Chai Discovery 的创始人讨论他们的 AI 模型和设计套件如何将药物发现从瀑布流程转变为敏捷循环，并与大型制药公司建立合作。
Chai Discovery's founders discuss how their AI models and design suite are transforming drug discovery from a waterfall process into an agile loop, with partnerships with major pharma companies.
本期章节 · Chapters（共 36）
引言与背景Introduction and Backgrounds
合作与商业模式Partnerships and Business Model
产品愿景与未来Product Vision and Future
结构预测进展与通用性赌注Structure prediction progress and the bet on generality
目标选择与50目标挑战Choosing targets and the story behind the 50-target challenge
抗体：挑战与吸引力Why antibodies are a challenging but attractive domain
抗体结构与治疗应用Antibody structure and therapeutic applications
精准药物设计Precision drug design
传统药物设计流程Traditional drug design process
AI驱动设计的优势Advantages of AI-driven design
选择性与交叉反应Selectivity and cross-reactivity
交叉反应定义与设计策略Defining cross-reactivity and design strategy
替代方法与反向筛选Alternative approaches and counter-screening
资金与模型扩展Funding and Model Scaling
Chai 1 简介Introduction to Chai 1
Chai 2：设计能力Chai 2: Design Capabilities
迭代设计与EM算法Iterative Design and EM Algorithm
验证结构预测Validating structure predictions
为何推出Chai 3Why Chai 3
Chai 2后的产品侧Product side after Chai 2
制药平台的安全与IPSecurity and IP in pharma platform
设计套件：分子工程可视化Design suite: visual tool for molecule engineering
说服药物化学家使用AI工具Convincing med chemists to use AI tools
内部跨学科团队与严谨性Internal cross-disciplinary team and rigor
产品演进与抽象化Product Evolution and Abstraction
抗体能力与新模态Antibody Capabilities and New Modalities
算力紧张与市场动态Compute crunch and market dynamics
持久执行与TemporalDurable execution and Temporal
生物学中的工程原语Engineering Primitives in Biology
产品通用性与设计哲学Product generality and design philosophy
行业前景与竞争Industry outlook and competition
差异化与战略Differentiation and strategy
合作模式与数据策略Partnership Model and Data Strategy
硅谷历史与生物技术融资Silicon Valley History and Biotech Funding