loading page

Residence time distribution in continuous virus filtration
  • +2
  • Alois Jungbauer,
  • Yu-Cheng Chen,
  • Gabriele Recanati,
  • Fernando De Mathia,
  • Dong-Qiang Lin
Alois Jungbauer
Universitat fur Bodenkultur Department fur Biotechnologie

Corresponding Author:[email protected]

Author Profile
Yu-Cheng Chen
Universitat fur Bodenkultur Department fur Biotechnologie
Author Profile
Gabriele Recanati
Universitat fur Bodenkultur Department fur Biotechnologie
Author Profile
Fernando De Mathia
Universitat fur Bodenkultur Department fur Biotechnologie
Author Profile
Dong-Qiang Lin
Zhejiang University College of Chemical and Biological Engineering
Author Profile

Abstract

Regulatory authorities recommend using residence time distribution (RTD) to address material traceability in continuous manufacturing. Continuous virus filtration is an essential but poorly understood step in biologics manufacturing. Here we describe a model that considers non-ideal mixing and film resistance for RTD prediction in continuous virus filtration, and its experimental validation using the inert tracer NaNO 3. The model was successfully calibrated through pulse injection experiments, yielding good agreement between model prediction and experiment ( R 2 >   0.90). The model enables prediction of RTD with variations—e.g., in injection volumes, flow rates, tracer concentrations, and filter surface areas—and was validated using stepwise experiments, and combined stepwise and pulse injection experiments. All validation experiments achieved R 2 >   0.97, except when valves were switched at a high flow rate. Notably, if the process includes a porous material—such as a porous chromatography material, ultrafilter, or virus filter—it must be considered whether the molecule size affects the RTD, as tracers with different sizes may penetrate the pore space differently. Calibration of the model with NaNO 3 enabled extrapolation to RTD of recombinant antibodies, which will promote significant savings in antibody consumption. This RTD model is ready for further application in end-to-end integrated continuous downstream processes, such as addressing material traceability during continuous virus filtration processes.