计算机科学
设计质量
工艺验证
过程(计算)
关键质量属性
采样(信号处理)
统计过程控制
桥接(联网)
风险分析(工程)
质量(理念)
医药制造业
工艺工程
生化工程
数据收集
可靠性工程
在制品
过程能力
数据挖掘
工艺设计
过程分析技术
稳健性(进化)
过程控制
差异(会计)
产品(数学)
过程开发
控制图
过程建模
过程能力指数
新产品开发
作者
Ajay Babu Pazhayattil,Marzena Ingram,Prasanna Sagar,Kishorkumar Kotini,Abhijit Bodhe,Mallinath Harwalkar,Satish Joshi,Subrata Chakraborty,Rajesh Sreedharan Nair,A. Elsaid
标识
DOI:10.5731/pdajpst.2025-000046.1
摘要
Lyophilization is a critical process, removing water and or solvent through sublimation to ensure the stability and longevity of injectable drug products. The complexity of the lyophilization process, involving multiple stages such as freezing, primary drying, and secondary drying, necessitates a robust approach to ensure product quality and consistency. Along with applying Quality by Design (QbD) principles in lyo process development, robust statistical and risk-based methodologies are essential for assessing process variability. This paper presents a risk-based and statistically sound sampling methodology for assessing variability in lyophilized drug products during Continued Process Verification (Stage 3a) of Process Validation. Sampling plans are strategically designed, ensuring representative data collection from lyophilizer shelves. By integrating variance analysis, capability indices, and probability, the methodology provides a comprehensive understanding of both intra-batch and inter-batch variability. The assessment enables estimation of future batch performance concerning critical quality attributes, including water content, assay, pH, and impurities. Identifying and controlling both intra-batch (within-shelf and between-shelf) and inter-batch variability ensures robustness. The study highlights the importance of statistically rigorous sampling plans, justification of the plans and data analysis to ensure process control. A case study is presented, demonstrating the application of the approach in a lyophilization process. The methodology supports regulatory compliance and enhances process understanding, enabling tighter process control and continuous improvement. The risk-based Stage 3a framework provides a structured method for post-commercialization variability assessment, bridging process design and continued verification.
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