Maternal cardiovascular and hemodynamic adaptations during pregnancy are critical for accommodation, growth and development of the placenta and fetus. Insufficient changes in cardiovascular function can lead to pregnancy complications including hypertension and represent a major risk for maternal and fetal health. The causes and mechanisms leading to maladaptations are not entirely understood. We aim to develop a dynamical model of cardiovascular function throughout pregnancy that will serve as a tool to aid understanding of cardiovascular adaptations and maladaptations in pregnancy and guide development of personalized therapeutic interventions. Dynamical modeling uses differential equations to describe the behavior of a system, and in contrast to statistical modeling allows computation of the outcomes of experiments that are significantly different from the ones used to build the model. The model's initial conditions and parameters are determined by patient's phenotype and genetic makeup, and by varying them one can simulate a wide variety of patients. A virtual patient's development can be analyzed through numerical solution of the model equations. The impact of risk factors, individual treatments, and combined effect of treatments aimed at various therapeutic targets are simulated through proper modifications of the equations and parameters. Therefore, dynamical modeling is a perfect tool for development of personalized treatments. It has been successfully applied to research of cancer, diabetes, arthritis, stroke, metabolic, hematologic, and autoimmune diseases. However, to date there is no dynamical model of cardiovascular adaptations throughout pregnancy. We aim to fill this gap by developing such a model based on synergy and integration of fluid dynamics, biomechanics, mathematical modeling, and simulation. We will first develop a compartmental non-pulsatile model of circulatory patterns in major organs and vessels, including the uterus, and their changes throughout pregnancy. This approach provides flexibility, mathematical convenience, and accommodates required features. Then we will test and refine the model by simulating physiological changes known to be associated with pregnancy hypertension and known therapeutic interventions that alleviate the hypertension. Finally, we will perform sensitivity analysis to make the model parsimonious and to gain insights into the order of significance of various pathophysiological mechanisms and the relative potential of various therapeutic interventions. In the future, the model may be used for in silico testing of novel therapeutic targets, management strategies, risk assessment, modeling of O2 and nutrient supply to the fetus, and combined effect of a patient's characteristics leading to development of hypertension, even when each individual characteristic is in the normal range. Innovation lies in integration of existing knowledge and previously developed models of individual organs and their...