Over the past decade the bioprocessing industry has embraced and led the creation of a number of initiatives to drive process development and optimisation. There has consequently been an increased demand for tools capable of meeting the requirements of these initiatives. Spectroscopic monitoring systems such as Near infrared (NIR), Mid infrared (MIR) and Raman can provide a number of substantial advantages over more conventional off-line monitoring methods, normally applied to bioprocessing. With these techniques the bioprocessing industry has means of meeting these demanding challenges. The aim of study was to determine the feasibility of using NIR, MIR and Raman spectroscopy as a combined ‘toolkit’ to correlate changes in metabolic profile to spectral changes, within low passage Chinese Hamster Ovary cell cultures. The target metabolites focused upon in the spectroscopic analysis for this study were glucose and lactate. Conventional off-line techniques were used to investigate any correlation between spectral changes and those in the reference data. A design of experiment (DoE) approach was used to identify the optimum preprocessing techniques of the data and to build more accurate process trajectory models. These models were subjected to both an internal and external validation to guarantee the reliability of the results. Feasibility of data fusion, to create a single ‘fused’ dataset from the three spectroscopic techniques was also assessed, to produce a model with lower errors of prediction that the individual parts. The other area investigated was the characterisation of low passage number cultures in various media and process formats, which was of interest to the industrial collaborators. To test this three media; CD CHO, CD OptiCHO and Dynamis were provided by Thermo Fisher Scientific. Currently there is no system which utilises this toolkit with a combined DoE and data fusion strategy, within the bioprocessing industry.This research demonstrates a gap in the industry and a novel approach as to how tackle process monitoring. The results in this project demonstrate the varying degrees of success the spectroscopic techniques across all process formats and media. The NIR proved to be the most successful at modelling the target metabolites, with MIR being unsuccessful and Raman only being able to detect but not model the metabolites. This research provides an indicator of media suitability in low passage number cell cultures, by comparing the batch culture processes. The CD CHO media proved to be the best of the three tested media, based upon the cell density, viability and mAb titre produced. Overall this study represents a valuable stage in the progression towards real time monitoring of biomanufacturing processes and development of tailored low passage number cell culture media. However there are areas of this study where further investigation could be improved.
|Date of Award||20 Apr 2017|
- University Of Strathclyde
|Sponsors||University of Strathclyde & University College London|
|Supervisor||Brian McNeil (Supervisor) & Linda Harvey (Supervisor)|