Depth filtration for clarification of intensified lentiviral vector suspension cell culture.

Depth filtration significantly impacts efficiency of lentiviral (LV) vector purification process. However, it is often deprioritized in the overall scope of viral vector manufacturing process optimization. The demand for LV vectors has increased with the rise in disease indications, making it crucial to improve current manufacturing processes. Upstream bioreactor process intensification has enabled cell densities of over 107 viable cells/mL, creating challenges for harvest unit operations. The larger size of LV vectors and their physiochemical similarity to host cell-DNA (HC-DNA) and poor clarification performance causes significant challenges for the subsequent chromatography-based purifications. As a result, a robust and scalable harvest of LV process is needed, especially for LV in vivo therapeutic quality needs. In this study, we systematically evaluated the overlooked yet important issue of depth filtration systems to improve enveloped LV functional vector recovery. We found that an established depth filtration system in process A that provided 94% (n = 6) LV functional recovery could not be translated to intensified Process B cell culture. Hence, the depth filtration process became a bottleneck for the purification performance in an intensified process. We demonstrated an improvement in LV functional vector recovery from 34% to 82% via filter train optimization for an intensified suspension cell culture system (>107 cells/mL with higher titer), while still maintaining a loading throughput of ≥82 L/m2 and turbidity ≤20 NTU. It was demonstrated that the two or three-stage depth filtration scheme is scalable and more suitable for high cell density culture for large scale for LV manufacturing process.

Control of antibody high and low molecular weight species by depth filtration-based cell culture harvesting.

Depth filtration-based harvesting is widely used in mAb manufacturing to remove cell and process-related impurities. However, it has not been studied on control of product-related impurities, which are very critical for product quality. In this article, we studied the interactions of depth filter with high and low molecular weight species (HMWs and LMWs) for their direct removal from cell culture. The process parameters (filter, loading, temperature, and flux) were evaluated for adsorption of HMWs and LMWs by depth filters. The adsorption is significantly dependent on filter media and loading capacity and is mainly on the basis of hydrophobic interaction during harvesting. The HMW and LMW species were characterized as HMW1, HMW2, LMW1, and LMW2. The increasing binding from LMW2 to LMW1, HMW1, and HMW2 is correlated with their increasing hydrophobicity score. Adsorption using enriched HMW sample demonstrated similar total protein binding capacity (36-40 g/m2 ) between depth filters D0HC and X0HC. However, X0HC has stronger HMW binding than D0HC (71% vs 43% of bound protein), indicating more hydrophobic interaction in X0HC. HMW2 DBC on X0HC reached 12 g/m2 , similar to protein binding on hydrophobic interaction membrane adsorbers. Further study showed LMW can induce HMW formation. This study provides a critical understanding of HMW and LMW interaction with depth filters. The strategy of HMW and LMW control by depth filtration-based harvesting was implemented successfully in mAb manufacturing.

Monoclonal antibody higher order structure analysis by high throughput protein conformational array.

The elucidation of antibody higher order structure (HOS) is critical in therapeutic antibody development. Since HOS determines the protein bioactivity and chemo-physical properties, this knowledge can help to ensure that the safety and efficacy attributes are not compromised. Protein conformational array (PCA) is a novel method for determining the HOS of monoclonal antibodies. Previously, we successfully utilized an enzyme-linked immunosorbent assay (ELISA)-based PCA along with other bioanalytical tools to elucidate the structures of antibody aggregates. In this study, applying a new multiplex-based PCA with 48-fold higher throughput than the ELISA-based one we revealed structural differences between different antibody molecules and antibody structure changes affected by various processing conditions. The PCA analysis of antibody molecules clearly demonstrated significant differences between IgG1 and IgG4 subclasses in epitope exposure and folding status. Furthermore, we applied small angle X-ray scattering to decipher mechanistic insights of PCA technology and validate structural information obtained using PCA. These findings enhance our fundamental understanding of mAbs' HOS in general. The PCA analysis of antibody samples from various processing conditions also revealed that antibody aggregation caused significantly higher exposure of antibody epitopes, which potentially led to a "foreign" molecule that could cause immunogenicity. The PCA data correlated well with protein stability results from traditional methods such as size-exclusion chromatography and protein thermal shift assay. Our study demonstrated that high throughput PCA is a suitable method for HOS analysis in the discovery and development of therapeutic antibodies.

A multikinetic model approach to predict gluconic acid production in an airlift bioreactor.

This paper uses a multikinetic approach to predict gluconic acid (GA) production performance in a 4.5 L airlift bioreactor (ALBR). The mathematical model consists of a set of simultaneous firstorder ordinary differential equations obtained from material balances of cell biomass, GA, glucose, and dissolved oxygen. Multikinetic models, namely, logistic and contois equations constitute kinetic part of the main model. The main model also takes into account the hydrodynamic and mass transfer parameters. These equations were solved using ODE solver of MATLAB v6.5 software. The mathematical model was validated with the experimental data available in the literature and is used to predict the effect of change in initial biomass and air sparging rate on the GA production. It is concluded that the mathematical model incorporated with multikinetic approach would be more efficient to predict the change in operating parameters on overall bioprocess of GA production in an ALBR.