Good day, and thank you for standing by. Welcome to the regulatory update on AMT-130 for Huntington's disease. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question-and-answer session. To ask a question during the session, you will need to press star one one on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star one one again. Please be advised that today's conference is being recorded. I would now like to hand the conference over to Chiara Russo, Senior Director of Investor Relations. Please go ahead.
Good morning, and thank you for joining us. This morning, uniQure announced alignment with and further productive guidance from the Food and Drug Administration on key components of the primary statistical analysis plan and CMC requirements in support of the accelerated approval pathway for our investigational gene therapy AMT-130 for the treatment of Huntington's disease. On this call, we will walk through the key components we have reached alignment on and guidance from the agency, as well as our anticipated next steps. Joining me on this webcast are Matt Kapusta, our Chief Executive Officer, and Dr. Walid Abi-Saab, our Chief Medical Officer. Please know that we will be making forward-looking statements during this conference call. All statements, other than statements of historical fact, are forward-looking statements. They are based on management's beliefs and assumptions and on information available to management only as of the date of this conference call.
These statements are subject to various risks, and our actual results could differ materially from those anticipated in these forward-looking statements for many reasons, including, without limitation, the factors described in uniQure's most recent SEC filings. Given these risks, you should not place undue reliance on these forward-looking statements, and we assume no obligation to update these statements even if new information becomes available in the future. Now, let me introduce Matt Kapusta, uniQure's CEO.
Thank you, Chiara, and good morning, everyone. We are very pleased to share an important regulatory milestone for AMT-130, our wholly-owned investigational therapy for the treatment of Huntington's disease. Following two Type B meetings with the FDA, we've now aligned with the agency on key components of the primary statistical analysis plan and CMC requirements to support a BLA submission planned for the first quarter of 2026. This alignment represents a critical step forward in the development of AMT-130 and adds to the growing momentum behind the program. It further strengthens our confidence in the accelerated regulatory path ahead and in our ability to bring this potentially transformative therapy to patients. Let me briefly walk through the highlights from our recent FDA interactions, and then I'll turn it over to Walid to provide additional details.
Starting with CMC, following our Type B meeting in March, the FDA agreed that validation of the AMT-130 manufacturing process should be possible using our experience and prior knowledge from HEMGENIX. This will be complemented by additional full-scale AMT-130 GMP batches and a single process performance qualification, or PPQ, batch. We view this outcome as a strong endorsement of both the quality of our manufacturing platform and the productivity of our interactions with the FDA thus far. This alignment streamlines our path forward and enables us to move forward more efficiently towards a BLA submission. In our second Type B meeting focused on the proposed statistical analysis plan, the FDA also agreed that the primary efficacy analysis will be based on the three-year change in cUHDRS in high-dose AMT-130 patients compared to a propensity score-adjusted external control group derived from the Enroll-HD Natural History database.
We believe this approach to accelerated approval, based on multiple years of clinical outcomes data, represents a differentiated and robust strategy that positions AMT-130 for success. We are grateful for the FDA's continued recognition of the critical unmet need in Huntington's and for their constructive engagement as we work to advance AMT-130 and prepare for a BLA submission. As a reminder, Huntington's disease is a rare inherited neurodegenerative condition that affects tens of thousands of people in the U.S. and Europe, with hundreds of thousands more at risk. It remains one of the largest genetically defined areas of unmet medical need, and AMT-130 is uniquely positioned as a potential one-time treatment targeting the root cause of the disease. Interest in AMT-130 continues to grow across all stakeholders, including patients, clinicians, investors, and strategic parties.
At the same time, we are advancing our commercial readiness in a phased manner to support a planned launch of AMT-130 in 2026. With that, I'd like to turn the call over to Dr. Walid Abi-Saab, our Chief Medical Officer, to provide more detail on the regulatory path ahead and next steps for the program. Walid?
Thank you, Matt. Good morning and good afternoon, everyone. I'm genuinely excited that we've continued to receive clear and constructive guidance from the FDA on both our CMC strategy and statistical analysis plan for AMT-130. This guidance provides important clarity for our development path and allows for continued hope for the Huntington's disease community, whose resilience and support remain instrumental to advancing AMT-130. Now, I'd like to walk you through the outcomes of our recent Type B meetings with the FDA. Following the successful initial RMAT multidisciplinary meeting in November of last year, the FDA agreed that data from our ongoing phase 1-2 studies, when compared to a natural history external control, may serve as the primary basis for a BLA submission under the accelerated approval pathway.
The agency also confirmed that the composite Unified Huntington's Disease Rating Scale, or cUHDRS, may be used as an intermediate clinical endpoint, and reductions in CSF and FL levels may be considered supportive evidence of therapeutic benefit. Building on this positive momentum, the uniQure team prepared briefing books for two Type B meetings: a CMC meeting, which was held in the first quarter of this year, and a statistical analysis plan meeting, which took place earlier this quarter. I will cover the outcome of the CMC meeting first. During this meeting, the FDA provided us with guidance that supports our plan to submit a BLA for AMT-130 in the first quarter of 2026.
First, the FDA agreed that it should be possible for uniQure to demonstrate validation of the AMT-130 manufacturing process using experience and prior knowledge from the Hemgenix process, complemented with additional full-scale AMT-130 GMP batches and a single PPQ run. Additionally, the FDA agreed with our proposed drug product release testing plan, including our proposed potency assay, pending completion of qualification and specification setting. We view this as a very positive outcome and are pleased that we will be able to fully leverage our previous experiences to achieve a BLA submission early next year. Turning to the recent statistical analysis plan meeting, the FDA continued to support its prior agreement that cUHDRS may serve as an acceptable registrational intermediate clinical endpoint for accelerated approval.
The FDA agreed that the primary efficacy analysis will evaluate the three-year change in cUHDRS in the high-dose AMT-130 patients compared to a propensity score-adjusted external control. Consistent with our July 2024 data analysis, we will be using a propensity score-weighted methodology for the primary analysis. Based on feedback from the agency, we will also be using additional sensitivity analysis using a propensity score-matching methodology and supplemental analyses to further assess the robustness of the conclusions. Lastly, and most importantly, the FDA agreed that Enroll-HD, a large, prospective longitudinal natural history study, may serve as an acceptable external control dataset for the primary analysis of the trial data, along with additional sensitivity analyses using TRACK-HD and PREDICT-HD datasets. This is significant as we believe the Enroll-HD database is a better fit-for-purpose comparator than datasets such as TRACK-HD and PREDICT-HD.
With more than 33,000 patients enrolled and approximately 3,700 patients meeting the eligibility criteria for the AMT-130 phase I-II studies, we believe that Enroll offers a more comprehensive contemporaneous dataset, lower attrition rates, and a significantly larger pool of patients who meet our eligibility criteria. These attributes allow us to better adjust for confounding variables and enhance the robustness of our propensity score model. Recall that earlier this year, a competitor who used a similar propensity score-adjusted methodology with the Enroll-HD database observed a two-year decline in cUHDRS that was consistent with the earlier analyses presented by uniQure using the TRACK-HD and PREDICT-HD databases. We view this as further support of the suitability for Enroll-HD as an external control. Overall, and again, we are very pleased with the guidance provided by the FDA and are grateful for the agency's continued productive engagement.
In terms of next steps, we plan to submit an updated statistical analysis plan later this quarter. We will present top-line phase 1-2 data in accordance with that plan in the third quarter. We expect to hold a pre-BLA meeting with the FDA in the fourth quarter. Finally, in the first quarter of 2026, we expect to submit a BLA for AMT-130 with a request for priority review. With that, I'll turn the call back over to Matt.
Thank you, Walid. As you've heard, our recent interactions with the FDA mark continued execution and meaningful progress in our journey to bring AMT-130 to patients with Huntington's disease. We now have a clear regulatory path that is reinforced by our ability to leverage our proven manufacturing platform and a robust natural history dataset. With this momentum, we are moving forward with confidence, fully focused on presenting three-year data in the third quarter of 2025 and submitting our BLA in the first quarter of 2026. I want to take a moment to sincerely thank the uniQure team for their hard work, dedication, and professionalism. Your commitment and collaboration have been instrumental in reaching this milestone. I also want to thank the Huntington's disease community for their continued support and partnership. Their strength, commitment, and trust have been essential to our progress with AMT-130.
We'll now open the call for questions. Operator, please proceed.
As a reminder, if you'd like to ask a question at this time, please press star 1-1 on your touchstone phone and wait for your name to be announced. To withdraw your question, please press star 1-1 again. Please stand by while we compile the Q&A roster. Our first question comes from Paul Matisse with Stifel.
Hi President. Sounds good that the Enroll-HD, in terms of the natural history progression, is consistent with what you've used previously, but can you just talk about, if you did the two-year analysis with Enroll-HD, what % disease slowing at the high dose you're seeing at two years? As it relates to the three-year data, is this the right way to ask the question? What are you powered for? Do you need a p-value? Is there a specific effect size hurdle? Any way that you can kind of help set up success relative to what you've seen so far in efficacy would be super helpful. Thank you.
Thanks, Paul. I will take this question. In terms of Enroll, we have looked at these data, and as you saw with data from our competitor, we expect that the rate of decline in this early-stage disease, like the patients who are enrolled in our trial, to be about 0.5 points in cUHDRS. That is what they found. That is what we found when we look at natural history Track and Predict as well. It tends to be fairly robust. The last time we shared data was based on the March 2024 cutoff of the data, which we shared with you last July. There, we saw at the high dose an 80% reduction compared to cUHDRS in that dataset. We do expect that the reduction or slow decline will continue past year two and into year three and more. We do not expect this to change at all.
In terms of magnitude of effect and p-values, those were not specifically discussed or requested by the agency. If you recall, even with that smaller dataset, at that time, we had only nine out of the 12 subjects who had data at two years. We have had statistically significant p-values when we compare to external control. Overall, I feel very confident with our mechanism of action, with the data progression overall, and with the robustness of the plan that we have. I expect that in three years, this will continue to remain steady and actually become even more salient when we compare to natural history.
If I can just ask a follow-up, I guess there isn't a specific hurdle for success at three years. The hope is that the data is consistent, and ultimately, the assessment of the three-year data is going to ultimately come down to just being a review issue. Is that the right way to think about it?
Yes, that's correct. The right way to think about it. There's no particular level of clinical meaningfulness that we propose in our SAP, nor it was raised by the agency. My personal interpretation is that the magnitude of effect that they have seen and the consistency of the data that they've seen so far lends itself to a level of comfort if those are maintained into three years. That is why I believe this was not specifically requested.
Okay. Again, not p-value driven. Is that right?
That is correct.
Okay. All right. I'll hop back in the queue. Thanks so much.
Our next question comes from Rai Forseth with Guggenheim.
Hey, this is Rai from DebJit's team. Thanks for taking our question. Could you elaborate on the sensitivity analyses using TRACK-HD, TRACK-ON, and PREDICT-HD? How do outcomes from these analyses influence the probability of accelerated approval, and what would be the potential drug label implications for this analysis?
In general, we believe that the propensity score methodology is robust enough that, to some degree, it's agnostic as to external database to compare to. Of course, Enroll, with its much larger sample size, would lend itself to more robustness when you're trying to deal with potential confounding biases. The agency very clearly looks at consistency of the results across various analyses and across various datasets. That's why it is important to do these sensitivity analyses, because if you just happen to pick the one that "is the winner" and the others are not consistent, that doesn't mean that you're going to be getting approval. The data have to show consistency across those.
When we look at all of what we have seen so far with the natural history, I'm very confident that the data are going to look fairly similar whether we use TRACK-HD or Enroll-HD in terms of the effect.
Thank you.
Our next question comes from Joseph Schwartz with Leerink Partners.
Hi, this is Denny on for Joe. Congrats on all the progress, and thank you for taking our questions. I was just wondering, in the PR and on the call, you've mentioned that Enroll-HD has a larger number of patients. Are there any other differences in these datasets versus Track and Predict that are important we should be aware of? Did the FDA give you any specific reasons that they preferred this study versus the other two?
First, let me start with that we were the one, actually, who proposed Enroll-HD. As part of our due diligence, when we compare what natural history we need to compare to, there are a set of assessments that we do in terms of better fit for purpose. There are many reasons why Enroll-HD, with the better fit for purpose database, they have more than 33,000 patients enrolled. It's contemporaneous. It has a lower attrition rate. It has higher follow-up or longer follow-up when you match to our patient population. Clearly, for us, it was the most appropriate database to use. We proposed it, and the FDA agreed with our proposal. The key difference between Track, Predict, and Enroll is that Track and Predict include the striatal volume calculation, which was an inclusion in our trial.
That's one of the reasons why we will include that in the sensitivity analysis, because it would be very informative. Interestingly, for us, when we tried to evaluate the effect of the striatal volume, we tested it in the Track and Predict. Essentially, whether you include the striatal volume after you include the other prognostic factors that we use to generate a propensity score, it turns out that there's no difference anymore between patients where we had striatal volume included or not. What that tells me is that the prognostic factors that we are using are highly correlated with the striatal volume. To a great extent, they take that factor into consideration and make such that if we use Enroll, we're not losing out on this piece. The bottom line, Enroll is the more robust.
We think that the prognostic factors that we use will obviate the need to add striatal volume. Nonetheless, we will be using the sensitivity analysis with Track and Predict, which I expect to have very similar results to what we saw in what we will see with Enroll in terms of the reduction in cUHDRS after three years.
Thank you. If I can just ask one more follow-up, can you give us any details about attendance in the two Type B meetings? Were there any significant changes from previous meetings or any new additions? Thanks.
Matt, do you want me to take this, or do you want to take it?
Yeah. I mean, no, the answer is both meetings were very well attended, senior officials from DBER and the Office of Therapeutic Products, and no material changes to the participation from meeting to meeting to meeting.
Thank you.
Our next question comes from Joseph Thome with TD Cowen.
Hey, this is Peyton Onford, Joe. Congrats on the progress, and thanks for taking our questions. I guess, can you talk a little more about the manufacturing process, about how long it would take, any differences between the Hemgenix and the AMT-130 process, and do you still anticipate needing a site inspection? Thanks.
Yeah. What was the last part? Do we still anticipate what?
Yeah, needing a manufacturing site inspection. Sorry.
Oh, okay. Yeah. The reality is the AMT-130 manufacturing process is highly homologous with what is done now for Hemgenix. Obviously, the biggest difference is that it's a different transgene, but the manufacturing would take place at the same licensed facility. It would take place at the same train with the same personnel, leveraging the same quality management systems. Of course, you know that both use the same AAV5 vector. Things like testing for impurities, right, or testing for viral clearance, right, those methods are identical, right? There's really no changes, and those are things that we can leverage. We would expect to initiate process performance qualification in the third quarter, as we've guided, and we would expect that that would take approximately four to five months to complete. This is a meaningful amount of work.
I wouldn't call it high-risk work, but just in terms of the extended characterization and all the testing that has to be done, that's how we would expect it to be. I will tell you that in doing we were deeply involved in doing the Hemgenix PPQ, and that took well over a year to complete. An estimate of it being four to five months, we think is a huge win to be able to leverage that experience from HEMGENIX and move forward in a streamlined manner.
Great. Thank you.
Yeah. In terms of the site inspection, I think we would assume that the site is inspected. It has to do routine inspections. We're not necessarily sure that this would trigger its own inspection, but there may be routine inspections that need to occur as the FDA typically wants to do those inspections every couple of years, and that will depend on their availability of personnel and where this sits on their inspection priorities.
Actually, if I can ask a quick follow-up, when was the last time the site had an inspection?
We said that the site has had an inspection as part of the approval for HEMGENIX. It's been inspected by EMA more recently, but has not been inspected by the FDA since the approval of HEMGENIX back in 2022.
Great. Thank you so much.
Our next question comes from Luca Issi with RBC Capital Markets.
Oh, great. Thanks so much for taking my question, and congrats on the conversation with the FDA. Maybe we'll need to circle back on a prior question. If I captured correctly, it sounds like there's no specific p-value threshold that is required. One, is that correct? If so, does it mean that there's no formal statistical analysis that needs to be done on the primary endpoint? Is this all based on kind of the totality of the evidence? I think any additional thought there would be much appreciated. Thanks so much.
Yeah. Thanks. You were breaking up a little bit, but I think I got the gist of what you were saying. I don't mean to imply that there will not be any formal statistical analysis. We will be doing a formal statistical analysis with a primary endpoint, and we will also be generating sensitivity analyses, looking at also p-values and all of this. What I meant to say is that there was no predefined degree of clinical meaningfulness that we were requested to meet or any discussion on that topic that were raised by the FDA. Beyond that, I think we will be sharing the data, in my opinion, based on our understanding of the space, rare disease, advanced therapies, that it matters a lot, consistency of the results. And depending on the statistical analysis and the various sensitivity analysis, the results have to be consistent enough.
I don't know to what degree a specific p-value needs to be met, whether you are close to it or not. Those were not things that were discussed specifically and would be a matter for review, in my opinion. We will be doing formal testing, and we'll be generating p-values, and those will be submitted as part of the documents.
Got it. Prof, if I can just follow up, if you are doing a formal statistical analysis on the primary endpoint, do you have a sense of what's the minimum delta in cUHDRS that you need to show in order to actually hit the stats? If so, whether the delta will be viewed as clinically meaningful to the physician community, especially in the context of this therapy requiring an intracranial injection? Again, any thought there? Much appreciated. Thanks so much.
Yeah. Thanks. That's very helpful. We have not conducted formal power analysis to evaluate what would be the minimum difference that we would need to see compared to an external control. To a large extent, that also depends on the size of your external control. Those analyses have not been conducted. It's really difficult to speak about power. All I can say is, with a smaller external dataset with Track and Predict that we essentially presented last July, and only with nine patients, we saw a very low p-value, very highly significant when we compared to the external control, with a large magnitude of slowing of disease progression when measured with cUHDRS after two years.
In terms of what constitutes a clinically meaningful difference for patients for this therapy, honestly, when we talk to our KOLs, they will tell us, and the patients as well that we discuss with patient organizations, they say any slowing of the disease matters a lot because that could translate into years of improved quality of life on the back end. I do not think there has been a consensus or a published figure that would indicate what would be minimal clinically meaningful difference. When we talk to our KOLs, they mention anything north of 30% would be meaningful. Again, this has not been confirmed or agreed to in the field in general.
Got it. Thank you so much.
Our next question comes from Suzanne van Voorthuizen with BLK.
Hi, Team. This is Suzanne from Kempen. Thanks for taking my questions. Congrats on this alignment. Maybe one on the difference between the propensity score weighted approach for the primary analysis and then the matched approach as a supplementary analysis. Given these are pointed out so specifically, can you remind us what the exact difference is and how these two approaches may influence the comparison? Secondly, can you elaborate a bit on what type of pre-commercial preparations you'll be undertaking in the time frame between now and a potential approval in the second half of next year? Thank you.
All right. I'll take the first question and turn it over to Matt for the second question. Propensity score methodology, both matching and weighting, are approved, well-established methodologies that leverage real-world data to support regulatory decisions. The FDA recognizes that multiple models exist and multiple methodologies, and they often look at the consistency of the results using different methodologies to evaluate the robustness of the conclusion. What's the difference between the two? Essentially, you generate propensity score based on a series of attributes that you have, and that will be the same for matching and weighting. With matching, you will select the matches from the natural history that closely resemble your subjects, and you end up with one-10, one-20 matches between the natural history and your subjects, and you compare them then using regular statistics.
Propensity score weighting takes that a little bit further and essentially utilizes the total sample to generate what you call a synthetic control group that will have different weights in those external controls depending on how well they resemble your subjects. As such, it leverages the larger sample, and you do not lose information from the natural history. You utilize the totality of that information. These methods are fairly robust, and actually, we expect that these two methods should yield fairly comparable results. That is why it is important to conduct both analyses and be able to present them to the agency, which is what our plan is. Matt?
Sure. Yeah. Hey, Suzanne. Yeah. Just in terms of commercial preparation, as I mentioned, we're going to be doing this in a phase-appropriate manner, but initially, we're going to be focused on medical education and market access reimbursement. Those areas we think are going to be essential for commercial success and ramping. In addition to that, we'll be looking at onboarding and identification of treatment centers as well as patient mapping. Those are kind of the broad work streams, and we'll be bringing on some key personnel and talent to help advance those initiatives.
Our next question comes from Kristen Kluska with Cantor Fitzgerald.
Hi. Good morning, everybody. Congratulations on this alignment. Did you speak with the agency in regards to any other endpoints, more as supportive pieces of evidence in addition to the cUHDRS? Did you have any talks about the post-marketing studies and plans to launch such a study ahead of filing?
Thank you, Kristen. We have previously discussed with the FDA the fact that changes from baseline in CSF and FL levels may be supportive of evidence of therapeutic benefit. In this statistical analysis plan, there were no additional discussions on this. In our opinion, whatever was agreed with the FDA still holds. They would be of the same opinion. There's been no other discussion on any other endpoints, nor requested by the FDA to evaluate those to support our submission. In terms of post-marketing or confirmatory trials, the FDA said they would be open to evaluating the data from this current study, whether based on the cutoff that we will be submitting of June 30 or after longer periods of observation, to evaluate whether this could serve the basis for potential full approval.
As such, any discussion for what it would take to have a full approval and what evidence will be needed to be generated will take place only after they have a chance to review those data, because if they are sufficient, then there will be no need to do another study. That will greatly inform what the next steps are. Our anticipation is that that discussion will happen at the PBLA meeting. We do not expect that to be slowing us getting approval because the agency would be much more open to have those discussions at that time and be informed with the data from our three-year cutoff.
Very helpful. Thank you.
Our next question comes from Ellie Merle with UBS.
Hey, guys. Thanks for taking the question. I think earlier in the call, you said you expect a rate of decline of 0.5 a year with Enroll-HD. Just to clarify, is that what you have already seen from the propensity score matched external control from that dataset or just what you would expect? Just further to that, I guess, have you done this analysis yet looking at the Enroll-HD external control using the propensity score matched analysis yet? Also, have you, I guess, done this analysis compared to your data with the 30-month follow-up yet? Thanks.
Thank you. Thank you, Ellie. We have not conducted any formal analysis comparing our efficacy to the natural history since we last did that and communicated to the FDA as part of the November 2024 meeting. That dataset included a June 30 cutoff where we had 12 patients on the high dose and 12 patients on the low dose that had 24 months of data. Having said that, the rate of decline that was observed recently by a competitor using Enroll-HD was fairly similar at two years to the rate of decline that we've seen at two years when we used TRACK-HD and PREDICT-HD with propensity score weighting as well. In our evaluating of the fit for purpose for the natural history for Enroll-HD, TRACK-HD, PREDICT-HD, we conduct propensity score weighted and propensity score matched analyses based on the baseline characteristics.
To be very clear, we're not comparing how our patients are compared to this. We just look what would be the rate of decline of a matched sample of Enroll-HD based on the baseline characteristics of our patients. In general, you get that same rate of decline of about 0.5 per year, whether you use propensity score matching or weighting with Enroll-HD or, for that matter, TRACK-HD and PREDICT-HD. That's why we believe that the propensity score methodology, especially with our competitors showing the same dataset with generally similar patient population, is a very robust method, and we expect the data to be very consistent across the board.
Understood. Just a quick follow-up. I know not a formal analysis yet, but have you looked at the 30-month data internally yet?
No. Look, this is an open-label study ongoing. We do look at the data to be able to manage safety. There are a small number of people who have access to these data for that purpose. We have not conducted a statistical analysis on this. We're just managing the study. We did not look at the 30-month data.
Understood. Thanks.
Our next question comes from Yanan Zhu with Wells Fargo Securities.
Great. Thanks for taking our questions and congrats on the update. I have a question about the sample size in the external control arm. Obviously, the larger the sample size, the smaller the error bar, and the better the p-value when compared with the treatment arm. I think I heard you mention for the matching, roughly one to 10, one to 20. Is that a rough kind of boundary for the end, or do you have flexibility in including an even greater number of matched patients given that Enroll-HD is a very large study? I'm sure you have no problem in including more patients. Thanks.
Yeah. Thanks. Very astute question. There are no black-and-white way of doing this. The best guidance that we could get is that you should try to match to the highest end to make sure that the quality of the match remains good enough. The way to do this is you calculate something called standardized mean differences, and there are criteria that you need to stay within a range to make sure that you have a good comparison. Because otherwise, if you loosen this, then you might have a higher number. You can have a precise estimate, but you have a precise estimate on a not well-matched group, and that is not really what you're looking for.
Without doing the analysis, I cannot give the exact number, but I would imagine with a database as big as Enroll-HD, we would be getting somewhere in the 10-30 range because you need to limit, again, those standardized mean differences to be close enough. I cannot give you the exact number.
Got it. Super helpful. Maybe if I can follow up with a question about the pre-BLA meeting, I think you mentioned at least one component or agenda for the meeting that is for the confirmatory trial requirement. Is there anything else regarding this filing itself that remains to be discussed at that meeting? If you can help us understand the need for that meeting, that would be super helpful. Thank you.
Yeah. Sure. I mean, pre-BLA meetings are usually very helpful for us to align with the agency about what we propose to submit. Is this what they want? Do they think that we need more data like this or like that, or we need to address a particular question? I think since we have an RMAT designation, I think this is the purpose, is to stay in closer contact with the FDA. And so far, they've been extremely helpful. I cannot tell you how pleased we are with our interactions with them repeatedly now. I expect that the pre-BLA has that purpose in mind, which is to look at the data that we're going to be submitting and then align with them as to whether this would be, I guess, meeting their requirements so that they can accept the BLA submission.
I view that as very positive and collaborative as it has happened so far.
Very helpful. Thanks for all the color and congrats again.
Sure. Thank you.
Our next question comes from Lydia Erdman with Goldman Sachs.
Hi. This is actually Lydia on for Salvine Richter. Thanks so much for taking our question and congrats on the update. Could you just remind us whether the third-quarter update will include both high and low-dose patients given your filing on only high-dose patients? Could you just speak to the potential ex-U.S. strategy? Thanks so much.
Yep. Our plan for the third Q is to present the top-line data based on the updated SAP that we would have filed with the FDA. With regard to the ex-U.S., we are engaging with the EMA with discussions as to what the next steps would be like. I have to admit that we prioritize the FDA at this point because things moved forward at a bit faster pace with RMAT. We're putting our resources there, but we continue to work with the EMA as well to try and figure out the way forward. I don't have more color to give you at this date, but perhaps later we can provide some more information.
Thanks so much. That's helpful.
Our next question comes from Oui with Mizuho.
Hi, guys. This is Charles on for Oui. In the upcoming update, can you guys confirm how many high-dose patients will be included? Also, if you guys will be including the low-dose patients in that update. Also, on the natural history cohort, what key changes have you guys made to the criteria for the matching? Are there any other besides the volumetric measurements? All right. Thank you.
Thanks, Charles. The cutoff will be the June 30th of this year. At that point, there will be 12 people on the high dose who would have completed three years and 12 people on the low dose who would have completed three years. In addition, all patients in the trial would have completed their two years. That will be the dataset that we will be analyzing data on. In terms of the top-line results, I believe we will be—yeah, it's difficult for me to say because we have not fully aligned yet internally on this. We have to be cognizant of the fact that we need to follow what the SAP says. We will be providing top-line results, which I believe will include both the high dose and the low dose.
We haven't yet fully aligned on this until after we submit the SAP and have a discussion internally on that. In terms of the natural history criteria and what has changed, actually, it's very similar to what we have done before with the exception of, as you said, the striatal volume. As I said, when we did the analysis with the only database where you can do that analysis, which is the one Track and Predict where you have a portion of the subjects whose striatal volume meets our criteria versus those who don't, when we use the propensity score variables, prognostic variables that we include in this and do those without including striatal volume or do those while adding striatal volume, the difference is essentially the change in cUHDRS after two years and three years are virtually identical.
This tells us that the model is actually very robust, and the prognostic factors that we use are obviating the need to have striatal volume. That is why I think that the results of the Enroll-HD look very similar to TRACK-HD and PREDICT-HD. I am really very confident. I mean, throughout this exercise, if I may give you some color personally, I felt very comfortable with how these propensity models operate because they are fairly robust, and they show very similar results if you apply them correctly and you match your sample patients to these. You end up with very similar results, which gives us very good confidence that we are actually comparing apples to apples in this case.
Great. Thanks so much for the color, and congrats, guys.
Sure.
I'm showing no further questions in queue at this time. I'd like to turn it all back to Matt Kapusta for closing remarks.
Thank you very much, operator, and everybody for attending the call. We're really excited about our path forward for accelerated approval, and we very much look forward to providing you additional updates in the near term. Thanks so much.
This concludes today's conference call. Thank you for participating. You may now disconnect.