IBG-1: Biotechnology, Forschungszentrum Jülich, Germany.
INM-4: Medical Imaging, Forschungszentrum Jülich, Germany.
J Chromatogr A. 2014 Mar 7;1332:8-13. doi: 10.1016/j.chroma.2014.01.047. Epub 2014 Jan 24.
A model-based approach is presented for quantitatively decoupling the impacts of non-ideal flow and non-ideal binding in membrane chromatography (MC) capsules at different scales. The internal geometry of Sartobind capsules with 0.08 ml and 1200 ml membrane volume is reconstructed from MRI measurements and manufacturer data. Based on this information, computational fluid dynamics (CFD) simulations are used for computing internal flow patterns of both capsules. Measured breakthrough curves (BTC) under non-binding conditions are used for calibrating PFR and CSTR models of the holdup volumes in the Äkta systems. A suitable binding model is determined and the binding parameters are estimated from binding BTC data of the 0.08 ml capsule. Due to the decoupling of non-idealities, the binding parameters can be directly transferred between the CFD models of both capsules. This advantage is used for quantitatively predicting BTC data of the 1200 ml capsule under binding conditions. The model-based prediction excellently matches with independently measured BTC data, facilitating an extreme scale-up factor of 15,000. The presented approach has previously been shown to be universally applicable to capsules from other vendors with different flow configurations and membrane types.
提出了一种基于模型的方法,用于在不同尺度下定量解耦膜色谱(MC)胶囊中非理想流动和非理想结合的影响。从 MRI 测量和制造商数据中重建了 Sartobind 胶囊的 0.08ml 和 1200ml 膜体积的内部几何形状。基于此信息,使用计算流体动力学(CFD)模拟计算两个胶囊的内部流动模式。在非结合条件下测量的突破曲线(BTC)用于校准 Äkta 系统中滞留体积的 PFR 和 CSTR 模型。确定合适的结合模型,并从 0.08ml 胶囊的结合 BTC 数据中估计结合参数。由于非理想性的解耦,可以在两个胶囊的 CFD 模型之间直接传输结合参数。该优势用于定量预测结合条件下 1200ml 胶囊的 BTC 数据。基于模型的预测与独立测量的 BTC 数据非常吻合,促进了 15000 倍的极端放大因子。所提出的方法以前已被证明对具有不同流动配置和膜类型的其他供应商的胶囊普遍适用。