IntiQuan Webinar Series

Efficient Support of Model Informed Drug Development (MIDD) in R

IntiQuan is holding a series of free webinars based on IntiQuan’s R-based open source modeling & simulation platform
IQR Tools. The topics range from model representation over population modeling, both in the context of PK(PD) and QSP, to advanced clinical trial simulation, considering drop-out and compliance models.

One of the many advantages of using IQR Tools lies in the fact that a model only needs to be coded once, and this is done in an intuitive format that relies on simple math. Behind the scenes conversion is done in an automatic manner – independent if it is to C-code (for fast simulation) or to NONMEM or MONOLIX (for NLME parameter estimation). In addition, the model syntax is application agnostic, meaning that IQR Tools can support both Pharmacometric and QSP modeling in an identical and equally intuitive manner.

Due to the breadth of topics to cover on the topic of MIDD, we decided to modularize the webinars. This allows for short duration single webinars that allow sequential participation.

Each webinar module is self contained but assumes (at least some basic) knowledge of the previous modules. QSP and PKPD webinar modules are independent of each other.


Material for each module is provided to participants as a download, including the webinar presentation (PDF) and all examples and scripts that allow to rerun.


Not many. You can just watch, listen and get information about state-of-the-art modeling and simulation approaches.

If you would like to run the examples yourself you will need to have an installation of IQR Tools on your computer. Installation is very easy and explained here.

  • For Modules 1.x and 4.x you only need R and IQR Tools.
  • For Modules 2.x and 3.x you will need in addition an installation of MONOLIX, NONMEM, or NLMIXR on your computer, as in these modules IQR Tools will be used to automatically generate NLME projects, run them, and postprocess results in report ready quality. The setup of tools can be cumbersome (ask your sysadmin about it :-)). And in addition CRAN typically totally messes up reproducibility. For this reason, we suggest to consider the installation of IQdesktop, a freely available virtual computer system that already includes all needed software package for efficient support of MIDD. Just bring you own MONOLIX or NONMEM license (or use NLMIXR). Installation of IQdesktop is easy and typically done within minutes.


Registration for each webinar module is free of charge but places are limited. You can register from the following webpage:

Goals of Module 1

Module Goals Time Link to registration page
M1.1 – Models
  • You will have seen examples on how to
    • Define ODE based models in the IQRmodel syntax
      • Standard pharmacometric PK models
      • PK/PD models
      • Mechanistic models
    • Perform simple simulations, including different dosing scenarios
  • Giving you the possibility to define own models and perform own simulations
90 min Registration
M1.2 – Simulation
  • You will have seen examples on how to
    • Perform a variety of different simulations in IQR Tools with focus on
      • Standard pharmacometric PK models
      • PKPD models
      • Exposure/response models
      • Mechanistic models
    • Changing dosing regimen and parameters
    • Determine exposure metrics of interest and present them in a tabular form
    • Optimize integrator settings adapted to needs of your model
    • Perform a simple population simulation
  • Giving you the possibility to write own scripts for simulations in IQR Tools
90 min Registration
M1.3 – Parameter Sampling
  • You will have seen examples on how to
    • Represent parameter estimates published for literature models allowing to easily perform sampling from uncertainty and variability distributions, covering
      • Fixed and random effects
      • Correlation of random effects
      • Uncertainty, including correlation matrix
      • Covariates
    • Sample from this representation
    • Perform simulations based on the drawn samples
  • Giving you the possibility to write own scripts for simulations with complex sampling of simulation parameters in IQR Tools
75 min Registration
M1.4 – Population Simulation
  • You will have seen examples on how to
    • Set up population simulations, considering the
      • Population to be simulated (covariates)
      • Sample individual parameters for simulation
      • Simulation of individuals
      • Two approaches will be demonstrated
        • IQRdosing based (easy but slower)
        • IQReventTable based (advanced but much faster)
      • Combine simulation results in a dataset
      • Postprocess simulation results in tables and figures
  • Giving you the possibility to write own scripts for population simulations

Note: populations simulations go a long way towards clinical trial simulations –this Module 1.4 takes up basic but important concepts. More details on Clinical Trial Simulations are given in Module 4.2”Clinical trial simulation”

75 min Registration

Goals of Module 2

Module Goals Time Link to registration page
M2.1 – Data Format
  • You will have been introduced to an NLME dataset format that can be used for NONMEM, MONOLIX, and NLMIXR.
    • No recoding required.
    • In addition, this dataset format allows to store critical metadata directly in the dataset – rendering the dataset self-explaining and its handling less prone to errors than typical “numeric only” NONMEM datasets.
    • This format can be generated automatically starting from an even more convenient “general dataset format”. An example will be provided.

This module is suggested to have seen before embarking on the following modules that will focus on NLME modeling in NONMEM, MONOLIX, and NLMIXR. It will give you the ability to define own datasets in this format.

60 min Registration
M2.2 – Basic PK/PD  (NLME) Parameter estimation
  • You will have seen examples on how to
    • Easily setup NLME parameter estimations based on
      • A dataset (see Module 2.1)
      • A structural model (see Module 1.1)
      • A flexible and powerful description of the error model, statistical model, covariate model, etc.
    • Automatic conversion to NONMEM, MONOLIX, and NLMIXR projects
    • Execution of the NLME parameter estimation
    • Automatic post-processing of results
    • Comparison of any desired models
    • Generation of a model development table
    • Easy access to  all generated output tables (same format across the different parameter estimation tools)
    • Main focus will be on PK models with a single output. PKPD models – both sequential and joint estimation will be considered in Module 2.3.
  • Giving you the possibility to setup own NLME parameter estimation projects in IQR Tools.
90 min Registration
M2.3 – Advanced PK/PD (NLME) Parameter Estimation
  • You will have seen examples on how to
    • Perform parameter estimation in more complex settings than presented in Module 2.2.
      • Multiple routes of administration
      • PKPD models both with sequential and joint parameter estimation
    • Generate VPCs and pcVPCs
    • Run bootstraps
    • Use automatically generated information to guide covariate modeling (full covariate modeling approach)
    • Simulation based on NLME results through direct sampling from the NLME projects
90 min Registration
M2.4 – Exposure Response Modeling
  • You will have seen examples on how to perform exposure/response modeling in IQR Tools
    • NLME based ER modeling using IQRmodels (linear, non-linear regression)
    • Logistic-regression
    • Parametric time-to-event analyses and cox regression
90 min Registration

Goals of Module 3

Note that currently not all modules are listed below – this will be updated as the webinar series progresses in 2021.

Goals of Module 4

Note that currently not all modules are listed below – this will be updated as the webinar series progresses in 2021.

Goals of Module X

Note that currently not all modules are listed below – this will be updated as the webinar series progresses in 2021.