Kabir Nath: So what I would say is when you’ve seen one sensor, you’ve seen one centre. So that’s part of the answer to that. And that’s one of the reasons why this is a lot of work as we build this. But I guess just on [Indiscernible], I mean we know that our job is to make sure that it is economically attractive to provide COMP60, and we had to understand how that compares to Spravato or TMS or whatever other interventions that these centres maybe deliver.
François Brisebois: Last one, in terms of your press release and something you had mentioned a publication recently. Can you just elaborate more on the significance of AI in this space?
Kabir Nath: Well, is obviously the top of everyone’s mind at the moment, we’ve looked and we use machine learning and we’re using large language models to try and understand the processes that go on both in preparing patients and also in integrating their experience after treatment. Our initial efforts of this suggests that certainly the session after treatment, we can look at the actual thing that take place between the therapists and the patient and make a pretty good estimate of whether people are going to be responders or non-responders subsequently. I mean, that’s something that is essentially confirming what our other measures tell us. So it’s not actually predictive in the sense that it precedes treatment, but we are looking in some detail whether it’s possible to do that and whether there are ways of really understanding patient experience, patient presentation using the kind of measures that emerge from these very complex models that can now be constructed.
I think there are other ways in which AI might contribute to training, and we’re also exploring those. And at some point next year, we’ll probably tell you a bit more about that because it’s quite interesting.
Operator: Our next question comes from Patrick Trucchio with H.C. Wainright.
Patrick Trucchio: I have a question about some of the dynamics that we’re seeing in the field. So as we begin to see these additional psychedelic compounds generate clinical data and depression anxiety. I’m wondering if you could provide some perspective on COMP 360 relative to these compounds? And what you see as advantages of your approach to COMP 360 treatment compared to others in the field?
Kabir Nath: So let me start, and I’m sure Guy will add as well. So first we are focused on generating and delivering the evidence for COMP 360. And just as a reminder, the Phase IIb we conducted remains by a significant way, the largest and most robust study yet done with any psychonomic compound with the potential exception of esketamine if you regard that study group is psychodetic. So I think our view is others have got to generate data on the same sort of scale and with the same sort of robustness before we can really start comparing across molecules or approaches. Again, as you know, our Phase III is designed not only to replicate but potentially enhance the benefits of COM360 with the repeat dose administration and also generate much more robust data around durability.
So very candidly, Patrick, I don’t think we’re at the stage of making comparisons across assets and so on. But if there’s a specific that you want to ask us to address, I’m sure Guy or I could take that.
Patrick Trucchio: I was just curious as there’s some of these second-generation compounds that have started to generate data. So with TMT or even with CYB 3 as we look ahead to perhaps larger studies with those compounds? How do you think about those relative to Comp360?
Kabir Nath: Well, I think it would be good to see them, Patrick. It would be good to see a proper study really, and we await those with great interest.
Patrick Trucchio: So then I guess just a follow-up question on the digital strategy. How do you envision digital being part of the go-to-market strategy with COM360 in depression? And is there an opportunity perhaps to partner with some of the emerging digital therapeutics companies in mental health care?
