Automated image processing as an analytical tool in cell cryopreservation for bioprocess development
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The continuous availability of cells with defined cell characteristics represents a crucial issue in the biopharmaceutical and cell therapy industry. Here, development of cell banks with a long-term stability is essential and ensured by a cryopreservation strategy. The strategy needs to be optimized for each cell application individually and usually comprises controlled freezing, storage at ultra-low temperature, and fast thawing of cells. This approach is implemented by the development of master and working cell banks. Currently, empirical cryopreservation strategy development is standard, but a knowledge-based approach would be highly advantageous. In this article, we report the development of a video-based tool for the characterisation of freezing and thawing behaviour in cryopreservation process to enable a more knowledge-based cryopreservation process development. A successful tool validation was performed with a model cryopreservation process for the β-cell line INS-1E. Performance was evaluated for two working volumes (1.0 mL and 2.0 mL), based on freezing-thawing rates (20 °C to − 80 °C) and cell recovery and increase of biomass, to determine tool flexibility and practicality. Evaluation confirmed flexibility by correctly identifying a delay in freezing and thawing for the larger working volume. Further more, a decrease in cell recovery from 0.94 (± 0.14) % using 1.0 mL working volume to 0.61 (± 0.05) % using a 2.0 mL working volume displays tool practicality. The video-based tool proposed in this study presents a powerful tool for cell-specific optimisation of cryopreservation protocols. This can facilitate faster and more knowledge-based cryopreservation process development
In this study, a video-based analytical tool was developed for the characterisation of freezing and thawing behaviour in cryopreservation process development. Evaluation of the practicality and flexibility of the developed tool was done based on a scale-up case study with the cell line INS-1E. Here, the influence of sample working volume on process performance was investigated. Increasing the volume from 1to 2 mL led to a delay in freezing and thawing behaviour which caused cell recovery loss. We believe that the developed tool will facilitate more directed and systematic cryopreservation process development.
KeywordsAutomated image processing Controlled freezing Cryopreservation Process development tool Thawing
Height to diameter ratio
Good manufacturing practice
We thank Prof. Hartwig and co-workers from the Institute of Food Chemistry at the Karlsruhe Institute of Technology (KIT) for sharing their labs and equipment and, additionally, the staff of the workshops form the Institute of Functional Interface and Institute for Inorganic Chemistry at the KIT for their assistance. We would also like to thank Prof. Maechler, from the Department of Cell Physiology and Metabolism at the University of Geneva Medical Centre, Switzerland for providing the rat beta-cell line INS-1E. This work was supported by the Helmholtz Program “BioInterfaces in Technology and Medicine (BIFTM).
Compliance with ethical standards
Conflict of interest
The authors have no conflicts to declare.
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