01. Discover
What is the Optimization Module?

The Optimization Module for GastroPlus® extends and enhances the program’s basic capabilities in several important ways:

02. Explore
Fitting Models
  • Fitting Models to Data

    One of the most important uses of GastroPlus is to fit absorption, pharmacokinetic, and pharmacodynamic models to observations. In doing so, researchers gain tremendous insight into how their compound is behaving in vivo. When a single set of model parameters can be found that properly describes the observed plasma concentration vs. time profiles for all dose levels, a useful model has been obtained. In general, if the model parameters must be changed for each dose level, then something is not being accounted for correctly. The Optimization Module performs the multidimensional search needed to fit model parameters to one or more data sets automatically.

    A software interface displaying the "Select Variables" window for the compound Propranolol HCl within Simulations Plus, Inc's GastroPlus® shows options under "Pharmacokinetics," "ACAT-Compound," and "Formulation" tabs, allowing users to select variables such as "Oral Mucosa Vol" and "Stomach TransT" in the advanced physiology model.

    A window titled "Optimization - Search Method" includes options to select objective function weights, choose a compound from a dropdown list, and input observation weights for the selected compound in your GastroPlus physiology model

  • Model fitting can include (but is not limited to):
    • PBPK model parameters to plasma and/or tissue concentration vs. time data
    • Peff and absorption scale factors to determine regional dependencies
    • A wide variety of physiological parameters (when necessary – rarely used)
    • Parameters to match profiles of parent drugs or any of their metabolites

    Model parameters can be fitted to data for a single record, or across multiple records simultaneously. The program will run one simulation for each record each time it changes the value(s) of one or more model parameters. Typically, hundreds of iterations will be performed, each with N simulations, where N is the number of records whose observations are being used to compare predicted and observed values. Objective function weighting is user-defined, and includes the most common weighting schemes.

03. RESOURCES
Optimization Resources