Thank you, Mark. Good afternoon. Many of you have expressed interest in hearing more about our work on virus evolution and the confidence we have in the quality and durability of PEMGARDA and our pipeline molecules. To start on Slide 15, I want to introduce VivydTools, which is our in-house proprietary software that tracks virus variation across our COV-2 from multiple sources, including clinical sample sequence data and the sequencing data collected from wastewater. As a general rule, variants that become clinically relevant are detected in wastewater well in advance of their broad emergence. Wastewater data also includes sequences of viruses that do not ultimately rise to high prevalence in the clinic. But these data provide a broad view of the mutational space that has been explored by the virus over time. We use this tool for 2 purposes: firstly, in furtherance of activity prediction and monitoring, but also, as you will see increasingly to power highly proprietary discovery approaches that we think give us a unique advantage in the field. On slide -- as you can see on the left side of the panel on Slide 16, at Invivyd, we log and analyze variation observed across the spike protein down to very low frequency polymorphic explorations. In this small excerpt, you're seeing graphs which depict the various changes on the amino acid by amino acid basis across positions 403 to 432. While this view of the data allows you to appreciate multiple data sets simultaneously, the sharp eye among you may notice that some of these graphs do not have a lot of color and noise on them, whereas others do. That reflects the degree to which less or more polymorphic exploration has taken place at a given residue as the virus has evolved. By evaluating epitopic sites for our antibodies, including VYD222, we can assess how mutable or polymorphic our epitope is. We got finally in the areas we track as part of the assigned epitope of VYD222, we have observed polymorphic stability since the emergence of Omicron through to the present day. Turning to Slide 17. Of course, once we pick an antibody to develop it, we cannot change it. And so monitoring and analysis of variation gets much more valuable when we can incorporate it into the design of our screens and the selection of our antibody candidates. In a moment, I'm going to describe how this practice has been integrated into our pipeline. But for now, I will simply note the following. When we look at the variation across Spike and RBD, the area we want to contact with the mAb, we see evolution, sometimes saltation or large structural shares. And then we see reconvergence along previously documented exploratory pathways. In simplest terms, while we cannot expressly predict variation, we are beginning to better understand the nature of SARS-CoV-2 evolution. If we can create some level of data-driven intelligence in predicting future potential changes, we can identify future theoretical or synthetics by proteins that may not even exist yet as variance, but which represent probabilistic futures for which we want to prepare. And if we can do that, we can deploy our proprietary discovery technology that takes advantage of the high-throughput yeast-based mAb optimization platform from Adimab, directing it to perform operations that would be practically impossible with less advanced technology. Turning to Slide 18. What that means is that armed with information about viruses that have circulated are now circulating and then armed with synthetic depictions about what might circulate, we can execute boolean or logic-driven discovery screens in which we direct the platform to identify predefined antibodies, all based on the original framework of adintrevimab and now Pemivibart, which, for example, neutralize XBB and JN.1 and so on, but which do not interact with the residues we may worry about from our probabilistic work. We can then select those candidate antibodies and indeed confirm the activity we believe we wish them to have, both against current virus, but also, which embrace the anticipation of single or multiple future convergently evolved variants. Moving to Slide 19. We are looking for antibodies that are not limited by Mammalian immune suite such as we might see in convalescent serum or a [ mouse ], we are seeking novel molecules that can go through rapid highly efficient development path and in each generation of molecule, we are looking to increase our design level confidence in resistance to variation and improve the overall pharmaceutical properties of our products. In practice, this approach started with adintrevimab, which was made early as the maturation of a SARS-CoV-1 antibody against Wuhan than its virus. The critical product attribute at that time was thought to have been achieved through conservation of H2 access, although the Omicron shift taught us and other sponsors that there were sufficient permissiveness in H2 access to make immune evasion a second critical dimension of the discovery process. Then we go to Pemivibart which is adintrevimab optimized against BA.2, but leaving as a criterion backwards-looking neutralization of ancestral pre-Omicron lineages, that constraint appears to be driving so far a highly encouraging conservation of the Pemivibart epitope across evolution, but impose at least a modest potency penalty on recent circulating viruses. Our next anticipated clinical candidate VYD2311, takes Pemivibart and optimizes it further for increased potency and assessed variation resistance. We will look forward to introducing you to 2311 more fully soon, but the early profile is very encouraging as it goes to improvement over Pemivibart in terms of possible dose, therapeutic index and route of administration. A bit earlier, still in Discovery, we are now integrating our forward-looking synthetic antigens to create antibodies that we believe have some in-built anticipatory intelligence, a process we expect to monitor and refine as we go. In these, we are now operating out past the frontier of what is, and we are actually discovering and qualifying molecules that are designed on multiple dimensions to address what we believe is likely in the future, a very unique approach in biopharmaceuticals as far as we are aware. Next, I'd like to turn it back over to Mark for some closing thoughts before we move to Q&A.