Okay. So, good morning, everyone. My name is Jeff La Rosa. I'm an equity research vice president on the immuno-oncology team here at Leerink Partners. And I'm excited to welcome Pyxis Oncology to the final day of our annual global biopharma conference. Joining me from Pyxis to participate in a fireside chat with me is Chief Executive Officer Lara Sullivan. So, welcome, and thank you.
Thank you, Jeff, for having us. We appreciate it. Our colleague, Pam Connealy, our CFO, will be here shortly.
Perfect. Well, let's not wait. Let's dive into it. So, I think first, just to set the stage here a little bit, provide some context for those who might be new to the story. Maybe you could provide a short overview of Pyxis, its history, you know, relationship with Pfizer, and really just how your pipeline has evolved from a predominantly IO-centric focus when you IPOed, to one really centered on your lead antibody-drug conjugate, or ADC program, PYX-201.
Sure. So, we were born as a target-stage IO company. The founding investors had put Pyxis together around IP out of the University of Chicago, Tom Gajewski's lab. This was back in 2018-2019. Tom had created a number of hot tumor and cold tumor models, and we had actually a pretty significant amount of IP that came into Pyxis as a result of that. But it was target stage, very, very early. The Series A was $22 million. If you do the math, that doesn't quite get you to value inflection points that are required these days. So I joined shortly after it was formed, and I realized a couple weeks in that we were going to need to do a modality expansion because otherwise the company just wasn't going to make it. ADCs came up as a natural modality to expand into.
This was late 2019, before sort of everything got super hot. And the reason for that was we had some of that technical capability in-house already, and we also were seeing these ADC and IO combinations coming into play. And we thought, all right, that could be a nice complementary modality to what we already have. So, we began to screen the variety of ADCs that were out there. Bayer was spinning some out. Pfizer was spinning some out. There were several in Asia. And, I'm an ex-Pfizer colleague who had spun SpringWorks Therapeutics out of Pfizer before. So, there was a natural conversation that happened about their commitment to spin the ADCs out. The pandemic hit, and that made it sort of accelerated our ability to do that.
So, we brought in the entirety of the Pfizer ADC toolkit, which includes the linkers, the payloads, the conjugation chemistries, as well as two preclinical assets, pre-IND assets, that Pfizer had gotten started, one of which is our lead program today. So that multimodality approach was the catalyst for the Series B and then the IPO in 2021, where we raised $320 million. And then, you know, with the market correction and, you know, the focus on the emphasis on being focused and disciplined, we decided to really hone in on the ADCs as our sort of lead technology and our lead focus area while we're maintaining some opportunistic activity in IO with our second program.
Perfect. So, let's dive into those ADCs in particular, PYX-201. So, obviously, you want to talk about the initial data coming up, but I think first, I think it'd be important to sort of kind of provide some perspective on why you think the stroma, as, you know, a first-in-class angle and also first-in-concept that you would argue as a tumor, as stroma targeting ADC. Why has that approach been overlooked? Why is PYX-201 different? Yeah, and what's it solving that maybe, other ADC approaches are not?
Yeah, I love this question because I think, you know, you get the chance to weave in a little bit of history into science. And what I mean by that is, you know, Mylotarg was approved in 2000, right? So, the first ADC, and here we are in 2024, and ADCs are, you know, one of the top three modalities. It took 25 years for this thing to mature. And I think that's because the, you know, to get a really, well-designed and active ADC, you need a lot of things to go your way. You need the right targeting antibody. You need the right target. You need the right linker, the right payload, all of that to line up.
I think, you know, when I was at Pfizer and this they were working on the ADC platform, and I saw it firsthand, we just had preclinical failure after failure after failure because, you know, like the cherries in the slot machine in Vegas, if you get one lemon, it's not working. And so that's what was happening preclinically. So, things just couldn't get out of the preclinical space. And that was for classic cell surface targets. So, if you were already struggling to get something that worked with, you know, biology that was understood, you weren't going to go, you know, the royal you, the industry wasn't going to go searching, you know, for targets in the stroma. So the way we ended up exploring this was, Pfizer did take a risk by putting this stromal target into preclinical development.
They had connected with a researcher in Switzerland named Dario Neri. He's a passionate scholar of the stroma. He's been doing it for years, and of course, our IO colleagues have made progress in, you know, the stroma as a targeting and the importance of the tumor microenvironment. So, that also was going on in parallel with, you know, trying to figure out the ADC slot machine. And so, Dario identified this target. He radiolabeled an EDB antibody fragment and demonstrated on PET imaging that it had localized specifically into the tumor tissue and was not seen at all in any normal tissue. The IHC analysis ensued. We saw, well, Pfizer saw at the time. We replicated this. Exquisite expression, very high expression in tumor tissue and negligible in normal.
That kind of gradient of target expression was pretty intriguing because you don't see that every day. So that work on the EDB target at Pfizer at the time was kind of going on in the background while all this, you know, cell surface targeting and ADC learning was going on. And so, we saw that data when we had the opportunity to license everything in from Pfizer, and we got pretty excited about the idea of targeting the stroma. You know, all the fundamentals of what you look for in a good preclinical program lined up. Taking the mechanistic risk still felt comfortable to us.
I would say it has been interesting as we got closer to the clinic and then into the clinic, you know, even today as we're a year into the trial, that, you know, we still see a lot of questions around, you know, why do we believe in the stroma? And ultimately, the clinical data itself, I think, is going to cure a lot of those questions about the mechanism. And until then, it's a lot of clues and breadcrumbs that, you know, lead people to conclusions of whether they think it'll work or not. We obviously think it will. So.
It seemed some prominent KOLs might think it might work.
Yes, yes.
Alluded to yesterday in our ADC panel, and that was refreshing to see, experts, you know, thinking about these novel approaches and how targeting the stroma could unlock certain opportunities. What about your ADCs design, though? I think when, you know, I talk to folks who are more risk-averse, they will say, well, you're just releasing the payload and the stroma, and the stroma surrounds the tumor. Then aren't you going to target all these healthy tissues, too, that are right there? And, even though, of course, we'd all love the bystander effect to exclusively go into tumors. But, what about the risks non-internalizing ADCs for you from a safety perspective, from a dose therapeutic window perspective?
Yeah. So, I think the linker payload that we have in this agent is, it's an optimized auristatin, which has improvements in stability and permeability over MMAE. So, some of the, I think, the preclinical data and work that we've done, that helped give us comfort around this will also be shared at AACR in April. We have a couple posters there. So, it really was around how the linker payload has been engineered for improved stability, improved, you know, permeability, improved metabolic properties. The DAR is approximately four, and it's a pretty homogeneous four. You know, we're not seeing sort of huge ranges of DAR that average to four. It's pretty close there. So I think that gave us confidence in this. Yeah, the preclinical work, the understanding of the linker payload and its improvements.
Excellent. So I think thinking of, I guess, looking at the data now, the upcoming data set, we're all excited to see it. So, I guess, if you could remind us all of kind of what we should expect from this data set, patient numbers, dose levels, you know, the types of analyses you want to provide, and everything around that.
Yeah. So, you know, a year into this, we're, you know, we're super excited as we get closer and closer to data release. You know, every week brings more information. And ultimately, what we would like to release out sort of with the full data set, the trial size for 45 patients. [crosstalk]