Model based process optimization of an industrial chromatographic process for separation of lactoferrin from bovine milk

Model based process development using predictive mechanistic models is a powerful tool for in-silico downstream process development. It allows to obtain a thorough understanding of the process reducing experimental effort. While in pharma industry, mechanistic modeling becomes more common in the last years, it is rarely applied in food industry. This case study investigates risk ranking and possible optimization of the industrial process of purifying lactoferrin from bovine milk using SP Sepharose Big Beads with a resin particle diameter of 200 µm, based on a minimal number of lab-scale experiments combining traditional scale-down experiments with mechanistic modeling. Depending on the location and season, process water pH and the composition of raw milk can vary, posing a challenge for highly efficient process development. A predictive model based on the general rate model with steric mass action binding, extended for pH dependence, was calibrated to describe the elution behavior of lactoferrin and main impurities. The gained model was evaluated against changes in flow rate, step elution conditions, and higher loading and showed excellent agreement with the observed experimental data. The model was then used to investigate the critical process parameters, such as water pH, conductivity of elution steps, and flow rate, on process performance and purity. It was found that the elution behavior of lactoferrin is relatively consistent over the pH range of 5.5 to 7.6, while the elution behavior of the main impurities varies greatly with elution pH. As a result, a significant loss in lactoferrin is unavoidable to achieve desired purities at pH levels below pH 6.0. Optimal process parameters were identified to reduce water and salt consumption and increase purity, depending on water pH and raw milk composition. The optimal conductivity for impurity removal in a low conductivity elution step was found to be 43 mS/cm, while a conductivity of 95 mS/cm leads to the lowest overall salt usage during lactoferrin elution. Further increasing the conductivity during lactoferrin elution can only slightly lower the elution volume thus can also lead to higher total salt usage. Low flow rates during elution of 0.2 column volume per minute are beneficial compared to higher flow rates of 1 column volume per minute. The, on lab-scale, calibrated model allows predicting elution volume and impurity removal for large-scale experiments in a commercial plant processing over 106 liters of milk per day. The successful model extrapolation was possible without recalibration or detailed knowledge of the manufacturing plant. This study therefore provides a possible pathway for rapid process development of chromatographic purification in the food industries combining traditional scale-down experiments with mechanistic modeling.

Design and optimization of membrane chromatography for monoclonal antibody charge variant separation

The manufacturing scale implementation of membrane chromatography to purify monoclonal antibodies has gradually increased with the shift in industry focus towards flexible manufacturing and disposable technologies. Membrane chromatography are used to remove process-related impurities such as host cell proteins and DNA, leachates and endotoxins, with improved productivity and process flexibility. However, application of membrane chromatography to separate product-related variants such as charge variants has not gained major traction due to low binding capacity. The work reported here demonstrates that a holistic process development strategy to optimize static binding (pH and salt concentration) and dynamic process (membrane loading, flowrate, and gradient length) parameters can alleviate the capacity limitations. The study employed high throughput screening tools and scale-down membranes for intermediate and polishing purification of the model monoclonal antibody. An optimized process consisting of anion exchange and cation exchange membrane chromatography reduced the acidic variants present in Protein A eluate from 89.5 % to 19.2 % with 71 % recovery of the target protein. The membrane chromatography process also cleared host cell protein to below limit of detection with 6 to 30-fold higher membrane loading, compared to earlier reported values. The results confirm that membrane chromatography is effective in separating closely related product variants when supported by a well-defined process development strategy.

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.

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

Fluctuations of the inlet feed stream concentration are a challenge in controlling continuous multi-column counter current chromatography systems with standard methods. We propose a new control strategy based on calculated product column breakthrough from UV sensor signals by neglecting an impurity baseline and instead using the impurity to product ratio. This calculation is independent of the inlet feed concentration. In-silico simulation showed that the proposed method can calculate the product column breakthrough perfectly even with fluctuating and highly unstable inlet feed concentration during a loading cycle. Applying the proposed method to control a three column periodic counter current chromatography process with fluctuating inlet feed concentration resulted in constant column loading in each cycle, while using the standard method failed to do so. Unavoidable band broadening caused by diffusion and dispersion has been identified as an inherent limiting factor for accurate calculation of column breakthrough comparing inlet and outlet UV signals. The proposed advanced calculations increase the robustness of periodic counter current chromatography and extend the capability to process unstable inlet streams.

Comparative evaluation of integrated purification pathways for bacterial modular polyomavirus major capsid protein VP1 to produce virus-like particles using high throughput process technologies

Modular virus-like particles and capsomeres are potential vaccine candidates that can induce strong immune responses. There are many described protocols for the purification of microbially-produced viral protein in the literature, however, they suffer from inherent limitations in efficiency, scalability and overall process costs. In this study, we investigated alternative purification pathways to identify and optimise a suitable purification pathway to overcome some of the current challenges. Among the methods, the optimised purification strategy consists of an anion exchange step in flow through mode followed by a multi modal cation exchange step in bind and elute mode. This approach allows an integrated process without any buffer adjustment between the purification steps. The major contaminants like host cell proteins, DNA and aggregates can be efficiently removed by the optimised strategy, without the need for a size exclusion polishing chromatography step, which otherwise could complicate the process scalability and increase overall cost. High throughput process technology studies were conducted to optimise binding and elution conditions for multi modal cation exchanger, Capto™ MMC and strong anion exchanger Capto™ Q. A dynamic binding capacity of 14 mg ml⁻¹ was achieved for Capto™ MMC resin. Samples derived from each purification process were thoroughly characterized by RP-HPLC, SEC-HPLC, SDS-PAGE and LC-ESI-MS/MS Mass Spectrometry analytical methods. Modular polyomavirus major capsid protein could be purified within hours using the optimised process achieving purities above 87% and above 96% with inclusion of an initial precipitation step. Purified capsid protein could be easily assembled in-vitro into well-defined virus-like particles by lowering pH with addition of calcium chloride to the eluate. High throughout studies allowed the screening of a vast design space within weeks, rather than months, and unveiled complicated binding behaviour for Capto^TM MMC.