Efficient bioprocess characterization is essential for both regulatory compliance and commercial viability of biologics. Traditional approaches using resolution III/IV screening designs followed by response surface methodology are time-consuming, costly, and not always effective in identifying the important experimental effects. Definitive screening designs (DSDs) represent a novel class of three-level screening designs that can simultaneously evaluate main effects and quadratic relationships. While DSDs are increasingly used in bioprocess development, practical implementation guidelines remain limited. This case study bridges this gap by introducing a model-based framework to identify critical process parameters (CPPs) and optimize operating ranges for robust biologics production using plasmid DNA (pDNA). Minimal 14-run DSDs evaluated six input parameters and successfully identified CPPs and optimal operating ranges. This approach reduces experimental requirement by >50% compared to traditional designs, providing an efficient and economical strategy for bioprocess characterization and optimization.
Category: <span>Analytics</span>
This study assessed a novel statistical approach using space-filling designs (SFDs) and self-validating ensemble modeling (SVEM) machine learning to efficiently identify key process factors using recombinant adeno-associated virus type 9 (rAAV9) gene therapy manufacturing as a case study. Based on risk assessment of parameters that may impact rAAV9 production, we have evaluated six process parameters using 24-run SFDs generated by the JMP statistical software. SFDs are a new class of design of experiment (DoE) created with the objective of covering the entire design space as completely as possible; this in turn allows more accurate modeling of complex response surface behavior typically found in bioprocesses.
The price per patient for protein-based and monoclonal antibody (mAb) therapies runs into thousands of dollars per patient each year. These therapies cost considerably more to manufacture than small molecules. Hence, if mammalian or insect cell lines expressing high protein titres can be selected and optimized for protein expression using microscale bioreactor models early in development, then manufacturing costs can be reduced significantly…
Extracellular vesicles (EVs) are particles of varying size, structure, and composition, which are secreted from cells and frequently mediate intercellular communication. Because they have been shown to travel through the circulatory system and also through biological barriers to deliver their molecular contents to distant target cells, there has been growing interest in using EVs, such as exosomes, as drug delivery vehicles. In the past ten years, the number of published articles linking EVs to drug delivery has increased 20-fold. EVs are being engineered to deliver protein, RNA, and small molecule cargo to target cells, tissues, and entire systems. Also, EVs derived from certain cells show inherent, therapeutically beneficial activity.
Agarose-based chromatography beads were first introduced by Stellan Hjertén in 1962. Fifty years later, beaded agarose has become the dominant resin for protein purification and is extensively used, ranging from research-scale in sub mL volumes to full-scale manufacturing in > 500 L chromatography columns. Recent resin development work has focused on increasing capacity and selectivity through different grafting technologies and ligand developments.
Human granulocyte colony-stimulating factor (GCSF) is produced by biotech laboratories and production facilities for reducing neutropenia duration and sequels in patients with myelosuppressor treatments, among other applications. However, real challenges for these laboratories started in 2015 when the PEGylated-GCSF patent expired, opening alternatives for developing biomanufacturing processes and new applications. Thus, the purpose of this study was to analyze downstream process controls designed to ensure recombinant human GCSF (rh-GCSF) quality and to provide some evidence of the downstream process validation status. Study outcomes proved that the rh-GCSF expression system was stable and chromatographic profiles were reproducible among samples.
Cation exchange chromatography is typically utilized in bind-and-elute mode for monoclonal antibody purification. However, during purification process development for a novel monoclonal antibody (MAb) intended for clinical use, it was determined that bind-and-elute conditions were not sufficient for removing significant levels of antibody aggregate. Based on preliminary purification data, an alternative purification method, operation of the cation exchange process in flow-through mode, was investigated.
Raman spectroscopy offers an attractive solution for monitoring key process parameters and predictive modelling in cell culture processes using transgenic Chinese hamster ovary (CHO) cells. Frequent in-line measurements offer the potential for advanced control strategies. However, an erroneous value created by analytical signal noise is a significant issue that can affect process controls negatively. One such challenge is to differentiate the signal reflecting process changes, ranging from random to gross error, in a timely manner so the process control system can respond to these changes and maintain adequate control.