| Summary: | The biotech community is under increasing pressure from the regulators to demonstrate effective implementation of the Quality by Design (QbD) principles and hence exhibit greater process understanding. Essential to achieving this goal is the implementation of a systematic framework that integrates experimental and predictive modeling techniques whilst accounting for the inherent variability of biologics. The aim of this thesis was to create a comprehensive framework for applying the principles of QbD throughout the lifecycle of a commercially distributed therapeutic protein produced in Chinese hamster ovary (CHO) cell culture. A systematic approach incorporating QbD principles was applied, involving risk assessment of potential process failure points, small-scale model development and qualification, design and execution of experiments, definition of operating parameter ranges and process performance acceptance criteria for validation and classification of operating parameters in the second generation process for this therapeutic protein. This methodology was illustrated through detailed process characterisation of a fed-batch production culture step and a virus inactivation step. One of the most prominent interactions found in the fedbatch production culture model was the three factor interaction of pH × temperature × seeding density. In the virus inactivation model, an increase in temperature (30 °C), incubation time (180 min), a reduction in pH (pH 3.5) at a relatively high protein concentration (5.5 g/L) resulted in a significant increase in the proportion of aggregated protein. Continuous process improvement and robustness are fundamental components in the QbD paradigm and are an integral component in the comprehensive framework described in this thesis. Following commercial implementation, Multivariate analysis (MVA) was employed to build upon the knowledge gained from process characterisation studies by identifying not only the process parameters but also the cell culture factors such as daily nutrient and metabolite levels which influenced protein titre and product quality attributes across scales. This analysis provided valuable knowledge for future troubleshooting and process refinement activities. Application of a statistical tool such as MVA adds scientific rigor to the data analysis thus improving the prediction of scale-up effects on the final product. Process robustness opportunities are often only realised when the process is run over multiple batches at manufacturing-scale. In this process, a perfusion culture which is employed to provide high cell densities to inoculate a production culture was identified as a potential risk to process and product supply and therefore identified as an area of focus for process optimisation activities. Application of a cell conditioning strategy enabled the generation of a seed fed-batch culture which achieved relatively high cell densities to inoculate the production culture. Shorter culture duration in the fed-batch culture also yielded comparable cell culture performance and productivity in production cultures relative to historical process performance. Successful commercial implementation and validation of the second generation process and the subsequent manufacture of hundreds of batches of this therapeutic protein verified the approaches described in this thesis as a suitable model for the development, scale-up and operation of any biopharmaceutical manufacturing process. This methodology is aligned with the QbD principles and can be applied to any biopharmaceutical manufacturing process, thus delivering sustainable, compliant and in-control processes throughout the product life-cycle.
|
|---|
