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Peel Hunt ‘Expanding the Pipeline’ Interview with Avacta CEO Christina Coughlin 27.11.2024

https://peelhunthealthcarelifesciences.gallery.video/241127

"....The third aspect is that as we get both of those to manufacturing the toxicology and the pharmacology ready. We are now prepping for our conversations with the health authorities. A common thought or a common misconception is that we just submit to the agencies. Not true. We can actually have conversations, the FDA has an entire program called the pre-IND where we can have conversations before. It allows us to do an early presentation of mechanism of action, the pharmacology, the early days of toxicology and we give them a draft of the trial, and we have a collaborative conversation about this. All of these aspects, those three that I mentioned, can take over a year before hitting go on manufacturing and really being ready to file that IND. Again we work collaboratively with the health authorities on approving and then opening the trial in the US. Similarly we will work with MHRA to open the trial in the UK. It is important to note though that these agencies are independent, they can have different timelines, and so we will get going as soon as we can, but looking forward to the next chapter the IND enabling studies for AVA6103."

+++

Mentions MHRA / UK trial.

Similar more recent discussions in the public domain do not discuss MHRA, - only FDA - in terms of 6103 Phase 1 readiness.

Grok states no NCT trial details exist, and thus not abnormal that trial centres are not published yet.

Slide 17

As Curtis mentioned, with our collaboration with Tempus AI, one of the questions that we asked was not only, where do we see FAP expression, but then combining that question along with the Gene that predicts for response to a topo 1 inhibitor like exatecan, - SLFN11.

So in these plots we're looking at here in dark teal. Each dot represents an individual patient in the database, and we're looking at both FAP expression along the x-axis and then SLFN11 along the y-axis, and asking the question:

- What are the tumor types that would be predicted to be sensitive. You can see here four of the top tumor types that were identified, that we are taking forward in the clinic. Gastric cancer, Cervical cancer, Pancreatic cancer and Small Cell Lung Carcinoma.

These four diseases, as you can see the dark Teal, that most of the patients would be predicted to be highly sensitive to the FAP exatecan molecule.

Slide 18

So topo 1 is a mechanism that is used, it's SLFN11 that we know, there's approved topo 1 inhibitors, and then leveraging that collaboration identifies the optimal indications.

There's multiple larger market opportunities, but we wanted to take those four tumor types forward, that would predict for the most sensitive. Predict those patients that would be most sensitive to the drug.

Slide 19

That way we walk into the clinic knowing that we should be seeing responses. Here what you're looking at is the clinical trial design for FAP exatecan.

From the outset we will take forward two different dosing regimens in every three weeks, and in every two weeks.

We've developed this clinical trial design to optimize the data collection, but also in collaboration with our multiple investigators, - experts in these four different disease settings, - to look at exactly what is the dosing regimen, and how do we want to take that forward.

So you can see we will dose escalate in all four diseases across those every three and every two week regimen, identify the recommended dose for expansion, or the MTD in both the every three weeks and in the every two weeks, and then move into the expansion cohorts with this one.

Slide 15

Curtis: This is a PK study with AVA6103 again in a HEK-FAP model. So these are tumor bearing animals that receive a single dose of AVA6103, and then had the tumor and plasma samples measured for either AVA6103, or released exatecan, over a five-day period.

What we can see is pretty impressive, we see released exatecan in these tumors within minutes of dosing. This extends for five days at concentrations above those required for cancer cell kill whilst remaining below the toxic concentrations that occur in humans.

If we look at the blue line, the plasma levels of released exatecan are not only incredibly low at two hours, but by four hours, they are completely undetectable. Which results in a highly favorable tumor to plasma ratio.

CC: And back to how Ellen described it in Gray, is the peptide drug conjugate. So that's the peptide and the drug together, and it's held in the tumor for five days. So that's the capping group - that's the way I think about the capping group, - holds it in the tumor for five days.

Then importantly you can see the horizontal line there that we indicate the Cmax, this was the Cmax that was achievable in the clinic with conventional exatecan.

This is the PK concentration, the top concentration that was seen in patients. A couple of important points - as Curtis mentioned in blue, is the released exatecan from our drug from AVA6103 that we see in the plasma, which is well below the toxic concentration that was seen in patients.

But importantly, which we don't always see with ADC's, we get a rapid Cmax in pink in the tumor of released exatecan that is well above the Cmax that could be achieved in the clinic with conventional exatecan.

Both of those together are exactly as we challenged you guys, and exactly the profile that we wanted to achieve in the animals.

So the concentration of released exatecan in the tumor, is well above the toxic concentration seen in patients with conventional exatecan. The level of released exatecan that we see in the blood stream, is well below.

Concentrate the drug in the tumor and mask it in the plasma.

So this figure shows you exactly what we wanted to achieve with AVA6103. Going back to the previous figure that we looked at, we compared and we learned from AVA6000.

Slide 16

CC: So what did we see in this experiment early on that you could change Curtis?

Curtis: Yeah, this is another preclinical study in tumor bearing animals. These received a single dose of AVA6000, and the PK profile looks slightly different to AVA6103.

With AVA6000 you get rapid clearance of intact AVA6000, but you still see tumor levels of released doxurubicin above the ic50 of different pancreatic cancer cell lines, for up to about 40 hours.

Our PK studies of AVA6000 in plasma demonstrate a very short half-life of the intact AVA6000, along with a low Cmax, and AUC in the plasma of released doxorubicin, which is what contributes to the favorable safety profile.

CC: so let's go into th

Slide 14

CC: Moving on from these animal models, we're going to look at some of the deep data, exactly how the sustained release mechanism works.

Curtis: Yes, so what you're looking at here on the left, this is a plot of the tumor and plasma concentrations of released doxorubicin at one hour post AVA6000 dosing in a HEK-FAP tumor model.

What we've found is that the median tumor plasma ratio in this study was around four-fold, so the concentrations of dox were around four-fold higher in the tumor than they were in the plasma.

CC: So we were encouraged by that in the clinical setting, but then the clinical data.

Curtis: Yeah, so if we look here this is once again a plot of the tumor and plasma concentrations of released doxorubicin at 24 hours post AVA6000 dosing in patients, and what we see was pretty striking.

We've dramatically increased that ratio where the concentrations of doxorubicin in the tumor are now a median of 100-fold higher than we see in the plasma.

CC: Right now the four to one tumor to plasma, we did do a few different animal models with AVA6000. We never really got better than about 15 to 1. So this is really relevant, and this one describes what we saw in the preclinical setting.

We were then pleasantly surprised when we got into the clinic, and the median tumor to plasma is 100 to 1. That's really how preCISION was designed. It was to concentrate the drug right in the tumor microenvironment.

We'll come on to this in a bit. Most of faridoxorubicin is converted to doxorubicin right away. Back to what Ellen was saying that kcad over km - so the efficiency of this one is incredibly high.

Ellen: Yes much higher than our FAP exatecan. So we're getting higher turnover higher conversion from FAP doxorubicin to doxorubicin.

CC: What we needed to do to get exatecan to work was slow it down and drop that efficiency.

Still Slide 14

Curtis: The next experiment we ran - so again these are the tumor and plasma concentrations of released exatecan at two hours post dosing with AVA6103, again in a HEK-FAP tumor model.

This is where we see how impressive AVA6103 is in its performance, because in a preclinical setting, the concentrations of released exatecan in the tumor are already 99 fold higher than we're seeing in the plasma, and will continue when AVA6103 gets to the clinic.

We will be doing exactly the same as we are doing with AVA6000 where we'll be measuring the tumor plasma concentrations of released exatecan in the patient tumor and plasma at 24 hours post dosing.

CC: Okay let's look a little bit at the data behind these profiles.

Slide 12

This is another preclinical efficacy study, this time in a pdx model of small cell lung cancer.

So this was a FAP mid, SLFN11 high model, and we see a similar thing with this pdx model as well, where AVA6103 is outperforming exatecan once again.

We are seeing greater tumor growth inhibition throughout those three doses, and we're actually seeing complete responses in all animals treated with this. Once again continue following treatment cessation.

CC: Another important thing about these two models, and one of the reasons that they were selected, so the gastric model, only a one+ ihc so low, and this one a little bit higher with a 2+ ihc.

Now you mentioned a gene in there (SLFN11). Why is that Gene important, - why mention that here.

Curtis: SLFN11 is something that we've looked at throughout the past year as a potential marker for sensitivity to topo 1 inhibitor treatment.

Our translational research team has done a lot hard work along with a collaboration with Tempus AI, on trying to identify which indications might be best to take AVA6103 into. Based on what their FAP expression, and SLFN11 expression looks like, which I believe you're coming to later.

Slide 13

CC: Great point. So the biology team took on that information that we found with the Tempus collaboration, and using AI and data Science to go after what are the indications.

The biology team then took that data back into the preclinical setting - back to you Curtis.

Curtis: Yes, so this is a continuation of some of the preclinical efficacy studies that were shown on the previous slides, with the addition of a few more.

Some of the data that came out of the Tempus AI collaboration showed us a few more tumors, or cancer indications that may be interesting to go into.

Here we have gastric which we've shown previously, and small cell lung cancer. Also pancreatic cancer, and colorectal cancer where some high FAP, high SLFN11 expressing indications.

What we see is the same across the board for all of these indications, where AVA6103 outperforms exatecan with greater tumor growth inhibition, but we're getting sustained durable responses in these animals even following treatments cessation.

Slide 8

So on the left hand side we have our FAP doxorubicin docked into a FAP model, and then on the right hand side it's the comparative preCISION exatecan molecule.

These have similarities of course in terms of the preCISION peptide, so our d-alanine ProLine sequence, and then we have our warheads on the right hand side of these models.

So two key areas are the capping group on the left hand side in A and then our self-immolative Linker position B. It's important for preCISION exatecan to have the self-immolative linker to allow FAP cleavability.

That was one important learning we had early on in our project.

CC: How does the capping group work? What does the capping group do?

Ellen: Yes the capping group sits in the active sight of FAP, so it's to the left of the d-alanine of our FAP cleavable peptide, and because it sits in the binding pocket, it is important for achieving good binding affinity.

Which is what we have with our FAP exatecan molecule.

Slide 9

We've got a capping group that has good binding affinity, and can be held in the FAP active site, contributing to a sustained release.

The capping group is also important in the ADME (Absorption, distribution, metabolism, and excretion, - also known as “ADME,” are the internal processes that describe how a drug moves throughout and is processed by the body.) PK profile, and so we have our capping group enhances of plasma protein binding, - and has lower clearance as well, - again contributing to our sustained release.

CC: So the half-life in the plasma of FAP doxorubicin (Faridoxorubicin), we know that it's quite short, it's only about 45 minutes in patients. What do we expect the capping group to do here, with respect to that. We expect that to prolong essentially right?

Ellen: Yeah, so by having a better binding affinity, it's going to be held more tightly in our FAP binding pocket, and because of slower release as well, it's going to be held there and not turned over as quickly as we see with our FAP doxorubicin molecule.

CC: Okay, so tell us a little bit about the Linker. So Faridoxorubicin doesn't have a Linker. Why did we use these and what were we trying to achieve with the Linker?

Ellen: Yes the linker was important with exatecan is that it allowed us to release. So if we don't have a linker with exatecan, we actually don't get that cleavability, so the linker is vital to achieve this.

Also what that linker allows us to do is to vary the rate of cleavage, so the enzyme efficiency, so what we didn't want with our FAP exatecan molecule is a Linker that has high turnover, because we want that sustained release.

So with the linker we've chosen we have a slower release, or slower Kcat/Km (enzyme efficiency), that allows that more sustained release profile.

CC: So Ellen, now that we've designed the chemistry, we're going to fast forward on this next slide through a lot of work that was done in the preclinical setting.

Slide 6

So four important observations from the first drug in the clinic, which also led us to understand a little bit more about the opportunities that preCISION and the peptide drug conjugates show over and really able to address, some of the limitations that we've seen with the highly successful drug class known as antibody drug conjugates (ADC's).

So these four key opportunities the first tumor specific release.

So FAP as I mentioned, on the membrane of the fibroblast. So membrane bound FAP is only found really in the tumors.

So there in the patients we're going to get tumor specific release. We limit the amount that's in the bloodstream, and so we're not releasing the drug in specific organs.

So we eliminate those organ specific toxicities, - Pneumonitis, Hepatitis - that we see with the ADC's.

The second is manufacturing. We get stable and controlled manufacturing. Ellen will talk about knowing exactly where on the peptide we insert the drug.

That leads to very sustained stable and controlled manufacturing. It's also because it's a pure small molecule manufacturing, it's much cheaper than ADC's. (ADC’s: DAR = Drug to Antibody Ratio)

Third we have small molecule penetration. Curtis is going to show you a little bit of the recent data that we've shown, of tumor to plasma.

We get penetration of these, and release of payload within minutes versus hours with ADC's.

And then finally, FAP is expressed in 90% of solid tumors, so we have a very large market opportunity here.

With the bystander effect active being shown that, with the salivary gland cancer data that we've shown with Faridoxorubicin, we can now show, down to just a low level of one+ ihc (Immunohistochemistry), exposure with FAP, that we get really nice concentration in the tumor.

So without further ado, let me turn it over to Ellen who led the chemistry team through the invention here of the sustained release mechanism.

Ellen: With our FAP doxorubicin molecule, we've got plenty of information to show that it's working in preclinical / clinical data.

But we need to take it back to the chemistry of this molecule, and understanding how the molecule binds into FAP, and the different parts of the molecule that create our FAP preCISION peptide drug conjugate.

So what we need to do is to then turn this molecule into our FAP exatecan molecule, and there are two key questions we needed to address.

First of all how we attach exatecan to our preCISION molecule, and then also with exatecan we want to have that sustained release mechanism due to the shorter half-life of exatecan compared to doxorubicin.

CC: Good point. - doxorubicin has a half-life of 35 hours, but exatecan has only 9. One of the reasons that it probably failed in the clinic.

Ellen: Yes exactly, so we needed to evolve / expand our preCISION platform to try and address this, and see if we can design a molecule to overcome the problem with exatecan.

Let's take a look at them.

Slide 3

The idea here is to mask the toxic effects of the payload or the drug within the healthy tissues, within the bloodstream.

Tumor specific payload release, meaning that the payload, - the drug, is only released within the tumor micro environment, by virtue of a FAP enzyme, that's only expressed on the cell surface within that tumor.

That is designed then to enhance the tumor exposure, so the amount of that released payload - released drug, that's right there in the tumor, and limiting the amount of the released payload that's in the bloodstream.

That's going to enable longer treatment, because patients can now tolerate the drug for longer periods. That's exactly what we've seen with the first drug AVA6000.

We want to talk to you today of how we've used all the observations that we've made in the clinic with AVA6000 Faridoxorubicin, and how those learnings in the clinic fed right into the team here - Curtis and Ellen, - that designed this sustained release mechanism.

So first how does this work.

You can see here the peptide drug conjugate can't enter cells. It's designed that way, once the peptide is attached it's unable to enter any tumor cell, fibroblast, hair cell, bone marrow cells.

The peptide is then released as soon as the drug encounters FAP, which is expressed on the cancer associated fibroblast (CAF). That payload is released extra cellularly. We call this the bystander effect.

It's released outside of the cells, and now able to move into a FAP positive or a FAP negative cell.

Importantly, most tumor cells in the epithelial malignancies are going to be FAP negative.

This bystander effect we've seen with the salivary gland data that we've shown SG cancers that we know can shrink tumors, even despite FAP only being expressed in the fibroblast.

Slide 5 (No slide 4)

So Faridoxorubicin our first drug that has entered the clinic there were four key observations in the clinical trial.

First FAP dox eliminated a severe cardiac toxicity that we observe with conventional doxorubicin. We also dramatically reduced the hematologic and the GI toxicities associated with doxorubicin. Two really important findings there.

Number one we can concentrate released doxorubicin in the tumor, 100 fold over plasma. Now this was much better in the patients, you'll see Curtis is going to explain what we saw in the animal models.

That then led us to some of the advances that Ellen and the chemistry team were able to make, as we designed the sustained release mechanism.

Finally, we do see evidence of preliminary activity in both salivary gland cancers as well as in soft tissues sarcoma.

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