Efficient Modeling and Simulation of Space-Dependent Biological Systems

Area of Science:

• Computational Biology
• Biophysics
• Microelectronics Engineering

Background:

• Hardware description languages (HDLs) are traditionally used for microelectronics simulation.
• Existing HDLs are unsuitable for space-dependent biological models described by partial differential equations.
• Space- and time-dependent models are increasingly crucial in biological applications.

Purpose of the Study:

• To develop a new modeling approach for simulating molecular diffusion on a mesoscopic scale using HDLs.
• To adapt existing electrothermal simulation tools for biological and thermodynamic analogies.
• To create a transdisciplinary simulation tool integrating biology with other physics domains.

Main Methods:

• Utilized a mesher to divide space into adaptable-sized parallelepipeds (or rectangles in 2D).
• Developed interconnected biological models integrated within a SPICE simulator.
• Employed Python scripts for interfacing the mesher, biological models, and SPICE simulator.

Main Results:

• Validated simulation results against analytical solutions for simple cases.
• Compared simulation outcomes with experimental data from existing literature.
• Demonstrated the tool's capability to simulate molecular diffusion on a mesoscopic scale.

Conclusions:

• The developed HDL-based simulator offers a direct interface between diffusion and biological models.
• Leverages a powerful SPICE simulation core for robust performance.
• Enables the study of transdisciplinary systems by interfacing biological models with other physics domains.