SimBiology provides a set of integrated apps that are designed to facilitate building, simulating, and analyzing models of dynamic systems such as quantitative systems pharmacology (QSP), pharmacokinetic/pharmacodynamic (PK/PD) and systems biology models.
The SimBiology Model Builder app lets you build dynamic models interactively using various modeling elements. For instance, you can model a variety of biological systems such as signaling pathways, metabolic networks, PBPK, QSP, and PK/PD models. It also lets you model biological variability and different dosing regimens to investigate various experimental conditions and dosing strategies.
The SimBiology Model Analyzer app lets you perform analyses on models of dynamic systems. You can simulate the dynamic behavior of a model using various solvers and estimate model parameters. To investigate system dynamics and guide experimentation, you can perform sensitivity analysis and parameter sweeps.
This example shows how to create and simulate a simple model of receptor-ligand kinetics using the SimBiology Model Builder and SimBiology Model Analyzer apps.
Incorporate sodium-glucose co-transporter 2 (SGLT2) receptor inhibition by a hypothetical compound into an existing glucose-insulin model.
Copy and paste SimBiology blocks while building models in the Diagram.
The SimBiology Model Builder app provides keyboard shortcuts for various modeling actions.
The SimBiology® libraries are collections of built-in components that you can use to build and analyze models.
The SimBiology Model Builder app uses contextual icons to provide more information about model components in the browser tables and blocks in the Diagram tab.
Perform noncompartmental analysis and calibrate model parameters by fitting to experimental PKPD data using nonlinear regression.
Perform sensitivity analysis to find important model parameters.
Generate sample values for model parameters to represent virtual patients and simulate to explore model variability.
Explore multiple dosing amounts that meet the efficacy and toxicity thresholds.