The NONMEM trial design feature is suitable for standard continuous data, whereas more elaborate trial designs or with noncontinuous data-types can still be accomplished in optimal design dedicated software like PopED and PFIM. In addition, the $DESIGN feature can be used on any model file and dataset combination to retrospectively evaluate the model parameter uncertainty one would expect given that the model generated the data, particularly if outliers of the actual data prevent a reasonable assessment of the variance-covariance. Conversely, a model developed in NONMEM could be used for design optimization. A design evaluator and optimizer within NONMEM allows any control stream first developed for trial design exploration to be subsequently used for estimation of parameters of simulated or clinical data, without transferring the model to another software.
Robust design techniques accounting for likely variability among subjects are also shown. This tutorial provides simple and complex pharmacokinetic/pharmacodynamic examples on obtaining optimal sample times, doses, or best division of subjects among design groups. Because evaluation of FIM is more efficient than clinical trial simulation, more designs can be investigated, and the design of a clinical trial can be optimized. If there is a trial version of NONMEM, it should be available on their official website.
Nonmem software full#
The trial software may include full or limited features. Model parameter identifiability may be uncovered by very large standard errors or inability to invert an FIM. Trial software is usually a program that you can download and use for a certain period of time. Parameter precision and model parameter estimability is obtained by assessing the Fisher Information Matrix (FIM), providing expected model parameter uncertainty. The purpose of this tutorial is to compare the characteristics of NONMEM, Berkeley Madonna, 2 and R 3 by simulating PM models.
Nonmem software how to#
This NONMEM tutorial shows how to evaluate and optimize clinical trial designs, using algorithms developed in design software, such as PopED and PFIM 4.0. Among the many software packages used in PM analysis, NONMEM is still accepted as the gold standard, although the user interface is not as good as other software and it has a steep learning curve.