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gQSPSim: A SimBiology-Based GUI for Standardized QSP Model Development and Application.

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gQSPSim is a MATLAB application that enhances the reproducibility and usability of quantitative systems pharmacology (QSP) models. It simplifies QSP model calibration, virtual subject development, and population simulations for drug development.

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Area of Science:

  • Pharmacology
  • Computational Biology
  • Systems Biology

Background:

  • Quantitative systems pharmacology (QSP) models are crucial for drug development but often face challenges in reproducibility, transparency, portability, and reuse due to diverse technical workflows.
  • Standardized methodologies are needed to streamline the development and analysis of complex QSP models.

Purpose of the Study:

  • To introduce gQSPSim, a graphical user interface (GUI)-based MATLAB application designed to enhance the reproducibility, transparency, portability, and reuse of QSP models.
  • To provide a user-friendly platform for key QSP model development and analysis steps, including calibration, virtual subject generation, and population simulations.

Main Methods:

  • Development of gQSPSim, a MATLAB application with a GUI for QSP model development and analysis.
  • Integration of model calibration (global/local optimization), virtual subject creation for variability/uncertainty exploration, and virtual population simulations for interventions.
  • Compatibility with SimBiology-built models, utilizing components like species, doses, variants, and rules.
  • Inclusion of interactive visualization and generation of presentation-ready figures.

Main Results:

  • gQSPSim successfully facilitates QSP model calibration, virtual subject development, and population simulations.
  • The application provides interactive visualizations and generates high-quality figures for analysis and presentation.
  • Demonstrated utility with a target-mediated drug disposition model and a PCSK9 inhibitor model for hypercholesterolemia.

Conclusions:

  • gQSPSim offers a standardized and accessible approach to QSP model development and analysis, improving reproducibility and reuse.
  • The application empowers researchers to efficiently explore biological variability, uncertainty, and intervention effects within QSP frameworks.
  • gQSPSim serves as a valuable tool for advancing drug discovery and development through enhanced QSP modeling capabilities.