Quantitative In Vitro-to-In Vivo Extrapolation: Nominal versus Freely Dissolved Concentration

Abstract

Discussions are ongoing on which dose metric should be used for quantitative in vitro-to-in vivo extrapolation (QIVIVE) of in vitro bioassay data. The nominal concentration of the test chemicals is most commonly used and easily accessible, while the concentration freely dissolved in the assay medium is considered to better reflect the bioavailable concentration but is tedious to measure. The aim of this study was to elucidate how much QIVIVE results will differ when using either nominal or freely dissolved concentrations. QIVIVEnom and QIVIVEfree ratios, that is, the ratios of plasma concentrations divided by in vitro effect concentrations, were calculated for 10 pharmaceuticals using previously published nominal and freely dissolved effect concentrations for the activation of the peroxisome proliferator-activated receptor gamma (PPARγ) and the activation of oxidative stress response. The QIVIVEnom ratios were higher than QIVIVEfree ratios by up to a factor of 60. The risk of in vivo effects was classified as being high or low for four chemicals using the QIVIVEnom and for three chemicals using QIVIVEfree ratios. Unambiguous classification was possible for nine chemicals by combining the QIVIVEnom or QIVIVEfree ratios with the respective specificity ratios (SRnom or SRfree) of the in vitro effect data, which helps to identify whether the specific effect was influenced by cytotoxicity. QIVIVEfree models should be preferred as they account for differences in bioavailability between in vitro and in vivo, but QIVIVEnom may still be useful for screening the effects of large numbers of chemicals because it is generally more conservative. The use of SR of the in vitro effect data as a second classification factor is recommended for QIVIVEnom and QIVIVEfree models because a clearer picture can be obtained with respect to the likelihood that a biological effect will occur and that it is not caused by nonspecific cytotoxicity.

High-Throughput Assessment of the Abiotic Stability of Test Chemicals in In Vitro Bioassays

“…QIVIVE models are usually based on the nominal concentration, which does not take into account either partitioning processes ( e.g. , binding to proteins or plate material) or loss processes (abiotic degradation, metabolism, volatilization) of the test chemicals during the assay. ,, Differences in the stability of the test chemicals between the in vitro bioassays and in vivo in humans may be a major impediment for using bioassay data for human health risk assessment.…”

“…Various loss processes, like volatilization, sorption to the plastic of the well plate, and interactions with components of the medium or the cells, can cause the actual bioavailable concentration to deviate from the nominal concentration. − Less attention has so far been paid to abiotic transformation of the test chemicals, although it has been shown that test chemicals can react with components of the bioassay medium. , Transformation processes may lead to a decrease in the concentration of the parent chemical over time, leading to an apparently lower effect. In addition, inactive or active transformation products can be formed, resulting in an underestimation or overestimation of the toxicity of the chemical. , If these processes remain unnoticed, this might lead to considerable errors in QIVIVE models . The stability of chemicals in in vitro assays is not routinely monitored, and prediction models are not tailored to bioassay conditions but rather to environmental degradation. − …”

“…16,17 If these processes remain unnoticed, this might lead to considerable errors in QIVIVE models. 18 The stability of chemicals in in vitro assays is not routinely monitored, and prediction models are not tailored to bioassay conditions but rather to environmental degradation. 19−22 The aim of this study was to develop a high-throughput (HT) method to quantify degradation kinetics of chemicals in bioassay media in the absence of cells to assess whether the chemical is abiotically degraded in the time course of an in vitro bioassay.…”

In vitro to in vivo extrapolation to support the development of the next generation risk assessment (NGRA) strategy for nanomaterials

“…Henneberger et al noted the advantages of using concentration in the assay medium as a metric for quantitative in vitro to in vivo extrapolation (QIVIVE) rather than the nominal concentration of the test chemicals. 41 Although their study was based on small-molecule xenobiotics, the same conclusions are also rational for NMs. Thus, developing a consistent and reliable methodology would require supplementing the in vitro tests with kinetic information.…”

Toward Realistic Dosimetry In Vitro: Determining Effective Concentrations of Test Substances in Cell Culture and Their Prediction by an In Silico Mass Balance Model

“…In addition to the experimental methods, in silico models have been established and used to predict in vitro -derived concentrations. , Commonly, these models assume steady state and an equilibrated partitioning between the compartment culture medium, cells, headspace, and plastics. Different elements such as spontaneous and enzymatic degradation, ionization of test chemicals, or the pH of different compartments were implemented in these models. ,,− More comprehensive models for predicting a test chemical’s fate in the in vitro test systems are recommended but not yet sufficiently established, mainly due to the lack of experimental data to validate them. , We have developed an as yet unpublished refined mass balance model using equations from versions developed by Armitage et al, Fischer et al, and Kramer et al While the equations used within the current model are not new, the combination of all of them is. The model assumes instantaneous equilibrium and is based on mass balance equations describing the partitioning between five compartments of an in vitro test system: headspace, serum components (proteins and lipids), cells, water phase (free), and plastic (Figure ).…”