Biotechnology Progress最新文献

Alzheimer's disease and other tauopathies are characterized by the misfolding and aggregation of the tau protein into oligomeric and fibrillar structures. Antibodies against tau play an increasingly important role in studying these neurodegenerative diseases and the generation of tools to diagnose and treat them. The development of antibodies that recognize tau protein aggregates, however, is hindered by complex immunization and antibody selection strategies and limitations to antigen presentation. Here, we have taken a facile approach to identify single-domain antibodies, or nanobodies, that bind to many forms of tau by screening a synthetic yeast surface display nanobody library against monomeric tau and creating multivalent versions of our lead nanobody, MT3.1, to increase its avidity for tau aggregates. We demonstrate that MT3.1 binds to tau monomer, oligomers, and fibrils, as well as pathogenic tau from a tauopathy mouse model, despite being identified through screens against monomeric tau. Through epitope mapping, we discovered binding epitopes of MT3.1 contain the key motif VQIXXK which drives tau aggregation. We show that our bivalent and tetravalent versions of MT3.1 have greatly improved binding ability to tau oligomers and fibrils compared to monovalent MT3.1. Our results demonstrate the utility of our nanobody screening and multivalent design approach in developing nanobodies that bind amyloidogenic protein aggregates. This approach can be extended to the generation of multivalent nanobodies that target other amyloid proteins and has the potential to advance the research and treatment of neurodegenerative diseases.

Amino acids are vital components of the serum-free medium that influence the expansion and function of NK cells. This study aimed to clarify the relationship between amino acid metabolism and expansion and cytotoxicity of NK cells. Based on analyzing the mino acid metabolism of NK-92 cells and Design of Experiments (DOE), we optimized the combinations and concentrations of amino acids in NK-92 cells culture medium. The results demonstrated that NK-92 cells showed a pronounced demand for glutamine, serine, leucine, and arginine, in which glutamine played a central role. Significantly, at a glutamine concentration of 13 mM, NK-92 cells expansion reached 161.9 folds, which was significantly higher than 55.5 folds at 2.5 mM. Additionally, under higher glutamine concentrations, NK-92 cells expressed elevated levels of cytotoxic molecules, the level of cytotoxic molecules expressed by NK-92 cells was increased and the cytotoxic rate was 68.42%, significantly higher than that of 58.08% under low concentration. In view of the close relationship between glutamine metabolism and intracellular redox state, we investigated the redox status within the cells. This study demonstrated that intracellular ROS levels in higher glutamine concentrations were significantly lower than those under lower concentration cultures with decreased intracellular GSH/GSSG ratio, NADPH/NADP⁺ ratio, and apoptosis rate. These findings indicate that NK-92 cells exhibit improved redox status when cultured at higher glutamine concentrations. Overall, our research provides valuable insights into the development of serum-free culture medium for ex vivo expansion of NK-92 cells.

Lung cancer has a high incidence rate and a low cure rate, hence the urgent need for effective treatment methods. Current lung cancer drugs have several drawbacks, including low specificity, poor targeting, drug resistance, and irreversible damage to normal tissues. Therefore, there is a need to develop a safe and effective new drug that can target and kill tumor cells. In this study, we combined nanotechnology and biotechnology to develop a CD133 ligand-modified etoposide-liposome complex (Lipo@ETP-CD133) for targeted therapy of lung cancer. The CD133 ligand targeted lung cancer stem cells, causing the composite material to aggregate at the tumor site, where high levels of ETP liposomes could exert a strong tumor-killing effect. Our research results demonstrated that this nano-drug had efficient targeting and tumor-killing effects, indicating its potential for clinical application.

Biopharmaceutical manufacturing entails a series of highly regulated steps. The manufacturing of safe and efficacious drug product (DP) requires testing of critical quality attributes (CQAs) against specification limits. DP potency concentration, which measures the dosage strength of a particular DP, is a CQA of great interest. In order to minimize the DP potency out-of-specification (OOS) risk, sterile fill finish (SFF) process adjustments may be needed. Varying the potency targets can be one such process adjustment. To facilitate such evaluation, data acquisition and statistical calculations are required. Regularly conducting the OOS risk assessment manually using commercial statistical software can be tedious, error-prone, and impractical, especially when several alternate potency targets are under consideration. In this work, the development of a novel framework for OOS risk assessment and deployment of cloud-based statistical software application to facilitate the risk assessment are presented. This application is intended to streamline the assessment of alternate potency targets for DP in biologics manufacturing. The major aspects of this potency targeting application development are presented in detail. Specifically, data sources, pipeline, application architecture, back-end and front-end development as well as application verification are discussed. Finally, several use cases are presented to highlight the application's utility in biologics manufacturing.

Advances in manufacturing technology coupled with the increased potency of new biotherapeutic modalities have created an external environment where continuous manufacturing (CM) can address a growing need. Amgen has successfully implemented a hybrid CM process for a commercial lifecycle program. In this process, the bioreactor, harvest, capture column, and viral inactivation/depth filtration unit operations were integrated together in an automated, continuous module, while the remaining downstream unit operations took place in stand-alone batch mode. CM operations are particularly suited for so-called “high mix, low volume” manufacturing plants, where a variety of molecules are manufactured in relatively low volumes. The selected molecule fit this mold and was manufactured in a low-capital micro-footprint suite attached to an existing therapeutic production facility. Use of a hybrid process within an already operating facility required less capital and minimized complexity. To enable this hybrid CM process, an established fed-batch process was converted to a perfusion process with continuous harvest. Development efforts included both process changes and the generation of a novel cell line adapted to long-term perfusion. Chromatography resins were updated, and purification processes adapted to handle variable inputs due to the fluctuations in harvest titer from the lengthy production process. A novel automated single-use (SU) viral inactivation (VI) skid was introduced, which entailed the development of a robust pH verification and alarm system, along with procedures for product isolation to allow discard of specific cycles. The CM process demonstrated consistent performance, meaning it met predefined performance criteria (including product quality attributes, or PQAs) when operated within established process parameters and manufactured according to applicable procedures. Using a 75% reduction in scale, it resulted in a five-fold reduction in process media and buffer usage, a fifteen-fold increase in mass per thaw, and an overall process productivity increase of 45-fold (as measured by grams drug substance per liter per day.) The hybrid CM process also enabled increased material demand to be met with no change in cost of goods manufactured or plant capacity, due to the repurposing of existing facility space and the flexible duration of the hybrid CM harvest. Overall, the success of the hybrid CM platform represents an exciting opportunity to reduce costs and increase process efficiency in industry.

Raman spectroscopy has been used to measure the concentration of a pharmaceutically relevant model amine intermediate for positive allosteric modulators of nicotinic acetylcholine receptor in a ω-transaminase-catalyzed conversion. A model based on a one-dimensional convolutional neural network was developed to translate raw data augmented Raman spectra directly into substrate concentrations, with which the conversion from ketone to amine by ω-transaminase could be determined over time. The model showed very good predictive capabilities, with R² values higher than 0.99 for the spectra included in the modeling and 0.964 for an independent dataset. However, the model could not extrapolate outside the concentrations specified by the model. The presented work shows the potential of Raman spectroscopy as a real-time monitoring tool for biocatalytic reactions.

Precipitation during the viral inactivation, neutralization and depth filtration step of a monoclonal antibody (mAb) purification process can provide quantifiable and potentially significant impurity reduction. However, robust commercial implementation of this unit operation is limited due to the lack of a representative scale-down model to characterize the removal of impurities. The objective of this work is to compare isoelectric impurity precipitation behavior for a monoclonal antibody product across scales, from benchtop to pilot manufacturing. Scaling parameters such as agitation and vessel geometry were investigated, with the precipitate amount and particle size distribution (PSD) characterized via turbidity and flow imaging microscopy. Qualitative analysis of the data shows that maintaining a consistent energy dissipation rate (EDR) could be used for approximate scaling of vessel geometry and agitator speeds in the absence of more detailed simulation. For a more rigorous approach, however, agitation was simulated via computational fluid dynamics (CFD) and these results were applied alongside a population balance model to simulate the trajectory of the size distribution of precipitate. CFD results were analyzed within a framework of a two-compartment mixing model comprising regions of high- and low-energy agitation, with material exchange between the two. Rate terms accounting for particle formation, growth and breakage within each region were defined, accounting for dependence on turbulence. This bifurcated model was successful in capturing the variability in particle sizes over time across scales. Such an approach enhances the mechanistic understanding of impurity precipitation and provides additional tools for model-assisted prediction for process scaling.

Two-dimensional electrophoresis (2DE) is a gel-based protein separation method based on size and charge which is commonly used for the characterization of host cell proteins (HCPs) during drug development in biotech and pharmaceutical companies. HCPs are a heterogenous mixture of proteins produced by host cells during a biologics drug manufacturing process. Different gel electrophoresis methods including traditional 2D SDS-PAGE with silver and SYPRO Ruby fluorescent dye staining as well as two-dimensional difference gel electrophoresis (2D-DIGE) were compared for their relative abilities to characterize HCPs. SYPRO Ruby was shown to be more sensitive than silver stain in the traditional 2D gels both with and without product protein present. Silver stain also displayed a significant preference for staining acidic proteins over basic ones while SYPRO Ruby was more consistent in imaging proteins across different isoelectric points. The non-traditional method of 2D-DIGE provides high resolution and reproducibility when comparing samples with similar protein profiles but was limited in imaging HCP spots due to its narrow dynamic range. Overall, 2DE is a powerful tool to separate and characterize HCPs and is optimized by choosing the best stain or method for each specific application. Using a combination of two or more different 2DE staining methods, when possible, provides the most comprehensive coverage to support the characterization of a complex mixture like HCPs. However, in instances where only one staining method can be used, SYPRO Ruby is shown to be the more reliable, more sensitive, and easier to use traditional staining method for most HCP-based applications.

Biopharmaceutical manufacture is transitioning from batch to integrated and continuous biomanufacturing (ICB). The common framework for most ICB, potentially enables a global biomanufacturing ecosystem utilizing modular and multi-function manufacturing equipment. Integrating unit operation hardware and software from multiple suppliers, complex supply chains enabled by multiple customized single-use flow paths, and large volume buffer production/storage make this ICB vision difficult to achieve with commercially available manufacturing equipment. Thus, we developed SymphonX™, a downstream processing skid with advanced buffer management capabilities, a single disposable generic flow path design that provides plug-and-play flexibility across all downstream unit operations and a single interface to reduce operational risk. Designed for multi-product and multi-process cGMP facilities, SymphonX™ can perform stand-alone batch processing or ICB. This study utilized an Apollo™ X CHO-DG44 mAb-expressing cell line in a steady-state perfusion bioreactor, harvesting product continuously with a cell retention device and connected SymphonX™ purification skids. The downstream process used the same chemistry (resins, buffer composition, membrane composition) as our historical batch processing platform, with SymphonX™ in-line conditioning and buffer concentrates. We used surge vessels between unit operations, single-column chromatography (protein A, cation and anion exchange) and two-tank batch virus inactivation. After the first polishing step (cation exchange), we continuously pooled product for 6 days. These 6 day pools were processed in batch-mode from anion exchange to bulk drug substance. This manufacturing scale proof-of-concept ICB produced 0.54 kg/day of drug substance with consistent product quality attributes and demonstrated successful bioburden control for unit-operations undergoing continuous operation.

Recent advances in messenger ribonucleic acid (mRNA) vaccines and gene therapy vectors have increased the need for rapid plasmid DNA (pDNA) screening and production within the biopharmaceutical industry. High-throughput (HT) fermentor systems, such as the Ambr® 250 HT, can significantly accelerate process development timelines of pDNA upstream processes compared to traditional bench-scale glass fermentors or small-scale steam-in-place (SIP) fermentors. However, such scale-down models must be qualified to ensure that they are representative of the larger scale process similar to traditional small-scale models. In the current study, we developed a representative scale-down model of a Biostat® D-DCU 30 L pDNA fermentation process in Ambr® 250 HT fermentors using three cell lines producing three different constructs. The Ambr scale-down model provided comparable process performance and pDNA quality as the 30 L SIP fermentation process. In addition, we demonstrated the predictive value of the Ambr model by two-way qualification, first by accurately reproducing the prior trends observed in a 30 L process, followed by predicting new process trends that were then successfully reproduced in the 30 L process. The representative and predictive scale-down Ambr model developed in this study would enable a faster and more efficient approach to strain/clone/host-cell screening, pDNA process development and characterization studies, process scale-up studies, and manufacturing support.