With the quality by design (QbD) initiative, regulatory authorities demand a consistent drug quality originating from a well-understood manufacturing process. This study demonstrates the application of a previously published mechanistic chromatography model to the in silico process characterization (PCS) of a monoclonal antibody polishing step. The proposed modeling workflow covered the main tasks of traditional PCS studies following the QbD principles, including criticality assessment of 11 process parameters and establishment of their proven acceptable ranges of operation. Analyzing effects of multi-variate sampling of process parameters on the purification outcome allowed identification of the edge-of-failure. Experimental validation of in silico results demanded approximately 75% less experiments compared to a purely wet-lab based PCS study. Stochastic simulation, considering the measured variances of process parameters and loading material composition, was used to estimate the capability of the process to meet the acceptance criteria for critical quality attributes and key performance indicators. The proposed workflow enables the implementation of digital process twins as QbD tool for improved development of biopharmaceutical manufacturing processes.

中文翻译：

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遵循质量源于设计理念的生物制药开发的计算机过程表征

借助质量源于设计 (QbD) 计划，监管机构要求始终如一的药品质量源于易于理解的制造过程。本研究展示了将先前发表的机械色谱模型应用于单克隆抗体精制步骤的计算机过程表征 (PCS)。拟议的建模工作流程涵盖了遵循 QbD 原则的传统 PCS 研究的主要任务，包括对 11 个过程参数的临界评估和确定其经证实的可接受的操作范围。分析工艺参数的多变量抽样对纯化结果的影响，可以识别故障边缘。与纯基于湿实验室的 PCS 研究相比，计算机结果的实验​​验证所需的实验减少了大约 75%。随机模拟，考虑到过程参数和装载材料成分的测量差异，用于估计过程满足关键质量属性和关键性能指标的验收标准的能力。拟议的工作流程能够将数字过程双胞胎作为 QbD 工具实施，以改进生物制药制造工艺的开发。