Simulation

Simulate responses to biological variability or different dosing conditions, scan parameter ranges, calculate sensitivities

Simulate the dynamic behavior of a model using a variety of deterministic and stochastic solvers. You can model biological variability by simulating alternate scenarios and what-if hypotheses without creating multiple copies of a model. Explore different dosing strategies such as bolus and infusion doses and determine the optimal dosing strategy by combining different dosing schedules. You can also perform parameter sweeps and sensitivity analysis to investigate the influence of model parameters and initial conditions on model behavior.

Highlighted Topics

Categories

Simulate Responses to Biological Variability and Doses
Simulate biological variability to compare animal species, strains, or experimental conditions, and investigate different dosing strategies
Scan Parameter Ranges
Explore simulation results over ranges of quantity values
Perform Sensitivity Analysis
Determine which model components are sensitive to specific conditions or drugs using local and global sensitivity analyses such as Sobol indices, elementary effects, and multiparametric GSA

Featured Examples

Perform PK/PD Modeling and Simulation to Guide Dosing Strategy for Antibiotics

Perform PK/PD Modeling and Simulation to Guide Dosing Strategy for Antibiotics

Perform a Monte Carlo simulation of a pharmacokinetic/pharmacodynamic (PK/PD) model for an antibacterial agent. This example is adapted from Katsube et al. [1] This example also shows how to use the SimBiology® SimFunction object to perform parameter scans in parallel.

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Parameter Scanning, Parameter Estimation, and Sensitivity Analysis in the Yeast Heterotrimeric G Protein Cycle

Parameter Scanning, Parameter Estimation, and Sensitivity Analysis in the Yeast Heterotrimeric G Protein Cycle

Build, simulate and analyze a model in SimBiology® using a pathway taken from the literature.

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Simulate the Glucose-Insulin Response

Simulate the Glucose-Insulin Response

Simulate and analyze a physiologically based glucose-insulin model for normal and diabetic patients.

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Stochastic Simulation of Radioactive Decay

Stochastic Simulation of Radioactive Decay

Build and simulate a model using the SSA stochastic solver.

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Analysis of Stochastic Ensemble Data in SimBiology

Analysis of Stochastic Ensemble Data in SimBiology

Make ensemble runs and how to analyze the generated data in SimBiology®.

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Finding Conserved Quantities in a Pathway Model

Finding Conserved Quantities in a Pathway Model

Use the sbioconsmoiety function to find conserved quantities in a SimBiology® model.

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