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Updated: Mar 15, 2026

Advanced 3D Liver Models for In vitro Genotoxicity Testing Following Long-Term Nanomaterial Exposure
Published on: June 5, 2020
Advancing In Vitro-In Vivo Extrapolations of Mechanism-Specific Toxicity Data Through Toxicokinetic Modeling
Markus Brinkmann1, Thomas G Preuss2, Henner Hollert3,4,5,6
1Department of Ecosystem Analysis, Institute for Environmental Research, Aachen Biology and Biotechnology - ABBt, RWTH Aachen University, Worringerweg 1, 52074, Aachen, Germany. markus.brinkmann@bio5.rwth-aachen.de.
Abstract:
International legislation, such as the European REACH regulation (registration, evaluation, authorization, and restriction of chemicals), mandates the assessment of potential risks of an ever-growing number of chemicals to the environment and human health. Although this legislation is considered one of the most important investments in consumer safety ever, the downside is that the current testing strategies within REACH rely on extensive animal testing. To address the ethical conflicts arising from these increased testing requirements, decision-makers, such as the European Chemicals Agency (ECHA), are committed to Russel and Burch's 3R principle (i.e., reduction, replacement, refinement) by demanding that animal experiments should be substituted with appropriate alternatives whenever possible. A potential solution of this dilemma might be the application of in vitro bioassays to estimate toxic effects using cells or cellular components instead of whole organisms. Although such assays are particularly useful to assess potential mechanisms of toxic action, scientists require appropriate methods to extrapolate results from the in vitro level to the situation in vivo. Toxicokinetic models are a straightforward means of bridging this gap. The present chapter describes different available options for in vitro-in vivo extrapolation (IVIVE) of mechanism-specific effects focused on fish species and also reviews the implications of confounding factors during the conduction of in vitro bioassays and their influence on the optimal choice of different dose metrics.
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