In silico modeling of directed differentiation of induced pluripotent stem cells to definitive endoderm

Differentiation of embryonic stem cells and induced pluripotent stem cells (iPSCs) into endoderm derivatives, including thyroid, thymus, lungs, liver, and pancreas, has broad implications for disease modeling and therapy. We utilize and expand a model development approach previously outlined by the authors to construct a model for the directed differentiation of iPSCs into definitive endoderm (DE). Assuming discrete intermediate stages in the differentiation process with a homogeneous population in each stage, three lineage models with two, three, and four populations and three growth models are constructed. Additionally, three models for error distribution are defined, resulting in a total of 27 models. Experimental data obtained in vitro are used for model calibration, model selection, and final validation. Model selection suggests that no transitory state during differentiation expresses the DE biomarkers CD117 and CD184, a finding corroborated by existing literature. Additionally, space-limited growth models, such as logistic and Gompertz growth, outperform exponential growth. Validation of the inferred model with leave-out data results in prediction errors of 26.4%. Using the inferred model, it is predicted that the optimal differentiation period is between 1.9 and 2.4 days, plating populations closer to 300 000 cells per well result in the highest yield efficiency, and that iPSC differentiation outpaces the DE proliferation as the main driver of the population dynamics. We also demonstrate that the model can predict the effect of growth modulators on cell population dynamics. Our model serves as a valuable tool for optimizing differentiation protocols, providing insights into developmental biology.