Today I sit down with Tyler Korman, the VP of Research at Exozymes and co-founder of the company. We discuss the scientific terms and concepts of the platform and its three distinct phases, and the conversation is left quite broad and open for all to understand. If you want to find out more information about the company or what we discussed today, I'll provide a link below to my company report over on my substack. Enjoy the conversation. My name is Tyler Korman. I'm the VP of Research here at Exozymes. So, you know, I started back in college, I thought I was going to be an organic chemist and I couldn't stand the fumes. So pretty quickly I turned my focus to studying enzymes because that's what made sense to me. And almost the rest is history. So I started off doing some basic science, figuring out how enzymes, enzymes were. And then when I went to graduate school at UC Irvine, in the late 90s, early 2000s, structure-based drug design was really hot. So, you know, you'd figure out what an enzyme looked like. And then the idea was that once you knew that, you could design drugs that fit into that enzyme and then inhibited it or did whatever. There were a number of companies in San Diego that were doing that. I thought that was really cool. And when I was interviewing for during orientation, actually during orientation, there was a professor who said, well, I'm actually studying the enzymes that make drugs in nature. Right. So it was a completely different aspect. It was, you know, there's pathways in bacteria and fungi that actually make these compounds that are most of the drugs that we use today, or at least the basis of. And I was like, oh man, that's what I want to do. Exactly that. It was structure-based drug design from a different aspect because these enzymes, these pathways already made these really interesting products. spent the next four years, spent the next four years, spent the next four years studying what those enzymes look like. And then moved over once I finished my PhD to UCLA. And the, I wanted to work on, on even more applied projects. So a lot of the stuff that I had been doing was, was still basic science, right? You're figuring out what something looks like and how it does it. It's still a little bit in the weeds. And so I met Jim and Jim said, you know, I've got this project. We have money from the Department of Energy, but I've never worked on it before. And that was similar to what I had done in grad school. I was the first grad student of an assistant professor. And she's like, here you go. Go learn how to do it. You don't have any resources and support. And I was like, okay, that sounds great. So similar thing. We started off trying to make engineer enzymes to make biodiesel, both cell-free and in vivo, because at that point, SynBio and that, the whole metabolic engineering frontier was, was kind of in full bloom. And we always were able to do things that worked just well enough to publish, but it was going to be really hard. Many years, many, many, many millions of dollars to, to get anything commercial. And, and it was an aha moment where, you know, we had been doing that for maybe a year or two. And Jim, Jim Bowie came out of his office and he said, you know, what if we just got rid of the cells and that would solve so many problems. And so I fell back on my background in, in natural product metabolism from grad school and said, oh, well, you know, all these bugs break down sugars and turned into building blocks and energy. We could use that and then just link it up to some other pathway to then make something interesting. So that's where it started. We got some depart, some more support from the Department of Energy. And within a couple of years, we had Paul, who's one of my other co-founders. He joined the lab. He was a grad student. And we basically built out all of the systems that you need to, to drive these multi-step metabolic pathways, cell-free to have them run for long periods of time, because that's the goal, right? You don't want something that just works for a little bit and then you publish. And so be it. Like you want something that's going to be robust. That's going to work for a long period of time. You can just walk away from it after you, you add things together. And that's the, that's the ideal. So we set about trying to figure out how you could get that to happen. Took us a little bit, but, you know, we were both lucky and good, which is a good combination sometimes, right? We were, we were smart enough to know when we were, when we had been lucky with some of the developments and then started applying it to really apply problems, biofuels, especially chemicals, pharma, like APIs. And once we got there, cause we could, we could, we could make different types of classes compounds that we knew we could, we could branch off and make other things. And so that's kind of how the terpene story turned into a cannabinoid story because they share some, some commonalities. And that was the hub that we used to raise money. Paul and I and Jim spun this out end of 2019, finally raised some money. And then the rest is history. We we've been supported by the U S federal government from another, number of agencies, which has been really nice to, to continue to work on isobutanol. Um, but also through the NIH to develop, you know, next generation APIs. I think that, so yeah, it's been quite the ride. Yeah. Thanks for the introduction, Tyler. I, um, I always love listening to a good backstory. Uh, in terms of your other scientific co-founders, Paul and Jim Bowie, uh, do they come from similar academic backgrounds to yourself or? Yeah. So, so, so, Jim actually, so he worked with enzymes. Um, he had some amount of computational background as well. Um, and, but he had studied membrane proteins and, and the most basic of basic science. Um, so he was studying like how you would pull a membrane protein apart, like single ones. Right. Um, and so this was a little bit of a deviation, but he was so good technically just understanding how enzymes work and the physics of all of it, that it was a match made in heaven. Um, Paul has a very similar background to mine. He had started off in chemistry as well. Um, he had done more traditional synbio type work. He had worked for, um, before he joined Jim Bowie's lab, he had worked for Jim Liao. You might've heard of him. He was, uh, I think one of the founders of what eventually became Givo, um, the whole in vivo, my subunal technology that was Jim Liao. And so he had some experience working on microbes and engineering them. Um, to do that. And so he came at it from a different perspective of, he had burnt his fingers on the traditional synbio approach and how difficult that was. And then came into this self-free paradigm where it's like, oh my God, like this is all so much easier and so much faster. Why aren't we all doing this all the time? And I know that you have other best in their field scientists working for the company. So broadly speaking, you know, what are their academic backgrounds? Yeah. So, so it's always useful to have experience working with enzymes, right? But at the same time, I think what we tried to avoid from the beginning is just hiring more of ourselves. Right. And because I think there's a lot of benefit on that you end up seeing in, in overlapping expertise, you have different perspectives. And so we've tried to bring on, um, scientists and people with expertise in various aspects, both of enzymology and the self-free space, but in the way beyond that, right. So, so people who have worked, um, from a more computational perspective, right. People who have, um, engineering backgrounds, right. As we're trying to scale these things up, um, and then develop these systems commercially. Right. And so they tend to think about things, uh, differently than your traditional, you know, kind of PhD level biochemists. And so that chemical engineering approaches, um, and perspective is important as well. So we also have some chemistry and some great chemists as well to kind of marry what's, um, what's, what's the best use of, you know, whatever given technology. I think at the end of the day. So enzymes and enzymatic catalysis is, is our focus and what we want to use, but we want to make sure that we're using the right technology and the right, for the right application. There's sometimes that chemistry is going to win or it gets to a really important point very easily. Same thing with nature, right? So nature can make some things really easily. Usually there's limitations to those approaches. And then we come in and we can use those to then build it all the way. Right. Um, I think that's what been one of the limitations of the traditional synthetic analogy approach is we're trying to force the cells to do everything. Right. And so, you know, I think it ends up being hard and costs a lot of money and be underwhelming. And so, you know, we're trying to, at the end of the day, develop things that work. And so that's always been our focus. Yeah, exactly. And, and that's what I've been so impressed by when I was looking at Exozymes and writing my report, as well as my previous conversation with Michael Hilton, the CEO of the company, is that this focus and this mission, which Exozymes has, has attracted a lot of significant talent. So not only from, you know, the scientific team that you just discussed, but also from the business and commercial development point of view. Um, it's a fantastic team and it's really going to drive the company forward. Um, you know, so now moving into Exozymes platform, I want to kind of keep this scientific conversation easy to understand for the general listener and general investor. So before we go into the specifics, can you detail what enzymes are and the associated biocatalysis process? Sure. So, so enzymes are really nice because they do very specific chemistry. So effectively enzymes do the chemistry of life. So when you eat a sugar food or, you know, any type of sugar, the enzymes are actually the things that take that, um, call it a feedstock. So that, that carbon material, what's turns it into the energy that your, your body needs to live. It turns it into the fat, it builds it into muscle, right? So the enzymes actually break down that carbon and then build it up into all of these things. Um, you compare that to traditional organic chemistry, which is mostly from petroleum, where there's a lot of things that you can do with chemistry that, that nature can't do. Um, but at the same time, uh, there are certain transformations and it's dirty generally, right? So there's, there's some things are hard and you get mixtures of things. Sometimes working with chemistry, enzymes are very specific. It's typically, uh, people describe it like a lock in the key effect where a single enzyme. It's a single effectively key or substrate consent to it. And then it converts it into a specific product. So if you now imagine leaking multiple enzymes together, each one with its substrate turns it into a product that's then the substrate of the next one. So on and so forth. It's a very specific chain of events that happens where you can now predict converting your input into that final product with very great control. And specificity. Right. And so, um, and specificity. Right. And so, um, that's the beauty of enzymes. And then we can leverage all of the developments. Um, numerous people have won Nobel prizes recently for how you now engineer enzymes to do novel things, um, to act on different substrates, um, or to be more stable. And so learning from, you know, there are microbes that grow in, uh, these, uh, volcanic vents, for instance. So nature has selected for these enzymes that are in these microbes to be very stable. And so you can use that sometimes as a starting point to say, oh, well, enzymes can actually be really stable catalysts as well. Right. And so you can, you can leverage that, uh, to, uh, make your bio-based catalysis. So you can do biological chemistry outside of, you know, the context of the cell. So when I spoke to Michael, he briefly described the three distinct phases of the exosynes platform. Uh, one being the design and engineering optimization of the company's enzymes, which they label as exosynes, uh, two, the expression and purification of these exosynes. And three, the synthesis of the targeted chemical compounds, you know, in the bioreactor environment. So I'd love to go into a bit more detail about each of these phases and the modern tools that are integrated into, uh, yeah, these, these areas. Sure. Yeah. So, so on the design side, we can leverage a lot of the, the sequencing that's been done, um, over the past, you know, 10 to 20 years where collection of organisms, be it microbes, be it plants, um, you know, fungi, all these types of different sequences. So all their DNA sequences are out there. So what that means is you have these collections of genes, which encode a protein that you can use to select from, um, you can use, you can look at the literature or you can, um, use kind of intuition and design tools to, to now link those enzyme steps. Cause a lot of times it comes with, you know, the function generally of what they're doing. Um, and so as those tools and that ability, become better, become better. And as the amount of information out there increases, that's just more you can choose from. Um, once you have all of that, all of the development of, you know, recombinant DNA technologies where people, that was the bedrock of synthetic biology, right? This ability to now take foreign DNA, clone it, and then put it into like a microbe, right? To get that microbe to do something interesting. Um, using all of those technologies, techniques and tools, we can now use those microbes to make our enzyme of interest. So that means like you have your, your E. coli bacteria, um, that normally doesn't produce, you know, your enzyme to make a cannabinoid, for instance, right? You put the gene sequence in it and now it does. And it makes a lot of that enzyme. And you can now separate that enzyme and use that as your catalyst cell free, right? And so that's effectively our process. We have the discovery, how the pathways work. We then isolate the enzymes by extract, by pressing them in, in some type of microbe. And then we put it together in the bioreactor and we've been really good at being able to develop these systems that are, that are stable, that are robust, that work for long periods of time, you know, and it's basically like doing a chemical reaction, which scales linearly, right? Cause you don't have to worry about oxygen and the growth of a living organism. Um, but still using a biological catalyst. Right. So still using biology. And so that's kind of the benefit that whole platform. Yeah. So in that first design phase, I understand that the company uses, uh, protein or enzyme databases such as alpha fold, as well as computational and AI models that the company has developed. Uh, so how all these different platforms integrate with each other in order to have an optimized engineering, uh, design system. Yeah. Yeah. So, you know, once you have an enzyme that works and you can figure out what its benefits are and what its limitations are, um, then you can go one step deeper and figure out how am I going to engineer this to be even better. Right. And so there's a couple, there's a lot of different tools that people have used in the past. There's the rational approach where you just try and, you know, put your finger on specific residues or locations within the enzyme that you can change to, to change it. Um, there's, uh, there's, uh, there's an approach called directed evolution where you just do it randomly, where you can make these large libraries of mutations and then screen for things that are better. And as we're building out technologies with, with AI, you can now be predictive. And so you can make, um, specific libraries of known mutations, um, screen them and then learn from that very quickly. And so we still leverage all three, um, things are going toward that, that third, um, I think generally out there in the industry, you know, this ability to leverage AI and machine learning to make things faster. We're trying to avail ourselves of that as well. Yeah. So in terms of the AI model, which the company has internally developed, is that specifically towards the optimized enzymes or is that related to the whole platform, such as the bioactor condition, the cofactors or other reagents? The AI right now is applied to the enzyme design primarily. There's no reason why it couldn't be applied to, you know, the more reactions and things that you set, the more you can learn from it. But still, that technology is still being developed, I think, by others. So it's not as mature as applying it to the enzyme problem. Yeah. Okay. So then obviously with the integration of these tools, it has quite significant cost and time savings related to R&D efforts. But how do you ensure that the selected enzymes, which will be, you know, engineered into the company's exozymes, how do you ensure that they are the most appropriate for the biocatalysis process? Yeah. So I think that comes down to having a good understanding of what the underlying economics will be. Right. And so that's what you do up front. You know, I think, you know, it's not just us. That's what a lot of the companies do is you figure out, you know, what are your costs of your inputs? How long does it need to run for? And how much can you make in terms of yield? Right. And then that gives you a general kind of how much can I make this for more or less. And so that defines, you know, how well your catalysts have to work. And then that gives you starting points or ideas of how much engineering or not you have to do for those enzymes. Yeah. And I really like how the economic factor is considered quite early on in the design phase, because ultimately, if the cost to synthesize the compound is too high, then there's going to be no market for it. And we've seen that time and time again in the symbiote space. So then in terms of the specific characteristic optimizations that the company can achieve towards its exozymes, can you detail the engineering traits which the company can achieve? Yeah. So we've demonstrated, and there's a number of papers that describe the ability to improve characteristics such as stability. And this will govern, and this will govern, you know, how you can isolate your, these, these enzymes, the biological catalyst better. It also can reflect how long they will last in a reaction. We've also used these approaches to change things like substrate specificity. So allowing an enzyme to work on a different substrate to make a different product. In addition to cofactor specificity. So, you know, there's biological molecules that are not enzymes. That are in your body like ATP. This is the energy molecule that powers a lot of the chemistry that happens in your, in your body. And so that's just one example. There's a couple others. And so we've developed, we've engineered enzymes to accept different cofactors that an enzyme, you know, wouldn't naturally, a given enzyme doesn't naturally take. For instance. And so, yeah, we, so we've applied it in a variety of different ways. Yeah. And I recommend listeners head over to my exosynes report on Substack and you can find more details about these scientific papers, which the company's released. So I want to zoom in on the stability and element of the exosynes. Is that with the intention to ensure that the biocatalysis process is effective and efficient over multiple batches or in multiple days? Yeah. I think it's, you know, all of the above, right? So there's certain scenarios where you would want it to have, um, be stable for multiple reactions. There's other scenarios where just having it longer over multiple days. We have a, we have a paper that we published, right? As I was leaving UCLA that we stabilized enzymes to the presence of solvent. So isobutanol, which is a biofuel. Um, one of the limitations is that because it's a solvent, it denatures proteins. So we stabilized those enzymes to that solvent. And now the reaction lasts much longer, right? And so, um, if you can make enzymes last or the reaction last twice as long, that's effectively the same as recycling the enzymes once. Could you have the same amount of enzyme that now lasts twice as long? You know, it's the same as if you just, you know, isolated them and restarted again. And so if you can have them last, you know, not just twice as long, you know, but you can have them last. long, but three, four, five times longer, then, you know, it solves tubers with gunstone. So it's a combination. It depends on the application, what the approach is. Yeah. And in terms of the cofactor regeneration innovations that the company has developed, how does this further optimize the chemical synthesis process? Yeah. So, you know, that was one of the things that when we were developing this at UCLA, and that was the first problem that we attacked. Because a lot of times when people are doing multi-step reactions, enzymatic reactions, cell-free, they do one of two things. They either add in exogenous substrate to just power the recycle of the cofactor. That's the traditional way of doing it. Or they basically design a perpetual motion machine, right? Which by definition will eventually, doesn't exist, so it'll eventually wind down. And so those initial core developments were to address that second problem. How can you actually build up excess energy, but maintain the flow of your carbon from your substrate to your product? And so that was, you know, some of the core developments that we allowed. And when you now break, so what that did is it breaks the rules of, or expands kind of what you can do stoichiometrically, because you can build up excess energy, or recover from lost energy. And so it widens the design space. So now there's a lot more types of molecules that you can actually go after, because you don't have to have this perfect balance of, you know, energy production and energy usage. Yeah. And so all these factors, you know, the cofactor regeneration, the specificity, the stability and other characteristic elements, they all work to reduce the cost per production batch of Exozyne's platform, which makes it very attractive. for partners, right? And out in the market. Right. Yeah, great. Okay. And I'll also be speaking with Damien Perriman, the chief commercial officer of Exozymes about what potential partnerships could look like in the future. So then now zooming into the second phase, how efficient is Exozymes at expressing and purifying its optimized Exozymes via microbial hosts? It's primarily based on the existing technology. That's a relatively mature technology, this ability to overexpress and isolate enzymes. There's a number of companies that have pioneered this going back decades. And that's the whole point is that that works. Cells want to make enzymes, right? They don't want to make your chemical X to be able to sell, you know, as some type of pharmaceutical. They want to make an enzyme to live, right? And to grow. So we can kind of leverage that ability of these cells that kind of want to just generally make enzyme. They do that really well to make our catalysts. And so a lot of that technology has been established, you know, standing on the shoulders of others, right? It's the saying. We still do try and push things forward as much as we can. But yeah, a lot of it is based on mature technology. So then moving into the third and final phase of the company's platform, where you synthesize the targeted chemical compound in a bioreactor environment. Does this occur in, you know, relatively standard industrial bioreactor equipment or has Exozymes developed, you know, unique infrastructure specific to its platform? As much as we can, you want to leverage kind of low cost infrastructure that's already established. That's not going to fit for every example, though. But by and large, that, you know, getting away from, you know, bespoke fermentation for every specific thing that you're trying to make, which is kind of the symbiote way of doing things to the more chemical way of doing things where, you know, you have a general, you know, glass or glass lined or stainless, depending on how big it is, right? Reactor that uses, you know, standard off the shelf parts. That's, that's the idea. So if I could, you know, summarize everything that's been said so far, Exozymes platform simply operates more like a chemical reaction process, whereby all these ingredients are added into the bioreactor, which allows the chemical synthesis process to occur. And it's these specific ingredients, which the company has innovated and developed, which provides the advantages of Exozymes platform over all the existing chemical production methods. And in the previous interview, Michael stated that obviously cell based technologies have significant issues towards scaling as well as the unit economic cost. You got it. Okay, so then having a great understanding of Exozymes platform and its three distinct phases, I'd like to discuss its advantages, and I provided a long list of these in my Exozymes report over on Substack. But I'd love to specifically zoom in on the near theoretical yields and titers in which the platform can achieve. Yeah, so because enzymes are specific, you tend not to get side products, right? Usually it goes down to a single product at the end. That's, that's a benefit. And if you design the systems appropriately, because one thing that you can never change is the thermodynamics of a system, changes the thermodynamics of a system. And so if you can make sure that it's over overall thermodynamically favored, then you can get to really high yields as well. And so because you don't have limitations of like a cell membrane, so you don't have to worry about like your cells dying, things like that. It really, and because there's not other things going on in the cell. So cell is, it has all of metabolism, right? It's not just going to take that sugar and turn it into the product that you want. It's going to turn it into the DNA, the fats, the everything else that it needs to live. So when you go cell free, you get rid of all of that background, right? And so now all of your carbon just goes to your product of interest. And so your theoretical yields can be high because of the specificity. And then the overall yields can also be high because that's basically all the only way place for the carbon. So then ultimately with these high titers and compound doesn't have that many impurities compared to, you know, cell-based technologies. So then the downstream processing is relatively straightforward and quite cheap. So then in terms of Exozyme's ability to synthesize new to nature compounds or tweak the performance of existing compounds, how does the platform achieve this? So, so, so we have a paper that was published where we made basically two different types of rare cannabinoid, right? A common one and a rare version simply by changing the input, right? And so enzymes, while they're specific, they can also be a little bit promiscuous, right? And so we leveraged that to be able to now make not just one, but two different products just using the same set of enzymes. Right? And so that's also the beauty of the cell-free approaches. You have complete control over all of your inputs. So because that you can more easily to, you know, a more diverse set of final products. Yeah. So then as the platform operates more like a standard chemical reaction process, now with this high level degree of control, it greatly reduces the risk when scaling from a lab into commercial setting, unlike cell-based technologies. I think there's a lot of things that go into scaling by like living cells, symbiose based systems. Only one consideration is whether your product is toxic or not. You know, sometimes something as simple as you need oxygen to aerate, and then your ability to do that at very large scale becomes more difficult. For a living cell. With a cell-free system, you only use oxygen if you need it, right? And because you have complete control, you can do things in smaller reactions because you can concentrate these enzymes as well. So it solves a lot of the difficulties, I think, in just setting up and deploying these things. They should scale more like a chemical reaction than bio-based solution. Yeah. And so like the system that we set up with isobutinol, for example, we were able to use a, like a biphasic system where you have like an overlay on top of it. And the overlay that we used would normally kill the cell, right? And so it, that ability, you know, because you don't have to worry about something living now expands just the types of things you can use to separate as well, right? And so it basically gives you more options at the end of the day. So now I think it's time to look at the scientific reports, which Exozymes has published in the past. And I've detailed these in length on my Substack report. So I recommend listeners to go and look at that and click on those links. But can you detail what occurred and also the achievements and results that were accomplished? Sure. So I'll start with the cannabinoid story. Both of them, all of this work started with central glycolysis, which is a fundamental metabolic pathway and that's present in all living organisms, where you basically take a sugar and you break it down into two or three carbon building blocks and energy. So that's where we started with that premise. And once we developed the regulatory systems, we could turn that sugar into these building blocks. And then the first thing we made was a terpene. So these are flavor and fragrance compounds. So it's, you know, limonene is the thing from lemons that gives it kind of its lemony scent. It's a, it's hydrocarbon at the end of the day, the department of energy supported this because it could be had potential as, as a biofuel as well. We were able to set up a, an ambitious 30 enzyme pathway relatively that worked to make, you know, tens of grams per liter. So we were able to set up a lot of products very quickly. And then the first thing we made was to make a lot of the products very quickly. Normally that compound itself, limonene is also toxic to cells. So it gave you that advantage. But we took a step back and we said, Hey, if you can make this much limonene directly from a sugar, that means we can make the, the compound that leads up to limonene. It's called geronyl pyrophosphate. We could then use that compound to modify small molecules. By simply feeding in now what's normally a plant. So it's called a plant product, all of tolic acid. So that's what plants make. And then you could specifically attach this GPP, the geronyl pyrophosphate to that. That makes CBGA, which is the precursor to all of the cannabinoids. Right. The key there though, was that we knew we could make the GPP, but the enzyme from the plant was a membrane protein. So we knew that that was going to be difficult to work with. Cell-free membrane proteins. And so we designed, we found a bacterial protein that did a similar reaction, re-engineered it to actually do the reaction that we want and show that we could use this approach now to make just by feeding in the one substrate and making the other one. We could then use that designed enzyme to put the two together to make CBGA. So that's how the, the whole glycolysis to terpenes and then marries with cannabinoid production because it's reusing all of the elements that we had already developed. So we had done a lot of that work, um, up front. So the terpen work was some of the earlier stuff that we had done. We had a lot of experience with glycolysis. And at the time we were talking to the DOE and they said, well, can you do something else? Can you make something that's more DOE related? Um, it has a better carbon yield. Can you make isobutinol? And that's actually just five enzymes off of the end of glycolysis. And so we demonstrated you could do that really quickly, um, show that you can make isobutinol. Interestingly, our first attempts made enough isobutinol to denature the proteins, which is also the limit that you get to in cells. Um, if you, if you don't do any kind of crazy engineering. And so we recognized, Hey, if we just stabilize the enzyme, that's one of the limitations. There's others, but that's one of the limitations is that the isobutinol you make, um, kills those enzyme. If we could just stabilize them, then we could produce potentially much more isobutinol as a biofuel. And so that's what we did. We didn't just stabilize the enzyme, the five enzymes to make isobutinol. We stabilized all of glycolysis. So the whole pathway. And so now you had enzymes that were, um, heat stable and solvent stable, simplified their isolation, and then it lasts, allow them to last much longer. And so then we were able to, to make, you know, I think the, the published amount is 250 grams per liter affected titer of isobutinol within, it was four days. So the, it was about, you know, two times the, the rate that you could get in, in cells. Um, so it's max rate was about four grams per liter per hour. It did slow down over time, but you know, it got to a really high titer and all of the sugar that went in, all that glucose went directly to isobutinol and nowhere else. So when you measure it, you basically have your starting input glucose, because we really tried to push it. as far as possible. And you had isobutinol and that was it. And so it demonstrated that not only could these systems be really efficient and last for a long period of time, but in engineering these enzymes to be stable, you could increase the length of time that these systems work. Yeah. And I'd like to add that these scientific reports were released quite a few years ago. So before the integration of the modern tools and all these exciting developments that have occurred more recently with the platform. Um, but something which was announced, uh, but something which was announced, uh, just recently, which is also very exciting is that Exozymes, uh, developed a chemical from the design to the actual synthesis in a matter of weeks, which is honestly something truly unheard of. So Exozymes also holds numerous patterns towards its platform and the numerous scientific innovations, which the company has developed. Uh, so what are the elements, uh, which make it hard for a competitor to represent? Yeah. So, so, so there's, so we have IP that covers, uh, a broad array of the technologies, right? And so you can bucket it into, so there's, there's process, uh, composition of matter and, and then the enzymes themselves, right? And, and the know-how to, to make them and to set up the, those reactions. And so, you know, within the process you have both how to set it up in addition to some of the, the specific enzyme mutants that are, go into that pathway. Um, and then on the composition of matter, we have definitely small molecules that we've made, right? That, that you have IP on, um, as well, right? That, that final product. And then kind of that third part within the trade secret about knowing how to set these things up, um, really makes it hard to, to replicate these systems and the ability to do that. Yeah. So existing chemical manufacturing methods and cell-based technologies have a lot of inherent issues. And X-design's platform looks like it can overcome a lot of these downfalls. So then with these advantages, uh, you know, competitors may enter into the space with, you know, competing technology platforms that are somewhat scientifically similar. However, X-design's has a lot of the patterns, which you alluded to, and also they're the first mover advantage. So then how significant is this? Yeah. I think, I think, I think that's actually quite big. You know, we have the knowledge and experience of working with these multi-step reactions, um, which takes some doing. Right. And I, I think that, um, you know, having that perspective, in addition to IP that covers some of the aspects that make these things run for long periods of time, I think gives us, gives us an advantage as well. We've also been doing this for a long time. Yeah. And I can imagine reverse engineering the platform would take a lot of time and also a lot of capital. Yeah. Yeah. And there was also an announcement released recently where there's more development, uh, occurring on X-design's platform. And this has been supported by federal funding, which is really exciting to see. Um, so as we finish off here, uh, what vision of the future are you most excited to bring forth with X-design platform? Yeah. You know, I'm, I'm really excited to see our technology solve problems in the market, right. To be able to produce chemicals that, that people want, um, that they've had difficult, a difficult time accessing, right. For a variety of reasons. Um, you know, can abenoids fit that picture? I should be an office that picture as well. Right. As a, as a, as a, as a renewable solution for fuels and modern chemicals. And so, uh, really being able to execute on, on what we've built in the, the platform that we've designed and, you know, seeing that be realized is, is, is where the vision goes and how this continues to grow. So yeah, I'm really excited. The future's going to be future's bright. I think, um, we have a lot of things that are exciting that, that we're trying to do. So yeah. Definitely. And the, the future's looking very exciting for X-designs. I'm very glad to be a shareholder as part of the company, but as, uh, as we finish off the interview here, was there anything final that you wanted to add? You know, I don't, I don't, I don't think so. I think, I think there's, there's been a lot of stuff that's been done using synthetic biology. A lot of things have been tried. Um, some things have worked kind of, um, but there's not a lot of successes. I think at the end of the day, you know, the markets need options to make chemicals that people want, right. As, as Michael says, to, to give them the life, to give us the life that we want to live, right. The good life. Um, and so, you know, I think, at the least we're providing options for, for people to be able to make those, those confines that can be used in, you know, as, as fuels, flavors, pharma type applications. So yeah. Great. Yeah. Well, thank you so much, Tyler, for jumping on and having this extended conversation about the science behind the platform, a bit more about the intricacies. I'd like to remind everyone to jump onto my Substack report on X designs and read all the details and find out further information about what we've covered today. But, uh, yeah, thank you so much for taking the time and I'm very appreciative. Yeah. Thanks again. I really appreciate your time and asked me to chat. Yeah.