A Toxicokinetic–Toxicodynamic Modeling Workflow Assessing the Quality of Input Mortality Data

Toxicokinetic–toxicodynamic (TKTD) models simulate organismal uptake and elimination of a substance (TK) and its effects on the organism (TD). The Reduced General Unified Threshold model of Survival (GUTS‐RED) is a TKTD modeling framework that is well established for aquatic risk assessment to simul...

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Veröffentlicht in:Environmental toxicology and chemistry 2024-01, Vol.43 (1), p.197-210
Hauptverfasser: Bauer, Barbara, Singer, Alexander, Gao, Zhenglei, Jakoby, Oliver, Witt, Johannes, Preuss, Thomas, Gergs, André
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container_end_page 210
container_issue 1
container_start_page 197
container_title Environmental toxicology and chemistry
container_volume 43
creator Bauer, Barbara
Singer, Alexander
Gao, Zhenglei
Jakoby, Oliver
Witt, Johannes
Preuss, Thomas
Gergs, André
description Toxicokinetic–toxicodynamic (TKTD) models simulate organismal uptake and elimination of a substance (TK) and its effects on the organism (TD). The Reduced General Unified Threshold model of Survival (GUTS‐RED) is a TKTD modeling framework that is well established for aquatic risk assessment to simulate effects on survival. The TKTD models are applied in three steps: parameterization based on experimental data (calibration), comparing predictions with independent data (validation), and prediction of endpoints under environmental scenarios. Despite a clear understanding of the sensitivity of GUTS‐RED predictions to the model parameters, the influence of the input data on the quality of GUTS‐RED calibration and validation has not been systematically explored. We analyzed the performance of GUTS‐RED calibration and validation based on a unique, comprehensive data set, covering different types of substances, exposure patterns, and aquatic animal species taxa that are regularly used for risk assessment of plant protection products. We developed a software code to automatically calibrate and validate GUTS‐RED against survival measurements from 59 toxicity tests and to calculate selected model evaluation metrics. To assess whether specific survival data sets were better suited for calibration or validation, we applied a design in which all possible combinations of studies for the same species–substance combination are used for calibration and validation. We found that uncertainty of calibrated parameters was lower when the full range of effects (i.e., from high survival to high mortality) was covered by input data. Increasing the number of toxicity studies used for calibration further decreased parameter uncertainty. Including data from both acute and chronic studies as well as studies under pulsed and constant exposure in model calibrations improved model predictions on different types of validation data. Using our results, we derived a workflow, including recommendations for the sequence of modeling steps from the selection of input data to a final judgment on the suitability of GUTS‐RED for the data set. Environ Toxicol Chem 2024;43:197–210. © 2023 Bayer AG and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
doi_str_mv 10.1002/etc.5761
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We developed a software code to automatically calibrate and validate GUTS‐RED against survival measurements from 59 toxicity tests and to calculate selected model evaluation metrics. To assess whether specific survival data sets were better suited for calibration or validation, we applied a design in which all possible combinations of studies for the same species–substance combination are used for calibration and validation. We found that uncertainty of calibrated parameters was lower when the full range of effects (i.e., from high survival to high mortality) was covered by input data. Increasing the number of toxicity studies used for calibration further decreased parameter uncertainty. Including data from both acute and chronic studies as well as studies under pulsed and constant exposure in model calibrations improved model predictions on different types of validation data. 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subjects Animal species
Aquatic animals
Calibration
Datasets
Ecological risk assessment
General Unified Threshold model of Survival
Mathematical models
Modelling
Mortality
Parameter sensitivity
Parameter uncertainty
Parameterization
Plant protection
Predictions
Quality assessment
Risk assessment
Survival
Toxicity
Toxicity testing
Toxicodynamics
Toxicokinetics
Toxicology
Validation
Workflow
title A Toxicokinetic–Toxicodynamic Modeling Workflow Assessing the Quality of Input Mortality Data
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