mRNA Hot Takes: Building A Solid Foundation For Your RNA Company & Products

Welcome to Advancing RNA's mRNA Hot Takes, the show where we talk about serious RNA things, but with a spicy twist. Here, in episode 1, Advancing RNA's ARW sits down with Radar Therapeutics' Sophia Lugo and Entrée Bio's Michelle Lynn Hall to discuss the biggest mistakes that can be made in building an mRNA therapeutics company—and much, much more.

Hot Takes Episode 1 Transcript

Anna Rose Welch: Hello everyone. Welcome to the first episode of Advancing RNA’s new mRNA Hot Takes, the show where we talk about serious RNA things, but with a spicy twist. I'm your host Anna Rose Welch, the editorial and community director of Advancing RNA, and I am beyond thrilled and honored and somewhat surprised a little bit to have found several people to embark upon this adventure with me. So, I'd like to give a really big virtual round of applause and my endless gratitude to the two powerhouses joining me today.

We have Sophia Lugo, CEO of Radar Therapeutics, and we've got Michelle Lynn Hall, general partner of the VC firm Entrée Bio. Thank you both for choosing to join me on this wild journey that we have before us. The concept is simple: We're going to talk about the scientific and business world of mRNA, and we could of course do this the normal way, like we're doing right now, where we just sit and stare at each other and talk about cool things on camera. Or, we could shake things up a little bit and we could have these conversations while doing something a little bit riskier, a little bit off the beaten path. Perhaps while eating hot peppers? I know. So excited.

Michelle Lynn Hall: Yes, but you asked two Texans to embark on this journey with you, which was perhaps a strategic error.

Welch: I know. I know.

Sophia Lugo: I think that's dangerous for you.

Welch: I was born and bred in Pennsylvania and these two are from Texas. So really this is mostly just going to be an exercise in getting my ass handed to me.

Hall: Potentially.

Welch: I'm really glad that you guys are here to enjoy this with me. So obviously as we all know, I chose the crazier option of doing this with hot peppers and some women from Texas to really show me up. So, ladies, the Pepper Gods have spoken and over the course of the next six episodes, we're going to be facing down a variety of spice options, whether that be mild-ish to nuclear-ly hot. And I guess my main question is, are you guys ready? Are you ready to embark on this journey?

Lugo: We're more ready than you.

Hall: We might regret that, but yeah, I think so.

Welch: It's sad, but it's so true. It's so true. We're going to be starting today with the classic jalapeno. I have brought a whole jalapeno with me and I'm going to try to eat this raw.

Hall: Wait, you're from Pennsylvania, don't you say ja-lop-eno?

Welch: Maybe. Maybe. Maybe not. All right. Here goes nothing. That was a big bite.

Hall: Nice job. And was that the seed end of it?

Welch: No. Nope, not yet.

Hall: Cheating.

Lugo: That's cheating. There’s no pain in that.

Welch: It's spicy. It's spicy already.

Hall: Pennsylvania girl.

Welch: Pennsylvania girl. Okay. Alright, so now that I have done this, I have to force myself to speak. Sophia, you're first in the hot seat, so you're going to get to join me in this land. So obviously you are the CEO of a startup that has come from academia – what's that?

Lugo: Sprayed jalapeno on myself trying to cut it in half.

Welch: I would like to start by asking you what are some of the biggest missteps for a company such as your own that is spinning out from academia, one that has to establish a foundation license agreement. So as we're thinking about the foundation of building a business — as this is our first episode, and I'm all about foundation building here — what would be some of the biggest missteps you think companies can make as they're coming out of academia and starting out into the business world?

Lugo: Okay, so I guess first I take a bite.

Welch: You do.

Lugo: Okay. I cut it in the middle. It's got the seeds, and I've got my Trader Joes pickled jalapenos too, and the seeds are right there.

Hall: Okay, okay. Let's see what you’ve got.

Welch: Should I take another bite? I feel like I should take another bite.

Lugo: I've got my seeds in me. I’ll also take a pickled one because I just like pickled jalapenos.

Welch: She's showing me up.

Hall: She's showing off. Yeah, she's a hundred percent showing off.

Lugo: Oh, if you want me to show off.

Hall: Okay, now I'm intimidated.

Lugo: My dad actually is a chili farmer in Mexico, so it's kind of a non sequitur, but it could scare people. I don't know. Anyway, the question was about the missteps that people can make in spinning out of academia. It is true that one of the first steps when you're an academic spin out, you are essentially taking something that was invented in academia and turning it into a company. One of the first things you need to secure is the license. If you don't have the license, you can't really be a company. I talked to a lot of people about this, and I really feel like what makes a company successful is the science and the business coming together. And if you're evaluating an early-stage company, one of the first ways you can know if the scientists actually care about economics or can make this into a business is to watch how the license agreement is negotiated. Because it is not about the science. It really is about the economics of the invention.

So red flag number one is thinking ‘my lawyer will handle it.’ I’ve talked to so many founders who are like ‘my lawyer's negotiating the agreement.’ Wrong. Your lawyers are not responsible for the economic terms. Lawyers' interests are making sure that they bill a lot of hours, A, and that B, they mitigate risks, that their client gets repped and they don't get sued. They do not get impacted if you make a license with shitty economic terms, so it is your job — in fact, it doesn't have to be you, the founder, or you, the scientist. If you do not feel like you can model the economic impact of the major terms of the licensing agreement, then it is your job to find the best person who can do it to do it for you and argue it very strongly. It doesn't matter who it is, but somebody has to do it well on behalf of the company.

Somebody has to own the economic model. Somebody has to own the financial model. So that is step A. If you hear ‘my lawyer is doing it’— wrong, that is bad, and they will probably be bad terms. I talked to the CFO of a later-stage company who, if he comes in right pre-IPO or for public companies, says the first thing he often does, if it's an academic spinout, is to renegotiate the license because the terms are so bad that they make any partnership NPV negative or even they could block [mergers and acquisitions], they could block a sale. They could make it so that the royalties are going back to the university and there are no other winners except for the pharma that probably has to sell your drug.

Hall: A hundred percent what she said.

Welch: I was just going to ask, what are some of the red flags that you typically will see in some of these situations?

Lugo: I'll say another thing — you are negotiating with people when you negotiate a license agreement. These people have interests. The interests are not actually the person you're negotiating with; they are not getting anything from the economics of the terms that you end up deciding on. They do have to ensure that the university gets a fair share for what they put into the invention. Stanford, for example, had foundational equity in Google that served them extremely well. They've gotten a taste of that. They want to be able to fund future research. They want some of those dollars to go back to the lab. They want dollars to go back to the university. They also typically do want to see their students succeed and they want to make sure that the pie, that they don't quash the pie. They want to make sure the pie is big enough that everyone can partake in it.

Licenses are interesting because they're basically legalese and scientific jargon all jumbled together, so you cannot expect your licensing officer to fully understand your technology and what it does. It is your job to tell them what it does. It's your job to tell them the stage of development that will matter. If something is ready to go into clinic, that is different than a lot of new RNA technologies, which are pretty far from the clinic. Often at the academic stage they're still in vitro. That's where we were. You have to tell the university, ‘This is the amount of money I actually have to put in to make the invention translational, and we shouldn't have to pay you for that.’ So, you have to tell them what your technology does, what it's going to be applied to, if it's a platform they should know, and how you expect to bring this to market. For mRNA technologies, especially if you try to develop a pipeline, it is very — I'm going to have more peppers. I feel like I don't feel anything honestly, but.

Hall: You seem way too chipper.

Welch: I mean my tongue is on fire, but I still feel like I should be eating more peppers, so continue.

Lugo: I also just like eating peppers. If you have a platform product, it's likely you're going to be creating pipelines of products. The first major platform tax you're going to hit is — and you're probably solving a piece of the puzzle because mRNA is so complicated that many pieces of the puzzle have to come together — but one of the major economic terms in a license is the non-royalty sublicensing consideration. This basically applies to anything that's not a royalty on the drug, so not eventual sales, but it can be an upfront, it can be equity, it can be milestones, it could be non-R&D reimbursement from, say, a deal with a pharma or another company. The university will want to take a chunk of that because they'll say they helped invent that foundational tech. The university is going to give you a template of what they typically do. You should actually be ready to make them understand how those terms might make a deal NPV negative. You should be prepared with ‘what do deals for these kinds of technologies look like and at what stages of development’ and you should be prepared with comps. And yes, you should look for comps that are other deals that the university has done with technologies that might be similar to yours, so you could tell a university, ‘you signed this agreement before, this worked out super well, you might want to use Beam or Moderna or Alnylam or something that worked out super well. You signed this before, these were great terms. You probably got money out of this. This is kind of what I want.’

Do not accept a template. Just be ready with what you think makes sense knowing that this is a term you're probably going to have. You have to show them the story of ‘We are going to be doing platform deals. It is very likely.’ There's hardly a successful company that's done two to three therapeutic areas. It is likely you're going to have to partner if you're doing more than one therapeutic area, and even if you're doing one, because it's so complicated, and you do not want to kill those deals with non-royalty sublicensing considerations. So, you should be ready with that. You should be the one coming prepared. They are not responsible for that. You are responsible for that. And honestly, the more prepared you look — comparables, models with sensitivity tests, et cetera, et cetera — the more they'll believe you. It is so important, and again, not your lawyer's job. This is your job.

Second, the next platform tax: royalties. Something that you could quickly kill a company is royalty stacking. There is no way that your one foundational tech is going to be the entirety of an mRNA product. There is no way you have developed a novel lipid or other delivery vehicle, and the payload, and the cap, and UTR optimization, and regulatory control elements. You're probably going to be a piece of the final composition matter or the final invention that's actually going to get to patients. And if each of these asks for 5%, let's just say the lipid asks for five, the cap asks for five, and this other one asks for five, then that's 15%. And then on top of that, if a pharma is going to help you take that through the clinic and get it to market, they are going to take a huge chunk of royalties. So do not kill yourself on royalty stacking. For universities, they know, they've seen it before, but it's your job to tell them.

You typically want to negotiate a floor, but you're going to want to negotiate, also, a floor and a ceiling and ways to step it down if you're bringing in other technologies. Again, part of this process is also convincing them, ‘okay, we actually developed it this much in university. We're going to put in this many millions of dollars to get it to — again, use comps, like places that other companies were when they took it out of the university and you gave them these terms — so we should be the ones taking the economics for this. We're happy to pay you for that.’ These are two major ones, but there are so many ways that you can kill a company through a bad foundational license agreement. It is the first negotiation you have to do. And it is not just good science that makes great companies. Yes, you have to invent breakthrough things and that's really hard. And then you actually have to execute on it. And this is the first time you can really show you actually care about economics. Yeah, I have many more things to talk about.

Welch: Oh, I'm sure. You've lit a fire under us. I think all the extra jalapenos really came through there, I think personally. But I saw Michelle, you were nodding quite a bit. Is there anything that you had to add? Are you in agreement? Is there anything else that sort of jumped out at you as being particularly important? Or do you think Sophia covered it?

Hall: Oh, all I'm thinking is I need Sophia to write a primer that we can circulate widely to anybody thinking about that. It's beautiful. And I've seen the other side where on the buy side, we've looked at companies who were very mired in extremely unfortunate terms with universities, and we walked away for all of the reasons that she articulated. So yes, it's extremely important.

Welch: Michelle, it's kind of your turn to show us what you have done to your pepper. You're going to get fancy with us.

Hall: Well, it was kind of an accident. I had a batch of peppers from the farmer's market that I was roasting, and I accidentally roasted my jalapeno. So, it looks a little sad, but you should trust me.

Welch: It's on a beautiful white plate though. It actually is very artistic.

Hall: I am so glad you mentioned that because this white plate, fun fact, was brought over from Europe. This is from the USSR, if you can believe it. And if my husband saw that I was using this plate, not just cherishing it because it's a USSR relic, he would be a little mad. But you know what? You liked it, so I think it’s fine.

Welch: We're honored that you are using your fine USSR china.

Hall: USSR china, yes. I'm not kidding. It even says on it ‘from West Germany.’

Welch: Yeah, that's incredible. Wow. So, you have just secured a new position, right? You are a general partner now for a VC firm, but you have had quite a few different experiences in your life. You've worked across tech, you've worked in biotech, you've worked now in pharma, now you're on the VC side of things. And one of the biggest differences, I think, again, as we're thinking about the foundation of our science, of our businesses, there's a lot of differences between how, let's say, the tech industry handles certain things versus the pharma industry. If we're thinking about openness, transparency into an invention, tech will iterate and share their learnings, whereas pharma will tend to patent things and kind of keep things close to the chest. So, my first question for you is going to be focused more on what you feel are some of the most defensible — in terms of patentable — or again, defensible attributes of our RNA products. Let's start there and we'll see where that takes us.

Hall: All right, I'm ready. I'm going to take some. All right. Just for the avoidance of doubt, here I am cutting it.

Welch: With a fork, too.

Hall: I did bring a fork. Listen, I'm a lady. Okay? No matter what anybody tells you. All right, just, again, there's seeds in that puppy. Let's see how it goes. If it's not too bad, I will eat the rest of it. Good. The roasting is really nice.

Lugo: I want roasted.

Hall: It's got a good kick.

Welch: Does it? I was going to ask.

Hall: Hang on, Sophia. Really? Wow.

Lugo: I feel like yours are spicier now.

Hall: It was a good punch. It was a good punch. Does the roasting make it spicier or are you just tougher than me?

Lugo: That's a good question. I don't know.

Hall: Hold please.

Welch: Oh, she's already at the milk.

Hall: Listen, I'm fine. It was good. I'm fine. It's going to take a while. Alright, so defensibility. So — I'm not fine.

Welch: I'm from Pennsylvania and I'm still able to talk.

Hall: I'm going to say it's because it was roasted.

Hall: So, defensibility. To me, there's patentability and then there's knowhow, right? And I would say that there's a lot in the knowhow space that is extremely defensible. One of the things that drives me nuts is people often think about the mRNAs as this one little thing, the LNPs as this one little thing, and then the way you scale it up as one little thing. I'm using LNP here as a placeholder knowing that obviously there's other ways to encapsulate it. They treat these all as sort of independent things that you can do, independent structure-activity relationships, and you can’t. It’s one big, mushy, interconnected nightmare. And so, the know-how around how to make all of those components play well together, both physically and biologically, it's a little bit of witchcraft and voodoo, right, on a bad day, and it's engineering on a good day. And I think that engineering and that complexity is I think part of what makes it both extremely daunting, but also for me, a really fun area. And I think that is the thing that I really view as differentiating people who are tinkering from people who are really going to make really substantial impacts with these types of therapies. To me, that know-how and how it all comes together to create these drug products that many of us have now had injected into our arms, that's the most defensible part.

Welch: If we're thinking too about how new mRNA companies are coming out into this world, you mentioned, this is going to be separating sort of the tinkerers, I like that word, from the, let's say the artists, the true artists in this realm. What do mRNA companies have to do to remain competitive in this space and to remain, to keep their know-how defensible outside of patenting, right?

Hall: Yeah, it's interesting. It's not just mRNA companies. I'm going to use genetic medicine companies writ large because I have many soapboxes, and another soapbox of mine is that mRNA is used for a bunch of different things, including but not limited to DNA editing, right? So, let's just say genetic medicine companies, because also, to me, one of the beauties and annoyances of genetic medicines, including oligos through viral and non-viral stuff and including the mRNA vaccines, is that they are so complex. And I think I might challenge what you said — that a lot of people treat it as artistry. I think the people who are really going to be competitive and excel and bypass all the competition in the future are going to be the people who treat this as an engineering problem.

Years and years and years ago, back when I was a small molecule computational chemist, I was really interested instead in genetic medicines, not because I don't believe in small molecules. I love small molecules as much as the next person, but if you think about the high dimensionality of a genetic medicines problem, right? Any small change completely changes the system, completely changes the way it works in your body. This is an engineering problem when you are dealing with complexity that high, and engineering problems are perfect for thinking about robust high-throughput screening, data collection, and model building. To me, what's really going to differentiate the artist-slash-tinkerer from the person who laps everybody else in the next round will be the person who treats this as an engineering problem and solves it as such.

Welch: Absolutely.

Lugo: I just want to say that I'm so glad you're an investor now because investors need to understand that you need to build infrastructure to solve these problems. We need to move toward rational design, and we need to learn the rules. Every time you add a novel component, which drives a lot of performance, you break the previous rules, and so you actually have to build some infrastructure. We have to move past the empirical screen, and we have to move toward rules. Nobody really knows a lot of these rules, which is beautiful, but if we're going to make it an engineering problem, you need to build infrastructure. A lot of investors don't realize that for RNA.

Hall: The good thing is Entrée Bio’s out of Entrée capital, which is a tech investor, so I am very hopeful that we will take a different approach on that. But I completely agree with you. I think so much is about chasing the next data point, which is pushing the next asset, and that that is potentially a short-term win for a long-term loss. And of course, I'm not going to deny that there's a tension there in that you can't make platforms and do data collection ad infinitum without having a product to show for it. But I do think that we do ourselves a lot of disservice when we insist that every new startup use AI in their pitch, but we completely ignore the fact that they need to have the infrastructure to build it. So yes, you hit on another one of my soap boxes.

Welch: Oh, there will be a chance for you to air that with a much spicier pepper.

Hall: Oh, I look forward to that. By the way, my eyes are starting to water.

Welch: How much of your pepper is even gone right now?

Hall: Only half, but it was a very spicy one.

Welch: I mean your face is slightly, you have turned slightly red. I'm not going to lie.

Hall: Yeah, it was substantial. Or I'm weak.

Welch: Are we going to make her eat the other half?

Lugo: Well, I'm trying to catch up. I feel like I have to finish this whole pepper if we're going to be on equal terms.

Hall: Sophia’s really taking one for the team.

Welch: Well, it’s interesting because Sophia, one of the things you'd said was investors don't always approach RNA companies or think about it from an engineering standpoint or from the infrastructure standpoint. Can you elaborate a little bit more on what you mean by that? What is it instead that they are paying attention to?

Lugo: Right now, what dominates the investor mindset is everybody wants assets. And so, they're really driven by the data milestone, and they don't understand that if you solve it as an engineering problem, if you spend time building the foundation, do what a lot of the AI companies are doing, you're going to be able to leap forward into either new products if you understand the rules, then you can start making many iterations of the product, or that some of the leaps that we're making are actually really important. This idea that you can have more rationally controlled intelligent design, just rationally designed products, is super important. So that's what they miss in focusing so much on making assets.

And then worse than that, they're looking at mRNA as an easy win. The idea is that mRNA is going to be able to tackle things that haven't been tackled before, and a lot of investors are focused on best in class, so they're just looking for easy wins, and RNA is in essence not an easy win. For a company that learns the rules, it's really hard to catch up to them, because there's so much complexity in the components that any individual company will bring together. If someone else that's not me and Eerik Kaseniit started Radar tomorrow, they're probably going to choose different components just because there's so much available.

To me, the current asset focus is missing the gains that you can get from actually learning the rules of the system. Often if you're doing high-throughput experiments, you're just using powerful statistical methods to figure out what your winners are, but if you're going to learn sequence design, you might actually want to bring in machine learning because it's a highly dimensional problem. Then you want to structure your data well, you want to pull out more information from the molecule. And actually Michelle gave us this advice — you might want to do libraries just for machine learning's sake, and that's a cost. So, it's building differently, but the potential gains are massive.

Hall: Agreed, but it requires a completely different investment thesis. Now we’ve got me on another soapbox. I do think that so many of these people, all you have to do is say AI, and they don't know the difference between AI and a hole in the ground. All you have to do is say that and they're throwing money at you, and then what that's doing is incentivizing a lot of people to, frankly, BS. Whereas understanding exactly what Sophia said, maybe you don't do the experiments to show the next inflection point in terms of, ‘oh, look, we got 25% greater efficacy.’ Maybe you do the experiments knowing you're pushing the boundaries of where the data is, pushing into areas that frankly probably won't work, but are helping you build a robust map of this landscape, which will then later prove dividends for your development and optimization exercise. I think it takes a fundamentally different approach in terms of patience and foresight than frankly, as investors, we are incentivizing right now, with the totally myopic focus on assets, which are important, but are part of what we're looking for.

Welch: So, it's looking at milestones differently, coming up with a different set of milestones?

Hall: I think it’s just having a lot more savvy about this. I think there's a large gap between the tech investors and the traditional biotech investors. I think the tech investors don't speak biology, and I know that the biology people don't speak tech. And so I think we are missing a lot of opportunities to leverage what both do well at the intersection. And so maybe it's not about missing milestones. I think it's about miscommunicating. Interesting.

Lugo: Yeah, it's like mRNA right now, we want to move biology toward an engineering problem versus just empirical trial and error, and we are not there yet. But mRNA, it's crazy that the body decided that the software of life, to use Moderna's term, would be a four letter code. Isn't that insane? We can conceptualize it super well, so it's possible to make an engineering problem, but we don't know the ground rules because there hasn't been enough investment in the ground rules. When investment has come in — what was it? From time that Moderna got the sequence to develop a product? Like 60 days or something?

Hall: Incredibly short. Something like that.

Lugo: Incredibly short. Whatever it was is incredibly short. So clearly, we've seen some breakthroughs of like, ‘oh, engineering problem.’ We just don't know the ground rules, and if you invest in learning the ground rules and that becomes your knowhow, that is extremely powerful.

Hall: You win. Absolutely. Yeah. Interesting. But you can't patent an algorithm, right? So that's the other thing. So then as an investor, you have to stop being so wedded to, ‘well, show me your patent estate’ and you have to value a knowhow estate as much.

Lugo: Yes, and you have to be able to look at, ‘can this company generate data at velocity? What's their design build test loop?’ That's like a tech thing, because again, we figure out novel components in mRNA all the time. You add it and you break it. So what do you need to have a good design-build-test loop, a good way of annotating your data?

Hall: And is your rate of learning greater than your rate of burn, I would say would be the metric. Now, I don't know how you quantify that necessarily, but heuristically it feels right.

Welch: Well, I want to be respectful of your time as well and transition us here from talking about spicy things into more of the cool down, although Michelle, you've already started.

Hall: My eye is still watering.

Welch: I know. I saw that.

Hall: I should have worn my waterproof mascara, but next time. Now I know.

Welch: Meanwhile, Sophia's eating more. Should I eat the full pepper? I probably should.

Hall: Y'all do you, but I'm going to wait.

Lugo: You're too afraid to touch it.

Hall: I know, and this would be so disappointing to all my friends and family, but here I am.

Lugo: I'm not just Texan, I'm also Mexican, so I definitely have a natural edge.

Hall: Yes, and I'm a pasty pale Scotch-Irish Texan. So yeah, different.

Welch: I'm from Pennsylvania!

Hall: You're doing great.

Welch: Thank you. I'm really proud of myself right now. So, we're thinking about the foundational wins of the space — we celebrated Karikó and Weissman, their Nobel Prize, in 2023, and in 2024, we also celebrated the discovery of micro-RNA, right? So, we've had a couple of good years in the RNA space in terms of big wins, big foundational learnings, but as we're thinking about scientific advancements that are going to be foundational for this field, I would really like to know in this cool down question from both of you, if you had to pick a recent scientific development in the mRNA field that you think is worthy of a Nobel Prize, what development would that be and why? What impact do you think this is going to have on the broader space as a whole? So Sophia, take us away here. I'm going to drink some milk.

Lugo: Thank you. You deserve it. I don't know if this is unfair, but I did not invent Radar, so I think I can be unbiased. In early 1900s, Paul Ehrlich got the Nobel, and he coined this phrase ‘magic bullet,’ this idea that you could create a medicine that could act like a bullet guided by a missile. And since then, people have been iterating on this idea that only disease cells should get the medicine and everything else should be left alone. And monoclonal antibodies got their chance to get a Nobel. The CARs have gotten a chance, and I think in the 21st century, when we want to deliver more powerful payloads and more versatile payloads that are genetic medicines, whether you're editing, whether you're disrupting a pathway, whether you're introducing a new function or a new gene, you're going to want a very intelligent way of targeting.

And that is what Radar does. We can sense an RNA marker in the cell, and I think that RNA is the ultimate level of precision you can get in a cell. We have tons of information available; it tells you everything you need to know about the cell. Even the non-coding regions are rich. And if we can truly sense any RNA region and output a payload that can modify the cell, there you go. That is the 21st century magic bullet. So now all we need is to get it into patients. We need to show how it actually changes the course of human history and has impact. And then yes, then I would nominate Jim Collins, Xiaojing Gao, and my co-founder Eerik Kaseniit. Again, I'm not eligible. I didn't invent this. I'm just trying to fund it. Not biased at all.

Welch: Biased, not biased.

Lugo: I'm not biased at all. But anyway, yeah, stepping back, it's going to be something in delivery because Weissman got it for the molecule itself, but it's going to be something on delivery front, I don't think that's really a solved space yet. Some parts have been solved. The other really interesting thing that is going on, again, we're trying to turn medicine into an engineering problem, so I actually think all of the efforts going into making virtual models of cells are really cool. I don't know how you evaluate that as a Nobel committee, but I am excited about the efforts going into figuring out what exactly is in a cell and how does it act to the extent that we can know it and track it.

Welch: I love that. Michelle, what do you think?

Hall: I want to pick up something she was putting down, because I totally agree. So obviously Karikó and Weissman very much deserve the Nobel Prize for the chemical modifications which made the mRNA ‘immune silent’ enough to take it from a scientific curiosity into a therapeutic that most of us have had now a couple times injected in our arms. Huge discovery, no doubt of its impact, and yet that impact would've never translated to the clinic were it not for the delivery vehicle. And I would argue exactly what Sophia said, that yes, there's still a lot there that is unsolved, but I think the foundational work that was done — the first-generation ionizable lipids for LNPs were pretty darn plasticky and not super fun for anyone. As we've continued to iterate and build on those, these LNPs, not withstanding some of the clinical holds that we've seen lately, are pretty damn safe and tolerable. And I think we're just seeing the beginning of what is going to be feasible. We've got obviously intramuscular injection for vaccines, as well as intravenous delivery for liver, and then clinical trials that are ongoing for lung delivery, but I think it's just the beginning. I think people are getting really excited about the potential of different non-viral nanocarriers to open up a whole bunch of different areas, and I would love to see the other part of the mRNA therapy, the delivery vehicle, also awarded a Nobel Prize.

Welch: It does deserve a little bit more love, doesn't it? I think we tend to give it some short shrift, even though we talk about how important delivery is.

Hall: That's the real interesting thing, right? Everybody's like delivery, delivery, delivery, and I'm like, why no award? 

Lugo: Lots of royalties though, to bring it back.

Hall: Lots — and litigation. And I don't know, maybe that's it. Maybe it's also that, again, it's more of an engineering problem than it is a basic research problem. I think that is only right now. I do think our understanding of the basic biophysics of how these particles behave, both in a test tube and in your body, is evolving, to bring it back a little bit to what Sophia was talking about earlier. Maybe we'll see it in the future, but yeah, I do think it should be acknowledged for what it is, which was transformative.

Welch: Nobody puts baby in the corner, right?

Hall: Nobody puts LNPs in the corner.

Lugo: I think you should start the Michelle Lynn Hall RNA award.

Hall: Yes. ‘Who did their data the best? Did you ever present data without error bars? You're out.’

Welch: We'll serve roasted jalapenos at the reception.

Lugo: And I win the jalapeno award because I'm still going.

Welch: She's still going. How much of that jar have you eaten just sitting there?

Hall: I'm so impressed.

Lugo: I do actually snack on pickled jalapenos sometimes because I find them quite good.

Welch: Okay, so this is unfair. I was unaware of this when I picked the jalapeno.

Hall: I was unaware of this as well.

Lugo: I was aware.

Welch: We were fooled.

Hall: I came in cocky. I didn't know what the competition was.

Welch: You're going to make fun of the Pennsylvania girl over here. Well, with that, we're wrapping up Episode 1 of Advancing RNA's mRNA Hot Takes with Sophia Lugo, CEO of Radar Therapeutics and Michelle Lynn Hall, general partner of Entrée Bio. Thank you both so, so much for getting spicy with me today, and I can't wait to sit down with you again for our next installment. Thank you.