BioProcessing Journal

The Impact of Process Closure on Biomanufacturing Risk

“Closed system.” The term itself appears deceptively simple. However, the definition of a closed system, its implementation, and its impact on biomanufacturing has been anything but straightforward.

The journey toward implementing closed systems spans over 20 years. The concept of closed systems was introduced in January 2000 with the draft issue of ICH Q7. Since then, other industry guidance documents emerged, defining and supporting process/system closure as a primary means of risk mitigation to meet the baseline requirement of protecting the product, as defined in cGMP.

Presently, global regulatory agencies recognize three distinct definitions of a closed system. These definitions, found in EU Annex 1, EU Annex 2, and the PIC Annex 2A, all focus on product protection where the product is not exposed to the immediate room environment during manufacturing. This is where the journey begins.

Manufacturing Risk Analysis and Management

closed system contaminant control cost reduction facility design GMP process closure

Article Preview: Practical Considerations in Using an Equivalence Approach to Establish Lot Release Limits for Vector Dose

The approval of several gene therapy products and gene-modified cell therapies over the last five years has led to increasing numbers of investigational new drug applications (INDs) using adeno-associated and lentiviral vectors. However, these successes have been tempered by the risks of dose-related toxicities. The therapeutic window for a product is derived from pre-clinical and clinical dose response models, which assume statistically that measurements of dose are exact. Whether vector is administered directly or used as a critical reagent to prepare a gene-modified cellular product, the assignment of a label concentration to a vector batch is critical for establishing consistency of product used in preclinical and clinical development.

Risk Analysis and Management Viral Vectors

coefficient of determination confidence interval consistency dosage lot release

Gamma-Immunoglobulin Response Characterization, in COVID-19 Convalescent Patients, Against the Spike Protein S2 Subunit with Eight Linear Peptides for Monoclonal Antibody Generation

The SARS-CoV-2 spike protein S2 subunit plays an essential role in the virus-host cell membrane fusion process. Therefore, the subject of this study was to characterize the gamma-immunoglobulin (IgG) response, in a group of COVID-19 convalescent patients, against the S2 subunit with eight linear peptides to generate a monoclonal antibody (mAb) against the immunodominant linear peptide to be used for therapeutic and diagnostic purposes. Results of antibody percentages against assessed linear peptides were 100% for A21P73, A21P74, A21P75, A21P76, M20P51, M20P65, M20P83, and 66.7% for M20P85. Plasma samples were also used for purifying IgG to corroborate specificity against the same linear peptides, where results reproduced those applying plasmas directly to ELISA-plates. Within these peptides, A21P75 was chosen as immunodominant (100% of recognition with higher absorbance). The A21P75 linear peptide showed poor immunogenicity in mice (1:4000–8000 after four doses), allowing the generation of a CB.HS2A21P75 hybridoma for mAb production that recognized the A21P75 linear peptide with middle-to-high affinity constant (K_aff) (0.8×10⁸ M^-1).

This study concludes that the A21P75 linear peptide is the assessed immunodominant linear peptide for this COVID-19 convalescent patient group. This peptide is located in the HR1 region that plays an important role in SARS-CoV-2 host cell membrane fusion process and is highly conserved between SARS-CoV-2 and SARS-CoV. Thus, due to CB.S2A21P75 mAb specificity and K_aff, it might be the proper reagent to study inhibition of virus-host cell membrane fusion, and as a diagnostic reagent for coronavirus. Finally, the combination of A21P75 linear peptide with other peptides (e.g., receptor binding domain [RBD]) could be suitable reagents for the development of vaccines and therapeutic antibodies with virus infection-blocking capacity.

Biologics Production

cell membrane fusion characterization gamma-immunoglobulin response inhibitory therapeutics linear peptide monoclonal antibody subunit

Human IgG Fc Production Through Methanol-Free Pichia pastoris Fermentation

Nowadays, therapeutic monoclonal antibodies (mAbs) are predominantly produced with mammalian cell culture systems such as those using Chinese hamster ovary (CHO) cells. Efforts are underway to reduce the costs of this process to meet the increasing global demand in biopharmaceuticals; meanwhile, cheaper and faster expression systems are being investigated as alternatives. The yeast, Pichia pastoris, has become a substantial workhorse for recombinant protein production. However, the N-linked glycosylation in P. pastoris, namely high mannose glycosylation, is significantly different from that in CHO or other mammalian cells, including human cells. In this study, a SuperMan5 strain of P. pastoris was constructed using Pichia GlycoSwitch® technology to successfully produce a more mammalian-like immunoglobulin G (IgG) fragment crystallizable (Fc), which showcases the potential of P. pastoris as a next-generation mAb production platform. Importantly, in this study, a strong methanol-independent promoter, P_UPP, was applied, which only requires glycerol feeding for protein production. Most P. pastoris promoters used for protein expression are derived from genes in the methanol metabolism pathway, creating safety concerns due to the flammable nature of methanol, especially at large scale. Here, a fed-batch SuperMan5 P. pastoris fermentation was carried out in which methanol induction, as well as its affiliated safety risks, were eliminated. Overall, this study provides insights into the development of safe and cost-effective industrial mAb production approaches independent of mammalian cell culture.

Biologics Production

antibody expression eukaryotic expression fermentation glycosylation mammalian-like glycosylation recombinant proteins

Demonstrating “Abdala” Subunit Vaccine Thermostability Study

From a regulatory standpoint, vaccine stability must be demonstrated, along with the prediction of stability during temperature excursions, before a vaccine can be approved for use in humans.

In this work, Abdala subunit vaccine thermostability was studied under thermal stress conditions (2–8°C [control], 25°C, 37°C, 45°C, and 60°C) for 15 days. Molecular integrity of the vaccine active pharmaceutical ingredient was monitored by SDS-PAGE, immunoblotting, RP-HPLC, mass spectrometry, and circular dichroism spectroscopy analysis. While functionality was monitored by immunogenicity assay, inhibition of binding between receptor-binding domain (RBD) and receptor, angiotensin converting enzyme 2 (ACE2), and RBD/ACE2 binding assay.

Results showed that no degradation, loss of disulfide bridges, nor modifications of secondary structure of the RBD molecule were detected at 25°C and 37°C. Moreover, high titers (1:48,853-1:427,849) of anti-RBD-specific mouse antibodies were detected with the ability to inhibit, to different degrees, the binding between RBD/ACE2.

In conclusion, the Abdala subunit vaccine is stable under thermal stress and storage conditions, which has an advantage over non-subunit vaccines previously approved or currently in development against COVID-19. The demonstrated high stability of this vaccine is a key factor in ensuring vaccine effectiveness, extending immunization coverage with fewer production runs, simplifying immunization logistics, and reducing cold chain-associated costs.

Biologics Production Regulatory

cold chain storage subunit vaccine thermal stress thermostability vaccines

Study of a Single-Use Stirred Tank Bioreactor for Manufacturing a Therapeutic Protein in a High Cell Density Microbial Fermentation

Stirred tank single-use bioreactors (SUBs) have been widely adopted for production of biopharmaceuticals such as monoclonal antibodies in mammalian cell culture. However, they are seldom used for commercial production of biologics with microbial fermentation. SUBs offer time-saving advantages because they do not require significant downtime for cleaning and sterilization, so finding a SUB that can perform well with high cell density microbial fermentation processes has the potential to increase the number of production runs. Therefore, for this study, a His-tagged protease inhibitor was chosen as a model protein to demonstrate that the Sartorius Biostat STR® MO, a SUB recently developed for microbial fermentation, is suited for recombinant protein production by high cell density Escherichia coli fermentation processes.

At 50 L scale, the SUB achieved good process control and allowed an oxygen uptake rate (OUR) of up to 240 mmoles/L/h. The fermentation runs produced up to 5.8 g/L of the soluble recombinant protein and a dry cell weight of >60 g/L at the end of fermentation. Additionally, the SUB showed a similar fermentation profile when compared with data from parallel runs in 15 L sterilise-in-place (SIP) vessels using identical media and process parameters. This study indicates that with a minimum investment of capital resources, stirred tank SUBs could be used in pilot-scale manufacturing with high cell density microbial fermentations to potentially shorten the timelines and costs of advancing therapeutic proteins to clinic.

Manufacturing

fermentation microbial fermentation recombinant proteins single-use bioreactor stirred-tank bioreactor therapeutic proteins

Robust and Scalable GMP Manufacturing of Chondrocyte Cell Therapy for Cartilage Regeneration

Cell therapy has emerged as a promising technology that involves implanting live cells to replace/repair and restore normal function of damaged tissue. Autologous chondrocyte implantation (ACI) has been proven effective for the regeneration of articular cartilage in defective cartilage tissue. The process starts with the collection of healthy tissue from an eligible patient, then isolation and expansion of desired cells in vitro under good manufacturing practice (GMP) conditions, qualification before release of the final cell product, and finally, implantation into the patient. The promise to deliver autologous cell therapies has its own challenges in robust and reproducible manufacturing. To commercialize a cell therapy, it is imperative that a robust and scalable manufacturing process is set up that is consistent, in terms of quality and quantity, in order to deliver the intended therapeutic effect.

We analysed the manufacturing parameters of over 100 cartilage samples that were used to deliver our proprietary, commercialized autologous cell therapy. The paper addresses the most cited challenges in the manufacturing of autologous cell therapies and describes a robust process of in vitro human chondrocyte cell culture. Also included are key factors in manufacturing for attaining a high-quantity and quality product for articular cartilage regeneration.

Cell & Gene Therapy Manufacturing

autologous cell therapy autologous chondrocyte implantation commercialization human chondrocyte cell culture raw materials qualification scalability

Optimization of a Conventional Glycosylation Analytical Method Using Machine Learning and Experimental Design

Glycosylation is one of the most common post-translational modifications in mammalian-expressed biologics, and is considered to be a critical quality attribute of therapeutic glycoproteins. Due to its biological relevance, physiochemical assessment on the glycosylation profile is always important to the success of a drug development initiative. This article describes the combination of experimental design and machine learning techniques applied to characterize and optimize a conventional, non-derivatized glycoprofiling method on glycans derived from a human immunoglobulin using high-performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD). Two independent experimental designs, a 16-run definitive screening design (DSD) and a 28-run central composite design (CCD), were incorporated with a machine learning technique known as “self-validating ensemble modeling (SVEM)” and used to build predictive models for four chromatographic responses. We show that the predictive models created using SVEM on the DSD data reliably predicted the behavior of the chosen responses when applied to CCD validation data. This demonstrates that the DSD is an efficient alternative to the larger, traditional CCD in which the combination of experimental design and machine learning can effectively characterize and optimize analytical methods.

Biologics Production

central composite design definitive screening design design of experiment glycosylation glycosylation profile high-performance anion exchange chromatography machine learning optimization

Separation of Empty and Full Adeno-Associated Virus Capsids from a Weak Anion Exchanger by Elution with an Ascending pH Gradient at Low Ionic Strength

Separation of empty and full AAV8 capsids was achieved during their elution from a weak anion exchanger with an ascending pH gradient at low conductivity. Experimental data suggest elution was mediated by loss of positive charge from the exchanger. The method produced a full capsid peak with fewer empty capsids than elution of a strong anion exchanger with a salt gradient. Elution of the weak exchanger by sodium chloride gradients or by pH gradients in the presence of sodium chloride gave inferior separation performance. Pre-elution of empty capsids with a pH step allowed full capsids to be eluted by salt without compromising separation. Loading at intermediate pH prevented empty capsid binding and enabled step elution of full capsids in a physiological buffer environment.

Biologics Production

adeno-associated virus anion exchange chromatography ascending pH gradient elution elution separation

A Novel, Risk-based Approach for Predicting the Optimum Set of Process and Cell Culture Parameters for Scaling Upstream Bioprocessing

The ability to scale a cell culture effectively and efficiently, from lab to manufacturing, is critical to maximizing productivity whilst minimizing the risk of run failures and delays that can cost millions of dollars per month. The task of scaling well, however, is still considered to be a challenge by many upstream scientists, and this can be an exercise in trial and error. Traditionally, scaling has most often been performed using arithmetic in a spreadsheet and/or simple “back of an envelope” calculations. For some, it may even come in the form of support from a team of data scientists using advanced analytical software. This dependency on what some consider to be complex mathematics or statistics has resulted in the common consideration of using just one scaling parameter at a time, one scale at a time.

However, it is difficult to determine easily or optimally, from the start, whether a process successfully transfers across scales based on only one process parameter, at one scale. In this article, we describe the benefits of using a risk-based approach to scaling, and the development of a software scaling tool known as BioPAT® Process Insights for predictive scale conversion across different bioreactor scales. BioPAT Process Insights can be used to consider multiple parameters and across multiple scales simultaneously, from the start of a scaling workflow. We briefly describe how it was used in a proof-of-concept scale-up study to allow a faster, more cost-effective process transfer from 250 mL to 2000 L. In summary, using BioPAT Process Insights, in conjunction with a bioreactor range that has comparable geometry and physical similarities across scales, has the potential to help biopharma manufacturing facilities reach 2000 L production-scale volumes with fewer process transfer steps, saving both time and money during scale-up of biologics and vaccines.

Manufacturing Risk Analysis and Management

cell culture data analysis process optimization risk-based scaling scale-up software upstream processing

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