Efficient Modeling and Simulation of Space-Dependent Biological Systems

We recently demonstrated the possibility to model and to simulate biological functions using hardware description languages (HDLs) and associated simulators traditionally used for microelectronics. Nevertheless, those languages are not suitable to model and simulate space-dependent systems described by partial differential equations. However, in more and more applications space- and time-dependent models are unavoidable. For this purpose, we investigated a new modeling approach to simulate molecular diffusion on a mesoscopic scale still based on HDL. Our work relies on previous investigations on an electrothermal simulation tool for integrated circuits, and analogies that can be drawn between electronics, thermodynamics, and biology. The tool is composed of four main parts: a simple but efficient mesher that divides space into parallelepipeds (or rectangles in 2D) of adaptable size, a set of interconnected biological models, a SPICE simulator that handles the model and Python scripts that interface the different tools. Simulation results obtained with our tool have been validated on simple cases for which an analytical solution exists and compared with experimental data gathered from literature. Compared with existing approaches, our simulator has three main advantages: a very simple algorithm providing a direct interface between the diffusion model and biological model of each cell, the use of a powerful and widely proven simulation core (SPICE) and the ability to interface biological models with other domains of physics, enabling the study of transdisciplinary systems.