Monitoring bioactive and total antibody concentrations for continuous process control by surface plasmon resonance spectroscopy

摘要

Monoclonal antibodies have become an increasingly important part of fundamental research and medical applications. To meet the high market demand for monoclonal antibodies in the biopharmaceutical sector, industrial manufacturing needs to be achieved by large scale, highly productive and consistent production processes. These are subject to international guidelines and have to be monitored intensely due to high safety standards for medical applications. Surface plasmon resonance spectroscopy — a fast, real‐time, and label‐free bio‐sensing method — represents an interesting alternative to the quantification of monoclonal antibody concentrations by enzyme‐linked immunosorbent assay during monoclonal antibody production. For the application of monitoring bioactive and total monoclonal antibody concentrations in cell culture samples, a surface plasmon resonance assay using a target‐monoclonal antibody model system was developed. In order to ensure the subsequent detection of bioactive monoclonal antibody concentrations, suitable immobilization strategies of the target were identified. A significant decrease of the limit of detection was achieved by using an adapted affinity method compared to the commonly used amine coupling. Furthermore, the system showed limit of detection in the low ng/mL range similar to control quantifications by enzyme‐linked immunosorbent assay. Moreover, the comparison of total to bioactive monoclonal antibody concentrations allows analysis of antibody production efficiency. The development of an alternative quantification system to monitor monoclonal antibody production was accomplished using surface plasmon resonance with the advantage of low analyte volume, shorter assay time, and biosensor reusability by target‐layer regeneration. The established method provides the basis for the technical development of a surface plasmon resonance‐based system for continuous process monitoring.