Dr. Claire de la Calle

And so there are other techniques to do tissue-based testing that we could consider using in the future.

So, for example, artificial intelligence, you know, using digital pathology.

The testing that we have currently commercially available is also based on only one core, but it would

makes sense to just do every single core, I think.

Hopefully we can do that in the future.

Or maybe PTEN loss.

PTEN loss, I think, has been shown on multiple studies to be really a strong predictor of bad outcomes.

And immunohistochemistry on every single biopsy core certainly is a lot of work, but less than doing DNA or RNA extraction on every single core.

So that's also something we could consider in the future.

Yeah, so there are other RNA, DNA-based testing, such as the Oncotype or Prolaris.

And there haven't really been great, I don't think, head-to-head comparisons and study.

The results of these are very mixed.

And also, we're today talking about intermediate-risk patients.

And so a lot of the studies are based on all active surveillance patients, which the majority are low-risk patients.

And then for the AI, AI reads, yes, there is the multimodal artificial intelligence tool that Arterra provides that has been tested in other radiation therapy clinical trials, but not specifically in active surveillance.

So we...

definitely need to do more research in active surveillance cohorts.

And of course, there are a bunch of other AI companies that are currently trying to develop algorithms for active surveillance.

There's also companies that are looking into MRI reads.

We know that there can be big discrepancies between MRI reads, sometimes