Tolga Tanguler: Yes. I mean, as Pushkal indicated, these analytical enhancements obviously makes us very confident and HELIOS-B visibility to show headed benefit on vutrisiran on top of TAP as well as obviously demonstrating the value of vutrisiran in a pure placebo. Now HELIOS-B really empowers us to position AMVUTTRA in a very unique way, both in first line utilization as well as on the switch with the tafamidis until eplontersen comes into market. Couple of key, I think attributes that we really need to highlight is the rapid knockdown and sustained knockdown of disease closing protein is very unique to AMVUTTRA. Along with clear outcomes benefit in total population as well as in mono, halting the decline in functional capacity and quality of life, demonstrated years of safety, which we zhave already established with our polyneuropathy indication, attractively sub-quarterly dosing and also limited co-pay burden in patients.
These are really going to be unique for AMVUTTRA, which we believe is going to position us a year before potentially even plan coming into the marketplace.
Yvonne Greenstreet: Yes. No, that’s great. And just to add that this is in the context of market that is growing really rapidly. And a market where we know that patients who are on current treatments continue to progress. So, with the profile that Tolga has described, we think we are in a really good position to drive broad commercial uptick of AMVUTTRA and obviously assuming positive results from HELIOS-B and approval. And both in first line, as Tolga described, but also switch from stabilized as we have shown how AMVUTTRA has led to a significant switch in the polyneuropathy market. And we anticipate we will see the same in cardiomyopathy as well with positive data. So, I think the changes that we have made, I think continue to support our confidence in the profile of AMVUTTRA and the potential that will be delivered in the cardiomyopathy market. Next question please.
Operator: Thank you. [Operator Instructions] Our next question comes from the line of David Lebowitz from Citi.
David Lebowitz: Thank you very much for taking my question. In terms of the primary readout, I know historically, you have released p-values as part of the update, will you be sticking to that plan, or is there additional data points you might be able to offer in the top line to allow for some level of differentiation between AMVUTTRA and the other therapies? And just kind of attached to that, when you look – since you are targeting really the front line here with your new analysis plan, what do you actually need in your mind to achieve in the study to be able to unseat tafamidis in the front line? I mean given that the trials are quite different, and it’s not necessarily going to be able to be easy to compare on a head-to-head basis. Thank you.
Yvonne Greenstreet: Yes. And just briefly, first question. Look, we will do what we normally do, and we will share p-values on the primary endpoints and key secondary endpoints as well as some qualitative assessment on safety. We will also present information on subgroups such as the tafamidis subgroups. So, I hope that answers that question for you. Tolga, if you could just very briefly respond to I mean take the commercial question.
Tolga Tanguler: Right. Look, we have extensive research that such as physicians believe 75% of their patients on a stabilizer continue to progress or experience inadequate treatment, which indicates to us that there is a significant remaining unmet need and a sizable potential to switch to AMVUTTRA and particularly prior to the tafamidis LOE, when payers are implementing already restrictions on combo use. And as Yvonne indicated, we have actually already that great experience starting with ONPATTRO first, and now with AMVUTTRA in ex-U.S. markets, where we actually compete with great data.
Yvonne Greenstreet: Great. Next question, please.
Operator: Thank you. [Operator Instructions] Our next question comes from the line of Jessica Fye from JPMorgan.
Jessica Fye: Hey. Good morning. Thanks for taking my question. Another one on HELIOS-B. Recognizing that the comparison is going to be versus placebo, what do you want to see in terms of how the event rate in the monotherapy AMVUTTRA patients looks relative to the monotherapy tafamidis patients?
Pushkal Garg: Yes. Jessica, thanks for the question. Look, I think it’s important to note this was not a head-to-head study looking at AMVUTTRA versus tafamidis. This is a study looking at AMVUTTRA or patisiran versus placebo where a proportion of the patients, 40% are on background tafamidis. And so really, the comparisons are AMVUTTRA placebo in those two situations. And as we have said, the primary analysis will be looking at this in the two populations, the blended population of overall as well as the monotherapy population.
Christine Lindenboom: Thanks for your question, Jessica. Next question.
Operator: Thank you. [Operator Instructions] Our next question comes from the line of Luca Issi from RBC Capital.
Luca Issi: Great. Thank you so much for – yes, thank you so much for taking my questions. Pushkal actually, if I may, circling back on a prior question, maybe ask a little more directly – is this informed by blinded event rates tracking below your expectation? And then maybe separately, is this considered a formal protocol amendment? And if so, will you incur any statistical penalties for changing the trial so late in the game? Any color there I much appreciate it. Thanks so much.
Pushkal Garg: Yes. Luca, let me take your second point first. There is no change to the operational conduct of the study. This was just a change in the statistical analysis plan. And we outlined in the slides really how the statistics around the primary endpoints are going to be analyzed. So, there is no statistical penalty for that at all. It’s just a change to the analytic plan that we have talked about, so no, not at all. And with regard to the first question, I think as trying to highlight the changes are really driven by what we have seen with APOLLO-B over 2-plus years. And the patterns that we are seeing there and our heightened confidence in terms of the impact of this class of medicines on this disease and what we can do to further optimize the study and set it up well for a strong and competitive label.
Of course, we have, as we have said before, have teams that are looking at the blinded data primarily to ensure excellent study conduct and execution, make sure the right patients are enrolled, make sure that the data are clean, make sure that we have got a complete capture of all the events, etcetera. And of course, they are looking at event rates, etcetera. But we are not going to be sharing dribs and drabs the data, and that’s not the driver here. Those types of events rates are extremely variable – subject to a lot of variability and interpretation. If I told you we had a very high event rate, you might say, well, that’s because that’s great. The placebo event patients are accruing events or you might say, wow, the drug is not working, or conversely, if we have a low event rate that might indicate that, oh, we don’t – we haven’t enrolled the right patients or maybe the drug is working remarkably well.
So, the primary drivers here are what we understand about science, biology and prior precedent from clinical medicine and clinical trials. And that’s the driver.
Akshay Vaishnaw: Let me just add, Pushkal. I think we will go to stand back a little bit. It’s obviously in Alnylam’s interest for patients and for everybody concerned to show definitive outcome for vutrisiran. If there had been mass panic at Alnylam, that the study design is wrong or too small or too short, there are many changes we could have made, and we could have made them well in advance. We have reiterated our confidence over and over again in the study, which was outlined today, deep insights from APOLLO-B, understanding the landscape. And what you see today is a three-month extension for the last patient giving a reasonable amount of additional data, just further enhance the robustness of what we are going to share with the world come June, July.
So, I think it’s well worth it. It reiterates our confidence in this study. And we haven’t fundamentally changed the design to a 1,500 patients or 2,000 patients study for 5 years. If we were panicked, you would have seen those things some time ago. Others have done what they have done. You have seen what we have done. And on the backdrop of the scientific edits we have built with the TTR mechanism in APOLLO, in APOLLO-B, I think we should have the confidence.
Christine Lindenboom: Thanks Akshay. Great. Next question.
Operator: Thank you. [Operator Instructions] Our next question comes from the line of Salveen Richter from Goldman Sachs.
Salveen Richter: Good afternoon. Thanks for taking my question. How much of a differential does extending the duration by three months provide instead of conducting the primary analysis at 36 months for all patients? And I am asking this in the context of recently announced studies in the field that are flexible up to 48 months or based on events, so just any clarity there. And then secondly, does the monotherapy analysis heighten the need to show significance on all-cause mortality alone just given task on label benefit for frontline use?
Yvonne Greenstreet: Pushkal, are you going to take this?
Pushkal Garg: Yes, absolutely. So, Salveen, look, I think what we have done here is we think meaningfully add to the duration of the study or the experience in the study in the tail end. And what we have done is actually for patients who are on the back end of the study, which is where the most – the greatest events accrue in the placebo arm and where you see the cause [ph] diverge, we have added exposure. It turns out that 60% of patients will actually have additional exposure in the study. And about a third of those, 20% more will actually complete all the way up to 36 months, which is when patients roll over into open-label extension. And so we really – and we think that, that critical addition, frankly, becomes a no-brainer for us, and it’s an important way to further add to study power.
So, that’s why that was done. And again, based on all the trends we have seen in APOLLO-B, which – where we start to see separation as we have highlighted much, much earlier, we – it’s just – we think this is a great enhancement that we were able to institute in the study. With regard to your question around monotherapy and all-cause mortality, look, I think it’s really important to just remember that in cardiovascular disease, we have about 40 years or 50 years of doing outcome studies and they typically focus on MACE type of endpoints, which include death and hospitalization. And the reason that, that’s been the focus and accepted by regulators and by the clinical community is because, in general, those events all go hand-in-hand.
Hospitalization events, predict mortality and doing mortality alone studies typically are – tend to be inefficient. They are too large and too long, and we need to get therapies to patients. So, we have designed a study that is focused on death and hospitalization, and we expect to show a positive result in that study. As well as we will of course, have the breakdown of events under those two, and we expect them to go in a consistent manner, which is what you would expect to see based on the biology and precedent in almost every other cardiovascular outcomes trial that’s been done.
Christine Lindenboom: Next question.
Operator: Thank you. [Operator Instructions] Our next question comes from the line of Gena Wang from Barclays.
Gena Wang: Thank you for taking my questions. I have two very quick questions. One is for the 60% monotherapy subgroup. Will your stats analysis or assumption, do you assume most of the tafamidis droppings will be in the placebo arm? And my second question, just wanted to double check my math is correct. And that’s based on the Slide 17, you said 60% of the patients remaining on study will have a greater follow-up. 20% more patients will have follow-up to full 36 months. , my calculation will be 40% plus 20% that equals 60% of the patient that will reach for 36 months? Just want to make sure that my math is correct.
Pushkal Garg: Yes. So, Gena, in terms of your questions, the – as we have said, our TAP drop-in rates are lower than we expected. Obviously, when we designed the study to, we are very encouraged by that. That represents another tailwind that supports the success in the powering of the study. And so I can’t get into any more specifics other than that, but to tell you that that’s – we are encouraged by those data. In terms of the additional follow-up, maybe what I can clarify is those are changes relative to what the study looked like when it was a 30-month to 36-month follow-up study. And so what we are seeing is – and of course, what we are focusing on is patients who remain on study. Throughout the study, we have had patients, for example, who have passed away because of their disease, etcetera.
And so what we are saying is that in the patients who remain on study, approximately 60% of them will have some extension of their follow-up in the study and roughly a third of those or 20% additional will get to the full – the full 36 months. So, I hope that clarifies.
