The Real Reason 23andMe Failed (And How It Will Double Human Life Expectancy) | ROP #42

Kian, why did you drop out of college?

I mean, honestly, I think you just have a calling. You know, I actually think of startups in like the hero's journey where you have to leave home and then you end up back home ultimately, but you have to leave home initially and because there's so much this greater calling. And I think part of the reason why I left college is this quote from Joseph Campbell. So Joseph Campbell writes a lot about The hero's journey and stories, right? And he notes that bliss or happiness is when your inner being matches the physical plane. And so in college, my inner being, who I knew I meant to be, who I knew I meant to become, very much was at odds with what was around me, with who I was around. And that fundamental chasm drove me away. And in going away, I ended up finding— myself and what I was meant to do.

Awesome. You've mentioned your cousin's tragic death as a turning point. Just talk me through how that experience shaped the mission and what Nucleus Genomics is today.

Yeah. So Nucleus is the genetic optimization company. So we basically help people use genetics to give themselves, their family, and future family the best possible life. Okay. Nucleus was born out of a personal experience of mine where I was probably almost 7 years old and I remember waking up one day and basically I was told that my cousin, she had died. And it's a weird thing. It's a weird experience to hear about your 15-year-old cousin who was there and then suddenly not. I think it kind of bends with your understanding of what it would— there's always this like, underlying bias with life that you assume it's going to be there forever. And then, death is this oddly permanent and it's so silent yet it's so loud kind of thing. And so, I asked my dad eventually, I was like, how does this happen? How did she die? And my dad was just like, oh, it's bad genetics. And that sort of triggered me in my unconscious apparatus like, wait a second, hmm, what does that mean? I don't know, genetics, what even is that? And eventually, I actually joined one of the first do-it-yourself genetic laboratories in the country where we engineered yeast to make them eliminate. We added bacteria to make them resistant to antibiotics. And, this was on the 2nd floor of a warehouse in Brooklyn. So, this is some deep biohacking stuff. This is OG CRISPR days. And, it's interesting because actually at that time, there was a Wall Street Journal journalist doing a story on the kind of almost hacker home for biology, if you will. And, it's amazing because 8 years later, It's the same journalist that wrote the story about nucleus embryo. So that we can talk about that and kind of that feeling. But going back to high school, I loved the sort of beauty and depth of biology, but it wasn't very iterable, right? So this idea that, hey, you can like manipulate biology was extraordinary to me. But something about the wet laboratory, you know, I didn't like it because if you make a mistake, you have to then repeat the entire experiment again. But on the computer, if you made a mistake, you just click the delete button. And so, I actually went to Penn to study computational biology, which is basically this intersection of bits and atoms where I could realize and harness the beauty and depth of biology, but on the computer. And so, I started taking statistics, computer science, genetics. And one day I was in Bio 221, which was biology. I think it was actually, might have been even genetics class. And the chairman of the biology department brought up this chart that showed the decreasing cost of reading the human genome. Wow. And it used to be $1 billion in 2000, and in 2020, it was about $1,000. And I thought to myself, wait a second, this is one of the greatest decreasing costs ever. Obviously, this price is converging on nothing. It's going to be negligible. Somebody needs to build the software application layer for DNA. And I kind of saw this chart and I had this weird moment. I turned to my friend and I said, bro, this is crazy. This is the craziest thing I've ever seen. And he goes, is it going to be on the midterm? Oh boy. And I said, talking to what I said earlier, which is there's this chasm between this inner calling, this beauty, this bliss, and then the physical plane, the environment I was in. I felt like I was in Get Out almost, like I needed to get out of here. And so I did. And so I moved back into my bedroom in Brooklyn. I lied to my parents about what I was doing. Sorry, Mom and Dad. I told them I was working in a lab, which in a sense I was working in a lab, except it was the Kian lab. And so, I filled in about 18 subject notebooks on genetics and statistics. And basically, the core problem I was trying to figure out is how do you build software that analyzes DNA, which is what we do. And, I basically eventually realized that I could provide myself the most comprehensive genetic analysis that's really ever been made possible, literally by combining also almost 200 years of genetic science into a product. And, I remember I told my mom and dad this and they said, We're kicking out of the home. I said, "Oh my God, that ain't good. I gotta figure this out." And so I actually found a phone number online. Shout out to Corey Levy from Z Fellows, and I texted him. This angel investor, and he ignored me. Don't worry, he ignored me two weeks. Oh, sorry, I have two phones. Who has two phones? We get on the phone, and I give him probably the most garbled pitch ever. I say, "Nucleus is." Silence. Forty-five minutes. 45 minutes straight of this silence. I'm waiting for him to see what he says. And he goes, so it's a better 23andMe? I said, yes, exactly. Then I thought, hmm, maybe I should just pitch like that. Important lesson learned there. And he said, okay, give me a minute. Let me call up one of my business partners. He did that and then they invested $200,000. That's how Nucleus got started. Since then, we've raised over $30 million. We brought to market the clinical-grade whole genome test, but more than the clinical-grade whole genome test, we're really building the first full-stack genomics company. And, what I mean is that you can see we're the only company, literally the only company that is sequencing and analyzing adult DNA and now also is testing and analyzing embryonic DNA. And, these things are actually all one of the same problem because, again, Nucleus is the genetic optimization company. We use genetics to basically help people not just optimize their health and longevity, but also optimize their future children. And we use the word optimize very deliberately because genetics and life really isn't just about the absence of disease, it's about thriving, right? If you think about the longevity movement today, no one is saying, oh, I don't want to get— no one is just saying, I don't want to get Alzheimer's, I don't want to get cancer. Sure, absolutely, you don't want to get disease, but you also want to thrive. You want to be strong, you want to be well, your mind wants to be sharp, right? That's what's really important to people. So, We recognize genetics for what it is, which is it isn't just about disease, it's about optimization. So, that's kind of the story of Nucleus.

Maybe everyone's marker for this sector, or when you talk about it, it's, oh, 23andMe. Of course, everyone's done a 23andMe test. Talk me through why did 23andMe fail and what are you doing differently?

2 things about that before I answer your question directly. Number one, what I'm perhaps most happy about, is since the launch of Nucleus Embryo, which is our embryonic analysis platform, people don't ask me anymore how we're different than 23andMe because they get it, right? I always like to say that with consumers, investors, and media alike, the best way of telling someone something isn't by telling it to them, it's by showing them. And Nucleus has shown— we've shown everyone. So, that's my first point. The next point is to answer your question more directly, which is genetics has undergone one of the grandest technological transformations Ever. And it's one that I think is not discussed enough because a lot of people don't even know it exists and/or understand it. And so, if you go back to 2006, or 2013, we got started, the cost— so think of your DNA as like a 1,000-page book. In 2006, the cost of reading all 1,000 pages, $10 million. To read all 1,000 pages of your DNA book was $10 million. So, in 2013, we said, okay, that's way too expensive. we're gonna use technology that looks at 1 page out of 1,000, right? In other words, the fundamental genetic testing technology they're built on was limited. They really couldn't actually do any hereditary disease analysis or family planning as examples. And because of that, they really were a gimmick. They were about genealogy, they were about ancestry, right? Which is actually what most people still even associate 23andMe with. And so the first problem was a technological problem. Next, Next problem was a business model problem. They really— this is one of the most profound misconceptions about 23andMe. People will say, I did 23andMe, but it was a one-time test. How do you create recurring value? This doesn't make sense. You weren't the customer. The customer wasn't the customer. Remember, 23andMe, the first investor was Google, right? We're talking about an era, Web 2.0, Google, Facebook, 23andMe. There's many other examples. Where the customer's object, the desire for the company was to provide them with data, and then they would use that data and sell it to a third party. Google and Facebook still offer this way. The customer is actually somebody else. It's not you. You provide the data that then you sell to someone else. 23andMe was actually very similar, right? People provide their genetic data and they use that information to sell to pharma. And so, if you actually think about it from that perspective, it makes perfect sense why 23andMe didn't build a recurring platform. because they placed a very specific bet on that the data would be sufficiently valuable that they wouldn't need to, à la Google, à la Facebook. Again, remember, Ann was actually married to the co-founder of Google, and Google was the first investor. It is the same kind of ideology that created 23andMe. Here's the problem, and this is a great example where business model and technology converge. The underlying technology of 23andMe, as I mentioned, was fundamentally limited. So now you have a situation where when actually you built the dataset that was so sufficiently valuable, that then you went to try to sell to the drug company, what did the drug companies find? The drug companies found that actually, it's not all that valuable because there are massive gaps in the DNA file that was read. You couldn't actually use it for drug discovery. And so, this is actually interesting now because you have a problem where the DNA fundamentally is just limited. You have a situation where you're not re-engaging your customers because you're making a bet that the pharma companies are going to get a lot of value from that and you fail there. And the last one I think is They did a really, really bad job communicating and operating under data privacy and security guidelines. What do I mean by this? So one of the most common questions I get is about how is Nucleus secure? And I think it's interesting because sometimes people will treat genetics data as somehow dramatically more— I agree that it's extremely important, but dramatically more important than the rest of your health information. Like if you get a cancer diagnosis, you would want that to be private, obviously. Right? You wouldn't want that to get leaked. If you get a full-body MRI, you'd want that to be private, right? And the reason why when you go to the doctor's office or hospital, you know, you do a test, even genetic tests people do in the hospital context, right? You know that information's bound by HIPAA. You know that information's only gonna be used to treat you with better care. And that's why Nucleus is HIPAA compliant, right? And that's why we follow all those guidelines because we basically say, look, there is existing regulations for handling people's health and genetic information, right, that we actually follow, right? 23andMe was never HIPAA compliant because they were a D2C test, not a physician-ordered test. They actually weren't bound by any of the massive existing regulations that protect customer health information, right? And because of that, I think they made a lot of mistakes in terms of communication and the way they handled the people's data, which was, I think, the final blow. So now you have technology problems, You have a strategic business model problem, and I think you have a PR/marketing and kind of customer agency problem. So now think about Nucleus. One, we're starting from a whole genome, right? Instead of looking at 0.1% of DNA, we're looking at almost 100% of DNA. Suddenly you can basically do every application known to man. Diseases, pharmacogenomics, tell you DNA affects metabolism of different drugs. IVF genetic testing analysis, you can actually build models that analyze that data. You can do traits as well if you really want. You can do preconception testing, right? So, you can do every possible application in one single thing. Next, business model. I like to say that Nucleus isn't a genetics company, we're a healthcare company. I think for a while people didn't understand that. Now they are. They can see how when you build the software out there for DNA, what you're actually doing is you're actually going to be merging 2 seemingly different markets, right? So today, if you go to adults, so if you think about the genetics industry today, right? There's Myriad Genetics, multi-billion dollar company that does hereditary cancer screening. There's Natera, which is like preconception testing amongst other things. Preconception testing just means checking to see if mom and dad are both a carrier for the same thing so they don't pass down some really bad condition, right? Then there's the IVF testing companies, right? Which we all know just analyze embryonic DNA. Then there's pharmacogenomics, which is how your DNA affects your metabolism. of different drugs, right? Then there's also like traits, right? Now suddenly all these which make up many, many, many, many billions of dollars worth of businesses, right? Through the power of the whole genome, they're combined into one business, right? So that's solving this problem like, hey, actually speaking, if you think about what Nucleus is, or you think about what DNA is, DNA is the foundation of building not just a real-time consumer-centric quantified health stack that integrates all your health data, but also building the reproductive stack of sequencing, analyzing, and eventually actually engineering DNA. So now we solve the second problem. The third problem is we want to give customers complete agency and control over their data. When I was building Nucleus in my bedroom, that was literally alongside rigorous science, the most important foundation, which is one, we're HIPAA compliant. So you can trust Nucleus at least as much as you trust your doctor, right? When you go to a doctor, there's a lot of very sensitive information. We follow all HIPAA guidelines. We're actually a clinical laboratory. in the way we treat and handle information. It's your information. You can download it at any time. And by default, we do not share your genetic information or protected health measurement with any third party. And that gives our customers comfort in knowing, okay, now I can get profound insights safely. And of course, the cost of sequencing keeps coming down. So we're going to be able to get sequencing into more and more people's hands. I think you're talking about one of the greatest combinations of different trends in the history of technology. Truly, I believe that.

I'm going to ask you about the whole genome sequencing and drug development very quickly. I and many, many millions of other people around the world stared at that cost per sequencing genome chart and said, oh, cool. You actually built a business out of it. Do you think it was that foundational story about the tragic death of your cousin that kind of compelled you to go a step further?

Yeah. Are you asking basically why me? Why am I doing this?

Yeah, because not many people have seen that chart and you were actually the one to do something about it, let's say.

Let me tell you a story. It's going to seem unrelated, but it's actually related. One time I was playing, you know, my life, I mostly played soccer as a sport. It was a sport that I love. Where did I play?

Yeah,

I played basically on a club soccer team in New York. I also played—

I meant like position, like—

Oh, okay. I used to play right mid. Okay. Usually, yeah. Sometimes I played center mid too. And I eventually picked up, actually, I played tennis on the side and I eventually picked up squash actually. So, this is kind of like I always played tennis and squash, probably a little bit more like I played soccer. And one time in college, I was there briefly, but I was playing squash. And what I was sort of known for is just basically almost dying on the court. Okay? And so, one time I was playing with my friend and I remember he hit like a— one thing I do in squash is I hit really short shots. I'm very good at hitting really short shots to kind of make someone have to really sprint. And then, I hit the kind of further out lobbies so they have to go back, just kind of part of the game. And my friend actually did it against me. He hit a really short shot. And I was sprinting so hard, I dove headfirst Okay. Straight, fully parallel to the floor. And I basically— my friend was like, oh, he's dead. Fortunately, I survived. But then in a way that became a metaphor, I think, as like a joke, both for me and him and just how my personality is, which is, I mean, I dove harder, more aggressively, More fervorously than anyone in the world. And when you do that, you win.

Now that we have whole genome sequencing, how do you think that's going to change drug discovery? Like, is the promise of— the original promise, or maybe what everyone thought 23andMe is going to do, do you think that's going to come true in the next 5, 10 years?

Man, do I have so many thoughts about this. I see so many misconceptions on Twitter about genetics and drug discovery. So a couple things here. Ultimately, when you are trying to use genetic information to make drugs, what you're really looking for is some sort of target or some sort of mechanism. One thing to know about genetics is that the genetic information that 23andMe had, it really focused on something called common variants. Common variants are variants that like everybody has, right, that have very small effect individually on disease risk. So that's why you build polygenic models or models that basically combine up to a million of these markers together into scores. In other words, what I'm trying to say is the data that 23andMe has is not actually all that good for drug discovery. And so you need to actually find rare genetic markers that have very high impact on a disease. And rare markers, you simply can't find them from 23andMe data. You actually need whole genome data. And so suddenly when you move from 23andMe data to whole genome data, you might start identifying rare genetic markers for common diseases like Alzheimer's or Parkinson's or cancers. And then you can use these rare genetic markers to actually inform drug discovery in a far better way than you can microarray data. I think, you know, people, I think someone's gonna say, someone's gonna be listening to this podcast and say, but 23andMe, you know, Regeneron bought 23andMe, presumably it was, you know, that valuable. Right. 2 things. One is Regeneron obviously did not end up buying 23andMe. So how valuable was it really? I mean, they got outbid by like $50 million. $50 million for Regeneron is nothing. Okay. If they wanted 23andMe, they could have gotten 23andMe. They said, okay, this is a nothing burger. The second thing is, remember, Regeneron's own genetic database isn't built on microarray data. It's built on whole exome data, right? So the way you think about this, the intuition for your listeners is to say, Whole genome data is the most advanced genetic test. It looks at all of DNA. Whole exome data looks at all basically the protein coding regions. You can think of it as looking at all the genes in your DNA. It turns out the genes actually make up a small bit of DNA. Only around 2 to 3% of the genome are actually genes. So there's whole genome, there's whole exome, which is smaller, then there's 23andMe data, which is even smaller, which looks at— doesn't even look at— it looks at different pieces throughout the genome. So pieces of a gene, pieces of non-genic regions. That's 23andMe data. And so Regeneron, they actually have the second bucket, which is whole exome data. Why did they actually do whole exome data? Why did they make that decision? They made that decision because the underlying assumption is that the genetic markers found in genes are going to be able to give insight or dramatically better insight into mechanism, right? Because obviously when you look at the genome, if there's some sort of weird genetic marker in some non-gene region, it's much harder to understand what does that marker do Versus if it's in a gene and kind of disrupts some mechanism, okay? And so Regeneron, in my opinion, probably speaking, and this is a narrative violation, so get ready for this, probably speaking, wasn't actually interested in 23andMe's data, okay? They were probably actually interested in the physical samples that 23andMe biobanked. No one has said this, no one has reported this, Okay. I don't know why. I think people maybe don't really understand. They look at what they think. And the thing is, Regeneron probably, because 23andMe has millions of samples biobanked. A lot of customers don't realize this. Their samples biobanked. And we, by the way, discard the samples. We don't store them. But 23andMe has these physical samples, these physical set samples biobanked. And so what they were going to do, in my opinion, is they were going to take those and use it to actually generate at least whole exome data. if not full genome data. And we know this because let's just say I know the industry really well and I know what goes on in the industry. And it's really interesting because it would've cost a lot of money, but probably would've been worth it because you can build a massive, massive database off of this information. But clearly it wasn't worth that much, right? Because they got outbid and they didn't continue bidding. And so actually I would go even further and say, People who said on Twitter that, oh, the microarray data is so valuable, this is like a moment, it's just not true. I don't think they really cared about that data. And in fact, I would argue there's evidence this is true because if you look at 23andMe had partnerships with GlaxoSmithKline, with GSK, and if you look at GSK, right, I mean, what happened? They had a couple of targets, but did anything materialize? Not to my knowledge. No, nothing really materialized. And so I also think that partnership, we never really heard anything about it. Something went sour there for sure. And this is not— I don't have inside information in that, to be clear. I just assume based off the way that the press was done on something, something kind of stinks. And so clearly nothing really came out of it. Then my last point is really important point, which is, look, 23andMe, they had existed for 20 years, okay, since 2006. They were by far the most prominent genetics company. At some point they'd IPO'd for billions of dollars, right? People will sometimes say, oh my God, 23andMe failed and now this data is made available for someone to buy it. 23andMe failed because the data wasn't that valuable. Okay, this is really important. People get the causality wrong. It's not that 23andMe failed, then now, oh my God, the data is available and someone's going to buy it. 23andMe failed because the data wasn't all that valuable. And this is what I find so— and I wish the media better reported this. Like, it's such a small sliver of DNA. People would go on 23andMe, they would discover their pee smells like asparagus. And then you see people talking about national security implications. And don't get me wrong, again, I'm all for obviously protecting genetic information, but I'm also for what's the facts on the ground. The facts on the ground that this information was fundamentally limited, fundamentally limited in what actually it contained. And so there was a chasm between what people thought was in the data and what was actually in the data. And they thought 23andMe failed was this massive exposé, when in reality 23andMe failed because the data wasn't all that valuable, right? They had what, 10 years to mine the data? They had literally billions of dollars. And nothing happened. And so that's another narrative violation I think people should think about and kind of chew on.

I think I've heard you say everyone will one day have their full genome on their iPhone. What are the second and third order effects of that on health, on relationships? Just how will the world change when that happens?

That's a great question. I think we're moving to the era of genetic optimization. What does that mean? Let's break this down. I like to always think and answer this question from a kind of stack perspective. Okay? Let's first start with adults and then let's go to the kind of embryo world, which people are excited about. So, when you start with adults, there's a lot of crazy stats with how much genetics impacts health. So, I always like to take a step back here and say, what is the objective? of the company like Nucleus on the adult side of things. Ultimately, it's longevity, right? Ultimately, we want people to use genetics to optimize. And when we say optimize, we want them to live longer. And so, if you look at, I think it's the mid-1800s, let's say 1880 approximately, life expectancy was about 40 years. Okay? From 1880 to 2024, life expectancy doubled to 80 years. So, in about 150 years or so, you see life expectancy double. Why? Why did life expectancy double between 1880 and 2024? Well, it was technological progress. It was vaccines. It was sanitation. It was antibiotics. If you look at the mid-1800s, more than 50% of people died from bacterial infection. Bacterial infection. This was until the rise of antibiotics. In other words, the rise of technology. And then people started living dramatically longer. Today, vast majority of people, more than 50% of people, you know what they die of? Chronic conditions, cancers, Alzheimer's, Parkinson's, heart disease, right? In other words, we have a very similar problem to what we had 150 years ago prior to doubling life expectancy. This time though, we're not dying of bacteria, we're dying of these chronic conditions. So, I put it as, okay, if we want to once again double life expectancy, in the next, let's say, 150 years, which I think people sometimes when we talk about longevity, it's important to ground the objective. I want to live forever. That's great. But I want to ground the objective in what has historically been done. It's like the old quote, the best way— history doesn't repeat itself, but does rhyme, that sort of idea. So, I want to think, okay, our objective right now as a species should be to double life expectancy in the next 150 years. Okay, how do we do it the first time? Well, we found the thing that was killing us. Yeah. And solve that problem. Now let's do the same thing. What is killing us? Chronic conditions. Now let's solve that problem. And so let's look at chronic conditions, right? Cancers, diabetes, Alzheimer's, breast cancer. If you actually look at these different chronic conditions, it's basically true that many of these conditions are at least 50% genetic, which is crazy to think about, right? Alzheimer's, heart disease, even some cancers are at least 50% genetic. And this is a really key point, which is DNA is going to be a critical piece of the longevity puzzle. Of course, it's not going to be everything because, of course, what you eat and your environment matters, and no one would ever dispute that. But it is a critical component to know. And so, when you break it down even further, now we have this interesting mental math if you think about what we're building. First is you have this idea that chronic conditions are killing everyone. It's how the vast majority of people are dying. So, obviously, you have to solve these chronic conditions. When we look at these chronic conditions, they're a complex interaction of both genetic and environmental factors. Let's pause the environmental factors and break down more into the genetics, because that's obviously what we do. Let's take 3 conditions of these 3 examples of these chronic conditions. Let's take colorectal cancer, let's take breast cancer, let's take high cholesterol. Okay? If you just look at these 3 conditions, in America, there are millions, millions of Americans with a rare genetic marker that dramatically increases their risk of one of these conditions. Okay? So, in other words, very famously, Angelina Jolie, I think it was in 2008, She had a rare genetic marker that increased her risk of breast cancer dramatically. Okay, what did she do? She got a double mastectomy and brought her risk of breast cancer down from around 80, 90% to basically negligible, 0%. And so if you think about that framework, you start realizing chronic conditions are killing us. If I just take a portion of these chronic conditions, you see that they're actually quite genetically driven. Okay, if you look at just, let's say, breast cancer, colorectal cancer, high cholesterol, Each of these millions of Americans have really bad genetic markers that dramatically increase their risk for a condition. If you have one of those markers, they're actually actionable. And that's the really important thing. They're actually actionable. I gave the example of Angelina Jolie to kind of show how actionable they are. In other words, those millions of Americans have a ticking time bomb in their DNA. Yet each of those conditions are entirely preventable, right? And so suddenly from just a swab, you could save millions of Americans' lives from a swab. And of course, I just gave examples of 3 chronic conditions. There's many more than 3 chronic conditions. And more than that, there's new ways of analyzing DNA. They're called polygenic scores, where they don't just focus on looking at really bad, rare genetic markers, which is the ones I'm alluding to. They're actually focused on taking people at population levels and more— and basically at a population stratifying people's risk. And when you apply polygenic scores, you find that someone's at least at least elevated for at least one of these chronic conditions, right? And, and, you know, it's really sad, but if you think about, you know, there's very common stories you hear people say, my mother died of this, my grandfather died of this. In other words, people know intuitively this idea of like genetics is kind of really driving something, right? Because there's long history of maybe diseases in someone's family. And so now we can actually quantify that and be more precise and then actually provide Basically, this idea of what we call generational health, identify that genetic marker, have someone actually act on it to prevent the kind of destiny, if you will. It's not actually destiny, but to prevent that fate that's in their DNA. And so, now, you're taking genetics from something that's scary maybe, and maybe even a little bit like, oh, I'm scared of knowing about my genetics, to, look, if you're going to get on a plane 3 months from now and I told you that plane is going to crash, you know what you're going to do? You're not going to get on that plane. So, as scary as that is, it's going to be distressing when you first learn out, you're not going to get on that plane. That's the power of genetics. And that's just in the adult testing and health optimization. And now, let's go to the next thing, which is preconception testing. So, basically, anytime people plan on having kids, it's possible that mom and dad are both carriers for a rare genetic marker. This genetic marker doesn't impact their health, but could impact their future child's health. if they receive the genetic marker from mom and dad. And so, if you think about it, if you look actually globally, there's millions, there's millions of babies with really bad genetic diseases simply because mom and dad did not swab their cheeks. So, it cannot be overstated. And one of the sad parts, both sad and happy, I guess, parts of doing this job is that parents come to us and say, my baby has this genetic disease, can you guys help? And what's really unfortunate and sad is at that point when the baby has the disease, there's actually not much you can do. But when upstream, before you have your child, you know, mom and dad swab their cheeks and suddenly you're able to actually prevent a child from having a severe genetic disease. And this is actually recommended by the American College of Gynecologists and Obstetricians for every couple in the United States to do just because it's such a common sense preventive measure. And so now, when you think about it, when genetics becomes ubiquitized, you can not only see adults living longer and helping solve the chronic disease epidemic, but also now you can see generationally, basically, you could help literally get rid of genetic disease. I mean, think how powerful that is. There is no other preventative measure in healthcare today that is as consequential and as profound as genetic testing. Why? Because it is the only non-invasive, non-painful— it's a cheek swab. Through a cheek swab, mom and dad cheek swabbing. Again, it's non-invasive. You don't put anything in your body. It's not like you have to actually even do any surgery or anything. Of course not. You put a cheek swab in your cheek, mom and dad put a cheek swab in their cheeks, and then you prevent millions of babies of having disease. Name me another preventative measure that is so easy, that is so quick, that is so painless, and now that it's so cheap. Doesn't exist. Okay, so that's on the preconception testing part. Let's keep going. Drugs. Okay. It turns out that drugs actually have a dramatic different effect on different people, right? And the way people respond to different therapies is dramatically different. Genetics plays a very large role in that. And so, if you actually look at the research, right, everything from blood thinners all the way to something like even Ozempic, they're beginning to find— and the way people respond to chemotherapies and also neuropsychiatric drugs. Genetics has a dramatic impact on the metabolism of these different drugs. So we're also talking about another application. So genetics cannot just tell you what you're at risk for, but also tell you how you respond to drugs differently, which obviously can be literally— also save someone's life to make sure that they get the right dosage or even the right drug, the right drug and the right dosage when they're undergoing some sort of therapy. That's another profound application. But I'm not done. I'm not done. So now we have adult testing, we have preconception testing, right? Stopping passing down disease. We have pharmacogenomics, which is picking the right drug for you based off your unique DNA. And then of course, Nucleus Embryo, IVF. Nucleus Embryo, for the audience who doesn't know, is basically our new genetic optimization software. And so we help parents undergoing IVF give their future child the best possible start in life. Okay? Okay. Nucleus IVF is now, if you think about it, it's longevity at life's inception. Why? Well, if you look genetically and you see, okay, if you ask the question, what genes are associated with longevity? What genes are associated with living a longer and healthier life? Well, the genes that are associated with longevity are the same genes that are associated with disease, right? That makes perfect sense if you actually think about it, right? If you take an example like Alzheimer's, the APOE gene, The ApoE gene is a gene that tends to be associated when people look at longevity. Well, of course, because if you don't have disease, you live longer. It makes perfect sense, right? Again, these things are the same side, are the same coin on opposite sides. And so, by that logic, suddenly, instead of being an adult and saying, oh, Angelina Jolie, it's amazing. She did genetic test. She got a mastectomy. That will save her life, right? Now, Angelina Jolie and you, first listeners, doesn't have to even pass down that BRCA variant in the first place. They actually don't need to pass down any kind of chronic disease, or at least they can reduce the incidence of chronic disease that they pass down to the future child. And so suddenly, instead of the child having to take some sort of medical intervention, which is, don't get me wrong, amazing for if you're an adult, but why as a parent, in my opinion, if you can basically in software in the cloud pick an embryo with a dramatically lower risk for something like Alzheimer's, You are basically helping the invisible language of life, the invisible code of life, make it such that your baby might not get Alzheimer's 50 years from now. I mean, that's pretty amazing. I mean, and think about that again. Think about you're dramatically reducing chronic disease incidence. There's no pain. There's no invasiveness. You're simply in the cloud. You're using our software. You have your, whatever, 5, 6 embryos. Yeah. You can sort and rank them and compare across any chronic disease. If you're undergoing IVF, this is the platform for you. And now you can pick the baby with the lowest disease risk. And so now I've laid out 5, 4 or 5 different applications that are gonna have profound transformation of society. Now, Steven, take a step back. Where do people think genetics is? They think genetics is about genealogy. People still think ancestry is the most important thing. Think about now that gap between where the technology is in the world that I described And what people think it is, that gap—it's disruption. I don't think it's our job to say. I really believe in liberty. I really believe that couples have the right to choose whether they want to engage or not with the technology. One of the things that's really, really, really important to me is. No one should be forced to do genetic tests. No one should be forced to do embryonic selection. I think our job is to educate consumers that it does exist, that it works, that it's sound, that it's great science, and that it's just an amazing opportunity for parents to give their child the best possible start in life. And then it's up to the marketplace, it's up to the consumers, it's up to the couples whether they want to use that technology or not.

There was a few weeks ago, we had the story of baby KJ and, you know, getting a rare genetic disorder cured by gene editing technology. And overwhelmingly, Everyone loved the story. They were like, how amazing this is. Yet there's been some controversy when you guys launched Nucleus Embryo. Why does that gap exist? I just really don't understand how preventing this even before the child has to, you know, stay in hospital for 300 days, how that's not infinitely better than what we had, which is still amazing, the gene editing stuff.

I agree. You make a profound point here, which I agree. First and foremost, what a feat of science. What a feat of engineering. I mean, the fact that you can cure babies with gene editing, I mean, what a marvel of science. That said, that's one tool in the toolkit. If you had used like Nucleus Family, for example, and screened mom and dad, you could have prevented that disease from being passed down in the first place. And so, in other words, I think gene editing is amazing. I think that story is amazing. But also, we need to start leaning into the stack more. Yeah. as society to say, hey, look, we actually don't want to have to use our gene editing tools, right? Because the baby's suffering, right? It's really expensive. This isn't technology that you can just like— I said earlier that millions of babies have genetic diseases. Those genetic diseases can be prevented if mom and dad swab their cheeks, right? And so suddenly you see something interesting where it's like, hey, this technology, you can actually use a combination of this family to flag these rare genetic markers. and then you can do IVF to pick the baby without the disease, right? I agree with you. I think that's pretty non-controversial, right? Because I think it's ultimately up to the parents. The parents have the right to say, I as the mom, I as the dad want to give my child the best start in life. And so I'm going to basically, excuse me. So I'm going to basically pick the baby without the rare hereditary disease because you don't want your baby to have to be in the hospital, God forbid. And hopefully gene editing is only for the cases where you can't prevent in some shape or form. And so I do think there's a bit of a dissonance here I do think though that you're seeing a broader story, and the broader story is that genetics is coming back to the picture. Right. And that's really interesting. You can start seeing how different genetic technologies from sequencing, analyzing, and now editing DNA might eventually converge in the future. And so I think we shouldn't think of this as a gene editing problem or analysis problem or a preconception testing problem. It's all part of the same thing. There's a genetic stack that is forming that I think those who are keen observers of the industry are realizing, and I think is going to probably change society as much as artificial intelligence will, just because we are DNA. We begin from DNA.

Sorry, go ahead.

Yeah, we begin from DNA. That's what we do. So, I mean, that's life's inception. I mean, so if you can understand DNA and start using genetic technology, you can start basically understanding humanity itself at a much more deeper, profound level. Please go ahead.

Yeah, you mentioned AI. You also mentioned you filled 18 notebooks before launching Nucleus. If you were starting and you had O3 Pro today and all the other tools, how, if at all, would that be different?

So this might be an aggressive take I have. I think AI would have helped in that It would've helped support me on my investigative journey. Because one thing to remember is that when you go out on a profoundly deep research project, like what Nucleus began as, I didn't just have to do the curriculum, so to speak, right? I had to make the curriculum, right? I had to say, hey, hey, here are the things I have to study, create that, and then actually study it. You take for granted when you go to school and the teacher's like, all right, topic 1 is this, topic 2 is this, topic 3, and they all build on each other, right? You never have to do that kind of higher order thinking of what is actually the curriculum So what I had to do is I had to make the curriculum and then I had to actually do the curriculum. And that's hard to make the curriculum when you don't even know about the subject. And so AI, I think, would've helped support my investigative efforts. But here, and I think it would've done that very well and I would've been grateful for that tool. But here's the thing, it also could have been a perverse distraction. Let me tell you why. One of the things that I've noticed most is People will always try to take shortcuts. They're always, always trying to take a shortcut. And let's say someone said, I want to go to the gym. Let's say someone said, I want to be an Olympic weightlifter. And the person says, I need advice. How do I become an Olympic weightlifter? You'd say, go to the gym 12 hours every day. Yeah. That's it, right? Go to the gym 12 hours every day. Hopefully have a good coach. But go to the gym 12 hours every day. If you do that, you'll be an Olympic weightlifter. Let's say you said that to 1,000 people. How many people you think, Steven, are going to go to the gym 12 hours a day? Okay. Pretty, pretty, pretty few. Maybe one, right? There was a great chart one time. It showed the 100-day coding challenge, and basically it showed the percentage of people on each day that were still doing it. And the curve is this, and it asymptotes towards zero. In other words, what I'm trying to say is that What someone might do is, of the 1,000 people that you said go to the gym every day who wanted to be a weightlifter, I guarantee you more people would take steroids than would go to the gym every day for 12 hours. Right. Most people wouldn't do anything. They'd be like, ah, go for 2 days, maybe 2 weeks, then they peace out. A portion would just take steroids and be like, oh, look how strong I am. Maybe 1 out of 1,000 who really wanted it would do it. But even then, I'm skeptical because how many Olympic weightlifters are there? It kind of goes back to your earlier question, like, why you? Why not someone else? And so, the thing with AI is it makes things that are actually complex, that require profound investigation, profound thinking. I mean, I've said this on one podcast before, it's not an anecdote I share often, but I would crawl into a ball and think for 3, 4 hours trying to put the statistical frameworks together in my head, right? And that's how much I was in my mind of trying to get the kind of see the matrix, so to speak, in genetics and really develop the intuition to build nucleus. Okay? It was a profound investigative effort. And AI gives the illusion of knowledge because knowledge is now immediate. It's at your fingertips. You feel like you understand, but true understanding is so complex. You usually only— you actually very rarely see it in entrepreneurs. Candidly, you usually see it mostly in scientists, really good scientists. If you talk to a very, very high-class academic, you could see they've built in their mind this sort of what I call intellectual castle, where they can just basically build something up in their mind and deconstruct it and then build it up again and then tell you how each part relates to each everything else. And you can actually do this in statistics. If you go get deep enough in statistics, you see that everything's actually just the same thing, right? And things appear different, but actually it's all just the same thing, right? And you start speaking a new language almost. And I think that AI would've made it easier to someone to get the illusion of knowledge, feel like they understand without really, really, really, really, really, really, really thinking about it in the same way that you might take steroids. And then be as strong as the person who's going to the, you know, lifting weights every single day. But of course, which one's a more enduring strategy? Well, it's the one where you show up every single day. I think that the number one thing that has been most— that is least understood and most omitted was the sincerity and intensity of intellectual reps that was required to start Nucleus. I mean, again, there are days I remember where I would look out my bedroom window 8 hours thinking. I know that sounds very crazy. I don't think people really understand that. I think one day, hopefully, the notebooks that I did become public and then someone could just see the sort of level of obsession I think that was in the notebooks. Because I think, and I see this on Twitter too, there's this problem I think in Silicon Valley sometimes where People just want to launch things. They want to raise money. And once you realize that you can raise money from just coming up with an idea, it short-circuits what is, I think, one of the most profoundly artistic, profoundly deep processes of both building your understanding up to an intellectual frontier and then actually productizing that intellectual frontier. I mean, this is art and it's a shame, I think, to see sometimes that art gets twisted, but actually it's not a shame in a way. And the reason for that is when you actually treat your craft like art, it's sort of like throwing a ball up in the air in that, you know, by the nature of gravity, the ball's gonna come back down. It's just a principle of life. In the same way, I know when someone puts everything into their work, their life, their body, their soul, The world adapts to your will. The world will actually open up for you in a way. And if someone tries to shortcut that process, the world also, in the same way that the ball always comes down, the world knows it. Everybody knows it. The essence of the creation reflects it. And so maybe this is a little bit too woo-woo, Steven. I don't know. I hope it's not too woo-woo. I love it. But for the people who are listening to this podcast, okay, get in the cave. All right, get lost. All right, go down the intellectual rabbit hole. Okay, you're going to start seeing some things. You're going to start maybe going a little bit crazy, but follow that little pull that I said earlier, that pull from God, whatever you want to call it. It doesn't need to be just God, just some greater force. And I think eventually you'll find on the other side, wait a second, you can actually be on the most profound Profound journey of a lifetime.

Kian, I could do this for hours, but I want to be respectful of your time. So we're going to finish with a couple of rapid-fire questions. Sound good?

Yeah, let's do it.

Besides genomics, the other area of biotech I'm most excited about is— I'm meaning Kian.

Artificial womb.

Oh, love it. Besides Nucleus, the startup in biotech I'm most bullish on is—

The startup?

Yes.

How do you define startup?

Non-public company.

I would say one of the foundation model companies, probably OpenAI, because they're probably going to win. I mean, it's kind of a cheat answer because it's like obviously duh, but I just think AI, it's just going to rewrite absolutely everything. I saw in this quick anecdote, I saw that Anduril beat out OpenAI in the list of top companies. And I'm just like, I don't know, OpenAI, it's going to help everything. It's going to help Nuke, it's going to help Anduril. It's sort of just like the thing. It's like the levered thing, right? Do I think AI is actually the thing? No. In the way that transistors are actually the thing? No. Ultimately, I think the application will be more interesting, but I do think it's just so profound and so ubiquitously dominant. But yeah, so yeah, keep going.

A decade from now, the single metric that will best capture how Nucleus genuinely improved human health and changed the world will be?

I think how many— I think how many— either how many lives that we saved and/or how many years we gave back to people. And I think there's ways of measuring it. I think how many years you give back to people is almost better because that's also a proxy for how many lives you saved. If you do that, you could do the other one.

When will we get artificial wombs? Coming soon,

TM. I actually think there's going to be some fun announcements coming out soon from some startups that you guys will see. I think you get artificial wombs in the next 5 to 10 years. I think you get the first kind. I don't think it's going to be like mass production. I think 5 to 10 years is very reasonable. Oh, and by the way, the problem is there's a lot more— it's like, how do you test it is sort of the problem, right?

The top 3 traits I would optimize in my own future child would be?

Oh, this is a great question. You're good. You could ask the questions. Schizophrenic, definitely, because schizophrenia is correlated. If you look at a population study, Higher schizophrenia means they're more likely to be an artist. And I think also entrepreneurs we find who do Nucleus, they tend to be very high schizophrenic. I'm personally in 99th percentile. So that's something that's interesting. And to be clear, schizophrenic disposition does not mean you're going to get schizophrenia, just to be clear. It just means you have a higher chance, relative chance. So one is schizophrenic, definitely. Another one is, I would say, I'm 5'6. I wouldn't mind giving my baby a little bit more inches. Oh yeah, I think I'd get a little bit more height. And the last is definitely, I would want lower, like, Alzheimer's risk because Alzheimer's is so correlated with longevity. I'd really want my baby to be lower Alzheimer's risk.

Second last one, the most valuable biotech company in 2030 will be?

I'd be ashamed. Nucleus, definitely. Can I not name snippets?

I was expecting that answer.

I mean, nothing else. I mean, come on. Yeah.

Last one, uh, a tip to your, your years as a Thiel Fellow. Uh, what's your most heretical belief in biotech?

Hmm, I think you're going to see mass gene editing globally. Maybe it's obvious to say that. I don't know. I don't know if people really talk about this really publicly, but I think you're going to see mass gene editing.

Kian Sadeghi, thank you so much for your time. Thank you so much for what you're building with Nucleus. And I look forward to hearing a lot more about you guys in the future.

Thank you so much.