10.25394/PGS.9104501.v1 Timothy James Sego Timothy James Sego Hybrid Kinetic Monte Carlo Models of Cellular Processes in Interactive Dynamic Microenvironments Purdue University Graduate School 2019 cell Dynamics Simulations Monte Carlo simulation models Biofabrication Computational Biology Biophysics Biological Engineering 2019-10-16 17:44:19 Thesis https://hammer.purdue.edu/articles/thesis/Hybrid_Kinetic_Monte_Carlo_Models_of_Cellular_Processes_in_Interactive_Dynamic_Microenvironments/9104501 Living tissue consists primarily of cells and extracellular matrix. Cells perform functions, communicate, respire and remodel extracellular matrix. Likewise, diffusive chemical conditions and extracellular matrix exhibit their own effects on cellular and intracellular processes, depending on the consistency of the matrix and phenotype of the cell. These interactions produce the emergent phenomena of tissue function, repair and morphology. Computational modeling seeks to quantify these processes for the purposes of fundamental study and predictive capability in various applications, including wound healing, tumor vascularization and biofabrication of living tissue. Hybrid kinetic Monte Carlo models are well known to be capable of predicting observed behaviors like cell sorting and spheroid fusion due to differential adhesion and energy minimization. However, no hybrid model sufficiently provides a formal treatment of full cell, chemical and matrix interactivity in a dynamic environment, including heterogeneous matrix conditions, advecting materials, and intracellular processes. In this work, hybrid kinetic Monte Carlo models are developed to describe full interactivity of cells, soluble signals and insoluble signals in a complex, dynamic microenvironment at the cellular level. Modeling of intracellular chemical dynamics and effects on the cellular state is developed as stochastic processes, and cell perform metabolic and matrix remodeling activities. Computational models of select \textit{in vivo} and \textit{in vitro} phenomena are developed and simulated, showing the ability to simulate new phenomena concerning cell viability, growth dynamics, highly heterogeneous cellular distributions, and complex tissue structures resulting from phenomena like intercellular signaling, matrix remodeling, and cell polarity.