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AMGET, an R-Based Postprocessing Tool for ADAPT 5.

B Guiastrennec1, L Wollenberg, A Forrest

  • 1Department of Pharmacy Practice, School of Pharmacy, University at Buffalo, SUNY, Buffalo, New York, USA.

CPT: Pharmacometrics & Systems Pharmacology
|August 2, 2013
PubMed
Summary
This summary is machine-generated.

The ADAPT 5 Model Evaluation Graphical Toolkit (AMGET) enhances population pharmacokinetic and pharmacodynamic analysis by providing advanced diagnostic plotting capabilities. This R package streamlines post-analysis processing for ADAPT 5, NONMEM, and S-ADAPT, improving efficiency and customization.

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Area of Science:

  • Pharmacometrics and Systems Pharmacology
  • Computational Biology
  • Biostatistics

Background:

  • Population pharmacokinetic and pharmacodynamic (PK/PD) systems analysis software like ADAPT 5 offers powerful modeling capabilities.
  • However, ADAPT 5 has limited built-in features for essential pre- and post-analysis diagnostic plotting.
  • This limitation can hinder efficient data interpretation and model evaluation.

Purpose of the Study:

  • To introduce the ADAPT 5 Model Evaluation Graphical Toolkit (AMGET), an external R package designed to address the diagnostic plotting limitations of ADAPT 5.
  • To demonstrate how AMGET facilitates efficient postprocessing of ADAPT 5, NONMEM, and S-ADAPT runs.
  • To showcase AMGET's ability to generate informative and customizable diagnostic plots through interactive menus and settings spreadsheets.

Main Methods:

  • Development of AMGET as an external package using the R programming language.
  • Integration of interactive navigational menus within AMGET for user-friendly plot generation.
  • Utilization of a simple settings spreadsheet for high-degree customization of graphical and numerical elements in plots.
  • Application of AMGET to a simulated dataset and a pharmacokinetic model optimized with ADAPT 5's maximum likelihood expectation maximization (MLEM) algorithm.

Main Results:

  • AMGET enables rapid creation of informative diagnostic plots for population PK/PD analyses.
  • The toolkit supports efficient postprocessing of runs from ADAPT 5, NONMEM, and S-ADAPT.
  • Users can achieve a high degree of customization in plot elements via an accessible settings spreadsheet.
  • The use of AMGET demonstrably improves the efficiency of utilizing ADAPT 5's numerical routines.

Conclusions:

  • AMGET significantly enhances the utility of ADAPT 5 and similar population PK/PD analysis software by providing robust diagnostic plotting tools.
  • The package offers a user-friendly and customizable solution for post-analysis visualization, improving workflow efficiency.
  • AMGET empowers researchers to better interpret model results and refine their population PK/PD models.