Good day, and welcome to the BridgeBio Pharma conference call to discuss top-line results from the phase III ATTRibute-CM study. At this time, all participants are in listen-only mode. After the speaker's presentation, there'll be a question and answer session. To ask a question during the session, you need to press star then one on your touchtone telephone. If anyone requires assistance during the conference, please press star then zero to reach an operator. As a reminder, this call is being recorded. I'll now turn the call over to Neil Kumar, Founder and CEO of BridgeBio Pharma. You may begin.
Thank you, operator, and thank you all for the time. I'm sorry I don't have better news to share with everyone today. Part A of our ATTRibute-CM trial did not meet its primary endpoint. Although the drug, as we'll discuss, seemed to have performed as we would have hoped, the placebo arm of the trial, especially on six-minute walk test, simply did not decline as compared with historical clinical trials or the natural history studies we reviewed. There was no real ability for our drug to show any signal against the measured baseline in the study to date. Before I continue, I'd like to acknowledge the disappointment many of you are feeling right now. For the patients and physicians we serve and for the investors we seek to perform for, I'm hurting, as is this team today as well. I'll break my comments up into two categories.
Number one, the search for answers regarding the seemingly puzzling finding regarding six-minute walk. Number two, the case for continuing this trial, where we'll explore the drug's effect on all other parameters excepting six-minute walk, which looked very positive to our eyes, to the trial steering committee's eye, and to the DSMB that reviewed the unblinded data and recommended that we keep the trial going. I'm gonna refer to slide numbers as we move through this deck for those of you following along with the documents. We'll start on slide 3. Slide 3 lays out the disappointing data related to the six-minute walk test on acoramidis. Patients declined around minus nine meters at mean or minus five at median over 12 months. On placebo, those respective numbers were minus seven and minus six meters.
What's remarkable, at least to me, is that the placebo performed almost 70%+ better than patients did on the drug arm of the ATTR-ACT study. We would have needed something like a 15 to 20 meter plus benefit or so to meet a P value given these data. Moving to slide 4, we present the context for this wildly divergent placebo arm. As you can see, the placebo of our trial closely mirrors historical healthy age-matched adult volunteer declines. The very best this company has seen in terms of decline for ATTR-CM patients on placebo over 12 months for a six-minute walk is a little under -40 meters in all of the studies that we've reviewed. You can see the major studies pointed out here on slide 4.
Turning to slide 5, we start to think about what really accounts for this deviation in placebo performance. Myriad subpopulation analyses present themselves in the face of such a surprising result. We don't have time to move through all of these. I'm sure we can move through some of them in Q&A. So far, we've found no answers. Here's one snapshot that further reinforces the strangeness of the six-minute walk result. Even for Class III heart failure patients, as you can see here, there's barely a decline in mean six-minute walk distance at 12 months. When we search elsewhere, as you can see it on slide 6, easy answers are not to be found. We enrolled a very similar cohort as compared with ATTR-ACT, as we've talked about before.
The mean six-minute walk baselines were essentially on top of each other at 360 and 352. The percent of Class II and Class III patients in each trial were 89% and 92%. We observed a slight shift to Class II patients, but this effect does not account for the discrepant result that we'll touch on later. In fact, just the opposite. We did have fewer variant patients where we did observe a minus two-meter change as opposed to minus 40 in placebo. But even modeling a 25% variant contribution to our trial, we still miss our primary endpoint handily. As discussed, we had more ex-U.S. patients than U.S. patients, but we did not see a difference in effect there when reviewing the forest plots. Turning to the next slide and drilling into our trial itself, we also see that the study was relatively well balanced.
A slight imbalance in Class III patients on treatment does not account for the lack of effect seen here either. Moving to slide 8, to summarize and expand on some of the points I've made thus far, the lack of benefit on six-minute walk and our placebo outperformance are not easily captured by the proportion of Class II versus Class III patients in our trial, U.S. versus ex-U.S. patients in our trial, or wild type versus variant participants in our trial. We're exploring quite a few current hypotheses as to why we might have seen this type of placebo response. Coupled with expert input on six-minute walk test, current hypotheses include context and training bias as well as an evolution in standard of care and diagnostic approach.
The first category suggests that because patients, one, new small molecule stabilizers work, two, had a 2/3 chance of being on a small molecule stabilizer that was active in our trial since we were randomized two to one, three, wanted to believe that they were getting better, and four, were engaged in a rigorous testing infrastructure that prompted the best performance that they outperformed even on placebo over this timeframe. The second category suggests that patients are simply, despite the class and BNP levels, healthier on ATTR-ACT, healthier than they were on ATTR-ACT, and that the deterioration associated with the disease is likely to come later in this trial. Okay, I'd like to turn to the remainder of the deck to the case for believing in acoramidis.
Starting on slide 9, and as we'll walk through, on almost every other measure resolved in this trial, we see promise for this drug. The enthusiasm has been mirrored by the steering committee of our trial and supported by the independent data monitoring committee. As you can see on slide 9, acoramidis essentially flatlined BNP levels, while placebo increased about 25% on the study. On slide 10, on quality of life, we see that the drug had a nominal P value. Although our expectation going in was that this endpoint and this questionnaire was gonna be the most sensitive to variance coming from the COVID era. Slide 11 shows that biochemically, the drug was performing the way we wanted it to perform.
Seems to be having the desired effect immediately and with immediate and sustained elevation of serum TTR in the 45% range, especially impressive considering the greater wild type patient population in the trial. Finally, on slide 12, we find a couple of points of promise in the safety tables. First, it should be said that to protect the integrity of Part B, our access to AE data for Part A excludes AEs leading to CV hospitalization, excepting events with an outcome of death. Furthermore, AEs leading to death account for a fraction, about 50% if you look at ATTR-ACT at 30 months, of total death and are collected to ensure the safety of our population. Looking at the event rate first, about 32 deaths, which equates to about 5% approximately mortality rate.
We see this tracks closely with ATTR-ACT in terms of event rate, which had about a 10% total mortality at this time, 12 months in. We might assume that the contribution to this mortality from AEs is about 5%, given their 1:1 split in their trial at 30 months. Further, looking at the numbers in the table, based on a 2:1 randomization, we can calculate a 27% reduction in AE-driven mortality, which is encouraging. Slide 13 summarizes our findings. No improvement on six-minute walk. All other measures positive. DSMB has recommended that we proceed after an unblinded review of the data. Slide 14 takes us outside of the trial, where BridgeBio is set to deliver on the promise not only of Part B, but other efforts with the current cash on hand.
Although we've experienced a very real setback today, we have the runway into 2024 to build back better. In the first half of 2023, we anticipate ADH1 and acoramidis phase III data, plus the realization in 2022 of multiple proof of concept events, including infigratinib for achondroplasia, our programs in LGMD2I, dystrophic epidermolysis bullosa, and congenital adrenal hyperplasia. Finally, on slide 16, although today did not meet our expectations nor yours, what does and always will continue to meet our expectation is the courage and dedication of the physicians and patients that are on our trial and in the ATTR-CM community. We hope that together we can play a role in furnishing a better future. With that, I'll turn it over to the operator and take any and all questions.
As a remainder to ask a question please press star then one. If your question has been answered and you want to leave the queue, please press the pound key. Our first question comes from Salim Syed with Mizuho. Your line is open.
Great. Good morning, guys. Sorry to hear the news. Neil, thanks for all the transparency, and I thought it was super helpful. Thank you. I guess, you know, if we kinda zoom forward here, you know, I appreciate the analysis on why we didn't see a difference on six-minute walk. I guess we'll wait for more color there. If we are looking towards the case here now for mortality benefit, I think you had noted in your prepared remarks, and I think it's also in the press release, that there was about 5% in each arm adverse event to death. Is that similar to the overall mortality as well, if that's a number you guys have?
I guess since these—I mean, this does seem to be tracking with how we would think wild type patients are doing. But I guess these look very similar. I know it's 12 months, but what are—I mean, how should we be thinking about the risk here for mortality given you know these are tracking similar. We are seeing more wild type. You know, is 30 months long enough here? Just things around that. Or do you think you need to go beyond 30 months in order to have something beyond tafamidis here when we start to compare the two? Thank you.
Yeah, good question, Salim. Thanks for your comments. I guess what I'll say at the outset is we're actually blind. I mean, since, you know, the primary endpoint here on Part B is or includes mortality, we're blinded to it and are maintaining a straight blind around that. We don't know what the total rate looks like. That's why we had the DSMB have a look. All we can see is AE-driven mortality, and that, as I've mentioned in ATTR-ACT, was about half of overall. If we're seeing 5% or so mortality rates right now in the AE table, it stands to reason that we're tracking somewhere in that what ATTR-ACT saw to date, right? That 10% or so after 12 months.
The real question is obviously, you know, the amount of mortality increase in ATTR-ACT by 30 months. That event rate needs to increase analogously in our trial, so that, you know, we have a baseline against which to show signal. There's no reason to believe that it's not so far. I mean, you know, one thing that's obviously that we've looked at is, you know, if you were just looking at the blinded six-minute walk data, you would've seen about 25% of the overall signal at 12 months. But if you look at many of the other parameters here, KCCQ, BNP mortality and what we can see, et cetera. You're a little closer. You're still not, you know, fully at ATTR-ACT levels of deterioration.
I guess the prediction would be that 30 months would be a long enough time to capture the you know the patient baseline going down. But it's hard for me to predict that right now, to be honest.
If I can follow up.
The best I can do. Yeah, I guess the best. Just to elaborate on that, the best I can do is looking at natural history and ATTR-ACT. Obviously, we've sampled a slightly different patient population here. You know, how different that is? Is it gonna be just healthy for a long period of time? If that's true because of some standard of care change or, you know, some way that we're relabeling what a Class II or Class III patient looks like, then, you know, then all bets are off.
If I could follow up. Thanks, Neil. With the tafamidis drop-in, then what sort of looks is the DSMB taking in terms of like is futility analysis even something we should be wondering about now, like, you know, every three months, like, there's an update, you know, from the DSMB? Or how long will this go for, you know? What sort of looks are they taking I guess, now that we have tafamidis drop-in.
Yeah.
The risk of the trial has increased, right?
There's about 3% tafamidis drop-in. Just as a reminder, there was no tafamidis drop-in on Part A. But it's a good question. The DSMB is reviewing this on an ongoing basis, obviously. But, you know, the overall ability to look and say, is the event rate high enough to discriminate on mortality? You know, that's gonna come very close to the end of the trial because these trials enroll like a hockey stick, and so we're gonna see a lot of patients coming in right toward the end. As you remember from the ATTR-ACT study, you saw the really, you know, the statistically significant separation. You started to see separation after 18 months, and you started to see large separation in those latter months. I would expect that.
I mean, first of all, there's no formal futility analysis built in. Secondly, that event rate's gonna pick up pretty close toward the end of the trial. Yeah, the DSMB is reviewing the data on an ongoing basis, and that's why we did ask them to take an unblinded look at the data just to make sure that it's still reasonable to continue this trial.
Got it. Thanks so much. Thanks so much, guys.
Yeah, thanks.
Our next question comes from Anupam Rama with JP Morgan. Your line is open.
Hey, guys. Thanks so much for taking a question, and sorry about the disappointing outcome. What additional analyses are you guys thinking about doing here on six-minute walk distance to better understand what happened here? Also, yeah, I guess that's my first question.
Yeah, it's a good question, Anupam. I mean, we're gonna continue to refine. I mean, these data are very recent, so we'll continue to refine our analyses around any hypothesis that we might have around subpopulation performance. You know, I think the critical thing will be looking site by site to understand whether or not we can learn anything at that level of detail. There's not a whole lot of other hypotheses that we have right now. Obviously, we'll be digging into some of the context and training bias questions, but that is not easily resolvable from our data set alone. We'll have to look at some external data as well.
You know, the other thing, we'll just be trying to do a little bit more work on who these patients are and how standard of care might have changed over the course since ATTR-ACT started to this trial. You know, we can see some of that right now, but not a tremendous amount, so we'll just have to dig in and do some more qualitative research. Certainly, there's nothing quantitative right now from the data associated with the patient populations that jumps out.
Because of the sort of COVID-19 pandemic, were there any trial conduct issues that could have, you know, resulted in something like this?
No, it's a great question. We didn't see any trial conduct issues. In fact, I think the trial was well conducted to date. I don't think that's the explanation, nor is it immediately apparent to me that COVID, although you know it obviously does have an effect on some of the other issues that we're measuring in the trial, questionnaire and hospitalization. It's really unclear as to what type of effect it has on six-minute walk. Honestly, there aren't enough studies that have read out in which we're using six-minute walk throughout the era of COVID to understand that.
Thanks so much for taking our questions.
Yeah, thanks.
Our next question comes from Paul Choi with Goldman Sachs. Your line is open.
Hi. Thank you. Good morning, and sorry for the disappointing news. My first question, Neil and team, is just on you know, how you're thinking about your next step of regulatory discussions and interactions, given that you missed here on the primary endpoint. Can you maybe just walk us through the path in terms of next steps, in terms of your discussions with the regulators? Then secondly, you know, how you would you know, think about your filing strategy or regulatory strategy with the 30-month data endpoint coming up in another year or so?
Yeah. Thanks, Paul. Appreciate the question. In terms of regulatory interactions in the near term, obviously there's nothing to file here, so there's nothing specific to do with the agency or European authorities in the near term. You know, we have checked in with all of the relevant parties. Our goal here is, as I discussed, to finish the trial and against the same endpoints of CV hospitalization and mortality ultimately file on the basis of that data, should that data be positive at the 30-month endpoint, which would, you know, be about 15 months from now.
Okay, great. As a follow-up, as you think about the 30-month data here, my second question to you is, with regard to the you know potential continuation for compounding factors here, how are you thinking about any you know other trial review or you know execution you know procedures or checks or quality controls just to make sure to what degree you can check on this these quality control factors can be implemented to hopefully drive a positive outcome?
Yeah. I mean, I think quality control to me lies in two buckets. Number one is actual trial conduct. As I mentioned, we looked at a lot of that, and I think we feel pretty comfortable that the trial's being conducted at a high level of fidelity. The second is obviously the ongoing event rate, 'cause you need to have a baseline against which you can resolve signal. You know, that I discussed with Salim's question as well, which is that the best we have is effectively allowing our DMC to have a look on an ongoing basis and to understand that the blended event rates are obviously the blinded event rates continue to track close to expected over time.
Okay. Thanks for taking my questions.
Yeah. Thanks, Paul.
Our next question comes from Mani Foroohar with Leerink Partners. Your line is open.
Yes, thanks for the question. I'd like to add my condolences on a tough update to everybody else's. I guess I have a little bit of a different trial conduct question. There's nothing you can do about the enrollment at this point, et cetera. The bullet's kind of out of the gun in that regard. One of the questions I've already gotten a few emails from clients about is, does this result potentially increase the risk of patient dropout, increase tafamidis drop-in, and the things that you and the rest of the Bridge team, or legacy Eidos team can do, to try and keep that at a reasonable minimum?
Yeah, great question. Obviously, you know, that when we first got the result, you know, since kind of step one was trying to understand for ourselves, did we still believe in this drug and its promise against the hard endpoints of Part B? Once we answered that question, the related next question was, do the physicians that are conducting the trial believe that 'cause they're gonna be a big part of keeping the patients on the trial? We've had a couple of PI calls since we got the data, and they've all been resoundingly positive, to be honest. People can check that out themselves. From our co-chairs, Dane and Julian, all the way down, we've heard a lot of enthusiasm for finishing this trial.
That's really what's gonna drive people staying on trial. At the end of the day, you know, the median patient's about 20 months in to this trial right now. Access to tafamidis has been challenging for a great many of our patients, which I think is why we see only a 3% dropout on Part B to date. You know, I think from that standpoint, lots of enthusiasm for finishing this experiment, at least from the physicians. We'll be continuing to monitor the dropout rate over time here. Can report back to people on it.
All right. Thanks. I know you guys have a bunch of other analysts on the call. I'll just hop in the queue.
Thanks.
Our next question comes from Ellie Merle with UBS. Your line is open.
Thank you, guys. Thanks for taking the question. Can you just elaborate a bit on some of the kind of, like, working hypotheses for, I guess, why the placebo arm performed the way it did? I mean, you mentioned a couple of them in prepared remarks like the context bias, training bias, some of the evolution in the diagnosis. Maybe just if you could sort of elaborate on sort of what you know so far and what could have potentially happened, because obviously some of these could impact mortality data at 30 months and some might not have an effect, such as a training bias. Just kind of elaborate on what we know and I guess what we might learn in the coming months, as you have more time with the data. Thanks.
Yeah. Great question. Thanks for that. Yeah. I would say that there's kind of two categories of hypotheses. The first relates specifically to the six-minute walk test, and that's training and context bias. I mean, very simply, you know, because this wasn't a primary endpoint for Pfizer, they probably weren't super focused on this test or not quite as focused as we were. In the context where patients knew small molecule stabilizers were working, they wanna be getting better, and they had a you know 2/3 chance of being on drug, and we made it a big deal.
I mean, this test was a big deal, and we used a lot of rigor for that 12-month visit. There could have been just sort of, you know, an added performance effort associated with the tests that we haven't seen or we didn't see in ATTR-ACT. That's one ongoing hypothesis that we're trying to study. The second is obviously it would affect mortality or could potentially affect mortality, which is that this is simply a different population of patients, given the fact that we're diagnosing using the technetium scan and, you know, that's different obviously than Pfizer.
Given the fact that standard of care might have changed, I mean, it could be that some of the concomitant meds are slightly different now that we're picking these patients up in a way that allows us to care for them more effectively. You know, that's not immediately apparent from, as I said, the quantitative descriptors, things like, you know, class of heart failure and BNP levels, et cetera. That could be the case. If that is the case, then it could well affect mortality rates going forward. We will continue to do research on that.
Got it. Maybe just if you could elaborate, I guess, on that NT-proBNP. I mean, just, you know, you saw some recruitments there, and I mean, I guess what we know so far from other studies and what this could mean for mortality, if at all.
Yeah. For the BNP, we saw, I think, you know, basically a flat lining on drug versus about a 24%-25% increase on placebo. Obviously that, you know, to our eye looks like a pretty good performance as compared to what's been seen before in this space. The, you know, the ability to use BNP as a predictor for mortality is not, quite honestly, well established in this space. It's a reasonable univariate predictor, as is here in TTR. That gives us heart. But yeah, that's the best I could say. It's based on natural history studies, you know, natural history studies and others. It's a reasonable predictor of mortality.
All right. Thanks for the color.
Yep. Thanks.
Our next question comes from Dane Leone with Raymond James. Your line is open.
Hi. Thank you for taking the questions and hosting the call to discuss the results. I guess for me, you know, the key question here is probably the two-part body problem. You know, the first part of this is just, you know, disappointment from investor expectations on a 12-month endpoint, which is, you know, it is what it is. I think the more important question now is from the drug development perspective. You know, one thing that stands out to me looking at the data today that we didn't have before is this looks like a wildly different patient baseline population than what was in ATTR-ACT. You know, at the end of the day, you know, this is fixed in terms of the patients you've enrolled.
When we get to month 30, I guess, how do you think about dissecting that data to eventually making a commercial argument, you know, where this drug could fit into the treatment continuum within the context of tafamidis? I guess maybe a pointed question on that. Were you surprised in terms of the low rate of variant patient enrollment into this study, especially given you guys were more anchored ex-U.S. to try and avoid overlap with obviously tafamidis utilization within the U.S.? Thank you.
Yeah, great question, Dane. Thanks. Dane, I'll start with the variant. I wasn't particularly surprised by that, just given that I think, I mean, ex-U.S. wouldn't necessarily bias you toward more, probably less, variants, especially the geographies we were trialing in. Maybe you're thinking about polyneuropathy as being having a founder effect in some of the European countries where we were open. On the cardiomyopathy side, I think the slightly lower variant rate made sense given the distribution of sites that we had. I think you asked a good question on patient population. It is fixed. That's why I mentioned earlier that we were sort of looking at some of the other variables to try to understand how just sort of different this is from the ATTR-ACT study.
It's certainly very different in terms of the six-minute walk performance. It appears to be less different with respect to things like KCCQ decline, mortality, BNP and the like. I think we feel still good about the general evolution of the patient population's performance and our ability to resolve signal within it. You know, commercially, I guess the only comment I would make is, we'll have to see. We'll put all the data together when we get there. This is reflective of the patients that are being diagnosed today with ATTR-CM, which it does appear is slightly different than the baseline of patients that were first enrolled in the ATTR-ACT study.
That does reflect an evolution of standard of care and diagnosis.
Thank you.
Our next question comes from Greg Harrison with Bank of America. Your line is open.
Good morning, and thanks for taking the question. What impact, if any, do these results have on your other programs? I know you're well capitalized, but.
Should investors anticipate any reprioritization within your pipeline to either preserve capital or to accelerate other programs that could provide an early proof of concept?
Yeah, it's a great question. You know, we remain focused on the diversified prosecution of our pipeline, certainly, you know, with an eye toward the four key value drivers. Outside of this, we've got ADH1, where we have a, you know, phase II meeting coming in January this year, and then hopefully initiating it, our phase III shortly after that. For infigratinib for hypochondroplasia, we should have data on our phase II sometime mid this year. For congenital adrenal hyperplasia, we should have proof of concept data late this year. All of those will continue to move forward. We haven't yet made any decisions on further prioritization within the pipeline.
Certainly we'll look to, you know, leanly prosecute the pipeline as we move forward and as we have in the past to make the most of the cash on the balance sheet right now. Yeah, like, no further decisions have been made.
Okay, thanks. Just one follow-up. Can you kind of set a hurdle or a bar as far as what do you think you would need to show on the mortality endpoint, you know, both for you know, potential approval and also to be competitive within the market?
Yeah. Well, great question. I think on mortality, what we'd be looking to do is a 15% relative risk reduction versus what Pfizer showed, which was taking 42% to 30% or so. That would be the bar again, would be outperformance versus tafamidis. You know, we continue to believe with serum TTR levels at 45%+ and a flat lining of BNP, that the drug's doing what we want it to do. If the path and mechanism of disease continues to be what it is, you know, that would be our expectation, and that I think would lead to optimal commercial performance in the marketplace.
Great. Thanks again.
Thank you.
Our next question comes from Ram Selvaraju with H.C. Wainwright. Your line is open.
Hi. Thanks very much for taking my questions. Just firstly, can you refresh our memories as to what you would have predicted the placebo six-minute walking distance rate of decline to have been if this study had mimicked other trials that you've obviously reported on before? The second question, also very quick, is from a regulatory perspective, have you already had discussions with or received feedback from regulators such that if in 15 months' time performance on these hard endpoints that you've discussed earlier is positive, there would be sort of a formal or semi-formal route to approval for this drug?
Yeah, maybe I'll address the second first. Yes is the quick answer. You know, if we show performance obviously against CV hospitalization and mortality, that would be a road to approval for this drug. The first question that you asked is around our expectations around six-minute walk decline over 12 months. We point that out in slide 4, I think, of our presentation. The ATTR-ACT cohort, which we were reasonably mimicking as discussed in my prepared comments, declined 56 meters over 12 months. You know, natural history studies that we've seen are in that -45 range or so.
I mean, you can go back and look at, and then there's an Alnylam placebo arm as well that was in that -40+ range as well with a reasonably similar patient population. Then there have been some IIT studies, all of which have reflected something between -40 and -50. Pretty much everything that we've reviewed as a company, certainly prior to this trial, suggested that -40 would be the best that patients would do, and we were expecting something based on our baseline characteristics in that -50+ range.
Just as a follow-up to that, I mean, you've talked about how, you know, there doesn't appear to have been an execution issue with this trial. I also do not think that. I'm no statistician, but it seems as though the difference between what was reported and what you would have predicted is so significant that this clearly doesn't appear to be a statistical analysis problem either.
Yeah.
Do you think at this juncture that it is possible to conclusively exclude any issues with data capture or data entry as it pertains specifically to this endpoint?
That's a good question. I think we feel pretty confident in our data capture here and the conduct of the trial. You know, we'll continue to do work on that. Maybe I'll ask Jonathan to.
Yeah, we had a very high percentage of people completing the 12-month visit, so not a lot of missing data. We had pre-agreed missing data imputation methodologies to account for missing data with the regulatory authorities. The result you see is pretty reliable.
The other thing I might mention is if you look at the standard deviations, they're similar across the two arms, about 60 meters on and off drug, and the distributions look reasonable. They're not wildly off in terms of the shape. So yeah, I don't think that there was. I don't believe as we look site by site that there'll be, you know, one or two sites that set this off or any outlier data set.
Yeah, maybe worth adding that we did have a core laboratory that reviewed everybody's six-minute walk course set up and execution methodology site by site and had to be certified and trained according to the standard methodology.
Thank you.
There are no further questions. I'd like to turn the call back over to Neil Kumar for any closing remarks.
Great. Well, thank you all for the time, and we look forward to being in touch with any and all who wanna be in touch with us over the next couple days to answer further questions. Thank you all for your support.
This concludes the program. You may now disconnect. Everyone, have a great day.