Ultrafiltration/diafiltration (UF/DF) is a typical step in protein drug manufacturing process to concentrate and exchange the protein solution into a desired formulation. However, significant offset of pH and composition from the target formulation have been frequently observed after UF/DF, posing challenges to the stability, performance, and consistency of the final drug product. Such shift can often be attributed to the Donnan and volume exclusion effects. In order to predict and compensate for those effects, a mechanistic model is developed based on the protein charge, mass and charge balances, as well as the equilibrium condition across the membrane. The integrated UF/DF model can be used to predict both the dynamic behavior and the final outcome of the process. Examples of the modeling results for the pH and composition variation during the UF/DF operations are presented for two monoclonal antibody proteins. The model predictions are in good agreement with a comprehensive experimental data set that covers different process steps, protein concentrations, solution matrices, and process scales. The results show that significant pH and excipient concentration shifts are more likely to occur for high protein concentration and low ionic strength matrices. As a special example, a self‐buffering protein formulation shows unique pH behavior during DF, which could also be captured with the dynamic model. The capability of the model in predicting the performance of UF/DF process as a function of protein characteristics and formulation conditions makes it a useful tool to improve process understanding and facilitate process development.

中文翻译：

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解释蛋白质制剂超滤/渗滤过程中唐南和体积排阻效应的机械模型

超滤/渗滤 (UF/DF) 是蛋白质药物制造过程中的一个典型步骤，用于将蛋白质溶液浓缩和交换成所需的制剂。然而，在 UF/DF 之后，经常观察到目标制剂的 pH 值和成分显着偏移，这对最终药物产品的稳定性、性能和一致性提出了挑战。这种转变通常可以归因于唐南效应和体积排斥效应。为了预测和补偿这些影响，基于蛋白质电荷、质量和电荷平衡以及跨膜平衡条件开发了一个机械模型。集成的 UF/DF 模型可用于预测过程的动态行为和最终结果。UF/DF 操作过程中 pH 和组成变化的建模结果示例针对两种单克隆抗体蛋白进行了介绍。模型预测与涵盖不同工艺步骤、蛋白质浓度、溶液基质和工艺规模的综合实验数据集非常吻合。结果表明，对于高蛋白质浓度和低离子强度的基质，更可能发生显着的 pH 值和赋形剂浓度变化。作为一个特殊的例子，自缓冲蛋白质配方在 DF 期间表现出独特的 pH 行为，这也可以通过动态模型捕获。