Xencor (XNCR) FY 2025 Conference September 03, 2025 03:00 PM ET Speaker0All right. Well, thanks, everyone, for coming to the Xencor panel. I'm pleased to have Dane Leone, EVP and Chief Strategy Officer.Speaker1Thank you for having us at the Wells Fargo Conference. Pleasure to be here, and thanks for having us on stage.Speaker0I'll let you start off with an overview to introduce those who may not be familiar with the company and then I'll go into questions.Speaker1Great, thank you so much. So I'm the Chief S ...

Core Viewpoint - The article discusses the advancements made using the GPT-4b micro model in protein engineering, particularly in enhancing the Yamanaka factors for stem cell reprogramming, which could significantly impact regenerative medicine and longevity research [1][17][50]. Group 1: Model Development - GPT-4b micro is a specialized version of GPT-4o, developed in collaboration with Retro Bio, designed specifically for protein engineering [7][8]. - The model was trained on a dataset rich in protein sequences, biological texts, and 3D structure data, allowing it to generate sequences with specific desired properties [9][10]. - The model can handle long input sequences of up to 64,000 tokens, which is unprecedented in protein sequence models, enhancing its controllability and output quality [14][15]. Group 2: Protein Engineering Breakthroughs - Scientists successfully redesigned the Yamanaka factors, achieving a 50-fold increase in the expression of stem cell reprogramming markers compared to wild-type controls [2][17]. - The redesigned proteins also exhibited enhanced DNA damage repair capabilities, indicating a potential for rejuvenation [3][47]. - The findings have been validated across multiple donor sources, cell types, and delivery methods, confirming the pluripotency and genomic stability of derived iPSC lines [4][18][41]. Group 3: Experimental Results - The Retro team utilized human fibroblasts to create a screening platform, where the GPT-4b micro generated diverse "RetroSOX" sequences, with over 30% showing superior performance in expressing pluripotency markers [24][27]. - The combination of the best RetroSOX and RetroKLF variants led to significant improvements in early and late pluripotency marker expression, with earlier appearance times compared to wild-type combinations [34][38]. - The engineered variants demonstrated a high hit rate of nearly 50%, significantly outperforming traditional screening methods [32][28]. Group 4: Future Implications - The research indicates that AI-guided protein design can accelerate stem cell reprogramming, with potential applications in treating age-related diseases and enhancing regenerative therapies [43][49]. - The team is exploring the rejuvenation potential of the redesigned variants, focusing on their ability to reduce DNA damage, a hallmark of cellular aging [44][46]. - The results suggest a promising avenue for improving cell regeneration and future therapies, highlighting the transformative potential of AI in life sciences [50][51].