2011 - Athens - Greece

PAGE 2011: Software demonstration
Harling Kajsa

Perl speaks NONMEM (PsN) and Xpose

Kajsa Harling, Andrew C. Hooker, Sebastian Ueckert, E. Niclas Jonsson, Mats O. Karlsson

Pharmacometrics group, Department of Pharmaceutical Biosciences, Uppsala University, Sweden

PsN is a toolbox for population PK/PD model building using NONMEM 6 and 7. It has a broad functionality ranging from results extraction from output files, data file sub setting and resampling, to advanced computer-intensive statistical methods and NONMEM job handling in large distributed computing systems. PsN includes stand-alone tools for the end-user as well as development libraries for method developers. New features include covariate model building functionality utilizing the cross-validation, linearization and lasso methods. The existing stepwise covariate model building tool has also undergone a major revision for increased flexibility and stability. In addition, handling of dropout censoring and missing observations in visual predictive checks and a new tool for Monte-Carlo mapped power have been implemented. <\P>

Xpose 4 is an open-source population PK/PD model building aid for NONMEM. Xpose attempts to facilitate the use of diagnostics in an efficient manner, providing a toolkit for dataset checkout, exploration and visualization, model diagnostics, candidate covariate identification and model comparison. <\P>

The cooperative functionality included in PsN and Xpose permits a synergistic use of both, allowing the end user to easily compute and display various predictive checks and other diagnostics. <\P>

Both Xpose and PsN are freely available at http://xpose.sourceforge.net and http://psn.sourceforge.net respectively.

[1] Jonsson EN, Karlsson MO. Xpose--an S-PLUS based population pharmacokinetic/pharmacodynamic model building aid for NONMEM. Computer Methods and Programs in Biomedicine. 58(1):51-64.
[2] Lindbom L, Ribbing J, Jonsson EN. Perl-speaks-NONMEM (PsN)--a Perl module for NONMEM related programming. Comput Methods Programs Biomed. 75(2):85-94.
[3] Lindbom L, Pihlgren P, Jonsson EN. PsN-Toolkit--a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed. 79(3):241-57.
[4] Hooker AC, Staatz CE, Karlsson MO. Conditional weighted residuals (CWRES): a model diagnostic for the FOCE method. Pharm Res. 24(12): 2187-97.
[5] Bergstrand M, Hooker AC, Karlsson MO. Visual Predictive Checks for Censored and Categorical data. PAGE 18 (2009) Abstr 1604.
[6] Bergstrand M, Hooker AC, Wallin JE, Karlsson MO. Prediction-Corrected Visual Predictive Checks for Diagnosing Nonlinear Mixed-Effects Models. AAPS J. (2011) Feb 8. [Epub ahead of print].
[7] Ribbing J, Nyberg J, Caster O, Jonsson EN. The lasso—a novel method for predictive covariate model building in nonlinear mixed effects models. J Pharmacokinet Pharmacodyn (2007) 34:485–517.
[8] Vong C, Bergstrand M, Karlsson MO. Rapid sample size calculations for a defined likelihood ratio test-based power in mixed effects models. PAGE 19 (2010) Abstr 1863.
[9] Baverel PG, Savic RM, Karlsson MO. Two bootstrapping routines for obtaining imprecision estimates for nonparametric parameter distributions in nonlinear mixed effects models. J Pharmacokinet Pharmacodyn (2010).
[10] Carlsson KC, Savic RM, Hooker AC, Karlsson MO. Modeling Subpopulations with the $MIXTURE Subroutine in NONMEM: Finding the Individual Probability of Belonging to a Subpopulation for the Use in Model Analysis and Improved Decision Making. AAPS J. (2009) 11:148-54.

Reference: PAGE 20 (2011) Abstr 2193 [www.page-meeting.org/?abstract=2193]
Software demonstration
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