All right. Good afternoon, everybody. I'm Luke Sergott. I cover life science tools and diagnostics for Barclays. With me, I have Emily Leproust, CEO of Twist, and Adam Laponis, CFO. Long time. You know, we've been doing this, so again, appreciate for making it down in Miami and March, as we were saying, is not too bad. I guess from the jump, let's talk about the resegmentation into the SynBio plus the protein solutions, and how you guys are an AI winner. This is kind of how it's been a big theme across the space, why, you know. Because there's not a Claude plugin for you guys. Like, how are you guys the AI winner and walk through the kind of the resegmentation, how that fits in with that.
Yeah. No, thanks for having us. Thanks for the question. It's definitely one area where we have a lot of momentum. The DNA synthesis and protein solution grew 27% in Q1 year-over-year. How traditional drug discovery is done is in vivo, in vitro. People inoculate the mouse with the target, and then you extract the DNA. You screen for the novel antibodies, or you take a large library of more than 10 billion antibodies, and then you pan them through phage display. In both cases, you get 10-100 antibodies that you have to characterize. The outcome of what we used to sell to customers when they gave us a target was up to 100 antibodies that were characterized.
We are also have serving customers that are doing their own drug discovery in-house by just selling them DNA, and/or protein. We still do that. Last year, our therapeutic drug discovery was about $111 million, growing more than 25%. We cannot achieve scale in drug discovery because it's a very fragmented market. Few companies get more than $50 million. That's the traditional before AI. When AI came in, what people did was use compute to come up with thousands of sequences of antibodies. Instead of using in vivo, in vitro, the computer spits out thousands of sequences, but then they need the data, they need the characterization.
What is the affinity, the functionality, the epitope binding, the developability, thermal stability for all those thousands of sequences. They came to us because we could make the DNA, we could make the protein, we could characterize, and what they really wanted was speed and scale. You know, we think we are the best in the business where if you give us thousands of sequences, we'll be able to give you data in 15 days. It's data for the full menu. What we are seeing is customer build their model either in one or several shots, so again, thousands of sequences.
Once they have the model, they go into the drug discovery process where they declare a target and through their model come out with a bunch of sequences. We do the building and the testing, give them data. The benefit of using AI versus in vivo and in vitro is in vivo and in vitro is 6 weeks to get to a hit. With AI, it's 2 weeks. You just can do 3 rounds of discovery and engineering while you could do only 1 round with in vivo and in vitro. It's been a great momentum for us, and it's contributed to our growth.
When a pharma company or biotech, like you just have like, we'll get the Invenra collaboration. You know, in the past it was you'd layer out and you get these press releases, you just partnered with XYZ biotech and, you know, we're gonna provide the antibody optimization platform with them. How has that moved further downstream or upstream, I guess it is, for the SynBio side? Now that you're doing this, you know, as one whole business where you were doing the DNA, you know, the synthesis piece and now you're doing like the protein optimization or the antibody optimization together, you know, like how was like what's the next step here for you guys as you're thinking about this workflow?
Yeah. Our next step for us is we want to have a full menu, right? Again, when we compete with people in the drug discovery space, and there's a lot of companies, and they all have a niche. There's a company that they only do mouse, and there's another that they only do humanized mouse and another one, they do only that kind of phage display. Someone else does yeast display, someone else does RNA. Everybody has their own little niche. What we want to do is provide the full menu and meet the customers where they are. We're very happy to sell data, but there are still customers, they don't want data. They want to buy DNA from us, and they want to do the work in.
in their lab. We are very happy with that. At the same time, for the new AI drug discovery companies that don't even have a wet lab, we also want to be their partner. Our approach is not to tell people how to discover drugs. Our approach is to again meet them where they are, provide whatever science they want to do. We are going to have the tools for them and enable them to go faster with the highest quality and, you know, the best price so that their budget can go further. You know, at some point you want to talk about Invenra, but.
Yeah.
Invenra, I don't know if it's the right time.
Sure.
It fits in the strategy.
In that menu, one area where we were not good or actually I should say we were equally bad to everybody else was bispecific.
Right.
Bispecifics are notoriously really hard to make. To make an antibody, you need two vectors, right? The two plasmids put together. For bispecific, it's four. If you don't have the right ratios for those four coming together, when you express, you get something that's not clean, and you have to purify to get the one bispecific that you want. That makes it really hard to process in high throughput. Invenra, they've come up with a system, a platform where it's almost auto purification where it doesn't matter what the ratio is, it comes out clean. Therefore now we have what we think is the only platform in high throughput to express and purify bispecific and therefore enable the discovery of bispecific molecule in high throughput.
When you marry that with AI, not only it can be used by traditional companies that want bispecific, but for people that will want to build a bispecific model through AI, which is very difficult to do now, it would be possible. It fits that strategy of just adding more all the tools.
Yeah.
That someone may need such that we're the one-stop shop.
How was, like from a, the throughput on the bispecific, how was that being done? Was it that was being done by the pharma company themselves? They have to build out that group?
Bispecific, the concept of bispecific is simple. In practice there is more than 100 different flavors of bispecific, but they all have the same issues around expressing them at high purity.
Which they don't. Any flavor out there you have to express, and then there's a heavy step of purifications. At Twist, we are able to make all the flavors, but we don't have an advantage to make them pure. But with Invenra we do. The other thing with the Invenra platform that's very smart is the engineered linker that they have is very small, is very human-like, and is in the clinic. You don't take immunogenicity risk.
With the Invenra platform. Again, if our customers say, "No, we want our own bispecific," we're happy to do that.
Yeah.
It's just that, like anybody else, we won't really have a high throughput advantage for non-B-Body approaches.
Yeah. On the protein side, you guys talked about being more choosy in what projects you're taking. As you're thinking about this as a more holistic across the SynBio and the protein synthesis piece or protein solutions, how much of that is because of the capacity? This is kind of what I was talking about before, where you take on almost any project from a biotech, and now like some of these projects are starting to scale and you're bumping up into like ability to deliver, which goes against the DNA of your company as like you want the fastest turnaround time. You know, the balance there of like how you choose these projects like profitability, things like that about as you mature into this market.
Yeah. Our approach, I would say, our north star is to always tell customer back up the truck, right? Don't worry about capacity. It's our prime. We've got you. And then the second is that, you know, we don't want, frankly, we don't want to subsidize our customer's R&D.
Like we want to be paid a fair value. It's a lot easier to do that now that we're established as a high quality and fast and a great price. It's much easier now than it used to be five or six years ago when you know we were known for being a DNA synthesis company.
We'll tell customer, "Oh, give us a target, we'll give you a drug." It was a harder sell then. Now I think, we're recognized as a very high quality, fast providers of products, DNA and protein, as well as services where end-to-end, you give us a target, we give you a drug. Such that now our job is to make sure that we stay ahead of the demand with capacity.
We are part of the process where we have ample demand. For instance, on the DNA side, I think we've said that we have capacity for 3 million genes a year. Last quarter we shipped 271,000 genes, plus we use 50,000 genes in-house.
To make proteins and characterize and sell data. You can see that we're still far from capacity. There are other product flavors where we're probably closer to capacity. It's ramping very fast. Data characterization grew more than 200% last year, and so there we are adding capacity ahead of the demand.
Okay.
Yeah, our goal is we never want to say no if the price is right.
Yeah. I mean, that's commercially viable.
That's the commercial viability right there.
Speaking of that, let's shift gears to the NGS side. I guess the timing issues from the commercial customer switching from translational to the clinical side, like that seems to be behind us. Talk about how you guys are thinking about that ramp from a test perspective, but also just kind of an overall update on the NGS side from the liquid biopsy piece of, you know, where you guys are playing, like where are you seeing a lot of the momentum in the business coming from?
You want to start?
Yeah, absolutely. Great to be here.
Yeah, yeah.
No, I mean, we're really excited what we're seeing in NGS. I mean, a lot of the end markets continue to show significant growth to be liquid biopsy, MRD, and then many of the other diagnostics. We also see longer-term opportunities in new markets, ag being one of those markets that we know is, you know, ripe for NGS opportunities, and we're just getting started in that. When we look closer into 2026, what we said is in Q1, excluding that one customer, we were about 18% growth. Overall the business, as that customer ramps back in, we see a path to being at 20% growth in our NGS business by Q4. I'm happy to say that, yes, we're seeing the customer order, things are going great, and the relationship is quite strong.
We're feeling very good about where things are going.
Okay. As you think about, you guys just came out with the TrueAmp, right, for the library prep. This is I guess more of a existential question where one of the bear arguments against you guys were, one, SynBio market's not as big as we thought it was, and then two, it's going to be on the NGS piece as you provide enrichment tools for panels and the market's moving towards genomes or panels to exomes, right? Now the market's moving to genomes, like you have a terminal value problem as that market shrinks. I feel like the TrueAmp is there to get into the library prep for whole genome. Talk about where you're, you know. Is that right? Right.
Is there a risk to the NGS business as you go from whole exome to whole genome?
Yeah. It reminds me of AGBT in 2009 when someone stood up and said I won't say who, but the panels were a flash in the pan. We are here, you know, 17 years later debating whether there's life for panel. Absolutely there is life and we're very bullish about the growth. It is true that in some applications, for instance, rare disease.
That, you know, rare disease in the U.S. is gonna go from exome to genome as the price goes down. For rare disease outside of the U.S., where the reimbursement is nowhere near what's available in the U.S., actually people will stop doing exome. Even in rare disease, ex-U.S., there's great growth. For cancer, I would argue that the lower price of whole genome is really good for our business because it's enabling more tumor-informed MRD. 'Cause to do tumor-informed, you have to have a whole genome sequencing upfront. We can do exome, but it's probably more powerful to do genome.
My view is the same as it was in 2009, which is as you lower the cost of sequencing for whole genome, you're going to enable more applications of panels. We are seeing that now in AgBio, where AgBio, they're currently using microarray. It's a market that's extremely price sensitive. Now that the price of the whole genome sequencing is there, Twist plus sequencing is going to be cheaper than running a microarray for all the AgBio applications. In general, I disagree with the premise that the whole genome sequencing is going to be right for us. At the same time, what we sell is workflows.
What we realize is that the performance of the enzyme is somewhat limiting the use case of what can be done. That's why a couple of years ago, we engineered a best-in-class ligase to this day, which lowers the limit of detection for rare mutants, so that ligase is great for increasing sensitivity of the assay. We next put our focus on the polymerase, which is what we just launched with TrueAmp.
What we find is that people, they like the PCR-free protocol because it's convenient and then there's no bias.
If you could do a PCR, it's just easier because you have more material to work with. With the TrueAmp, what we did is we provided the same performance as a PCR-free, but with the convenience of a PCR. We did that by engineering a polymerase that has extremely low bias at high or low GC, and a polymerase that was able to go through repeat regions without stalling or skipping. We think it's the best of both worlds. Again, PCR-free-like performance, but with a PCR convenience.
It's the kind of things that we're showing that Twist is not only great at making DNA, but also are great at engineering enzymes that are key to a particular workflow. For NGS application, we now have what we think a terrific library prep that's going to enable us to go into new markets that we were not in, such as, for instance, academia.
Yeah.
For NGS.
Okay. With the capturing the workflow and becoming that solutions provider, is that the genesis behind MRD Express as well?
Yeah. For MRD Express, the genesis was, so actually five years ago at AGBT.
Yeah, it was a long time ago.
We launched MRD. We saw that tumor-informed MRD was going to be the winner. Way back then, there was a lot of bear thesis against that as well.
Now it's clear that a tumor-informed is the way to go. What we are seeing is that the medical need is going to be for high sensitivity MRD. When you say, "No, you don't have cancer," well, it's better that you really don't have cancer.
Yeah.
If there is going to be a recurrence, you want to find it as early as possible. High sensitivity is gonna be key. That's our MRD. You get 100, 500 probes for the price of 16, or you can get thousands of probes. But what we also heard is, "Yeah, it's great to get 10,000 probes in 5 days.
I mean, it's amazing, but you know what would be better? If you could do it in one day. That was the genesis of MRD Express, is actually a customer request saying, "You know, those five days, actually, it can limit the window.
Yeah.
That was the customer demand, and we responded, and now we have MRD Express. Sometimes we are seeding the market with technology. That's what happened with MRD.
In the case of MRD Express, we also listen to what customers need and we rise to the challenge.
On that tumor-informed versus tumor-naive, but like, as you think about where you guys are playing within your liquid biopsy customers, in general, there are a few that still have not adopted from, you know, your technology. I guess, like, when you go out to those big players that still haven't adopted, like, what's their pushback? What's the reasoning why they won't come to you guys? 'Cause it seems like you're the only ones with this one-day turnaround and accuracy and cost and everything else.
It's like you're listening to my sales call review every Friday. It's like, we're doing well, but why aren't we doing better? You know, why don't we have 100% of the market? Yeah, there's inertia, right? Victory is certain, timing still to be determined. What we know is when we get into a pilot, head-to-head, we win the panels, we win on the workflow, we win on the enzymes, we win on the supply chain, we win on IVDR. I think right now nobody is getting fired for choosing Twist. We are seeing the sentiment change.
There were customers that were saying, "I picked someone else before you were in business, and I won't switch." Now we are seeing more and more of those people calling us, saying that they need to switch because the supply chain confidence that they are getting from our combination is not where it needs to be at the scale, the volume they are now. We are playing to win, we're playing to win it all, and I think it's a question of time.
Gotcha. In the last 55 seconds, Adam Laponis, let's talk about some margins. You know, the gross margin trend here towards 55%+, it seems like that's you guys been building good momentum there. You know, targeting breakeven, even breakeven at the 4Q. You know, talk about where you think. I know you're not gonna put numbers around where you think.
Yeah.
Like margins are gonna be, but when you think about the incremental margin opportunity built within the business, where it is now and where you think it could go, like, walk us through that?
If you look at the journey over the last three years, we've seen our margin growth over 20 points of margin growth. Obviously, some of that is due to the continuous process improvements, but the vast majority of that is the fact that for every dollar of revenue growth, whether it be on the DSPS, the DNA synthesis and protein solution side or be on the NGS side, we're targeting about 75%-80% of that dropping through to the gross margin line, so the revenue growth dropping through. We're seeing that pretty consistently as we scale up any of our areas of the business. I think that trend will continue. What's gonna accelerate or decelerate the pace of the margin expansion is how much incremental effort we put on driving out cost versus introducing new products.
What we've said is, now that we're above the 50% gross margin line, there's no going backwards ever. We're gonna continue to see progress as we move forward because we know we can drive that revenue, and we know we can do it, but we wanna make sure we're also investing in the capabilities. The pace at which we grow it is to be determined.
Got it. When you're thinking about the, from a guidance perspective, you guys typically would, you know, guide conservatively, and you tend to beat them on the numbers, you know, from a quarter or for a year. You know, at what point do you start leveling out on that margin piece? 'Cause again, you gotta take on and do it on the investments. Does the change in kind of the segmentation and the ramp of MRD, the ramp of all the NGS stuff, set you up for, like, significant upside, much more so than you ever saw in the past? Like, typically, you beat by like, you know, a few percentage points here and there, but those are longer term contracts or longer term projects.
Like, is the business starting to change now where you can get a lot more juice, I guess, on the quarter than what we've seen?
I guess you'll have to wait and see.
That's all I needed to hear. That's amazing.
See you in May.
Yeah, on the Investor Day. Any sneak peek there or.
We look forward to it in May.
Okay. All right. I appreciate it. Thanks again.
Thank you so much.
Yeah, this has been really good.
Thanks, Luke.