RESUMEN
Manufacturing of cell therapy products requires sufficient understanding of the cell culture variables and associated mechanisms for adequate control and risk analysis. The aim of this study was to apply an unstructured ordinary differential equation-based model for prediction of T-cell bioprocess outcomes as a function of process input parameters. A series of models were developed to represent the growth of T-cells as a function of time, culture volumes, cell densities, and glucose concentration using data from the Ambr®15 stirred bioreactor system. The models were sufficiently representative of the process to predict the glucose and volume provision required to maintain cell growth rate and quantitatively defined the relationship between glucose concentration, cell growth rate, and glucose utilization rate. The models demonstrated that although glucose is a limiting factor in batch supplied medium, a delivery rate of glucose at significantly less than the maximal specific consumption rate (0.05 mg 1 × 106 cell h-1 ) will adequately sustain cell growth due to a lower glucose Monod constant determining glucose consumption rate relative to the glucose Monod constant determining cell growth rate. The resultant volume and exchange requirements were used as inputs to an operational BioSolve cost model to suggest a cost-effective T-cell manufacturing process with minimum cost of goods per million cells produced and optimal volumetric productivity in a manufacturing settings. These findings highlight the potential of a simple unstructured model of T-cell growth in a stirred tank system to provide a framework for control and optimization of bioprocesses for manufacture.
Asunto(s)
Reactores Biológicos , Técnicas de Cultivo de Célula/métodos , Tratamiento Basado en Trasplante de Células y Tejidos , Linfocitos T/citología , Recuento de Células , Proliferación Celular , Células Cultivadas , Costos y Análisis de Costo , Humanos , CinéticaRESUMEN
Pichia pastoris is becoming a desirable host in the biopharmaceutical industry for therapeutics production. It grows on methanol to high cell densities ≥100 g DCW/L and secretes foreign proteins at high titers. However, the culture conditions to reach high cell densities pose a challenge to the processability by primary recovery operations, in particular centrifugation, used for cell removal. This work aims to assess the impact of recombinant P. pastoris strain selection on centrifugal dewatering. Normally, the choice of P. pastoris recombinant strain is based on best target protein expression levels; however, it is unknown whether the choice of strain will have an impact on performance of centrifugation operation. To achieve this aim, a previously developed laboratory ultra-scale down (USD) methodology that successfully predicted centrifugal dewatering of pilot-scale disk-type machines, was used in this work. Two recombinant P. pastoris strains, namely a X-33 and a glycoengineered Pichia strain, were used to perform fermentations secreting different products. The resulting harvested fermentation culture properties were analyzed and the dewatering performances of a pilot- and a large-scale disk-type centrifuge were evaluated using the USD methodology. The choice of P. pastoris strain was found to have a considerable impact on dewatering performance, with P. pastoris X-33 strain reaching better dewatering levels than the glycoengineered strain. The USD method proved to be a useful tool to determine optimal conditions under which the large scale centrifuge needed to be operated, reducing the need for repeated pilot-scale runs during early stages of process development for therapeutic products.