This interview by Jane King first aired on Bloomberg TV on April 12, 2025 as part of the New to the Street segment.
Interview transcript
eXoZymes is a pioneer of AI engineered enzymes that can sustainably transform feedstock into essential chemicals, medicines, and biofuels. With me is Dr. Tyler Korman, co-founder and vice president of research for eXoZymes. So I gave a brief description. I was kind of mind blown when I was doing research about what you do. Explain what the company does.
So thanks for having me. So at the end of the day, what we're trying to do is really redefine how people make chemicals. So chemicals that you use in your everyday life. These could be flavors and fragrances. These could be nutraceuticals, fuels, these types of things, but in a sustainable way. Okay. Okay. Right?
And so, you know, the feedstock part of that is how do you utilize, you know, sugars and these natural types of things to turn those into these compounds that everybody wants. We do that by using enzymes, so the little chemical factories within a cell, but then we don't use the cells. So it really is a way to redefine how chemical manufacturing is done. Yeah.
Well, I feel like we get a lot of chemicals from petroleum.
We do. So this would be a more sustainable way, not such a reliance on fossil fuels. That's right. It's more sustainable. It's easier to diversify. It gets us away from, you know, not just petroleum, but there's an issue with, you know, how you grow huge fields and all the agricultural burden, right, for some of these chemicals that you need on demand if they're pharma type compound or something like that.
And so, you know, we can do things in smaller batches to get just as much things without having to grow and ruin the environment. And you're not interfering with food supply. Exactly. It sounds like. Correct.
Now, we all bought into synthetic biology, and it didn't work out great. Is this different than synthetic biology?
It's different. And so we define it, we really think of it as the logical successor. So synthetic biology was a great idea. It's very, very simple. You're going to, you know, take a yeast that normally makes something like beer, and you're going to turn it into a factory that makes what you want. Turns out it doesn't work very well, because those cells don't really want to make something that's going to kill them.
And so we said, well, if we just take those things, those catalysts outside of the cell that are doing those, that transformation, we could use that more efficiently to make things better. And so effectively, that's what we're doing.
We still rely on synthetic biology to make our enzymes, right? So there is still this give and take between technologies that were developed before us. We utilize a lot of the recent developments that, you know, have been awarded Nobel Prizes in AI and enzyme engineering.
And so we're really using the best of all the technologies to make these sustainable solutions. And pharma uses small molecules, right, to create their pharmaceuticals.
Is that a part of what you're doing as well? How will exozymes kind of play into that?
Right. So most of our targets are small molecules. And so pharma, like the drugs that you use, is a small molecule. You know, a fuel is also a small molecule type of thing. And so what we're trying to do is enable the production of those small molecules more efficiently, right? We can also, getting into the diverse, like the pharma space, we can take a natural product.
So natural products make up most of what the drugs are today on the marketplace. So antibiotics are actually from bacteria in the soil. And so we can take some of those similar types of pathways that make those drug-like molecules and then diversify even further by changing our inputs. And we can do this fast and really simply.
Fascinating. How does AI play into the process?
Yeah. So, you know, with all of the AI machine learning techniques to enable you to learn really quickly, what we can do is we can learn really quickly how to engineer the enzymes that we use in our exozyme biosolutions. And so AI allows us to predict faster. It allows us, if we can generate data sets, clean data sets much faster, we can then really start to utilize all of these advances that are now becoming fundamental in the space in biotechnology. Yeah.
And you recently had an IPO.
We did, yes.
So how long have you been in business? What did it take to get to that point?
So we've been, this has been an idea from starting in about 2014. In 2019 is when we officially launched with a small seed round from our initial investors, MDB Capital.
And since 2019, we've been building it to what you see today that we just IPO'd yesterday. So we started with three people in a warehouse and now we're in 30, you know, multi-state, multi-city endeavor that is looking to start to scale and commercialize. And potentially changing the way all this is done.
So I love stories like that. So what's the future then? Would you say like 2020? 2025, what are your goals? 2025, what are your goals?
2025, the future is to grow both in terms of capabilities. So the things that we can do, the types of molecules we can make. So more in the nutraceutical pharma space focused. In addition to growing our core competencies and really getting to those scale-up market, right? So getting compounds that are ready to enter into the commercial market.
Okay. And who would your customers be pharmaceuticals or where?
So initially some of the partners would be either partnerships or joint ventures, right? There will be also some customers that are probably more in the nutraceutical space. So nutraceutical with potential pharma applications. And so it really runs that gamut as well.
Okay. Well, congratulations and best of luck and fascinating to hear about what you're doing.
Thanks for having me. Appreciate it.
Forward-Looking Statements
This video contains "forward-looking statements." These forward-looking statements are made as of the date they were first issued and were based on current expectations, estimates, forecasts and projections as well as the beliefs and assumptions of management. Words such as "expect," "anticipate," "should," "believe," "hope," "target," "project," "goals," "estimate," "potential," "predict," "may," "will," "might," "could," "intend," "shall" and variations of these terms or the negative of these terms and similar expressions are intended to identify these forward-looking statements.
Forward-looking statements are subject to a number of risks and uncertainties, many of which involve factors or circumstances that are beyond eXoZymes' control. eXoZymes' actual results could differ materially from those stated or implied in forward-looking statements due to a number of factors. The forward-looking statements included in this video represent eXoZymes' views as of the date of this press release. eXoZymes anticipates that subsequent events and developments will cause its views to change. eXoZymes undertakes no intention or obligation to update or revise any forward-looking statements, whether as a result of new information, future events or otherwise. These forward-looking statements should not be relied upon as representing eXoZymes' views as of any date subsequent to the date of this release.