Bask Gill explains how they report preliminary efficacy and safety data to users. They always state participant numbers (N), use color and opacity to show data robustness, and link everything back to published journal articles so users can verify the sources themselves.
Dimitri, do you want to come on? I saw you raise your hand.
Correct me if I'm wrong, but it sounds like you're reporting kind of preliminary efficacy numbers to your users. And I'm kind of worried, how do you think about how much of that is sort of noise versus true clinical numbers? And my second question is, how do you kind of handle this, you know, with the fact you have rival pharma companies that may be very much interested in this information, or you have investors that would really like to know if some clinical trial is starting to look good. How do you kind of think about those 2 things?
Yeah, really good questions. So the first thing I'll say is there's a bunch of ways we think about presenting data in a way that is just like honest and transparent. So always reporting participant numbers, right? How many, like, is this N of 6 or N of 60 in some of this stuff? And making clear what N means, because for lots of folks that doesn't mean anything. We're exploring different, different ways of communicating this. I think we could probably do a better job. But for example, you could imagine using color as a dimension or opacity as a dimension to make clear how like robust or, or actually like flimsy and novel this, this data is. So hey, it might be a higher bar, but if it's really low opacity or if it's a soft blue versus a bright purple, is that like a gauge users can, can, can tap into to understand how reliable that data is? And then we, we've also in some of our visuals presented confidence intervals. I don't think that's a great solution because I don't think people always understand them, but But, but we're trying things. And I think we have a habit of showing stuff to the folks who are consuming it and understanding when it's sort of missing the mark. We also always link out to the primary literature and try— yeah, we'll encourage folks who want to dive deeper to, to dig into that. As of right now, we don't have proprietary efficacy or safety data. We have sort of more usefully packaged safety and efficacy data. So everything we have lives in a journal article somewhere, can be referenced, and we've just pulled it out and like made it comprehensible to a typical person, or tried to. And what I would say is we do have pharma and investors who are sort of interested in some of this data. I think there's a lot of potential for data products in this space. And we view that opportunity through some of the lenses I just mentioned, which is that, is this going to be a quick sales cycle? Will it actually accelerate our time to get the recruitment contract that we're ultimately after? Really thoughtful questions though.
