Curing Age-Related Diseases w Epigenetic Medicines | Lada Nuzhna, General Control

0:00There is this very interesting company that I followed called Isobiotech. They sold to AstraZeneca for like a billion. European company, very small. They went from the idea to human data in like less than four years, which is an insane timeline. The way they did it is they went to China. The investors that used to fund by the companies in Boston or Silicon Valley are now going to China. And so you have to ask yourself, how am I competitive with a nine and six? This is Lada Nuzhna, and she is the founder and CEO of General Control. Do you want to just start off with why are we here in the Redwoods?

0:35Well, you invited me here. We drove two hours to Redwoods. While we were driving here, I did realize there was a little bit of symbolism to this and that trees around us are close to a thousand years old. And I was like, oh, there is a connection here. The interview is about aging. So, yeah. What got you inspired about aging in the first place? I didn't start in biology. I, since my early childhood, was hell-bent on sort of doing physics and figuring out secrets of the universe, answering like very fundamental questions. But like why are we here? What was there before anything? Like can we reconcile quantum mechanics with like general relativity?

1:19And I think at some point when I was in college, I had like a list of random questions that I was like, I want to spend my career answering those and realize that many of them are many Nobel prizes away from being answered. And probably won't be answered within my lifetime. It was sort of like I'm not a person who naturally feels FOMO. I can miss a thousand parties and never notice. But it was the first time I truly felt a FOMO for the future because I realized that the future is this like crazy exciting party and I won't be part of it. um and that was the moment i was like okay um can i stay here for longer um and i didn't know that agent was like a real space because like i think i googled it for the first time when i was a kid she's like can we live forever and there was something about telomeres that popped up which is like a dad theory of aging by now but uh back then that was like the only answer and then i started looking at the space again around 2020, 2021, and realized that there's actually a lot of work being done.

2:25It's still very early stage, but at least there are like real labs in academia working on those things. And it was like, the time is now. If the telomeres like don't work, what kind of path did you decide to go down in the first place? Yeah, I mean, telomeres do work biologically, but it's not the answer for why we age. I think the answer is like there are thousands of reasons and like a messy house can be messy in multiple ways. So there isn't necessarily a cause of aging. It's just that evolution never, like, we never evolved to live to 200 years. There is no reason to keep us around for that long once we've reproduced and have an offspring that can carry on our genes.

3:08But I think, so I started from sort of a founder perspective. I spent a few years just funding early stage research and got to see a lot of science happening across academia, ever since from basic science to clinical trials. My favorite area of research has always been sort of tools and new ways of measuring and editing biology, partially because I realized just like looking at the history of biotechnology, those were the biggest multipliers of progress in bio. It's not studying just one protein that might be causing the disease. It's figuring out how to measure thousands of them at the same time.

3:48Like, I think it's especially obvious when you look at something like Human Genome Project, where we spent several decades and, like, billions of dollars trying to sequence one human genome. Like, just map one human. Yeah. And they would publish every few years, like, it's almost complete now. It's almost complete. and um at some point you're like why is it taking so long and it's because we are using sanger and shotgun sequencing and now we can sequence one human genome like multiple human genomes per day and spend like a few hundred bucks doing that and i kind of think about aging in a similar way in that we can use existing therapeutic modalities small molecules um like existing therapeutic approaches to try to extend lifespan by a bit, or we can just discover new fundamental ways of modulating the biology.

4:36And that's what we are working on. It's a new therapeutic modality that allows to essentially ride the operating system of the cell. Do you want to explain that? Yeah. So where do I start? Every cell in your body has essentially the same DNA. Like if I took your neuron cell and say your liver cell and compare the DNA of the two just a sequence it would be no different you wouldn't be able to tell which cell is which and it's interesting because the same DNA somehow manages to produce like completely different cell type like a brain cell and also like a little muscle or yeah yeah like all of them have this fundamentally the same code um So what makes them different is the epigenome.

5:20So epigenome encodes which genes express in a particular cell. It also encodes how your cell develops over time. And in a way, epigenetics is one of the only ways we know that nature can preset the age of a cell. So one example that is interesting to think about is no kid is born being 30 years old, even if it's conceived by parents who are 30 years old. So everyone who's born is given a set of eggs and sperm cells at their birth that age for several decades before they conceive a baby. Somehow babies are not old, even though they somehow appear from the old cells. And so the way it happens is through epigenetic layers.

6:09So nature figures out how to reset the age of the cell when it gives rise to a new embryo. And a few people figured it out a few decades ago. There was a famous scientist, Nobel Prize winner now, Shinya Yamanaka, who was trying to figure out the factors that makes a cell reset its own age that are now called Yamanaka factors. There's just four proteins that if you express them in the cell, turned it into induced pluripotent stem cell. That somehow, if you compare its epigenetic age, it's much younger than the cell it was derived from. And so that really was the inspiration for the whole field of genetic reprogramming and the idea that we can use epigenetics to control the programs that cells run.

6:59In a way, most of the medicine today works with downstream processes of the cells. Most of the drugs that you go to CVS and grab off the shelf tweak the proteins very transiently and you have to take them every day to keep having the same effect. To get the effect. Yeah. Yeah. Epigenetics can like... We write how it interacts. Yeah, you can write a certain program into the cell at epigenetic layer and your daughter cells would keep having the same program. It very much depends on the gene, but I think the exciting thing about the epigenome is that it allows you to permanently alter the state of the cell and go to something that feels more like a cure and less like a band-aid.

7:45A chronic treatment, yes. so you did something before this which was the impetus grants and I think that's kind of interesting because you didn't like immediately jump into starting a company and you like doled out a whole bunch of money and tried to support a bunch of projects before this what was kind of the logic of doing that in the first place and then at what point did you decide that there was like some path that was clear enough where you're like I can start a company in this and go down that I don't think I was ever a person who optimized for starting a company I know that's sort of like the meme of silicon valley but i actually resisted the meme for a while because i had this idea that aging is the most important thing i can be working on and i want to do whatever i need to do to solve it even if it involves doing the things that i don't like which is like if i need to go to work in the government to make this happen i will go and work in the government so i think i started with that perspective and then started thinking of things where i could contribute that would be would accelerate progress significantly.

8:44And I think when I started, it wasn't clear to me that the company is a way to go. It changed over time, but back then it was clear that the aging field, especially the crazy ideas are just not getting enough funding. If you look at the National Institute of Aging, 60 % of their funding goes towards Alzheimer's, literally just one disease. And we know that if we were to cure Alzheimer's, we wouldn't cure aging so it's just like broken incentive structure like if you want to be working on aging you have to be working on alzheimer's in academia you just don't get funding yeah exactly so when you first started it i think you basically raised it from a bunch of like crypto people which is a hilarious way to i love that crypto saudi arabia how the hell did you get there you know them interested in the first place just reach out i mean it was gradual the first check and was from Juan Bené, God bless his soul, who is like a true visionary in the space of MetaSense.

9:45He was doing a lot of those little projects. And I also was lucky to meet my mentor around the same time. And so we all put it together. And I think after you have some initial traction, it's much easier to propel that forward. so after we gave out the first round of funding like um i think it's like a million bucks or something no it was more than 10 million i think it was around 15 million that the first round was and um after we gave it out um it was easier to go out and say like look at all the things we've done and actually there are more projects like that out there and i think everyone And we obviously heard a lot of positive feedback from academics who would otherwise spend like years trying to write their own grant.

10:36It's kind of like very sad because you are trained as a scientist to go and do cold science. And then you go and start your own lab and you're like, well, actually 70 % of your time right now is writing 70 page grants. You basically spend your entire life optimizing for like being a good researcher. And then the actual success or failure is just being able to raise money. yeah yeah i just submitted my first governmental grant recently and it was like very so like i was like i'm never doing this again like i'll take on any delusion to never experience this process again yeah yeah um and so we made the process much easier it was like two pager like two week response time um obviously everyone was happy about this um and like to put it in perspective what's the typical response time and like what's the typical like is it like 100 pages in six months I would say it's about 70 pages.

11:29And depending on the grant, it can be anywhere from like seven months to like 12 months response time. And after you get a response, it will take even more time to get the actual money. And then you have to do reports. We didn't ask any reports. We're just like, if the person is submitting an ambitious idea, we'll trust them to do their best work. How did you tease out like who was kind of worth trusting in the first place? i mean we made a bunch of mistakes so i didn't know if we figured it out but um it gets easier over time because you see who's getting shit done who's not getting shit done um we also had like an incredible reviewer team and setting that up was like a big chunk of effort with setting up the program because within agent space you kind of have to identify people who are rigorous yet ambitious because some academics are rigorous but then they don't truly have a vision for how the space should look like and then there are people who are rigorous and ambitious but they are so centered around like so focused on their own research that they would only give a positive review to the ideas that is like in their field or actually like if they see someone who is working on the same ideas they're like well actually my lab is working in it so it's a little bit like a horse with blinders on yes exactly and it's they're finding people who like truly care about the progress in the space they realize that this mission is more than they are it's more than their life it's actually like if you if that other competitive lab succeeds you will succeed too and i think that's what's unique about aging versus like any other scientific field is like you really want other people to succeed i mean i imagine that most people that are in aging are generally like interested in it in the first place because they kind of want to live for a very long time and so success equals you get to you know reap the rewards of that yeah yeah exactly yeah okay so how did you decide to go from that you're starting your own company what like what is it yeah i mean there are many many approaches to how people build aging companies there are people who are pursuing the disease there are people who are trying to target aging like in the preventative sense um i think most companies to date largely focused on targeting the disease and that's what we are doing we are essentially developing therapeutic modalities that would make it easier to target multifactorial diseases of aging um the problem with many existing therapeutic modalities is that at best we can do by specific antibodies and target two proteins at the same times that are still extracellular we really can with no idea what to do if thousand proteins are dysregulated like and if you want to target all of them like we can throw multiple pills into your cell but it doesn't really help and like i don't know like how old your parents or if you ever been around old people but like once you've been around a few it's like rarely like once you get to a certain age you don't just have one disease like diabetes or it's like this cascade yeah it's a cascade and you have to take like three pills for each of the diseases that you have and like eventually it's just like a routine of taking like 15 pills every day and don't think it's very sustainable how do you decide which one to go after first yeah it's actually an important distinction we are not working on the partial reprogramming itself which is like just introducing the transcription factors in the cell and like broadly changing the landscape and identity of the cell.

15:00I think it's a promising approach. Our way of targeting is slightly different in that we want to rewrite the gene expression status of specific genes that are obviously driving the state of the disease. To give an example, there is early preclinical work on some epigenetic editors that can permanently suppress your cholesterol. So instead of taking, say, years of statins to keep your LDL cholesterol low, you can just like do one and done suppression of genes that degrades your LDL or receptor and you never get heart attacks. So it's more targeted. We are focusing, so your question was like, which diseases, how do we decide which diseases to go after?

15:45I think because we are focused on the technology validation, our goal is to pick whichever indication makes it easiest for us to demonstrate dramatic effect size um the way people usually go about picking what to target is like having genetic validation um to go in and studying people who have certain mutations in certain genes that makes them prevent them from developing certain disease so there are people who never have high cholesterol doesn't matter how much red meat they eat so i think genetic status is usually like a great asset for figuring out what to target because like that's the only way way you can ever have like human data it's just like by studying people with certain genes who seem to be who seem to never develop dementia or to never develop um i know high cholesterol and whatnot how are you getting like a short feedback loop on figuring out whether or not something is working the interesting thing about targeting disease versus targeting aging is that plus you can run a clinical trial for that with aging we technically haven't figured out how to run a clinical trial like the best we can do right now is like what people are doing with glp1s right now we're like well we know caloric restriction extends lifespan glp1s allow you to calorically restrict the population it seems like glp1s are working for all this like a set of disconnected age-related diseases i think li lily is now lily is in a trial like testing glp1s and alzheimer's which is like how is this related you're just losing weight and so the way people go about approving aging drugs right now it's like we'll pick a set of diseases we'll run trials for each of them and then like if the drug delays inside of all those diseases at the same time that might be an aging drug that's obviously inefficient um each trial takes years years 100 millions of dollars um the problem is we just don't know how to measure aging like we can measure if we die or but that takes years um and also by the time that you actually like get the result you don't want to know like you don't want to go so far down the road that you just don't even apply this to yourself yeah i mean yeah right it's like if you have a disease there is nothing to lose like if you have glioblastoma you just like you'll enroll in any trials that would have you or like if you have alzheimer's um it's like the neural link trials where people are just taking them or they're they're you're implanting these things because they literally can't move anything and you can like play with your kids again yeah yeah like you're willing to take that bad because the alternative is actually not that great with aging like that happens over decades and for most of that time you're actually like a semi-healthy person so whatever first aging drugs that we develop it has to be like extra safe um and for that reason it will probably have like a very small effect size because the bar for safety has to be so high yes exactly yeah like I mean even Norgia with GLP-1s in the clinical trials is kind of like out there like I don't know like if we can give this drug to many people so were there pathways that you were considering going down but because the safety is maybe like more dubious or not as obvious you just kind of had to decide no I mean it's different for us because we are a new therapeutic modality so every time you work with the new therapeutic modality is a safety slightly different so you have to pursue the stage of a disease so severe where you're technically one of the only options um that's why i said we sort of have like several camps of aging companies some that are making it easier to solve a disease or making it easier to discover targets of aging um making it easier to replace whole tissues and then companies that and those are targets of the disease and then we have companies that are targeting aging or preventing aging that actually like less ambitious like bioengineering wise often working with like existing drugs but taking on the risk of sort of being the first company to run the aging trial and there are a few of those like one of them i don't know if you know celine halua working on loyal she is sort of uh building out that path with fda to run the first aging trial for dogs i think they're already running the trial they might even have the data come out soon are they not fda approved already because i thought they had already gone through that process i think there was an approved safety and they're now focusing on efficacy but yeah she's uh i think it's a visionary company but celine would tell you herself that like they can't they probably wouldn't be able to do it with gene therapy because gene therapy has all kinds of like question marks and uh it only makes sense to applies at in severe cases how long would you want to leave how long would i want to live there's this weird dynamic where the people i don't know if i've ever met someone that was well-adjusted and had like they were waking up in the morning and working on something that they generally cared about and they ever wanted to die and so i think well does he want to die yeah Yeah, Elon doesn't believe in longevity.

21:01Do you think he actually doesn't? Or do you think that that's just... He was arguing, I think, with David Sinclair at some point on Twitter. I might be misremembering something, but... I think it's... He lives a death life, so... Yeah, with him in particular, I totally understand him saying that. But then if you look at his actions, it doesn't, you know, he's, like, trying to create super intelligence and then also trying to, like, make it so that you can upload your brain into a computer. you know through neural link or you know radically change how humans interact with the world yeah and i don't i think that maybe 55 or 60 year old elon feels that way but i don't know that elon is going to want to die at 80 yeah there is no age at which you're like even if you're the person who doesn't believe in like immortality or like limited to 100 there is no like any day you wake up someone asks you like are you ready to die today the answer is not today ever yeah it's just that continual loop of like you know what do you say the god of death just not today yeah never so i don't i don't i don't know um i don't i don't think i want to die do you want to die no yeah from like a business building perspective you are trying to keep your team incredibly small um and like agile how are you deciding you know to hire even the first person yeah i think it's like i don't know how it is for other industries but it's impossible to be building like a big haunted biotech company in at this time because of how fast and enabled china is it just doesn't make sense financially for any receipt to put money into u.s but a company that raised 200 million it's just being very inefficient and i think especially in the field of science before we got started there was a whole graveyard of companies that were just raising absurd amounts of money and just spending a lot of time on science and that i think is like big mind trap for scientists and that they just love science they love like exploring things and like doing things better but never continual research but never actually producing something there are companies that raised 200 million spent like six years developing something and never developed a drug and pushed it to the clinic China can do that like with a few million dollars and a few people wait so okay what is what is the typical process for like getting a drug you know approved or some therapy approved in China versus the US like why can China do it with literally one what is that 40th the capital yeah it actually doesn't doesn't really make sense to approve drugs in China, even for Chinese people, they are coming to run trials here.

23:43What makes more sense is get into human data as fast as you can. Because before you have human data, you literally have no value as a company. Your drug might work, might not work. You might have amazing efficacy in mice, but we know that like a small fraction of things that work in mice actually work in humans. And so being able to get to the answer of whether your drug is safe in humans is like, if you can do it as cheaply as possible, you just like reach the inflection point where people are willing to fund you. Like after you have that safety human data, you suddenly have a bunch of pharma partners.

24:23You have ways to exit the company after phase one. Many startups actually do that. It's like very few startups actually see the drug development journey end to end because. They just exit early for like a billion dollars or something? Yeah. After phase one, you can exit at a billion dollar valuation. There is like this very interesting company that I followed for a few years called EzoBiotech. So it sold to AstraZeneca earlier this year for like a billion. European company, very small. They raised like, I think, less than 50 million. Very tiny company. And with that money, they went from the idea to human data in like less than four years, which is an insane timeline.

25:04The way they did it is they went to China. And now that companies that bought them AstraZeneca, they are using that human data to go and run trials in the US. It actually, I mentioned that it really doesn't make sense to prove drugs in China because China is just like not a big market. it. They're big by volume, but the willingness to pay a higher price for drugs is much higher in the US. So like every other company in the world would come to the US to run their final clinical trial. I like read one of the things that you wrote earlier this morning, and you were actually mentioning that there's probably like a bunch of rare diseases or things that, you know, you could go create a drug for it.

25:44But I think like the US has like made it illegal to be profitable on those. Oh, no, it's no, actually like 50 % of drugs approved to this day are for rare diseases like every year because you as just created financial incentives that makes it easier to develop drugs for diseases that have like fewer than a thousand patients and for diseases that are like very big. um what is i think what you're referring to is the idea the sort of compassionate use trials where um say a patient comes they have some rare disease or like they have parkinson it might be a common disease too uh and they collaborate with the lab to self-fund um a trial in that academic lab or hospital and it's usually like end of one trials i i don't know um you heard about like one of the first gene edited babies earlier this year baby kj that was a compassionate use trial where a group of academics gathered to develop a gene editor for this one baby but with those it's basically like you can't profit from that so it's not a scalable model for a startup um yeah other than that people are developing drugs for rare indications all the time it's very hard to make money on that yeah a few people did but what was it like growing up in ukraine i think my childhood in ukraine was probably different from other childhoods in ukraine because i did grow up in the eastern ukraine um meaning that many people were started 2022 for us were started back in 2014 um i think it's one of those things that if it didn't happen I don't know if I would be sitting here because it introduced enough of good chaos in my life such that I just like got in a way detached from the routine and like normal childhood pretty early on.

27:42I was living alone since I was 14. Really? Yeah. What? Why? Many circumstances. this i mean um when the war started my school got shut the very same same year and i was living in small towns hometown so there were no schools left you just got bombed a rubble uh it wasn't a rubble but it was not operational for basically a whole time after that and they never reopened it um right now my hometown is a rubble um what was taken over by russia i think 2024 in february It was for a long time like a gray zone right the border where most of the battles happened But yeah right now it's almost inexistent But back when I was 14 just that school got shut down there weren't many schools In that small town so I had to move somewhere where I could get education And my parents didn't really want to move They were pretty attached to the place Yeah yeah yeah What makes sense in like Bayeux what makes sense to back and like to start in the first place and what is just like absolutely you're throwing money away and like lighting on fire yeah I mean I think like any crazy mega rounds without the clear side to product is a waste of money we know that like starting the company was a billion dollars in funding is almost never a good idea it doesn't matter how many Nobel Prize winners you put you on their board I think biggest outcomes for any investor is like a small company that's moving fast, like elsewhere, really.

29:16But in biotech now, especially, many of the investors that used to fund biotech companies in Boston or Silicon Valley are now going to China. And so you have to ask yourself, how am I competitive with the 9 and 6? Chinese teams that are stamping these drugs. I think people used to cope with this by saying that, well, at least US is innovative. That's where China is stealing from. China can be creative. They can produce their own drugs. I don't think it's true at all. I think we are now starting to see absolutely new science come out of Chinese labs that never been published in the yet before. So it's clear not the execution speed.

30:03So far, it's still sort of the creativity of American biotech. That's why I personally prefer to work on a new therapeutic modality because if it works, it's a big deal. If I were to work on an antibody for a known target, there are like thousands of Chinese biotechs doing the same thing. There are like 300 GLP-1 companies out there in China. Really? Yeah. But just a slightly better version of GLP-1s. it's interesting because i think glp1 starting like a glp1 companies company now is sort of a biotech version of a vibes app for like a wrapper like okay you actually can be working on a deep tech biotech like complicated company and still be doing meaningless things or like things that have little counterfactual impact that's a better way to say it yeah okay so how are you thinking about building your own company and like actually shipping that first therapeutic that's not going to have like a massive impact it'll be like directionally correct yeah um we are at animal study stage now we are testing out drugs in mice our next stage is doing first in human trials um i think the cheapest way of doing it is going to china for any therapeutic modality why is that um china was actually like pretty slow um in terms of their inds and drug approvals before uh they had two waves of deregulation in the past say like 10 years which allowed you to essentially get your ind package which is like clinical trial application package approved much sooner um it's also true that in china you can do an iat which is investigator initiated trial where you approach a doctor in a particular hospital and ask them to co-author uh the first in human clinical study it's small scale um it doesn't give you an opportunity to go and uh like initiate phase two in united states after but it gives you human data which is like why is human data so important?

32:18Because that's where most of the sense fail. They largely fail at efficacy stage, which is phase two. Phase one has, depending on indication, has approximately like 50 % failure rate, which is actually, I think, is not as bad as like software companies. How many startups are created every year? And then like how many flame out? Yeah, I don't know. Many. It's interesting. There are more biotech, there are more drugs generating billion dollars per year than there are software companies doing the same. Really? Yeah. Is it just one of those situations where as soon as you have a drug that is successful, it just gets sold to one of the big guys?

32:56And so it just goes into their portfolio? Not even that. You don't even need to approve a drug. Most startups never approve the drug. Most startups... Just get the efficacy data. not in advocacy sometimes you for certain targets in our case we know that if our drug can target this target and if drugs are safe we know it will work because if the target is genetically validated and someone targeted before um it's like not a big jump to make um many companies just show safety in phase one and then partner with a pharma to exit after or okay partner on the asset and then continue developing and like on on like a personal side um what do you do day to day to kind of increase the likelihood that you do live for a long time even outside of just taking a bunch of random drugs yeah i've been taking a bunch of random drugs by the way um i do intermittent fasting have been doing it for many years now i think it's just like an easier thing to do like once you get into it you're actually like not hungry most of the time um except when you want to doordash a burger into the redwoods which apparently the cellular just out here doesn't work yes um yeah while you're trying to build this company who are the role models that you've seen in the past that have built similar companies to the thing that you're trying to create and like what are you learning from them or taking why i love this question um i love this question because i feel like not many people in the area in silicon valley in general know about the hero super biotech but to me one of the reasons Bayer is so great is because partially biotech industry was born here with the birth of Genentech so the two people that I would probably look up to the most is Bob Swanson founder of Genentech and John Maragonore founder of Alnylin both of them worked on thematically something similar to what I'm trying to do which is develop a therapeutic modality in case of genotex that was the first recombinant proteins um bob swanson amazing guy um he was working at kleiner perkins as a vc didn't have a phd there was no biotech industry because then no biotech vcs no biotech companies he gets fired from his job at kleiner perkins right around the age of 26 27 so by the age of 27 he hasn't done truly much and then he come across this paper from stanley cohen and herbert boyer on cloning and cloning is this idea of like can we take a particular protein and make many copies of it like produce it at scale in bacteria by inserting the gene into bacteria and then outgrowing it with a bacteria um he came across this paper and he's like holy shit this is a big deal this will be big um he called males not even called emails he called mails a red boyer shows up in his lap her boy doesn't want to talk to him he's like we should start a company around this nobody like company existed before that they were like big pharma somewhere in the europe that were working on dice and heroin this was like in the 70s 80s yeah yeah like there weren't many abc funds back then um there was not there was not like a whole lot of risk capital and i know i know that like in the east especially in the 90s i think there was like a massive biotech boom yeah right like a bunch of companies were genentech was part of the birth uh was it just like right after that that a bunch of those other companies were started because of the genentech success there was in a way a race um when genentech started to clone the first human insulin so before genentech managed to right now you buy insulin that has been produced at scale in this like huge tanks before what we would do if you have diabetes we would slaughter 50 pigs per year to extract insulin from their pancreases for one patient per year.

37:01It wasn't very scalable. So what Bob Swanson saw back then is that we can use this cloning method to produce protein at scale. And he somehow managed to convince this academic to work with him. they got a lot of criticism back then because it was kind of considered bad taste to try to for for pure academics and scientists to go and try to make money from their science they got a lot of bad press they didn't raise a lot of money but their execution speed was insane um and again bob swanson wasn't a phd he wasn't like a legendary scientist he was just some dude who got fired from his job and then wrote the paper um so i do yeah i do really look up to him so are you how are you thinking about having like really really fast execution speed even if you're going to be working in something where the feedback loops are super long like how do you do that i think you need to know the direction you're going with from the get go many people start with a new technology many crispers come started with like crisper it just works without knowing where to apply it like knowing that it might be useful for genetic disease but not finding the right target to apply it to before we started we already knew like the direction that will take this technology it was super clear i think that saved us probably years because by the time we were raising our first round um we literally heard feedback that like what you guys figured out early on is what many people figure out like once they have like years of data and then this turn thinking about their clinical strategy like i think because it's one of those examples where it's like tough times create strong men uh tough biotech markets create amazing biotech companies um and you kind of have to be more disciplined with your execution not to like spread yourself thing in multiple directions just like figure out the direction you want to go that and execute and go for it okay yeah not i i think one big thing is like not taking on a lot of scientific risk people what do you mean by that um i generally split the risk in by in building biotech company into engineering and scientific i would always prefer the engineering risk to scientific risk the question with scientific risk is like the unknown unknown like if i target the sport and will it cure this disease like i never want to take that type of risk like that is the thing that costs like a billion dollars or whatever?

39:30I mean, even if you know the things that you want to target, it would still cost you like$2 billion to approve of drugs. That's the average right now. But I don't think any of the best-selling drugs of all time, we're trying to do truly new biology. They usually targeted the proteins that had years of papers published around it. Like some examples of best-selling drugs of all time is like cumira and keytruda those were like non-proteins and they weren't the first ones to target those proteins so i never want to work with new biology i think biological and scientific risk is a dumb risk unless you have like billions in capital and just like you want to do crazy lots of crazy things and infinite runway which is like probably like a cool company to build to like eventually i want to get to a place where i take on way more risk but with a small startup you kind of need to know that the first thing that you try will work.

40:25Or else you never get to the stage where you have, like, the infinite runway to go tackle all that other stuff. Yeah, yeah, exactly. And so with engineering risk, the question is, like, can you get your molecule to the set of properties that would allow it to be a drug? And that's much easier to address because many people addressed it multiple times before. We know how to engineer proteins. We know how to do high-surput screens. Like, that's a much easier thing to do. So what are the different stages of your company going to be? Like walk me through the next like five years and what are you going to be doing?

40:57Yeah. So we've existed for almost two years now. Our first year was focused on developing the technology, optimizing it, testing it largely in cell lines and dishes and formulating it to get it to the stage where we can dose mice with us and show that it's efficacious in mice, which is where we're now. Once you show that it works in mice, you do the final few tweaks to make sure that your molecule is as specific as it can be. It's safe. It can be at the lowest possible dose so that you're not overdosing your humans. You test it in monkeys and usually prepare an IND package. What's an IND package?

41:42The IND-enabling study is a study that you submit to FDA to ask them to run your phase one clinical trial. It usually includes monkey data and mice data, depending on your indication. It includes a batch of drug manufactured at scale, safe for human use, which has all kinds of its own restrictions. So once we have our monkey data, that's the package we will be submitting. And after that, autosoresis with human data. And I know you said that you're going to do monkeys here in the U.S. and then humans in China. No, actually, we might do monkeys in China, too. But the calculus that I was giving you is sort of if you compare the cost of monkey study in the U.S.

42:28and the cost of human clinical trial in China, monkey study in the U.S. is somehow more expensive than running a human clinical trial in China. So it's like a million five or two million dollars? Very much depends on sort of the type of drug. Like biologics are more expensive than small molecules. But yeah, you can run like a 10 people trial with AAT in China for like less than two million dollars. And what are you going to be looking for when you do those like first monkey studies? What data are you like expecting or like hoping for? I don't know how much I can disclose about our programs, but usually with IND packages largely safety so it's less like even on the like efficacious side it's more just like does this monkey die or what?

43:15people do efficacy studies in monkeys specifically it depends on the disease because some monkeys might not have your disease many of the efficacy studies are done in mice actually okay this is my like the biggest pain of the bio attack it's like that we are doing efficacy studies in mice and i think it's actually like the biggest thing that slows aging field down um is almost like counterproductive because it's just the wrong thing like you can do something in mice and it works and then it just doesn't translate to humans well it's even worse than that like say you're trying to take an alzheimer's drug to humans you test it in mice mice doesn't develop alzheimer's what are you you can publish many papers on curing alzheimer's in mice mice just doesn't have Alzheimer's.

44:03You create an artificial model where you're like, let's induce, like overexpress this toxic proteins from human in mice brain and pretend that it's Alzheimer's. No, it's thousands of times at the same time. One protein will never recapitulate it. It's true for basically every other disease, age-related disease that humans have. Like mice largely die of cancer. They don't die of heart attacks. It's like, so if you, if anything, like if you find something that cures cancer, you can probably very drastically extend lifespan in mice. But cancer is just one of the causes of death in humans. What are the biggest causes of death in humans?

44:42Depends on the country. In the U.S., it's still cardiovascular disease, which is actually kind of interesting because I think our generation would be the first generation not to die of cardiovascular disease. It really doesn't make sense to me that high cholesterol will be an issue like 30 years from now even if no more progress will be made imagine like we are like totally failing in research and development um we just have so many solutions not to have including gilp ones um earlier this year li lily one of the biggest farmers of all time like i love those guys they um bought a gene editor that permanently lowers your cholesterol um very squeaky clean safety we'll see where they'll take it it's still in phase one clinical trials but like 20 years from now this is just going to kind of be a solved problem well it depends on how much um tolerance you have for doing something like a gene editor i don't know if you would be willing to do a gene editor i think yeah it's yes yeah like why not you can why would you decide to like pop statins for the rest of your life if you can gene edit your liver to stop cranking out ldl how do the incentives work because if a company can just like edit your genes and suddenly you don't have any problem with statins isn't like statins a massive multi-billion dollar industry and why would someone invest in figuring out how to solve it permanently if yeah i mean statins no longer make that much money because they're generic so it's like a very cheap pill to manufacture and everyone can manufacture it but you're right that there is like a broken incentive structure about how to pay for drugs that cure the disease.

46:25I think it's especially broken in the US because you have a multi-payer system and there is no reason for anyone to prevent the disease that occurs after you're 65 because after 65, who pays for your drugs? That's Medicare. Before that, you rotate your insurance every few years. So why would one insurer pay for your one and done drug if you'll change the insurance and they'll never reap the benefits of you being healthy. It's not a solved problem. I don't know what's a solution here. I suspect Lily is thinking about possible solutions if they bought a one-and-done drug for high cholesterol. But eventually we do have to figure it out because I can't imagine an aging drug being approved and widely used and being commercially successful in this type of system.

47:17Unless people pay out of pocket, which is probably a working model too. like direct to consumer, which is, I used to think it's weird. I think it's becoming more popular now with like Lili Direct, where they sell GLP-1s direct to consumer instead of... Like the HIMSS model? Yeah, HIMSS, yeah. When you're thinking like day-to-day, when you wake up in the morning, what are you spending your time on? It changed over time. often it's um unfortunately a lot of it is like arguing with vendors and what's that been like yeah i mean biology is annoying it's like the worst discipline for an impatient person to be in because you just can't make your cells grow faster there's like a limit to how many times cells divide per unit of time so you can't just like screw me at your cells and make them divide or like you can't accelerate your experiment because there's like a biological bottleneck on time.

48:16And same with vendors. I think I'm known as a person who could just like very good arguing with them. I think it's kind of like my talent. What do those typical arguments look like? Make the cell grow faster. This study costs 100K. Like, well, can we make it 10K? Like, well, that's the cost of mine. I was like, well, we'll do many more studies with you. can we make it 10k? They're like, yes. Or we'll ship it to you next week. They're like, no, we need it this week. Now can we ship? And I'm sure it's like true for many other deep tech industries where you're like, where are my parts? The same is true for me.

48:55It's like, where are my parts? Where's my mRNA? So is the general like pace in biotech just extremely slow? And you're kind of like at every point in the cycle or every action that you're taking is basically just trying to speed it up by a few days on every little interaction. and like decrease cost yeah yeah um doesn't seem to be too slow in china i think it's fundamentally that the biotech industry in the united states became complacent what do you mean by that like what does complacency look like um not rushing to develop a drug for your patients um spending too much time optimizing the technology i think crisper companies especially has been guilty of that.