New insights to compare and choose TKTD models for survival based on an inter-laboratory study for *Lymnaea stagnalis* exposed to Cd

In Environmental Science and Technology. 52(3):1582-1590


Toxicokinetic-toxicodynamic (TKTD) models, as the General Unified Threshold model of Survival (GUTS), provide a consistent process-based framework compared to classical dose-response models to analyze both time and concentration-dependent data sets. However, the extent to which GUTS models (Stochastic Death (SD) and Individual Tolerance (IT)) lead to a better fitting than classical dose-response model at a given target time (TT) has poorly been investigated. Our paper highlights that GUTS estimates are generally more conservative and have a reduced uncertainty through smaller credible intervals for the studied data sets than classical TT approaches. Also, GUTS models enable estimating any x% lethal concentration at any time (LC(x,t)), and provide biological information on the internal processes occurring during the experiments. While both GUTS-SD and GUTS-IT models outcompete classical TT approaches, choosing one preferentially to the other is still challenging. Indeed, the estimates of survival rate over time and LC(x,t) are very close between both models, but our study also points out that the joint posterior distributions of SD model parameters are sometimes bimodal, while two parameters of the IT model seems strongly correlated. Therefore, the selection between these two models has to be supported by the experimental design and the biological objectives, and this paper provides some insights to drive this choice.


GUTS models, classical dose-response models, constant exposure, aquatic toxicity, x% lethal concentration

Citation in bibtex

    author    = {Baudrot, Virgile and Preux, Sara and Ducrot, Virginie and Pavé, Alain and Charles, Sandrine},
    title     = {New insights to compare and choose TKTD models for survival based on an inter-laboratory study for \emph{Lymnaea stagnalis} exposed to Cd},
    journal   = {Environmental science \& technology},
    year      = {2018},
    date      = {2018-01-23},
    number    = {52},
    issue     = {3},
    doi       = {10.1021/acs.est.7b05464},
    publisher = {ACS Publications}