Hi, good afternoon, everyone. Welcome, welcome to this session of the twenty-second Annual Morgan Stanley Healthcare Conference. I'm Judah Frommer, one of the mid-cap biotech analysts, and we're very pleased to have Pyxis Oncology with us, represented by President and CEO, Lara Sullivan. Let me just read a quick disclaimer before we get started. For important disclosures, please see the Morgan Stanley Research Disclosure website at www.morganstanley.com/researchdisclosures. If you have any questions, please reach out to your Morgan Stanley sales representative. With that, Lara, maybe we could start with just a short overview of your programs for those less familiar with the Pyxis story.
Sure. Thank you for having us.
Sure.
We appreciate the opportunity to be here and to share our story with everyone. Pyxis Oncology is an ADC-focused company, with our lead asset being an ADC that is a first-in-class and first-in-concept approach, targeting the tumor stroma. What we'll spend most of our time talking about today. Our second program is an immuno-oncology approach. It's also in the clinic, and it's a novel checkpoint inhibitor. Our history came... We were born as an IO company, but we added in the ADC technology, the end of 2020, early into 2021, about a year or so after we launched. So we have a fair amount of IP to be able to create a pipeline of ADCs behind our lead program, and so our company focus has really been primarily shifted to the ADC space.
Okay, great. With that in mind, can you talk a bit more about the differentiated approach in targeting the stroma with ADCs, as opposed to others who are targeting cell surface receptors? Success has been limited clinically in stromal targeting.
Yeah.
Maybe an ADC approach could have better prospects.
Yeah. You know, it's a real interesting time for us to be a stromal targeting ADC, because there's a confluence of changes happening in the ADC modality itself, as well as an improved understanding of the tumor microenvironment and stroma, how it behaves, you know, how to, how to drug it. In the case of the ADC modality itself, you know, the canonical belief has been that you need to, you know, target something that sits on the cell surface that can be internalized into the tumor cell, and then the ADC would be cleaved inside the tumor cell, the payload would be released, and it would, it would kill the tumor from the inside out. Our approach is different.
We are targeting extracellular domain B, which is a splice variant of fibronectin, which is a structural component of the tumor stroma. Essentially, you can think of us as, you know, attacking the stroma in a way to take down the structural support of the tumor. What we had learned preclinically with our program, and which, you know, as we disclose our clinical data later this fall, I think we'll demonstrate clinically, is that you don't have to have the ADC payload completely internalized to be able to effectively kill tumors. That's a big shift in thinking here, and I think part of the reason that the last 20 to 30 years of ADC development has focused on internalizing targets is that ADCs have been technically complex to build.
The field spent twenty years trying to figure out the right linker, the right payload, the right conjugation chemistry, what target, and so you've got multiple technical variables you're managing at once. You don't want to take target risk if you're taking molecule risk, right, technical risk. As the field has gotten more comfortable with the ADC construct, being able to take target risk and really understand how the ADC works is more within frame, and so that's where we come into play. I think the past approaches that had worked in the stroma, to the earlier part of your question—
Mm-hmm.
had targeted, different components of the stroma that were still cell surface. So, fibroblasts, for exam-
Mm.
For example, as a target, right? An antigen that's sitting on the surface of a fibroblast or other cells within the stroma still had relied on that previous mechanism. We're opening up a new field of understanding, I think, not just in the tumor microenvironment, but also within how ADCs can be effectively used.
Okay, great. And you in-licensed the ADC platform from Pfizer. Can you walk us through key differentiators with that platform, what makes it special in terms of—
Yeah
... payload, conjugation, linker technology, and how can that impact the ultimate therapeutic window of your ADCs?
Yeah. We were very fortunate, about six years ago or so, five years or so ago, that Pfizer, for corporate reasons, had decided to externalize its technology. Their initial intent was to spin out a company led by Pfizer employees to create an ADC-focused company off that technology. The pandemic hit, that plan went away. We were there and able to, through our Pfizer relationships, receive the technology. We were very excited about it because we knew Pfizer had spent at least a decade empirically testing and optimizing all elements of the ADC construct, the linkers, the payloads, the conjugation approaches. Little biotechs who create their own technologies can't do that degree of investment, and so, when the construct was selected to go with this target, with this EDB target...
We knew that it had been empirically evaluated, and that the best of each of those components was put forth. Some of the improvements that Pfizer made into the technology toolkit were around the stability and the permeability of the ADC construct itself, and the payload's ability to be permeable into the tumor. We have a very specific conjugation chemistry. Sometimes, you know, earlier in development ADCs have been less specific in their conjugation approaches, more, more generalized conjugation approaches.
Between sort of more site-specific conjugation chemistry, better stability of the ADC, better potency, better permeability, and the appropriate matching of each of those elements to the target, in this case, our 201 program, we feel it is a very de-risked technology compared to what else you would see in SMIDs, who simply do not have the resources to do that kind of empirical work.
Okay, that makes a lot of sense. As you are moving through the 201 program and your Phase I trial, what's the level of enthusiasm look like from investigators? What does that tell you about unmet need or willingness
Yeah
... to try such a new mechanism? Maybe you could tie in recruitment and trial conduct overall.
Sure. We launched our Phase I basket trial in March of 2023, so we're about eighteen months into the clinical trial now. It was extremely well-received by our investigators. We had waiting lists right out of the gate for our program, and I think the early days of the trial, those waiting lists demonstrated a couple things. One is a real interest in this novel mechanistic approach, and a hunger for the fact that there's still very few ADCs that are broadly applicable across multiple tumor types. The stroma is common across tumor types, so the thinking in the investigator mind is, "Well, this could potentially be a very broadly applicable, new ADC therapeutic." We had waiting lists right out of the gate at multiple sites. It's a global trial. We have eighteen sites across the U.S. and the world.
We're in Europe, Spain, U.K., Belgium, and that waiting list, that demand for patients has continued. Now here we are, eighteen months into the trial. We've announced dose levels at 5.4 , eight mg/ kg, dosing cohorts, and there's real-world clinical experience that these investigators have with our agent, and we still have waiting lists. You know, that tells you that as these investigators have become more familiar with this agent and have seen the experience their own patients are having, as well as those of their peers, that there's a real reason to believe and be excited about the potential of this agent. The enthusiasm remains very high. I think it's also less common to see a broad basket trial in any modality from a small biotech.
You know, it's much more of a, kind of a pharma-style approach, and, you know, that speaks to our confidence, the preclinical work that we had seen from Pfizer and that our CSO and his team have replicated, that indicates real broad potential here. I think that was another thing that's been driving the enthusiasm.
Okay, got it. You mentioned some of the doses. How can you put the doses reached in context of kind of—
Yeah
... the broader ADC landscape, and what that could mean for the profile of the drug versus your expectations heading in and modeling in the Phase I trial?
Sure. Being a novel target and a novel mechanism, there's not a lot of clinical precedent, right, that we had to draw upon in planning our trial. The best analog we could draw upon was the Pfizer HER2 ADC, the legacy one. They now have another one from Seagen, but their originating one, and that had the same linker payload as what we have.
Mm-hmm.
We looked very carefully at how their Phase I trial unfolded, and remember, HER2 as a target is ubiquitous, ubiquitous... What's the word? How do I say it?
Ubiquitous.
Ubiquitously expressed across a variety of tissue tumors. You have a less specific target in HER2. You have a much more specific target with our target. We have very high expression in tumor, essentially negligible in normal-
Mm-hmm
... but same linker payload. Pfizer's HER2, we observed a sort of a limit of dose, a dose ceiling. They could not get above 5 mg per kg.
Mm-hmm.
Their major dose range was 3-4 mg per kg. They had two DLTs at each of those dose levels. They had a 50% discontinuation rate at 5. We used that as a proxy in our planning.
Mm-hmm.
We were very pleasantly surprised and pleased to see that we sailed through the 3.6 mg per kg cohort, which was right in the middle of their range from a safety perspective, and then same with 5.4, where we dosed 10 patients we announced in March. We were already exceeding the upper limit of where they were able to get to, and our belief is that two things are driving that. One is, the specificity of the target, so the payload is going where it needs to go within the tumor. There's not a lot of places in the body where this target exists to draw the ADC away from the tumor.
Mm-hmm.
Whereas in the HER2 setting, there is.
Right.
That's sort of point number one, and then point number two is mechanistic.
Mm-hmm.
You know, perhaps something about drugging the stroma rather than the tumor is allowing us to inject more payload into the tumors, and that could go all the way into the detailed level, which I won't get into here, around, you know, efflux pumps and channels and permeability kinetics. There is all kinds of interesting science that could be underlying and explaining that as well.
Got it. Okay, maybe we could spend a minute on, on safety profile generated thus far.
Mm-hmm.
What adverse events might you expect with the EDB mechanism and with the payload that we should be watching out for? How would you characterize the qualitative safety updates?
Yeah
-you've gotten so far?
With any ADC, platform-level toxicity is something that you pay very close attention to. The neutropenias and neuropathies, the ocular tox, something we are scrutinizing very intensively. With such a specific target, our concern about target-specific tox is actually pretty low. Again, I'll use HER2 as my comparative example, because there are known HER2 target-related toxicities. Of course, you know, that was-- those insights came from the preclinical work. Once you get into humans, you never know exactly what's gonna happen for the first time, but we've been very pleased that we've had very little in the way of target-specific tox. It is really around those three-
Mm
Elements of payload-related tox, and our philosophy is to dose up to the maximum tolerated dose. By definition, as we get closer to that dose level, we will experience, you know, those types of AEs. The challenge, right, is the knife edge of getting to the optimal efficacy with sufficient tolerability.
Okay.
Mm-hmm.
Perfect. Can you talk about evidence of activity you've seen so far? What gives you the confidence that there is antitumor activity?
Mm-hmm
... with 201 , and that the high doses aren't just reflective of a sink-
Mm
-or potentially a less activated?
Yeah. I'll sort of answer that in reverse.
Yeah.
I think the specificity of the target, as we just talked about, I think is one, you know, one of the most, sort of clear reasons to believe there's not a sink effect going on because there's just nowhere else for the ADC to be, to be kind of drawn to.
Mm-hmm.
In terms of the, the, sort of efficacy potential here, what we have commented on through our press releases and through our dialogues is that we are seeing clear evidence of biological activity. What is... We always get the question, "What do you mean?" We mean sort of any and essentially any and all of the following: that can be considered unconfirmed PRs, confirmed PRs, clinical improvement-
Mm-hmm
AEs, right? Because you're getting to the MTD, and reduction in tumor markers. We're very confident with the data disclosure that's coming up later this fall, sometime between now and Thanksgiving, that investors will see very clear evidence of biological activity and real clarity around what the dose range is.
Mm-hmm.
You know, we're reserving judgment on the precision of the dose because, you know, ten tumor types with multiple dose levels, it's hard to-
Yeah
... to have enough N to have the comfort on exactly what the dose is, but we know what playing field we're in, and the next stage of development is gonna help us refine that. We're pretty, we're pretty comfortable with the data we're, we're seeing. We've dosed 72 patients. We'll probably dose up to 80 by the time the data comes out, so it's a nice data set for a Phase I dose escalation.
Mm.
It still has limitations. It's Phase I dose escalation.
Right.
Yeah.
Okay, you recently talked about narrowing down to four tumor types.
Mm-hmm.
Can you talk about how you chose to hone in on those? How much of those, of that decision was driven by clinical or versus preclinical data?
Yeah. In March, about a year after the start of the study, we announced the focus on four tumor types. That was really driven by the mixture of some of the preclinical insights we had, you know, target expression patterns, you know, PDX models, et cetera, as well as clinical experience to date. The purpose of honing in on those four was not to signal that we had made the decision that those are the four to develop further, but that we had enough interesting reason to increase the N of patients being recruited into the trial in those four tumor types to enable better decision-making. In May, we added a fifth tumor type to the mix, which is sarcoma. The four were head and neck, lung, ovarian, and pancreatic.
Mm.
Then we added sarcoma in May. You know, when you've got 10 tumor types, even at 80 patients—
Mm
... and it's never straight math, but if you did straight math, that's eight patients per tumor type. It's still a low end.
Yeah.
Right? So, and we're not doing the straight math exactly that way. You'll see anywhere from, you know, five to ten patients per tumor type of interest, you know, at those higher dose levels, and then you'll, we're, you know, we're also trying to augment the N in the other five tumor types.
Mm.
Because again, you just, you really—the name of the game is, you know, obviously tolerability, but identify and follow the signal.
Yeah.
The burden of proof is different for different tumor types, right? In terms of the response rate expectations, in terms of the pretreatment population. You know, there's so many variables going on. That being said, with 80 patients, roughly, for data disclosure, we think we will be able to demonstrate clear, actionable next steps from a development path perspective. We'll be very clear on, "We're going in this direction. Maybe we're not going in this one. Here's areas for further exploration. Here's the catalyst calendar, investment required," et cetera.
Okay, got it. And related to that, how are you thinking about EDB expression as a marker for selecting patients?
Yeah. We published some... In our corporate deck, we have some really nice IHC data, and at AACR earlier this year, we had a couple posters with further insights on the IHC data across tumor types as well as the PDX models. It is a very helpful—the expression pattern is a very helpful piece of information. Now, we have not been able to use it prospectively as of yet because this is the first time in the clinic. What we are working to do is capture insights around the target expression, correlated with responders or non-responders, and then leverage that as helpful for any patient selection going forward. The biomarker strategy is very important to us.
Mm-hmm.
Whether it ends up being solely dependent on EDB or other sort of elements related to the mechanism is very much under scholarship right now from our CSO and his team. We do think that the data disclosure, in addition to the data on safety and tolerability, will provide some real insights on the mechanism at play here and how this, to your opening questions, right? How targeting the stroma in a different fashion is really beneficial. We think that the mechanistic information will be pretty interesting, and sort of putting all that together is gonna help us ultimately with a biomarker strategy.
Okay, got it. As we think about the data later this year, what measures should we think about beyond ORR and safety?
Mm-hmm.
Will we get a sense of potential durability based on duration of follow-up? And then can you tell us if it'll be at a medical conference or whether you'll do it at a company sponsored?
Yeah.
Yeah.
The initial data disclosure for this fall will be a company event. We've, you know, with emerging active dose escalation, it's tough to make those abstract deadlines for the medical meetings. We would expect after this data release going forward, we'll be able to plan more, you know, around those kinds of conference calendars. The data will be fulsome. It'll be efficacy, safety, as you mentioned, PK. We'll have a lot of insights on the mechanism. You know, exactly what we're building out of the AACR posters that we had shared earlier this year, Jan's team's working on right now. I think that'll be very helpful. We'll have patient vignettes.
Mm-hmm.
We'll have real clarity around what we're doing next and the catalyst calendar for next year.
Okay. And a couple more boxes to check just on the actual release. Can you help us with number of patients, doses-
Mm-hmm, mm-hmm.
-scans?
Yep.
You're gonna be focusing on response rate, PFS, duration of response.
Right. Oh, yeah, so duration of response. Let me start there. I did neglected to say it earlier. Since the trial's been going on about eighteen months-
Mm-hmm.
We will have some durability from the lower doses. And to the extent that we are able to capture it for some of the higher doses, we will.
Mm-hmm.
You know, we announced in March the 5.4 dose had cleared. We announced we were starting 8, you know, you'll have some month of durability data there. The data will look like, roughly 80 patients total.
Mm-hmm.
The vast majority will be, have scan, two scans.
Yep
...clean data. We're reserving the right to include walk-in data of patients whose, you know, scan timeline is a little bit outside the database lock.
Mm-hmm.
I'd say, you know, probably 90-95% of the data points will be cleaned and validated.
Mm-hmm.
It is not gonna be one of these situations. We've seen several of them this year, where little companies rush out data, and it's unconfirmed, and then they have to reverse it later. That's not the way we operate, so.
Okay. That makes a lot of sense. How should we think about, win on the efficacy side? Are there bars you can help us with?
Yeah. You know, the temptation is always, of course, to look at data coming out of studies like ours relative-
Yeah
... to what we know the current emerging standard of care is going to from Phase II or Phase III trials, which is inherently tough coming out of Phase I that's not powered that way.
Yep.
That being said, we use all of that in our own internal decision-making to assess the strength and quality of the signals that we're evaluating. For example, you know, if a particular tumor type has a response rate, you know, the standard of care is converging on 40-50% response rate, we have an N of 10 in that tumor type, and we see one signal.
Mm.
Even if the rest of it's promising, we'd probably make the judgment it's not the best place to spend our resources. You know, conversely, if we have an N of five, and we have an 80% response rate, and the standard of care is 35%—
Mm
... we'd see that as a strong signal to go forward, but we wouldn't go around saying we're gonna get an 80%-
Right
... response rate, right?
Mm-hmm.
We balance that. We use it as informative but not determinative. We also use everything else at our disposal, right? Looking under the hood at each patient, what is their response history? What does that look like? You know, what do the spiders look like? What do the waterfalls look like in aggregate? Within each patient, what do we understand about the meaning of the signal there? I think putting that together with our understanding of where we can be competitive and win, along with the characterization of the signal, is what informs our judgment, and that's gonna be part of the narrative that we share with the Street when our data comes out. We want to be very clear for everybody how we're interpreting the data.
And of course, you know, the market will make its own judgment on what we say, but we don't want the judgments made in the absence of, you know, explanation, so we'll be very clear about all that.
Okay. That makes a lot of sense. And if we look kind of at next steps for 201 —
Mm-hmm
... how do you think about positioning a stromal targeting ADC?
Yeah.
Should we be thinking about monotherapy, combo, early line, late line, you know?
Yeah
... relevant to tumor size?
Yeah. It is, honestly, it's a, it's a super exciting advancement here that I think the investigator community might be a bit ahead of the investor community in understanding, to be honest with you.
Mm.
And, you know, with 30 years of ADC development, and everyone's focused on the same concept of internalizing targets. I think that the way to—the guidance we're gonna provide around this will clearly be driven by the tumor types that we think this type of mechanistic approach will be equal to or superior to what we see now, from—certainly from a monotherapy perspective to start, right? You've got to meet the bar on that.
Yeah.
I think monotherapy strong, strong monotherapy data gives you the right to then explore combination potentials that can juice that return, right? Padcev plus Keytruda, the standing ovation in bladder, I mean, I actually think with our mechanistic approach, that kind of outcome could be within reach for us.
Mm-hmm.
Because you're looking at an orthogonal treatment approach to everything else that's out there, right? You could imagine combining our agent with other ADCs that are-
Mm-hmm
... internalizing. Of course, you've got to manage the toxicity layering. You could imagine combining us with checkpoints. You could imagine combining us in certain tumor types with other emerging standards of care. The right to do that, we earn by showing the monotherapy strongly in those areas. That's how I would guide all of us to kind of think about the data as sort of clarity around the monotherapy strategy, and then the pull-through on that for what it means for the next stage of monotherapy development, and then potential combination, combinations from there.
Okay, that makes a lot of sense. Maybe just taking one step back, we talked about the four tumor types you honed in on and adding a fifth in May. The fifth was soft tissue sarcoma.
Yeah.
Can you just give us a little bit more detail on what led you to add that as a target?
Yeah, and sarcomas are interesting and a little bit different than every other tumor type in our trial right now because there's such a heterogeneous classification of tumors.
Mm-hmm.
They're almost—it's almost an umbrella term for a hundred little diseases, right? Even in the context of our trial, where, you know, we're trying to land an N of anywhere from, you know, five to ten per tumor type at the higher dose ranges, you could imagine a scenario where every sarcoma patient who walks in is different from each other. We've been trying to wrap our brain around that. I would point to the AACR posters and the IHC analysis and the PDX models there for sparking our interest in sarcoma, and then, like, again, like you asked earlier, some of the clinical experience. We do think that from a development pathway perspective, that one can, you know, has more complexity associated with it. Can you consider...
This is where the FDA would need to weigh in, can you consider sarcomas as their own package, of multiple tumor types in there, or is it an individual development path per tumor type? The answer to that would have huge implications on, you know, what we would see as the viability to chase that particular signal. I think right now, our job in this Phase is to surface the clarity of the signal.
Mm-hmm
... where it is and where it isn't, and then apply our regulatory and commercial acumen to, "Okay, is this signal worth chasing or not?
Mm-hmm.
You know, make the judgment call there.
Okay.
Some of those answers, I think, can be quite clear coming out of this stage, and I think others will require more scholarship through the next stage of development.
Okay. And then just following up on kind of the potential for combos here, you mentioned ADCs and checkpoint inhibitors. Anything else we should consider from a modality perspective that could make sense as a combo?
Yeah. I think that there are other modalities that would make sense. I, I, we'll, I don't think we'll comment on that specifically right now.
Mm
... because, you know, Jan's team is, is really taking a look at the right, you know, preclinical models by tumor type, and this is where I think little companies could get in trouble versus big companies.
Mm-hmm
... where it can be an endless, you know, an endless decision tree on what to choose to chase. I think there's some clear hierarchies with respect to the checkpoints and the ADCs to start with. Then depending on as we peek under the hood for each tumor type and understand where certain patient types are more amenable or less so, and then understand the current emerging standard of care, that's where I think we can say, "You know, maybe in ovarian it might look like this, maybe in head and neck it might look like this," and see what the preclinical models tell us before. I think the kind of the overall way to think about the development plan is sort of monotherapy, clear, clear catalyst, to be articulated for next year.
Mm-hmm.
For combination, I think that's more opportunistic, and then we'll see how, you know, how the monotherapy guides us on that, and those could be catalysts that get layered on, sort of after the, after the monotherapy catalysts, prove themselves.
Okay. That makes—
From a timing perspective, too. Yeah.
Got it. Okay. I mean, I think this has been a great overview of the company, but maybe just to wrap up, we could focus on cash position, cash runway, and then key events.
Yeah
... that investors should be focused on the next six to twelve months.
We have roughly $160 million, I think, was our last disclosed cash position, and that takes us through the second half of 2026. We are very appreciative of that, and the development path that we will, you know, be sharing with the data is funded, you know, with this cash that we have on hand. You know, that being said, we all know what the market looks like and, you know, we would be interested to continue to augment our cash position at the appropriate time, you know, coming off of data. You know, this fall, we'll have an opportunity to consider, you know, raising, depending on the market conditions and of course, what's going on in the macro.
Next year, you'll see, as part of the data release, a catalyst calendar around which we could anticipate potential future raises as well.
Okay, great. I think that's all we have, so thank you very much for the participation today.
All right. Thank you. We appreciate it. Thank you.