Natalie Kuldell Speaker 1 (00:04):
All right. Hi, welcome. Frederic nice to see you again. Thank you so much for joining. I really appreciate it. We’ve have had such wonderful conversations as part of these career conversations and yours is such an interesting journey into the work that you do. Can, can you introduce yourself and, uh, where, where you’re working now and what you’re busy doing?
Frederic Vigneault Speaker 2 (00:31):
Yes, that’s what it is. My name is Frederick Vigneault. I’m a senior staff scientist for the Wyss Institute, which is a transitional research Institute at Harvard University. I’ve been there for 10 years. I work on many different projects. My background is in molecular biology, uh, and at the Wyss I started first with the George Church, like working on genome engineering and bacteria, then next gen sequencing, uh, later along the CRISPR. So doing that in the tadpoles and frogs. I also work on diagnostic companies with, uh, Jim Collins. Uh, we made the news or in COVID, that’s my journey in the short amount of time.
Speaker 1 (01:20):
That’s all the big terms, all the big folks all the heavy hitters in the science and engineering and in this field. So pretty amazing stuff. Do you have a favorite of all the things that you’re working on, or I think tadpoles is incredible that you’re doing this in, in tadpoles, but what, what do you find the most exciting or interesting?
Speaker 2 (01:44):
Well,The one I’m trying to doing now, uh, I think is very interesting because we were using it as a model to, for cognitive disorder. So, we’re taking, we’re trying to model rare diseases. The one we’ve picked on as a, as a first prize is Rett Syndrome, which is a rare disease neurodevelopmental disorder. Uh, so there’s this symptoms from learning’s abilities or seizures. So we started using tadpole as a way to model it quickly. So instead of having to spend months, or maybe even a year developing a mice model, uh, we can do it in just a couple of weeks. And then a couple of weeks we can also start screening for compounds that can address those symptoms.
Speaker 2 (02:33):
And it turned out that the tadpoles, because of a lot of similarities in our genes, the brain structure, there’s a lot of things we can screen for we can also train them and we can also look at sleep disorders. Uh, so yeah, so we can basically in a couple of weeks, can we just start creating [inaudible] for like 10, 20, 30 different drugs figure out which one is the best, it’s something you cannot do with cell culture. You cannot train for a cognitive disorder like behavior and something that’s very hard to do with mice, just because of the scale that in mice nobody does that. Typically you are going to have one drug, you got to try it on the 20, 30 mice and then, you know, it’s hit or miss to try it again.
Speaker 1 (03:21):
You seem to have found that Goldilocks space, right? Cell culture, all very interesting, but it’s very limited in terms of what you can find. Mice, very cool, but you can only do so many and they’re slow. So tadpoles are kind of in the middle. There are lots of them and they grow pretty fast. If you can get the breadth of the application space in them, that’s very, very interesting stuff. Cool. And a lot of applications, a lot of health applications for this, are you thinking forward in terms of what this would look like? If you’re wildly successful,
Speaker 2 (03:53):
That’s the way I’ve been coupling this with the prediction, like a conditional prediction. So it would bring the machine learning to predict what drugs going to work with this, uh, like biological models training. And so we did that for Rett syndrome and we are sort of like the current best candidates. We tried it in the mice model for Rett syndrome, and it worked well. Uh, so now we’re actually looking to bring it to a clinical trial, uh, in the next year or so. And if that works from there, we are thinking to start doing other rare diseases. Uh, so we’re thinking to start a company.
Speaker 1 (04:29):
Amazing. So like, you know, not only like all the heavy hitters in terms of molecular biology, genetic engineering, synthetic biology, and all the amazing labs doing it, but now also bringing in AI and clinical trials and entrepreneurship. So you run the gauntlet, you’ve got the whole, the whole package going. So that’s very important.
Speaker 2 (04:50):
There’s a lot of the reason it’s pretty resourceful and the Wyss, a matter of funding of the PIs. So a lot of different disciplines too. So putting different people together, uh, I try to give like a different, uh, approach to, uh, like a current need, uh, something like something that’s different that that’s in a pharma company might have had a trouble, uh, getting into a second in general, when you look at like Alzheimers or Parkinsons, they’re very tough disease to go after. So maybe, maybe that’s one point, that’s what we’re, that’s where we’re going to aim. Uh, but yeah, so we’re trying to have like a different angle, uh, hopefully that angle is going to be helpful.
Speaker 1 (05:30):
Yeah, no doubt. No doubt. I think when you put people with different perspectives together, there’s ways of thinking that any individual might not have had the ability to do not. A lot of people may not know about the Wyss. Can you just say a few words about where it is and what it is?
Speaker 2 (05:48):
So the Wyss Institute, this part of Harvard University, we’re located in the Longwood medical area. So Harvard medical school, uh, it’s what started in 2009. So I joined in 2010, uh, second year after it started. And the goal of the Wyss is transitional, which means, uh, you take, uh, academic research and you try to de-risk it. So we can become like a product or a company or being licensed in other company. That’s, that’s basically their goal. And I’ve done that a few times. I have several patents and they all went to different companies. Yeah.
Speaker 1 (06:25):
Wow. So you, you are a scientist engineer, entrepreneur forward looking thinker. Did you start off this way? You didn’t, I mean, the Wyss is new, how does one start if you’re looking at landing at a place like the Wyss?
Speaker 2 (06:44):
For me it was a true networking. Uh, so I did my, uh, PhD, so I’m from Quebec, uh, in Canada and I did my PhD there. I actually did it in plant biotechnology, and instead of doing a post-doc in academia, I tried to look for a postdoc in industry and I, uh, took me a while. You know, you just apply to go to conferences, you present, you meet people. And after six months like that, I found a place, I call it SRI International, which is a, it’s a nonprofit research Institute, but they’re really big on research. SRI uh, that comes from SRI basically, uh, there’s a, they’re a powerhouse in terms of innovation. So that’s, that’s where I came from originally. Uh, we’re doing mostly computational. So even though my background is like really much wet bench biology, uh, they wanted biologists to have them with which what we call data analysts these days. But that 12 years ago data analyst wasn’t a trend like today. So the computation they were using AI, uh, but then as trendy was just getting started. Yeah. Uh, the vision started, uh, I learned about it from, from different, from different people. They like told me about it. So I, I applied got an interview, that went well know.
Speaker 1 (08:10):
Yeah. That’s and the rest has happened, as you said.
Speaker 2 (08:14):
And then networking is basically the best way to go about it. That’s an issue or looking for people actively like going to conferences, meeting, uh, and like talking to people then, you know, that that’s how you make your networking happen.
Speaker 1 (08:30):
Yeah. I get that question sometimes, you know, like what courses should I take or what should I be doing if I want to become a synthetic biologist or an entrepreneur or an AI, data analyst or whatever you’d like to call them now. Right. So, um, you know, is there, is there a recipe? I mean, networking is the way you sort of bring yourself forward out into the community, but is there a background that you think is particularly helpful for getting going?
Speaker 2 (08:58):
I don’t know. I mean, uh, when I got my interview at SRI international, my background was in plant biotech. Uh, they didn’t do any plant biotech at all. They were looking for position mostly on the biology of disease. Uh, so the way I did it was to really tailor my presentation, so the same, I’ve been gaining better people then instead of that, I tailor. So so you have like your PowerPoint slide and I find, I put like a plant, like a plan model or adapt to the, for using, because I didn’t expect them to know all the parts of the plant. And I was doing molecular biology, like on the like tiny pieces of [inaudible] growth. Uh, so basically every time I’d, I’d be somewhere I’d like be pointing toward the plant. Exactly what it is. I give them some context and I finish something I was interested to do, but I didn’t really do as part of my PhD is, uh, like a network analyzers, like a, like a signaling cascade.
Speaker 2 (09:53):
They’re signaling molecule in yourself. And the job application was for doing the computation for making network. So I basically created a network from like, I just draw it, like from the literature, from what I know from my own I saw this, or this means that this network is good this way and not this way. And they loved it. Right. I tailored it to what they wanted to know. And this, I was the only one who did that. Right.
Speaker 1 (10:26):
It’s such great advice because I think what it shows is that you put yourself into the mind of the person who is watching you. A lot of times people think that they have to present themselves, it’s all about them, but it can be very successful to think in the reverse, like if you were sitting in the audience, what do you need? What do you want to know? What would be helpful? And when the presentations meet all of those things, there’s an instant connection. And you know, you feel like it could be a win by working more with that person. I think that’s so wise,
Speaker 2 (11:04):
And it’s not always easy. Right. But when I got my target, the Wyss, they were looking for people with a private sector, like a two years of experience in private sector. So I had that, but it was basically the main thing you were looking at this, like if you’re experienced or willing to try their projects, but trying to put your stuff into the mind of George Church, uh, is not possible. We don’t want to go there. My ceiling of what is possible was already pretty high. So I think that’s why it went well. But George doesn’t have a ceiling, to a point where sometime, I think like, it’s like, yeah, you’re thinking it this way, but that’s not possible. That’s like, we’ll have to invent new physics type of things. And you’ve done that before, you know, those things all the time, you know, there to be they’re predictable.
Speaker 2 (11:56):
Uh, but there’s something your ceiling has to be really high. What are you going to want to meet with George Church as a scientist or like a teacher, things that we can control or would like to control one day they’re pretty high. Uh, my feeling is basically if it’s possible in this universe, uh, you know, it’s possible, that’s it? So if you, if you can, like, sort of make the step to get to that point. Uh, I remember when I started at the Wyss people were mocking the idea of to go do like a brain transplant and then tried, uh, more or less successfully, but, you know, they, they tried it on the and, uh, it must have survived for a few hours. Right.
Speaker 1 (12:59):
Yeah. I, I think that the, the goalposts keep moving and I think the things that we would have thought were impossible, we take as a given right now. We just sort of accept as truthful and, and part of our world. We, I certainly think a lot about that with computers. So what people imagined computers would be used for, and we’re capable of is very different than what we are living with right now and where computers are in our lives. So biology next frontier I’m hopeful is going to be in a similar boat.
Speaker 2 (13:32):
Yeah. I mean, the thing about longevity by example, you know, now we’re not saying like the top leader, like including George in the fields of longevity, they’re saying, uh, like aging sort of treating aging as a disease. Uh, so yeah, it’s a biological process, uh, where all, or what’d you call it process or became older here and there. So maybe we can fix that you know, in therapy, it’s possible that we may be able to extend someone or make someone younger, already early, but, you know, that’s a hot field. And on the computer side, there’s actually people have devised AI a long time ago. Like back in the sixties, it was just, we didn’t have the computational power and the same thing’s happening with, uh, like just in CRISPR now, , it makes making models like computer models so much easier. Like we can make, like, I, it takes me a day to design something, order it from a company and it takes them longer to ship it than for me to do everything else around it. So, yeah,
Speaker 1 (14:38):
Isn’t that incredible. The ability to accelerate biology and biological research and engineering is just it’s, it is the world we are, we are looking towards. So that’s a great thing. We need that for sure. So amazing. So, um, so if there was a very excited 17 year old students watching this, what would you advise that student?
Speaker 2 (15:02):
Having an internship. Uh, I just had this like like two years in a row. So like really like, get, get, get out there, try to find like a place where you can just do science. I mean, you you’re, you’re building yourself by your experience by place. You want to become a scientist, do science.
Speaker 1 (15:26):
Absolutely. Hear, hear, I couldn’t agree more. Yep.
Speaker 2 (15:31):
He started, he knew a little bit about PCR because, you know, you’ve been telling them about that. And the whole, my whole internship was like, yeah, you’re going to need to do PCR. So, so basically you spend a bunch of summer learning about PCR design and achieve and went to real-time PCR. And he came back with me the year after he was now, like at college yeah, we’re gonna do PCR, but depend on the new, like, to assemble pieces. So now I started doing my Gibson assembly. Those, all those construct send it to companies that we can make. I had a really good time with Brian, any super shy person, especially the first year, the second year was much better. And, uh, I don’t know exactly what he was doing. I mean, this called that they probably stayed home. Hopefully he stayed home.
Speaker 1 (16:20):
Yeah. We’ll follow up. We’ll make sure we do a little reunion because he has been one in the BioBuilder, community, mentoring the students and, and teaching them what it is like, as you say, you know, if you want to be a scientist, do science and learn, learn as you go. I think that’s a great, great bit of advice
Speaker 2 (16:39):
And it didn’t mention it was helpful to him during his first year, because there was a lot of things that we’re learning about and they say, yeah, I’ve done that.
Speaker 1 (16:46):
Right. It positions you well. And I’m very glad to hear that. Well, thank you so much for sharing your story. It’s fascinating. I cannot wait to see what all this leads to with you. It will be so exciting.