2025/10/15 by Podéus, Henrik, Magnusson, Gustav, Keshmiri, Sasan +4
#65L05 (Primary) 37M05 #92C42 (Secondary) #FOS: Biological sciences #Quantitative Methods (q-bio.QM)
paper · doi:10.48550/arxiv.2510.13932
When modeling complex, hierarchical, and time-dynamic systems, such as biological systems, good computational tools are essential. Current tools, while powerful, often lack comprehensive frameworks for modular model composition, hierarchical system building, and time-dependent input handling, particularly within the Python ecosystem. We present SUND (Simulation Using Nonlinear Dynamic models), a Python toolbox designed to address these challenges. SUND provides a unified framework for defining, combining, and simulating multi-level time-dynamic systems. The toolbox enables users to define models with interconnectable inputs and outputs, facilitating the construction of complex systems from simpler, reusable components. It supports time-dependent functions and piecewise constant inputs, enabling intuitive simulation of various experimental conditions such as multiple dosing schemes. We demonstrate the toolbox's capabilities through simulation of a multi-level human glucose-insulin system model, showcasing its flexibility in handling multiple temporal scales, and levels of biological detail. SUND is open-source, easily extensible, and available at PyPI (https://pypi.org/project/sund/) and at Gitlab (https://gitlab.liu.se/ISBgroup/projects/sund/).