Modeling and Simulation Workbench for NONMEM: Tutorial on Pirana, PsN, and Xpose

Abstract

Several software tools are available that facilitate the use of the NONMEM software and extend its functionality. This tutorial shows how three commonly used and freely available tools, Pirana, PsN, and Xpose, form a tightly integrated workbench for modeling and simulation with NONMEM. During the tutorial, we provide some guidance on what diagnostics we consider most useful in pharmacokinetic model development and how to construct them using these tools.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e50; doi:10.1038/psp.2013.24; advance online publication 26 June 2013.

Figure 1

Pirana main window.

Figure 2

PsN dialog window.

Figure 3

Xpose graphical user interface in Pirana.

Figure 4

Visual run record example. Green indicates a significant improvement in fit, red indicates a worsening, yellow indicates approximate identical fit (ΔOFV < ±3.84), and gray indicates a noncomparable child model (e.g., change in dataset). The blue line is the path to the final model, whereas a dashed line indicates a nonnested model. OFV, objective function value.

Figure 5

Visual predictive check. A visual predictive check for run3.mod. The solid line connects the observed median values per bin, whereas the dashed lines represent the observed 5th and 95th percentile of the observations. Blue areas indicate the 95% CIs of the 5th and 95th percentile of the predicted (simulated) value, whereas the red area indicates the CI of the median. The logarithmic y-axis makes it easier to judge correspondence between observed and predicted, especially in the terminal part of the plot. For this problem, it would be advisable to make a separate plot for the initial part of the VPC (0–4 h), because it is difficult to see the accordance between observed and predicted in that area. The VPC would also be clearer in the initial part if it would have been plotted without the observations (observed percentiles only).