Archives: Agenda

• Government & Regulation: From “Approver” to “Ecosystem Cultivator and Rule-Maker”.
• Pharmaceutical Companies: From “Drug Suppliers” to “Key Ecosystem Builders and Enablers”.
• Medical Institutions: From “Service Endpoints” to “Data-Driven Innovation Hubs”.
• Patient Population: From “Passive Recipients” to “Empowered Active Health Partners”.

• 政府与监管：从“审批者”到“生态培育者与规则制定者
• 医药企业：从”药品供应商“到”生态系统的关键构建者与赋能者“
• 医疗机构：从“服务终端”到“数据驱动的创新协同中心”
• 患者群体：从”被动受众“到”自我赋能的主动健康伙 伴

• Clarifying the differences in using the terms RWE vs
• Proving examples of RWE sources available: commercial, society, private.
• Case study to explain a detailed implementation of RWE to support an expanded indication for a medical device

• RWE（真实世界证据）与 RWD（真实世界数据）术语使用的区别
• 现有 RWE 来源的实例：商业数据库、学会数据、私有数据源
• 如何运用真实世界证据支持医疗器械适应症扩展的案例介绍

• Understanding the current biotech landscape.
• Top considerations for future development.
• Engaging a global CRO.

• 了解当前生物技术领域的发展态势
• 未来发展的关键考量因素
• 如何与全球 CRO 建立合作

• New regulations and guidance around clinical trials in China: how will this impact you?
• Navigating the constantly evolving vendor and CRO landscape as a small to mid sized sponsor
• An overview of technology and innovation in the clinical trial industry: what’s working and what isn’t?

• 中国临床试验新规解读：对中小型企业的实际影响
• 动态变化的 CRO/供应商生态应对策略
• 临床试验技术创新应用评估：有效方案与现存瓶颈
• 海南封关对中国医药企业的影响与机遇

• Summary of market data and where Phase 1 studies are being performed.
• What are investors looking for from Phase 1 clinical trial datasets?
• What and where can Phase 1 studies be done to meet or exceed market demands?
• Review relevant case studies given recent China Biotechs market success.

• 市场数据总结及一期临床试验开展地区分析
• 投资者对一期临床试验数据的关键需求
• 满足或超越市场需求的一期临床试验方案及实施地点
• 结合中国生物科技公司近期市场成功的相关案例研究

• AI integration across the drug development lifecycle
• Building AI-driven drug discovery pipelines in China
• Overcoming challenges in AI adoption
• Success case study from Degron

中国正快速将人工智能（AI）整合到药物研发和临床开发中，这得益于机器学习、大数据分析的进步以及政府对生物技术创新的支持。本环节将聚焦AI从早期发现到监管申报的实际应用，并探讨企业如何在不断变化的中国监管环境中成功利用AI技术。

• AI在药物研发全生命周期中的整合
• 构建AI驱动的中国药物研发管线
• AI技术落地面临的挑战与应对
• 达歌生物成功案例分享