Thanks, Harpal. And hello, everybody. At GRAIL, we have implemented one of the largest clinical evidence programs in the MCED space with more than 385,000 participants overall. More than 21,000 participants were included in the studies to support the development and launch of Galleri and over 170,000 individuals are included in our registrational studies, which support our PMA submission to the FDA. Now let's be clear. Galleri is working in the real world. We are detecting clinically meaningful cancers and early stage cancers in asymptomatic adults. Our signal detection rate in commercial use is very much in line with what we expected based on our prior clinical studies. The majority of the early stage cancers Galleri has found are in cancer types where a recommended screening test does not even exist, thereby allowing patients an opportunity to access more effective and even curative treatments. Now we've described over time the key performance metrics, features, and capabilities for multi-cancer early detection tests, which importantly, are quite different from those for single cancer screenings. Positive predictive value, or PPV, is a key metric which discerns among positive test results how many are true positives. Specificity, critically important, defines the false positive rate. A very low false positive rate helps reduce unnecessary workups and their associated costs and contributes to driving a high positive predictive value. Our demonstrated specificity at 99.5% equates to a false positive rate of 0.5%. So just to remind you, a 1% reduction in specificity to 98.5% would triple the false positive rate. That is a 0.5% false positive rate would then become a 1.5% false positive rate, 3 times higher. So applying this to a real world population of a million people tested, instead of there being only 5,000 false positives, there would now be 15,000. Such a reduced specificity would be expected also to result in a positive predictive value about half of what we see at a specificity of 99.5%, holding all other metrics constant. Finally, one of the most important features of a multicancer early detection test is the ability to localize that cancer signal. In multicancer early detection, CSO capability or our cancer signal of origin prediction is the key to guiding physicians to an appropriate and efficient workup to diagnosis. We consistently hear from physicians in the field that this is a critical component of any multi-cancer screening test. Even an FDA advisory committee on multi-cancer detection in November 23 similarly emphasized the importance of a cancer signal of origin feature in any multi-cancer detection test. Our teams have continued to present evidence demonstrating Galleri's performance at renouned medical conferences. In April, at the AACR meeting, we showed a real world dataset on Galleri's test performance and implementation in over a 100,000 individuals. Galleri indeed identified cancers across this large intended use population, including early stage cancers and cancers without recommended screening. Generally, the test performance in this real world setting remain consistent with what we've consistently observed in our prior clinical studies. Among other data, we also presented at AACR an analysis highlighting the importance of annual screening with an MCED test. Model data of post test probabilities of cancers for individuals receiving MCED tests show that individuals receiving a negative MCED test and they have a reduced risk of late stage cancer diagnosis for one year after the blood draw and then this risk increases as the screening interval extends beyond one year. This study really supports the need for annual testing. Finally, I'd like to highlight that US health systems are now publishing their own experiences with Galleri performance and implementation. A paper authored by the Mayo Clinic and published recently in March in the Journal of Primary Care and Community Health showed that Galleri effectively detected cancers in an asymptomatic population within their healthcare system and had a 73% positive predictive value. In other words, 73% of those with a positive Galleri test yielded a confirmed new cancer diagnosis. Now the sample in this Mayo Clinic analysis was relatively small and had some different patient demographics compared to our prior trials. Importantly, this paper included the Mayo Clinic's standardized approach to pursue a diagnostic workup following a positive cancer signal and our signal of origin prediction. The outlined steps are informed by a multidisciplinary expert council convened by the Mayo Clinic. Then they reviewed our cancer signal of origin prediction and other data from our first PATHFINDER trial. These recommendations continue to be updated and they've really served as a centralized resource for the Mayo Clinic physicians. Now additional health systems and clinicians are beginning to publish their experience with Galleri. Upcoming ASCO 2025 presentations of note include the implementation and evaluation of multi-cancer early detection testing at the Dana-Farber Cancer Institute, a retrospective analysis of clinical outcomes and diagnostic pathways and an independent analysis by Alabama Cancer Care, titled a clinical review of a novel blood test use in rural Alabama for multi-cancer detection, analyzing methylation patterns of cell free DNA and future strategies. Now looking forward, we anticipate performance data from the first 25,000 participants in our other registrational study PATHFINDER 2 later this year. We also plan to conduct a bridging study between the version of Galleri used in our registrational trials, NHS Galleri and PATHFINDER 2, to the updated version that we plan to submit to the FDA for premarket approval. We plan to submit data from the prevalent screening round of the NHS Galleri trial, the first 25,000 participants in the PATHFINDER 2 study and the bridging study as part of our premarket approval application in the first half of '26. I'll now hand it over to Aaron for a review of our financials.