Rikard Nordgren (1), Sebastian Ueckert (1), Andrew C. Hooker (1) and Mats O. Karlsson (1)
(1) Department of Pharmaceutical Biosciences, Uppsala University, Sweden
PsN [1][2][3] is an open source toolbox for population PK/PD model building using NONMEM. It has broad functionality ranging from results extraction to advanced computer-intensive statistical methods. PsN simplifies the organization of NONMEM output files, helps with starting jobs on different types of clusters (i.e. slurm, torque, sge and lsf) and can perform a cornucopia of different statistical, computational and other methods, including: benchmark – combinatoric benchmarking of different NONMEM control stream settings, bootstrap – assessing uncertainty of parameter estimates, cdd – case deletion diagnostic to look for influential individuals, crossval – model cross validation, frem – full random effects modelling, linearize – generation of model approximation using linarization and second order approximation for likelihood models, llp – log likelihood profiling, mcmp – monte carlo mappend power for power compuations, nmoutput2so – converting NONMEM results into the standard output file format, parallel_retries – estimate the same model multiple times with different initial parameter estimates, qa – fast and automatic assumption assessment and quality assurance of models, resmod – residual modelling for quickly assessing appropriateness of structural and residual error models, scm – stepwise covariate model, simeval – simulation evaluation diagnostics of outliers, sir – sampling importance resampling for parameter uncertainty assessment, sse – stochastic simulation and estimation, transform – do changes to a model programmatically and vpc – visual predictive check.
Updates to PsN since PAGE 2019 include major improvements of the qa tool. The qa report has been updated with interactive help sections explaining each plot and table, the technical background and actionable advice for how the model could be improved. The advice sometimes include references to transform commands that could perform the model improvements automatically. The Minor uppdates include automatic reordering of OMEGAs/ETAs and support for likelihood models by frem, an updated installation procedure for PsNR using renv to be able to isolate and control versions of dependencies, automatic canceling of SLURM jobs when the main PsN process gets killed and the -html option for rplots rendering.
PsN can automatically generate plots for most of the different tools by adding the -rplots option. This automatically generates documents with, for example, visual predictive checks as part of the PsN output, without the need to manually run any R script. Many of these plots use functionality in the Xpose4 R package [4]. It is possible to customize the plots or replace them entirely by using custom R templates. These templates can either be plain R or R Markdown.
PsN is freely available at https://uupharmacometrics.github.io/PsN, the userguides for the different tools can be found at https://uupharmacometrics.github.io/PsN/docs.html and the new R package needed for R plots can be found at https://github.com/UUPharmacometrics/PsNR.
References:
[1] 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.
[2] 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.
[3] Keizer RJ, Karlsson MO, Hooker A. Modeling and Simulation Workbench for NONMEM: Tutorial on Pirana, PsN, and Xpose. CPT Pharmacometrics Syst Pharmacol. (2013) 2, e50.
[4] 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.
Reference: PAGE () Abstr 9460 [www.page-meeting.org/?abstract=9460]
Poster: Software Demonstration