Open source software from the Uppsala University Pharmacometrics group
Rikard Nordgren (1), Andrew C. Hooker (1), Stella Belin (1), Johan Borg (1), Zhe Huang (1) and Mats O. Karlsson (1)
(1) Department of Pharmacy, Uppsala University, Sweden
The Uppsala University pharmacometrics group develops and maintains several different open-
source software packages.
assemblerr – Construction of pharmacometric models by combining pre-defined model
components.
ncappc – Can perform traditional non-compartmental analysis and simulation based posterior
predictive checks for PK and PKPD models [1].
Pharmpy – A library for pharmacometric modelling. Has functionality for reading, parsing and
transforming models and datasets as well as for estimating models and collecting results. Scope of
funcionality ranges from single models to full tools which creates and runs models. NONMEM and
nlmixr are supported.
pharmr – R interface to Pharmpy.
piraid – An aid for development and diagnostics of pharmacometric IRT and composite score
models.
PopED – Computes optimal experimental designs for population or individual studies based on
nonlinear mixed-effects models. [2][3]
xpose4/xpose – Model building aids for nonlinear mixed-effects model analysis using NONMEM,
facilitating data set checkout, exploration and visualization, model diagnostics, candidate covariate
identification and model comparison [4].
bemod – Model based bioequivalence analysis.
PsN – 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. [5][6][7][8]
PsN is freely available at https://uupharmacometrics.github.io/PsN, xpose4 at
https://uupharmacometrics.github.io/xpose4, xpose at https://uupharmacometrics.github.io/xpose4,
PopED at https://andrewhooker.github.io/PopED, ncappc at
https://github.com/UUPharmacometrics/ncappc, Pharmpy at https://pharmpy.github.io, assemblerr
at https://github.com/UUPharmacometrics/assemblerr and piraid at
https://github.com/UUPharmacometrics/piraid.
References:
[1] Chayan Acharya, Andrew C. Hooker, Gulbeyaz Y. Turkyilmaz, Siv Jonsson and Mats O.
Karlsson (2016), A diagnostic tool for population models using non-compartmental analysis: The
ncappc functionality for R, Computer Methods and Programs in Biomedicine, 127, 83-93.
[2] Nyberg J, Ueckert S, Stroemberg EA, Hennig S, Karlsson MO, Hooker AC (2012). “PopED: An
extended, parallelized, nonlinear mixed effects models optimal design tool.” Computer Methods
and Programs in Biomedicine, 108.
[3] Foracchia M, Hooker AC, Vicini P, Ruggeri A (2004). “POPED, a software for optimal
experiment design in population kinetics.” Computer Methods and Programs in Biomedicine, 74.
[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.
[5] Karlsson MO, Nordgren R et al., PsN: An open source toolkit for non-linear mixed effects
modelling, 2004-, https://uupharmacometrics.github.io/PsN/ [Online; accessed 2023-03-17]
[6] 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.
[7] 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.
[8] 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.