Cyriac Roeding - Part 4: Revolutionizing Cancer Detection & Diagnostics

Intro - 00:00:01: Welcome to The Biotech Startups Podcast by Excedr. Join us as we speak with first-time founders, serial entrepreneurs, and experienced investors about the challenges and triumphs of running a biotech startup from pre-seed to IPO with your host, Jon Chee. In our last episode, Cyriac shared how he founded Shopkick during the 2008 financial crisis and what it meant to secure partnerships with major brands like Best Buy and Target. He also discussed how his entrepreneurial journey led to an interest in life sciences and biotechnology. If you missed it, be sure to go back and listen to part three. In this chapter, Cyriac shares the inspiring story behind founding Earli, sparked by a Thanksgiving article about Dr. Sam Gambhir. Learn how a singular idea ignited a mission to revolutionize cancer detection and transform patient outcomes. He delves into the scientific breakthroughs shaping Earli's vision, the challenges of translating discovery into real-world impact, and his unwavering commitment to transforming cancer into a manageable,

Jon - 00:01:19: How did the opportunity to lead Earli come about?

Cyriac - 00:01:24: I looked at over 200 ideas. And I have a simple first filter. I try to forget every business idea as fast as I can. And only if I absolutely can forget it, then it's potentially interesting. That kills most ideas. So what happened here was I live four miles from Stanford in a little town called Portola Valley. And so I naturally started stumbling around the campus. And I talked to over 100 scientists at Stanford, all super interesting people. And every person was kind of telling me that they were working on the world's most important idea. By definition, 99 out of 100 were wrong, likely all of them. Unfortunately, since I'm not a biologist, I couldn't tell which one. I'm probably able to tell a good idea from a bad idea, but I'm not able to tell a good idea from a very good or an outstanding idea. I happen to believe that there's an ocean of good ideas, but a dearth of outstanding ideas. And only outstanding ideas are worth pursuing as a startup. So that was very frustrating. And I really hit a wall. And I remember it's Thanksgiving now, 2016. And I'm very frustrated. Because to me, Thanksgiving means the year's over.

Jon - 00:02:42: Yeah, yeah, yeah. 

Cyriac  - 00:02:44: There's not much happening after that, right?

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Jon - 00:02:46: Yeah. 

Jon - 00:02:48: I had not accomplished my goal for that year, which was to find the next thing I was going to do. And lo and behold, I'm sitting there in the room in a house that was not our house. We were subleasing somebody else's home in Portola Valley because our own home was being remodeled. That's relevant to the story because we kept receiving the magazines of the people who usually live there. I'm talking print magazines.

Jon - 00:03:11: Yeah, yeah.

Cyriac - 00:03:12: So one of these print magazines is Stanford Medical School's print magazine. The door opens, Angel, my wife, comes in, and she says, I think you've got to read this story. And I'm looking at the story and it's called, And Yet You Try. It is a story about Sam Gambhir, one of the world's most preeminent early cancer detection and treatment experts at Stanford University. A revered scientist with 800 people working for him at Stanford, two labs, and ran the entire radiology department at the clinic dealing with patients every day. And the article was about how he worked with his only child named Millen at age 15 in his lab already. He was so brilliant. And how his only child Millen died from cancer at age 16. And I read the story. And I felt a gripping sense of grief. And I decided to send Sam an email right in that moment, a cold email. I said, Sam, I can only imagine how hard this day is for you on this holiday. It is not a coincidence that I'm writing you on this day for that reason. I just read your article. I felt a gripping sense of grief, although I don't even know your son. But I was also very inspired by the work you're doing. I am not a biologist. I'm not a scientist. I'm a serial entrepreneur. I would like to build my next business. I'd like to meet with you. Two months later, we met on a Saturday morning. At a small restaurant in Portola Valley, 4,000 people. It turns out he also lived in Portola Valley. We were neighbors and didn't know of each other.

Jon - 00:04:54: Wow.

Cyriac - 00:04:55: And my first question to Sam was, Someone with my background or better lack thereof. Bother the world of biology with my presence. And it was not fishing for compliments. I meant it because I know every new company takes like almost 10 years. And I didn't want to waste his time, my time, anyone else's time. And he looked at me and he said, I have two answers for you. The first one 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, and we have even fewer people who know how to build a startup company. 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. And then he stopped and looked at me. And I took the second part of the answer as the cost of doing business and moved on. Maybe too far. So then before I knew it, every other Saturday morning, I... Found myself sitting at his kitchen table in his house in Portola Valley, and 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 all these interesting people at Stanford. In order to help me find my next thing. The problem is, you know this. A good idea is one out of 10,000. And a great person that fits to you is one out of 10,000 too. You multiply the two and you know the odds. The odds struck me as well. I couldn't find it. So three months later, I went back to Sam and I said, Sam, I'm really sorry. I still don't have it. May I ask you a simple question? You've seen hundreds of ideas in your own lab, outside of your own lab. Which one has the highest potential of all of them? 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 Earli.

Jon - 00:06:47: That is crazy. Something that I... Appreciate about your willingness to just like put yourself out there like even though you're like i am not an expert here but just put yourself out there and i see this across every single time you're like well i'm going to figure it out And it's just kind of what we were talking about before too, about like. Trial and error and just like going out there and trying it and it's almost like feeling around just like feeling around in the dark until you you find when you talk about the statistical likelihood it's like, very, very difficult to pair that with the founder and the idea and have both of those be kind of like grand slams. And when. That idea was presented to you. How did you, I guess, okay, it's almost like lightning in the bottle. This has been captured. And I'm going to imagine. Inspiration struck. How did you begin to execute on this? Because again, you described it like running a biological biotechs are complex and very different types of businesses. How did you start to unpack that and really tackle the problem and start the company and get it going?

Cyriac - 00:08:05: Okay, yeah, so... First, I applied my filter. Could I forget this idea? And I really couldn't.

Jon - 00:08:12: Yeah, yeah.

Cyriac - 00:08:13: It started haunting me.

Jon - 00:08:15: Yeah, yeah.

Cyriac - 00:08:16: I really looked at many other things still after that. And in the end, one died. I was sitting there in the house and I was saying, okay, I think it's the one.

Jon - 00:08:27: It kind of reminded me when you were thinking about your mobile app. There can't be an alternative. If there's an alternative, throw it out. In this instance, it's like, I can't stop thinking about it. And if I can forget about it, then we're moving on. So it's a, you know, that's, again, it's kind of a, it's a very, I think, helpful mental model for anyone who's trying to think about if they want to start a business or pursue an idea. And it's very, I don't want to say simple, but it's a, it's clear.

Jon - 00:08:55: It has to be profoundly clear to you that this is the thing. That it's so different and unique and so good. And if it works, it is so changing the world, so fundamentally important, and so moldable, and big, and modular, that you can't play with it until it works. That's what I like to do. I don't like single shots. I like opportunities where you can build and mold and make it work. But if they do work, they're going to fundamentally change the game. So perhaps I explain what it is. 

Jon - 00:09:26: Yeah, yeah, yeah. 

Cyriac - 00:09:29: So Sam was not only great at Stanford, he was also on the advisory boards of GRAIL, which is a liquid biopsy firm that uses fragments in the blood or methylation patterns to find whether you have cancer or not. Fascinating technology. He was also on the advisory board of Earli, Google's life science arm. And he loved all those new technologies. But he was also really concerned and frustrated that no one seemed to address what he believed to be the number one problem in the clinic, sort of the elephant in the room. And that is... That in the last 30 years, Pharma companies have spent billions of dollars trying to identify natural biomarkers on the outside of cancer cells. In order to make them draggable targets. The problem with that approach is that most cancers don't have natural biomarkers on the outside of cancer cells. That are druggable, and even those few cancers that do have them, don't have them for all patients because of individual mutations. After all, cancer is a mutation of your own cells, and therefore the biomarkers also keep mutating. That's why there's no drug that ever works for all people. So Sam said, What if we stopped this entire cat and mouse game of always trying to catch up with cancer's latest thing, mutation, and by definition, always being behind or lost? What if instead... We went into the cancer. In fact, into the cancer cell nucleus where the mutation happens that causes the disease? And what if we could create a genetic construct? That we bring into those nucleus that only switches on when it's cancer and doesn't switch on when it's not cancer. But when it does switch on, what if that construct could genetically force the cancer cell to produce any protein of choice that is pre-encoded into the sequence, which can then either be an epitope to bind a radioactive tracer to locate the tumor in a pet image for diagnostic purposes. Or it can be a cytokine protein released to activate the immune system to attack the tumor and ultimately kill it for therapeutic purposes. In other words, what if we could take control of the cancer and tell it what to do? Rather than it telling us its latest mutation ideas. And us trying to catch up? What if we could control the system by engineering the system and consistently producing the same biomarker over and over and over again that we want, that we encode, and that makes it the first synthetic target platform ever created? That's what Earli does.

Jon - 00:12:24: Freaking badass, super badass. And you described it very aptly as like this cat and mouse game. It's kind of like the flu. We're just guessing. We're just like, yeah, this feels about right this season. We're just going to roll this out.

Cyriac - 00:12:41: And so much money and so much time. And I want to think about the patients here, because I don't know if everybody on the podcast knows this. Sam Gambhir sadly died from cancer himself for years. The inventor, the creator and the amazing person. He was an amazing scientist. He invented it together with one of his postdocs at his lab. Sam died from cancer from a tumor of unknown primary, which makes it even worse because he couldn't detect it any earlier. And then his wife, Aruna, died a year ago. From cancer. The whole family is gone. And Jon, we are carrying the torch. We need to make this mission a reality. This has to happen so that all of this wasn't lost and so that all the people that are suffering from this can actually have a game changer. And every pharma company needs targets so that the drugs can work. What if you could synthetically engineer these targets? Make them. Only in cancer. And that brings us to... How do you know it's cancer? Because that is probably the hardest problem in cancer of all questions, right? The holy Grail in cancer, if you put it really simply, is to kill the bad cells and don't kill the good cells while you're at it. That simple statement belies the reality of how hard this is. And Siddhartha Mukherjee wrote this incredible book, The Emperor of All Melodies, in 2011 that got the Pulitzer Prize for describing the history of cancer and its treatment. And in the prologue, he says something to the effect of... Malignant and healthy cells, tissues are so genetically intertwined. That ungrading the two, meaning knowing what's malignant and what's benign. Is probably one of the hardest scientific challenges faced by our species. Well, for better or worse, that's what Earli is doing. So we started with lung cancer. Lung cancer is the biggest killer of all by a factor of two. It kills twice as many people as the next one, which is colon cancer. So we started with lung and then went to liver. And in lung cancer, when you see lesions in the lung on an image, right, these little dots that are lesions. 94% of those on average are completely benign. But 6% are malignant. And if you don't take them out, they will kill you. The problem is no one knows which 6%. Because until they're really large, you don't really know the difference. And then clinicians have only two options. They can either, send you home and do nothing. And asks you to come back after six or 12 months for another imaging, more radiation, and if it has grown, then it's cancer. And sorry, sadly, it was already canceled the first time, except nobody treated you. And the problem is not just the size of the tumor that got bigger. That's less of the issue. The bigger problem is that it might have started spawning off tiny micrometastases elsewhere in the lung, in your lymph nodes, or elsewhere in your body. 50% of all lung cancer patients are recurring. The primary tumor is removed. Everybody hopes you are now safe and you're cured. A year or two later, the cancer comes back. Those were the micromets that now have grown. So timing is of the essence. You've got to move fast. The only other option that clinicians have is a needle biopsy. They put a needle through your throat, into your lung, and they try to fish some cells out and send them to pathology. That procedure costs $20,000 to $40,000 under full anesthesia in the US because the lung has to stop moving so you can move the needle around. It produces over 20% complications of collapsed or bleeding lungs and people start coughing up blood. 1% die on the gurney from the procedure. But maybe the worst of all is that if you do have lung cancer, the needle is so hard to navigate, it might miss the tumor by a millimeter or two in 16 to 40% of all cases, depending on the location and the size of the tumor. You go home, people told you you don't have lung cancer, but you do, and you don't get treated. So what's the alternative? I'm going to ask, what if? We could light up only the malignant nodules and not the benign ones. In a pet image immediately. The next day, you would go to surgery or radiation and be treated. So Earli's job is to turn millions of unclear findings in images from liquid biopsies or from imaging into immediately actionable diagnosis and treatment. You get an injection into your arm. Takes 20 seconds, normal syringe. Two days later, you get a pet image and the pet image shows up only the malignant, not the benign nodules. So by this time, you might wonder, how does this whole thing work? There are four main elements to this thing. The first one is a nucleic acid template. It's a cargo container. Inside the container, we're writing an if-then clause. If it's cancer, then produce an output. Produce an epitope for imaging, produce a cytokine or an ADC, whatever you want for therapy. We define the protein, right? And then there's a fourth element, which is the non-viral delivery agent that gets it to the nucleus of the cancer cell. This is very hard anywhere but the liver. Anybody who knows something about lipid nanoparticles, they usually go to liver. Took us four and a half years to solve that problem. Very hard to do. We did that with the help of partners and internally. But the hardest and the most important element of all is, is it cancer or not? That goes back to the prologue of the book. When we first got the construct from Stanford, It was an endogenous natural promoter called Survivin, BIRC5, very good at separating lung cancer cell line in the labs from non-cancerous cell lines in the lab. But when we looked at individual cancer patient samples, The whole thing broke down. Because of the individual mutations. So the natural next step for us was to think, okay, well, why don't we look at the genes that can cause the lung cancer? Lung cancer might have over hundreds of different driver mutations that can cause the disease. If we wanted to interrogate every single driver mutation, the construct would get so large that there's no way you can get it back into the nucleus again. So either we are accurate and we can't get into the nucleus, or we can get into the nucleus, but we're not accurate. We hit a wall, to be honest. It was pretty bad. One and a half years into the company, we hit a wall. Two and a half years ago, we had a breakthrough. We said... If we cannot look at every single driver mutation or gene that can cause the disease, what if we looked at none of them? What if instead... We looked at the downstream commonalities that can cause the disease and looked at the master transcription factor binding sites. That actually drive the disease downstream that are the common factors such as rapid cell proliferation and lack of cell death. But to find the right ones, there are hundreds of those too. We have to take 20,000 fully sequenced cancer samples and run massive machine learning and AI against it. So much so that we had to rent four of the largest AWS secrets and have them run for an entire month through the data. And then we used a high-throughput system in the lab for the wet lab to create different motifs, thousands of different genetic motifs, and tested them in the lab and then on 20,000 mice. And the result is now that... Our original construct from Stanford. We tested it on about 45 fresh lung cancer samples from the operating room at Stanford, right? And it only turned on at 13% of all cases. Now with our fully synthetic constructs. The same samples. Turn on in 98% of all cases. It took us five years and $60 million to get to this point, to know that it's cancer or not. Now, it's really great to know that it's cancer, but it's not sufficient. You also need to know when it's not cancer and not turn on. 

Jon - 00:21:05: Yeah.

Cyriac - 00:21:06: And to that end, our friends in liquid biopsies are usually comparing healthy against cancer tissues and look for the differences, right? But unfortunately, that's not the biggest problem in the clinic. The biggest problem in the clinic, remember, are the benign lesions. They look like a tumor, but they're not. They keep people from being treated. On time. So we needed to go hunting for benign lesions, which are really hard to find. Nobody keeps them. We finally found them and we showed that we had a 98% accuracy under the curve between benign lesions and cancer. Why? Because a granuloma has nothing to do genetically. With a cancer. We are doing genetic imaging for the first time, not anatomical imaging. And that's why we don't get a signal. So then we took it from 30 gram mice to 60 kilogram pigs. Almost the size and weight of human beings with a fully functioning immune system. And we got to the point where we could... Light up! Like really small lung cancers, liver cancers of like eight millimeters and even smaller some of them. And they have the brightest signal, why the control pig has only one out of five, and even the one is like at the lowest level of signal. So the next step is to become that bridge between detection and treatment. Because unless you have not just detection, but a diagnosis, without a diagnosis, there is no treatment. And then we're raising the money now to... Take this into a human phase one and two trial on patients that have suspicious lung nodules, but we don't know if it's cancer, and they will get a needle biopsy anyway, and we will predict what the needle biopsy will find. And the job, of course, in the long run is to get rid of this needle biopsy. Nobody wants it. The clinicians don't like it because of the faults, the error proneness, and the side effects, and the patients hate the invasiveness, and the insurance companies hate the cost. So there's nobody who likes this thing. The goal is to replace that with our injection, which costs only $3,500 instead of $20,000 to $40,000, and it still has a 90% gross margin. We calculated the market revenue potential for Earli, just for lung cancer in the US, at $16 billion a year, and another globally over $50 billion for lung. $20 billion for liver cancer, and then various other ovarian, stomach, and so on. And that's just for diagnostics. Because the whole platform lends itself also to therapeutics. How can you do therapeutics? Well, take immuno-oncology, the most important invention in cancer in the last 20 years, right? Jim Allison is on our advisory board. We're very lucky to have him and Pam Sharma. And Phil Greenberg, and a drug like Keytruda made by Merck. Can be like a miracle for some patients. There are literally stage four patients that get cured. The C word, right? Literally cured. Stage four. Happens. It produces $25 billion a year in revenue for Merck. The problem is, unfortunately, it only responds in 30 to 40% of the patients, and 60 to 70% show zero response. Why is that? It's largely because those patients' immune system does not recognize the tumor as an enemy or it doesn't have enough immune cells in the vicinity of the tumor. And so it doesn't matter how many drugs you take, there is nothing the immune system does. But what if you could use the Earli platform to release a cytokine right from the inside of the tumor into the tumor microenvironment to teach the immune system that there is a problem? Have it attack the tumor, and then you give Keytruda or another immuno-oncology drug when the immune system is primed and knows where it is. Imagine if you could drive the response rate just from 30% to 50%. What that would mean for patients and for these Pharma companies. So that is where we are now. We're testing that now in mice. The therapeutics element. The company has raised $99 million as of today from Andreessen Horowitz being the lead investor in the seed round, Kossler the lead investor in the A round, and then Marc Benioff, Sands Capital, Breyer Capital, Perceptive Advisors, the life science hedge funds, Casdin Capital, and various other very great investors. So that's where Earli is today. 

Jon - 00:25:39: One, I think I would say. Congratulations getting through that kind of that moment where you hit the wall. Because like, that's kind of that chasm. That a lot of founders just like you hit the wall and that's where the story ends. So I guess, first just congratulations on getting through that.

Cyriac - 00:26:01: I'm sure we'll hit another wall.

Jon - 00:26:02: But still, you gotta like count the victories when you can, right? It's like, you gotta count the wins and getting through that first kind of wall, again, I can see the through line. You was like, we need to flip the paradigm. We had the blinders on. We just need to like completely reset this thing and approach it from a completely different angle. Same problem, different angle. Kind of just like when you're in Japan, right? It's like the whole thing. Should I tell my teacher that they graded this wrong?

Cyriac - 00:26:34: Yes.

Jon - 00:26:35: And then you flipped it and you looked at it from the perspective of someone else in their culture. And then you kind of like, ah, I can see this and it logically makes sense. And I can see almost how that connects to this. And, this is incredibly exciting to hear because I think also too, nothing against therapeutics. But I think sometimes diagnostics doesn't get nearly as much love as therapeutic efforts. And exactly what you said is right. It's like, unless you get a proper diagnosis, the therapy may or may not be applied. And that's the problem. That's where it lies. And, you know, I think we sometimes forget that. If you don't even know when to use the tool, the therapeutic tool, then like. All of this is moot. It's all moot to begin with. So we need to, it's incredible, like what Earli is doing is incredibly important. Because like exactly what you said, it's like, can we make, can we make Keytruda? Do we know when we can use it? And can we boost its efficacy? That is a major win. That's like a major, major win. And, but the thing is, it gets back to the proper diagnosis. 

Cyriac - 00:27:44: That's right. If you have an Earli diagnosis and you can then turn the cancer against itself. And you stand a real chance, maybe not only to get rid of the initial tumors, but maybe also of... Either minimal residual disease or... Even Earli spanoffs of micromets, because this could activate everywhere. So you might have a shot in the longer run to really preempt the game. And turn the tables against cancer. And that maybe leads us to the final thing about the mission statement of Earli is exactly that. It sounds crazy when you hear it, but if you understand what we do, maybe it starts ringing a bell. It is to make cancer a benign experience. It's not going to get eradicated. But what if cancer became like a cold? Where you have it, it feels bad, and then it goes away, and you move on with your life. Our North Star Earli are the patients, not the financings. Not the partner collaborations. They are all important. Both of them are required to get to the next game. But ultimately... It's all about really helping people live longer. That's our major milestone. And the faster we can get there, the better. With partners, with the right investors, with the right team. That's why we've assembled all these wonderful people to give us a real shot at helping people in the end.

Jon - 00:29:16: Absolutely. And that really, really resonates with, you know, one is exactly what you said. You have like the ingredients for success. They are, it's insufficient, but it is required like to have the right people on the bus, but the ultimate, like we need to do more for the patients and also just think about exactly what it is that we're all shooting for here. And hearing Earli admissions got me fired up. I'm really, really excited to just like from the sidelines, watch you guys continue to go through the clinic in the next year or two, because that is a world that I would want to live in. And hearing the origin story of Earli is gut-wrenching. That is honestly, it is terrible what has happened and what happened to Sam. It's just so terrible. So I want to live in a world where that doesn't have to happen again. So one, thank you so much for sharing that story. And also, I'm just super pumped up to see where Earli continues to take it. In the traditional closing fashion of The Biotech Startups Podcast, we like to round things out with two closing questions. First is, would you like to give any shout outs to anyone who has supported you along the way?

Cyriac - 00:30:27: Oh, the number one shout out. Goes to David and Sam. David Suhy is my co-founder. I know nothing and he knows close to everything. He's the gene therapy expert and there would be no way we would ever be where we are. And I got very lucky. I would never have started the company without him. I looked at over 200 people and met with 50 and he was the only one of it to the profile we were looking for. He's an amazing scientist. And the team had Earli incredible people and the best of the best. Some people have been there for a long time, Badri Evan and amazing people. And then, of course, Sam is the beginning of it all. And then there are the board members like Jorge Conde from A16Z and Marc Andreessen at the earliest stages, they believed it. And Marc Benioff, first call I took, he called me by FaceTime, called me back after an email, like he does. And then in 10 minutes into the conversation, he said, I want to fund this. I want to do this. These are the people that are on the road with you. And the investors and the advisory board members are special. If you take a look at, I don't know where to start. I've already called out several of them, but it's an incredible group, very unusual.

Jon - 00:31:47: Absolutely. And I think with all business ventures and especially scientific venture, it might sound cliche or corny, but it takes a village because each of these are, these are little miracles that we're trying to manufacture and you can't do it alone. So I love hearing that you've assembled such a formidable team to tackle such an important problem. And looking back in our last closing question is, if you can give any advice to your 21-year-old self, what would it be?

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Cyriac - 00:32:20: It's all going to work out in the end. If you hustle, if you bustle, and if you keep going the road less traveled. You might reach destinations other people will probably not reach. By definition, the roads that most people travel on lead to the same destinations everybody else is trying to get to. And they lead to known destinations. But if you are willing to take roads less traveled and hustle and bustle along the way, and you're creative. And you're curious, and you just enjoy the journey, it will take you to amazing places. Take risks and it will all be fine. 

Jon - 00:33:08: And honestly, that is like that's some advice that I, you know, I wish I heard early on, because I think sometimes, there's a lot of existential dread that I experienced, by pursuing these kind of like paths less trodden and for anyone out there who's listening know that, following these paths is important. It's important work, and it's important to do, and you never know, where it will take you and obviously, hearing your stories and like that has been a theme is like start a radio show, working at a newspaper, working you know one you're just like, I'm going to Japan, I don't know Japanese. Like all of these things, and that experience in forming now the early journey, you just never know. And everything is a creative in these experiences. So I think that's really, really valuable advice for anyone out there who's listening. Jon. Thank you for your time. You've been super, super generous. And thank you for being willing to share this with all of us. We're all, I know we're all going to be excited to watch Earli. And as you guys proceed into the clinic and thanks again. And, you know, I could do this for hours and hours and hours with you. So maybe, you know, come JPM. I know JPM going to be, you know, in the near future. So maybe we, we can link up, grab coffee. I'd love to double click and, you know, go down kind of additional kind of rabbit holes where we can. 

Cyriac - 00:34:28: I would love that. And I'm so grateful for you taking the time as well. You're doing something so important by highlighting these journeys for other people to inspire them. And if I could just help a little bit with that, then that makes my day. And I really appreciate that.

Jon - 00:34:45: Sir, thank you again. I'll be talking to you again soon.

Cyriac - 00:34:48: All right. Take care. Bye-bye. 

Jon - 00:34:49: Bye. 

Outro - 00:34:52: That's all for this episode of the Biotech Startups Podcast. We hope you enjoyed our four-part series with Cyriac Roeding. Be sure to tune into our next series featuring Rafael Rosengarten, CEO and co-founder of Genialis, the RNA biomarker company. Genialis is reimagining biomarkers for every target, drug, and patient using a combination of precision oncology, RNA, and AI. Before co-founding Genialis, Raphael spent nearly 20 years in biomedical research, publishing extensively on evolution, immunology, bioengineering, and genetics. He also co-founded the Alliance for AI in Healthcare, AAIH, a global nonprofit advocating for responsible AI in medicine, where he is currently a board member. Raphael holds degrees from Dartmouth and Yale, where he earned his doctorate as an NSF Graduate Research Fellow. He trained in synthetic biology under Jay Keasling at Lawrence Berkeley National Laboratory, co-inventing the J5 DNA assembly tool, now commercialized by Tessella Gen Biotechnology. He later completed a National Library of Medicine fellowship in biomedical informatics at Baylor College of Medicine. With a deep well of experience spanning academia, industry and entrepreneurship, Raphael offers insights that will inspire scientists, aspiring biotech founders and first-time entrepreneurs alike. The Biotech Startups Podcast is produced by Excedr. Don't want to miss an episode? Search for the Biotech Startups Podcast wherever you get your podcasts and click subscribe. Excedr provides research labs with equipment leases on founder-friendly terms to support paths to exceptional outcomes. To learn more, visit our website, www.excedr.com. On behalf of the team here at Excedr, thanks for listening. The Biotech Startups Podcast provides general insights into the life science sector through the experiences of its guests. The use of information on this podcast or materials linked from the podcast is at the user's own risk. The views expressed by the participants are their own and are not the views of Excedr or sponsors. No reference to any product, service or company in the podcast is an endorsement by Excedr or its guests.