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Related Concept Videos

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Updated: May 26, 2025

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
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Modular dynamics paradigm in biosystems multilevel modeling: Software design and PBPK/PD validation.

Manuel Prado-Velasco1

  • 1Departamento de Ingeniería Gráfica and Multilevel Modeling and Emerging Technologies in Bioengineering Group, ETSi, Universidad de Sevilla, C. de los descubrimientos s/n, Seville, 41092, Spain.

Computers in Biology and Medicine
|February 22, 2025
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Summary

This study introduces Cyborgs Simulator (CybSim), a novel modeling and simulation tool for biological systems. CybSim utilizes a modular dynamics paradigm for flexible and evolving mechanistic models, validated with physiologically based pharmacokinetic (PBPK) models.

Keywords:
Computational multilevel modelingIn silico medicineModelicaPharmacodynamicsPharmacokineticsPhysiologySystems modeling language

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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.