Anna Greka

And that sort of led us into, you know, the early projects in my young lab.

And in fact, it's interesting, we didn't talk about that work, but that work in itself actually has made it all the way to phase two trials in patients.

This was a paper we published in Science in 2017.

And in follow on to that work, there was an opportunity to build this into a real drug, targeting one of these ion channels that has made it into phase two trials.

And we'll see what happens next.

But it's this idea of sort of

following your scientific curiosity, which I also talked about in my TED talk, because you don't know to what wonderful places it will lead you.

And quite interestingly, now my lab is back into studying familial Alzheimer's and retinitis pigmentosa in the eye and the brain.

So I tell people,

do not, you know, you know, limit yourself to whatever, you know, someone says your field is or should be, you know, just follow your scientific curiosity.

And usually that takes you a lot more interesting places.

And so that's certainly been a theme for my career, I would say.

Sure.

Yeah, thank you.

I think there are many ways in which, you know, even for quite a long time before AI became such a, you know, well known kind of household term, if you will, the concept of machine learning in terms of image processing is something that has been around for some time.

And so this is actually a form of AI that we use in order to kind of process millions of images.

My lab has by now produced probably more than 20 million images over the last few years, maybe five to six years.

And so if you can imagine, it's impossible for any human to process this many images and make sense of them.

So of course we've been using machine learning

that is becoming increasingly more and more sophisticated and advanced in terms of being able to do analysis of images, which is a lot of what we cell biologists do, of course.