Build QSP, PBPK, and PK/PD Models

Build models just as you would draw them on a piece of paper in SimBiology Model Builder or import existing SBML models. Use dose and variant objects to apply dosing strategies and store alternative quantity values.

Simulate Model Behavior

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

Fit Data to Estimate Parameters

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

Perform Monte Carlo Simulations

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

Global and Local Sensitivity Analysis

Explore the effects of variations in model quantities on model response by performing sensitivity analysis. SimBiology supports global, Monte Carlo, and local, derivative-based analyses.

Noncompartmental Analysis

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.

Accelerate Simulations

Accelerate large models or Monte Carlo simulations by converting to compiled C code. Further improve performance by distributing across multiple cores, clusters, or cloud resources with Parallel Computing Toolbox.

Share Models as Web Apps

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

Community Tools

Use SimBiology programmatically with MATLAB scripts to customize and automate analyses. Community-contributed tools can be used as add-ons for model analysis, such as virtual population simulations.