Model-based design of mesenchymal stem cell seeding-cultivation-passage processes considering dynamics and variabilities

Mesenchymal stem cells (MSCs) represent a promising route for regenerative medicine because of their therapeutic functions. Considering the anticipated demand growth of MSCs, design spaces (DSs) have been emphasized to ensure cell quality by process design. However, a model that can consider all the effects throughout the multiple steps of MSC manufacturing processes has yet to be presented. Here, we propose a model-based design that considers dynamics and variabilities through the seeding, cultivation, and passage culture of MSCs. An integrated kinetic model was developed, incorporating the effects of seeding heterogeneity and passage-associated senescence into dynamic variations of quality indicators. Two seeding cases were implemented to yield DSs, fulfilling quality specifications with a specified probability. The DS assessment proposed a condition that maximized cell growth efficiency, with confirming robustness against seeding deviations. The presented methodology would contribute to simulation-based decision-making in therapeutic cell manufacturing process design.