Simulate Responses to Biological Variability and Doses

Simulate biological variability to compare animal species, strains, or experimental conditions, and investigate different dosing strategies


sbiosimulateSimulate SimBiology model
createSimFunctionCreate SimFunction object
sbiodoseConstruct dose object
adddoseAdd dose object to model
addobservableAdd observable object to SimBiology model
sbiovariantConstruct variant object
addvariantAdd variant to model
sbiosteadystate Find steady state of SimBiology model
sbioacceleratePrepare model object for accelerated simulations
sbiosampleparametersGenerate parameters by sampling covariate model (requires Statistics and Machine Learning Toolbox software)
sbiosampleerrorSample error based on error model and add noise to simulation data
sbioplotPlot simulation results in one figure
sbiosubplotPlot simulation results in subplots
sbiotrellisPlot data or simulation results in trellis plot
sbioensemblerunMultiple stochastic ensemble runs of SimBiology model
sbioensembleplotShow results of ensemble run using 2-D or 3-D plots
sbioensemblestatsGet statistics from ensemble run data


ObservableObject containing expression for post-simulation calculations
ScenariosSimulation scenarios
SimFunctionFunction-like interface to execute SimBiology models
ScheduleDoseDefine drug dosing protocol
RepeatDoseDefine drug dosing protocol
VariantStore alternate component values
SimDataSimulation data
ConfigsetSolver settings information for model simulation
SolverOptionsSpecify model solver options
RuntimeOptionsOptions for logged species
CompileOptionsDimensional analysis and unit conversion options


SimBiology Model BuilderBuild QSP, PK/PD, and mechanistic systems biology models interactively
SimBiology Model AnalyzerAnalyze QSP, PK/PD, and mechanistic systems biology models

Examples and How To

Model Biological Variability with Virtual Patients Using SimBiology Model Analyzer App

Generate sample values for model parameters to represent virtual patients and simulate to explore model variability.

Simulate Biological Variability of the Yeast G Protein Cycle Using the Wild-Type and Mutant Strains

This example shows how to create and apply a variant to the G protein model of a wild-type strain.

Simulate Model of Glucose-Insulin Response with Different Initial Conditions

This example shows how to simulate the glucose-insulin responses for the normal and diabetic subjects.


Doses in SimBiology Models

Use doses to model different dosing regimens.

Variants in SimBiology Models

Use variants to store alternate parameter values and initial conditions of a model.

Model Simulation

Simulate dynamic models using various solvers.

Choosing a Simulation Solver

SimBiology® uses a solver function to compute solutions for a system of differential equations at different time intervals during model simulation.

Accelerating Model Simulations and Analyses

Accelerate the simulation or analysis by converting the model to compiled C code.

Combine Simulation Scenarios in SimBiology

Combine generated samples using two different methods.


Troubleshooting Simulation Problems

Troubleshoot SimBiology simulation errors, such as the Integration tolerance not met error, by changing the solver or tolerances.

Selecting Absolute Tolerance and Relative Tolerance for Simulation

SimBiology uses AbsoluteTolerance and RelativeTolerance to control the accuracy of integration during simulation.

Deriving ODEs from Reactions

For model simulation, SimBiology derives ordinary differential equations (ODEs) from model reactions using mass-balance principles.