Diego, that is just a fantastic question. I'm gonna 100% fail to answer it. Well, I'm gonna have a crack. I think it's a huge tension. And it's a big question in genomics. But it also goes beyond that to, you know, all of health really, and probably other areas too, like, you know, social care, welfare, everything. And the first thing I'm gonna say is just super recently, I've started to listen to some of the podcasts - I'm going to name check a different podcast here, the Center for Personalized Medicine at University of Oxford has a podcast series. And Gabby Samuel, Dr. Gabby Samuel is one of the hosts, she's at King's College, and she's starting to do some really interesting work on the carbon footprint of data. And firstly, I think it's basically impossible to count. But secondly, it is significant. And so I think a really big avenue, following Gabby's work, is to actually really think about the value of this information, not just for banking it all, and drawing upon it as and when we need to, but really stopping first and thinking, why are we banking? What are we banking? What is the intended value? What are the standards that we are using in order to do this? So, I think, you know, a big hallmark of the work I've done and in collaboration with folks like Lisa and Belle is to really think mindfully and prudently about the way we use technology. And to use this in a way that is first asking what the purpose is, now and in the imminent future. Longer term, I think, we have to recognize that what we have now will always be improved upon. And so we don't necessarily need to save and bank everything, because the quality of it just might not stand up to time. So for me, at least, all of this needs to be led by normative questions, you know, critical questions asking: why are we doing this? What are we hoping to gain? What are the drawbacks? What might- What might we do with this? How can we join it all together? Is that infrastructure there yet? What do we need for that to happen? And not just thinking about it only in terms of benefits to individuals, but actually, what are the firstly, I guess, broader public implications, but also global implications, not just for humans, like, and I think that's where this idea that Gabby's working on of carbon footprints of types of data like this is really important. So yeah, I think ultimately, there might be an argument for looking for less rather than more to start with, because then you can answer the question that's in front of you well, and then in the future, when you need more, you can go look for it, then, of course, the counterpoint to that is, you're not always going to have people sitting in front of you, holding out their arm or offering their mouth for a cheek swab or a blood draw, depending on your method. And there is that kind of idea of: "Let's capture people while they're in front of us" if we're talking about personalized medicine. And so I think we have to think not just about that, but we have to think about ways of engaging populations in this type of work as we go forward.