A Mathematical Model for Determining Probabilistic Design Space in Mesenchymal Stem Cell Passage Culture

With their many therapeutic functions, mesenchymal stem cells (MSCs) are promising sources for regenerative medicine. However, in the manufacture of MSCs, without a method for exploring the effects of long-term passage on cell proliferation potentials, the design of passage culture processes is challenging. Here, for the process design of the MSC passage culture, we propose a model for predicting the growth rate as a function of the cumulative population doubling level (cPDL) for each passage. Three steps were implemented: (1) passage culture experiments to correlate apparent growth rate with cPDL were conducted, (2) a model for predicting the growth rate as a function of cPDL was developed, and (3) a model to design the passage culture of MSCs from bone marrow (BM-MSCs) and umbilical cord (UC-MSCs) with stochastic simulation was applied. Two design variables (passage number and harvesting time) were investigated to define feasible operation regions as probabilistic design spaces to meet three quality indicators (senescence level, confluency level, and total number of cells) with given probabilities. Consequently, 10 and 62 conditions out of 165 were identified as feasible for BM- and UC-MSCs, respectively, which would contribute to the industrial MSC passage culture process design.