Image-based hybrid model incorporating initial spatial distribution for mesenchymal stem cell cultivation process design

This work presents an image-based hybrid model incorporating the initial spatial distribution for mesenchymal stem cell (MSC) cultivation process design. First, three levels of seeding bias in static MSC cultivation were experimentally investigated, and the resulting initial distribution was quantified using phase contrast microscopy image analysis. Second, the observed spatial heterogeneity was defined as a new parameter by calculating the standard deviation of the seeded cell number fraction among numerical 8 x 8 tiles on two-dimensional plates. Third, the parameter was incorporated into kinetic models to consider spatial growth limitation. The model was then applied to simulate MSC cultivation processes with experimental data. Using dynamic and stochastic simulation outputs, feasible ranges of cell-harvesting time could be determined to satisfy a given requirement for the minimum cell number and acceptable confluency level. The developed hybrid model could serve as a basis for quantitative decision-making in the design of MSC cultivation processes.