Palatin Technologies, Inc. (0KF3) Earnings Call Transcript & Summary

Greetings. Welcome to Palatin's PL9643 Phase III Clinical Study Results Conference Call. [Operator Instructions] As a reminder: This conference call is being recorded. Before we begin our remarks, I would like to remind you that statements made by Palatin are not historical facts and may be forward-looking statements. These statements are based on assumptions that may or may not prove to be accurate and that the actual results may differ materially from those anticipated due to the variety of risks and uncertainties discussed in the company's most recent filings with the Securities and Exchange Commission. Please consider such risks and uncertainties carefully in evaluating these forward-looking statements made by Palatin's prospects. Now I would like to turn the call over to our host, Dr. Carl Spana, President and Chief Executive Officer of Palatin. Please go ahead.

Thank you. Good morning and welcome to the Palatin PL9643 MELODY-1 Dry Eye Disease Phase III Results Conference Call. I'm Dr. Carl Spana, CEO and President of Palatin. With me on the call today is Steve Wills, Palatin's Executive Vice President, Chief Financial Officer and Chief Operating Officer. Steve and I are excited to have this opportunity to review the positive initial top line results from our PL9643 MELODY-1 Phase III trial in dry eye disease which were announced by press release earlier today. The objectives of today's call are to provide additional context around the positive results and, to the extent possible, answer some audience questions. MELODY-1 was our first large randomized controlled clinical trial with PL9643, a melanocortin receptor agonist, in subjects with dry eye disease. MELODY-1 evaluated PL9643 in [ 455 ] subjects with dry eye disease at multiple centers in the United States. Subjects were randomized to receive either PL9643 or vehicle. There was a 4-week run-in where subjects used vehicle, followed by a treatment period of either PL9643 or vehicle for 12 weeks. MELODY-1 was designed to evaluate the safety, ocular tolerability and efficacy of PL9643. The study had 2 co-primary efficacy end points, 1 clinical symptom, pain, and 1 clinical sign, conjunctival lissamine green staining; as well as multiple other symptom and sign secondary end points of dry eye disease. In accordance with FDA and EMA guidance, the analysis of the data indicated that both age and sex factors that can affect dry eye disease needed to be accounted for in the primary statistical analysis. 60% of the subjects were over the age of 60 and 68% of the subjects were female. For a positive study, 1 of the co-primary end points needed to achieve a p-value of less than 0.025. Our symptom end point did, and we're excited to report that we have a positive study. Now let's get into the data, starting with safety and ocular tolerability. There were very few ocular adverse events, and PL9643's ocular tolerability was excellent. PL9643 was very well tolerated. There were very few ocular treatment-related adverse events in the PL9643 arm, 5.6%, compared to vehicle, which was 6.3%; and fewer study discontinuations in the PL9643 arm, 7% versus 11% in the vehicle. In dry eye disease, having a well-tolerated product is extremely important. Next-generation compounds all need to have excellent ocular tolerability. And I think the tolerability here is absolutely superior and will play very well in the market. Now let's review the efficacy data. For the intent-to-treat population, we are happy to report that, for the co-primary symptom end point of pain, the PL9643 treatment arm met the statistical requirement for a positive study, with a p-value of less than 0.025. In addition, subjects treated with PL9643 had a clinically meaningful benefit of greater than 10 points on their visual analog scale, meaning this result was not only statistically significant but it was medically important or clinically important as well. Statistical significance of -- [ meaning ] less than 0.025, was also achieved for multiple exploratory secondary symptom end points, including eye dryness, ocular discomfort, burning and stinging and others as well, so very strong response here on the symptoms; again ocular tolerability; excellent [ relieving ] symptoms, really important for dry eye disease. Now let's move on to the co-primary end point of signs, which was conjunctival lissamine green staining. For the intent-to-treat population, PL9643 did not achieve a p-value of less than 0.025; nor did the secondary end points, sign end points, as well. However, [ PL9643 treatment ] demonstrated positive treatment effects over vehicle for multiple signs. And in addition, we are seeing an improvement, as a function of time, for many of these signs as well. Based on our preliminary analysis of the signs end point data, we are confident that, as we advance into future clinical trials, PL9643 will reach significance, statistical significance, for the sign end points as well. In summary. We are very pleased that the positive results of MELODY-1 support the continued advancement of PL9643 as a treatment for dry eye disease. PL9643 treatment had excellent safety and ocular tolerability, statistically significant and clinically meaningful effects on the primary symptom end point of pain and multiple exploratory secondary symptom end points. And the effects of PL9643 were superior to vehicle on multiple signs of dry eye disease. Before we open the call to questions, I'd like to summarize some of the next steps for this Phase III program. As you might expect, there will be a detailed analysis of the full data set for the study, followed by a meeting with the FDA to discuss the results and the remaining studies required to support a new drug application submission. We are now planning and preparing for the next clinical studies that we believe will be needed to support the new drug application submission. These are MELODY-2, a Phase III safety and efficacy study to confirm and advance the results of MELODY-1; and MELODY-3, an open-label safety study. We will continue to advance our business development activities to find a partnership for PL9643. And in support of these, our business development activities, we will publish and present data from MELODY-1. Steve and I would like to thank all of you for participating in the PL9643 MELODY-1 Dry Eye Disease Phase III Results Conference Call. And we're now going to open the call to questions.

[Operator Instructions] Your first question is coming from Joe Pantginis with H.C. Wainwright.

Interesting data. I think a bunch to discuss here, so -- to help us all understand some of the analyses, so I'm going to approach it in a stepwise fashion. And hopefully, we can address it like that, so I'll start with my conclusion question first. Why do you feel these MELODY-1 results could or could not fulfill 1 of the 2 Phase III requirements per the FDA, looking towards dry eye disease? So that's the ultimate question but more specifically hoping you can help me understand a couple of these points: The unadjusted planned analysis for both co-primary end points did not reach stat sig, so I think the perception there would be then that the study did not work from a -- from the co-primary and stat sig. However, you do state that the ITT for adjusted age and sex did reach stat sig for the co-primary of pain, so can you please explain how this adjusted result is or isn't, say, a post hoc analysis; and how it's useful for your future FDA discussions?

Absolutely. So just to be clear here. And it's going to take a little of -- bit of explaining, but it's pretty straightforward, I think. So in the primary analysis, although we did not reach statistical significance for pain, it actually had a p-value of 0.03, so very close. In addition, we had multiple other pain -- or other symptom end points that actually did transcend 0.025, so we now have a positive study [ on its phase ]. And we're required by the FDA -- all sponsors are required to do this, by the way. This is not something that we made up. Whenever you have a positive study, you are required to then go in and do and examine the covariates that could affect the outcome of that study; and that's what we did. And age and sex are covariates that are known to affect dry eye disease. And in fact and as we can see, we had a very large -- a much larger [indiscernible] number of patients that were older, 60% over the age of 60. And almost 70% were women, so you're required to now examine your -- these covariates. And indeed the trajectory of the response in those populations were different; and required that, per -- FDA and EMA guidance, that you now have to adjust your primary analysis. So this is done, this routine. Now by the way, in the adjustment, you don't know which way it's going to go. It could go positive or negative. There are many cases where we -- the FDA does these analyses all the time when you submit your data, so you need to do them upfront because, if this, say, went the other way, if it moved the study from -- to a negative, you -- then it's a negative. So you control for these covariates. It's standard. Everyone does it. You're required to do it. And in our case, we felt, just to be transparent, we want to make sure everybody understands exactly what we're doing, so from our context, this is the analysis plan that would -- is submitted to the agency. This is what we will do in the next studies, so we feel very confident that the agency will be absolutely fine with what we're doing. This is what is required to be done per their guidance and so this will be a supportive study. To be a fully supportive study, obviously we want the sign. And when we really look at the sign data, it's very interesting. We do see -- for most of these signs, we see that, treatments with PL9643, these subjects are all getting better and improving with the treatment more than they are with the vehicles. We had a little bit more of a vehicle response, so we didn't quite [ separate and get there ], but I think -- as we look at this data, I think it's pretty clear there is an effect on multiple signs. And I think that we are -- we will be able to adjust in the next study to make sure that we do hit the sign. And I think, hitting the sign [ and the symptom in the next study, in the study with the ] -- I'm optimistic the agency will accept those 2 studies in support of an NDA submission. Ultimately we will have to discuss it with them, but just based on precedent, it is very rare for dry eye disease studies and particularly the first large one to hit everything, to get everything you want. And the agency -- because of the excellent safety of these compounds and the excellent tolerability, I think that you -- and precedent, you -- it is likely we will be able to do just an additional trial and then...

So that -- yes, no, that makes good sense. So again -- not to belabor the point, but again it's just for understanding purposes. So once you start the required covariate analysis that you described well, does that then negate the ultimate primary end point, that you can then use this as one of the required Phase IIIs? Hopefully, that question makes sense.

Yes -- I mean that's essentially what you're required to do, right? So in other words, you have to add them into -- required to add these into your models. And you do that; and that becomes your analysis, your primary analysis.

Okay, I understand. And then separately, because -- I mean, when you look at the level of vehicle response that you guys are talking about here, how do you think you can address that going forward with additional studies? Because I guess, when you talk about just the physical use of these vehicles, it's in essence providing a level of lubrication for the eyes, which then allows for a patient -- alleviation of symptoms or what have you.

Sure, yes. And that's this is not -- this is very typical. You can look at -- for example, you can pull the Xiidra data set, the summary basis of approval; and you see a very similar pattern. You see, in the smaller Phase II study, vehicle didn't perform very well and active looks great. And then you go to these large studies, and all of a sudden, vehicle and active are almost in lockstep. And you have to -- so there are a couple of ways of doing it. One, of course, is just powering up. You do more patients and you just do a brute force approach. I -- and that is certainly an acceptable approach and sponsors do that, and that's not a problem from an agency standpoint. I think a different way of doing it and one that I think will probably come out as we delve into this: Keep in mind we just got this data set, so we're really talking about top line data here, but I had an opportunity to look at the -- a lot of the science data and graphed it out and sort of taking a visual look at it. And I think, because of the very clear improvement of the signs, as a function of time, that opens up different analytical techniques for looking at the sign data versus just a straight baseline end of study. There are other models that you can use that other sponsors have used actually and is -- used quite routinely. And I think, when you begin to use some of those and you combine that with just maybe some more patients, you're going to see the signs really pop, over vehicle. The vehicle is never -- is not as consistent as you see with the active. The active is improving, as a function of time, which is what you want to see, which is what you'd like to see.

Got it. I appreciate the color. And looking forward to the FDA's visibility from this.

Your next question for today is from Michael Higgins with Ladenburg Thalmann.

I wanted to follow up on Joe's questions and more specific on the adjusted [ basis ] that you've done this review [indiscernible]. Are there other examples where the FDA has approved [ a dry eye drug ] where the pivotal data reached the co-primary end points but only on an adjusted basis, as it happened here?

Sure. I mean you can -- it's very typical that these covariates [ are added in. So Xiidra added ] covariates in. They [ added sight ]. They added prior dry eye drug use and several other covariates in as well. And so this is very typical for most studies, that you do a covariate analysis. And you can -- you add them to your model.