来自其他物种的具有潜力的治疗性抗体在到达人类患者之前通常会经历人源化过程。人源化包括改变其氨基酸序列，使其更接近人类抗体。虽然这是一种最大程度上降低免疫原性风险的常用方法，但人源化仍然是一项重大的技术障碍。Twist Bioscience 开发了一项将高精度 DNA 合成与机器学习（ML）相结合的人源化平台，以改进该过程，从而实现更快、更高效并最终获得生产力更高的抗体工程。

Utilizing its proprietary DNA technology to write synthetic libraries, Twist Biopharma provides end-to-end antibody discovery libraries including both (1) highly diverse synthetic naïve antibody phage display libraries and (2) target class specific antibody phage display libraries against difficult-to-drug targets.  In this talk, Aaron Sato, CSO, will present on how Twist uses our libraries coupled with Machine Learning to discover 1) antibody sequences from NGS sequencing of our successive panning rounds and 2) optimize existing leads derived from traditional screening.

CAR-T 细胞疗法是一种富有前景的实体瘤治疗方法。但要确定专门针对肿瘤抗原的适当 T 细胞受体（TCR）结构域依然是一个挑战。Toxicity, tumor activation, and tumor persistence are significant challenges to using CAR-T cell therapies for solid tumors.In this webinar, Twist Bioscience’s CSO, Aaron Sato, will present several proof-of-concept studies showing how these technologies can be utilized for cell therapies. Aaron will also be joined by Justin Farlow, CTO of Serotiny, who will tell the story of how Twist’s Combinatorial Assembly Libraries helped his company design and evaluate thousands of CARs, each with novel intracellular signaling architectures. 通过使用这些文库，Serotiny 快速地选择了多种新颖的 CAR 设计，进而增强原代 T 细胞的治疗性能。