Modular dynamics paradigm in biosystems multilevel modeling: Software design and PBPK/PD validation.

Area of Science:

• Computational Biology
• Systems Biology
• Pharmacokinetics

Background:

• Mechanistic modeling and simulation (M&S) are crucial for understanding complex biological systems.
• Existing M&S tools often impose rigid links between biological components and their dynamics.
• Advancements require flexible M&S tools that accommodate evolving mechanistic knowledge.

Purpose of the Study:

• To present Cyborgs Simulator (CybSim), a novel M&S software tool.
• To introduce a modular modeling paradigm within an acausal object-oriented modeling language (OOML) architecture.
• To facilitate the integration of new mechanistic discoveries into biosystems models.

Main Methods:

• Developed CybSim based on a modular dynamics paradigm and an acausal OOML architecture.
• Implemented features including multi-modeling, separation of biological and artificial components, and algorithmic blocks.
• Validated CybSim by constructing and comparing physiologically based pharmacokinetic (PBPK) models against published references in other M&S tools.

Main Results:

• CybSim demonstrated high accuracy in predicting bacterial counts (logarithmic absolute errors < 2%) and physiological parameters.
• Prediction errors in CybSim were comparable to the numerical precision of established integrators.
• The modular modeling paradigm in CybSim proved reliable, requiring minimal components for complex PBPK/PD models.

Conclusions:

• The modular dynamics paradigm is effectively implementable in modern acausal OOML M&S tools.
• CybSim successfully integrates this paradigm, offering a flexible graphical tool for biosystems modeling.
• The validation confirms CybSim's reliability for PBPK modeling and its potential for advancing mechanistic biological understanding.