4.7 Article

Modular Representation of Physiologically Based Pharmacokinetic Models: Nanoparticle Delivery to Solid Tumors in Mice as an Example

Journal

MATHEMATICS
Volume 10, Issue 7, Pages -

Publisher

MDPI
DOI: 10.3390/math10071176

Keywords

modular model; nanoparticles; physiologically based pharmacokinetic modeling; nanoparticle delivery to tumors; BioUML

Categories

Funding

  1. Russian Science Foundation [21-75-30020]
  2. Russian Science Foundation [21-75-30020] Funding Source: Russian Science Foundation

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This article describes a toolkit for presenting physiologically based pharmacokinetic (PBPK) models in a modular graphical view in the BioUML platform. The toolkit is demonstrated using an existing model of nanoparticles delivery to solid tumors in mice, and guidance is provided for converting the PBPK model code from a text modeling language to a visual modular diagram. The proposed approach offers clarity and ease of perception, and reduces the risk of technical errors during model reuse and extension.
Here we describe a toolkit for presenting physiologically based pharmacokinetic (PBPK) models in a modular graphical view in the BioUML platform. Firstly, we demonstrate the BioUML capabilities for PBPK modeling tested on an existing model of nanoparticles delivery to solid tumors in mice. Secondly, we provide guidance on the conversion of the PBPK model code from a text modeling language like Berkeley Madonna to a visual modular diagram in the BioUML. We give step-by-step explanations of the model transformation and demonstrate that simulation results from the original model are exactly the same as numerical results obtained for the transformed model. The main advantage of the proposed approach is its clarity and ease of perception. Additionally, the modular representation serves as a simplified and convenient base for in silico investigation of the model and reduces the risk of technical errors during its reuse and extension by concomitant biochemical processes. In summary, this article demonstrates that BioUML can be used as an alternative and robust tool for PBPK modeling.

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