BRIC DOCTORATE PROGRAMME on Linking High Throughput Cell Culture Multivariate Analysis and Economics for More Effective Process Integration

Lead Research Organisation: University College London
Department Name: Biochemical Engineering


As the antibody sector has matured, it has seen SIGNIFICANT INCREASES IN UPSTREAM (USP) PRODUCTIVITES that have opened up the possibility for radical changes to the design and operation of cell culture suites. However, due to the inherently complex set of interactions that can affect cell culture performance, IT IS HARD TO PREDICT THE CONSEQUENCES ON THE IMPURITY PROFILES AND HENCE ROBUSTNESS OF DOWNSTREAM (DSP) OPERATIONS as titres increase. Quality by Design initiatives are driving the need for greater understanding of the impact of cell culture strategies on the downstream processing equipment duties so as to enable EFFECTIVE PROCESS INTEGRATION and hence CONTINUOUS IMPROVEMENTS. This project will explore STATE-OF-THE-ART HIGH THROUGHPUT CELL CULTURE and MULTIVARIATE DATA ANALYSIS techniques to characterise cell culture operations, not only in terms of growth and productivity BUT ALSO IMPURITY PROFILES AND QUALITY. The resulting cell culture statistical cause-and-effect correlations will be integrated into PROCESS ECONOMICS MODELS developed in the UCL Decisional Tools team so as to TO IDENTIFY THE MOST COST-EFFECTIVE INTEGRATED USP AND DSP MANUFACTURING STRATEGIES FOR THE FUTURE. The proposed programme will link MedImmune's leadership in antibody production and UCL's leadership in bioprocess decisional tools and scale-down techniques to tackle these intricate process-business decisions. Project stages: 1. MICROSCALE DATA GENERATION (Yr 1, 2). Increases in titres can be a result of different combinations of increases in cell densities or specific cell productivities, each with a different impact on impurity burdens on DSP. This depends on factors such as the cell line characteristics, bioreactor operating parameters, medium or feed type and the feeding strategy. These have a significant impact on cell growth, productivity, viability, impurity profiles and may also have an impact on product quality. Initially large datasets characterising cell culture strategies will be generated by a) leveraging historical data from MedImmune and b) high throughput experimentation using both the 'ambr microscale bioreactor system' (developed in a collaboration between The Automation Partnership and MedImmune) and microwell systems from current UCL EPSRC IMRC activities. 2. MULTIVARIATE ANALYSIS (Yr 2, 3). The next challenge will be exploring effective techniques to analyse such large datasets and reduce to predictive correlations. Advanced multivariate analysis techniques will be investigated to help predict the product and impurity profiles resulting from different cell culture strategies. Statistical (rather than mechanistic) cause-and-effect correlations will then be derived to link the impurity profile to key factors such as the cell density, specific cell productivity, culture duration, and titre. Key quality attributes that will be focused on are the levels of HCP (host cell proteins), HMW (aggregates), cell viability and product potency. 3. LINKAGE TO PROCESS ECONOMICS MODELS (Yr 3). The resulting cell culture predictive correlations will be linked to a whole bioprocess cost model developed at UCL in a TSB/EPSRC collaboration with MedImmune so as to predict the equipment sizes, COG and risks associated with different cell culture strategies. 5. SCENARIO ANALYSIS (Yr 3, 4). Several cell culture strategies will be plugged into the integrated cell culture and process economics model to enable rapid identification of the most promising and robust combinations of USP and DSP activities for more streamlined development in both existing and new facilities. The overall outputs of this research will be a systematic framework combining microscale experimentation with statistical correlations and cost modelling so as to enable selection of innovative cell culture strategies early in the development cycle that BALANCE THE NEEDS OF UPSTREAM AND DOWNSTREAM MANUFACTURABILITY, ROBUSTNESS TO PROCESS VARIABILITIES AND COST-EFFECTIVENESS.


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