Open source software from the Uppsala University Pharmacometrics group

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 – Performs traditional non-compartmental analysis and simulation based posterior
predictive checks for PK and PKPD models [1].
Pharmpy – A library for pharmacometric modelling. Functionality includes parsing and
transforming models and datasets, estimating models, and automatic development of models.
NONMEM and nlmixr2/rxode2 are supported. Pharmpy also has a graphical user interface (GUI)
for model building. See separate PAGE abstract and poster for more information about Pharmpy.
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 both population and individual studies based
on nonlinear mixed-effect models. Often this is based on a computation of the Fisher Information
Matrix (FIM). [2][3]
xpose4/xpose – xpose4 is a collection of functions to be used as a model building aid for nonlinear
mixed-effects (population) analysis using NONMEM. It facilitates data set checkout, exploration
and visualization, model diagnostics, candidate covariate identification, and model comparison.
xpose was designed as a ggplot2-based alternative to xpose4. xpose aims to reduce the post
processing burden and improve diagnostics commonly associated the development of non-linear
mixed effect models. [4].
bemod – Model based bioequivalence analysis.
MBAOD – The MBAOD package can be used to simulate experiments (often clinical or pre-clinical
trials) using predefined adaptation and optimization rules. The package can be used to plan and
evaluate the predicted effectiveness of an upcoming trial. In addition the package can be used to
optimize any specific cohort of an actual study using MBAOD.
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 – make changes to a model programmatically.
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/xpose/,
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.

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.