设计质量
比例(比率)
单变量
过程(计算)
多元统计
工艺工程
计算机科学
放大
多元分析
生化工程
工业工程
尺度分析(数学)
制造工程
可靠性工程
工程类
机器学习
运营管理
物理
经典力学
量子力学
下游(制造业)
操作系统
热力学
作者
Valerie Liu Tsang,Angela X. Wang,Helena Yusuf‐Makagiansar,Thomas Ryll
摘要
In characterizing a cell culture process to support regulatory activities such as process validation and Quality by Design, developing a representative scale down model for design space definition is of great importance. The manufacturing bioreactor should ideally reproduce bench scale performance with respect to all measurable parameters. However, due to intrinsic geometric differences between scales, process performance at manufacturing scale often varies from bench scale performance, typically exhibiting differences in parameters such as cell growth, protein productivity, and/or dissolved carbon dioxide concentration. Here, we describe a case study in which a bench scale cell culture process model is developed to mimic historical manufacturing scale performance for a late stage CHO-based monoclonal antibody program. Using multivariate analysis (MVA) as primary data analysis tool in addition to traditional univariate analysis techniques to identify gaps between scales, process adjustments were implemented at bench scale resulting in an improved scale down cell culture process model. Finally we propose an approach for small scale model qualification including three main aspects: MVA, comparison of key physiological rates, and comparison of product quality attributes.
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