Robust Fit of Toxicokinetic–Toxicodynamic Models Using Prior Knowledge Contained in the Design of Survival Toxicity Tests
Abstract
Toxicokinetics–toxicodynamic (TKTD) models have emerged as a powerful means to describe survival as a function of time and concentration in ecotoxicology. They are especially powerful to extrapolate survival observed under constant exposure conditions to survival predicted under realistic fluctuating exposure conditions. But despite their obvious benefits, these models have not yet been adopted as a standard to analyze data of survival toxicity tests. Instead simple dose–response models are still often used although they only exploit data observed at the end of the experiment. We believe a reason precluding a wider adoption of TKTD models is that available software still requires strong expertise in model fitting. In this work, we propose a fully automated fitting procedure that extracts prior knowledge on parameters of the model from the design of the toxicity test (tested concentrations and observation times). We evaluated our procedure on three experimental and 300 simulated data sets and showed that it provides robust fits of the model, both in the frequentist and the Bayesian framework, with a better robustness of the Bayesian approach for the sparsest data sets.
Cited By
This article is cited by 7 publications.
- Virgile Baudrot, Sara Preux, Virginie Ducrot, Alain Pave, and Sandrine Charles . New Insights to Compare and Choose TKTD Models for Survival Based on an Interlaboratory Study for Lymnaea stagnalis Exposed to Cd. Environmental Science & Technology 2018, 52 (3) , 1582-1590. https://doi.org/10.1021/acs.est.7b05464
- Tjalling Jager . Comment on “Robust Fit of Toxicokinetic–Toxicodynamic Models Using Prior Knowledge Contained in the Design of Survival Toxicity Tests”. Environmental Science & Technology 2017, 51 (14) , 8200-8201. https://doi.org/10.1021/acs.est.7b02001
- Tjalling Jager. Robust Likelihood‐Based Approach for Automated Optimization and Uncertainty Analysis of Toxicokinetic‐Toxicodynamic Models. Integrated Environmental Assessment and Management 2020, 44 https://doi.org/10.1002/ieam.4333
- Yongfei Gao, Zhicheng Xie, Mingfeng Feng, Jianfeng Feng, Lin Zhu. A biological characteristic extrapolation of compound toxicity for different developmental stage species with toxicokinetic-toxicodynamic model. Ecotoxicology and Environmental Safety 2020, 203 , 111043. https://doi.org/10.1016/j.ecoenv.2020.111043
- Virgile Baudrot, Sandrine Charles. Recommendations to address uncertainties in environmental risk assessment using toxicokinetic-toxicodynamic models. Scientific Reports 2019, 9 (1) https://doi.org/10.1038/s41598-019-47698-0
- An He, Xinyong Liu, Liang Qu, Yongfei Gao, Jianfeng Feng, Lin Zhu. Comparison of the General Threshold Model of Survival and Dose–Response Models in Simulating the Acute Toxicity of Metals to Danio rerio. Environmental Toxicology and Chemistry 2019, 38 (10) , 2169-2177. https://doi.org/10.1002/etc.4534
- Virgile Baudrot, Philippe Veber, Guillaume Gence, Sandrine Charles. Fit Reduced GUTS Models Online: From Theory to Practice. Integrated Environmental Assessment and Management 2018, 14 (5) , 625-630. https://doi.org/10.1002/ieam.4061