Chris Twitty
Analyst · Citizens JMP. Your line is open.
Yeah. I think backing up just a half second and looking at the potency directly, that question I think is a fair one, and certainly a bias towards beta-resin-based recruitment in terms of a measure of potency. But if we look at the more classic super KNP-based readout, very similar potency, whether you’re a small molecule monlunabant or on the nimacimab. So from a potency perspective, very similar. You can look at our modeling data and that’s pretty clear there in terms of our IC50, IC90 values. I think where, in terms of translating DIO studies, and I think what Punit was alluding to, really the way to do this is in the same study if you want to have that sort of direct comparator in terms of understanding relative efficacy, it can be difficult by clinical trials to do cross-trial comparisons. It can be challenging and what we typically do to kind of get a soft comparison, if you will, is we use a benchmark where you dose at the same concentration, same dosing schema, and you can use something that’s fairly validated. In this case, we did use some semaglutide at a 10 nanomol per kg dose, and you can see that that sort of had a 5% to 10% weight loss over our dosing range and that is in line with other published research. I would argue more of a suboptimal dose of semaglutide, but if we look at that as a benchmark, we can see that our highest dose of nimacimab actually was significantly improved -- had a significant improvement relative to that semaglutide dose. So that’s one way of looking at it and sort of comparing to other therapeutics, benchmarking on semaglutide. But in the end, we really needed to look at that head-to-head comparison, which is something we’re interested in doing. We haven’t really given guidance on what that will be and when that will come out, but that is something that I think is of interest. But overall, we feel very comfortable with our efficacy profile, especially considering it’s the initial study, and I think we have a lot of room to improve the efficacy results, so we’re really digging into some of the key parameters to understand in this model what is the exposure, what are the kinetics of that exposure, and how do we achieve that inhibition as quick as possible. This is an IP dose that we use, but we’re exploring other routes to really get that inhibition happening quickly and really drive that efficacy down, so more room to optimize the model and drive even better weight loss.