IQR Tools

Efficient State-of-the-Art Modeling across Pharmacometrics and Systems Pharmacology – in R!

IQR Tools supports and increases the efficiency, quality, and compliance of model-based analyses in pharmacometrics, systems pharmacology, and systems biology by incorporating and extending the capabilities of existing tools. The user-friendliness of the package considerably lowers the threshold for the conduct of pharmacometric analyses, which also makes it useful both for complex analyses and for educational purposes.


Increased demand for support of model-based pharmacometric and quantitative systems pharmacology (QSP) analyses requires tools that meet requirements regarding user-friendliness, flexibility, efficiency, compliance, and state of the art methodology. It can be argued that there is no single tool, currently used in the pharmaceutical industry, that fulfills all of these requirements. The personal preferences of a modeler regarding software may lead to the adaptation of an analysis problem to the software, rather than adapting the tool and methodology to the project at hand.

Over the last decade, the MATLAB based IQM Tools have been developed as a software package that enables a seamless access to available pharmacometric parameter estimation tools, such as NONMEM and MONOLIX, enabling a straight forward transition from mechanistic systems pharmacology to descriptive pharmacometric models, and efficient support of reproducibility and compliance, including support of automated report generation in the Microsoft Word format (using IQReport).

Now some of that functionality is also available for R and the package is called IQRtools:

Selected Features

  • Intuitive format for representation of models and dosing scenarios / event tables.
  • Fully integrated workflow to efficiently support population PK/PD analyses (under development).
  • NLME modeling through a seamless interface to NONMEM and MONOLIX.
  • Support for handling of pre-clinical and clinical datasets in typical “NONMEM” format.
  • Powerful graphical data exploration tools.
  • A wide range of simulation and model analysis tools.
  • Support of the Systems Biology Markup Language (SBML) via a seamless interface to IQRsbml.

Improvements with respect to IQM Tools

  • Far more powerful parameter estimation method for QSP models (or any models not requiring variability). A gradient based trust region optimization method is used. Gradient and Hessian are not determined via finite differences but by using symbolic differentiation and integration of the sensitivity trajectories.
  • NONMEM and MONOLIX linear models do not need to be set up in a cumbersome way. IQR Tools automatically detects if an ODE based model can be solved analytically and will generate the appropriate NLME tools code (e.g. ADVAN 2, 4, 5, 7, 12).
  • Thorough implementation of the IntiQuan general dataset format with meta information that is used during the generation of goodness of fit and other diagnostic plots. For example, ETA vs. Covariate plots will be annotated by 1 (Male) and 2 (Female) rather than in IQM Tools with 1 and 2.
  • Seamless integration of the IQReport software, allowing to generate Word DOCX reports right from R.
  • Considerably improved simulation performance for population simulations, when using the eventTable concept.


  • IQR Tools is made available as an R package for Windows and Linux. On Mac it has not been tested.
  • IQR Tools is obfuscated as of now – this might change in the future.
  • IntiQuan publishes new versions of IQR Tools from time to time.


Please download the “IQRtools_Documentation.pdf” file from the right panel. It will guide you through the installation process and provide some additional documentation.

Release Notes

V0.5.6 December 14, 2017
- Allowed for bioavailability terms in NONMEM infusion/absorption0 models
- Smaller improvements (e.g. showing ID in addition to USUBJID in individual PK plots)
- Added clustering function for binning and function to generate binned statistics
- Small bug fixes

V0.5.5 December 04, 2017
- Handling NONMEM 7.4 bug by automatically setting the MUM=N(...) option when needed
- Allow to provide simulatiokn time vector for plot.IQRsysData
- Add convergence info steps to trust and IQRsysPharm
- Add function setparameters_IQRmodel
- Allow not to provide doseNAMES and obsNAMES in IQRdataGENERAL - Handled by identifying doses by ! and the rest as observations.
- Addition of a number of graphical data exploration functions
- Adding optional columns PROFTIME and PROFNR in the general dataset format
- subset_IQRdataGENERAL function
- Access to IQRdataGENERAL attributes via "convenience" functions
- ETA correlation plots were changed to allow for reasonable formatting when a larger number of parameters available in model
- Bug fix and improvement in ETA plots

V0.5.1 October 14, 2017
- Special ACoP8 version

V0.5.0 October 10, 2017
- Exchanged "." in all non-S3 methods to "_"
- Added functions for generation of graphical exploration plots for IQRdataGENERAL objects
- Improved determination of estimated parameters for display purposes
- Display selected order metric in summary IQRnlmeProjectMulti tables
- Improved test-suite for validation of IQRtools
- Minor bug fixed that displayed in print.IQRnlmeEst function the wrong initial guesses for random effects
- Fixed all Notes that were important to fix.
- Improved ETA and ETA vs. COV plots by adding better titles for plots
- Added comparison based on t-test to ETA vs. categorical covariates

V0.4.2 September 21, 2017
- Added function to generate an observation summary table for IQRdataGENERAL objects
- Added function rmDosePostLastObs.IQRdataGENERAL
- Optional removal of doses post last observation in clean.IQRdataGENERAL
- Bootstrap function updated to work with NLMIXR
- Simple NLMIXR Test functions
- Improved annotation of covariateEffect.IQRnlmeProject
- Sampling from uncertainty for MONOLIX results now ensures parameters in correct range (log, logit)
without the user needing to take care of it
- Minor bug fixes

V0.4.1 September 14, 2017
- NLMIXR has been interfaced with IQRtools ... it is experimental still
- Demographics tables generated for IQRdataGENERAL objects
- Exported auxiliary functions
- Small fixes
- Added log for project_model.txt in MONOLIX export and also the graphics.xml one
- Removed the ADM=2 for IV by default if single ROUTE ... for single admin ADM=1 will be default if single ROUTE
- Write out which covariates are not in the data when importing general dataset
- Fixed covariate forest plot if covariate centering was chosen
- Added residuals over TAD to GoF plots
- Removed required dose names from IQRdataGENERAL
- Minor bug fixes where needed


By downloading IQR Tools you agree to have understood that the downloaded software comes without any warranty.

Installation Guide & Documentation


Shiny App for Systems Pharmacology Modeling (see more info here):