Mm-hmm

... look at years of history of data.

And, you know, metadata has a discrete set of data that we, we access and, and use.

The industry has a much larger, uh, set of data that could be used, and there's a lot of initiatives out there to bring some of those together.

There's an Alzheimer's, uh, organization that's bringing all the Alzheimer's data together to be able to screen through that.

I think the, the lesson learned there is we can look at these years of data of clinical trials that have been run and say, "What is the appropriate amount of time that needs to be spent or, or for a particular type of compound? What are the, the different primary endpoints and secondary endpoints we should be looking at?" Not just the pie in the sky, let's look at everything.

I think the other side of it is the amount of data.

So with that in mind, I'm wondering if you could share with our audience, you know, some of those governance frameworks or best practices that you see emerging to ensure ethical, reliable, but also sustainable use of AI in clinical research as we move forward.