Grant Aarons - FabricNano - Part 1

Intro - 00:00:01: Welcome to The Biotech Startups Podcast by Excedr. Join us as we speak with first-time founders, serial entrepreneurs, and experienced investors about the challenges and triumphs of running a biotech startup from pre-seed to IPO with your host, Granthee.

Jon  - 00:00:23: My guest today is Grant Aarons, Co-Founder and CEO of FabricNano, a London-based biotech whose mission is to transform industrial chemical processes using cell-free biomanufacturing. FabricNano empowers users with the world's most advanced, flexible, and easily scalable biocatalyst platform. With clients ranging from startups to multinationals like Sumitomo Chemical Company, FabricNano provides highly stable and performant biocatalysts to enable profitable production of sustainable and biobased chemicals. FabricNano's approach starts with novel immobilization engineering for enzyme stabilization, followed by budget-conscious protein engineering and process engineering to reach their clients' targets for commercialization of their new biochemical production process. Before FabricNano, Grant was a Research Analyst at the Federal Reserve Bank of New York, and while pursuing his PhD at the London Business School, became an Entrepreneur In Residence at Entrepreneur First, an international business accelerator that has created over 300 companies worth over $10 billion. Grant's diverse experience gives him a unique perspective on the startup ecosystem that everyone can benefit from. Over the next three episodes, we cover a wide range of topics, including Grant's New York upbringing, his hands-on academic experience at Cooper Union, the once-in-a-lifetime opportunity at the Federal Reserve Bank of New York, his decision to attend London Business School, and FabricNano's unique approach to industrial biology and creating a more sustainable future. Today, we'll chat about Grant's early years growing up in New York City and its influence on his leadership style and business philosophy. We'll also touch on his time as an engineering student at Cooper Union, his roles at the Federal Reserve, the impact of changing interest rates on different sectors, and the challenges faced by capital-intensive industries like deep tech. Without further ado, let's dive into this episode of The Biotech Startups Podcast. Grant, good to see you again. Thanks for coming on the podcast.

Grant - 00:02:03: Yeah, nice to see you too, Jon. Hope you have a happy holiday.

Jon - 00:02:06: Yeah. You know the drill. It's a whole thing, but we made it to 2024. We're alive and well. But yeah, so our team and I were looking into fun ways to start off this conversation. And we thought it'd be cool to start off with the early days, maybe jumping to what was your upbringing like and how did it influence your leadership style and your business philosophy?

Grant - 00:02:28: Yeah, I'd love to talk about that in more detail, Jon. And especially thinking back to the most recent holiday that we were both on with the winter break, it's nice to think back to New York City in New York, where I grew up. I grew up in a small town called Croton-on-Hudson, which is upstate New York. Westchester meets more of New York State, where the big legislature is. I remember being a kid and driving around in a car at a very young age and just thinking to myself as we went through all of New York State. How does all this infrastructure work? And just really loving the idea of being a young kid who didn't know anything. And I feel like going all the way back to that time in New York where I grew up, it's been helpful to think about that in preparation for this interview, because that is consistently what it feels like to be running a company. It's just constantly thinking about the world around you and how it operates. So, yeah, I grew up in New York, then moved on to university in New York, called Cooper Union in New York City, and ended up being a mechanical engineer. That's how I started my career from high school off to undergrad.

Jon - 00:03:30: It's interesting that you brought up looking at the infrastructure around you and how it works, because growing up in the Bay Area, I was looking at the infrastructure and I was like, why doesn't it work? It was more of the inverse.

Grant - 00:03:43: I saw dams, big water dams and big power lines, things that can't break down. And they seemed to be working just fine when I was a kid.

Jon - 00:03:50: Yeah, you had a much far more lucky upbringing than this. I was like, hmm. So our equivalent of like the subway over here is BART. And I was like, is this supposed to be like 30 minutes late every time? And going to New York, the New York subway, I'm like, oh, it works. I mean, granted, you've been on the New York subway far more than me, but.

Grant - 00:04:10: Yeah, it's a fascinating thing, like having 10 million plus people go into New York City every day. And it functions without almost like a hitch. My dad always tells us funny stories. He asked this funny question. He's like, how many eggs get transported into New York City for breakfast every day? And he does this funny thing when we were a kid. He'd be like, back calculated, two eggs per person, maybe 50% of families, 50% of people eat eggs. There's still 10 million eggs that every day have to get inside of this tiny city. And it's those kinds of questions that I think are so fun to play with and toy with because these logistical challenges are fascinating. How does material and how do produce get to where they need to get to and get consumed by people who need to live a nutritious and healthy life? I think it's fascinating.

Jon - 00:04:58: It is actually kind of crazy because also I feel like they're like limited ways into the city too. And so.

Grant - 00:05:04: You can imagine a hundred trucks on a bridge. Yeah.

Jon - 00:05:07: Yeah. That's it.

Grant - 00:05:08: Like hundreds and hundreds of egg trucks.

Jon - 00:05:09: Yeah.

Grant - 00:05:10: That's what I thought when I was a kid.

Jon - 00:05:12: Yeah. So as you're growing up, did you always know that you were going to get into business and eventually science? Or was this something that kind of like coalesced as you were at Cooper Union and getting further along in your academic studies?

Grant - 00:05:29: In high school, I had a really strong inkling that I wanted to be in business, and I had a fascination with economics. But then moving into the university sphere, I thought, let's do something practical. Let's become an engineer. I want to build things. You can start companies by building cool inventions. That's a bit harder than it looks as a kid. As you get through your degree and you realize that there's not many new things that get invented every year in terms of physical systems. But when I went off to university, I really had this mindset of, I just want to build things. I want to build physical things, cars, engines, wings of planes, things, things, things. And that's why I chose to go to Cooper Union, where it was one of the only schools that I had researched and applied to, where there was a philanthropist back in the Industrial Revolution who decided to make the school, kind of like Andrew Carnegie, less well-known, named Peter Cooper. And so Peter Cooper started this thing called The Cooper Union, which was a trade school, 1859. He was an inventor at heart. This guy invented gelatin, the washing machine, the modern washing machine, and some of the earliest I-beams that connected two different types of railroad ties into what looks like an I-shape so that they could be mass manufactured. And this guy was responsible for inventing the infrastructure for some of the first really tall buildings in New York City that were over five stories, six stories tall. And so I decided to go to that university because I was enthralled in the idea of building and inventing, but also the legacy of that school as being an inventor's school and a trade school from first principles.

Jon - 00:07:05: Very cool. I didn't know the history of Cooper Union, and that's really fascinating. And as a kind of a more inventor-esque kind of lens as an academic education, did that lead to a laboratory environment where you had like an undergraduate lab experience? Or was it something more theoretical where you're doing the thing where you're like, okay, yeah, in theory, this is how you build something reading in a book, and then you spit it out on a test?

Grant - 00:07:28: I think if you've ever been to Cooper Union or if you ever plan on visiting, you'll see lots of labs and lots of things being created that are physical. So I remember being a freshman and 18-year-old kid comes to this school that was invented by a heavily bearded man in the 1850s with like a four-piece eyeglass. And the first freshman year class I was in, I was on a lathe making brass screws, but also using a CNC machine to carve out metal as an 18-year-old. I was like, how are people allowing me to play with this stuff? This is crazy. You're letting kids touch tools that adults are supposed to use, right? It's a really exciting time. And we did a lot of work in the machine shop, but we also did work with chemistry labs where we'd use synthesis techniques. But then we'd have to purify and dry out the products. I remember like the word crucible appearing. All I could think of was like Shakespeare and all these old English terms. It's a crucible. What's the crucible? It's made in the crucible. And we use the crucible to dry out something and create some kind of powdered substance that you could then measure. And we did all that when I was 18. And it was really exciting at the time. And I was really driven into engineering because of those applications. And I felt the education was fantastic at Cooper Union.

Jon - 00:08:45: That's wild. The labs that you kind of described to is like, there's like physical harm, serious physical harm, because the labs I was in, like, yeah, a pipette can hurt you if you're being silly, but like a CNC machine can lop off a finger or more very seriously.

Grant - 00:09:02: Yeah, there are serious risks of accidents. And trust me, I know what an MSDS sheet is because I had to read them and I had to put them in a physical notebook. Way back then reporting all the important things you need to know before you did your experiment. Most of my team at FabricNano does not know that story, but I too have read a few MSDSs in my day. And I'm opposed to that level of granularity. And that's not what I do today, running FabricNano, but it's a very important part of being a safe practitioner of science.

Jon - 00:09:34: Absolutely. The stakes are high. The stakes are very high, especially when you're young. So while you're at Cooper Union and getting this experience, were there any standout mentors or professors that inspired you while you were there?

Grant - 00:09:48: Yeah, I didn't actually apparently talk about this, but there was a course, it was called like EI103 or something, it was taught by this professor named Eric Lima. And the course was all about making new inventions. I remember it really fondly, actually. We were building a laser adapter for the CNC machine. This is like 10 years or more in my memory now. But we had built this cardboard setup of all the arms that would have to be put in place for a laser to traverse a bunch of mirrors and allow you to cut out something in real time while you were working on metal. You could then cut out something else using a laser. I remember the laser that it's like, had this huge warning on it was like level four laser, do not look at it, you could go blind. And everyone in our class thought that was the coolest thing. It's like, oh my god, the laser. And then later in that course, we learned to like laser cut out small parts for automata little machines. And yeah, it was a great experience. And the professor was a true inventor that wanted to make things happen with his hands and wanted the students to do the same. And it was exciting. It definitely sticks with me.

Jon - 00:11:02: That's super rad. I can empathize like, oh, that laser is like, ooh, shiny and very powerful thing. Like..

Grant - 00:11:09: Cuts metal.

Jon - 00:11:10: Yeah. On the fly.

Grant - 00:11:12: They did not let us turn it on.

Jon - 00:11:13: Yeah.

Grant - 00:11:14: But we built the enclosure. That's about as far as we went.

Jon - 00:11:17: Yeah. And I know during your time at Cooper Union, you kind of started a lot of work opportunities simultaneously, I believe, in between each year of your studies. Can you talk a little bit about the work you got into during your academic studies?

Grant - 00:11:29: Yes. So the work I got into follows, I guess, the trajectory of a traditional engineering student. You come in as a freshman, you do all these really cool things I just talked about. And then by the end of your four years in an undergraduate institution at OECA, you end up ready for consulting. You've done a lot more work on data and preparing presentations. And so you've reached the other end of the spectrum. And so a lot of the summer jobs I took followed the similar trajectory. So in my freshman year, I did a project where I coded up on Android with another student. The augmented reality package so that we could do a really cool kind of like QR code that was hung up on the side of the building. It was like 10 feet by 10 feet. And we had this mobile app on my Android phone at the time that you could download, point at the QR code from across the street. And then all of a sudden these pictures pop-up. So it sounds like a lot of the stuff you now use post-COVID when you go to a restaurant to order some food 2021 and beyond. This is 2011. And these packages were awful, you wouldn't recognize what they called the glyph at the time. It wasn't a QR code, it was a glyph. And you had to learn to work in these weird like coding environments. The one we were using was called Eclipse. And it was like a very strange thing to be coding as a 18 year old. But that's where the jobs started. Then I ended up applying and trying my hand at the mechanical engineering trade. And I joined an engineering firm that does MEP, which for the engineers out there is mechanical electrical plumbing. The core constituents of a building. And that was a great summer of learning what it's like to be a real practicing engineer, which to Cooper Union's credit, 50% or more of the students do come out and practice engineering, which is very rare in America now. But the school is known as a trade school. And so I tried my hand at the trade and that was interesting. But by the time I reached my junior year, I was doing a lot more research into economics. So finding that love that I had in high school and bringing it back and taking a few elective courses in economics, even taking some art classes, which was fascinating because the school has art architecture and engineering. But expanding my horizons to what might be my interest in my first career. And that's where I started applying for jobs in banks and eventually got a job at the central bank, The Federal Reserve, and took a job as a summer analyst. And I was so proud of that at the time because it was a totally random online portal, thousands of applicants. I got one of the 10 jobs there. As a mechanical engineering student with no econ background, I got an internship. And it's just fascinating to be at the bank. As a 21-year-old, having done this crazy thing called Fed Challenge, which these 16, 17, 18-year-olds do in high school. So I had done some presentations around Ben Bernanke at around the time of the financial collapse, and then moved forward from 2008, 2009, all the way to what was 2013. And there I am at the bank, trying to apply for a job, getting a job. And I'm like, I'm going to get to work here, at least for a summer. And then it turned out to be a full-time job thereafter.

Jon - 00:14:39: That is wild.

Grant - 00:14:41: So many career changes that you're going to get like mind blown because I've changed careers three or four times. I'm only 32.

Jon - 00:14:46: That is so fascinating to me because like, I think sometimes when people see people in their current career, they think it's kind of like this straight line where it's like, you've been bestowed like this, like calling from early days and like, it just like connects. But I love hearing that because my journey was a sort of cubitus one as well. But a couple of questions, when you were an Android developer, did you just like, yeah, I'm just going to learn how to do this. Because I don't think at least I'm not a mechanical engineer that mechanical engineering and Android are even adjacent. Was it a hobby?

Grant - 00:15:20: You could use Eclipse, this programming environment to manage your MATLAB packages, which we used a lot of mechanical engineering, and you could download and install Android packages and then create like these applications for the phone that you could ship to the phone. So it really just became a summer project because I had asked that the student, like, can we get into this space? Sounds like a really cool thing that people are developing now. And we learned that we could download some packages and do some pretty cool things pretty quickly using the same coding environment. So we're like, this is cool. I got my MATLAB homework assignment next to my summer project. And they're all in the same kind of cool sandbox that you get to play in as a coder. So I found it to be difficult to pick up syntax back then without as much stack overflow as there is now. And as much help from like copilot and code generation as ChatGPT will give you. But I do think that back then, the syntax was the hard part, learning a brand new language with documentation at the time. But the experience was great. Just like getting your hands on code for the first time and running it and debugging it. I remember when I learned about debugging, I was like, you could put breakpoints in code and just check out what happened midway through. This is so cool.

Jon - 00:16:30: By no means do I have this level of experience that you have, but I do remember having a similar experience during the debugging process. In the early courses I took, I was like, oh, granted, that was many, many years ago. And I'm sure it's like far easier to debug now.

Grant - 00:16:44: Honestly, I am a bad coder nowadays. Debugging has become a whole art.

Jon - 00:16:48: Yeah.

Grant - 00:16:49: And back then it was a fun little toggle you could put in your code to like, okay, what's happening now?

Jon - 00:16:54: Yeah, yeah. And it's like you tried your hand at practicing the trade. Was there an aspect of the trade that you're like, eh, this doesn't vibe with me?

Grant - 00:17:02: It was, to put it extremely simply, which I think we'll get back to when we talk about the current company that I run, FabricNano, the feedback loops in engineering are incredibly slow. And they could be slightly faster if you're working for a product company like, let's say, Dyson or a car company that's innovating on new electric cars. That could be really fun. And there could be feedback loops of less than a year to see your product actually come to fruition. But the types of projects that traditional engineers work on are 10, 20-year, build a new bridge over a river. And I remember when I was in school, the big project that everyone was talking about at Cooper Union was the fact that the Tappan Zee Bridge, which is this bridge that goes over the Hudson River, connects New Jersey to New York, further up from Manhattan, where the furthest bridge in Manhattan is the Washington Bridge, which is not that far north. The Tappan Zee Bridge is going to fall down. It's 20 years past its 100-year lifespan. We've got to build a new one. And everyone was like, we know we have to build a new one. And so the exciting thing was all the civil engineers were saying, yeah, I'm going to get into bridge building, structural civil engineering. And maybe by the time I'm like 40 years old, we'll have built the new bridge across the Hudson River. And it has been built. That bridge has been built. But it took 10 years to build that thing. And it is incredible. And it stands the test of time. But it's too slow, I think, for someone who wants to see feedback, iteration, pivots, moving in a consistent direction that you get to nudge to something that's truly innovative. I don't think that the traditional engineering projects fit that mold of fast iteration and feedback loops.

Jon - 00:18:40: Interesting. And so now you got the sweet gig at the Fed. And correct me if I'm wrong, did you find faster feedback loops at the Fed? Or talk a little bit about that. I'm really interested about your experience there at first as like kind of your summer gig, and then that turned into your full-time gig.

Grant - 00:19:00: Yeah. So my summer gig was to come in as an analyst, which means you do a lot of different things. I was actually hired into the operations team of the Fed, which is a whole organization in and of itself. The New York Fed, which is part of the grand central bank system of America, is one of the larger Feds. It has a permanent open market operations seat. The president has a seat at that table as the vice chair to the chairman, who everyone knows. And when I was hired into this 3,000 person organization in New York, I was part of a 100 person team, just making sure the bank ran smoothly. So what this meant was checking in on certain sites that exist in the system to make sure that treasuries can be transacted, even in the worst apocalyptic scenario. And making sure that the financial system wouldn't collapse. So there's a few of those sites and I got to visit a few of them. And making sure, for example, that the police force that protects half the world's gold in New York City that's sitting in the basement is actually paid and is happy with their pay. But I also had this feedback loop. They gave me one big project, which was to build a sustainability initiative within the bank. This is back in 2012, 13. And the sustainability initiative was really about publicity and knowing what was good and knowing what was bad about what the Fed was doing with circulation of money, destroying of money. There's a lot of paper that's used by the central banks of the world and the power that goes into running the servers that run the transactions of treasuries. But I was working on a website that I got to build, and I had never built a website. I was like, let's build a website. So I'm building an intranet website to talk about sustainability in my getting feedback every week about what needs to change. And my manager is saying, this thing doesn't resonate. This looks too childish. Can you fix this? And I was like, man, my CSS skills are really going through the roof now. It's like trying to learn how to build this stuff. But at the same time, I thought that the feedback loops and the iteration that went into learning economics at the research level was unprecedented. So every week there would be numerous research presentations from Nobel Prize winners that would come in and give talks. So I worked on the second floor. But on the third floor, every week in the corner, 30 person room, you'd get people like Chris Sims, who won a Nobel Prize, coming in to listen to someone who came in from Europe to chat because he works over at Princeton. And so one day I'm sitting there and I'm listening to this conversation about a research paper in economics. I was like a 21 year old kid who knows nothing about economics research. I've never even taken a course in it. I was listening to these papers and these ideas that people are throwing around for statistical models and all this. And I leave the room and one of the interns that had gotten an economics internship. Turns to me and goes, did you know who you were seeing next? I was like, no, who's that? That's a Nobel Prize winner. They're at Christopher Sims. He won in like 1999. I was like, what are you talking about? And so the opportunities to think about things were unprecedented at the Fed. The models, the statistics, the way in which they incorporate new ideas into modern thinking for how the system should operate. I ended up getting a job in the research group because I showed up to all of those meetings, all of those extra brown bag lunch talks. I got a real research job doing dynamic stochastic general equilibrium modeling, which is a fancy way of saying really great MATLAB with matrix math, right? And those models still confuse me, but I got a job in that department and I got a two-year full rotation as a research analyst doing real economics work for the Fed. And that was one of the fastest paced environments I ever joined. And 20 economists I had worked with on projects. So it would last two weeks to six months. Ended up presenting those types of things to the president, to the New York Fed. So this person could then go make good policy. It was a wild experience in presentation prep. Would have made a really good consultant.

Jon - 00:22:55: Yeah, exactly. Exactly. That is wild. And also seems like a stark contrast to the role that you're in previously, where you're like, well, I'm not going to see this for 10 years. And now it's just like, no, no, go, go, go, go. We need to institute policy changes here.

Grant - 00:23:11: Yeah, they're like, we're going to let Fed funds rate. This is 2014 to 2016. 2015, they're like, we've had a zero interest rate for 10 years. What happens when it goes off of zero? And everyone's freaking out. Like, we need to figure it out. We need to figure it out. And there was a lot of work that went into making sure the economy didn't collapse when interest rates went from zero to something other than zero. But if you think about how big of a problem that is for an industry that operates on correlations and linear algebra to have a discontinuity in your major policy instrument for 10 years out of a 70-year sample, how do you even think about modeling the next time point? It's impossible. You have like zero basically plays like a man or not a value, right, in your math. And that's the most important value in all of your math. And you can't use it really.

Jon - 00:24:02: Yeah, I'm making light of it, but it sounds like prayers. You're like, well, let's pray that this doesn't just bore the system.

Grant - 00:24:11: It's that kind of thing where you're asking the question, we've never been here before. What happens next? That people have to innovate and build new models. So when we were at the Fed and working there, I got to work with this guy named Domenico Giannone, who was building some of the most advanced models on how to think about understanding the economy in real time. And so these models ended up being my focus in my early years of my PhD before I dropped out. And they're today, a lot of the models that go into dynamic pricing for groups like Amazon. This economist had worked at Harvard, was a functioning full senior economist at the Fed in New York, had published some great stuff. We put a model out called The Now Casting Model that forecasted GDP every day and could be very useful to things like financial asset pricing. But actually this economist moved over to Amazon to help with the dynamic pricing. Like these models come out of periods of extreme stress where you don't know what's going to happen. That's when you innovate and you build new systems and you rely on new tools.

Jon - 00:25:22: Interesting. That's super fascinating. We've talked about the Fed in some detail, but we hear about the Fed in the news and how the rates are going up or where everyone's making their predictions. But for those who maybe are unfamiliar, and I'm going to say I'm an outsider looking in, could you maybe just set the table for us on what is the Federal Reserve Bank's purpose? What do they do and why is it important?

Grant - 00:25:49: There's a dual mandate at the Fed. So the reason the Fed was established and is separate from government, but not really private either, just works with the Treasury to facilitate transactions for the Treasury of the United States government and to control market conditions. There's two reasons. One is to keep inflation in check, and two is to keep unemployment low. This is those two goals that drive the entire set of activities that the New York Fed and the rest of the Fed system across the country executes. So how do they do that? They have this thing called the central bank rate or the Fed funds rate. The Fed funds rate is something that could be anywhere from 0% to 10%, 20% in really difficult times, and it's traditionally in our lifetime been around 5%. Now, the Fed funds rate, you can think of as the cheapest rate you can get to borrow some money. So if I were to borrow some money from the person who has the most money in the world. What would they charge me as interest? That's your Fed funds rate. How that's established is slightly confusing in terms of what the market operations are to make that rate a reality. But the Fed has the tools to set this lower rate of borrowing. And if you imagine what that means, that means that if the safest place to borrow money gives me 5% interest on the loan I take, then if I take a loan from a less safe place, I'm going to be paying more than 5%, maybe 6%, maybe 7%. And so you'll always see that the Fed funds rate is the lowest rate in the market for borrowing money. And then everything is stacked on top. So a five-year mortgage, a 10-year mortgage, a 30-year mortgage, we call this thing the yield curve for mortgages. There's the same thing for treasuries. Treasuries at one year, two year, 10 year, 20 year. They're all increasing interest rate based on risk that comes off of the base rate, which is the central bank rate, the most safe place to borrow money and what rate they're willing to give you. So the Fed is a very important institution because if you control that rate, you make sure that people don't spend beyond their means, and you make sure that there isn't a bubble forming in things like the housing market. And you have more stability and predictability to things like inflation and unemployment. And that's the goal of the Fed, is to create stability. It's not to create prosperity. Prosperity is something that depends on technical innovation, technology. A lot of people in economics think technology is the core thing that drives the abundance of productivity and wealth for a nation. And the US is very good at productivity and creating innovation. And so it's very wealthy. And yeah, all these models align with the Western economy. Of course, they do and there's problems with that as well. But we won't go into that. The thing that's quite beautiful here is that an economy that is stable is an economy that you can rely on, and is an economy that you can build your life in. And so if you want to live in a place, you don't want unemployment to go above 5% because it means you'll be out of work for a very long time. You don't want your life savings to erode because inflation is 40% in one year. And now everything you've saved for your entire lifetime to have a retirement is worth 10 cents on the dollar. This is the purpose of the Fed, is to make sure that people can build a life and can rely on that life in the country they live in. I hope I did a decent job explaining that.

Jon - 00:29:14: No, that was kind of like that meme, just like mind blown. So that was very good. That was very good.

Grant - 00:29:22: You're seeing the interest rates going up. You're seeing the interest rates go up. And you're thinking about that dog in the brain house. It's fine. It's fine. It's fine for a reason. It's okay.

Jon - 00:29:30: Yeah, everything is fine. Everything's fine. And you touched on at your time working at the Fed, you guys were contemplating what would happen if you're going off zero. And now we're coming off that right now from 2020, 2021. And then we're in 2024 now. From that perspective, can you just give us a little bit of your thoughts on what we're coming out of and what we are in now and how that has an impact on companies who are in hard tech, deep tech, innovative technology, and the broader economy?

Grant - 00:30:02: It's incredibly important. And I think people do ask me this question quite frequently in my board and my investors ask questions like this. So you worked with the Fed, you must know how this impacts. The point is, I can give you a mechanical understanding of what we're going through. And I think it's important to put things in this high level mechanical light. But there is always idiosyncrasies in the economy and what will happen in the future that I can't predict, right? So everything I'm about to say is with a grain of salt, because things could just fall off a cliff if there's a war tomorrow. I mean, things will change. And what I say is completely invalidated. But when we think about increasing Fed funds rate, so you're right that through 2021, the Fed funds rate or the base rate of loaning and borrowing money was quite low, which meant that returns on mortgages or the interest on mortgages was only, let's say 3%, 4%, which meant that if you were an investor at spare money, you might not want to give your money to a homeowner, which gives you 3%, 4% return because you're giving them the loan. And you might want to want to look at startups that could give you maybe 5%, 6%. And so the barrier was a lot lower for startups in terms of return on capital invested. Nowadays, the interest rate is up at 5%, 6%, depending on the country you're in. The home mortgages are at that rate. So interest rates are like four-ish, but the home mortgages are at 5%, 6%. So now a startup has to compete with the stability of the housing market, returning 6%, 7%. A startup has to return 9%, 10%. And what we're seeing is a real pullback of dollars because the math just doesn't work out as easily anymore. And first I'll talk about what I think is happening to deep tech, but then I'll get to, I guess, the surprising thing is that investors are not investing more in deep tech. First, what's happening in deep tech? If interest rates are going up, cost of capital goes up, capital is more valuable, liquidity is more valuable. It's harder to get your hands on that liquidity. If you're a deep tech company that's got to build a brand new shiny reactor. You got to build new equipment, machines, a brand new car that you're inventing, a plane, a robot, or a spaceship. These things cost 20, 30, 40, a hundred million dollars. These rounds are getting done in 2021. And these companies will not be able to raise with the high cost of capital in today's market, because it's very hard to convince a hundred million dollar liquidity holder to give you a hundred million dollars when they can make $5 million tomorrow by just putting it in the government bonds. So we're seeing a pullback of big chunks of money going to big hardware, hard deep tech problems. And the funny thing about this is not how that's going to hurt the deep tech community. But the funny thing is that investors seem to believe that a flight to quality means a flight to software or things that are easier in terms of capital expenditure and they're more capital efficient. If you throw $10 million into a more capital efficient business, it still needs to net you 10% return, the only things that are going to return 10% year on year compounded for five, seven, 10 years are deep tech companies. So Even the investors in the world that are playing this game today and investing very heavily in 2024 now, they're going to be investing in companies that cannot meet the return that you could get in the housing market or you can get by investing in treasury bills and bonds. So it's all a bit backwards right now. Things have inverted. Things are a bit strange. But I do think that by the end of 2024, things will reorient themselves. But as a business owner in deep tech, the big thing we have to do is we need to get ourselves off of the dependence on that capital. Because that capital is not coming back for another two to three, four or five years. You won't see a billion dollar investment in a huge facility like Ginkgo Bioworks has to do a foundry approach to generate data, generate learning, generate machine learning. You don't have a billion dollars anymore to spend on stuff like that. So those business models should not even be considered by deep tech founders at this point.

Jon - 00:33:56: Very fascinating. And there's a bunch of different places I want to kind of go. But the first thing that comes to mind, and life sciences, deep tech, all of this, the capital intensity is real. And the capital markets and investors that I speak to is a recurring theme where everyone's scared of the capital intensity. But I think as these rates have gone up, we're seeing how software is maybe not as defensible as investors once thought. And there's a defensibility to capital intensity that people in the past decade have a lack of appreciation of.

Grant - 00:34:32: Think about this. Those software companies that are losing that defensibility, it's not just that the investors are noticing, the public markets have started to notice. We've seen enough companies go public that don't have true defensibility on banking, well, I don't have any companies, right? And you don't need me to tell you which ones because it's in the common vernacular that these companies are not defensible. They're a dime a dozen. And so if the public thinks that, then the multiples in an IPO are going to be lower. And that doesn't seem to have affected the way that investors think about defensible businesses and software. What I think you're catching where I would love to go with this conversation, which I think is a really great place for it, but we prefer, is this idea of a deep tech should embrace its capital dependency, but you should find the application areas where the capital invested leads to the highest efficiency of multiple return on the business that you're trying to build. I have this thesis about industrial bio that the companies that can utilize the lowest cost of fermentation and have the lowest fermentation and reactor risk profile from a capital intensity perspective are the successful ones. If you need a tank to grow every kilogram of your product, you're in trouble. If you need a tank to grow a kilogram of a very special product that's used for 10 years because it lasts that long, you're in a great place. Because the capital intensity allows you to build a defensible business. But the thing you get from that capital that you invest, that one reactor that costs 10 million, great. If that $10 million reactor can fund a multi-billion dollar global company, that's the industrial bio company to invest in. And too infrequently do we talk about that. Capital intensity is great. It's great. But capital efficiency with capital intensity brings capital markup and multiples that we want. So we should be embracing capital needs. And the only place I see that really is climate tech.

Outro - 00:36:33: That's all for this episode of the Biotech Startups Podcast. We hope you enjoyed our discussion with Grant Aarons. If you enjoyed this episode, please subscribe, leave us a review and share it with your friends. Thanks for listening. And we look forward to having you join us again for part two of our conversation with Grant. The Biotech Startups Podcast is produced by Excedr. Don't want to miss an episode? Search for The Biotech Startups Podcast wherever you get your podcasts and click subscribe. Excedr provides research labs with equipment leases on founder-friendly terms to support paths to exceptional outcomes. To learn more, visit our website www.excedr.com. On behalf of the team here at Excedr, thanks for listening. The Biotech Startups Podcast provides general insights into the life science sector through the experiences of its guests. The use of information on this podcast or materials linked from the podcast is at the user's own risk. The views expressed by the participants are their own and are not the views of Excedr or sponsors. No reference to any product, service or company in the podcast is an endorsement by Excedr or its guests.