Some models developed by LAP&P have been published in the public domain. These can be found in their respective publications listed in the ‘Science’ page of our website. A few selected models have been adapted in R and have been made available as an R-shiny application. These models can be directly applied on a webserver by colleague modellers and scientists for their specific requirements. This way, we try to stimulate the application of modelling and simulation in the research and development of new pharmacological treatment options.

The first two models that can be applied are the Glucose-GLP-1-Glucagon-GIP-Insulin (4GI) model and the cardiovascular safety (CVS) model, also known as the ‘Snelder’ model. The 4GI model relates the homeostatic relationship between glucose, GLP-1, glucagon, GIP, and insulin in a quantitative manner. The CVS model relates the heart rate, stroke volume, cardiac output, total peripheral resistance, and mean arterial blood pressure in rats, in order to aid the development of novel pharmacological interventions.

4GI Model

The 4GI model characterizes important known feedback mechanisms between glucose, GLP-1, glucagon, GIP and Insulin (4GI) after food intake and/or drug administration and can be used as a quantitative decision making tool to support progression of novel molecules modulating the glucose homeostasis. The model was developed using clinical literature data after various non-pharmacological challenges to glucose-regulated pathways (e.g. intravenous glucose, meals, glucagon and incretins). Mean data from three clinical studies (LEAD-3, LEAD-6, AWARD-6 and SUSTAIN-7), in which the effect of GLP-1 agonists on glucose was investigated, were used to describe and validate the effects of GLP-1 agonism.

The 4GI model was linked to the IGRH HbA1c model from literature (Llìedo-Garcìa 2013), to describe changes in HbA1c based on the predicted average daily glucose from the 4GI model.

Currently, the model is being furthered to include mechanisms of energy expenditure and effects on body weight and lipid changes.

The model developed by LAP&P researchers has been translated into an R-shiny application and is available at the following address:

The R-shiny app contains liraglutide, dulaglutide and semaglutide with their PK and corresponding effects on glucose, insulin, GLP-1, glucagon, GIP and HbA1c in a typical Type 2 Diabetic (T2DM) subject. As standard plots fasting plasma glucose and HbA1c over time are visualized. Simulations can be overlaid to compare between dosages and/or compounds. Additionally custom plots can be generated to visualize the free drug, glucose, insulin, glucagon, GLP-1or GIP concentration, HbA1c, as well as the separate compound effects on the system.

For more information please contact


The user can:

  • Simulate compound effects on fasting plasma glucose and HbA1c by:
    • Selecting a compound
    • Selecting a dose (standard dosing schedules and titration schemes for the compounds are applied)
    • Selecting the glucose baseline
  • Generate custom plots after simulation for example
    • Selected biomarker concentration during the day on selected study days
    • Plot the separate GLP-1 agonistic effects over time e.g.
      • Effect on glucose absorption
      • Effect on glucose dependent insulin secretion
      • Effect on glucagon secretion

Literature (see Science)

Bosch R., Petrone M., Hoefman S., Arends R., Vicini P., Snelder N. Predicting the effect of GLP-1 agonists on glucose and HbA1c with a 4GI-HbA1c model. ACOP, 2019.

Bosch R., Petrone M.,Hoefman S., Arends R., Vicini P., Snelder N. Integrate QSP model of in vivo human glucose regulation to support development of a glucagon/GLP-1 dual agonist. WCDT 2019.

Rolien Bosch. Successful Prediction of Continuous Glucose Dynamics and HbA1c Response to the GLP-1 and Glucagon Co-Agonist Cotadutide using the 4GI-HbA1c, Systems Model Systems Pharmacology (SP) Community Network and Community meeting at ASCPT2021 (


CVS model

The CVS model relates heart rate, stroke volume, cardiac output, total peripheral resistance, and mean arterial blood pressure in rats, in order to aid the development of novel pharmacological interventions. This model has been developed on the basis of multiple, advanced pharmacological studies in rats, in which effects of compounds with different mechanisms of action on the system have been studied. The model is currently being further developed in collaboration with the University of Leiden to include contractility and other hemodynamic markers. Furthermore, the model will be translated in order to make predictions in humans possible.

The CVS model developed by LAP&P researchers has been converted into an R-shiny application and will be made available on a webserver. The development of the shiny application has been presented as a poster presentation at the PAGE meeting in 2016.

The CVS model was transformed from NONMEM to R with an in-house developed R package, and implemented in Shiny. The R-shiny app contains several library compounds (e.g., propranolol, amlodipine) with their PK and corresponding effects on MAP, CO, TPR, HR and SV. An option was incorporated to interactively visualize the output of new (hypothetical) treatments based on its experimental or anticipated PK and PD characteristics, including the possibility to investigate a site of action and a type of exposure-response function.


The user can:

  • Select a library model
    • Select dose/dosing regimen
    • Display the model structure and selected site of action
    • Plot its PK and PD
    • Overlay with observations or combine with other treatments
  • Select experimental PK and PD properties
    • Select site of action
    • Select type of exposure-response function
    • Select dose/dosing regimen
    • Select rat strain
    • Overlay with observations or combine with other treatments
    • Change PK and/or PD characteristics based on discussions or known properties (automatic update to outputs)
  • Upload additional data
  • Select plot types, layout and simulation characteristics
  • Save and export results for reporting or re-use

Literature (see Science)

Snelder N., Ploeger B.A., Luttringer O., Rigel D.F., Webb R.L., Feldman D., Fu F., Beil M., Jin L., Stanski D.R. and Danhof M., Characterization and prediction of cardiovascular effects of fingolimod and siponimod using a systems pharmacology modelling approach, J Pharmacol Exp Ther, 1 (116): 236208, 2016. [Link to publication]

Teun M. Post, Nelleke Snelder, and Richard Hooijmaijers. Application of a Shiny Workflow in Cardiovascular Effects Evaluations. PAGE 25 (2016), Abstr 5733. []