46
traits.
41:47
SPEAKER_02: It's this fallacious dichotomy.
41:48
SPEAKER_02: And when you actually do genetic studies on longevity,
41:51
SPEAKER_02: what do you find the genes that are associated with longevity?
41:54
It's something like APOE,
41:56
which is a gene that's associated with Alzheimer's.
41:58
SPEAKER_02: In other words, it makes a lot of sense.
41:59
SPEAKER_02: If you don't have Alzheimer's, you live longer.
42:01
SPEAKER_02: In other words,
42:02
SPEAKER_02: there's been this weird thing where people say,
42:04
SPEAKER_02: oh,
42:05
SPEAKER_02: somehow diseases and traits are very separate.
42:06
SPEAKER_02: but it's a completely arbitrary line in the sand.
42:10
SPEAKER_02: They're actually,
42:10
SPEAKER_02: genetically speaking,
42:11
SPEAKER_02: and also if you just literally think about it,
42:13
SPEAKER_02: it's one just long continuum,
42:14
SPEAKER_02: one spectrum.
42:15
SPEAKER_02: And so we really don't see,
42:17
SPEAKER_02: and then on that point too,
42:19
SPEAKER_02: I don't see there a difference being saying,
42:20
SPEAKER_02: I wanna optimize my embryo in the same way that when the child's born,
42:23
SPEAKER_02: You want to optimize every aspect of them.
42:24
SPEAKER_02: You want them to be as healthy as possible.
42:25
SPEAKER_02: You want them to get the best possible education.
42:27
SPEAKER_02: You want them to be on the best sports team.
42:28
SPEAKER_02: You want them to have the best friends.
42:29
SPEAKER_02: It's like kind of this parental optimization of your child.
42:33
Genetics is just another tool in the toolkit that helps parents
42:37
give their child,
42:38
SPEAKER_02: their son,
42:38
SPEAKER_02: their daughter,
42:39
SPEAKER_02: the best start in life.
42:40
And I think the thing that people actually get chipped up on is
42:44
on the underlying
42:45
SPEAKER_02: assumption that genetics is deterministic.
42:48
SPEAKER_02: It's not, and it never will be.
42:50
SPEAKER_02: When people mention Gattaca,
42:52
SPEAKER_02: They never mentioned the fact that... I saw you get that a lot.
42:54
SPEAKER_02: It's really funny.
42:58
SPEAKER_02: It's like, oh, is it Gattaca or is it Theranos?
43:00
It's like on the one end,
43:01
it's like the most powerful technology we brought to the world.
43:03
SPEAKER_00: It felt like X was Gattaca and Reddit was Theranos.
43:08
Yeah,
43:09
it's like if it's Gattaca,
43:10
it's like the most consequential technology ever.
43:13
SPEAKER_02: It's going to dramatically change the world.
43:15
SPEAKER_02: If it's Theranos, it's a sham.
43:16
SPEAKER_02: So I don't know what people think.
43:17
SPEAKER_02: What's the consensus, right?
43:19
SPEAKER_02: And the reality is that genetics is not nothing.
43:21
SPEAKER_02: It's not everything.
43:22
SPEAKER_02: It's something in between.
43:23
SPEAKER_02: And we know this intuitively, right?
43:25
Like if you ask anyone like,
43:26
oh,
43:27
do you think height,
43:28
how genetic do you think height is?
43:30
SPEAKER_02: Someone would probably say, well, it's probably pretty genetic, right?
43:32
SPEAKER_02: Probably 80% of, you know, or so of height is attributed to genetics.
43:35
SPEAKER_02: If you ask something like, you know,
43:37
SPEAKER_02: Extroversion, for example, it's dramatically less.
43:40
In other words,
43:40
different phenotypes are more and less driven by genetics.
43:43
And in other words,
43:44
genetics is not deterministic and never will be deterministic.
43:47
Even if you built the best possible genetic model in the world
43:49
for IQ,
43:50
there's still error bars.
43:52
SPEAKER_02: That's not a bug.
43:53
SPEAKER_02: That is a feature.
43:54
SPEAKER_02: That is a feature because DNA is not destiny.
43:57
SPEAKER_02: In other words,
43:57
SPEAKER_02: when you put it from that perspective,
43:58
you realize this isn't some evil deterministic tool that's
44:01
going to create some
44:02
SPEAKER_02: crazy unsubstantiated caste system.
44:05
This is actually a tool that is like any other modern medical
44:09
intervention that's
44:10
SPEAKER_02: going to help babies live longer,
44:13
SPEAKER_02: healthier lives.
44:14
SPEAKER_02: And in fact, it is the only diagnostic test.
44:16
SPEAKER_02: It is the only lab test.
44:18
SPEAKER_02: that you can even run at that level because there's no body.
44:20
SPEAKER_02: You can't run a blood test.
44:21
SPEAKER_02: You can't give your baby a vaccine, but you can run their whole genome.
44:24
SPEAKER_02: And imagine this.
44:25
I know right now someone's using nucleus embryo and they're
44:28
going to pick a baby
44:29
SPEAKER_02: that is not an E4 carrier for Alzheimer's.
44:31
And this baby is going to have a dramatically lower risk for
44:33
Alzheimer's than they
44:34
SPEAKER_02: would have had.
44:35
SPEAKER_02: And I know that maybe 40, 50 years from now, that, you know,
44:39
SPEAKER_02: that baby is going to be living their life beautifully.
44:42
SPEAKER_02: It's going to be thriving.
44:44
And they won't even know that the underlying genetic code was
44:47
in a simple software
44:49
SPEAKER_02: in the cloud,
44:49
SPEAKER_02: a simple decision,
44:50
a click of a button basically stopped debilitating pain and
44:54
suffering for the
44:55
SPEAKER_02: entire family.
44:56
SPEAKER_02: That's what nucleus embryo is about.
44:57
It is about the ultimate instantiation of preventative medicine
45:01
and optimization.
45:03
SPEAKER_02: If a parent wants their child not to have
45:06
SPEAKER_02: a cancer, that's their right, that's their choice.
45:08
SPEAKER_02: If a parent wants their kid to be taller, that's also their choice.
45:11
SPEAKER_02: And let me tell you why that already actually exists in society today.
45:14
One of my friends came up to me in a spirited debate and said,
45:17
Kiana,
45:17
I think this is eugenics.
45:18
SPEAKER_02: I said, okay, well, why?
45:20
And we started talking and I said,
45:21
when you're at a party,
45:23
who do you go to?
45:24
SPEAKER_02: They're like, oh, I want someone who's tall.
45:25
SPEAKER_02: I want someone who's this.
45:26
SPEAKER_02: I want someone who's smart.
45:27
SPEAKER_02: So where do you think the DNA comes from?
45:29
SPEAKER_02: It comes from mom and dad.
45:31
You're already selecting for the phenotypes that you want,
45:34
whatever it is you want.
45:36
SPEAKER_02: different things.
45:36
SPEAKER_02: Six five.
45:37
SPEAKER_02: Right.
45:37
SPEAKER_00: Six five.
45:38
SPEAKER_02: Right.
45:38
SPEAKER_02: And what do you think that is?
45:39
SPEAKER_02: You're going to make your, yeah, exactly.
45:40
SPEAKER_02: You're going to make your baby taller.
45:41
SPEAKER_02: And so like,
45:42
SPEAKER_02: I always find it strange because embryo,
45:44
SPEAKER_02: embryo selection is always a relative optimization.
45:46
SPEAKER_02: You're picking from the DNA material of mom and dad,
45:49
which you've actually already selected for by the nature of
45:51
selecting for your
45:52
SPEAKER_02: partner.
45:53
And so,
45:53
you know,
45:53
it's actually,
45:54
I think people get these ideas so confused.
45:56
SPEAKER_00: Um, yeah, go ahead.
45:57
SPEAKER_00: Well, okay.
45:58
I'm going to try to ask a question where I may end up looking
46:01
stupid and possibly a
46:03
SPEAKER_00: But here we go.
46:04
SPEAKER_00: I mean,
46:05
so many of the fascinating people that I've interviewed over
46:07
the last 20 years are
46:09
SPEAKER_00: on the spectrum,
46:09
SPEAKER_00: you know,
46:10
SPEAKER_00: and it's like incredibly high functioning,
46:14
SPEAKER_00: exceptional,
46:14
SPEAKER_00: brilliant people.
46:15
SPEAKER_00: If we do this for 100 years, you know, and people are trying to
46:22
SPEAKER_00: There are costs that come with being on the spectrum, right?
46:26
And so you could imagine a world where society is trying to
46:28
push away from that.
46:30
SPEAKER_00: Well, I actually don't know if I agreed that.
46:32
SPEAKER_00: Let me tell you a little more about this.
46:33
SPEAKER_00: Well, some people I think would choose it.
46:34
SPEAKER_00: But I think writ large, I suspect not.
46:38
SPEAKER_00: Do we end up with less exceptional people in 100 years?
46:42
SPEAKER_00: It's so funny.
46:42
SPEAKER_02: So I wanted to send this on Twitter.
46:44
SPEAKER_02: I was going to send them so many podcasts I've done because...
46:49
SPEAKER_02: Me, I'm in the 99 percentile for my genetic risk for schizophrenia.
46:52
SPEAKER_02: Okay.
46:53
SPEAKER_02: Crazy, right?
46:56
SPEAKER_02: I was that weird.
46:57
SPEAKER_02: They would have, phew, you don't want that.
47:02
It's interesting because if you actually do population studies
47:04
and do correlations
47:04
SPEAKER_02: of polygenic scores,
47:06
high schizophrenia genetic disposition is associated with being
47:08
an artist.
47:09
SPEAKER_02: Makes sense.
47:10
SPEAKER_02: Low ADHD is associated with being like a doctor.
47:12
And what we find is,
47:13
generally speaking,
47:14
founders tend to be very high schizophrenic.
47:16
SPEAKER_02: And for me,
47:17
SPEAKER_02: knowing that piece of information,
47:18
SPEAKER_02: being empowered by that information,
47:20
SPEAKER_02: if I was using a nucleus embryo,
47:21
SPEAKER_02: I would actually pick a more schizophrenic baby.
47:23
SPEAKER_02: And to be clear, I'm not saying the baby's not gonna get schizophrenia.
47:26
SPEAKER_02: It's a disposition, right?
47:27
SPEAKER_02: So I'm saying,
47:28
SPEAKER_02: hey,
47:28
SPEAKER_02: you know,
47:28
SPEAKER_02: instead of having,
47:29
SPEAKER_02: you know,
47:30
SPEAKER_02: whatever,
47:30
SPEAKER_02: a 0.5% population chance,
47:32
SPEAKER_02: maybe it has a three,
47:32
SPEAKER_02: four X higher chance,
47:34
SPEAKER_02: right?
47:34
SPEAKER_02: Relative to the population.
47:35
SPEAKER_02: And because I know,
47:36
SPEAKER_02: and this is a fundamental point,
47:37
SPEAKER_02: Ashley,
47:38
SPEAKER_02: oh my God,
47:38
SPEAKER_02: I cannot express this enough times.
47:39
SPEAKER_02: And I've been saying this for years, which is,
47:41
SPEAKER_02: This is a great example of the inextricability of diseases and traits.
47:45
SPEAKER_02: You cannot select for diseases without selecting also for a trait.
47:48
If I select for higher schizophrenia,
47:49
I'm inextricably selecting for creativity.
47:51
Similarly,
47:52
if I select lower for schizophrenia,
47:54
I'm also selecting for lower creativity.
47:56
SPEAKER_02: These things are a complex web of what's called plyotropy, basically.
47:59
SPEAKER_00: Yeah, but why would you take that risk, darling?
48:02
SPEAKER_02: I know the risk because the risk is still pretty small.
48:04
SPEAKER_02: Like for me,
48:05
SPEAKER_02: even though I'm in 99 percentile for genetic risk for schizophrenia,
48:07
SPEAKER_02: 99 percentile genetic risk,
48:08
SPEAKER_02: it's a relative risk.
48:09
SPEAKER_02: What does that mean function?
48:10
SPEAKER_02: That means I have around a 1.5% chance of schizophrenia.
48:13
SPEAKER_02: That's still really low.
48:13
SPEAKER_00: Yeah, but why would you, I understand what you're saying.
48:16
SPEAKER_00: You would want your child to have the potential for more creativity,
48:19
SPEAKER_00: but like,
48:20
SPEAKER_00: why would you even,
48:21
SPEAKER_00: I mean,
48:21
SPEAKER_02: it just seems like- A 1% chance in risk.
48:23
SPEAKER_00: Like,
48:24
SPEAKER_00: I mean,
48:24
SPEAKER_00: you know,
48:24
SPEAKER_02: you could,
48:25
SPEAKER_02: there's so many things like to me,
48:26
SPEAKER_02: that 1% chance for me,
48:28
SPEAKER_02: it's very little.
48:28
SPEAKER_02: It's a very minimal risk for what you can get.
48:31
SPEAKER_02: Also,
48:32
SPEAKER_02: another thing is that,
48:32
SPEAKER_02: for me,
48:33
SPEAKER_02: I know that we don't have a...
48:35
SPEAKER_02: But here's the thing,
48:36
SPEAKER_02: which is,
48:37
SPEAKER_02: like,
48:37
SPEAKER_02: for me,
48:37
SPEAKER_02: I know there's not a family history of schizophrenia in my family either,
48:40
SPEAKER_02: right?
48:40
SPEAKER_02: So,
48:40
SPEAKER_02: I mean,
48:41
SPEAKER_02: like,
48:41
SPEAKER_02: if you think about the disease model threshold,
48:42
SPEAKER_02: basically,
48:43
SPEAKER_02: one way,
48:43
SPEAKER_02: and this is maybe a little bit too technical,
48:45
SPEAKER_02: but let's just go here.
48:46
SPEAKER_02: Let's fly.
48:47
SPEAKER_02: So if you think about getting a disease, okay?
48:50
SPEAKER_02: Imagine that getting a disease is some really,
48:53
SPEAKER_02: really complex function of genetics and environment,
48:56
SPEAKER_02: which it is,
48:56
SPEAKER_02: right?
48:58
SPEAKER_02: At some point,
48:59
SPEAKER_02: imagine there's whatever,
48:59
SPEAKER_02: 100 random variables in this,
49:01
SPEAKER_02: and each variable is like a zero or one.
49:03
SPEAKER_02: Just imagine it this way.
49:05
SPEAKER_02: And basically,
49:05
SPEAKER_02: if you get enough ones across these 100 variables,
49:07
SPEAKER_02: and let's say you cross 90,
49:09
SPEAKER_02: you get the disease.
49:10
SPEAKER_02: This is how people actually think about disease.
49:12
SPEAKER_02: There's this threshold model,
49:14
SPEAKER_02: which is past a certain point of different environmental genetic factors,
49:17
SPEAKER_02: you will get a condition.
49:19
SPEAKER_02: If there is a genetic history
49:22
SPEAKER_02: like in my family,
49:23
SPEAKER_02: we all have very high genetic risk for schizophrenia,
49:25
SPEAKER_02: but we don't have schizophrenia.
49:27
SPEAKER_02: In other words,
49:28
SPEAKER_02: for whatever reason in my family,
49:30
SPEAKER_02: that kind of complex function never crossed the 90 threshold.
49:33
So I'm not worried given the kind of set of genetic and
49:36
environmental factors,
49:37
right?
49:37
SPEAKER_02: Because obviously given my entire family history plus my genetics,
49:40
SPEAKER_02: that's like kind of my kind of scope.
49:42
I'm not worried that that introduction in this case is going to
49:46
introduce kind of cross that
49:48
SPEAKER_02: And the thing is,
49:50
SPEAKER_02: you know,
49:50
SPEAKER_02: someone might be listening to this and be like,
49:51
SPEAKER_02: oh,
49:51
SPEAKER_02: this is such a technical point.
49:52
SPEAKER_02: Like,
49:52
Kian understands so much about this stuff that like he can
49:54
almost like optimize,
49:56
SPEAKER_02: but that's what we're trying to do for everyone,
49:57
SPEAKER_02: right?
49:57
SPEAKER_02: People should understand these trade-offs.
49:59
Like there are babies running around with 99 percentile
50:01
schizophrenia,
50:02
right?
50:02
SPEAKER_02: 99 of them don't have schizophrenia, right?
50:04
SPEAKER_02: And 99 out of 100, right?
50:07
I think this is part of the difficulty of actually eventually
50:11
creating this genetic
50:12
SPEAKER_02: optimization software,
50:13
which is we have to understand the inextricability of diseases
50:17
and traits and what
50:18
SPEAKER_02: you're optimizing for and not,
50:20
and realize that there are very high-functioning exceptional
50:23
people with extreme
50:23
SPEAKER_02: genetic dispositions.
50:25
One more point here,
50:25
which is to be very clear,
50:26
I'm not selecting for a hereditary marker.
50:29
SPEAKER_02: I'm not selecting for a BRCA.
50:31
SPEAKER_02: I'm not saying I'm going to give my kid brackets so they're more.
50:33
SPEAKER_02: I think, no, no, no, that's bad.
50:34
SPEAKER_02: That's like a very high penetrant decision.
50:36
SPEAKER_02: That would take your kid's chance from,
50:37
SPEAKER_02: let's say like 1% to like,
50:38
SPEAKER_02: I don't know,
50:39
SPEAKER_02: 80% or something.
50:40
SPEAKER_02: That's obviously not, I mean, that's crazy.
50:42
I think that'd be crazy to do that,
50:43
to just like that,
50:44
maybe even unethical,
50:45
you could argue.
50:46
SPEAKER_02: This is a whole polygenic prediction, right?
50:47
SPEAKER_02: So it's inherently probabilistic.
50:49
And knowing all like the prior weights of my entire family,
50:51
I think it makes sense.
50:52
SPEAKER_02: And, you know, me, I have a high genetic versus schizophrenia.
50:55
SPEAKER_02: You know, my parents obviously, you know, where does my DNA come from?
50:57
SPEAKER_02: It's a mom and dad.
50:58
You can induce that my mom and dad have a high genetic versus
51:00
schizophrenia.
51:00
SPEAKER_02: What is my point?
51:01
My point is that genetics is actually a lot more interesting
51:05
than people think in
51:06
SPEAKER_02: that the diseases and traits are a lot more restrictive.
51:08
SPEAKER_02: which is why we shouldn't put an arbitrary line in the sand.
51:11
Instead,
51:12
we should educate parents about the different trade-offs and
51:15
choices.
51:16
And then this gets to the fundamental point,
51:17
which is different parents want different things.
51:19
SPEAKER_02: Notice the way you reacted when I said,
51:21
I'm going to pick my kid to be more schizophrenic because
51:23
naturally I'm more
51:24
SPEAKER_02: schizophrenic.
51:24
SPEAKER_02: So what the hell is wrong with you?
51:26
SPEAKER_02: In other words, you might not do that.
51:28
SPEAKER_02: which is great.
51:29
SPEAKER_02: And you see that already when people pick embryo,
51:31
SPEAKER_02: excuse me,
51:31
SPEAKER_02: when people pick sperm and egg donors,
51:33
SPEAKER_02: people actually will pick for different things.
51:35
SPEAKER_02: Some will value IQ more,
51:36
SPEAKER_02: some will value EQ more,
51:37
SPEAKER_02: some will value some other axes more,
51:39
SPEAKER_02: maybe height or physical appearance.
51:41
SPEAKER_02: And so all these things together,
51:42
SPEAKER_02: you actually have a world where everyone's informed,
51:45
SPEAKER_02: everyone's using our genetic optimization software,
51:47
SPEAKER_02: and people are picking based off what matters most to them,
51:49
SPEAKER_02: which is different.
51:50
And you actually never end up in this world where everyone
51:52
picks for the same things.
51:53
SPEAKER_02: One final point here,
51:54
which is there's a great example that one of our advisors gives
51:56
in the scientific
51:57
SPEAKER_02: advisory board.
51:57
He says he went to a deaf couple one time and he said,
51:59
what kind of kid do you want to have?
52:00
SPEAKER_02: And they said, I want to have a deaf child.
52:04
SPEAKER_02: Is it for you or me to say, oh, no, no, that's not right?
52:06
SPEAKER_02: It's up to the parents.
52:07
SPEAKER_02: People have different value frameworks.
52:08
SPEAKER_02: They make different decisions.
52:10
You're going to see that playing out globally,
52:13
basically,
52:13
when people use the software.
52:14
SPEAKER_00: So what do you think this looks like in five or 10 years?
52:18
SPEAKER_00: Everybody's doing this?
52:19
SPEAKER_02: I think a couple things.
52:20
SPEAKER_02: One is I think IVF becomes much cheaper and much more ubiquitous.
52:22
SPEAKER_02: Right now, it's still invasive.
52:24
SPEAKER_02: It's still kind of really expensive.
52:25
SPEAKER_02: It's still sort of painful.
52:26
SPEAKER_02: I think stem cells, you make eggs, you make sperm.
52:29
SPEAKER_00: And to get the most out of the...
52:32
SPEAKER_00: Whether it's you guys,
52:34
SPEAKER_00: organs,
52:36
in order for people to be able to take advantage of these types
52:39
of technologies the
52:40
SPEAKER_00: most,
52:41
SPEAKER_00: I mean,
52:41
SPEAKER_00: you really,
52:42
SPEAKER_00: you have to do IVF if you're focused on the child part.
52:46
SPEAKER_02: Yes.
52:47
SPEAKER_02: So, yes.
52:48
SPEAKER_02: If you want to do nucleus embryo, you have to do IVF today.
52:51
SPEAKER_02: The reason why I just keep saying today is like...
52:54
I really do think in the future IVF won't even be a thing
52:58
that's different.
52:58
SPEAKER_02: It's just going to be how people have children.
53:00
SPEAKER_02: I really believe that.
53:01
SPEAKER_02: For the most part.
53:01
Because what's going to happen is it's going to become so much
53:03
cheaper,
53:03
so much easier.
53:04
SPEAKER_02: You're going to make stem cells, make it into gametes, whatever.
53:06
SPEAKER_02: And then all of a sudden you're going to be able to effectively,
53:09
SPEAKER_02: anyone,
53:09
SPEAKER_02: literally anywhere,
53:10
SPEAKER_02: maybe even you can take your own cells and mate the cells.
53:13
SPEAKER_02: Who knows?
53:15
Having sex to have kids,
53:16
I do think it's going to eventually be an archaic thing.
53:18
SPEAKER_02: I do believe that.
53:20
SPEAKER_02: And I actually think genetic technology is,
53:23
SPEAKER_02: along there with AI,
53:24
going to be the single most consequential technological
53:27
revolution ever because it
53:28
SPEAKER_02: literally is the language of life.
53:30
SPEAKER_02: And on that point,
53:31
SPEAKER_02: you're going to bring together sequencing DNA,
53:32
SPEAKER_02: analyzing DNA,
53:34
SPEAKER_02: and also then editing DNA.
53:35
SPEAKER_02: And then that stack forms.
53:36
SPEAKER_02: And then,
53:36
SPEAKER_02: of course,
53:37
all these things are related to each other because if you don't
53:40
understand DNA
53:41
SPEAKER_02: well,
53:41
SPEAKER_02: you can't possibly edit it.
53:43
SPEAKER_02: This is something that people always miss.
53:45
SPEAKER_02: It's like, oh, we're gonna engineer DNA, CRISPR, and all these things.
53:48
SPEAKER_02: It's like, yeah, but what are you gonna engineer?
53:50
SPEAKER_02: In order to engineer, you have to understand DNA.
53:52
We don't even have a whole genome database today that's
53:56
millions of people large.
53:57
The largest whole genome database is half a million people in
53:59
the UK biobank.
53:59
SPEAKER_02: Half a million people?
54:00
SPEAKER_02: When I think about that,
54:01
SPEAKER_02: there are billions,
54:02
SPEAKER_02: billions,
54:03
SPEAKER_02: billions of genomes to be sequenced,
54:05
SPEAKER_02: billions of genomes to be phenotypically mapped.
54:07
And then think about all that data to then far greater
54:09
understand the actual
54:10
SPEAKER_02: underlying genetic architecture.
54:12
All that information is going to be fed into then actually
54:14
understanding more and
54:15
SPEAKER_02: more what are actually the cause of markers,
54:17
which then all that information is going to be fed to and what
54:19
actually can be
54:20
SPEAKER_02: edited and engineered.
54:21
SPEAKER_02: And I actually think of it as almost the great equalizer.
54:24
Because now suddenly anyone anywhere can actually use genetic
54:27
technology to,
54:28
SPEAKER_02: and it's so cheap,
54:29
SPEAKER_02: it's so beautiful,
54:30
SPEAKER_02: it's like your iPhone,
54:31
SPEAKER_02: right?
54:31
SPEAKER_02: It's like,
54:32
SPEAKER_02: you know,
54:32
SPEAKER_02: the college,
54:33
SPEAKER_02: I put this on Twitter,
54:34
SPEAKER_02: the college student has the same iPhone as the billionaire,
54:36
SPEAKER_02: right?
54:36
SPEAKER_02: It's no different, it's gonna be the same thing.
54:37
Genetic technology can make sure anyone anywhere can basically
54:40
have the child they want.
54:41
SPEAKER_02: I think that's a beautiful thing.
54:42
SPEAKER_00: So something would have to change in some ways.
54:45
SPEAKER_00: There was the scientist in China who what?
54:48
SPEAKER_00: Dr. He, I think.
54:49
SPEAKER_00: Yeah, yeah.
54:51
you know he got thrown in jail for three years after editing
54:54
some babies to block
54:56
hiv yeah and you know so so it's like seems pretty pretty
55:02
pretty pro um health you
55:04
know i mean i mean trying to make sure they didn't get hiv
55:07
later on got thrown in
55:09
jail um chinese government they've like let him reopen a lab
55:13
but he's kind of like
55:13
SPEAKER_00: being monitored all the time he just
55:16
got married to Kathy T.
55:20
And now the Chinese government won't let her come back into
55:25
China.
55:25
SPEAKER_00: So, you know, they're upset with him.
55:28
The scientific community was outraged because he raced forward
55:31
doing this stuff
55:32
SPEAKER_00: before people felt like they'd solved all the ethics.
55:35
SPEAKER_00: And so,
55:35
SPEAKER_00: like,
55:36
SPEAKER_00: if we're thinking of the Overton window on some of this,
55:39
SPEAKER_00: I mean,
55:41
SPEAKER_00: you know,
55:41
SPEAKER_00: huge backlash against what he was doing.
55:43
SPEAKER_00: And then now...
55:45
companies like yours are out here you know offering these
55:48
services more and more
55:49
where we're kind of heading this direction yeah i'm trying to
55:51
i'm trying to figure
55:52
out where i think a couple things here one is that like look at
55:54
the crisper you
55:55
know how the baby was recently uh for the first time ever this
55:58
baby that was
55:58
crisper that was in the us yeah that was in the united states
56:00
yeah they cured they
56:01
SPEAKER_02: cured a baby um
56:03
SPEAKER_02: Some really rare hereditary condition.
56:05
SPEAKER_02: And so I want to say a couple of points on this.
56:07
SPEAKER_02: One is extraordinary scientific achievement.
56:09
SPEAKER_02: I mean, amazing.
56:10
SPEAKER_02: So why was that okay?
56:11
SPEAKER_02: And what he did was not okay?
56:13
SPEAKER_02: I think you have to ask society that.
56:14
SPEAKER_02: But I think one thing on this point is that,
56:17
SPEAKER_02: you know,
56:18
SPEAKER_02: we need to use the entire genetic stack here,
56:21
SPEAKER_02: right?
56:22
ultimately genetically engineering a baby to get rid of a heart
56:25
disease the fact
56:26
that we can do that today is exceptional but also there's
56:28
preconception testing
56:29
right there's a reason why mom and dad can get together swab
56:31
their cheeks to
56:32
describe so that you god forbid have a baby with a severe
56:36
debilitating disease and
56:37
then need to use some the most frontier technology in the world
56:40
we have to try to
56:40
cure that baby right um if mom and dad had swabbed their cheeks
56:43
you could you know
56:44
use ivf and then amortize it so on this point i think it's
56:46
really really important
56:47
SPEAKER_02: to say which is gene editing for gene editing purposes
56:50
SPEAKER_02: When we have technology that's easier,
56:51
SPEAKER_02: cheaper,
56:52
SPEAKER_02: and basically already mass ubiquitous to stop a baby from having HIV,
56:55
SPEAKER_02: to stop a baby from having a rare heretic disease,
56:56
SPEAKER_02: that exists today.
56:57
SPEAKER_02: That future is here today, right?
56:59
SPEAKER_02: You could do preconception testing at scale,
57:02
SPEAKER_02: and you could,
57:02
SPEAKER_02: in a single generation,
57:04
SPEAKER_02: rid the entire world of monogenic disease.
57:07
SPEAKER_02: That's today, with no gene identity required.
57:09
SPEAKER_02: Which, like, people should know are, like, the worst conditions.
57:11
SPEAKER_00: I mean, it's horrible.
57:13
SPEAKER_00: It's like kids dying at really young age.
57:15
SPEAKER_02: Horrible.
57:15
SPEAKER_02: Horrible.
57:16
SPEAKER_02: Truly horrible.
57:16
SPEAKER_02: And this is what's really interesting now,
57:18
SPEAKER_02: which is like,
57:18
SPEAKER_02: you shouldn't just geneitize it for the person with geneitizing.
57:20
The geneitizing should come when it's actually like you can't
57:23
already use the tools
57:24
SPEAKER_02: we have to basically stave off disease,
57:26
SPEAKER_02: if that makes sense.
57:26
SPEAKER_02: So like HIV and these hereditary conditions,
57:28
SPEAKER_02: like using CRISPR,
57:29
SPEAKER_02: I'm almost like,
57:31
SPEAKER_02: it's a great,
57:32
SPEAKER_02: it's amazing.
57:33
SPEAKER_02: And especially in the baby's case in the United States, that's amazing.
57:35
I mean,
57:35
that's like a feat of science and thank God for that baby,
57:37
thank God for that family.
57:39
but also people should be aware that there's upstream measures
57:42
they could take to
57:43
SPEAKER_02: make sure that we don't have to,
57:44
SPEAKER_02: you know,
57:45
SPEAKER_02: solve the problem,
57:46
SPEAKER_02: but you can prevent it in the first place.
57:47
SPEAKER_00: Why do you think it was okay?
57:49
SPEAKER_00: Was it because it was the U.S.
57:51
SPEAKER_00: and not China?
57:52
SPEAKER_02: I think because it was a really rare predatory disease.
57:54
SPEAKER_00: Okay.
57:55
SPEAKER_00: It's less like cosmetic.
57:56
Right,
57:56
because he was kind of just preparing them for maybe in life
58:01
they encountered HIV.
58:02
SPEAKER_02: The thing, too, though, to remember is that, like,
58:05
SPEAKER_02: For a lot of the phenotypes, they're polygenic.
58:08
So a lot of the times people think it's like,
58:09
okay,
58:10
I'm going to switch this one thing.
58:11
SPEAKER_02: Again,
58:11
SPEAKER_02: it's like if you're going to gene edit BRCA,
58:13
SPEAKER_02: which increases your risk of breast cancer,
58:15
SPEAKER_02: why would you even do that?
58:17
SPEAKER_02: You can just do IVF and screen it out.
58:18
SPEAKER_02: There's no reason to engineer that.
58:20
SPEAKER_02: It doesn't even make sense.
58:24
What's going to be the future in my mind of gene DNA is going
58:26
to be multiplex
58:27
SPEAKER_02: engineering,
58:27
SPEAKER_02: where you can actually engineer many,
58:29
SPEAKER_02: many sites in the genome.
58:31
SPEAKER_02: But the thing with that is to do that,
58:32
you actually need to identify the causal markers in the
58:35
different parts of the
58:36
SPEAKER_02: genome.
58:37
SPEAKER_02: And we often know that a region of DNA is associated,
58:39
SPEAKER_02: but we don't know that it's actually causal.
58:42
SPEAKER_02: And to do that, there needs to be even more research.
58:45
And so maybe my point is that it's going to be a company like
58:48
Nucleus that actually
58:49
SPEAKER_02: puts these pieces together.
58:50
SPEAKER_02: Because there is no,
58:51
SPEAKER_02: you know,
58:51
SPEAKER_02: it's interesting,
58:51
SPEAKER_02: Brian Armstrong put a tweet up recently about a gene editing startup.
58:55
SPEAKER_00: And how awesome the Core Memory podcast is.
58:59
SPEAKER_02: Yeah, exactly.
58:59
SPEAKER_00: Good for Brian.
59:00
SPEAKER_02: That's great.
59:00
SPEAKER_02: Amazing.
59:01
SPEAKER_02: Thank you.
59:01
SPEAKER_02: Thank you, Brian.
59:04
SPEAKER_00: You did it.
59:05
SPEAKER_00: I did it.
59:05
SPEAKER_02: I remembered the button.
59:07
SPEAKER_02: Okay, how do I stop it?
59:08
SPEAKER_00: It goes on for a while.
59:09
SPEAKER_00: Oh, it goes on.
59:10
SPEAKER_02: Okay.
59:13
SPEAKER_02: And so we talked about gene editing, and I think that's great.
59:17
I think it's great that these babies now have these genetic
59:21
conditions that didn't
59:22
SPEAKER_02: use these preventive genetic measures.
59:24
SPEAKER_02: CRISPR should become cheaper and better and faster.
59:27
SPEAKER_02: But I really think to do the kind of engineering that people imagine,
59:29
you're going to need to combine a dramatic increase in genetic
59:32
understanding.
59:33
SPEAKER_02: This is a decades-long play.
59:35
Dramatic increase in genetic understanding through the rise of
59:38
a whole genome
59:38
SPEAKER_02: testing analysis company.
59:40
And then applying those learnings throughout the entire stack
59:43
from adults all the
59:45
SPEAKER_02: way down to embryos.
59:46
SPEAKER_02: And actually, I'm looking around and I see nucleus.
59:50
SPEAKER_02: It's the only company that's actually saying,
59:52
SPEAKER_02: actually,
59:52
SPEAKER_02: forget about you're doing this,
59:53
SPEAKER_02: you're doing this.
59:54
SPEAKER_02: We're going to do the entire stack.
59:56
SPEAKER_02: And you know my background is in gene editing originally,
59:58
SPEAKER_02: before I went to the computer side of things.
1:00:00
SPEAKER_02: I don't see a world where,
1:00:02
SPEAKER_02: as the decades come,
1:00:03
SPEAKER_02: you're going to combine massive whole genome data sets.
1:00:06
SPEAKER_02: You're going to combine artificial intelligence.
1:00:07
SPEAKER_02: You're going to combine a profoundly new knowledge of the human genome.
1:00:11
SPEAKER_02: IVF is going to become much, much, much cheaper.
1:00:13
And suddenly,
1:00:13
you can do mass multiplex engineering at scale across anyone.
1:00:17
SPEAKER_02: And I think that's actually a beautiful future because anyone,
1:00:20
SPEAKER_02: no matter your background,
1:00:21
SPEAKER_02: no matter how much money you have,
1:00:23
SPEAKER_02: can access basically the best possible genetics.
1:00:26
SPEAKER_02: Now everyone can give their child the best start in life.
1:00:28
SPEAKER_02: And here's the kicker.
1:00:28
That society will never be deterministic because DNA is
1:00:31
inherently not deterministic,
1:00:32
right?
1:00:32
SPEAKER_02: So if you can have people without disease,
1:00:34
if someone wants their child to be taller or if they want their
1:00:37
child to have brown
1:00:38
SPEAKER_02: eyes or if their child wants to maybe be more schizophrenic,
1:00:41
SPEAKER_02: whatever it is,
1:00:42
SPEAKER_02: now anyone
1:00:43
SPEAKER_02: no matter actually the combination of mom and dad,
1:00:45
SPEAKER_02: if you think about it,
1:00:46
SPEAKER_02: you're not limited by mom and dad's genes.
1:00:47
SPEAKER_02: It's literally anyone can access the best genetics.
1:00:50
SPEAKER_02: And so I think that is a great equalizer for society.
1:00:53
SPEAKER_02: And I think that's an awesome future to be built toward.
1:00:56
SPEAKER_02: We're far from it.
1:00:57
SPEAKER_02: We're far from it.
1:00:58
SPEAKER_02: But I think that's what's coming in the future.
1:01:00
So on Reddit,
1:01:02
I know we're kind of joking about it,
1:01:04
but I mean,
1:01:05
you did a Q&A and you did get
1:01:07
SPEAKER_00: Oh, wow.
1:01:08
SPEAKER_00: That Q&A was intense, let me tell you.
1:01:10
SPEAKER_00: I mean, you got a bunch of questions.
1:01:11
SPEAKER_02: Can I just say something about this Q&A?
1:01:12
SPEAKER_02: Which is,
1:01:13
I want to apologize to the Reddit community because I put this
1:01:15
Q&A out and I was
1:01:16
SPEAKER_02: like,
1:01:16
SPEAKER_02: oh,
1:01:17
SPEAKER_02: maybe one person asked me a question.
1:01:18
SPEAKER_02: Because I think it was about 23andMe, I collapsed at the time.
1:01:20
SPEAKER_02: You got a lot on that, yes.
1:01:22
SPEAKER_02: Let's just say we were,
1:01:23
SPEAKER_02: I was caught up in conversations around 23andMe and that whole thing,
1:01:27
SPEAKER_02: because it's a whole thing.
1:01:28
SPEAKER_02: And so I'm like distracted the entire day and I opened up Reddit.
1:01:30
SPEAKER_02: I'm like, oh my God.
1:01:31
SPEAKER_02: I was like...
1:01:37
SPEAKER_00: There were a handful that basically I would summarize them as,
1:01:42
SPEAKER_00: you're a 25-year-old,
1:01:44
SPEAKER_00: you're a Teal Fellow,
1:01:45
SPEAKER_00: you dropped out,
1:01:46
SPEAKER_00: how are we at all supposed to trust you?
1:01:50
SPEAKER_00: enthusiastic about all this stuff.
1:01:53
SPEAKER_00: You're like,
1:01:54
SPEAKER_00: you know,
1:01:54
SPEAKER_00: if you put those dots together,
1:01:56
it's like you can have a stereotypical sort of view of like
1:01:59
vaguely where you're
1:02:00
SPEAKER_00: coming from.
1:02:01
SPEAKER_00: I know you listed off like, look, these are our scientific advisors.
1:02:05
SPEAKER_00: These are, you know, they're people at the top of their field.
1:02:08
SPEAKER_00: So I'm putting that part out there,
1:02:10
SPEAKER_00: but you know,
1:02:10
SPEAKER_00: there is,
1:02:11
SPEAKER_00: there is,
1:02:12
there is a world where you go off and get a medical degree or a
1:02:15
PhD and come and do
1:02:18
SPEAKER_00: this.
1:02:18
SPEAKER_00: I mean,
1:02:18
SPEAKER_00: you have,
1:02:19
SPEAKER_00: there is a,
1:02:20
there's an argument to be made that you've kind of stacked the
1:02:23
deck against you
1:02:25
SPEAKER_00: just because this is biotech.
1:02:26
SPEAKER_00: It is medical.
1:02:27
SPEAKER_00: People like to see these kinds of credentials, um, in this type of thing.
1:02:33
SPEAKER_00: I think, um,
1:02:35
ultimately the the measure of nucleus is what we put out into
1:02:40
the world where
1:02:41
SPEAKER_02: people can use touch feel see learn and i think that those comments are
1:02:48
SPEAKER_02: understandable understand why people are saying it
1:02:50
SPEAKER_02: I think the most beautiful thing about the company is that we are live in
1:02:54
SPEAKER_02: production,
1:02:55
SPEAKER_02: and that when people do Nucleus,
1:02:56
SPEAKER_02: when they actually see the product,
1:02:57
SPEAKER_02: when it goes from this kind of abstract teal fellow mess to,
1:03:01
SPEAKER_02: wait,
1:03:01
SPEAKER_02: let me actually use the product,
1:03:03
SPEAKER_02: and then they see a video of a patient,
1:03:04
SPEAKER_02: for example,
1:03:05
SPEAKER_02: recently,
1:03:06
SPEAKER_02: he was suffering.
1:03:08
SPEAKER_02: He had brain fog.
1:03:09
SPEAKER_02: No doctor could figure out what was wrong with him.
1:03:11
SPEAKER_02: His name's Ethan.
1:03:13
SPEAKER_02: And he did nucleus,
1:03:14
SPEAKER_02: and we found out that he had a condition called heretary hemochromatosis,
1:03:17
SPEAKER_02: which can lead to excess iron levels in the blood.
1:03:21
SPEAKER_02: And then from there,
1:03:21
SPEAKER_02: he actually started doing monthly blood withdraws,
1:03:24
SPEAKER_02: which effectively saved his life.
1:03:27
SPEAKER_02: These are very different narratives.
1:03:30
SPEAKER_02: The thing that I always find funny about the Theranos comments is,
1:03:32
SPEAKER_02: we're live in production,
1:03:33
SPEAKER_02: maybe.
1:03:34
SPEAKER_02: We're live in production, maybe.
1:03:36
SPEAKER_02: I never did a Theranos test.
1:03:39
SPEAKER_02: You want to do a nucleus test?
1:03:40
SPEAKER_02: Go order it right now.
1:03:41
SPEAKER_02: You can go order it.
1:03:42
SPEAKER_02: People have used it.
1:03:43
SPEAKER_02: People see it.
1:03:43
SPEAKER_02: And it's funny,
1:03:44
SPEAKER_02: because a journalist said to me yesterday,
1:03:45
SPEAKER_02: they said,
1:03:45
SPEAKER_02: you know,
1:03:45
SPEAKER_02: sometimes I look at your Twitter.
1:03:47
SPEAKER_02: And I'm like, oh, okay, this guy's very energetic.
1:03:50
SPEAKER_02: He's right out there.
1:03:51
SPEAKER_02: He's super young.
1:03:53
And then I used the Nucleus product,
1:03:54
and I was like,
1:03:54
oh,
1:03:54
my God,
1:03:55
this product is rigorous.
1:03:56
SPEAKER_02: It's beautiful.
1:03:57
SPEAKER_02: Everything's well-cited.
1:03:59
SPEAKER_02: You're talking about Nucleus is a clinical laboratory.
1:04:01
SPEAKER_02: We're clear certified.
1:04:02
SPEAKER_02: We're top accredited.
1:04:03
SPEAKER_02: We're physician-ordered.
1:04:05
SPEAKER_02: We're, at this point, decades' worth of scientific research.
1:04:08
SPEAKER_02: I mentioned Lasse Fokers, our chief scientist.
1:04:10
He's been doing this for such a long time,
1:04:13
almost as long as I've been alive.
1:04:15
SPEAKER_02: And so when you start actually looking at what we put into the world,
1:04:18
SPEAKER_02: that's how I want us to be assessed.
1:04:21
SPEAKER_02: I want us to be assessed by how much value are we giving patients?
1:04:24
SPEAKER_02: What are we telling patients?
1:04:26
SPEAKER_02: And then what you find is when you actually look at that,
1:04:28
SPEAKER_02: you find that we're helping parents,
1:04:29
SPEAKER_02: we're helping couples,
1:04:31
SPEAKER_02: we're helping individuals live longer,
1:04:32
SPEAKER_02: healthier lives and have healthier children.
1:04:34
SPEAKER_02: And so to me then,
1:04:35
SPEAKER_02: what people say and don't say doesn't matter,
1:04:38
SPEAKER_02: because I know we're shipping our customers value,
1:04:40
SPEAKER_02: I know customers are using it,
1:04:41
SPEAKER_02: they're getting value,
1:04:42
SPEAKER_02: and now I know in the embryonic context,
1:04:45
SPEAKER_02: people have already used Nucleus Embryo,
1:04:47
SPEAKER_02: and they've said to me,
1:04:49
SPEAKER_02: this is the most spectacular product I've ever used.
1:04:51
SPEAKER_02: That is the measure.
1:04:52
And it's funny,
1:04:53
I got a funny LinkedIn DM yesterday from someone that said,
1:04:57
SPEAKER_02: I think he said,
1:04:59
SPEAKER_02: my wife is doing IVF,
1:05:01
SPEAKER_02: and she saw the launch of a nucleus embryo,
1:05:03
SPEAKER_02: she started crying.
1:05:04
SPEAKER_02: She said, the world needs this.
1:05:07
SPEAKER_02: That's what this is about.
1:05:09
SPEAKER_00: Okay, one more devil's advocate question.
1:05:12
SPEAKER_00: Sure, go ahead.
1:05:13
SPEAKER_00: And I'll change tack.
1:05:14
SPEAKER_00: This is just from a friend who actually knows what they're talking about.
1:05:19
SPEAKER_00: Which friend?
1:05:20
SPEAKER_02: Is this a friend who builds a competitive company?
1:05:23
SPEAKER_02: I don't know.
1:05:24
SPEAKER_02: I cannot reveal any sources.
1:05:26
SPEAKER_00: Sometimes people's friends in tack are like, let me, you know.
1:05:31
SPEAKER_00: They're saying, doesn't actually detect thousands of serious diseases.
1:05:37
SPEAKER_00: They're kind of like knocking on the whole genome part,
1:05:40
SPEAKER_00: receiving 1% of data,
1:05:42
SPEAKER_00: running through software that's not validated.
1:05:46
SPEAKER_02: I mean,
1:05:47
SPEAKER_02: first I would say,
1:05:48
SPEAKER_02: you know,
1:05:48
SPEAKER_02: to the audience,
1:05:49
SPEAKER_02: which is like,
1:05:50
SPEAKER_02: you know,
1:05:50
SPEAKER_02: whenever someone says my friend in Silicon Valley,
1:05:52
almost certainly this person has some vested interest in saying
1:05:55
something that is
1:05:56
SPEAKER_02: negative or positive.
1:05:57
SPEAKER_02: Just be always aware of that, always know who's saying this.
1:05:59
SPEAKER_02: I mean, it's just not true.
1:06:00
SPEAKER_02: Yeah.
1:06:02
I think there's a reason why Genomic Prediction picked Nucleus
1:06:05
to do our analysis
1:06:06
SPEAKER_02: because,
1:06:06
SPEAKER_02: again,
1:06:07
SPEAKER_02: we are a clinical-grade whole-genome laboratory.
1:06:09
SPEAKER_02: We are,
1:06:10
SPEAKER_02: at this point,
1:06:10
probably one of the most well-backed genetic testing companies
1:06:12
in the world.
1:06:13
SPEAKER_02: We have an army of scientists and engineers,
1:06:16
SPEAKER_02: and we,
1:06:17
SPEAKER_02: again,
1:06:17
SPEAKER_02: are live in production,
1:06:18
SPEAKER_02: so the science
1:06:19
SPEAKER_02: I mean,
1:06:20
SPEAKER_02: I would tell your friend,
1:06:20
SPEAKER_02: go to Nucleus and see what you learn,
1:06:22
which is we can screen for over 900 conditions by combining the
1:06:26
power of our whole
1:06:27
SPEAKER_02: genome test in adults with genomic predictions technology.
1:06:31
SPEAKER_02: Suddenly,
1:06:32
SPEAKER_02: you can screen for not only hereditary conditions,
1:06:33
SPEAKER_02: but also you can do polygenic testing as well.
1:06:35
And as I said to you,
1:06:36
I think we're complementary to the companies that you mentioned
1:06:39
as well.
1:06:39
SPEAKER_02: If someone does one of those companies,
1:06:40
SPEAKER_02: they can take their raw whole genome file and they can upload to Nucleus.
1:06:44
SPEAKER_02: I mean, that's what we do.
1:06:45
SPEAKER_02: That's what we do.
1:06:47
SPEAKER_02: In a way,
1:06:47
SPEAKER_02: actually,
1:06:47
I would argue we're more suited than a lot of the IVF testing
1:06:50
companies probably do
1:06:51
SPEAKER_02: because all our models touch grass.
1:06:53
SPEAKER_02: We have adults that do our models, right?
1:06:55
SPEAKER_02: Where do you think the embryo models come from?
1:06:56
SPEAKER_02: They come from adults, right?
1:06:57
SPEAKER_02: And so in that way,
1:06:58
SPEAKER_02: we're actually much better,
1:06:59
SPEAKER_02: I would argue,
1:07:00
SPEAKER_02: at not just testing and validating our models,
1:07:02
SPEAKER_02: but moreover,
1:07:04
SPEAKER_02: we're better at actually
1:07:07
SPEAKER_02: during the IVF process to keep cost as cheap as possible.
1:07:10
SPEAKER_02: Because there's going to be certain companies that say,
1:07:13
SPEAKER_02: oh,
1:07:13
SPEAKER_02: you need to do this test on your embryos.
1:07:14
But what they don't tell you is that by actually combining our
1:07:17
adult testing
1:07:18
SPEAKER_02: technology with the different technology at the embryonic level,
1:07:21
SPEAKER_02: we can make things much cheaper and more accessible.
1:07:23
And moreover,
1:07:24
on that point,
1:07:24
again,
1:07:25
I want to be very clear,
1:07:26
we're a software layer.
1:07:27
We don't see ourselves as competitive with these other IVF
1:07:31
testing companies.
1:07:32
SPEAKER_02: We see them as complementary.
1:07:33
SPEAKER_02: You can go do those companies.
1:07:35
In fact,
1:07:35
you need to do one of those companies before you come to
1:07:37
Nucleus.
1:07:37
SPEAKER_02: And then you can bring over the DNA data,
1:07:40
and then you can start optimizing your embryos based on
1:07:42
whatever you want.
1:07:44
SPEAKER_02: And so I think a rising tide will bring up all ships.
1:07:47
SPEAKER_02: And I think it's really interesting.
1:07:49
SPEAKER_02: Nucleus is in a funny position because depending on who you ask,
1:07:53
SPEAKER_02: they will say our competitors are different people.
1:07:55
right some people will say 23me another person will say some
1:07:57
other consumer health
1:07:58
startup then someone else will say some ivf testing company and
1:08:01
then someone else
1:08:01
will say some pgx company and i always find it funny what's pgx
1:08:04
a pharmacogenomics
1:08:05
like how your DNA affects metabolism drugs right because we
1:08:07
also also some will
1:08:09
even say other clinical genetics companies like myriad for
1:08:11
example or notera right
1:08:12
because they can't pin us down and the reason why they can't
1:08:16
pin us down is because
1:08:16
we are violating all the underlying assumptions of what does it
1:08:19
mean to be a
1:08:20
SPEAKER_02: genetics company
1:08:21
SPEAKER_02: They want to pigeonhole us in 23andMe.
1:08:23
SPEAKER_02: They want to pigeonhole us in the IVF testing marketing.
1:08:25
SPEAKER_02: They want to pigeonhole us in clinical testing.
1:08:27
SPEAKER_02: We do it all.
1:08:28
SPEAKER_02: Why do we do it all?
1:08:28
SPEAKER_02: Because, again, we're this application layer.
1:08:30
SPEAKER_02: So we can take in the data for any of these people.
1:08:33
SPEAKER_02: We can focus all our effort,
1:08:34
SPEAKER_02: all our capital,
1:08:35
SPEAKER_02: all our scientific expertise on building the best possible software.
1:08:38
SPEAKER_02: And part of building the best possible software,
1:08:40
SPEAKER_02: this is an important point,
1:08:41
SPEAKER_02: isn't just the rigorous science.
1:08:42
SPEAKER_02: That's a must, the most rigorous science.
1:08:44
SPEAKER_02: But also, it's making software that's actually usable for people.
1:08:47
One of the things about if you notice that there was a thread
1:08:49
on Twitter that I
1:08:50
SPEAKER_02: think got millions and millions of impressions,
1:08:52
SPEAKER_02: it was screenshots of our interface.
1:08:54
And I was thinking,
1:08:54
I was like,
1:08:55
why did that resonate so much with this Twitter user?
1:08:58
SPEAKER_02: What, people were like into it or?
1:09:00
SPEAKER_02: They loved it.
1:09:01
SPEAKER_02: Okay.
1:09:01
And I think it's because for the first time we built true
1:09:04
selection software.
1:09:05
SPEAKER_02: Like literally, it's embryo 1, embryo 2, embryo 3, embryo 4, right?
1:09:08
SPEAKER_02: You can compare across any vertical,
1:09:10
SPEAKER_02: any axis,
1:09:10
SPEAKER_02: you can rank them,
1:09:11
SPEAKER_02: you can sort them,
1:09:11
SPEAKER_02: you compare them,
1:09:12
SPEAKER_02: right?
1:09:13
SPEAKER_02: You can leave notes on them, you can even name them if you want.
1:09:15
SPEAKER_02: In other words, it's true consumer-first healthcare.
1:09:18
SPEAKER_02: And that is in itself a narrative violation for the IVF testing industry,
1:09:23
which is saying what the adult genetic testing industry said 20
1:09:26
years ago when 23Me
1:09:27
SPEAKER_02: got launched.
1:09:28
SPEAKER_02: So follow this story with me, Ashley.
1:09:29
SPEAKER_02: In 2006,
1:09:30
I would argue one of the most profound breakthroughs of 2013
1:09:33
wasn't necessarily the
1:09:34
SPEAKER_02: microarray technology.
1:09:35
It was the fact that we are going to go direct to consumer and
1:09:38
give them insights into the DNA.
1:09:40
SPEAKER_02: That was a crazy idea.
1:09:41
SPEAKER_02: You're going to give someone a bracket?
1:09:43
SPEAKER_02: Are you crazy?
1:09:44
SPEAKER_02: That was a crazy idea.
1:09:45
SPEAKER_02: Now you're seeing the same thing.
1:09:46
SPEAKER_02: Nucleus is taking that D2C ethos.
1:09:49
SPEAKER_02: Too clear, we are consumer-initiated, but we're really consumer-focused.
1:09:52
We're taking that ethos and we're going now to a world where
1:09:56
it's honestly a
1:09:56
stronghold by IVF physicians and clinics and the doctors really
1:10:00
feel like they're
1:10:01
SPEAKER_02: the ones in charge of the embryo,
1:10:02
SPEAKER_02: and then we're breaking that.
1:10:03
SPEAKER_02: So you should almost expect...
1:10:05
SPEAKER_02: As nucleus embryo scales,
1:10:07
SPEAKER_02: as we help more parents optimize their embryos,
1:10:10
you're going to see in the same way that people revolted
1:10:13
against the kind of
1:10:14
SPEAKER_02: customer centricity of a 23andMe,
1:10:15
SPEAKER_02: they're going to revolt again.
1:10:16
SPEAKER_02: And they're going to say, oh, it's the science, it's this, this is that.
1:10:19
SPEAKER_02: But actually what it's about is not about the science.
1:10:21
SPEAKER_02: It's about politics.
1:10:22
SPEAKER_02: It's about power.
1:10:23
SPEAKER_02: It's about power that they have over the process.
1:10:25
SPEAKER_02: Because fundamentally,
1:10:26
SPEAKER_02: when you start empowering patients,
1:10:27
SPEAKER_02: someone is going to lose power in that equation.
1:10:30
SPEAKER_02: The IVF clinic starts losing some power.
1:10:32
SPEAKER_02: The doctors start losing some power.
1:10:33
SPEAKER_02: Even,
1:10:33
SPEAKER_02: I would argue,
1:10:34
some of the other companies start losing some power because it
1:10:36
comes all about the
1:10:37
SPEAKER_02: customer,
1:10:37
SPEAKER_02: which is not just how it should be in the adult world,
1:10:39
SPEAKER_02: which on the back of the 23rd,
1:10:41
SPEAKER_02: we're pioneering,
1:10:42
SPEAKER_02: but now also in the IVF testing world.
1:10:44
And then also the fundamental realization that these things are
1:10:45
false dichotomies,
1:10:46
SPEAKER_02: that the application is what matters,
1:10:48
SPEAKER_02: the analysis is what matters.
1:10:50
SPEAKER_02: And we're actually integrating in the adult and embryonic testing.
1:10:53
SPEAKER_00: Okay.
1:10:55
SPEAKER_00: I'm keeping an eye on time.
1:10:56
SPEAKER_00: I just want to change gears just for a couple of seconds.
1:10:59
SPEAKER_00: We could go on for hours.
1:11:00
SPEAKER_00: Are we going to the Joe Rogan style?
1:11:02
SPEAKER_00: I mean, let's go, baby.
1:11:03
SPEAKER_00: Let's go.
1:11:04
SPEAKER_00: We'll break you down.
1:11:07
SPEAKER_00: Hour 10.
1:11:09
SPEAKER_00: I've always wanted to do this.
1:11:11
SPEAKER_00: Oh, wait, one real quick question.
1:11:12
SPEAKER_00: Is this, is it US only for the moment?
1:11:15
SPEAKER_02: No, we accept the files from anywhere.
1:11:17
SPEAKER_02: From anywhere, okay.
1:11:18
SPEAKER_02: And nucleus embryos specifically you're talking about?
1:11:20
Yeah,
1:11:20
no,
1:11:21
I mean,
1:11:21
so you accept people's DNA,
1:11:23
but like if I want to order a test,
1:11:25
SPEAKER_00: Do I have to do that?
1:11:26
SPEAKER_02: We're actually launching international very soon.
1:11:28
SPEAKER_02: So if you want to do that, DM me on Twitter or the like.
1:11:30
SPEAKER_02: Right now, strictly speaking, right now it's US-based for the testing.
1:11:34
SPEAKER_02: Nucleus embryos, anyone can do it.
1:11:36
SPEAKER_02: Also, if you upload your whole genome file, you can come from anywhere.
1:11:39
Our testing infrastructure is about to launch internationally
1:11:42
in a couple of weeks.
1:11:43
SPEAKER_00: Wait, so do I have to do the test or I could just upload my file?
1:11:45
I would still recommend doing our test because I don't know the
1:11:48
quality of the file
1:11:48
SPEAKER_02: that you have.
1:11:49
SPEAKER_00: So I would just record doing the test.
1:11:51
SPEAKER_00: It was aluminum.
1:11:51
SPEAKER_00: It was trustworthy.
1:11:53
SPEAKER_00: So really quick, I hang out with a lot of Teal Fellows.
1:11:57
SPEAKER_00: I've actually never really talked to anyone about the process.
1:12:01
SPEAKER_00: I mean, we have a lot of young kids who listen to the show.
1:12:04
SPEAKER_00: And I mean, what's it like?
1:12:07
SPEAKER_00: I don't know if this is a secret or not.
1:12:09
SPEAKER_00: No, it's not a secret.
1:12:09
SPEAKER_00: There's no secret.
1:12:11
SPEAKER_00: What happens?
1:12:12
SPEAKER_00: I mean,
1:12:12
SPEAKER_00: you send in some application and...
1:12:15
SPEAKER_02: You know,
1:12:15
SPEAKER_02: actually,
1:12:15
SPEAKER_02: I think I applied to the Teal Fellowship like...
1:12:17
SPEAKER_02: five years in a row.
1:12:19
SPEAKER_02: So if you're out there and you've applied so many years in a row,
1:12:21
SPEAKER_02: know that it's a slog,
1:12:23
SPEAKER_02: can be a slog.
1:12:24
SPEAKER_02: I think in a way that's a good thing actually,
1:12:26
SPEAKER_02: because it kind of tests to see who's actually committed.
1:12:28
SPEAKER_02: I think the best way,
1:12:29
SPEAKER_02: I mean,
1:12:30
SPEAKER_02: implicitly what you're asking me here,
1:12:31
SPEAKER_02: I think is like one,
1:12:32
SPEAKER_02: how do you get in and then what's it actually like?
1:12:33
SPEAKER_02: There's like two questions.
1:12:34
SPEAKER_00: Just totally curious what it's like.
1:12:36
Because people always ask me this,
1:12:37
like how do you get into the Teal Fellowship?
1:12:38
SPEAKER_02: I would say that
1:12:40
The people getting the Teal Fellowship are people who,
1:12:43
generally speaking,
1:12:43
drop out before.
1:12:45
SPEAKER_02: I was out of school before the Teal Fellowship admitted me,
1:12:49
SPEAKER_02: and I know that's been true for many of my peers as well.
1:12:51
SPEAKER_02: They were actually out of school already working on their thing.
1:12:54
SPEAKER_02: So that's one thing to note.
1:12:55
It's almost like the ultimate test of how much conviction you
1:12:58
have is not if
1:12:58
SPEAKER_02: someone sends you $100,000 and then you do it.
1:12:59
SPEAKER_02: It's already doing it.
1:13:00
SPEAKER_02: It's already doing it, yeah.
1:13:03
SPEAKER_02: It's like the best evidence is that you're already doing it.
1:13:05
SPEAKER_02: So that's one thing.
1:13:06
When you're actually in,
1:13:07
I mean,
1:13:07
it's a lot of fun primarily because of the community,
1:13:10
right?
1:13:10
SPEAKER_02: I mean, there's an application process, whatever.
1:13:13
SPEAKER_02: But the community, I think, is what is just so phenomenal.
1:13:17
SPEAKER_02: You're hanging out with the people in your cohort,
1:13:19
SPEAKER_02: your class,
1:13:20
SPEAKER_02: but then also all the previous ones and the people in Peter's.
1:13:23
SPEAKER_02: Peter, I mean, yeah.
1:13:24
I mean,
1:13:24
also we're founders from back to,
1:13:25
and founders from that are seed round.
1:13:27
SPEAKER_02: So I also had,
1:13:27
SPEAKER_02: I think,
1:13:28
SPEAKER_02: maybe a different experience too,
1:13:29
because I was sort of exposed to that kind of world before even
1:13:32
doing the Teal
1:13:33
SPEAKER_02: Fellowship.
1:13:33
SPEAKER_02: Like Delian led the round, Keith and Delian led the round in late 2021.
1:13:37
SPEAKER_02: And then the Teal Fellowship probably came, I think,
1:13:40
SPEAKER_02: a year later maybe.
1:13:41
SPEAKER_02: And so I sort of saw that a little bit.
1:13:43
And it's kind of funny actually to be backed both by Teal's
1:13:46
Foundation and the
1:13:47
SPEAKER_02: Founders Fund,
1:13:48
SPEAKER_02: because they're actually very independent entities.
1:13:49
SPEAKER_02: They usually don't like to cross over.
1:13:50
SPEAKER_02: So that's interesting.
1:13:53
But really the value is in the network of kids and the fact
1:13:57
that you can,
1:13:57
I mean,
1:13:58
SPEAKER_02: It's so small.
1:13:59
SPEAKER_02: I mean, you know, it's like so small.
1:14:01
SPEAKER_02: It's just one of these things.
1:14:02
SPEAKER_00: Well,
1:14:03
SPEAKER_00: and then in the Teal Fellowship,
1:14:05
I guess it's changed a bit over the years because you used to
1:14:07
be paying you to drop
1:14:08
out of school and then now it seems more like this couple of
1:14:11
years to go work on
1:14:12
SPEAKER_00: your...
1:14:12
SPEAKER_00: They still give you like $100,000.
1:14:13
SPEAKER_00: Right, but it seems less dependent on you.
1:14:17
SPEAKER_00: dropping out and doing it.
1:14:19
SPEAKER_00: I don't know.
1:14:19
SPEAKER_00: It seems like a way to explore an idea.
1:14:22
SPEAKER_00: How many, is there a number on how many each year?
1:14:26
SPEAKER_00: I think it's around 20, if I remember correctly.
1:14:29
SPEAKER_00: I'm completely sure.
1:14:30
SPEAKER_00: I think around 20.
1:14:31
SPEAKER_00: And what?
1:14:32
And you get selected and then you all meet for like a dinner or
1:14:34
something like that?
1:14:35
SPEAKER_02: Yeah, there's like meetups, dinners.
1:14:36
SPEAKER_02: You go to Peter's house if you're lucky.
1:14:39
SPEAKER_02: That's always fun.
1:14:41
SPEAKER_02: You know, there's always, like, you know, it's interesting.
1:14:44
SPEAKER_02: It's interesting because sometimes,
1:14:45
SPEAKER_02: like,
1:14:45
people are on very different parts of their journey in the Teal
1:14:47
Fellowship now,
1:14:48
SPEAKER_02: too.
1:14:48
Like,
1:14:48
someone might have,
1:14:49
like,
1:14:50
raised money and,
1:14:51
like,
1:14:51
be building their thing,
1:14:52
right?
1:14:52
SPEAKER_00: And so it can be weird.
1:14:53
SPEAKER_00: I think that's what I was trying to get at.
1:14:54
SPEAKER_00: It can be kind of weird.
1:14:54
SPEAKER_00: It used to look more the same.
1:14:56
It was,
1:14:56
like,
1:14:57
someone's,
1:14:57
like,
1:14:57
a freshman or sophomore,
1:14:58
and they're bailing out.
1:14:59
SPEAKER_00: Now it feels...
1:15:00
SPEAKER_00: Yeah,
1:15:00
SPEAKER_02: it used to be like,
1:15:01
SPEAKER_02: you know,
1:15:02
SPEAKER_02: Dylan from Figma,
1:15:03
SPEAKER_02: where it's like literally like,
1:15:04
SPEAKER_02: you know,
1:15:04
SPEAKER_02: like the raw dog,
1:15:05
SPEAKER_02: you know,
1:15:05
SPEAKER_02: it's like,
1:15:05
SPEAKER_02: okay,
1:15:06
SPEAKER_02: let's give this kid money.
1:15:07
SPEAKER_02: I'm like, let's hope for the best, right?
1:15:10
SPEAKER_02: I think it's evolved a lot.
1:15:11
SPEAKER_02: I think they're going back to their roots now,
1:15:12
SPEAKER_02: actually,
1:15:12
SPEAKER_02: a lot,
1:15:12
SPEAKER_02: and they're trying to find really the undiscovered talent.
1:15:15
SPEAKER_02: I mean,
1:15:15
SPEAKER_02: I have to give a shout out to Corey Levy from Z Fellows,
1:15:18
SPEAKER_02: who's done,
1:15:19
SPEAKER_02: I mean,
1:15:19
SPEAKER_02: I was originally a Z Fellow before,
1:15:21
SPEAKER_02: Founders Fund Invested,
1:15:21
SPEAKER_02: before Teal Fellowship,
1:15:22
SPEAKER_02: I was a Z Fellow,
1:15:23
SPEAKER_02: and Corey,
1:15:25
SPEAKER_02: you know,
1:15:25
SPEAKER_02: had this program where you could actually text him
1:15:27
SPEAKER_02: So you know Corey Levy or no?
1:15:29
SPEAKER_02: I don't.
1:15:29
SPEAKER_02: Okay, oh my God, Corey's great.
1:15:31
SPEAKER_02: He has a program where it's called First Text,
1:15:32
SPEAKER_02: where basically he has a phone number,
1:15:35
SPEAKER_02: and you could just text him.
1:15:36
SPEAKER_02: And actually,
1:15:36
SPEAKER_02: originally,
1:15:37
SPEAKER_02: the fun name for Nucleus came from,
1:15:38
SPEAKER_02: I found this firsttext.com,
1:15:40
SPEAKER_02: and I found this phone.
1:15:41
SPEAKER_02: There was literally just a webpage with a phone number, and I texted him.
1:15:44
SPEAKER_02: It's on my Android on Signal.
1:15:44
SPEAKER_00: Did you just text the idea?
1:15:46
SPEAKER_02: I said, hey, yeah, I'm Keanu.
1:15:47
SPEAKER_02: I'm building blah, blah, blah, blah, blah.
1:15:48
SPEAKER_02: And this is a funny story.
1:15:49
SPEAKER_02: So...
1:15:50
SPEAKER_02: I text him.
1:15:50
SPEAKER_02: He doesn't respond for like a week, two weeks.
1:15:52
SPEAKER_02: He eventually responded, oh, sorry, you know, can we talk?
1:15:55
SPEAKER_02: I said, okay, sure.
1:15:56
SPEAKER_02: And then he says, okay, let's talk at this day, this time.
1:15:58
SPEAKER_02: I say, okay.
1:15:59
SPEAKER_02: I go outside.
1:16:00
SPEAKER_02: He doesn't call me.
1:16:01
And then I'm like,
1:16:01
well,
1:16:01
these fucking investors,
1:16:02
you know,
1:16:03
they're the biggest assholes.
1:16:04
SPEAKER_02: And then he,
1:16:06
SPEAKER_02: by the way,
1:16:06
SPEAKER_02: I'm like desperately trying to find money because my parents are like,
1:16:08
SPEAKER_02: you can get kicked out of the home.
1:16:10
SPEAKER_02: So I'm like, I don't know anybody.
1:16:11
SPEAKER_02: I don't know how any of this thing even works.
1:16:13
SPEAKER_02: And then he's like, oh, sorry.
1:16:14
SPEAKER_02: I'm so sorry.
1:16:14
SPEAKER_02: I have two phones.
1:16:15
SPEAKER_02: I'm like, who has two phones?
1:16:16
SPEAKER_02: And he's like, can we talk in the basement?
1:16:18
SPEAKER_02: I'm making fun of Corey now because he's a friend.
1:16:19
SPEAKER_02: Corey's fantastic, just so everyone knows.
1:16:22
SPEAKER_02: So I go to my basement.
1:16:23
SPEAKER_02: I remember I see my brother.
1:16:24
SPEAKER_02: I'm like, you, get out of here.
1:16:26
SPEAKER_02: I kicked him out of the basement.
1:16:28
And I talked to Corey,
1:16:28
and I'm like,
1:16:29
nucleus is...
1:16:33
Like a year of verbal diarrhea.
1:16:36
SPEAKER_02: And then I remember it's like 45 minutes straight.
1:16:38
SPEAKER_02: He's just listening.
1:16:39
SPEAKER_02: Corey's kind of like a quiet, very astute person.
1:16:41
SPEAKER_02: And he goes...
1:16:43
SPEAKER_02: So it's a better 23 and me.
1:16:45
SPEAKER_01: Exactly.
1:16:47
SPEAKER_02: Exactly.
1:16:47
SPEAKER_02: I was like, maybe I should have just led with that.
1:16:49
SPEAKER_02: I was like, maybe that's how you pitch, actually.
1:16:51
He ended up coming in,
1:16:52
investing,
1:16:53
you know,
1:16:54
100,000 bucks,
1:16:55
also with Ed Lando.
1:16:55
SPEAKER_02: So it was $200,000.
1:16:57
SPEAKER_02: And that's how Nucleus got started.
1:16:58
And so,
1:16:59
you know,
1:17:00
and then now I think Z Fellows is,
1:17:01
I mean,
1:17:01
so now First Text became Z Fellows.
1:17:03
And ZFellows,
1:17:04
to me,
1:17:04
is like the most preeminent program today in finding young
1:17:07
founders.
1:17:07
SPEAKER_02: I mean, Corey does not get enough credit.
1:17:09
SPEAKER_02: He's kind of done this very quietly, I think.
1:17:11
SPEAKER_02: He is in every single great deal, every single top founder that's known.
1:17:16
SPEAKER_00: Yeah, I haven't heard of him.
1:17:17
SPEAKER_00: Now I feel, yeah.
1:17:18
SPEAKER_02: Where did he work before he became an investor?
1:17:20
SPEAKER_02: Corey, he built a company.
1:17:23
SPEAKER_02: I can't remember the name of the company.
1:17:24
SPEAKER_02: He built a company.
1:17:25
SPEAKER_02: He actually sold it to ancestry.com, which is pretty funny.
1:17:27
SPEAKER_02: And then from there,
1:17:28
SPEAKER_02: he started doing different projects to help basically very young,
1:17:30
SPEAKER_02: very ambitious technical founders get their start.
1:17:33
And then I think he had a couple of really big winners and he
1:17:35
could scale it more
1:17:36
SPEAKER_02: and more and more and more.
1:17:36
And now suddenly he has almost this like mini monopoly on like
1:17:40
very young,
1:17:41
you know person under 25 that's starting a business he he
1:17:43
manages to kind of uh
1:17:45
find them when they're truly undiscovered and put them in and i
1:17:48
think people like
1:17:49
corey don't get enough credit in silicon valley because it's
1:17:51
very easy to follow on
1:17:52
capital right the hardest thing is when there's a kid and also
1:17:56
i shout out to
1:17:56
delian and keith at the time when when founders from the round
1:17:59
because in the seed
1:18:00
SPEAKER_02: round
1:18:00
SPEAKER_02: I mean, oh my God, every single investor said no.
1:18:03
SPEAKER_02: I mean, every single investor.
1:18:04
SPEAKER_02: One, they don't understand it.
1:18:05
SPEAKER_02: Two, like no one ever really bought into 23 May.
1:18:07
Three,
1:18:07
there's like the whole Theranos thing that they're kind of
1:18:09
scared about,
1:18:09
right?
1:18:10
SPEAKER_02: And like those reasons, and it's also not really tech.
1:18:13
SPEAKER_02: It is tech.
1:18:13
SPEAKER_02: I would argue it's actually tech, but they don't really see it that way.
1:18:15
SPEAKER_00: It was probably the year when you were pitching,
1:18:16
SPEAKER_00: because that would have been close on the Theranos heels,
1:18:19
SPEAKER_00: right?
1:18:19
SPEAKER_02: It was 2021.
1:18:20
SPEAKER_02: Yeah, it's not a good time.
1:18:21
SPEAKER_02: And then they all said no.
1:18:21
And then I'll never forget,
1:18:22
and Founders Fund pitch meeting,
1:18:24
I got introduced to Keith.
1:18:26
SPEAKER_02: Keith takes the meeting.
1:18:27
SPEAKER_02: Good on Keith.
1:18:28
SPEAKER_02: Keith Reboe.
1:18:28
SPEAKER_02: Keith Reboe, yeah.
1:18:29
SPEAKER_02: And Keith says, I'm pitching him.
1:18:34
SPEAKER_02: He says,
1:18:34
SPEAKER_02: you know,
1:18:35
the cost of sequencing is going to come down dramatically in
1:18:38
the next five years.
1:18:39
SPEAKER_02: I was like, wait a second.
1:18:40
This is the first investor that actually has some clue of what
1:18:42
the hell is going on here.
1:18:43
SPEAKER_00: Seriously?
1:18:43
SPEAKER_02: And I can't believe it.
1:18:44
SPEAKER_02: He's the first one.
1:18:45
And he's like,
1:18:45
you know,
1:18:46
I just gave a company half a billion dollars to actually do
1:18:48
that.
1:18:49
SPEAKER_02: I said, what?
1:18:50
SPEAKER_02: First off, half a billion dollars in my mind.
1:18:51
SPEAKER_02: I was like, that's a lot of money.
1:18:53
SPEAKER_02: And then I was like, what is he even talking about?
1:18:54
SPEAKER_02: And then I was like, well, to what's the name of the company?
1:18:56
SPEAKER_02: And he's like, no, no, I can't say.
1:18:58
SPEAKER_02: It's confidential.
1:18:58
SPEAKER_02: So we get off the phone.
1:18:59
SPEAKER_02: And I'm like, well, he does not know what he's dealing with.
1:19:01
SPEAKER_02: And so I asked.
1:19:02
SPEAKER_02: I find a patent, okay, with the name Gilad.
1:19:06
SPEAKER_02: And this is a really funny story.
1:19:08
SPEAKER_02: I find this patent,
1:19:09
SPEAKER_02: and I somehow find his phone number,
1:19:10
SPEAKER_02: and I text him,
1:19:11
SPEAKER_02: and I'm like,
1:19:11
SPEAKER_02: hey,
1:19:12
SPEAKER_02: my name's Keanu.
1:19:12
SPEAKER_02: I'm really good friends with Keith.
1:19:13
SPEAKER_02: Lie.
1:19:14
SPEAKER_02: And I'm like, you know, do you want to, like, you know, talk?
1:19:17
And Gilad's actually,
1:19:18
well,
1:19:18
actually,
1:19:18
before I break it,
1:19:19
let me just finish the story.
1:19:20
SPEAKER_02: And so this guy's like, okay, sure.
1:19:23
SPEAKER_02: It's like he's friends with Keith, I guess.
1:19:24
SPEAKER_02: Like, he's got my number, whatever.
1:19:26
SPEAKER_02: And so we get on the phone the next day.
1:19:28
SPEAKER_02: So I pitched Keith Friday.
1:19:28
SPEAKER_02: We get on the phone with Gilad on Saturday.
1:19:31
SPEAKER_02: And Gilad and I are talking.
1:19:33
And it turns out Gilad is the CEO of a company called now
1:19:36
Public Ultima Genomics.
1:19:38
Ultima Genomics is a new sequencing company that's looking to
1:19:40
drive down the cost of sequencing.
1:19:41
SPEAKER_02: They raise like half a billion dollars.
1:19:43
SPEAKER_02: A lot of it's from Keith.
1:19:43
SPEAKER_02: I think Keith's actually on the board.
1:19:45
SPEAKER_02: And I'm telling Gilad.
1:19:46
SPEAKER_02: And he says, this is such a good idea.
1:19:49
SPEAKER_02: Okay.
1:19:50
SPEAKER_02: And I'm like, oh, thanks.
1:19:51
SPEAKER_02: He's like, well, you know, how much money have you guys raised?
1:19:53
SPEAKER_02: I'm like, well, basically nothing.
1:19:54
SPEAKER_02: He's like, what?
1:19:55
SPEAKER_02: That's crazy.
1:19:56
SPEAKER_02: And then he's like, but where'd you get your PhD from?
1:19:58
SPEAKER_02: Yeah.
1:20:00
SPEAKER_02: I said, no PhD.
1:20:01
SPEAKER_02: He said, really?
1:20:02
SPEAKER_02: I said, yeah, just my bedroom, I guess Brooklyn.
1:20:04
SPEAKER_02: And he's like, okay, okay, okay, one second.
1:20:05
And then supposedly he called Keith and he's like,
1:20:07
you have to invest in this company.
1:20:08
And then I spoke to Delian on that Monday and then five minutes
1:20:11
in the call,
1:20:11
SPEAKER_02: Delian said,
1:20:11
SPEAKER_02: we're investing.
1:20:13
SPEAKER_02: And so I have to give credit to
1:20:15
SPEAKER_02: you know, people who took big bets.
1:20:17
SPEAKER_02: And of course, Alexis Rohanian too from 776, a big bet.
1:20:20
SPEAKER_02: They just saw something.
1:20:21
SPEAKER_02: They believed.
1:20:22
SPEAKER_02: And I think that's the hardest thing.
1:20:23
SPEAKER_02: Now it's like,
1:20:23
SPEAKER_02: there's Nucleus Embryo,
1:20:25
SPEAKER_02: there's the Wall Street Journal articles,
1:20:26
SPEAKER_02: you know,
1:20:26
SPEAKER_02: Twitter's riots,
1:20:27
SPEAKER_02: you know,
1:20:27
SPEAKER_02: we're causing riots on Twitter,
1:20:28
SPEAKER_02: you know,
1:20:29
SPEAKER_02: we're doing the podcast circuit.
1:20:30
Now if someone wants to invest,
1:20:31
I'm sort of like,
1:20:32
yeah,
1:20:32
I mean,
1:20:32
thank you for the support.
1:20:33
SPEAKER_02: Of course, I love it.
1:20:33
SPEAKER_02: You know, it's great to be partnership, but come on, let's be real.
1:20:35
Like there was a time when I was in my bedroom with notebooks
1:20:38
and these are people
1:20:38
SPEAKER_02: who allocated millions of dollars toward us.
1:20:41
SPEAKER_02: That to me is the true spirit of venture.
1:20:45
SPEAKER_02: So that's kind of what I always think about.
1:20:47
SPEAKER_00: Okay, that's cool.
1:20:48
I feel like there's obviously a lot of people super into Peter
1:20:53
Thiel and Founders
1:20:53
SPEAKER_00: Fund and what they do,
1:20:54
SPEAKER_00: and then there's a whole world of people who sort of,
1:20:57
SPEAKER_00: well,
1:20:57
SPEAKER_00: they kind of like detest Peter on a political,
1:21:00
SPEAKER_00: personal level and maybe are suspect of Founders Fund.
1:21:03
I always find the Founders Fund people in that orbit in
1:21:09
particular to be just like,
1:21:12
SPEAKER_00: Don't agree with everything, but who does?
1:21:14
SPEAKER_00: I just find them to be really intellectually stimulating.
1:21:16
SPEAKER_00: I think there's no greater party than a founders fund party.
1:21:20
SPEAKER_00: Yeah.
1:21:20
SPEAKER_00: It is maniacal.
1:21:21
SPEAKER_00: Because, and I know, I don't know, there's people who just would think.
1:21:26
SPEAKER_00: it's all evil or whatever,
1:21:27
SPEAKER_00: but I go spend a weekend with the Founded Fund Circle and like,
1:21:33
SPEAKER_00: honestly,
1:21:34
SPEAKER_00: my brain is just humming as I'm going to bed.
1:21:36
SPEAKER_00: It's hard to like, actually, I'm a really good sleeper.
1:21:39
SPEAKER_00: It's hard to sleep because you just,
1:21:40
SPEAKER_00: I have all these story ideas and then you just,
1:21:43
SPEAKER_00: I have major,
1:21:45
SPEAKER_00: Imposter syndrome because you're just with all these incredibly high IQ.
1:21:48
I'm usually like a talker and then that's like one of the few
1:21:51
places where I just
1:21:52
SPEAKER_00: shut up or try to.
1:21:53
SPEAKER_00: And I just, and then people ask me about the stuff I'm doing.
1:21:56
SPEAKER_00: I'm like,
1:21:56
SPEAKER_00: whatever I'm doing,
1:21:57
SPEAKER_00: it's not,
1:21:58
it's not interesting compared to whatever's about to tumble out
1:22:01
of your mouth.
1:22:02
SPEAKER_00: Just, just keep, keep talking.
1:22:04
SPEAKER_02: What's so interesting about Founders, I mean, think about Nucleus, right?
1:22:06
SPEAKER_02: Like,
1:22:07
SPEAKER_02: They really do live up to their ethos.
1:22:09
SPEAKER_02: I think sometimes on Twitter,
1:22:10
SPEAKER_02: it's kind of a joke,
1:22:11
SPEAKER_02: this idea of a contrarian,
1:22:12
SPEAKER_02: but here's a 20-year-old kid,
1:22:15
SPEAKER_02: dropout,
1:22:15
SPEAKER_02: no reputation,
1:22:16
SPEAKER_02: knows nobody,
1:22:17
SPEAKER_02: in his bedroom with no books.
1:22:19
SPEAKER_02: I never forget the time when I was on my LinkedIn.
1:22:21
If you used my LinkedIn back then,
1:22:23
I see Keith Woodboy looked at your profile.
1:22:25
SPEAKER_02: And the fact that he looked at that profile...
1:22:28
SPEAKER_02: And then invested in a bio,
1:22:30
SPEAKER_02: I mean,
1:22:31
SPEAKER_02: seed round founders fund,
1:22:32
SPEAKER_02: institutional investors in a bio related company.
1:22:34
SPEAKER_02: Okay.
1:22:35
SPEAKER_02: In, in a random ass kid, you know, off, you know, in Brooklyn, I mean,
1:22:41
SPEAKER_02: They live up to their ethos, man.
1:22:45
SPEAKER_02: They take the swing.
1:22:47
SPEAKER_02: And I texted Keith recently.
1:22:49
SPEAKER_02: I was messing with him.
1:22:49
SPEAKER_02: I was like, look at the launch of Nucleus Embryo.
1:22:51
SPEAKER_02: I'm like, look, five years ago, I called it.
1:22:54
And that's the thing,
1:22:54
which is to actually have the proof hit the pudding.
1:22:57
SPEAKER_02: It's kind of what I say to you about some of the hater comments.
1:22:59
SPEAKER_02: It's like, you can say whatever you want.
1:23:01
SPEAKER_02: The proof is in the pudding.
1:23:03
SPEAKER_02: I mean, you can go back eight years.
1:23:04
SPEAKER_02: You can read...
1:23:06
My work I was doing with gene editing in the laboratory in the
1:23:08
Wall Street Journal.
1:23:09
SPEAKER_02: I love genetics.
1:23:11
SPEAKER_02: And the thing is,
1:23:11
SPEAKER_02: I was telling this to someone recently,
1:23:12
SPEAKER_02: I was telling this to my friend,
1:23:13
SPEAKER_02: which is,
1:23:13
SPEAKER_02: when you are so sincere in what you do,
1:23:16
SPEAKER_02: and when the mind,
1:23:17
SPEAKER_02: body,
1:23:18
SPEAKER_02: soul is all aligned,
1:23:19
SPEAKER_02: it shines so bright.
1:23:22
SPEAKER_02: Everyone is, I think, lifted up by it.
1:23:24
SPEAKER_02: And I think that's where I feel like I am in my life.
1:23:26
SPEAKER_02: A lot of times in college, I didn't feel that way.
1:23:29
But when I'm on this pathless path,
1:23:32
I just feel so...
1:23:33
I see angel numbers around me.
1:23:36
SPEAKER_02: I feel just so... I'm called to do it.
1:23:41
SPEAKER_00: So I'm very, very grateful for that.
1:23:42
SPEAKER_00: Well, I mean, that's cool.
1:23:43
SPEAKER_00: That's when you know you're doing what you're supposed to do.
1:23:47
SPEAKER_00: I think I'm supposed to let you get to Berkeley.
1:23:50
SPEAKER_00: Yeah.
1:23:50
SPEAKER_00: So thank you so much for your time.
1:23:53
SPEAKER_00: Thank you to E1 Ventures for...
1:23:55
SPEAKER_00: Help us out.
1:23:56
SPEAKER_00: Yeah.
1:23:56
SPEAKER_00: No, thank you so much for coming to the office.
1:24:00
SPEAKER_00: Give them the love.
1:24:00
SPEAKER_00: Give them the love.
1:24:03
SPEAKER_00: I'm just going to say, yeah.
1:24:03
SPEAKER_00: Those were both.
1:24:05
SPEAKER_00: No, but thanks for checking out there from New York.
1:24:07
SPEAKER_00: And it's actually like mynucleus.com.
1:24:10
SPEAKER_00: Mynucleus.com.
1:24:11
SPEAKER_02: If you want to do the embryo stuff, mynucleus.com slash embryo.
1:24:14
SPEAKER_02: People want to check out.
1:24:15
SPEAKER_00: All right.
1:24:15
SPEAKER_00: Awesome.
1:24:15
SPEAKER_00: Thank you so much.
1:24:16
SPEAKER_00: Have a great rest of your day.
1:24:17
SPEAKER_00: Thanks.
1:24:18
SPEAKER_00: Thanks everyone for listening.
1:24:22
SPEAKER_00: Core Memory is hosted by me, Ashley Vance.
1:24:25
SPEAKER_00: The show is produced by David Nicholson and me.
1:24:29
SPEAKER_00: Our theme music is by James Mercer and John Sortland.
1:24:33
SPEAKER_00: And the show is edited by the John Sortland.
1:24:38
SPEAKER_00: Thank you all for listening.
1:24:40
SPEAKER_00: As mentioned, the show is sponsored by Yuan Ventures.
1:24:44
SPEAKER_00: Thanks.