Control strategy for multi-column continuous periodic counter current chromatography subject to fluctuating inlet stream concentration

Sensors and chemometrics in downstream processing

The biopharmaceutical industry is still running in batch mode, mostly because it is highly regulated. In the past, sensors were not readily available and in-process control was mainly executed offline. The most important product parameters are quantity, purity, and potency, in addition to adventitious agents and bioburden. New concepts using disposable single-use technologies and integrated bioprocessing for manufacturing will dominate the future of bioprocessing. To ensure the quality of pharmaceuticals, initiatives such as Process Analytical Technologies, Quality by Design, and Continuous Integrated Manufacturing have been established. The aim is that these initiatives, together with technology development, will pave the way for process automation and autonomous bioprocessing without any human intervention. Then, real-time release would be realized, leading to a highly predictive and robust biomanufacturing system. The steps toward such automated and autonomous bioprocessing are reviewed in the context of monitoring and control. It is possible to integrate real-time monitoring gradually, and it should be considered from a soft sensor perspective. This concept has already been successfully implemented in other industries and requires relatively simple model training and the use of established statistical tools, such as multivariate statistics or neural networks. This review describes a scenario for integrating soft sensors and predictive chemometrics into modern process control. This is exemplified by selective downstream processing steps, such as chromatography and membrane filtration, the most common unit operations for separation of biopharmaceuticals.

Evaluation of dynamic control of continuous capture with periodic counter-current chromatography under feedstock variations

Multi-column periodic counter-current chromatography is a promising technology for continuous antibody capture. However, dynamic changes due to disturbances and drifts pose some potential risks for continuous processes during long-term operation. In this study, a model-based approach was used to describe the changes in breakthrough curves with feedstock variations in target proteins and impurities. The performances of continuous capture of three-column periodic counter-current chromatography under ΔUV dynamic control were systematically evaluated with modeling to assess the risks under different feedstock variations. As the concentration of target protein decreased rapidly, the protein might not breakthrough from the first column, resulting in the failure of ΔUV control. Small reductions in the concentrations of target proteins or impurities would cause protein losses, which could be predicted by the modeling. The combination of target protein and impurity variations showed complicated effects on the process performance of continuous capture. A contour map was proposed to describe the comprehensive impacts under different situations, and nonoperation areas could be identified due to control failure or protein loss. With the model-based approach, after the model parameters are estimated from the breakthrough curves, it can rapidly predict the process stability under dynamic control and assess the risks under feedstock variations or UV signal drifts. In conclusion, the model-based approach is a powerful tool for continuous process evaluation under dynamic changes and would be useful for establishing a new real-time dynamic control strategy.

Continuous Affinity Purification of Adeno-Associated Virus Using Periodic Counter-Current Chromatography

Replacing batch unit operations of biopharmaceuticals by continuous manufacturing is a maturing concept, with periodic counter-current chromatography (PCC) favoured to replace batch chromatography. Continuous affinity capture of adeno-associated virus (AAV) using PCC has the potential to cope with the high doses required for AAV therapies thanks to its inherent high throughput. The implementation of continuous AAV affinity capture using a four-column PCC process is described herein. First, elution buffer screening was used to optimize virus recovery. Second, breakthrough curves were generated and described using a mechanistic model, which was later used to characterize the loading zone of the PCC. The experimental runs achieved a stable cyclic steady state yielding virus recoveries in line with the optimized batch process (>82%), with almost a three-fold improvement in productivity. The PCC affinity capture process developed here can bolster further improvements to process economics and manufacturing footprint, thereby contributing to the integrated continuous manufacturing concept.

An integrated and continuous downstream process for microbial virus-like particle vaccine biomanufacture

In this study, we present the first integrated and continuous downstream process for the production of microbial virus‐like particle vaccines. Modular murine polyomavirus major capsid VP1 with integrated J8 antigen was used as a model virus‐like particle vaccine. The integrated continuous downstream process starts with crude cell lysate and consists of a flow‐through chromatography step followed by periodic counter‐current chromatography (PCC) (bind‐elute) using salt‐tolerant mixed‐mode resin and subsequent in‐line assembly. The automated process showed a robust behavior over different inlet feed concentrations ranging from 1.0 to 3.2 mg ml⁻¹ with only minimal adjustments needed, and produced continuously high‐quality virus‐like particles, free of nucleic acids, with constant purity over extended periods of time. The average size remained constant between 44.8 ± 2.3 and 47.2 ± 2.9 nm comparable to literature. The process had an overall product recovery of 88.6% and a process productivity up to 2.56 mg h⁻¹ ml_resin⁻¹ in the PCC step, depending on the inlet concentration. Integrating a flow through step with a subsequent PCC step allowed streamlined processing, showing a possible continuous pathway for a wide range of products of interest.