Operator: Our next question comes from the line of Lidia Rachkova with Goldman Sachs. Your line is open.
Lidia Rachkova: Hi, this is Lidia on for Salveen. Thanks so much for taking our question and congrats on the progress. Just another on the end of Phase II meeting with the FDA for Angelman. What would you view as a positive outcome here? And could you just remind us how you plan to message to The Street post this meeting and what details you plan to disclose? Thanks so much.
Emil Kakkis: So, I think positive outcome is essentially finalize the endpoint palette of endpoints and statistical approach we’re taking, as well as what’s the ability to put that forth and get it a fileable for approval. That would be the idea. So, while we already have agreement on basic studies, I want to set some comfort on the duration as well as the dose dosing regimen and the endpoints. But I think the majority issue will be finalizing endpoints with them and that’s what people are most interested in. With regard to messaging, if we complete the meeting and have a very clear solution, we’ll put out a notice to the street on that fact. Sometimes the meeting can be pretty clear, but there’s still a couple of pieces to solve, in which case we’d finish that discussion until there’s a final agreement between FDA and us. And then we would only announce at that point in time.
Operator: Our next question comes from the line of Jack Allen with. Your line is open.
Jack Allen: Hi. Thanks so much for taking the question and congratulations to the team on the progress made over the course of the quarter. I know a few people have focused on this idea, but what are you thinking about as it relates to expectations for the annual fracture rate in the placebo on the Orbit? And I also wanted to ask, are you matching patients based on their seasonal enrollment in the study? I recently did some work with the KOL and they mentioned that seasonality can affect fracture rates as well. Any context you provide there would be very helpful.
Emil Kakkis: Yeah. Well, we don’t have any way to control the seasons, but if we did — so there’s a lot of things affect fracture rate. And one thing I’ll tell you is actually coming into a trial will increase the fracture rate simply coming into the trial because they’re transporting, getting out of cars. And in fact, in the Phase II study, 25% of the fracture occurred between screening in the beginning. It was like a lot of the fractures in their last year were actually part of the process coming to a trial. So, I would say to you there’s fractures and fractures that are harder to predict. What we have assumed right now, I think is about 0.67 fractures. The threshold to be in the study is one fracture per year, but we’re assuming and people ask me why we’d be assuming that.
Well, you don’t want to assume the middle ground of what you expect. You always assume on the boundary. You want to pick a safe boundary. Our expectation is it should be higher than 0.67. How much higher will be somewhat dependent on who’s enrolled, what happened to them, how far are they traveling, how many potential risks are there and the type of OI they have. But at the boundary of 0.67% and the 50% reduction, we have ample power for the study. And if the fracture rate is higher and the reduction is higher, you synergize those two, we could have substantially more power than required. So, I think we’re in a good place and what we’re positioning, but we’ve said 0.67 with the criteria for entry thought of having at least one a year.
Jack Allen: Got it. That’s great color. I guess just as it relates to seasonality component, I understand it’s a global study, the patient is going to be distributed and matched across the geographies?
Emil Kakkis: Yes, they will be. But remember, they’re always going to be in small, you randomize a little blocks. Right? So, within any period of time, the blocks are small enough that you should be creating evenness. We’ll also be stratifying based on fracture rate, right? So, the patients with high fracture, low fractures are even are even numbers between the two groups. I will also point out to you the way the trial enrolled, it actually enrolled the majority of the patient enrolled between November March, right, probably. So, they’re all really in a pretty tight window. I would say as synchronously enrolled as we’ve seen in terms of number of patients.
Eric Crombez: Yes. And the randomization should help with seasonality too, because you’re not random you’re not randomizing exactly one to one, but you are trying to keep that balance through randomization. So that could help there as well.
Operator: Our next question comes from the line of Luca Issi with RBC Capital. Your line is open.
Luca Issi: Great. Thanks so much for taking my question. Congrats on the progress. Maybe circling back on the prior questions and the first interim look for COSMIC, maybe just ask slightly differently. In a scenario where the Phase II data is replicated and the 57% reduction in fracture is actually reticulated in the Phase III, would that be sufficient to hit the staff by year end or do you need to see something better in order to hit the stats by year end? So, that’s question number one. And question number two on OI, can you just remind us the latest thinking on the competitive landscape? It looks like Amgen is actually running a trial Phase III versus bisphosphonate in 5 versus 17 years of age versus you’re obviously running a Phase III versus placebo in 5 to 25 years of age.
How should we reconcile that difference? Why is the FDA asking them to run a trial versus biphosphate in 5 and older versus your run rate trial versus placebo? Any thoughts there? Much appreciated. Thanks so much.
Emil Kakkis: Sure. Well, I’d reconcile that ours is better, but that would be the simple answer. Our trial will be 5 to 25 against placebo, but we’re also running a 2 to 7 which against bisphosphonate. So, we can you’ll be able to look at both sides of the story. But I feel confident that we’re in good position. The data that Amgen put out in BMD, at six months was about half what we achieved. That was at their highest dose that they tested in their dosing study. So right now, our data will look stronger than theirs, just based on that. So, so far we’re not right now we’re not concerned. With regard to the COSMIC, 60% is one of the factors. The real other important factor is how many fractures really are going. For example, if it was 1.5 fracture that would greatly help the ability in the control group to hit the endpoint.
