Reprogramming Cancer And Competing With China With Earli's Cyriac Roeding

0:06Welcome back to the business of biotech. I'm your host, Ben Comer, chief editor at Life Science Leader. And today I'm speaking with Cyriac Roeding, a serial entrepreneur and investor in the fields of technology, AI and science broadly. He built CBS's mobile unit and as entrepreneur in residence at Kleiner Perkins, he co-founded Shopkick, a shopping app sold to a Korean telecoms company for$250 million. He's now CEO and co-founder at Early, a tech bio company that uses genetic constructs to turn cancer cells against themselves, which I'll get him to explain. Syriac is a keen observer of technological trends and startups and predicted in 2016 that China would become Silicon Valley's biggest rival.

0:54He's an investor in a bunch of companies, including OpenAI and venture capital funds through his family office, Roading Ventures. And I'm excited to have Syriac on the show today for two primary purposes, to talk about early story in cancer and what it takes to make a startup succeed. And second, what China's five-year plan in biotech means for biotech companies everywhere else. Syriac, thank you so much for being here.

1:24Cyriac Roeding: Pleasure to be here. I'm looking forward to the conversation. Me too. And I want to start off with a couple of background questions, as we do here on the business of biotech. I read in your bio, Syriac, that you sold your first computer program in Germany when you were 15 years old. What was that program? And is that, you know, when you were first bit by the entrepreneurial bug or did that come later? Well, actually, that probably came before then. But I was working for this newspaper publishing house doing my spring break, I think, at my school. And I was assigned this really, it was my first job.

2:07Cyriac Roeding: And I was assigned this really tedious job of looking whether in a newspaper, whether an ad had appeared or not. And if so, you had to scratch it out. And I was sitting there the first day doing this for eight hours, a stack of paper. And at the end of the first day, I was ready to jump off a wall. And I thought, well, that would probably be a bad way to start the first job. So I went through with it for three weeks. And I thought, wow, man, if this is how it is to go to work, I'd rather go back to school. First time I wanted to do that. And I went to my boss and I said, why don't you automate this?

2:52Cyriac Roeding: And he said, what do you mean automate this? Mind you, this is like stone ages of computing. And he didn't really know. And I said, why don't you use computers to do this whole thing? So then a few months later, the phone rings and he calls me and he says, why don't you, you know, I remember you said something about automation. I said, yeah, sure. He said, why don't you come back and do that? So I picked up my own computer, went there and started coding. And by the end of the summer, I had written the code for him and sold the program to him. And I guess I basically got rid of my own job. Nobody ever got hired for that again.

3:33Well, yeah, somebody was probably thankful that they didn't have to do that job after you. So you must have been into coding at a pretty early age. You kind of took to computers early on.

3:42Cyriac Roeding: Yeah, I think I started coding at like 11, teaching myself how to do it. And I found it fascinating that you could literally take control of a machine and tell it exactly what to do. And then it would spit out exactly what you asked it to do over and over again. and and that was my first thing that really fascinated me and the other thing that i found to this day still absolutely impressive was this idea there was this like small robot self-made produced out of little pieces of equipment at my school and a computer attached to it and it couldn't do much, but you could program it how to move. And I will never forget this.

4:29Cyriac Roeding: When I first saw this and I started using it and I started coding it, the idea that I could use software to manipulate the actual real world, the world we live in, that a piece of code would change how the real world would look like because something was actually moving and being moved, that never left me and to this day everything i've done since in my startups has been on the intersection of the physical world of atoms and the digital world of bits and where the two meet that's why i'm at home interesting um i i also read that in college you were a talk show host and a reporter and i was curious you know what your beat was like what you talked about Well, I actually love the radio and I also like media in general.

5:27Cyriac Roeding: So when I was in college, I could not take the idea that I would walk in in the morning when it was dark and I walked out in the evening when it was dark again. It was like, what the heck am I doing? so there was no attendance requirements at my college in Germany so I decided to do this offline sometime and rather work nights at a radio station and first I was a reporter who was literally driving around reporting from the life from the road then I did reporting on political topics and did stories about them and then after a while I literally became a a DJ, a host at night, a radio host. And I was supposed to only do a music show.

6:12Cyriac Roeding: But over time, you know, I turned this into a talk show more and more with music interruptions. And I ended up having my own reporters out on the street as well, talking to people. And it became a very interesting combination. And, you know, for a while, I flew under the radar that I actually changed the whole format of the show. at some point I had to answer to my bosses about it. But it was a great it was a great experience. Well, I imagine all of that experience in storytelling is helpful, right, as an entrepreneur and as an investor. It's something that I don't talk about a lot on this podcast.

6:51But, you know, as someone who's worked in media, my entire professional career, you know, the importance of storytelling, regardless of whether it's reporting on news, talking about a company, talking about a product, whatever it is, it's the narrative. It's a very powerful form. And people who are good at telling stories, I think it's one of those tools for success. I mean, have you found that to be true?

7:18Cyriac Roeding: That is absolutely true. I just think we need to clarify something for the listeners. Storytelling doesn't mean you make things up. You can. You can tell a story that's completely fictional, but you can also tell a story completely based on facts. But your job is to connect the dots and explain it in a way that first it can be understood, but beyond that, it's actually, I don't know, do you know the three stages of actually getting people fully convinced of something? No, I don't think I do. So there are three levels, right? The first one is basically it's called persuasion where you basically tell somebody, hey, can you just do this?

8:05Cyriac Roeding: And I'm just going to do it because I kind of owe you something or I think, you know, I just want to be nice to you. But you're not really convinced of it. The second level is conviction. This is where your brain, your mind tells you, okay, I think this makes a lot of sense. I should do this. But the third level is enrollment. And enrollment means both your mind and your heart are fully engaged and are bought in. And when you reach that, anything becomes possible. The walls tumble and people become engaged and they actually take ownership of the thought of the mission. That's what we're in the business of doing when we are building something.

8:58When you truly want to build and you don't want to build it all alone by yourself,

9:04Cyriac Roeding: it's absolutely critical to not just persuade or convince people. You need to enroll them. And once you do that, some really powerful forces begin to work where you don't have to be officially in charge anymore. People take ownership. They run. And that's beautiful to see. And I think what we call storytelling is essentially a way to enroll people, but not by making stuff up, especially in biotech that's really important. We can't just make stuff up. Everything has to be based and grounded in facts, in hypotheses that are declared as such, and in results accordingly. And once you have that, you can then combine it into a flow that people understand, not only intellectually, but also with their minds and their hearts and bring that together and get people on the mission.

10:00Cyriac Roeding: And then you are really on to something. That makes a lot of sense to me. It seems like the emotional aspect or the heart part would be the most difficult. You know, you can get the rational part, but how do you get the heart in? Yeah. I guess it depends. Yeah. I think the heart comes from recognizing that regardless whoever is listening or watching you, they're all humans like you and me. Yeah. I always find it amazing that people, when they talk to really important people, and there's all this, like, the deference, and all of that is building up walls. But when you break down the walls, we're just humans.

10:45Cyriac Roeding: We're just sitting in front of each other. We're talking with each other. You have your story, your personal story. And I'm sure there's a lot of interesting things that happened in your life. And when you understand, believe that every person has something really interesting to tell and to share, then there are a lot of connection points, how you can actually build a bridge into their world. Cancer is one of those, unfortunately. Well, let's talk about early. Biotech can be a turnoff, I think, for some Silicon Valley investors, primarily due to the long R &D timelines, regulations. Before co-founding early, did you have previous experiences with biotech or with the life sciences sector?

11:34Absolutely none. None. Okay. Well, maybe you can tell me the story then of how you got connected with the late Dr. Sam Gammer at Stanford and how that turned into early.

11:49Cyriac Roeding: Well, by background, I'm an industrial engineer. I'm not a biologist and I'm not a scientist. So what happened? I told you before, I love to be on the intersection of the physical atom and the digital bit, right? Right. And my last company did that in mobile. And mobile is essentially like a mobile phone is like a digital overlay on top of the real world. And that company was doing that in the retail world. And it was super interesting from that point of view. So then the next company I wanted to build was on the intersection of biology and software, also known as AI. And that intersection, I believe, was going to change fundamentally how we live.

12:35Cyriac Roeding: Because if you think about AI meeting the real world, this is called physical AI. And physical AI comes in two forms. One that everybody knows and thinks of immediately, which is called robotics. robots are essentially the non-living atom combining with the digital bit with AI and then there is a second R and that's the living atom combining with the digital bit and that's called biology meets AI I call it bio AI and bio AI is an intersection of to me the ultimate frontier it's the living atom it's our own bodies and when you can start manipulating that world, you're talking about fundamental changes to how we treat diseases.

13:27Cyriac Roeding: Perhaps one day we will be able to treat many diseases by using software. And that's how was my first premise. So now, then I was looking for my next thing to do in that field. And I was looking at many ideas. I think it was over 200 in total. I have a very dense filter when it comes to ideas because most of them are either features or they're products, but they're not company ideas. So finding a company idea is rare. I also believe there is an ocean of good ideas out there, but there's a dearth of outstanding ones, and only outstanding ideas are worth pursuing. It's very hard to find. So what happened was I looked everywhere, and since I live only five miles from Stanford University, I started stumbling around the campus.

14:13Cyriac Roeding: And I talked to all these scientists there. I talked to over 100 of them. I think. And almost every single one was telling me they were working on the world's most important idea. Sure. By definition, 99 out of 100 were wrong or all of all 100 were wrong, right? Right. The problem was I didn't know which one was which because I'm not a scientist. So that was very frustrating. I could probably tell the difference between a bad idea and a good idea but i couldn't tell the difference between a good idea and an outstanding idea and only outstanding ones are worth pursuing so then i got very lucky i was living with my wife and my at the time tiny micro children in a another person's house that we had rented because our own house was being remodeled.

15:12Cyriac Roeding: And so we got their subscription magazines and all the stuff that they usually order, but they weren't there. So Thanksgiving Day comes around. And I was actually at the time, very disappointed with myself because I had spent the whole year looking for my next thing and I still hadn't found it. And when Thanksgiving comes around, it's usually the end of the year in the US, there's not much happening anymore. So I thought literally I was sitting there thinking, I absolutely didn't do it. The year's over and I have nothing. And while I was sitting there thinking that, the door opens and my wife Angel comes in with a magazine in her hand.

15:51Cyriac Roeding: She says, Syriac, this just came. I think you should look at this. She hands me the magazine. And it was from Stanford University, a medical school. and it was the cover story which was called and yet you try and that story was about sam gambier one of the world's most preeminent early cancer detection and treatment experts in the world at stanford university and about how he lost his only child to cancer at age 16. And I read this story and I didn't know him, but I felt a gripping sense of grief just reading this. But I was also very inspired by the work he was doing on early cancer detection and treatment, including his son who died, by the way, who helped him in the lab at age 15.

16:52Cyriac Roeding: That's how brilliant he was. so i made a decision to send him a cold email that day and i said something along the lines of i can only imagine how hard this day is for you today this holiday but i read your story i was very touched but i was also very inspired by the work you're doing I'm not a scientist. I'm not a biologist. I'm a serial entrepreneur. I want to build my next company. I'd like to meet you. Two months later, he finally found time to meet with me. On a Saturday morning at a small restaurant in Portola Valley, which is where I live. It's like 4 ,000 people close to Palo Alto and Stanford, right?

17:39Cyriac Roeding: Well, it turns out he also lived in Portola Valley, and we had no idea. We were neighbors three minutes away from each other. Oh, wow. So my first question, and this gets back to your question. My first question to Sam was, I'm not fishing for compliments when I ask you this. Should someone with my background or better lack thereof bother the world of biology with my presence? And he looked at me and he said, I have two answers for you. The first answer is the world of biology needs more people like you, not fewer people like you. We have a lot of experts and very few generalists. We have even fewer people who know how to build a startup company.

18:24Cyriac Roeding: And the second part of the answer is the world of biology will always find a way to screw you over. It will take longer than you want, and it will be harder than you want. I took the second part of the answer as the cost of doing business and kept moving. And before I knew it, every other Saturday, I was sitting at his kitchen table in his own house where he was trying to teach me biology, largely in vain, but I give him credit for trying it. And then he started introducing me to a lot of people. And I met all these scientists. And unfortunately, the odds of finding the right person and the right idea combined is like probably one out of 10 ,000 times one out of 10 ,000.

19:04Cyriac Roeding: You can do the math. so after three months I went back to Sam and I said I'm so sorry Sam I still don't have it may I ask you a simple question you have seen hundreds of ideas in your own lab outside of your own lab probably just in the last year alone which one has the highest potential of all and he looked at me in his scientist underselling type of way and he said there is this one idea that i believe has some real potential and that became early wow okay and i you know getting back to to ai it's a major tool that early uses i think to create these genetic switches that that turn cancer cells into um immune therapy factories so to speak.

19:59Can you describe what that process looks like, how AI is used, and then how the genetic constructs work when they're delivered to cancer cells with the understanding that you're not a scientist, neither am I. So we can keep it high level. But give me a sense of how AI is applied and how the eventual candidate that I assume you'll be moving into clinical trials will actually work. Great.

20:28Cyriac Roeding: So we are two non-biotech people talking biotech. That's awesome. Exactly. Yeah. Okay. So let me first explain why we're doing what we're doing. What are we trying to accomplish here? Because who cares what we do when there's no real problem to solve? Sure. The main problem we're trying to attack is what we believe is the number one problem of all cancer drugs, which is when they go into the body, they cause major toxicities. These toxicities, also known as side effects, are not just uncomfortable for patients, like hair falling out and all of these things, but they're actually dose limiting. It means you can't give the patient as much of the drug as you actually want to because there are too many side effects.

21:13Cyriac Roeding: and these are almost cynically called on target off tumor effects it means your drug hits its target but unfortunately your target is not just on the cancer cell it's also on healthy cells and that drives toxicities you don't want at the same time what happens is you inject the drug it goes everywhere in your body you have five liters of blood volume and by the time your drug reaches the tumor, there's this much left of the initial drug and this much elsewhere in the body where you really don't want it. So how could you change the whole game? What if you could flip it? What if you could no longer try to target it to tumors and hope for the best that it really only activates there.

22:02Cyriac Roeding: What if you could inject it but it's only actually produced, made into a drug where it is actually needed? What if the drug could be produced in the tumor by the tumor against the tumor? In the tall order. If you could do that then you would suddenly have very limited systemic toxicity. Right. If you can keep it in the tumor, you could have very high local activity inside the tumor where you want it. You could even potentially turn cold tumors hot, meaning make them susceptible for immuno-oncology drugs by inflaming them from the inside. Now, that would be a significant deal because the biggest drugs, the most powerful immunodrugs right now are these checkpoint inhibitor drugs.

23:05Cyriac Roeding: I don't know if everybody knows about them. So very briefly, like the biggest drugs called K-Truda from Merck, right? I think it produces like 35 billion in revenue a year. But all of these checkpoint inhibitor drugs have one major problem. They only activate in about 35 % of all patients, meaning two thirds of all patients show no response at all. But these are very powerful when they work. They're amazing drugs. So how could you turn this up, this percentage? And one of the major problems is that these tumors are cold. They're not responding at all to immune activity. And that's where early could potentially drive a major impact.

23:47Cyriac Roeding: So now how do we do it? We use AI to create the first fully synthetic drug. Genetic switches made out of DNA code that get injected into your body. They go everywhere in your body. But they're designed to only turn on in cancer cells. And when they turn on, they program the cancer cell to become their own drug factory to make a drug against themselves by activating the immune system locally to attack and kill the cancer. So now a step back for a moment and imagine this actually worked. If you could have a genetic switch that really only turns on in cancer cells, and then you can program these cells to make drugs, what would that unlock that we cannot do today?

24:46Cyriac Roeding: And I think the answer is you could make extremely potent therapies that are otherwise today too potent. They're too toxic. but if you could make them only in the tumor and keep them there, you could be much more toxic against the tumor, which is what you want because you want to kill it. And that's precisely what early is working on. And that's why we chose the poster child of, of toxicity. You know, for decades people have been wanting to use this specific drug interleukin 12, a cytokine that activates the immune system to attack. IL-12 has been loved by pharma companies before its toxicity against cancer, but also hated by pharma companies for its toxicity against the rest of the body.

25:41Cyriac Roeding: And that's why it's the perfect poster child for early technology as the first drug that we're taking to the clinic. And if all goes well, we want to dose the first human patients in late-stage lung cancer by the summer of next year. Excellent. And so the genetic constructs are delivered to tissues beyond the liver using cancer lipid nanoparticles. Are you making those in-house? Yes. So that's the second big thing. You just brought up the key second requirement to make this work. If you inject DNA freely into the body, the body immediately destroys it. The immune system discovers there's a foreign object and it destroys the whole thing.

26:25Cyriac Roeding: So you need to somehow wrap it and hide it from the immune system. And that is being done by a container. And that container is a lipid nanoparticle. So for anyone on the call here on the podcast who doesn't know what a lipid nanoparticle is, most of us have had it in their own bodies already as part of the COVID vaccine. because the COVID vaccine, it was mRNA that was transported in a lipid nanoparticle. So now, lipid nanoparticles are great FedEx trucks. They transport DNA or mRNA cargo through the body. Here's one problem, though. The FedEx truck knows only one destination. It takes you to the liver.

27:14Cyriac Roeding: And nowhere else. It's always the same route. and within 10 minutes, your cargo gets flushed out into the liver and out of the liver. And that was it. And why is that? Because your liver is responsible for getting rid of anything that doesn't belong in your body, from alcohol to lipid nanoparticles. So if you want to treat any cancer except liver cancer, what are you going to do? So we had to take on the challenge to design completely new lipid nanoparticles that can take you to other parts of the body. We intentionally started with lung. Lung cancer is the biggest killer by far. It kills twice as many people as the second biggest, which is colorectal cancer.

28:02Cyriac Roeding: So how do you get to a lung tumor with a lipid nanoparticle? This is called the billion-dollar bottleneck in the industry. Why? Because if you solved it, it would unlock so many therapies, from gene therapy to what early is doing, cancer therapies. But nobody has done it. So what people have tried is to stealthify these lipid nanoparticles from the immune system, so the immune system wouldn't destroy them immediately or flush them and transport them to the liver and get rid of them. The problem then is if you stealthify them, then they are so stealthy, so compact that they also don't get into a tumor anymore.

28:53Cyriac Roeding: That's called the so-called PEG dilemma. PEG because PEG, because PEG is the stealth code around the lipid nanoparticle. So you have this dilemma. You got a really good PEG that hides it, but you can't get in anymore. So how do we solve this problem was the question. Most companies have solved it or tried to solve it, I should say, because it hasn't really worked so far, by using a different ionizable lipid in the inside of the LNP. However, unfortunately, there's a lot of IP, there are a lot of players involved, but it hasn't really worked. So early went down a completely different route. We looked at the formulations, meaning the composition of all the different materials that make up an LNP.

29:41Cyriac Roeding: We created a whole assembly line, a factory. We tested thousands of them, many thousands in vitro, and I think close to a thousand different ones in mice. So we did a lot of work over years. It took six years of work. And now I'm really excited to say we developed this new technology called FlexCore, which is a very different formulation and composition of the LNPs. And it allows us not only to get to other tissues, but to get into tumors, because that's another challenge. And once you're in the tumor, you also have to get into the nucleus of the tumor, because that's where the DNA cargo has to go.

30:24Cyriac Roeding: and now we're at a point where our LNPs are like I think 22 times higher transfecting these cells these tumor cells than what's currently market standard and with that kind of power we can now actually deliver our genetic switches into the place where they need to go into the nucleus of the cancer cell and make sure they only turn on there and that's where AI comes into play because the genetic switches, there are trillions of possible combinations, how you can design these. I'm not making this number up. It's trillions. And that's because what we found was when you try to build it the traditional way, it won't work.

31:13Cyriac Roeding: Maybe I should explain. The traditional way is normally by using endogenous pieces, meaning what nature provides. You find it somewhere. We were looking for this. And what Stanford did originally was to use an endogenous promoter. A promoter is like a switch in the genetic world. And it worked really well on cell lines in the lab that never changed. They're always the same for 50 years, right? Lung cancer cell lines. Wonderful results. 95 % activation. Look great. Well, until we actually took real cancer patient samples out of the operating room at Stanford. They very nicely, graciously helped us get these samples.

31:57Cyriac Roeding: And we tested it on these real human samples. And every person's cancer is a little bit different because these are mutations, right? Right. And the result was we went from 95 % to 26 % activation. Right. It was so bad that it would have been better for you to bet against our result than for our result. So then we thought, what are we going to do next? And the natural next step is to think about, okay, what causes cancer? It's mutations of genetic mutations. So now you're going to look at all the mutations that can cause lung cancer. Well, guess what? There's over 100 of them that can cause lung cancer.

32:36Cyriac Roeding: And that's just non-small cell lung cancer. There are other types. So if you use 100 different mutations and you interrogate each one of them with a genetic switch, your whole switch, total switch, becomes so large that you can't get into the nucleus of the cancer cell anymore. So either you're accurate, but you can't get in, or you can get in, but you're no longer accurate. So that was our situation. Rock and a hard place. You choose. so then the next logical step is to think about the 80-20 rule where maybe 20 % of the limitations cause 80 % of the problem unfortunately that's not true either and so now what and this is where I've learned once again the the the wisdom of this of this statement the most important step to solving a really hard problem is to ask the right question And I think it took us over a year to ask the right question.

33:37Cyriac Roeding: We had literally hit over. Which was what? The question was, if we can't interrogate every single mutation that can cause cancer, what if we didn't interrogate any one of them? None. What if instead of looking for the upstream causes, the mutations that cause cancer, What if we looked at the downstream consequences of such a mutation? The results, the symptoms. Okay. And those are called the hallmarks of cancer. Panahan and Weinberg described them over 20 years ago in the literature. These are rapid cell proliferation, lack of cell death, rapid blood vessel construction, angiogenesis, and so on.

34:28Cyriac Roeding: and when you look at these results you don't have to look at all the causes that can cause it you only look at the results and then we used machine learning on thousands of fully sequenced cancer samples from the lab from real patients and sequenced them and looked at them and analyzed them with machine learning for patterns and we found these master transcription factor binding sites that were dysregulated in cancer. And we used a lot of techniques to filter out the right ones. So that was a big step, but it was only the beginning. Because the next step is to say, okay, we know some of these transcription factors.

35:09Cyriac Roeding: When you combine them, and you not only look at one, you can't just look at one, it will not work. It won't be specific. But when you combine them and look at multiple, you can get a very high specificity rate. But when you do that, you have many ways to space them, directionality and order, and that leads to trillions of combos. So then we applied some other logic to trim that down. Now you need to test it in the wet lab. And what do you do? Normally you can sequence like 50 a week in your lab. Well, if you have millions of possible combos, you're going to sit here in a hundred years. So then we went to the University of Austin in Texas and found the super expert at building massively parallel reporter essays for the wet lab.

35:56Cyriac Roeding: We hired her, brought her on board, took nine months to build this very special essay that allows us to genetically barcode these sequences and test 250 ,000 in one batch in the wet lab. Wow. Okay. We went from 50 to 250 ,000. Now we were talking. When you test these sequences, 99 % of them are useless. It's like a power curve. They are not much better expressing than the rest of it. But then there are some outliers, and these outliers are really interesting. You can take those and test them in mice and so on. That used to be the end of the process that was technically possible. Today, it's the beginning of the process.

36:43Cyriac Roeding: because we're taking this very high quality data and turn it into the training data for an AI large language model. That proprietary data flows into an LLM that's trained on DNA. And then we build a proprietary oracle, which is a prediction model to say which of these new sequences that get spit out by the LLM are going to be interesting or not interesting. By the way, 99 % are not interesting. But even in the 1 % that we do select, most of it is not useful. So we filter as much as we can. The best players we're putting back into the wet lab that I just described. We run another cycle. The best ones out of those go into mice and all the data that comes out goes back into the LLM for the next round.

37:38Cyriac Roeding: And with every turn of this flywheel, it gets stronger and smarter and stronger and smarter. And what we're essentially doing with this is turn DNA into a programmable language. Just like AlphaFold made proteins programmable, we make DNA programmable. and that is so exciting that we can now we now are working on the next generation of of this with some of the largest top ai labs because this is becoming a top quality tool for developing disease-based switches and when you can do that for cancer maybe for autoimmune diseases, you now control the disease cell. And Ben, think about this, what this means.

38:36Cyriac Roeding: If we could stop chasing the latest mutation, by definitions, always two or three steps ahead of us. We're always behind. We have to be, otherwise we don't know what to chase. But if we control the disease cell itself and can tell it what to do, we are suddenly taking over. We can take control and tell the disease cell what to do, the cancer cell what to do, rather than it doing what it wants. That's what we're really doing here. That is really exciting, Syriac. And you said first in human next summer. Is that right? That's the plan. We're already manufacturing the drug. It's already in manufacturing.

39:19Cyriac Roeding: We've already had an FDA meeting. So we are moving really rapidly towards dosing the first humans. This will be our first time we're taking it from mice and monkeys to humans. We've done a lot of NHP work, non-human primates, to show safety. It's exceptionally safe. This is one of the big problems with lipid nanoparticles containing DNA cargo that often they produce high fevers and so on. And our monkeys are not even showing elevated, mildly, not even mildly elevated temperature levels because we have engineered this out. You also have to focus on redosability. A lot of these LNPs are not redosable because it means they're effective the first time, but not the second and third time.

40:05Cyriac Roeding: So we've done that. The other big thing is a lot of people, when they use lipid nanoparticles, they put a moiety on it. That means a connector to the cancer cell. that looks really great in an animal model that has that exact connector, that exact moiety, the counterpart, your data looks great. The problem is once you go to heterogeneous human cancers where every cancer is a little different, the whole thing falls apart. So we took at least two years more work. It was a very hard road to do this without any moieties. There is zero moiety on the LNP. Everything is very clean and is built to go to as many places as possible, but the genetic switch makes sure it only turns on in cancer.

40:49That's fascinating. And I think it'd be very easy for us to stay on early for the rest of this conversation, but I have to get to China. So I'm going to switch the year with Syriac. And I wanted to ask you about the five-year plan that was recently announced by China, 2026 to 2030. Through the plan, the Chinese government is designating biotech an emerging pillar industry targeting over$520 billion in sector revenue by 2030, other goals, producing five global blockbusters, a blockbuster being a drug with over a billion dollars in revenue annually, and then a 25 % share of the world's first-in-class drugs.

41:34A bold agenda, a bold five-year agenda from China. My question for you, Syriac, is what are the biggest implications of this plan for biotech companies outside of China?

41:49Cyriac Roeding: Yeah, first off, I think this plan will be absolutely fulfilled. You do? To me, I have no doubt about it because the momentum is so high. Some people have always thought of China as the copycat of the world. Right. That is so outdated. it was already outdated in 2016 when i wrote my first piece on this in the tech world people were talking about china as the cloning the cloning engine you know at the time it was already visible in in traditional tech heart and hardware software and hardware that china was innovating not just copying at the time they already had i think 70 percent share of home home-use drones by DJI.

42:34Cyriac Roeding: And now you're seeing the same thing 10 years later in biotech. We're way beyond the idea of just cheap knockoffs. China is innovating. China is an innovation powerhouse. And that is not a bad thing for the world. It's a great thing that there is another place besides the United States where deep innovation happens on biotech in order to help cure or treat the worst diseases of humanity. Absolutely. There is nothing bad to say about this. The question is, what does America think about somebody else taking over the lead in innovation in biotech and developing the world's most innovative and powerful drugs?

43:20Cyriac Roeding: What do we think about this? And I want to just turn this into a question that's more personal. Imagine we get to a point where the majority of the most powerful new drugs come out of China. And for some reason or another, may it be with intent or without intent, let's just say without any intent, there is a shortage of production. And we've seen this before. It was called the pandemic with COVID vaccine. Yeah, absolutely. What do you think every country did? Every country served its own citizens first, as you would expect. So what would happen and how would we feel personally about this? Imagine, God forbid, one of us gets diagnosed with cancer.

44:18Cyriac Roeding: and the most powerful cancer drug against that specific cancer comes out of China, but there is a shortage. Do you think you and I, you or I, will get this drug? No. So now there might be other situations where it's geopolitical. Like, for example, we've seen this with rare earths. This is a constant battle between China and the U.S. because China has more rare earth than the U.S. And I don't actually expect China to do this with drugs because that is very cynical to do this on purpose. But there might be simply a shortage of supply. So now I'm asking everyone, do we want to be dependent on another country to develop the world's most leading edge drugs?

45:10Cyriac Roeding: And most people would answer this question with, of course not. But the problem is, we're not acting the way that we're talking. We are facilitating just what I just painted as a picture is what we are currently preparing to happen. For the first time ever, since the biotech industry has emerged 60 years ago, we are risking losing the innovation leadership. And why is this happening? Yes, there are some regulatory issues. We're slower with clinical trials and certain other regulatory issues in the approval process, and we need to change that. But that is not the number one problem. The number one problem is, believe it or not, money.

45:59Cyriac Roeding: It's funding. Let me explain. You mentioned it at the very beginning, Ben, when you talked about biotech. Biotech has long cycles, right? Right. It takes 12 to 15 years to develop a drug from start to finish. And in the US, we have a completely free market, which is awesome. I'm a big believer in capitalism. But there are certain situations where the system is failing us that is otherwise so efficient. And that is called boom and bust cycles in biotech. The boom and bust cycles in biotech are more extreme than I believe in any other innovation-based industry. Yeah, and we're just coming out of a long bust cycle, right?

46:45Hopefully coming out.

46:46Cyriac Roeding: Yes. Thank you. So the last four years, not this year, but the prior four years, have been the biggest bust, I think, in the last over 20 years. Right. So now, this happened after the pandemic. It was sort of like an aftershock of this overhype situation, and all the money went away. But now let me give you three major facts that paint this picture how extreme this is right now. Number one, guess how many percent of venture capital dollars this year are going to AI versus to other parts of innovation? Oh, 10 to 1? 87.5%. Wow, okay. That means everyone else gets 12 and a half. Now, fortunately, early is on the intersection of bio and AI.

47:34Cyriac Roeding: So that's great. You can get some of those. That's special. But not every biotech is. Most biotechs are. So 12.5 % left for everything else. That's number one. Number two, five years ago, less than 5 % of the licensing dollars from pharma companies went to China. This year, it will be two-thirds. Yeah. Two-thirds. One-third is left for U.S. firms or anywhere else in the world, outside of China. That is a dramatic shift. What are they buying? They're not just buying cheap knockoffs. They're buying innovation. Right. So how come there's so much innovation to buy? And the answer is a sustained, flat, much flatter curve of funding by strong support, largely from not only from private sources, but also from the government.

48:41Cyriac Roeding: It's not that they invested every startup. They also developed ways to buy things from them. There are all kinds of mechanisms to support these prioritized industries. You mentioned the new five-year plan. This is the second five-year plan in which biotech has been listed. Not the first. And with every biotech, stating biotech as a major pillar together with AI and fusion technology and robotics and so on, this means the whole country is behind it. So now, we don't want to shift to communism. Last time I checked, I don't. I guessed you don't. So what are we going to do about this? And the answer to this question, I believe, needs to be a sovereign biotech wealth fund.

49:33Cyriac Roeding: What is that? What's a sovereign wealth fund? A sovereign wealth fund is money from the government, from taxpayers, that is designed and allocated to be invested in innovative companies. exactly between this phase of preclinical to clinical, because that's where most of the cut shutdown happens. The valley of death, that's right. The valley of death. It's like you get some early funding, you show some promise, but now you need money to get it to the clinic. And you know this beautiful Catch-22 statement that everybody hears in funding in biotech? When you have clinical data, there will be money.

50:12Cyriac Roeding: When you have money, there will be clinical data. Right. So to overcome this valley of death, we need a concerted effort to flatten out this boom and bust cycle. Right now, the remaining 12.5 % that might be left over for biotech, if at all, they go to late stage companies because they are also desperate for cash after the last bust cycle. So they're cheaper and the VCs have lower risk. There was an article in the Financial Times, an opinion piece a few weeks ago. the headline was, biotech VCs are becoming like bankers and it will probably all come to hurt us because there's not enough risk taken anymore.

50:50Cyriac Roeding: And they don't have to because there's so much desperation for starvation for cash at the later stage too. So a sovereign wealth fund can fix this. Let me explain how this works because it's actually a beautiful model. Some people might say, well, this only works when you have so much money like oil rich industries or countries like the United Arab Emirates or Saudi Arabia or Norway that pump it out of the North Sea, right? We don't have that. So what are we going to do? Well, look to Singapore. Singapore started its sovereign wealth fund with no oil and no other resources in the late 80s. Today, they have$1.3 trillion in these funds.

51:36Cyriac Roeding: they cannot add as much as they're earning automatically every year just by having this much money it's like a self-running train you can't stop it and when you invest in these high quality high innovation companies many of them will go belly up and won't make it but a few moonshots will become so successful that if this system is properly handled like it is in Singapore. This will more than feed itself. And the money will go back to taxpayers or to future innovation for the next cycle of innovation to keep the country at the top edge of innovation. That's what a sovereign wealth fund looks like.

52:21Cyriac Roeding: And of all industries of innovation, I think biotech needs it the most. We're risking losing our leadership and we shouldn't do that. And this is something that would need to be taken up by the federal government approved by Congress to get started, right? That is correct. Interestingly enough, the Trump administration, actually Trump himself signed an executive order about a year and a half ago to start a sovereign wealth fund. And strangely, it happens very rarely in this country. The other side of the aisle wants this as well. Even Bernie Sanders. Except they have no agreement where the money should come from.

53:05Cyriac Roeding: okay and that's where this is stuck right now to decide yes we want it we both understand both iels understand the benefit how do we fund it and there are some interesting proposals that are being discussed like taking a small percentage of the largest ai companies uh in order to fund it who have actually some of them even expressed an openness towards that idea but there is no agreement on this yet. But I guess what we first need to create is a common understanding of how big this problem is. When you suddenly see two-thirds of all licensing dollars go into China from global pharma companies up from less than 5 % five years ago, you know there is an issue.

53:55Cyriac Roeding: When you see some of the best biotech firms go belly up right before they can hit the humans after having spent years of research. You know what's happening. Some of the potentially best drugs of the future just got buried. I don't think we want that. Do we? No, I'm glad you mentioned the Sovereign Wealth Fund. That's a really interesting idea. One follow-up question to that I have is, who would be the administers of it? Who would decide which companies get investment? Would it be the party in power? That's a great question, Ben. And the answer is hell no. Okay. It has to be an independent body of absolute professional top life science investors who know exactly what they're doing.

54:44And those members couldn't be swapped in and out depending on who's in power.

54:48Cyriac Roeding: No, cannot. And also, let me also make another suggestion, which I think would be really helpful, especially in the beginning. My suggestion would be that in the beginning, for the first few years, until you see it's going well, the sovereign wealth fund is only allowed to co-invest with the top 10 % best performing VCs of the world. Interesting. Okay. So you take the percentile of the top best performing ones, whether they're American or non-American, doesn't matter. You just want the best investors of the world. And whatever they invest in, the sovereign wealth fund can opt to co-invest into.

55:33Okay.

55:34Cyriac Roeding: And by doing so, you have a really good shot at not wasting taxpayers' money and coming out on top in 10 to 20 years from now. And then it starts compounding, and that's what you want to see. I want to be respectful of your time, Syriac. We're coming to the end here. I have one final question that I just have to ask you because you're close to this. OpenAI announced yesterday that they would not roll out their newest model due to safety concerns. And I'm curious if you agree with that decision and how much you think this idea of AI potentially eliminating the human species in 10 or 15 years, how much of that is hyperbole versus an actual possibility?

56:24Cyriac Roeding: well it's definitely a possibility but I think we have to be careful to understand we don't know what we don't know there is a lot of different scenarios this could play out and it's very wise to be careful and yet at the same time and both can be true I would also highly encourage everyone to prepare for a non-doomsday AI scenario. Yeah, right. Where we see AI literally help not only treat, but potentially cure some of the worst diseases humanity has experienced. And where we design a future that has more abundance than it has today. In order to do that, we need to be very responsible. We need to do it right.

57:21Cyriac Roeding: We need to act really well. We also need to understand that humans are generally not very good at constraining themselves. We're not very good at that. Honestly, we kind of suck at it. Yeah, very true. But you know what we're really good at? We're really good at out-innovating our problems. So what I would also encourage is a debate about innovation, innovating solutions against threats of AI. In other words, the counter AI. A defense scheme. that defends AI because we are probably not going to always succeed at constraining ourselves. Even if we do it, other people may not. And if the bad guys don't, then the good guys can't if they're constraining themselves.

58:19Cyriac Roeding: That's always the problem, right? By the way, I don't want to misuse this argument by saying, oh, let's just run and not look. I'm not misusing that argument. I'm just saying it is also really important, just like we do this in general defense technology, we do this in AI too. We have to develop, out-innovate the threats of AI by innovating against them. And as humans, we're really, really good at that. Often much better than at constraining ourselves. And I'm not saying we shouldn't in certain cases, but I am saying let's actually ramp up on the innovation side against the threats. So we're prepared.

59:05Right. Well, I think we're going to have to end it there. It's been a real pleasure speaking with you, Syriac. Thank you so much for coming on the show.

59:13Cyriac Roeding: Thank you, Ben, for having me. It was really fun. We've been speaking with Syriac Roading, co-founder and CEO at Early. I'm Ben Comer and you've just listened to the business of biotech. Find your, find us and subscribe anywhere you listen to podcasts and be sure to check out our weekly video casts of these conversations every Monday under the business of biotech tab at life science leader.com. We'll see you next week. And thanks as always for listening.

59:50Thank you.