Transcript:
00:00 [Natalie Kuldell – NK] Hi Eryney!
00:02 [Eryney Marrogi – EM] Hey, good morning.
00:03 [NK] Nice to see you. Thank you for joining. I’m really grateful that you can take some time out of your day to have this conversation. I’m very lucky to get to know you. I got to meet you for real at LabCentral and the work you guys are doing there is impressive and interesting and I thought it would be a great conversation for the students who are in this program. So maybe we can start there: could you introduce yourself and say where you work and what you do?
00:34 [EM] Sure. my name is Eryney Marrogi. I’m a research associate at Dyno Therapeutics. It is – I guess you can say it’s an early stage startup; I think midstage is at this point more appropriate – but I’ve been working at this company, Dyno Therapeutics, for about a year and a half now at this point in Kendall Square. We are an AAV delivery company, and yeah I think that is the highest level overview that I can give about that.
01:05 [NK] Can you just say what AAV is?
01:06 [EM] Oh sure, yes. It is an adeno-associated virus. It’s one of the most popular, if not the most popular, vectors for gene therapy delivery currently in the field.
01:20 [NK] Right, right. So it’s an incredibly interesting and relevant field that you’re working in and it’s also fascinating, you know, the whole startup community. I know a lot of people are curious about what it is to work and be part of a startup. So maybe let’s start by talking about the science and the company, and then we’ll talk a little about the culture of being in a startup. But what is your day like? What attracted you to doing this work?
01:49 [EM] Yeah that’s a great question. So to start off, I think something that’s unique to Dyno is the approach that we take to the problem. So one of the biggest problems that exists in the field for gene therapy – or gene therapies that use AAV – is they are reliant on sort of naturally occurring virus that will do, more or less, as it pleases and oftentimes that means you are using a virus that may not go exactly where you want it to go. And if we want to treat patients, I think one of the biggest – the most important factors is you have a reliable model that you’re using, so you know that when you use this virus, it’s going to go to the heart and it’s going to do this thing. And so one of the biggest difficulties with AAV is that you’re using a virus, and there are different serotypes of that virus that are maybe better for one thing or another thing, but overall so far in the field there hasn’t been much luck in getting these serotypes to be more specific than they already are in nature. And what Dyno is doing is applying machine learning to rapidly develop viruses that are able to better adhere to criteria that we want. For instance, we might take a naturally occurring serotypes that’s generally really good for the central nervous system and make different modifications to that, so we tend to do mutations on the scale of hundreds of thousands, and we make those mutations in the virus in the cap of the virus and then we use animal models to see which mutations had what sort of advantageous effects. So maybe that’s increased packaging sizing; maybe that is higher specificity; maybe that’s a better binding to a certain organ or tissue type over another one. And all of that kind of amounts to improved capsids for – or capsid it’s kind of like the actual virus itself it’s improved viruses for – gene therapy, which ultimately means better gene therapy for patients.
04:16 [NK] Yeah, yeah. It’s fascinating because it’s a platform that you’re developing; it’s not that you have a particular gene therapy target that you’re working towards, it’s really a platform technology that you are focused on and, in that sense, I see it very engineering focused as well as scientifically and life science focused, which is very cool. And it’s just so interesting to hear you mention as you describe the science of it, and then the machine learning of it, and all the testing of it. So which aspects of the platform development are you most focused on?
04:56 [EM] I have worked since I’ve started at Dyno since I know this kind of infancy on everything that is downstream of machine learning. Dyno’s platform is kind of more like a feedback loop where you have machine learning that’s kind of: starting step, one making the designing the library or designing the viruses; and then you have step two which is making the viruses; and then step three which is testing the viruses; and then that testing phase, then loops back into the machine learning to then generate the next iteration of the library. I have worked on the middle and the last stage, generating viruses and then the testing phase.
05:44 [NK] We talk all the time in BioBuilder about that design-build test cycle as an engineering cycle, and so it’s really just amazing to hear it so directly applied to such a vital question, and then a growing company. So awesome! So your training must be quite broad, and I want to ask you how you got to where you are, but just backing up just to ask before I forget about how do you like working at the early stage and now mid-stage startup?
06:14 [EM] So I joined – when I joined Dyno, we were not very big. It was – I think I was maybe like the eighth full-time employee; I don’t really remember at this point. But now we’re closer to 40. So the changes that I’ve seen in the company have been pretty stark from when I started. When you kind of start an early stage company, you wear a lot of different hats that don’t necessarily apply to your job title. That might include sometimes going to business meetings even though you have no business training. But now we have a really great team for that sort of thing. It was spending a lot of time doing company culture work; that was spending a lot of time on just generating the life of a company, and now I think my focus is a little bit more finite to the science. So that transition has been – it’s been exacerbated, I think by the rapid growth of the company, but it’s one that happens for everybody, regardless of whether you had a biotech startup, or a regular tech startup, or just a small company in general that grows.
07:29 [NK] Yeah.
07:30 [EM] And, you know, it can be difficult to lose out on some of the diversity of what you do, but I think ultimately when you get back to what you’re good at, everybody is happier in the long run.
07:42 [NK] Yeah, yeah. Just as a side note, starting up BioBuilder – it’s a non-profit organization but it is also a startup and I wore many many hats from curriculum designer, to chief bottle washer, to finance and communications, and all that. And yes as you grow, you start to sort of lean back into the things that you’re trained to do and you find experts in the areas that you still need help in for the company.
08:08 [EM] Exactly yeah. I mean it’s great because you get a little bit of everything, and you wouldn’t really get that anywhere else. But ultimately, like I said, I think everybody is happier in the long run when you don’t need to wear a lot of different hats.
08:25 [NK] Right, exactly. Yes, fall back on the things that you’re like “oh yeah I know how to do that.” Right so then actually maybe that’s a good segue to ask you about your training and when did you know you were interested in doing science? Where did you go to school? And what did you study?
08:43 [EM] Sure. I think that I’ve had a little bit – I’ve had an easier time with the scientific route, just because of the path that I took. So when I was in high school – I grew up in Virginia – I did a summer program at the NCI – the National Cancer Institute – in Bethesda, Maryland. And I really enjoyed it; I found the work to be really fresh for me. It kind of tied what I was learning in the classroom with the real world. Kind of like you just mentioned, right with the process of designing, you learn about that in the classroom but sometimes you wonder like “what does that look like in real life?” Well that for me was that sort of summer experience. That looped into a more continuous role there working in the lab, and I also did the Intel Science Fair – I don’t know if that’s still around anymore but – I did that all four years of high school and I very much enjoyed that. I strung that into an undergrad degree at Virginia Tech in biochemistry and, naturally, biochemistry is very science oriented – entirely so. And during that time, I was working in a protein modeling lab, so I did a lot of computational work. During my summers, though, I actually spent them in Boston in the Church Lab – George Church Lab at Harvard Medical School – and I was working at the time on something completely new for me. After spending several years in cancer biology, I now was working in mosquito engineering of vector engineering, and that was a completely new experience. You know you learn a lot of things that are unintuitive, and I learned a lot about the mosquito that I would not have ever learned beforehand. I spent two summers working on the Gene Drive Project – as it’s called in George’s lab. And then when I graduated from college in 2018, I stayed on in the Flaminia Catteruccia lab as she was working with George on the mosquito project at Harvard School of Public Health. I worked on that after graduating through her lab and I then joined Dyno after a year there. Eric, our CEO, was actively recruiting from George’s lab at the time and I was ready to, I think, move away from academia and into industry and the opportunity kind of just aligned with what I was looking for.
11:31 [NK] Yeah. Well it sounds like, you know, again a broad set of skills and training that didn’t have a direct line to the things that you’re doing now, but when you learn how to ask good questions and answer good questions, that carries over from mosquitoes into adeno-virus to anything – is the way the ways of thinking and the ways of being and doing.
12:03 [EM] Yeah, yeah. They’re, I guess, I like to think of it as there are sort of hard skills that you learn which are maybe like PCR – I don’t know if this is something that a lot of the students are aware of – but there are certain lab skills that you learn. You learn how to run a gel, you learn how to do Western Blotting, you learn how to do PCR, you learn how to do all these things. And these hard skills, maybe they need tweaks between whatever work you’re doing, but they’re pretty translational. And then you have your soft skills which are, as you’re mentioning, the ways of thinking about ideas and thinking about problems and coming up with solutions. Those skills are equally transferable and I think oftentimes more so just because you can kind of plug and play the thought process of – yeah I mean like the details around mosquito engineering are definitely different than AAV, but the principles of using tools are the same, and so your thought process ultimately stays the same.
13:11 [NK] Yep, yep. A good experiment is a good experiment and data analysis requires a sort of skepticism about what you’re looking at and seeing and that’s true no matter what you’re actually studying and doing. So, yeah. I think that’s great. The other thing that I really love about your story is the notion, that it was an early experience – a high school experience – that sort of directed you towards the the application of the things that you’re learning in classes because I do think that classes do teach a lot of the, you know, good science classes are teaching those hard skills like how do you run a PCR and things like that, but I think the realization of how it all fits into the actual being of a scientist and the doing of science is really most clear when you have a chance to be in a lab, and that should come earlier. I’m all about getting that sort of experience of being a scientist or an engineer early, giving people early opportunities to do that.
14:10 [EM] To me, I think the earlier that someone has an exposure to those hard skills, the faster they can develop the softer skills because you no longer require an awareness about “how do I do a qPCR? How do I do a sequencing run?” That sort of becomes second nature, and you can just focus on “how do I use those things to my advantage?”
14:44 [NK] Yeah.
14:45 [EM] And it’s all about just developing the muscle memory, and all of a sudden you no longer – one day you no longer have an aversion to doing a complicated experiment just because it’s in everything you do.
14:57 [NK] Your technique is there, you know the foundations are there, you just start growing from it, yeah. Yeah, I think it does make you brave; I completely agree. I think that these experiences and the confidence that you have in the sort of base technique the scales of doing science – which I love that analogy I think is great – and it does give you confidence to do more, and that’s what we need, right. We need young people coming into this who are not afraid and who are bringing their good ideas and able to do more, so that’s awesome. Now, I’ve been fortunate not only to know you a little bit through Dyno and the connection we have through LabCentral, where the Learning Lab is, but also through BioBuilder where you have been a mentor to teens and students. So do you want to say anything about your interest in being part of BioBuilder or what you’ve done as part of BioBuilder?
15:46 [EM] Sure, yeah. As I mentioned, I worked on different projects through science fairs when I was in high school; I always valued that early exposure. And when I was in college, I tried to still be involved with that process as a judge at those science fairs. And as I have graduated and kind of moved on, I was interested in exploring like what does that look like now for me? And luckily I think I saw an email that had been circulated at Harvard when I was there, and it seemed fitting for that sort of experience that I was looking for, and I’m glad I reached out at the time – that’s over two years now that I think about it, so it’s been it’s been a while. And I’ve worked with different teams, but I’ve also worked consistently within the same two schools which I think has been really – it’s been easier for me because I’ve been able to develop a connection with the teachers and then certain students, certain faces you see from year to year. But I think the best part of that experience has just been being able to see the ideas that these students are coming up with. They’re out there, you know, they’re definitely out there and it’s really great to see that they’re not yet grounded on the reality of how difficult it is to do certain things, and that comes with time. But I think it’s easier to learn that, than to learn how to think very abstractly and creatively. So the projects that I’ve seen have been I think really neat; they’ve been really cool. And the work that the students put in – it’s awesome to see they clearly have a lot of passion about it. I imagine that most of them are not just doing it because they have to, and that’s always a good thing, as well.
17:48 [NK] Right, yep, yep. Well I’ve heard great things about your mentorship of the teams, and that is you know what you articulated is exactly the sort of ethos that we try to make sure gets conveyed here through BioBuilder – is that you know your good ideas are what really matter, and that we will teach you the techniques and the tools for for you know testing them and and how how you might build them. But the ideas really do matter and the people. It’s sort of surprising at least when you learn science, especially in high school, it’s sort of a big collection of facts, right. It’s like everything that’s in a book, and so it doesn’t always seem clear that there’s actually a lot to do with it, right! It’s not just a passive sort of learning of lots of things already known, but it’s actually the way you put it together, the way you can actually craft it into a technology and a solution that you want to design, right.
18:43 [EM] Exactly, yeah.
18:48 [NK] Well it’s wonderful. So is there anything – last question that I’ll ask you and then I’ll let you get back to your day – is there anything that you kind of wish you knew way back when that you that you know now and think is important to keep in mind or something?
19:07 [EM] Yeah, I think every experience that you have teaches you something. Some experiences teach you more than others, but something that I think I still recommend to people who ask me this sort of question is to think about what an experience can offer you in terms of where you would like to be. If your eventual goal is, for instance – if you really want to be a physician, think about what sort of experiences will get you to be the best version of that goal. It can be really easy I think to chase prestige and very easy to chase very attractive options that don’t really fit well with your story, and the sooner you can get over that desire to want that sort of stuff, I think the easier it becomes to be really happy with what you’re doing. So that’s my piece of advice: think very critically about like what is something offering me in terms of where I want to go? And does that help me not only get there, but once I am there, does it help me to be the best version of that whatever it is?
20:34 [NK] I think that’s awesome. To continue to try to be the best version of ourselves is going to be a very key element to success and to happiness. I think that’s exactly right. Well I wish you certainly great success and great happiness, and I appreciate you taking the time to just articulate and walk through your story a little bit.
20:57 [EM] Absolutely. Thank you very much for speaking with me, and I am always available for questions.
21:03 [NK] Awesome; I will let folks know. Thanks.