AbCellera Biologics Inc. (ABCL) Earnings Call Transcript & Summary

All right. Welcome, everyone, to Credit Suisse's 30th Annual Healthcare Conference. I'm Tiago Fauth. I'm a biotech analyst here at Credit Suisse, and we're joined today by AbCellera. We have Carl Hansen, CEO, for a fireside chat. Happy to ask any questions on your behalf and try to work those in, in our fireside chat. The e-mail is T-I-A-G-O dot F-A-U-T-H @ credit-suisse. Happy to try to address some those.

But Carl, as usual, we generally like to start with a brief overview, and you just reported earnings fairly recently with some fairly impressive results from an operations perspective. Can you just kind of briefly recap the AbCellera story and the progress you've made since you've gone public almost a year ago now, right? That's -- it feels like it's only yesterday so...

Yes. I think we're coming up on exactly a year. So first, Tiago, thanks for having me. It's great to be here. I'll try to keep it brief. AbCellera is a technology company. We were founded back in 2012. So we're -- we just had our ninth birthday. The company was founded with a bit of a different idea of how to build a sustainable biotech company in the drug development space. So first and foremost, our business model and our business strategy has emphasized capability building, investments in technology that covers the -- a space that sits between an idea and right before but not including drug development. So we are essentially trying to disaggregate from a vertically integrated biopharma, the capabilities that allow you to change or to transform fundamental insights into biology into new drugs that can be developed in the clinic. That entails building a modern platform or tech stack that supports therapeutic antibody discovery across a broad range of indications and modalities. We have been assembling that now for 9 years, and we believe we have the industry's best capabilities for the discovery and the early stage development of therapeutic antibodies. The last piece of this tech stack is the development of translational science, CMC and GMP manufacturing capabilities. And that is on track to be completed in 2024. At which point, we will cover the entire value chain right from idea. So an e-mail from a client right up to an IND filing, including the composition of matter, the drug substance and the data that supports the biological part of an IND filing. The other thing that's different about AbCellera is the business model. Most biotechs get forced early on or decide early on that they are going to focus on internal portfolio. When you do that, as an early stage company, your fate rests on the output of a Phase II trial or a Phase III trial. And you have the potential to hit it very big, but of course, you're taking on a big binary risk. So this is an industry where success rates are typically around 5%, and you've got a 10-year path with about $300 million to $500 million of investment to see if you actually have a product. Our business model is different. Instead, we provide access to the capabilities that other companies need to get to that point of clinical testing. We work with the biggest companies, solving the really tough problems in the industry. We also work with the early-stage companies, where access to the full technology stack can save them the time and effort and capital that would be required to boot up their efforts. And that often is saving them 3 years and tens of millions of dollars. In exchange for our work, we then keep a stake in the long-term success of those molecules, so typically through milestones and royalties. So deal structures include some payments for upfront tech access, some payments for the research work, but the vast majority is connected to the success of those molecules through clinical development and ultimately commercial development. The long-term strategy is to build up a diversified portfolio of those stakes. So over the next years, we anticipate having that portfolio comprise hundreds of therapeutic programs. And then, of course, some of those will fail. But if we pick the right partners, if we invest in technology, if we help our partners to have a competitive advantage in getting to the clinic, we believe we can exceed the traditional probability of success and build a very long-term and high-return company without taking on the risk that is normally associated with biotech. So that's quite an unusual model. It's one that was not, I think, widely embraced early on in the company, but definitely something that people are now getting excited about. And fundamentally, our business is about trying to use partnerships and investments in technology to move the needle in drug development to the benefit of patients, of partners and society in general and our shareholders, of course. So that's AbCellera in a nutshell, and I'm happy to dig into any parts of those, Tiago.

Yes. I know. We have a lot of ground to cover, so I'll try to be direct here. But honestly, I think it would be helpful to discuss some of the more frequent pushbacks and some of the more heated debates that I have with investors, right? So -- and I think, at least in your intro, you've kind of outlined pretty clearly that on a risk spectrum, you're definitely not a single-product biotech. You're also not necessarily either a medtech company with predictable revenue base of installed boxes or you're not a CRO, where you're just getting a fee for service. But specifically on the CRO debate and just drug-discovery demand overall, we got a lot of questions, right? So again, what is so proprietary about either certain aspects of the technology stack or the integration of the technology stack relative to what someone could get at Charles River -- or I shouldn't have mentioned specifically, but like a more typical CRO kind of a fee for service. What is so unique about your capabilities that would not be as easily replicable by a competitor? That's, by far, the most frequent question, and I would love to hear any thoughts on that.

Yes. I've got several thoughts there. That question is often posed as, "AbCellera, what is your secret sauce? Or what is the key piece of technology that differentiates you from others?" That's a question that I think misses one of the bigger advantages of AbCellera. So there are, within this workflow, probably 5 key steps. You need to generate immune diversity. You source the immune diversity. You search it. You find the right antibodies. You then analyze them and then engineer them to hand off a development-ready lead. So that's 5 steps. We have proprietary technologies, the types of technologies that are patent-protected that go up on a slide, that stand toe to toe with or are best in world at every one of these steps. And we could go through these. And I think probably in the follow-up question, we'll dig into maybe a couple. But the -- so we could bring forward one of those. That's like the ace in the hole. But the real important thing is that unless you put all these things together, you have only solved 1 of the steps on a process that is highly technologically and know-how intensive. And only once you put all things together and integrate them well do you have the winning hand. So it's like here's your ace, but you need to have the king, the queen, the jack, the 10 to have a full hand that wins, and you also have to put them all on the same suit, which is integration. So one of the key differentiators for AbCellera is we are the only company that has put all of those together and that has invested in bringing those technologies into a workflow that is faster, that goes deeper, that can solve more problems, more versatile and that is accelerating in terms of its ability to solve those problems. And I know you're probably going to dig in. The first technology there was a microfluidic single-cell screening technology. That's how we got into the industry. That is at the core of the platform, and people often focus on that. It is critical. It allows for at least 10x deeper screening than anything else that even exists today and probably 1,000x deeper screening than the conventional technologies like hybridoma that were -- that have been used now since the 1980s. But that advantage would not allow us to deliver on the goal of actually handing off drug candidates were it not for all of the investments we've made upstream and downstream. And while we are still, I think, by far, best in the world at that step, we have spent 80% or 90% of our effort on putting everything together upstream and downstream of that, including humanized technologies at the front end; repertoire sequencing; single-cell genomics; high-throughput, industrialized protein biochemistry and analytics; and then the data science element, which I'd love to talk to that actually knits all of this together and helps you to move more quickly, get economies of scale and ultimately to skip steps by learning in a better way how to anticipate and see around corners of drug discovery.

No, I think that makes a lot of sense. And to build off of that, again, because we do get asked, okay, so what if I get this transgenic mouse model and I do get this piece of hardware and if I do this, like how -- why is that not AbCellera, right, so -- which is a really simplified way of thinking about it. So can you talk more about the time that took you guys to actually integrate all those technologies and the investment you've made so far to make sure that you have those capabilities? And how easy would it be to actually replicate that at scale given that you guys have been, again, around for some years, but you've accumulated a huge portfolio of programs under contract so far, right? So the scale is something that I want you to address.

Yes. So the first proposition is if we put up the flagship technologies that we often talk about, so a modern implementation of transgenic animals, high throughput microfluidic single-cell screening, repertoire sequencing, single-cell genomics, high-throughput protein expression and characterization, protein engineering technologies, including a clinically validated and very flexible bispecific platform and then the data science investments that bring this together, if we just took all those things -- the first answer to the question would be, not all of those are even available to acquire. And the time and expense that it would take to actually get those technologies is a major hurdle. It's one that we've been putting together now for a decade. But even if we were to hand that over to someone and say, "Here's all the technologies. Here's the IP. Here's the game book, and go ahead and rebuild this." You still have years, probably 5, 6, 7, 8 years to build up an engine like what AbCellera has accomplished. So we have now a workforce of about 375 people. We have built up the know-how and the workflows around that. We have the data sets. It's the instrumentation, it's the facilities, it's the protocols that put all that together. All of that is something that needs to be deliberately built with a long-term view to have established a technology workflow that has today best-in-class capabilities and is on a technology curve that will continue to accelerate. And there has not been a group in big pharma or in small companies that has had that vision to really put those technologies together. So if you went on that path today, just dealing with the complexity and the hiring of building that would be a formidable barrier and one that would be very hard to make a business case for given where AbCellera is today. We believe we are far and away ahead of the pack in building that up. Of course, there are some pieces of that also that you could not replace in a way that would be comparable. And I mentioned, for instance, the single-cell screening platform. It is a proprietary Abcellera platform. There are companies trying to follow that. Perhaps you can get an instrument that does something that is in a format similar to that. But it operates in order of magnitude lower in throughput, and then you rely on your customers to build everything around it. And for us, that defeats the entire purpose of the technology. So the purpose of this is that drug developers shouldn't need to build everything that is the basis for their work. They should be able to access best-in-class capabilities from a firm that specializes in that. And by doing this type of work day in, day out, making that our business and now working on coming up on 100 programs and 150 or so under contract, we are on a learning curve that allows us to become experts in this and to refine and direct that technology development, so that every client that comes in gets the benefit of years of investment and years of learning. And that to me is sort of the core insight in the business model and one that I think is a path to accelerating differentiation relative to the field.

No, that's fair. And I guess somewhat related to that, there's also a TAM discussion or even a demand discussion, right, which is interesting because there seems to be a skepticism that there will be a sufficient demand for multiple players, given internal R&D efforts and more competition in certain aspects of the discovery process overall. Despite that, you guys continue to sign contracts with validated large biopharmaceutical partners and high-quality early stage biotech company. So how do you square off those 2 competing thoughts, the perceived lack of demand or volume that would require a company to exist, like a company like AbCellera to exist, versus what you're seeing in practice and executing?

Yes. Well, first, the premise that there is anywhere close to a limited addressable market in the discovery of therapeutic antibodies or related modalities, I would take exception to. I mean we've got an industry that is one of the largest, one of the fastest-growing sectors of biotech. It's been growing at 11% per year. That means -- unless you believe that success rates were getting better and, if anything, they're getting worse, that means that the early stage work is growing at least that fast. And I would say it's even faster than that given that there are new modalities and new ways of using antibodies, conjugates, bispecifics, cell therapies, for instance. So this is a giant market. I believe that what you're seeing on the early stage is kind of a bifurcation of the types of companies. There are companies that are setting up operations to do fee-for-service work. They basically have a scope of work, and they execute it for a price and they watch the margin. And they have largely built those businesses on technologies that have their roots in the 1970s and 1980s. So this is old technology. It's not differentiated. And it has for a long time been for many companies the only option if you want to move your science into something that can be developed in the clinic. So that's one camp, and that's sort of competing on price and not investing in the technologies that underpin the industry. But there's another trend, and it's the one that we recognize and believe we're leading the charge on, which is those drug developers that realize, if I'm about to embark on a 10-year journey, if I'm going to spend $500 million, if what hangs in the balance is a therapy that may or may not work and treat patients, it makes no sense to be going for the very cheapest solutions at the very front of this process. It makes a lot of sense to get a competitive advantage to find better molecules to do it on a faster time line and to allow organizations like us, who have invested in best-in-class technologies and admitted our business to do this day and day out, to get those programs off to the very best start. Those tend to be the companies that are more serious about drug development. And our business development efforts have absolutely seen, if anything, a growing inbound interest from partners. So we often report programs under contract. This quarter -- this last quarter we just reported, we added another 17 programs under contract. That brings 55 programs under contract for the year. By all metrics, that exceeds anyone's expectations, including our stretched expectations internally. So we have a robust book of business. But what has been even more exciting is the quality of the partners that come to us and their conviction in actually moving things forward into the clinic to find drugs. And so we are focused on trying to get that section of the market. And I think you're seeing the validation of those companies in our partners, companies like the Lillys, the Regenerons, the Gileads, Everest, EQRx, Moderna recently. I mean these are companies that have the means and are sophisticated and have chosen AbCellera as their partner, and we're proud to stand beside them and help them meet their goals.

Right. I think that's an interesting segue into some discussions about the business model and the financial underpinnings of that. Again, there's also a perceived notion that the portfolio itself might be higher risk than average or that it might be kind of difficult to assess, given that you don't necessarily have a lot of visibility on the specific programs, the specific targets we, as therapeutic analyst, would love to do a DCF. So if you give me 150 programs, and I don't know what they're for, like how should I go about this? What is the best way to kind of address some of those uncertainties? And how much value is there from getting perhaps a lower share through a royalty in a more diversified portfolio rather than taking more concentrated bets and the risk/reward that comes with that? I mean by design, you were supposed to have a different business model, but how do you kind of reconcile that portfolio building aspect of the business? And how should that go forward? How should we think about that?

Sure. It's a great question. Look, the -- a question that we often get is, "Can you give me details of the targets, the indications, the status of preclinical programs?" I'm sympathetic to that request. I mean I would love -- in principle to help people understand the value of the business, I would love to be able to share that information. The reality is that when we engage with partners, their programs -- the status of their programs, certainly the targets are confidential information. And there's good business reasons that we cannot disclose those. So when we do work for a partner, we hand off a program. We expect that it will be some time until that program finally reaches an IND application. And at that point, we can share with the market, hey, this is a program that came from our platform. People start to see on clinicaltrials.gov, this is the indication, they can start to build those models. That just takes some time to mature. So as of today, as I mentioned, we have well north of 150 programs under contract. These are programs that we either have executed or have signed up to execute. And we have executed or started to execute on about 69 of those. Typically, a program will take anywhere from 3 months to at the sort of extreme end a year. Once that happens, we hand it off to a partner. The fastest you might expect that to get to the clinic would be, say, 2 years. In some cases, for a variety of business reasons or scientific reasons, it could be significantly longer. So given that we are a company that is growing quickly, we're executing more programs -- or we're executing at a faster rate all the time. The vast majority of that portfolio has happened in the last 2 years. So we have -- we're in this period now where it will take some time for that to really blossom, and people will start to see molecules coming in the clinic. 1.5 years ago, we had no molecules in the clinic. As of last quarter, there are 5. And while that's going to be variable from quarter-over-quarter or year-over-year, the trend is definitely going to be upward into the right and accelerating is our belief. So that's a challenge in the business model. But that challenge is one that we do our best to address with investors, but it doesn't mean that we should deviate from our conviction that this is the way to build a business that's going to be valuable in the long run. In terms of how you think about these things, we typically on our, I'd say, middle-of-the-fairway type deals have royalty stakes that are in the low to mid-single-digit rate. And when we use our internal analysis to try to calculate what is the value of a program, we view that component of any deal as being the dominant source of value. And what that means is that if we work on a program, there will be some revenue that shows up on the top line. That's revenue for executing the program. That is not what our business is about. Our business is about building the portfolio behind it. In addition to those deals that layer on top of each other, we have recently started additional deal structures, particularly with early companies that include deepening our position through either taking equity stakes. We've done that a few times now in terms of performing companies. During the earnings call, I mentioned an equity position with Invetx, which brought a molecule into the clinic this quarter. So that's a good example of that, and there have been others. Another model is to build in optionality to co-invest along partners as they develop molecules through Phase I, Phase II, Phase III. Those options, we view as very valuable because we get the chance to work with a partner, assess the teams, see the science. We know the molecules. And then if it makes sense for our business, we have the ability to deploy capital and build a deeper position in those particular molecules. We did a recent deal with EQRx that has that flavor and view that as a very high-value deal and one that -- on a program, if we were to take investment all the way through, we start to approach what is a co-ownership position. So building up a subset of what will be hundreds of programs that has the profile of the -- economic profile of an internal program or something more akin to what we've recently done with COVID with Eli Lily.

Perfect. And started to jump around a little bit more about the technology and the business model, but just to circle back to the technology stack, right? So can you talk a little bit about the single-cell screen capabilities that it seems -- that is a proprietary piece of -- core IP that you have, can you talk about some of the key drivers up and downstream from that particular step of the discovery process and what's unique about those specifically, just briefly in layman's terms for most investors?

So I think what you're asking about is what makes that single-cell platform differentiated over the field, is that right?

Yes. Also you already kind of alluded to the actual throughput capabilities. So perhaps a step before, so when you're talking about sourcing antibodies, right?

Okay. Sure. Yes.

Your technology is agnostic to animal models, but you do have a proprietary suite of animal models. And then downstream from the single-cell step, there's a lot of misconceptions of how easy or how difficult it is actually analyze and actually get to the right antibody and how to engineer that antibody. So yes, if you can give us just some quick snips on what's proprietary and what's unique before the single cell and after the single-cell screening.

I got it. And I'll try to be as brief as possible because I could go on at some length. On the front end of the platform, which broadly we're calling the source step, this is about generating the appropriate immune diversity from which you're going to find your therapeutic leads. Maybe the first thing to say is that we have focused our company on leveraging the power of natural antibody responses, the immune responses. That is in comparison to alternative approaches that are trying to use synthetic libraries. So display -- eased display, phase display where you've got artificial antibody diversity that you have engineered or you've cloned out of an animal, and you're trying to apply that to discovery. The first thing to say is that natural immune systems are, by far, more successful in generating high affinity antibodies that are developable, and that has been proven out over now 3 decades of drug development. So well over 90% of all drugs have come from natural immune systems. The early ways to find those antibodies were with hybridoma. That's a technology that was invented in the '70s and is woefully inefficient. So you miss most of the diversity. The other -- but of course, you need to have great diversity to start. And as you get into difficult targets, what you want is a very high-quality immune response of human antibodies, and you want to be able to generate that against the right epitopes and against difficult targets. So we have internally a transgenic animal, most call the Trianni Mouse. It's been engineered with modern genetic engineering techniques to put in all of the human antibody genes into the mouse. And then we've paired that with a whole suite of biochemistry and immunization technologies. Most recently, this quarter, we announced the acquisition of TetraGenetics, for instance, which is a company in Boston that has spent about 17 years building up the technologies to express high levels of multipath transmembrane protein targets. This is something that is a very big challenge in the industry. And if you cannot make the target, you can't even start on the program. So it's one of the key pieces. That's an example of a proprietary technology in the front end. On top of that, building out the immunization methods, the tolerance-breaking methods, genetic immunization. And having done that now on hundreds of programs over time and working on some of the most challenging programs, we've built up expertise that we believe is second to none. So we believe we are well suited to generate those antibody responses from that proprietary animal. And then, of course, we pair that with the single-cell screening to let us look much, much more deeply. In terms of what comes downstream, downstream of that, after a screen, we will have looked through perhaps millions of cells in a day. We will have selected hundreds to thousands that we know make an antibody that has some property that you want in the therapeutic. And then we bring those into an industrialized single-cell genomics and repertoire-sequencing workflow. That's another part that sits downstream. What that allows you to do is within days to find out what is the genetic code that encodes for those antibodies. And that is automation, it's molecular biology, it's also the bioinformatics and data science to help you to do that. And then I realize I could go at length, but once you've done that, you need to convert the hundreds, the thousands of antibodies into the actual protein sequences and bring them through the gauntlet of biophysical analysis to try to understand them, generate data clouds around each antibody and predict which ones have the properties that you want, the potency; the epitope recognition; the affinity; but also importantly, the developability. And that is a major investment in protocols and data science and industrialization that very few companies have put in place. And for smaller companies, there is no business model and no possible way to ever put that in place. And if you cannot do that, how can you possibly select what would be the best antibody to be the therapeutic?

Yes. Got it. No, I think that makes sense. Since we are running a little bit out of time here, I'll be remiss if I didn't ask about COVID, right? And I left that item towards the end by design, just hoping to get away from it. But we still get probably a disproportionate amount of inbounds related to the COVID aspects of the business, 1404, any updates there? But how do you think investors should think about the COVID antibody relative to the broader AbCellera story given that a lot of that has played out already to some extent?

Yes. We have been consistent. So for like over a year, I've been getting this question and sincerely believe, look, what is COVID? The COVID success, first, it's something that we're very proud to have participated in. So if you look at the recent order from the U.S. government, there was an order that came -- announced from the U.S. government of another 614,000 doses of bamlanivimab and etesevimab. Combined with previous orders, I believe that comes up to about 2 million total doses that we expect will be used out in the world in patients. So that is a massive impact that we've had in the fight in COVID-19 and helping patients and something that if you're in a biotech, you could work multiple careers and never have that impact. So first and foremost, that's what's important, that we were able to contribute. Beyond that, it is a tremendous endorsement of the technology to respond quickly. So we brought that first molecule bamlanivimab to the clinic with our partner in world record time, in 3 months. And then we were later able to follow that up with a second molecule, so 2 molecules in the clinic in under a year. And it's also an endorsement of the execution of the team to be able to pull that off in what was almost certainly the most highly subscribed and competitive antibody discovery effort that the industry has ever seen. So it is literally the case that every company that had a dog in the race was doing that. Of course, that has also been a proof point for the partnership business. We've seen that the value of that has been -- economically has been driven by the royalties. And those royalties have been a large source of nondilutive financing for us to double down on what is the real mission of AbCellera, which is to repeat that again and again across multiple indications. In the long run, AbCellera is about building capabilities and technology that help to get therapies more quickly to patients and not to do that just in infectious disease, but to do that in oncology, to do that in neurodegenerative disease, inflammation, arthritis, whatever it is. So for me, it's a proof point of the technology and the team. And it is also a terrific source of nondilutive financing, which helps us to execute on what we think is the much bigger opportunity over the coming years.

Got it. No, that's perfect. I mean, we did cover a lot of ground here, so went in a lot of different directions there. Any last things that perhaps you want to highlight that is important for investors not to miss out on or something that perhaps is misunderstood? What else your folks kind of been paying attention to? And how do you expect AbCellera to change over the next couple of years?

Well, look, I think with that question, I would just turn to what are the top priorities in the business today, because I think it all starts there. Like what are we spending our time and effort on? And what do we believe is going to really move the needle for drug development and create returns for investors in the long run? That's 3 things. So one is execution on the partnership business. It is about building out the business development teams. It's about building the capacity to execute on those programs so that we are rapidly building that diversified portfolio that, over the long run, will mature into first milestone streams and then royalty streams, all of which will come in without us bearing the cost of development, and so at 100% margin, and help to grow a very attractive long-term business. So that's the first thing. And you will see that quarter-over-quarter through programs under contract and increasingly our focus on program starts, which is when these programs actually begin. The second priority is finishing off this 10-year project that we've been on to reinvent this workflow of antibody discovery. And right now, that is investments in translational science, CMC and GMP. So that by 2024, AbCellera has the world's most technologically advanced end-to-end therapeutic antibody discovery engine. That is a capability that is incredibly valuable and allows you to build a business in multiple ways by providing access in technology and molecules out to the industry. And the third piece, which we didn't have time to talk about but it is a critical advantage, and I don't have time to really unpack it here, is our vision is to not just do technology to do things better, not just to do them faster, but to do it at scale. And the way that you achieve scale and efficiency is through complex coordination of these technologies and your workforce and data science, which represents at least 1/3 of our R&D for us, is the big lever on that. That is the way that you can not just do something well once, but do it year-over-year dozens of times, and we're making big investments in that. And so what I hope people watch is, is AbCellera delivering on that? Do you believe this business model exists? To me that is on its face, obvious. And do you believe that we have the path to being the leader in that space with an accelerated advantage? Of course, we do, otherwise, we wouldn't be running the business this way.

Fair enough. I think that's a good stopping point in our discussion. But again, as usual, I appreciate the time, Carl. Hope you all the best, and we can probably wrap it up here. But I'm sure you're available, I'm available for follow-up questions from investors. So have a good rest of the conference.

All right. Thanks much, Tiago.

All right.