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Supporting mechanistic modelling for survival

DEBtox Researc

Support sites and documents

On the software.
Manuals and documentation can be downloaded from the download page. There is no helpdesk for the use of the software. However, the DEBtox discussion board has an area for discussions on GUTS. We hope that in the future this becomes a place where users can help each other. For reporting bugs, errors or wishes for future releases, please use the discussion board or send an email to Tjalling Jager (see email at bottom of this page).
    For the Matlab version, feel free to contact Tjalling Jager directly. He will be able to assist with small problems. Larger problems or additional functionality can be discussed as well, although they will generally require funding.

On the statistical/optimisation framework. The general statistical framework and the automated optimisation algorithm as developed for openGUTS have been described in detail in a manuscript, including an extensive supporting information: Jager, T. (2021). Robust likelihood-based approach for automated optimization and uncertainty analysis of toxicokinetic-toxicodynamic models. Integr. Environ. Assess. Manag. 17(2):388-397

On GUTS. The e-book on GUTS is now the definitive guide to the framework. It also provides the conceptual background, as well as the technical details on the model equations and the statistical framework. This book is freely-downloadable from Leanpub (payment is optional).

On risk assessment with GUTS. The EFSA opinion on TKTD models is the current go-to document when it comes to risk assessment for pesticides. Also relevant in this context is the EFSA opinion on good modelling practice. Note that openGUTS can also be used to calculate a no-effect concentration (threshold), or the traditional LCx,t values, for a range of effect levels x and time points t (using the complete data set with all observations over time).
   See also the following paper: Brock et al. (acc.). Application of GUTS models for regulatory aquatic pesticide risk assessment illustrated with an example for the insecticide chlorpyrifos. Acc. Integr. Environ. Assess. Manag.

Publications on GUTS. The DEBtox information website maintains a list of publications that apply GUTS, or predecessors now viewed as special cases (for stochastic death only). Currently, this list contains more than 100 entries.

Alternative software for GUTS analyses

If openGUTS cannot do the analysis that you want, or if you want a 'second opinion', feel free to try one of the alternative software platforms. We have not tested these versions in detail, so we cannot comment on their correctness or user-friendliness. However, these platforms (often in an older version) were included in the ring test, which is reported in the e-book. A potential source of differences between these platforms lies in how they constrain parameter space; for some data sets, parameters will not be constrained by the data, and can go to zero or infinity (consult the interpretation guide from the download page for typical examples). 'Frequentist' applications generally use hard min-max boundaries, whereas Bayesians use (weakly) informative prior distributions.

MOSAIC. A web-based and user-friendly way to perform GUTS calculations (reduced SD and IT models only) is available at See also the paper of Baudrot et al. Under the hood, it applies Bayesian inference with the MORSE R-package (see below). Predictions for exposure profiles can be made with the associated Shiny app. It is good to note that the rules for designing priors, as used in this version, tend to block 'slow kinetics'. An example is provided in the "test results for openGUTS" document from the download page. Since 'slow kinetics' would generally be the 'worst case' interpretation of the data in risk assessment, use of this software requires due care.

GUTS-3S. Developed at the Fraunhofer Institute in as a standalone executable. More information.

EasyGUTS. Under development by RIFCON. A test version is available on request. More information (scroll down to EasyGUTS). It is a shell around the GUTS R-package of Albert and Vogel (see below).

R-packages. There are two R-packages available for GUTS calculations in a Bayesian framework. The first package was developed by Carlo Albert & Sören Vogel, is currently maintained by RIFCON, and can be found at The second is the MORSE R-package, as developed and maintained by the University of Lyon. It contains the reduced SD and IT models. This package can be found at and forms the basis for the web-based interface MOSAIC. Requires installation of R (free). It is good to note that the rules for designing priors, as used in this version, tend to block 'slow kinetics'. An example (using MOSAIC, which applies the same rules) is provided in the "test results for openGUTS" document from the download page.

Python package. A Python toolbox for GUTS calculations was developed by Raymond Nepstad (SINTEF, Trondheim), and can be downloaded from GitHub: Requires installation of Python (free).

Matlab packages. Apart from the Matlab prototype, there is also an extensive Matlab toolbox as part of the BYOM platform (developed and maintained by Tjalling Jager, DEBtox Research). This toolbox includes all GUTS cases (also the full model), can do 'frequentist' and Bayesian inference, but has limited user-friendliness. Requires a license for Matlab.

Mathematica package. Developed by Andreas Focks (WUR, Wageningen). This package is part of the huge file with supporting information of the EFSA opinion (if you are able to find it), but the Mahematica part can also be downloaded here (ZIP file, 17 MB). Requires a license for Mathematica.

Links with more information or useful tools

  • Roman Ashauer's website about models in ecotoxicology at:
  • The DEBtox information site at This site contains information on GUTS and DEBtox, and also includes lists of publications that feature these models.
  • SETAC-Europe interest group on effect modelling. More information.

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EFSA scientific opinion

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The openGUTS project, This site is maintained by Tjalling Jager, email: tjalling (at)