This project involves the development of fundamental algorithms and software tools for the efficient simulation of multi-scale, biological systems. The target application for these tools is the simulation of the adaptive human immune system response to viral infections. The multi-scale nature of these applications arise from the different length and times scales inherent in inter-cellular and intra-cellular processes. At the inter-cellular level, the movement and interaction of a variety of human cells, viruses, and antibodies must be modeled. However, at the intra-cellular level, chemical pathways are simulated by complex network models that occur at much smaller time and length scales.
To make such computationally challenging simulations tractable, this project addresses two main research directions. First, the algorithms and software necessary for an efficient, multi-scale, agent-based software framework will be developed. These algorithms include efficient solution methods for the diffusion of biological agents, diffusion with drift (cell chemotaxis), and fluid flow. Second, to make the intra-cellular processes tractable, a novel model repository scheme will be developed whose goal is to achieve orders-of-magnitude improvement in computational time. The intellectual merits of this proposal will result from progress in the development of the fundamental algorithms required to enable the simulation of multi-scale, biological systems. The broader impacts of the project lie in the exposure of graduate students to multi-disciplinary research as well as in enabling an important class of applications. For example, collaborators in biology will be able to develop models for the adaptive immune system response to Epstein-Barr and influenza viral infections with the aim of developing more effective disease intervention strategies.
