Thanks, Alex. Good morning, everyone. Thank you for joining us for our fourth quarter and full year 2024 business update call. 2024 was a successful year for Absci. I'm proud to say we executed across all aspects of our business, including advancing our proprietary internal programs, delivering on partner programs, and adding four new partners to our ecosystem of collaborators. We capped the year off with our 2024 R&D Day in December, where we unveiled our potentially category-defining ABS-201 program, targeting the prolactin receptor for the treatment of androgenic alopecia. At this event, we shared new data supporting a potential best-in-class profile for ABS-101, our anti-TL1A program, and preclinical data for ABS-301 and ABS-501 programs. Additionally, we showcased new breakthroughs in de novo antibody design from our leading AI platform and hosted distinguished guest presenters, including our KOLs and partners, such as Dr. Dennis Slamon from UCLA and Dr. Luis Diaz from Memorial Sloan Kettering. For those who did not view the webcast, I encourage you to access the replay on our website. ABS-201 in particular is an asset we are extremely excited about. We see the opportunity for ABS-201 to become a potential flagship asset for Absci. But first, I'd like to reflect on the capabilities that enabled us to generate these differentiated antibody assets. Looking back on 2024, we're encouraged by the significant advancements in our AI integrated drug creation platform. Similar to how the broader tech industry is experiencing successive breakthroughs in Generative AI, we view the progress of our model and platform in a similar light. Just two years ago, in January 2023, we released our first AI de novo blueprint. Since then, we have demonstrated notable platform improvements progressing from single CDR design to designing antibodies to targets with no known binders. These capabilities were clearly showcased in December, particularly through our collaboration with Caltech, which focused on designing a universally neutralizing HIV antibody. Before discussing that collaboration further, I'd like to highlight the key factors behind our success. At Absci, we see four key ingredients for success. Our data advantage, our leading AI models, access to scalable compute, and fostering a team with multilingual expertise. While we've spoken extensively about each of these in the past, I'd specifically like to focus on compute. In January, we announced a collaboration with AMD, a leader in high-performance computing. As part of this partnership, AMD made a $20 million strategic investment in Absci. This collaboration supports our mission of creating better biologics faster by offering optimized compute solutions for complex biological modeling. These solutions provided exceptional performance, reduced infrastructure costs, and accelerated cycle times. At the JPMorgan Healthcare Conference in January, I outlined several key reasons we chose to partner with AMD. AMD's chips gave us unmatched training resolution, allowing us to model large protein complexes without the need to crop, preserving biological context and enhancing model accuracy. Furthermore, this collaboration significantly accelerates throughput, scaling in in silicone antibody design and evaluation, and ultimately reducing R&D timelines and costs. Stepping back, what's the broader purpose of harnessing Generative AI for antibody design? It's not just about designing faster or cheaper, it's about creating truly differentiated candidates and unlocking novel biology for the benefit of patients. In December, we shared a case study illustrating breakthroughs in AI de novo design for our collaboration with Caltech. Using our proprietary de novo design model, we created antibodies targeting a difficult to drug epitope in the HIV caldera region, essentially facilitating the development of a universal neutralizing HIV antibody. The caldera region uniquely accessible only in the gp120 open confirmation has remained untargeted by previously neutralizing antibodies. Successfully creating these antibodies marks a potential pivotal milestone in HIV vaccine research and underscores the capability of our de novo design model to target previously undruggable epitopes. We're also actively applying our Generative AI drug creation capabilities to our proprietary internal pipeline. In December, we unveiled ABS-201, a potential best-in-class anti-prolactin receptor antibody for androgenic alopecia. This is an indication unmet need in a large patient population, approximately 80 million people in the US alone. Androgenic alopecia, also known as male and female pattern hair loss, affects 50% of men and 40% of women by the age of 50. There's been no real innovation in nearly 30 years, creating a large market potential. Our approach aims to not just slow hair loss, but to unlock an entirely new category focused on hair regrowth. We've nominated a development candidate for ABS-201, supported by preclinical data suggesting high affinity and potency, favorable safety and immunogenicity, extended half-life enabling convenient infrequent dosing, and excellent developability and manufacturability. Preclinical models demonstrated improved hair growth compared to minoxidil. As we advance ABS-201, we envision a straightforward path to clinical development and have assembled a robust network of renowned hair and dermatology KOLs advising our progress. ABS-201 is currently in IND enabling sites, with Phase 1 trials anticipated to begin in early ‘26. Since unveiling ABS-201 three months ago, we've received very positive responses from industry experts and the financial community. Given the compelling data, clear development path, and significant market opportunity, our strategy is to develop ABS-201 internally through later stage clinical development and proof of concept, retaining maximum value for Absci. Turning now to ABS-101, our potential best-in-class anti-TL1A antibody. At December's R&D day, we shared new data indicating ABS-101 does reduce internalization of TL1A complexes in in vitro THP1 immunogenicity tests compared to competitive molecules that have high clinical ADA rates. These data suggest ABS-101 may have lower ADA development risk in clinical settings. Additionally, in January, we shared new ABS-101 NHP- PK/PD data confirming prolonged target engagement, demonstrating dose-dependent engagement, including a ceiling effect, and significantly improved target engagement compared to competitor molecules at comparable dosing regimes. We plan to initiate Phase 1 clinical studies for ABS-101 in the first half of 2025, with an interim readout expected in the second half of this year. We continue to see active partner interests and have begun developing a potential first-in-class bispecific antibody incorporating our TL1A antibody as one arm. Additional data will be provided later. We recently shared data on ABS-301 and ABS-501 programs as well. ABS-301 targeting an undisclosed immuno-oncology target discovered through ABSAI's reverse immunology platform showed expression across squamous cell carcinomas. Our first in vivo target validation study demonstrated potent anti-tumor response, strongly supporting further development. For ABS-501, our potential best-in-class AI-designed anti-HER2 antibody, preclinical data confirms novel epitope interactions, affinity comparable or superior to trastuzumab, efficacy against trastuzumab-resistant xenograft tumors expressing wild type HER2, and good developability. Earlier, I mentioned that our team was a key ingredient to Absci’s success. This is evident in our achievements in 2024. As always, I'd like to thank our dedicated team at ABSI for their unwavering commitment and effort towards our mission. With that, I'll turn the call over to