Quality by Design characterization of the perfusion culture process for recombinant FVIII

An innovative hybrid modeling approach for simultaneous prediction of cell culture process dynamics and product quality

The use of hybrid models is extensively described in the literature to predict the process evolution in cell cultures. These models combine mechanistic and machine learning methods, allowing the prediction of complex process behavior, in the presence of many process variables, without the need to collect a large amount of data. Hybrid models cannot be directly used to predict final product critical quality attributes, or CQAs, because they are usually measured only at the end of the process, and more mechanistic knowledge is needed for many classes of CQAs. The historical models can instead predict the CQAs better; however, they cannot directly relate manipulated process parameters to final CQAs, as they require knowledge of the process evolution. In this work, we propose an innovative modeling approach based on combining a hybrid propagation model with a historical data-driven model, that is, the combined hybrid model, for simultaneous prediction of full process dynamics and CQAs. The performance of the combined hybrid model was evaluated on an industrial dataset and compared to classical black-box models, which directly relate manipulated process parameters to CQAs. The proposed combined hybrid model outperforms the black-box model by 33% on average in predicting the CQAs while requiring only around half of the data for model training to match performance. Thus, in terms of model accuracy and experimental costs, the combined hybrid model in this study provides a promising platform for process optimization applications.

Current challenges and recent advances on the path towards continuous biomanufacturing

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.

Optimization of an adenovirus-vectored zoster vaccine production process with chemically defined medium and a perfusion system

OBJECTIVES

Cells grown in chemically defined medium are sensitive to shear force, potentially resulting in decreased cell growth. We optimized the perfusion process for HEK293 cell-based recombinant adenovirus-vectored zoster vaccine (Ad-HER) production with chemically defined medium.

METHODS

We first studied the pseudo-continuous strategies in shake flasks as a mimic of the bioreactor equipped with perfusion systems. Using design of experiment (DoE) in shake flasks, we obtained the regression models between Ad-HER titer/virus input-output ratio and three production process parameters: time of infection (TOI), multiplicity of infection (MOI), and virus production pH (pH). We then confirmed the effect of Pluronic F68 (PF-68) at 3.0 g/L on HEK293 cell growth and Ad-HER production in shake flasks and a 2 L benchtop bioreactor.

RESULTS

The optimized process was scale-up to a 2 L benchtop bioreactor with the PATFP perfusion system, which yielded cell density of 7.4 × 10⁶ cells/mL and Ad-HER titer of 9.8 × 10⁹ IFU/mL at 2 dpi, comparable to the bioreactor with a ATF2 system.

CONCLUSION

This optimization strategy could be used to develop a robust process with stable cell culture performance and adenovirus titer. Increasing PF-68 concentration in chemically defined medium could protect cells from shear stress generated by perfusion system.

Perfusion culture of Chinese Hamster Ovary cells for bioprocessing applications

Much of the biopharmaceutical industry's success over the past 30 years has relied on products derived from Chinese Hamster Ovary (CHO) cell lines. During this time, improvements in mammalian cell cultures have come from cell line development and process optimization suited for large-scale fed-batch processes. Originally developed for high cell densities and sensitive products, perfusion processes have a long history. Driven by high volumetric titers and a small footprint, perfusion-based bioprocess research has regained an interest from academia and industry. The recent pandemic has further highlighted the need for such intensified biomanufacturing options. In this review, we outline the technical history of research in this field as it applies to biologics production in CHO cells. We demonstrate a number of emerging trends in the literature and corroborate these with underlying drivers in the commercial space. From these trends, we speculate that the future of perfusion bioprocesses is bright and that the fields of media optimization, continuous processing, and cell line engineering hold the greatest potential. Aligning in its continuous setup with the demands for Industry 4.0, perfusion biomanufacturing is likely to be a hot topic in the years to come.

Critical Analysis of cGMP Large-Scale Expansion Process in Bioreactors of Human Induced Pluripotent Stem Cells in the Framework of Quality by Design

Human induced pluripotent stem cells (hiPSCs) are manufactured as advanced therapy medicinal products for tissue replacement applications. With this aim, the feasibility of hiPSC large-scale expansion in existing bioreactor systems under current good manufacturing practices (cGMP) has been tested. Yet, these attempts have lacked a paradigm shift in culture settings and technologies tailored to hiPSCs, which jeopardizes their clinical translation. The best approach for industrial scale-up of high-quality hiPSCs is to design their manufacturing process by following quality-by-design (QbD) principles: a scientific, risk-based framework for process design based on relating product and process attributes to product quality. In this review, we analyzed the hiPSC expansion manufacturing process implementing the QbD approach in the use of bioreactors, stressing the decisive role played by the cell quantity, quality and costs, drawing key QbD concepts directly from the guidelines of the International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use.

A novel approach to residence time distribution characterization in a mAb continuous process

Residence time distribution modeling of integrated perfusion to capture process can elucidate the impact of product quality excursions and filter fouling on monoclonal antibody production. In this case study, a glycosylation inhibitor and fluorescently labeled antibody are applied to the continuous process to study protein quality modulation, perfusion filter fouling, and unit operation hold times. The unit operations were modeled as continuous-stirred tank reactors and the residence time distribution of a small molecule glycan inhibitor and impact on glycosylation were characterized. A fluorescently labeled antibody was applied as a tracer molecule and confirmed the impact of packed cell volume and filter fouling. This study demonstrates how a biologics continuous process can be modeled and characterized through residence time distribution to ensure a robust, well-understood process.