Abstract
This work details the development of a five-step workflow for design space determination of mesenchymal stem cell (MSC) cultivation. The workflow employs mechanistic models to represent system dynamics of MSC cultivation processes while introducing stochastic simulations to capture uncertainties. The developed workflow was applied to an MSC cultivation case study where seeding density and medium change ratio were selected as critical process parameters (CPPs), while the number of cells cultivated was specified as the sole critical quality attribute (CQA). Monod kinetics based modelling and stochastic simulation were used to determine a dynamically evolving probabilistic design space. The results were then visualized on a 2D map with probability contours. In the presented calculations, the optimal batch termination time was identified as Day 10, given a probability preference of 90 %. The results illustrated the need to account for both raw material and process/operation uncertainties and dynamics in design space determination for MSC cultivation.
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