So Julia, we talked quite a bit about the basics of the technology and usability, but again, implementation is always the big question and, and since you lead the cancer biomarker development in this space at AstraZeneca, briefly, how do you foresee some of this being tested, validated, and implemented in the clinical trial or perhaps even in real world setting?

The technology is the first hurdle to overcome, but understanding the impact of the pre-analytic variables all the way from the time a blood sample is taken until it gets into the testing process requires a lot of additional validation work, especially in a company like AstraZeneca that conducts trials with a global footprint.

So one of the things that is always necessary and probably one of the least glamorous parts of getting something like, uh, new technology to work is to work out all of those elements that could impact the results to ensure that we're not seeing an artifact instead of a signal.

And I think similarly, one of the key things when we're looking at signals that are derived from healthy tissues, this is going to rely on us understanding the individual variability of the signals that come from normal physiology across the wide range of the patient population that we're gonna be looking at.

So ensuring that we understand not only various physiologic states and the signals that come from those, but also ensuring that we include the widest possible range of patients to set these norms for our standards.

And this is particularly relevant considering some of the biases that are inherent in some of our databases based on who normally either has access to laboratory testing or who participates in clinical trials.

Is there a thought or maybe is there already processes going on where some of this is being evaluated from the blood and being matched to toxicity that you see on the clinical side to see if there is a true signal that you pick up in the blood that matches to what the clinicians have, uh, documented as adverse events?

Absolutely.