结合法规要求(QbD, PAT)及Pharma 4.0 的趋势介绍数据分析在生物制药研发中的作用及应用案例 Biopharmaceutical companies today are facing increasing challenge on quality requirement. Quality by Design (QbD) and design space estimation, initiated by International Council for Harmonisation (ICH), are moving into to the phase of establishing standardized procedures within biopharmaceutical companies. In product and process development, deriving the design space is the main challenge; it needs risk analysis to thoroughly investigate and define critical quality attributes (CQAs), critical process parameters (CPPs), and criticalmaterialattributes(CMAs), together with using design of experiments (DOE) to derive mathematical models relating CQAs with CPPs and CMAs. The advent of modern instruments provides vehicle for an efficient development yet also brings challenges. Development work involves larger and larger masses of data and data analytics becomes crucial. Correct management of data can give us valuable insights to product and process development, help us understand the progress of cell culture and purification, and also point us in the right direction to troubleshoot. By applying state-of-the art data analytics, the risk can be reduced, yield can be improved, and cost can be reduced. The presentation will discuss an overview of regulatory stance and requirement, value of data analytics in biopharma R-D and Pharma 4.0. Examples are given on how data analytics is used within the framework of QbD and PAT to improve quality and throughput.