SynBioBeta 2026 A 10 Year Overnight Success Building Twist Bioscience One Base at a Time

Thank you.

Yeah, I mean I'm a DNA chemist, right? And so once you have a hammer, everything looks like a nail. But definitely buying DNA at the time used to cost a dollar a base and then the vision that we have for Twist was to lower that price. And when we started Twist, we had a vision that nine cents per base for a clonal gene would be a great place to be. So me and the two Bills, we went out there and we were like we need to raise money.

This is Bill Bet and Bill Peck. The two bills. And we went out there and we raised $600,000 for the first run. And I think we have a picture behind us from April 16, 2013, right? We got the money April 15. We went to IKEA. We got three desks and we got in a corner and that was the best day of our lives.

It was a coincidence that it was indeed tax day.

I think so. Yeah. Because you had the first SynBioBeta and then I was like I need to talk to this guy and that was you.

No, because it's key, right? So you have this big idea and you're like we're going to raise a lot of money. We're going to build technology. Will anybody bite? And so calling people to get that discovery of validating am I crazy or am I really seeing something big there? Because our view was can we miniaturize the DNA chemistry? Can you use inkjet printing to print some droplet on a silicon chip which was novel at the time. The idea was if you print 10 plates, it's going to be a lot less expensive because all that chemistry is super expensive. And to this day that's the technology we're using.

Yeah. So very quickly we're able to print DNA, we're able to make DNA. We're like okay let's jump off the cliff. Let's burn the boat. Let's go commercial. If you're a startup, going commercial is key. Everybody wants it, but it's a treadmill. Once you get on, you can't get off, right? You have to keep pedaling. So we're thinking, what is the best way to launch? Obviously, had to be at SynBioBeta. And actually, when I reviewed the picture yesterday, it turns out I'm wearing the same sweater. It was not 10 years ago, it was 11 years ago.

Well, after the launch we got our first orders. That was our alpha access. We couldn't make the DNA and frankly we could not track the DNA. We lost it. We made a thousand genes and we didn't know which one was which customer. So I had to go to the board and say we got to shut down, we had to retool because we built the printing machine, but we didn't build the software infrastructure around it. And so it actually took us six months and then we relaunched with the full launch.

You know, we were using Google Sheets and we didn't have a tracking system that was sophisticated enough. But since then now we have and we've been able to ship more and more genes. I think last year we shipped almost a million genes. And it's a million genes in a million vectors in a million tubes with a million barcodes to a million addresses with a million invoices. And you would think the easy part is the DNA synthesis. You would think the hard part is the DNA synthesis. The hard part is sending the right invoice. We just reported our earnings yesterday. We shipped 300,000 genes last quarter. We used more than 50,000 in-house. So we're on a run rate already of 1.4 million genes a year and growing 20% year-over-year.

Okay. But now we also make protein. We also characterize for customers and so we also used more than 50,000 genes internally. So we made them. It's just that we ended up shipping data instead of shipping product. And shipping the invoice is hard. And what's really hard too is the speed. I don't know if you remember but at SynBioBeta when we launched actually we were slow. And I got some charts where it used to be like 20 days to make a clonal gene and now we make a clonal gene in five to seven days, so an average of six days. We make a clonal fragment in three days. Again, at scale, anybody can make a gene in five days. But making a million, that's the hard part.

Man, we have so much confidential information. So I have to be very careful. The product lineup that we have is very broad. Maybe I can share two that I know are public. On the cancer diagnostic side, Guardant Health is a customer where you take a blood draw. It's not synovial, right? It's for real. A lot of blood, but they can detect cancer when it's tiny like this. Sometimes it's super hard to see even on a CT scan instead of finding cancer when you can feel a lump. So that's a customer we're very proud of where they do early stage cancer diagnostics. And then the other end, we're working with a number of AI companies. There are hundreds and thousands of customers. X A is one of them. They're going to speak on our behalf in May. So I know I can mention their name.

X A. They did a billion dollar series.

That's right. But if you want names, those are names, but it's really thousands of people we ship to every day.

Yeah, I mean when I started I was frankly a little bit naive through my discovery. I thought everybody wants the same thing. They want DNA so that's easy. And actually when we launched we only had a few flavors of DNA. And it turns out that everybody wants something different. So over the years, this is the product roadmap we are in 2021. By now, we've added more and more product. If you ask five people how they do drug discovery, you get six opinions. So some want fragments, some want genes, some want preps, some want IGGs, some want data. And they want different modalities. And they want it in plates, they want in tubes, they want 2D barcodes, sometimes they want it lyophilized or normalized. And so what we realized quickly was that we had to massively customize everything because there were no two orders the same. And so that's what we do: we leverage software and industrialization to be able to meet you where you are for your science. No matter the way you want to do it, we'll be there. We'll never tell you what to do. You tell us what to do and then we'll find a way to fold ourselves into a pretzel to do it. And now, even though we are the DNA company, we are going into protein because that's a lot of the demand is protein.

We'll do whatever you want. But yeah, there are a lot of customers now. They come to us and they say 'We don't have a wet lab. We are a dry lab company. We'll do the learning, we'll do the designing, but we need someone to do the building and the testing.' So part of what we had to do is not only... and they say 'By the way, we don't want DNA, we want protein because we need antibodies, we need VH, we need bispecific, we need scFv, we need FAB, many different modalities.' So we've leaned into that. I think the stats speak for themselves. Last year we made more than 200,000 IGGs in-house, which is super hot scale for a DNA company being the company that makes the most IGG I think in the world. And those are one IGG per tube, expressed either mammalian or cell-free, and then it's purified, polished, characterized. We did more than 130,000 characterizations of antibodies, so that's functional testing, epitope, all the developability assays. We had to learn how to do that but do it at scale, super fast, super low cost, super high quality. It's kind of exciting. And actually, if you want, I've brought in some data.

We had one customer that came to us and they said we want 10,000 antibodies. We want all the functionality. We want specific binding. We want non-specific binding. We want thermal stability. And by the way, we want it in 20 days. And so yeah, actually it's no problem because it's all automated. And so this is real data on 10,000 antibodies and now we do it routinely. We're happy to do one antibody, but in 20 days we're happy to do 100 in 20 days, a thousand in 20 days, or 10,000 in 20 days. You can't break us. You'll run out of money before you break us.

Yeah, I mean we're super excited. Again, there's a lot of excitement in AI. AI, our view, is that there's a place for in vivo, in vitro, but AI is going to be the first path of drug discovery, the first line. And so we have lots of customers. They come in and they have their own algorithm, they want their own thousands of IGGs. That's great. But there's also a lot of groups that don't necessarily know where to start, and the activation energy is hard. I think Amazon has a great vision: let's build a marketplace where they have a lot of models available. You can start just by buying a few tokens, upload your target, do your design. You leverage the learning that they've done to do your design, but then you still have to do the building and the testing. So you just press a button, buy from us, and we'll send data back in just a few weeks to the Amazon owned marketplace. You don't have to do anything. You just have to do the thinking. We can take care of deploying the capex, maintaining the machine, caring for the people. And some people are on vacation, or it's the weekend, or they're depressed. So we take care of all of that. You don't have the overhang of having to run a wet lab. We do it at scale for you. And so I think that's where the Amazon partnership is fantastic. It really enables people to lower the activation energy to use AI for drug discovery. And there are two big ways: one way is to do pooled discovery, or there are ways to do array discovery. We're happy to support both. Our goal is to lower the activation energy, lower the barrier for anybody to get going in the area of drug discovery. But if you want to do in vivo, I don't know if people know but Twist owns alpacas, we have an alpaca farm. So we'll do alpaca discovery if you want. We have rabbits and mice. So we'll do everything. We see a lot of excitement in bispecific. So again, we don't want to tell people how to do science. If they want to do AI, we'll have the best tools. If they want to do in vivo, in vitro, we'll have the best tools.

No, it's on the east coast.

That's right.

It's fantastic, right? Because it brings critical mass to the ecosystem. It brings capital. It reduces friction. So yeah, I think it makes sense. The bioeconomy is so critical to the economy, but it's so critical to the human condition and improving the well-being of people, improving sustainability even in a dirty world. So we are all for it. And that's one of the things that SynBioBeta has always been really good at: nurturing, enabling, catalyzing the ecosystem.

That's right.

Yes, thank you. I had a breakfast this morning, so I told people that once you're a public company, doing the IPO is like peeing your pants. First it feels great and then you realize what you've done. You're on that quarterly treadmill of having to announce your earnings. So we had $111 million rounding revenue for the quarter, and we grew 20%. Revenue is good but growth is very important. Our gross margin was more than 52%. So we're not gouging as a company. We don't make 90% margin. 52% is a good deal for us. It's a good deal for our customers. We always want to have the highest quality fastest DNA and protein but at a great price. And we're going to be profitable in September. After 10 or 11 years, finally we're going to be profitable. Very excited about that. But the key is growth. It's our 13th quarter of consecutive growth. Over the last three years we've grown 24% a year. Last five years we've grown more than 35% a year. And growing 20% on $111 million is really hard. And I heard you earlier say that there's one person responsible for Twist. If you don't mind me correcting, it's a team. If it's good at Twist, it's the team. If it's bad, it's me. I'm only in charge of the bad stuff. It's really the team. We've hired an amazing team and they're really the ones that did it. And we are here to serve our customers.

Yeah, you are Batman and we are Robin. We're here to help you. So, whatever you need, whichever DNA, protein, data, again, we'll fold ourselves in a pretzel to make you successful.

Thank you.