Modeling Exposure in the Tox21 <i>in Vitro</i> Bioassays

Fischer, Fabian C.; Henneberger, Luise; König, Maria; Bittermann, Kai; Linden, Lukas; Goss, Kai‐Uwe; Escher, Beate I.

doi:10.1021/acs.chemrestox.7b00023

Cited by 115 publications

(210 citation statements)

References 66 publications

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“…The sorption of lipophilic substances to plastic material used for exposure is well known [36,104]. Sorption could decrease the exposure concentration leading to underestimation of effects if based on nominal concentrations.…”

Section: Materials Used For Exposure Vesselsmentioning

confidence: 99%

Hypo- or hyperactivity of zebrafish embryos provoked by neuroactive substances: a review on how experimental parameters impact the predictability of behavior changes

et al. 2019

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Tests with zebrafish embryos have gained wide acceptance as an alternative test model for drug development and toxicity testing. In particular, the behavioral response of the zebrafish embryo is currently seen as a useful endpoint to diagnose neuroactive substances. Consequently, several behavioral test methods have been developed addressing various behavioral endpoints such as spontaneous tail coiling (STC), photomotor response (PMR), locomotor response (LMR) and alternating light/dark-induced locomotor response (LMR-L/D). Although these methods are distinct in their application, most of their protocols differ quite strongly in the use of experimental parameters and this is usually driven by different research questions. However, if a single mode of action is to be diagnosed, then varying experimental parameters may cause incoherent behavioral responses (hypo-or hyperactivity) of zebrafish during toxicity assessment. This could lead to inconclusiveness of behavioral test results for use within a prospective and diagnostic risk assessment framework. To investigate the influence of these parameters, we conducted a review of existing behavioral assays to address the following two questions: (1) To what extent do varying experimental parameters influence observed effects in published behavioral test methods? (2) Is the observed behavior change (hypo-or hyperactivity) of zebrafish embryos consistent with the expected mode of action of a chemical? We compiled a set of 18 substances which are anticipated to be neuroactive. We found that behavioral changes are not only affected by chemicals but also variation in the use of experimental parameters across studies seems to have a high impact on the outcome and thus comparability between studies. Four parameters, i.e., exposure concentration, exposure duration, endpoint parameter and developmental stage were the most influential parameters. Varying combinations of these parameters caused a non-reproducible outcome for the hyperactivity expected for the organophosphates; chlorpyrifos and diazinon. We highlighted that the STC test shows a higher capacity to predict the hyperactivity of organophosphates, while PMR and LMR-L/D were more suitable to predict the hypoactivity expected for anticonvulsants. We provide a list of recommendations which, when implemented, may help to exclude the risk of bias due to experimental parameters if similar goals are desired.

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Section: Materials Used For Exposure Vesselsmentioning

confidence: 99%

Hypo- or hyperactivity of zebrafish embryos provoked by neuroactive substances: a review on how experimental parameters impact the predictability of behavior changes

et al. 2019

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“…An in vitro biokinetic study plays a significant role in translating a nominal concentration used in in vitro systems to the actual level of cell exposure producing the effect. Several methodologies can be applied to address such a relationship, such as in vitro fate and transport mass balance models recently developed by several research teams [26] , [27] , [3] , [21] , [73] .…”

Section: Salient Features: Constructing Pbk Models For Safety Assessmmentioning

confidence: 99%

Next generation physiologically based kinetic (NG-PBK) models in support of regulatory decision making

Paini

Leonard

Joossens

et al. 2019

Computational Toxicology

111

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Highlights PBK models have helped to facilitate quantitative in vitro to in vivo extrapolation. PBK modelling has the potential to play a significant role in reducing animal testing. It is critical to assess the validity of PBK models built using non-animal data. A framework is needed for communicating characteristics and results of PBK modelling.

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“…The Virtual Cell Based Assay (VCBA) project in Joint Research Centre in European Union aims to predict time-dependent concentrations of a test chemical both in the culture medium and within the cells by using ordinary differential equations that incorporate the physicochemical properties of the chemical and metabolic and cellular properties of the cell lines. The determined free concentrations in the culture medium can be different from the nominal concentrations by several orders of magnitude, emphasizing the importance of characterizing chemical distribution in in vitro assays ( 46 , 47 ). These in vitro kinetic models can be used to predict cultural and intracellular chemical concentration changes over time for initial chemical dose or repeated dose not experimentally tested.…”

Section: Computational Approaches For Dose-response and Extrapolationmentioning

confidence: 99%

Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling

Zhang

Jin

Middleton

et al. 2018

Front. Public Health

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Chemical toxicity testing is moving steadily toward a human cell and organoid-based in vitro approach for reasons including scientific relevancy, efficiency, cost, and ethical rightfulness. Inferring human health risk from chemical exposure based on in vitro testing data is a challenging task, facing various data gaps along the way. This review identifies these gaps and makes a case for the in silico approach of computational dose-response and extrapolation modeling to address many of the challenges. Mathematical models that can mechanistically describe chemical toxicokinetics (TK) and toxicodynamics (TD), for both in vitro and in vivo conditions, are the founding pieces in this regard. Identifying toxicity pathways and in vitro point of departure (PoD) associated with adverse health outcomes requires an understanding of the molecular key events in the interacting transcriptome, proteome, and metabolome. Such an understanding will in turn help determine the sets of sensitive biomarkers to be measured in vitro and the scope of toxicity pathways to be modeled in silico. In vitro data reporting both pathway perturbation and chemical biokinetics in the culture medium serve to calibrate the toxicity pathway and virtual tissue models, which can then help predict PoDs in response to chemical dosimetry experienced by cells in vivo. Two types of in vitro to in vivo extrapolation (IVIVE) are needed. (1) For toxic effects involving systemic regulations, such as endocrine disruption, organism-level adverse outcome pathway (AOP) models are needed to extrapolate in vitro toxicity pathway perturbation to in vivo PoD. (2) Physiologically-based toxicokinetic (PBTK) modeling is needed to extrapolate in vitro PoD dose metrics into external doses for expected exposure scenarios. Linked PBTK and TD models can explore the parameter space to recapitulate human population variability in response to chemical insults. While challenges remain for applying these modeling tools to support in vitro toxicity testing, they open the door toward population-stratified and personalized risk assessment.

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Modeling Exposure in the Tox21 in Vitro Bioassays

Cited by 115 publications

References 66 publications

Hypo- or hyperactivity of zebrafish embryos provoked by neuroactive substances: a review on how experimental parameters impact the predictability of behavior changes

Hypo- or hyperactivity of zebrafish embryos provoked by neuroactive substances: a review on how experimental parameters impact the predictability of behavior changes

Next generation physiologically based kinetic (NG-PBK) models in support of regulatory decision making

Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling

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