Journal article
Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling
Frontiers in public health, Vol.6, pp.261-261
09/11/2018
DOI: 10.3389/fpubh.2018.00261
PMCID: PMC6141783
PMID: 30255008
Abstract
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.
Details
- Title: Subtitle
- Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling
- Creators
- Qiang Zhang - , , , , , , , ,Jin LiAlistair Middleton - UnileverSudin Bhattacharya - Michigan State UniversityRory B. Conolly - Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory, United States Environmental Protection Agency, Durham, NC, United States.
- Resource Type
- Journal article
- Publication Details
- Frontiers in public health, Vol.6, pp.261-261
- Publisher
- Frontiers Media S.A
- DOI
- 10.3389/fpubh.2018.00261
- PMID
- 30255008
- PMCID
- PMC6141783
- ISSN
- 2296-2565
- eISSN
- 2296-2565
- Grant note
- Unilever P42ES04911 / National Institute of Environmental Health Sciences
- Language
- English
- Date published
- 09/11/2018
- Academic Unit
- Neurology
- Record Identifier
- 9984302199002771
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