Computational Modeling of Platelet Aggregation and Blood Coagulation
Elijah Newren, University of Utah
Despite more than a century of brilliant research in blood coagulation and related fields, the complexity of blood clotting under flow has prevented quantitative and predictive modeling. Yet such modelling could have numerous diagnostic and therapeutic uses. The goal of my research is to simulate these systems computationally as we seek to elucidate fundamental biological mechanisms and improve biomedical therapies and devices.
Biofluid dynamics problems of this kind have numerous challenges. They involve complex flows; interactions between flow and moving, deformable objects (such as red blood cells or platelets); long cascades of chemical reactions occurring within the fluid and on cell surfaces and having multiple feedforward and feedback loops; chemical and cell transport; and chemically induced phase transitions (polymerization).
Models of these phenomena are likewise complex. They typically involve coupled nonlinear PDEs, dynamic fluid-structure interactions, and complicated networks of kinetic equations for chemical reactions interacting on multiple spatial and temporal scales.
The complexity, size, and dynamic nature of these problems makes them intractable to analysis. Their time and space requirements also place them far beyond the computational capacity of serial computers. These problems require the use of high-performance computing.
The Immersed Boundary and Immersed Interface methods (IB/II) have proven to be very useful for numerical solutions of a fluid interacting with an active deformable structure, but have not yet been extended to deal with three-dimensional multicellular biofluid problems with chemistry. I will be implementing the IB method (with some II variants) with the necessary biofluid and chemical extensions in the SAMRAI framework. This will allow for distributed memory parallelism with adaptive mesh refinement, load balancing, and fast multigrid/multilevel solvers.
Abstract Author(s): Elijah Newren