BioProcessing Journal Posts

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

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 ā€œself-validating ensemble modeling (SVEM)ā€ 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

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

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 ā€œback of an envelopeā€ 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 BioPATĀ® 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

SARS-CoV-2 is an enveloped, positive-strand RNA virus that contains four structural proteins: spike, envelope, membrane, and nucleocapsid (N-protein). The N-protein participates in virus RNA packaging and particle release, is conserved within SARS-CoV-2 isolates, is highly immunogenic, and is abundantly expressed during SARS-CoV-2 infection. For these reasons, the N-protein could be used as a marker for detecting SARS-CoV-2 in early infection when antibodies against SARS-CoV-2 have not been produced yet. This paper describes the production and characterization of mouse monoclonal antibodies (mAb) and rabbit polyclonal antibodies (pAb) specific for the M20P19 peptide (N-protein linear epitope) for detection purposes. For this study, B-cell hybridomas were generated from mice independently immunized with two different M20P19 peptide-carrier protein conjugates: (1)Ā meningococcal protein P64K; and (2)Ā the keyhole limpet hemocyanin (KLH). Rabbits were also independently immunized with these two immunogens. Study results demonstrated that the M20P19 peptide was very immunogenic in mice and rabbits, and both mAb and pAb specifically recognized the non-conjugated M20P19 peptide, conjugated M20P19 peptide, and N-protein with high affinity and specificity, which could allow SARS-CoV-2 detection by different analytical techniques. This study corroborated that specific and high affinity constant mAb and pAb against the M20P19 peptide can be used as biological reagents for specific and rapid SARS-CoV-2 detection, mainly in tissue samples.

Biologics Production

In-line conditioning (IC) is a form of dilution where a process buffer is formulated in-line from concentrated stock solutions of acids, bases, and salts that are mixed with the correct amount of water-for injection (WFI). This new buffer preparation strategy must prove its equivalency to buffers made the traditional way (i.e., weighing salts, stirring in water, titrating with acid or base). In this paper, such a demonstration is presented using two control modes: (1) ratio control with flow feedback; and (2) pH/conductivity feedback. To obtain the necessary parameters for an error propagation analysis, a robustness study has been performed. Our analysis showed that with low incoming variability, or when the uncertainty of the stock solutions is below 2%, the two modes of control give comparable performance. When the uncertainty increases, so does the uncertainty of ratio control with flow feedback, more with respect to conductivity than pH, while the precision of pH/conductivity feedback remains at the same level. The choice of control should therefore take into consideration the critical process parameters, their tolerances, and the input variability in the stock solution concentration. In situations where there are higher variabilities in stock solution concentrations or process temperatures, this study suggests that pH/conductivity feedback might be a better option.

Biologics Production

A perfusion approach at N-1, where cells stay in the exponential growth phase throughout the entire culture duration, is becoming more common as a strategy for process intensification. This is because the higher cell densities it generates allows manufacturers to skip seed stages and reduce process transfer time through multiple bioreactor sizes, thus providing more cost-effective biologics production in smaller facilities. However, this N-1 perfusion approach requires optimization. In this article, we describe the development and proof-of-concept studies with single-use rocking motion perfusion bioreactors in which we have achieved a ten-fold increase in viable cell count in N-1 seed stage, compared to the fed-batch control process, in just 6ā€“8 days. We also mention in detail how we inoculated a 50 L bioreactor production run using this intensified seed train and show comparable growth kinetics and yield with a control process, also at 50 L scale. Using this intensification approach in the future will help our manufacturing facility, the Biopharma Division of Intas Pharmaceuticals Ltd., reach 4000 L production-scale volumes with fewer process transfer steps, and without changing the feeding strategy or production bioreactors of our biologicsā€™ portfolio.


Tissue-derived products are a class of biological materials harvested directly from animal or human tissue, in contrast to recombinant DNA materials grown in cell culture bioreactors. Tissue-derived products are often used for structural purposes and are typically regulated as medical devices. However, when used to treat human patients, tissue-derived products are subject to many of the same concerns as recombinant DNA biotherapeutics, with viral safety being one of them. To address this, the tissue source material must undergo a risk analysis and testing regimen for the presence of viral contaminants. In addition, viral clearance studies must be performed to evaluate whether the purification process is robust enough to remove and/or inactivate viruses that may be present in the starting material.

The goals of viral clearance studies are the same for tissue-derived products and biotherapeutics, but the design and performance of these studies can be quite different because of the diverse nature of the materials. In this article, we will present an overview of viral clearance studies for tissue-derived products based on our experience in performing a large number of such studies. Rather than discussing the issues related to viral clearance in general, our focus will be on the unique challenges that tissue-derived products pose.

Biologics Production Regulatory Risk Analysis and Management

Due to its antioxidant properties and favorable safety profile, glutathione (GSH) finds use in protein formulations by improving overall protein stability. Once degraded, primarily by oxidation into glutathione disulfide (GSSG), the protecting effect of GSH is lost. A simple, direct method using reversed-phase separation and charged-aerosol detection (RP-CAD) to quantitate GSH is described in this paper. The analytical methodology is also capable of monitoring several by-product degradants of GSH, both oxidative and non-oxidative. For high-concentration protein formulations, the method provides direct analysis of GSH and its degradants in the presence of protein at up to 225 mg/mL simply through a dilution of the sample. Quantitation of many amino acids typically included in pharmaceutical protein formulations is also possible. Use of an online diverting valve in the method prevents interference in the detector from the high protein concentration in formulation. Accuracy and effectiveness of this method is demonstrated through monitoring the stability of GSH in high-concentration protein formulations through confirmation of GSH concentration and mass-balance of its loss over time. Monitoring GSH stability in protein formulations is necessary, as GSH concentration is indicative of protein stability.

Biologics Production

NOTE: Page 7 of this article has been revised to correct an error in the original article which stated that “..the probability of failing a lot when it actually is not equivalent, becomes 1-2*α.” The correct equation, 1-α, has replaced the errant one and a single sentence following it was added to further clarify this concept.

ABSTRACT: Pre-clinical and clinical trials conducted to establish the minimum effective dose and the maximum tolerated dose of a viral vector assume that the assigned dose values are comparable across studies. Toxicity has been associated with high dose administration of both adenovirus and adeno-associated virus-based vectors, and increased attention must be paid to assays used to measure dose. High assay variability can be mitigated by replication and the reporting of a mean value for product lot release. The establishment of a dose specification and a testing strategy must take into account the risk of errant quality control decisions. This can be accomplished by linking assay qualification information to measurement uncertainty through a statistical framework. By adopting an equivalence approach, the risk of releasing lots with unacceptably high or low dose values is minimized by reducing measurement uncertainty. This article provides a worked-through example to introduce applicable statistical concepts and the equations necessary to facilitate their implementation in the field.

Risk Analysis and Management Viral Vectors