She came in to answer some of the most common questions we get from founders in biotech.
Craig Cannon [00:00] - Hey this is Craig Cannon and you're listening to Y Combinator's podcast. Today's episode is with Elizabeth Iorns. She is the CEO and co-founder of Science Exchange. She went through YC in the summer of 2011. She is now an expert here at YC, helping out with biotech companies. I thought it would be cool to have Elizabeth come by and answer some of the most frequently asked questions about biotech companies in YC. We did that in this episode, but if you have more questions you can feel free to tweet our way and maybe we can setup a round two of this podcast. Just two quick announcements before we get going. The first of which is YC is going on a fall tour. If you want to see the dates and locations you can check out blog.ycombinator.com. We have all that stuff up there. Second of which is the winter 2018 application is open. That is at ycombinator.com/apply. Alright, here we go. Welcome to the podcast.
Elizabeth Iorns [00:55] - Thanks!
Craig Cannon [00:56] - How about we just start with, yeah, your just quick background.
Elizabeth Iorns [01:00] - Sure, so I'm Elizabeth Iorns. I'm the founder and CEO of Science Exchange, and I'm a cancer biologist by training. I did my PhD at the Institute of Cancer Research in London and then did a postdoc at the University of Miami and became an assistant professor there. And then, I left in 2011 to create Science Exchange and that was part of the 2011 Summer batch of Y Combinator. That's really where I first got involved with Y Combinator and then have subsequently continued to grow Science Exchange and then two years ago I joined, as a part-time partner, which is now called the Expert Program, here, to help out with the biotech companies that were starting to apply to Y Combinator.
Craig Cannon [01:38] - Okay, and so let's just get this out of the way. Very common question. It's like, "I'm a biotech company, like I'm a founder. Why should I do YC?"
Elizabeth Iorns [01:48] - Yeah, we definitely get asked it a lot, and I think there's kind of two camps. One is that there are people who have genuinely not heard of Y Combinator, previously, so they ask, "Oh, what is Y Combinator? Why should I do it?," more from a sense of, "I'm not sure what this program is. What will the benefits be?" That's more a generic answer of YC is a great starting point for companies that want to kickoff the launch of their company successfully. We provide a lot of expertise and resources around how to incorporate, how to really focus on building their first initial stage of creating part of that market fit, and getting a company off the ground. There's that kind of avenue and that's usually PhD students or postdocs who maybe haven't been exposed to entrepreneurship first, and I think that's a great program for them from that aspect. We definitely have more established biotechs or people who are in the biotech world and they sort of look at it like, "Well, why would I do that?," or, "Why would any biotech company want to do that?" Really, our answer there is around the tremendous access to capital and the expertise around fundraising, the opportunity to interact with really different sectors that you may not have been familiar with. We have a very diverse and cutting edge group of companies that are a part of every single batch. You actually get access to things like artificial intelligence, all of the technologies that are being developed in different verticals. You're exposed to those as you're part of the program, and that can really benefit the companies in interesting and unexpected ways as they participate. But, one of the unexpected ways is that there's been a lot of crossover funding that has occurred for the biotech companies. Many of our biotech companies have been able to raise significantly more capital than they would have been able to if they just sort of stuck with the traditional biotech venture world and not taking part in the program, and that's, I think, an area where people didn't expect that there would be such an appetite, but there has actually been over $200 million of capital raised for these companies already.
Craig Cannon [03:54] - How do you see a batch play out for an average biotech company? Because, one of the main questions I get during office hours is "YC's three months long. Like what do I actually do in three months? You know, this is like a decade long project."
Elizabeth Iorns [04:09] - Yeah.
Craig Cannon [04:09] - How does it work out, normally?
Elizabeth Iorns [04:10] - Yeah, so normally the company, similarly, actually to any enterprise company, right. Most enterprise companies are not going to be making really significant, sort of fundamental advancements in a three month program, either. But, what Y Combinator does is it provides that focus to really hone what is the company doing, what's the minimal, viable product that's required to get to the next stage. For us, a lot of our biotech companies are genuinely able to figure out what is their go-to-market strategy, very efficiently in the program, and, then, execute against that. They may not make really significant advancement in terms of the experimental work, but they certainly will make a significant advancement in terms of understanding the market and understanding what steps are required to get to the market in a way that allows them to then raise funding and capital that's required to take those steps. That is a pretty big deal in terms of just figuring out what you need to do and minimizing the noise and increasing the focus on what you need to do.
Craig Cannon [05:15] - Where do they put the money to work during YC?
Elizabeth Iorns [05:18] - It's not a lot of money. So...
Craig Cannon [05:20] - Yeah, exactly.
Elizabeth Iorns [05:21] - They really put the money to work through things like they may do some initial critical path experiments.
Craig Cannon [05:26] - Okay.
Elizabeth Iorns [05:28] - If they can outsource those experiments, then they'll often be able to get results quickly, and we have had a lot of success with that with our biotech companies where they've actually worked with external companies that are already up and running to do, for example, proof of concept studies or efficacy studies that they can then submit to the regulated authorities to get approval to the next stage. We've seen companies work with regulatory consultants to devise a go-to-market strategy and make significant advances in terms of their filing status. We've definitely seen people to be able to use that time to actually advance the company alongside with really planning and talking to initial customers and figuring out with their potential markets what would be required at each stage to get to the next level.
Craig Cannon [06:16] - You kind of talk about like market and figuring out go-to-market and a lot of these business ideas, basically. Do you find that a lot of biotech companies are bringing on a business co-founder? Or are they just like picking it up while they're going through YC?
Elizabeth Iorns [06:33] - I think they pick it up. I think there's... You know, I think one of the interesting differences between biotech companies and, sort of, software, just tech companies is that the actual market does not really that question. If you're a biotech company and you're going to cure Alzheimer's disease, there's no question of whether that's going to be a great market. That's, obviously, going to create enormous value. But, the question is more of the technological risk and how you de-risk the actual innovation that's being developed. For a lot of the time, we really focus on that de-risking and figuring out, for the biotech companies, what do they need to do to really significantly de-risk the technology as quickly as possible. Versus, the software companies, I think, there is questions around market, right? There is questions around how big could this really get. A lot of questions around execution strategy to get to market as quickly as possible and have a competitive differentiation over others that are doing similar things. Those are more those fundamental questions where business partners and marketing and growth hackers, and all those type of people come into play. But, I think with the science, mostly the scientists are, I think, fairly... Scientists... People have this kind of illusion that they're like anti-social or like they don't understand business, and I just like completely disagree with that. I think scientists have to be very articulate. They frequently present in front of large audiences. They write very complicated grant funding strategies. So many of these every day skill sets are already present in scientific stuff. It's actually like not really a need to have a business co-founder.
Craig Cannon [08:18] - By nature, like so many of these things are gigantic markets if you happen to like...
Elizabeth Iorns [08:23] - Yeah, absolutely.
Craig Cannon [08:25] - You said something that I didn't fully under... If I'm de-risking a project, what does that actually mean over the course of the three months?
Elizabeth Iorns [08:32] - Yeah, so de-risking is really around getting experimental data or actually looking at the go-to-market strategy for a particular technology. Mostly for de-risking technology is things like showing in an animal model that the therapeutic intervention is able to cure the disease or reduce the impact of the disease or in a cell model, or something like that. You're really looking for those proof points along the way. If you're starting out and your goal is to cure Alzheimer's disease, then your initial steps to get there will be to, one, come up with a biological mechanism that you think is plausible for the disease. You'll, then, need some sort of model system to be able to test how your intervention is going to impact that biological mechanism, and then you will basically develop a therapeutic, either an antibody or a medical device or a small molecule inhibitor, and you will add that into the model and see whether you actually improve the survival in that particular model. And then, you'll have to do basic studies around toxicity studies that are required to submit for an initial human study. Basically, all these steps happen before you're able to go into the clinic and test on people, "Does my intervention really work to cure Alzheimer's disease?"
Craig Cannon [09:55] - Okay, gotcha. In your experience, when people are applying to YC, how far have they gotten along that process? Because I imagine, there's probably a spectrum.
Elizabeth Iorns [10:04] - A huge spectrum. Yeah, a huge spectrum and it's very interesting because actually particularly that earliest phase of discovery, that is an area where there's significant under-investment, just generally, in the industry. Everybody wants these new molecules or new strategies that are at the clinical stage. If you have initial proof of concept data in a clinical phase, then you're probably already acquired, right. There's...
Craig Cannon [10:32] - Oh wow!
Elizabeth Iorns [10:33] - Oh yeah, so, I mean, people, like the pharma companies are desperate for buying an innovation. They're really looking for companies to get to that initial proof of concept in human studies. That's really where a lot of their innovation is coming from is biotechs that have got new molecules through to that point in the process, and the investment in that earlier stage, that's where there's a lot of challenges. Definitely there's investment from the academic setting, but there's a huge gap between what's done in academia and, then how do you get it into the clinic. That area of translation is called translational research, is just increasing focus on it, but it's definitely an area where we see a lot of companies apply. They apply when they have some initial data that suggests that they have an interesting approach to studying, to curing a disease, or to developing, for example, a new way to test for a particular disease. They're sort of at that stage. It's really that going from that initial experimental data, the discovery, through to actually having some initial proof of concept in the clinic that it works. That's the gap where we really focus.
Craig Cannon [11:54] - I don't have a PhD, like you do. So walk me through like... You know, say I'm doing a PhD program, which you said was seven years average?
Elizabeth Iorns [12:05] - Yeah, the median is seven years, yeah.
Craig Cannon [12:07] - In the US, I guess?
Elizabeth Iorns [12:07] - In the US.
Craig Cannon [12:08] - Yeah, because yours was like three or four?
Elizabeth Iorns [12:10] - Yeah.
Craig Cannon [12:10] - Okay, but overseas, yeah. At what point in the process would I start thinking about, "Okay, maybe this is a company," versus, like, "I'm just going to round out my seven years." So much time.
Elizabeth Iorns [12:23] - There's so much time.
Craig Cannon [12:25] - Yeah, and like complete it? I don't like, yeah, why?
Elizabeth Iorns [12:27] - You definitely want to it, of course, if you've invested...
Craig Cannon [12:30] - Yeah, I don't know.
Elizabeth Iorns [12:30] - All of that time. I think most people would want to complete it. But, yeah, so I think it's when you're getting to the end of your PhD, you're thinking about, "What am I going to do next?" Of course, like that's the excitement of you're finally finishing after all this time. It's time to go do something else. And, traditionally, that next thing was always postdoc. If you're going to become a professor and be an academic investigator, you would go to a postdoc, and that's a big shift that's happened recently. There's this pretty well known phenomenon called the postdocalypse that Ethan Peristein came up with which is this concept that there's so many postdocs now and no jobs for them. There's just nowhere for them to go in terms of staying as an assistant professor or professor in academia. Instead, you have to look for what are the alternative paths and you've already invested all this time and energy into your research and not all of it will be relevant to starting a company, but there's definitely people who've made some pretty significant advancements in that period of time, and they have something that might be commercially valuable. For them, the question is, "Do you go forward and just continue in academia?" And, probably, if you do that, you'll work on something different because you usually switch labs and go work on something different for your postdoc. Or, perhaps, you can think about taking that idea and that discovery and thinking about an entrepreneurship opportunity to turn that into a company. There's more and more acceptance of that strategy, obviously, so people have realized that. Leaving academia and going into industry is not so evil as it was once thought of because the reality is all innovations that come to market are through industry. You don't see drugs on the market that came from academia. They were all, many of them, discovered in the earliest phases, the basic research was done in academia, but then those were spun out into commercial biotech companies or pharmaceutical companies license them and took them through to commercialization. That is a long path, very, very expensive path. There's a big opportunity for these students to think about the discoveries they've made and say, "Well, maybe, I want to create this into a company, and maybe there's a real opportunity for me to actually take the discovery I made and really use it in the real world," as opposed to just in the academic setting which is often distance from the actual commercial application.
Craig Cannon [15:04] - Of course, yeah, and are there IP concerns that are specific to biotech companies that someone should be thinking about?
Elizabeth Iorns [15:09] - Yeah. Absolutely.
Craig Cannon [15:10] - Okay.
Elizabeth Iorns [15:11] - IP and biotech is like very, very critical and this is something that's very challenging, actually, with academia.
Craig Cannon [15:17] - Yeah.
Elizabeth Iorns [15:19] - Intellectual property is fundamentally the cornerstone of a biotech strategy because you need to own the intellectual property in order to invest all of that development time and money that's required to go through clinical studies, to get it out into the market, and then you need some window of exclusivity around the intellectual property to sell your compound before some generic manufacturer comes and sells it for $2, right? That's really why IP is so important in this space. It's not because people are inherently trying to be greedy. It's just that there's such a lot of dollars invested in these molecules and the development of them that then you need some kind of time period at which you can recover that investment, or else it's just simply unsustainable, there is no path to actually developing those drugs. In academia, most intellectual property is owned by the actual university. When you..
Craig Cannon [16:14] - Completely?
Elizabeth Iorns [16:16] - Yeah, so when you are working in a university, your IP belongs to the university and then there is path to actually license it from the university. Essentially, you have to go through that process of licensing the intellectual property to develop the company. For most PhD students, there is an exception where they're not subject to it. It really depends on the specific program. That's another area of complexity to have to research, but for professors and postdocs, definitely, the intellectual property generated there belongs to the university.
Craig Cannon [16:55] - How does that work for an average YC company? Do they license it prior to YC?
Elizabeth Iorns [17:01] - Yeah, so they... Not always prior. They will have... One of the things we do during the program is help them with strategies around licensing, intellectual property, figuring out who can they work with to do that.
Craig Cannon [17:13] - Yeah.
Elizabeth Iorns [17:13] - Like how does it work at the university. There's a Tech Transfer office and a Sponsored Research office at each university. You have to interact with them and figure out a compelling business case for why they should license it to you. And, usually if you're the discoverer, then there is a compelling business case for why they should license it to you.
Craig Cannon [17:31] - Okay, gotcha. Then, what about what happens after the three month period? What's a fundraising process like for a biotech company?
Elizabeth Iorns [17:41] - Yeah, it's really interesting, actually, because we don't have tremendous amount of data on this, so far, because the program has only included biotechs for the last couple of years, but has been really interesting is that there is a lot of appetite from early stage technology investors for funding biotech and interesting science companies, in general. We've seen many companies raise pretty large rounds straight out of YC, from a seed funding perspective, so several million dollars or more. Then, it's that path of how do you get to that next stage for the institutional round, so the Series A round, and we've only just started to reach that point with several of the companies and they are raising rounds. We're definitely seeing success with them being able to continue to fund their companies even at the later stages, but we don't have a lot of historical data to go back, three or four years. We're only at this sort of two year mark.
Craig Cannon [18:39] - Hmm, do they tend to raise from, funds out here, or do they go, you know... Are they raising money in Germany? How's it going?
Elizabeth Iorns [18:47] - Oh, interesting. Mostly here. Definitely a lot of Silicon Valley funds are doing investments in this space, even funds that people may not have thought about, traditionally. Khosla Ventures has done a lot. Andreessen Horowitz has done a lot, Data Collective, Founders Fund. There's a lot of funds like that. ...NEA, that are interested in science and interested in, not just software applications, but really interesting companies that are combining insights particularly from the software world into the actual biological world. That's an area where there's been a lot of interest in investment.
Craig Cannon [19:27] - It's actually much more like a traditional fundraising path than I thought. I don't know why figured that it was coming from other sources.
Elizabeth Iorns [19:30] - Yeah, definitely. In the biotech world, generally, there's kind of two ways that people raise money. One is, if they are sort of unknown, and they're young and they haven't got any history of doing successful biotech companies before, then that would be one of the paths they do it is to come and do something like Y Combinator, get some area of growth, and de-risk their strategy, right, and then they can raise money. But what we've seen historically in the biotech sector is very much like the old-school days of raising funding, as a software company, where a lot of the funding was going to repeat entrepreneurs, people who... Basically, these funds will create... They'll basically license in a discovery and then they'll create a team, internally, to develop that to a certain stage and then spin it out and put in a professional team of, like a professional CEO and everything to run the company. That's a much more common sort of path that the biotech funds would take to developing companies. There's almost an internal incubation strategy that then spins out companies.
Craig Cannon [20:45] - And that's been effective?
Elizabeth Iorns [20:47] - That's very effective. That's like Third Rock, Atlas, Polaris, Flagship... That's all of those big funds take that strategy and its very successful. They have created a lot of the most well funded and recognized companies that you probably have heard of in the biotech space. But, there's also the opportunity to look at the landscape in a more broad setting which is, what else is there? If you just fund, like, the same people over and over again...
Craig Cannon [21:16] - Yeah, of course.
Elizabeth Iorns [21:18] - Then, yes, they'll be like efficient. They'll understand what it takes to do this, but you'll also miss out on all of the other innovative, different thinkers who are out there who actually make the discoveries, like the PhD students and postdocs, the ones that actually made the discoveries. Then, if you can provide a path for them to also participate as founders and as entrepreneurs, they potentially have a lot of inside knowledge about the discoveries that they made that can help those companies succeed. What we kind of missing is the funding and the mentorship because it is a steep learning curve to navigate how you take a drug to market through all of the regulatory hurdles. If we can build a path that supports those people more effectively, that's going to be, I think the killer sort of application. It's going to be how do you get a lot more of these shots on goal and actually get a lot more people involved in the biotech innovation ecosystem developing companies and bringing drugs to market and not just staying in academia.
Craig Cannon [22:20] - How do you advise folks when they... maybe you do office hours or maybe you do a YC event, or someone just emails you. Say I'm a PhD student, like, what's your advice to me?
Elizabeth Iorns [22:31] - Yeah.
Craig Cannon [22:31] - And I'm working on something that I'm excited about, but the whole thing is completely foreign to me. We were talking about before, you met with PhD students and they thought the money that they raised was a loan, wasn't an investment.
Elizabeth Iorns [22:46] - Yeah.
Craig Cannon [22:46] - They would have to pay it back if it didn't work out.
Elizabeth Iorns [22:48] - Yes! I think that's just an education in the ecosystem thing where I think if you're a software developer, you kind of know about entrepreneurship. It's become such an essential part of the ecosystem that people just inherently understand. How does entrepreneurship work? How do you start a company? What are the basics? But, that's not the case for a lot of PhD students and postdocs. They may not be exposed to that world at all. I found it very interesting when I was talking to them when I basically gave presentations for alternative careers. There's this whole alternative careers focus in the industry because for PhD students and postdocs in academia, like I mentioned, there's not often a job path that exists for them to become professors. There is actually a focus on saying, "What other alternative careers are out there?" Obviously, one of those alternative careers is entrepreneurship. I've talked to some of these groups, and I really did get questions like, "Okay, well what if my company fails? Will I have to pay back that money? Will I be personally liable?" Just removing those misconceptions. I can't even imagine... all of the questions around starting a company. You're worried about, job path and, "What if it doesn't work out," and, "Will I be able to get a job if it doesn't work out?" All those questions are still there and scary. But, you'll also have, so much misconception around even things like "I'd have to pay back money that I raised." That is, to me, a big red flag that, this particular sector just doesn't even know what steps are required and, doesn't understand the path to being able to start a company and doesn't realize that there's real opportunity to do this in a way that isn't as scary as it looks. If you take part in programs like Y Combinator, it really does sort of provide you with the framework and the confidence to know that you're incorporating your company properly, you are not personally at risk when you do this. Obviously, if the company fails then you have to think about what other job you're going to do. But, I mean, at the same time, there's a huge degree of risk of staying in academia when you're at that stage in your career, because there's no job certainty. You're definitely, like, "What's going to be my next job? I don't know, I could be a postdoc forever." Which is really difficult, so...
Craig Cannon [25:17] - Is that what's happened with your... Because you were in Miami right?
Elizabeth Iorns [25:21] - Yep.
Craig Cannon [25:21] - When you started Science Exchange.
Elizabeth Iorns [25:21] - Yep.
Craig Cannon [25:24] - What's happened to the people you were working with? How have their careers progressed alongside yours?
Elizabeth Iorns [25:29] - Yeah, that's a good question. A lot of them have done some pretty interesting things, actually.
Craig Cannon [25:36] - Yeah.
Elizabeth Iorns [25:36] - One of the students that was in our lab that he actually did start a biotech company with my mentors. They started a biotech company together, which is pretty cool.
Craig Cannon [25:45] - Yeah, that is really cool.
Elizabeth Iorns [25:47] - I definitely think that there's more and more people doing this and particularly if they see other people doing it. Then, it gives them one, a person to ask, like, "How did you do that? How did you, like, figure out the next steps? Can you introduce me to people that can help me?" Just having more colleagues that have done similar things allows you to explore it as an opportunity for yourself. So...
Craig Cannon [26:13] - Are you still reading journals? Can you mention this stuff?
Elizabeth Iorns [26:16] - Yeah, still do. Yeah, I love science.
Craig Cannon [26:19] - What's the cool stuff coming out? I mean, I guess you read applications, too, for YC? Maybe, there's like a particular focus. What are the things that are right on the edge, you feel like? You know, like, ten years, realistically, to reaching market that you're excited about.
Elizabeth Iorns [26:35] - Well, there's a lot of things that are really exciting at the moment and I think science, in general, it's like a huge broad area. I try to stay on top of the areas where I have like the deepest understanding. Cancer biology is obviously, for me, an area of intense interest. We actually see a lot of those new technologies and new advancements through Science Exchange, actually, because we sit between the pharmaceutical companies that are outsourcing their R&D through us and we also work with lots of early stage biotech companies. And then, on the other end, we have all these actual service providers that are running the experiments for them. We sort of see, "Oh, that's interesting." People are starting to do this differently, or they're starting to think about the next stage or they're looking at this new therapeutic area. At the very cutting edge, that's mostly still coming from academia. You're seeing those, in journals like Science, Nature, Cell, and there's some really interesting work that's happening. But, for me, the applied area, that's probably one of the more interesting areas, is looking at things like the application of artificial intelligence in the biological sector. There's some pretty interesting work that's occurring around how to be better at predicting efficacy or toxicity in the pre-clinical stage so you don't have clinical failures. There's a lot of innovation in that space. There's actually some interesting innovation, even, in the design of clinical studies. How to more quickly get initial data in humans that will tell you whether or not your application is likely to work. Historically, people would do phase one, which is basically just like a dose escalation study where you're just looking for toxicity. And then, you would do a much larger study, afterwards, where you were looking for efficacy. That's really time consuming and expensive and people are starting to say, "Let's look for, like, endpoints that we can use, more quickly, in those initial, versus human studies that can give us a sense for whether our targets are going to work." I think there's a lot of innovation in that space, which is pretty exciting. And, I'm sure you've seen, like, everyone's talking about editing of human embryos with CRISPER. All of these things are..
Craig Cannon [28:52] - Well, this is like, yeah, this is like the random question section. Okay.
Elizabeth Iorns [28:55] - Yeah.
Craig Cannon [28:56] - Where do you fall in CRISPER? Are you into it?
Elizabeth Iorns [28:59] - Yeah, I'm very excited about CRISPER. CRISPER is game-changing. It allows us to do things that, in the past, we only dreamed about.
Craig Cannon [29:06] - Yeah.
Elizabeth Iorns [29:06] - Actually, for my PhD, I worked on RNAi screens and RNAi screens were the first technology where you could basically inhibit gene expression, but you couldn't knock it out completely.
Craig Cannon [29:19] - Okay.
Elizabeth Iorns [29:19] - You would be systematically knocking down the expression of a gene, maybe 50% or 60%, but...
Craig Cannon [29:26] - Over generations?
Elizabeth Iorns [29:26] - You couldn't... No, no, just in real time. Like, within a couple of... Basically, RNAi works within like 48 hours.
Craig Cannon [29:32] - Oh, wow.
Elizabeth Iorns [29:32] - And it's only transient unless you create like stable cell lines. But, so you can knock it down, transiently, and then see the effect, but it was so error prone because you couldn't really control it that well and you would knock down gene expression like 50% and you would be like, "What does it really mean?" Versus, if you knock out the gene and it's no longer there, or you create a mutation that truncates the gene and it's no longer expressed, then you're good, right, it's gone. You know for sure what is the functional fit of doing so. We had to a ton of issues with artifacts and challenges in that space with RNAi, but it did lay a lot of the frameworks for some of the really interesting applications of CRISPER. Now, not in the therapeutic space, but doing, like, high throughput screens where you basically knock out every single gene. And, for the first time, you can do that, at scale, and understand what is the function of every single gene, right. It's incredibly powerful.
Craig Cannon [30:28] - Where do you think CRISPER, assuming everything gets tested, it goes all the way through. Where will it start to see traction, first?
Elizabeth Iorns [30:37] - I mean, it's already, I think, there's some really, interesting applications that people are looking at. The most obvious application is to edit genetic defects. If there's like a lethal genetic defect, being able to correct that. Definitely, there's a lot of innovation in that space. Actually, there was just a recent application of it for RNA editing. That's the expression of the gene. Rather than editing the gene, itself, editing the expression of the gene kind of transiently.
Craig Cannon [31:06] - Okay.
Elizabeth Iorns [31:06] - Which is pretty interesting. I think, the area, you'll see less of a regulation barrier, because you're not editing the actual genetic code. You're just editing the end product.
Craig Cannon [31:18] - I have one more question. People in Silicon Valley seem to continually be obsessed with life extension.
Elizabeth Iorns [31:26] - Yeah, they are. Yeah, they really are.
Craig Cannon [31:29] - Yeah, I always wondered how that like correlates to even just fundraising. Like, what gets funded, here. People are like, "Oh, I can live forever, finally." Have you been following, calorie restriction all of this. Obviously, you work with cancer, too, it's related.
Elizabeth Iorns [31:44] - Yeah.
Craig Cannon [31:46] - What is real, and what is just hype, right now, that people are paying attention to regarding life extension?
Elizabeth Iorns [31:53] - Yeah, I think there's... It's a challenging space, as a scientist, for the main reason being that there isn't really assays. You know how I was just talking about, earlier on, like models that you can use to understand the biological mechanism of a disease. For example, in cancer, you can say, if I create certain genetic mutations in a normal cell, it then turns into a cancer cell, and I can tell that because it does certain things that it wouldn't do if it was not a cancer cell. It will form a tumor in a mouse, or it will grow in suspension where a normal cell wouldn't. These kind of basic assays that you can use to understand better what you're looking at. With aging, or longevity, that is more challenging in the sense that in model systems, we have C. elegans is a good model that they use a lot where they're looking at these nematode worms and saying, like, "How long do they normally live?," and, "Can we extend their life?" But, a lot of that research, it's difficult to know how it translates into humans. You don't have really a good endpoint in a human system. People have used telomeres, telomeres length, as an endpoint, but I don't think that is very well established. You actually see a lot of noise in that particular endpoint. It's hard to know if you do this intervention in a nematode and it extends the life span. If you do that intervention in humans, you're going to have to wait a really long time to know whether it actually worked. That clinical study is very difficult if you don't have a secondary endpoint that you can measure.
Craig Cannon [33:38] - Okay.
Elizabeth Iorns [33:39] - Think about cancer research that you always are looking at extension of life or reduction of tumor size, and these are in patients where they have advanced disease. You're going to see in a very short window. If most of them are going to die in one year, you can quickly see does the drug extend their life, and you can actually monitor their tumor size in real time. Does the drug shrink the tumor? Those are the endpoints you're looking at so you can quickly tell does this drug work? For the longevity research, it's like what is the endpoint we can use to say that our interventions are having an impact in the clinical setting. There's a lot of interesting research that's happening. Certainly, Silicon Valley even made fun of it, but the parabiosis workers.
Craig Cannon [34:24] - Yeah.
Elizabeth Iorns [34:24] - Obviously, fascinating. Very, very interesting work. The calorie restriction stuff's been around for awhile. There's actually like a lot of controversy there because there is mixed effects that you see in different models. For example, in some strains of rodents, if you do calorie restriction, it actually decreases their life span. And, there's two primate studies that were done. One, which it extended life spans, and, one, in which it decreased life span. The work in the pre-clinical setting and animal models is pretty mixed for calorie restriction. Again, we don't that endpoint to really measure and say if it works, or not. And then, with parabiosis, which is the other kind of big, trendy area, right now, they have...
Craig Cannon [35:11] - Can you explain that if people don't know what that word means? It's kind of terrifying.
Elizabeth Iorns [35:12] - Yeah, so that's, basically, it's kind of... I don't really want to... I know, I don't know if I want to say, it's like, it's so into animals to get an old mouse and a young mouse and like connecting their blood streams so that the old mouse and the young mouse are receiving each other's blood. But, that's then being done in a less, like, sort of dramatic way through actually just harvesting blood from young mice and injecting it into old mice. That's being done that way and so, there, you also see an effect. What hasn't been very successful is trying to figure out what causes the effect. When people have tried to analyze the blood of young mice and old mice and say, "What is the growth factor, or the hormone, or what is it that's causing this?" There's been controversy over what it is. Some people have published certain factors that other groups have not been able to reproduce the effect. That area is still unknown.
Craig Cannon [36:17] - Okay.
Elizabeth Iorns [36:17] - And, obviously, if you could find out what it is, that would be huge because you could make a recombinant version of it and you wouldn't need to take, young blood and inject it into old people. You could just take this recombinant factor, or group of factors, and just use that as a supplement, as an injection or whatever it needed to be.
Craig Cannon [36:38] - Okay, so right now it's like time for snake oil, basically.
Elizabeth Iorns [36:42] - Well, right now, it's still very very much in that stage of figuring out, figuring out how to apply it. The hard part is getting that initial, robust result. The fact that people are consistently seeing that if you take young blood and inject it into the old mice that it has an impact is actually, very exciting. Most of the time when you're doing fundamental research, you're finding something that seems interesting, but then the more you study it, you realize it was just an artifact.
Craig Cannon [37:13] - Oh.
Elizabeth Iorns [37:14] - It's mostly disappointment. Then the fact that people have consistently see this is pretty interesting.
Craig Cannon [37:21] - Interesting. Okay, last question. Are you applying any of this stuff to your daily life? Do you have any weird bio habits that you're like taking different, whether it's like a medicine, or supplement, or you're fasting, anything like that? Are you doing any of this stuff?
Elizabeth Iorns [37:36] - The one thing that I am trying to do, but it's so hard, is to do fasting. I used to try to do it every couple of weeks, but, honestly, I only managed to do it once a month, because, for me, if I don't eat for a whole day, I end up like just unable to function properly. I have to choose like a Saturday or Sunday where I don't have to do anything because I can't really function well enough to do it on a work day. But, I definitely think there's a lot of science, there, around fasting, improving your metabolic control, and just, in general, for me, when I do it I feel my appetite control is a lot better and it just seems to have good impact going forward. I definitely... Like, that's one that I do think people, like, "Oh, it seems kind of hype-y." But, I think, the science is there.
Craig Cannon [38:26] - Like 24 hours?
Elizabeth Iorns [38:27] - I do it from the evening through like the whole next day, through to breakfast the next day.
Craig Cannon [38:34] - Okay, so it's like 36 hours.
Elizabeth Iorns [38:34] - 36 hours, yeah.
Craig Cannon [38:36] - Interesting, but, yeah, you're kind of like slower during that fasted state?
Elizabeth Iorns [38:40] - Well, my brain just doesn't work at all. I just have to watch T.V. or do nothing useful because I can't think properly. That's the downside of it, but I do think it seems like it has some benefits. I don't take like supplements or...
Craig Cannon [39:02] - Nootropics, none of that stuff?
Elizabeth Iorns [39:03] - No, none of that. I should probably research more into it, but I haven't so far. I'm very interested, I have some theories myself, around these things, but one of the things I'm very interested in is individual responses to food. I think that all of the research that's been done on diet and dietary interventions, if you actually look at the clinical data, it suggests that there's a subgroup of people that respond to that dietary intervention very well, but the vast majority don't, really at all, and so you get this kind of modest effect. If you do things like Paleo diet or, any of those diets, you have a small group of people who lose great a lot of weight. And then, most people don't really lose much weight, and so you just have a small effect. It would make sense to me that there's actually different responses, as individual people, because if you think evolutionary about how to have a diverse population of people, you would never want to be everybody responds the same way to certain food availability, because if there was a famine of a certain type of food, you would lose the whole population. It kind of makes sense that you would have diversity in the types of diets that people respond well to. That's an area where I think there's some initial data that looks pretty interesting around personalization of response to foods.
Craig Cannon [40:34] - What are those studies called? This is fascinating. What would I look for if I want to learn more?
Elizabeth Iorns [40:40] - Most of what's really at the cutting edge there is actually around measurements of things like insulin response to certain food types. People are actually wearing like insulin monitors, like continuous insulin monitors, to like look at things, glucose, insulin levels, trying to understand people's response to food for those kind of key hormones. That's an area where you could probably research it. It's pretty cool.
Craig Cannon [41:10] - That is pretty cool.
Elizabeth Iorns [41:10] - Yeah.
Craig Cannon [41:11] - Alright, well, thank you for coming in.
Elizabeth Iorns [41:13] - Great, well, thanks for having me.