Dielectric Spectroscopy to Improve the Production of rAAV Used in Gene Therapy

• Published in: Processes Vol. 8; no. 11; p. 1456
• Main Authors: Pais, Daniel A. M., Brown, Chris, Neuman, Anastasia, Mathur, Krishanu, Isidro, Inês A., Alves, Paula M., Slade, Peter G.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2020
• Subjects: Artificial chromosomes; Baculovirus; Bioreactors; Cell culture; Control theory; Correlation coefficients; Cryopreservation; Diameters; Dielectrics; E coli; Feedback loops; Gene expression; Gene therapy; Infections; Insects; Manufacturing; Mathematical models; Monitoring; Pharmaceutical industry; Physiology; Prediction models; Process parameters; Product quality; Real time; Regression analysis; Regulatory approval; Spectroscopy; Spectrum analysis; Technology assessment; Vectors (Biology); Viruses; United States > US
• ISSN: 2227-9717; 2227-9717
• DOI: 10.3390/pr8111456

The insect cell-baculovirus expression vector system is an established method for large scale recombinant adeno-associated virus (rAAV) production, largely due to its scalability and high volumetric productivities. During rAAV production it is critical to monitor process parameters such as Spodoptera frugiperda (Sf9) cell concentration, infection timing, and cell harvest viabilities since they can have a significant influence on rAAV productivity and product quality. Herein we developed the use of dielectric spectroscopy as a process analytical technology (PAT) tool used to continuously monitor the production of rAAV in 2 L stirred tank bioreactors, achieving enhanced control over the production process. This study resulted in improved manufacturing robustness through continuous monitoring of cell culture parameters, eliminating sampling needs, increasing the accuracy of infection timing, and reliably estimating the time of harvest. To increase the accuracy of baculovirus infection timing, the cell growth/permittivity model was coupled to a feedback loop with real-time monitoring. This system was able to predict baculovirus infection timing up to 24 h in advance for greatly improved accuracy of infection and ensuring consistent high rAAV productivities. Furthermore, predictive models were developed based on the dielectric measurements of the culture. These multiple linear regression-based models resulted in correlation coefficients (Q2) of 0.89 for viable cell concentration, 0.97 for viability, and 0.92 for cell diameter. Finally, models were developed to predict rAAV titer providing the capability to distinguish in real time between high and low titer production batches.