Leonid Timashev: Got it. Thanks. And then may be one on IGM-2644, obviously, there’s a few different bispecifics in multiple myeloma now, BCMA GPRC5D. How are you thinking about how IGM-2644 is going to play in the space and the advantages that you might have over some of the other offerings?
Fred Schwarzer: Maybe I’ll start with that and then let Chris take over. But we see IGM-2644 as pretty differential €“ at least the way we’re intending to develop it as hopefully quite differentiated from those other bispecifics. We would like to see this as a next generation CD38 molecule. And so we would like to assuming safety and efficacy. We’d like to randomize against dara as fast as we can in order to show that we can potentially work better than dara and some of those patients who may be seen dara previously and then maybe eventually moving up. So the focus here for IGM-2644 is a €“ hopefully a next generation CD38. Chris, you want to add to that?
Chris Takimoto: Yes. And it is a crowded space with bispecifics, but about 10 or 12 of those are all BCMA, CD3 bispecifics and then you have the BCMA CAR-T cells coming into the space. And I can tell you that, the fact that we’re not a BCMA bispecific is actually an important differentiating factor. There’s €“ obviously, there’s been reported cases of resistance to CAR T-cell therapy in multiple myeloma through lots of the BCMA antigen and things. And so it’s not necessarily clear, you’d want to use the BCMA targeting bispecific before you would use a CAR T-cell or that you could use it afterwards. So the fact, CD38 bispecifics, there are many fewer out there. There are a handful of other targets in multiple myelomas for bispecifics too, but it’s not anywhere near as crowded as BCMA.
So we think there’s a way to differentiate there. And then Fred has already outlined a major tenant to our strategy here, and that is to really think about this as potentially the best CD38 targeting agent in this class. So that’s really kind of driving our strategic thinking at this point.
Leonid Timashev: Got it. Makes a lot of sense. Thanks for the answers.
Operator: Thank you. And our last question is from Asthika Goonewardene with Truist. Your line is open.
Asthika Goonewardene: Hi, guys. Thanks for taking my questions. And I appreciate all the colors provided today. So Chris, I have a couple questions for you here. On your slide where you have the caspase-3 increase, what was the on-treatment €“ when was the on-treatment measurement made at which cycle, perhaps again, tell us that. And then do you expect a change in baseline to increase which subsequent cycles? And then related to that, do you had four patients that you profiled, the five patients had profiled, including four with PRs, and then one went on to curative surgery? What was the level of increase in caspase-3 that you noted in those profile patients? Then I got a couple of follow ups.
Chris Takimoto: Sure. Yes. Thanks for the questions. So just to be clear on our biomarker slide, what we’re doing this, so these are normalized data. So not surprisingly caspase-3 levels in the plasma can vary highly at baseline from our patients. So what we’ve done is taken the pre-treatment sample, normalize that to one and then show the relative change and actually the data that we’re showing you here. So we monitor the caspase levels during the first cycle, second cycle. And what we’re actually showing here is actually the maximum change that we see in the caspase-3 levels in patients who are on study. Now that could vary somewhat at different time points. So though, we do tend to see a very immediate rise in the caspase-3 levels with treatment. So it’s something that’s very consistent that we’re seeing across our patients. But there is some noise to the €“ in the timing of this, but in general it goes up in essentially all of the patients that are on treatment.
