Neal G, Christie J, Keshavarz-Moore E, Shamlou P Ayazi
The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, University College London, Torrington Place, London, UK.
Biotechnol Bioeng. 2003 Jan 20;81(2):149-57. doi: 10.1002/bit.10454.
In this article, we describe a new approach that allows the prediction of the performance of a large-scale integrated process for the primary recovery of a therapeutic antibody from an analysis of the individual unit operations and their interactions in an ultra scale-down mimic of the process. The recovery process consisted of four distinct unit operations. Using the new approach we defined the important engineering parameters in each operation that impacted the overall recovery process and in each case verified its effect by a combination of modelling and experimentation. Immunoglobulins were precipitated from large volumes of dilute blood plasma and the precipitated flocs were recovered by centrifugal separation from the liquor containing contaminating proteins, including albumin. The fluid mechanical forces acting on the precipitate and the time of exposure to these forces were used to define a time-integrated fluid stress. This was used as a scaling factor to predict the properties of the precipitated flocs at large scale. In the case of centrifugation, the performance of a full-scale disc stack centrifuge was predicted. This was achieved from a computational fluid dynamics (CFD) analysis of the flow field in the centrifuge coupled with experimental data obtained from the precipitated immunoglobulin flocs using the scale-down precipitation tank, a rotating shear device, and a standard swing-out rotor centrifuge operating under defined conditions. In this way, the performance of the individual unit operations, and their linkage, was successfully analysed from a combination of modelling and experiments. These experiments required only millilitre quantities of the process material. The overall performance of the large-scale process was predicted by tracking the changes in physical and biological properties of the key components in the system, including the size distribution of the antibody precipitates and antibody activity through the individual unit operations in the ultra scale-down process flowsheet.
在本文中,我们描述了一种新方法,该方法能够通过对单个单元操作及其在超规模缩小的过程模拟中的相互作用进行分析,预测从治疗性抗体的初次回收中大规模集成过程的性能。回收过程由四个不同的单元操作组成。使用这种新方法,我们确定了每个操作中影响整体回收过程的重要工程参数,并在每种情况下通过建模和实验相结合的方式验证了其效果。从大量稀释血浆中沉淀免疫球蛋白,并通过离心分离从含有包括白蛋白在内的污染蛋白质的液体中回收沉淀的絮凝物。作用于沉淀物的流体力学力以及暴露于这些力的时间被用来定义时间积分流体应力。这被用作缩放因子来预测大规模沉淀絮凝物的性质。在离心的情况下,预测了全尺寸碟片式离心机的性能。这是通过对离心机内流场的计算流体动力学(CFD)分析以及使用缩小规模的沉淀罐、旋转剪切装置和在规定条件下运行的标准摆式转子离心机从沉淀的免疫球蛋白絮凝物获得的实验数据实现的。通过这种方式,成功地从建模和实验的结合中分析了各个单元操作的性能及其联系。这些实验仅需要毫升量的过程材料。通过跟踪系统中关键成分的物理和生物学性质的变化,包括在超规模缩小工艺流程中各个单元操作过程中抗体沉淀物的尺寸分布和抗体活性,预测了大规模过程的整体性能。