Application of dielectric spectroscopy for monitoring high cell density in monoclonal antibody producing CHO cell cultivations

• Published in: Bioprocess and biosystems engineering Vol. 37; no. 2; pp. 311 - 323
• Main Authors: Párta, László, Zalai, Dénes, Borbély, Sándor, Putics, Ákos
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2014; Springer Nature B.V
• Subjects: Animals; Antibodies, Monoclonal - biosynthesis; Biotechnology; Cells; Chemistry; Chemistry and Materials Science; CHO Cells; Cricetinae; Cricetulus; Cultivars; Cultivation; Density; Dielectric properties; Environmental Engineering/Biotechnology; Food Science; Industrial and Production Engineering; Industrial Chemistry/Chemical Engineering; Monoclonal antibodies; Multivariate Analysis; Original Paper; Principal Component Analysis; Principal components analysis; Spectroscopy; Spectrum analysis; Spectrum Analysis - methods; Mathematical pre-treatments; Dielectric spectroscopy; Monoclonal antibody production; PLS; Concentrated fed-batch (CFB) process; Cole–Cole modeling; PCA
• ISSN: 1615-7591; 1615-7605
• DOI: 10.1007/s00449-013-0998-z

The application of dielectric spectroscopy was frequently investigated as an on-line cell culture monitoring tool; however, it still requires supportive data and experience in order to become a robust technique. In this study, dielectric spectroscopy was used to predict viable cell density (VCD) at industrially relevant high levels in concentrated fed-batch culture of Chinese hamster ovary cells producing a monoclonal antibody for pharmaceutical purposes. For on-line dielectric spectroscopy measurements, capacitance was scanned within a wide range of frequency values (100–19,490 kHz) in six parallel cell cultivation batches. Prior to detailed mathematical analysis of the collected data, principal component analysis (PCA) was applied to compare dielectric behavior of the cultivations. PCA analysis resulted in detecting measurement disturbances. By using the measured spectroscopic data, partial least squares regression (PLS), Cole–Cole, and linear modeling were applied and compared in order to predict VCD. The Cole–Cole and the PLS model provided reliable prediction over the entire cultivation including both the early and decline phases of cell growth, while the linear model failed to estimate VCD in the later, declining cultivation phase. In regards to the measurement error sensitivity, remarkable differences were shown among PLS, Cole–Cole, and linear modeling. VCD prediction accuracy could be improved in the runs with measurement disturbances by first derivative pre-treatment in PLS and by parameter optimization of the Cole–Cole modeling.