Fraunhofer Institute for Molecular Biology and Applied Ecology IME

Exposure and Effect Modelling

Integrating exposure and effect models to predict environmental risks of chemicals.

We combine mechanistic exposure modelling with statistical and mechanistic effect models to link time-variable environmental exposure to internal concentrations and biological effects. Our workflows support environmental risk assessment by quantifying uncertainty, comparing scenarios, and translating data into decision-ready results.

Key benefits

Mechanistic and data-driven: from chemical properties to organism and population-level endpoints.
Transferable: applicable across species, life stages, and environmental conditions.
Regulatory-ready: validated workflows including sensitivity and uncertainty analysis.

How it works

Data & study design: integrate lab, field, and (where available) omics data; define endpoints, scenarios, and acceptance criteria.
Environmental fate & exposure: simulate concentrations in water, sediment, and soil using established scenarios and models.
Effect modelling (TKTD): link exposure profiles to time-dependent effects (e.g., survival, growth) and calibrate models to experimental data.
Risk interpretation: compare scenarios, quantify uncertainty, and provide transparent outputs for regulatory and research decisions.

What we deliver

Exposure profiles: predicted environmental concentrations and time series for defined scenarios.
TKTD model applications: calibrated models linking exposure to survival and growth under time-variable exposure.
Uncertainty & sensitivity analysis: transparent quantification of key drivers and confidence in results.
Decision-ready reporting: clear documentation and outputs aligned with regulatory and research needs.

Implementation & tools

We implement exposure and effect models in reproducible workflows and provide software-based solutions where appropriate (e.g., for exposure scenarios, model calibration, and sensitivity analysis).

Software

Use cases

Selected Publications

Witt, J.; Hommen, U.; Klein, J.; Gabsi, F.; Solga, A.; Schrader, D.; Kuhl, K.; Preuss, T. G.

MAGMA: A modelling approach for growth inhibition of macrophytes to predict effects of time variable exposure under laboratory conditions.

(2025) Environmental Toxicology and Chemistry

Publication

Daniels, B.; Hommen, U.; Ratte, M

Four parameter nonlinear regression and maximum achievable effect in ecotoxicology: just visually appealing or relevant for risk assessment?

(2025) Integrated Environmental Assessment and Management

Publication

Klein, J.; Skodras, D.

Leaching Calculator: a tool for predicting leachability within the framework of the new mobility-related hazard classes PMT and vPvM.

(2025) Integrated Environmental Assessment and Management

Publication

Burkhardt, M.; Rohr, M.; Patrick, M.; Tietje, O.; Lange, J.; Linke, F.; Skodras, D.; Klein, M.; Klein, J.

Groundwater discharges of biocides from façades in urban regions (GRUBURG)

(2025) German Environment Agency

Publication

Essfeld, F.; Ayobahan, S. U.; Strompen, J.; et al

Transcriptomic Point of Departure (tPOD) of androstenedione in zebrafish embryos as a potential surrogate for chronic endpoints.

(2024) Science of the Total Environment

Publication

Hommen, U.; Charles, S.; Preuss, T. G.

Mechanistic effect models in ecological risk assessment.

(2024) In: Vighi, M. (ed.), General Principles of Ecological Risk Assessment: Protecting Ecosystems in the Third Millennium. Cambridge Scholars Publishing

Publication

Pohl, M.; Hommen, U.; Eilebrecht, S.; Schäfers, C.; Gadau, J.; Otto, M.

Estimation of relevant exposure routes of ants to pesticides and plant incorporated protectants.

(2024) Environmental Chemistry and Ecotoxicology

Publication