Dielectric Spectroscopy and Optical Density Measurement for the Online Monitoring and Control of Recombinant Protein Production in Stably Transformed Drosophila melanogaster S2 Cells

The production of recombinant proteins in bioreactors requires real-time process monitoring and control to increase process efficiency and to meet the requirements for a comprehensive audit trail. The combination of optical near-infrared turbidity sensors and dielectric spectroscopy provides diverse system information because different measurement principles are exploited. We used this combination of techniques to monitor and control the growth and protein production of stably transformed Drosophila melanogaster S2 cells expressing antimicrobial proteins. The in situ monitoring system was suitable in batch, fed-batch and perfusion modes, and was particularly useful for the online determination of cell concentration, specific growth rate (µ) and cell viability. These data were used to pinpoint the optimal timing of the key transitional events (induction and harvest) during batch and fed-batch cultivation, achieving a total protein yield of ~25 mg at the 1-L scale. During cultivation in perfusion mode, the OD880 signal was used to control the bleed line in order to maintain a constant cell concentration of 5 × 107 cells/mL, thus establishing a turbidostat/permittistat culture. With this setup, a five-fold increase in productivity was achieved and 130 mg of protein was recovered after 2 days of induced perfusion. Our results demonstrate that both sensors are suitable for advanced monitoring and integration into online control strategies

REAL-TIME MONITORING OF CELL DEATH PROGRESS USING CAPACITANCE SPECTROSCOPY

Biologics, including the monoclonal antibody (mAb), has experienced rapid development in the last decade. However, the price of biologics is often prohibitively high because of the low process efficiency. Delaying the inevitable cell death improves the productivity of upstream bioprocessing, whose success relies on monitoring the cell death onset that indicates the timing for preventive actions. This study proposes to develop a real-time monitoring model that quantifies the dying cell percentage in lab-scale bioreactors using capacitance spectroscopy. The capacitance spectroscopy contains cell death-related information due to various physical properties changes during the cell death process, e.g., cytoplasmic conductivity change. The partial least square (PLS) regression algorithm constructed the model between the normalized capacitance spectra and dying cell percentages measured by flow cytometry. Samples following an orthogonal calibration design were prepared to build an at-line model, which was then transferred to the in-line monitoring condition to achieve real-time monitoring. The global calibration method was applied during the calibration transfer process to alleviate the difference between the at-line and in-line monitoring conditions. Furthermore, orthogonalization preprocessed the capacitance spectra, improving the model performance and mitigating the undesired prediction fluctuation due to process operations. The resulted model had a low Root Mean Square Error of Prediction, suggesting a good prediction accuracy. Additionally, the trajectory described by the final model captured the cell death onset hours earlier than the traditional viability test, providing a time window for subsequent preventive actions

Development of advanced monitoring and control tools for rAAV production in the insect cell system

"Since the first publication introducing the concept in 1972, gene therapy has had a series of success stories and setbacks. However, the recent rise of awareness, public interest, promising results in clinical trials and recent market approvals indicate that gene therapy has come to stay. Currently there is a growing interest from the biopharmaceutical industry in gene and cell therapy, mostly using viral vectors. (...)