SimBiology

SimBiology is a MATLAB-based toolbox that provides an app and programmatic tools for modeling, simulating, and analyzing dynamic biological systems. It is designed for researchers and scientists working in quantitative systems pharmacology (QSP), physiologically-based pharmacokinetic (PBPK), and pharmacokinetic/pharmacodynamic (PK/PD) applications. Models can be built interactively using the SimBiology block diagram editor or constructed programmatically using the MATLAB language, and can be created from scratch, imported as SBML-formatted files, or based on provided model examples.

SimBiology supports a range of analysis techniques for ODE-based models of varying complexity. Users can run simulations to assess target feasibility, predict drug efficacy and safety, and identify optimal dosing schedules. Parameter estimation, sensitivity analysis, noncompartmental analysis, and Monte Carlo simulations are all available within the platform.

Model Building

• Build models interactively using the SimBiology Model Builder, in a manner similar to drawing diagrams on paper.
• Import existing models in SBML format.
• Use dose and variant objects to apply dosing strategies and store alternative quantity values.
• Start from provided model examples or build from scratch.

Simulation

• Simulate model behavior using a variety of deterministic and stochastic solvers via the SimBiology Model Analyzer or programmatic tools.
• Automatic unit conversion brings all quantities into a consistent unit system.
• Generate reports directly from analyses.

Parameter Estimation

• Estimate parameters using nonlinear regression with local, global, or hybrid methods.
• Calculate parameter and prediction confidence intervals.
• Account for both fixed and random effects using nonlinear mixed-effects (NLME) modeling.

Monte Carlo Simulations and Parameter Sweeps

• Perform parameter scans and Monte Carlo simulations to assess model behavior under different conditions and dosing regimens.
• Use interactive sliders to explore how variation in model quantities impacts model response.

Sensitivity Analysis

• Perform global (Monte Carlo-based) and local (derivative-based) sensitivity analyses.
• Explore the effects of variations in model quantities on model response.

Noncompartmental Analysis (NCA)

• Compute PK parameters from the time course of drug concentrations without assuming a compartmental model.
• Perform NCA on both experimental and simulation data for single or multiple dosing schemes.

Simulation Acceleration

• Accelerate large models or Monte Carlo simulations by converting to compiled C code.
• Distribute simulations across multiple cores, clusters, or cloud resources using the Parallel Computing Toolbox.

Sharing and Collaboration

• Create apps using App Designer, package them with MATLAB Compiler, and host them on MATLAB Web App Server.
• Collaborators can access and run apps in a browser without installing any software.

Community and Programmatic Tools

• Use SimBiology programmatically with MATLAB scripts to customize and automate analyses.
• Community-contributed add-ons are available for model analysis, including tools for virtual population simulations such as gQSPSim, QSP Toolbox, and VQMTools.

SimBiology integrates with the broader MATLAB ecosystem, including the Parallel Computing Toolbox for distributed computing and MATLAB Compiler for app deployment. It supports SBML import for interoperability with other modeling tools and platforms.