Update and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.0

This study demonstrates the utility of an updated mass balance model for predicting the distribution of organic chemicals in in vitro test systems (IV-MBM EQP v2.0) and evaluates its performance with empirical data. The IV-MBM EQP v2.0 tool was parameterized and applied to four independent data sets...

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Autores principales:	James M. Armitage, Alessandro Sangion, Rohan Parmar, Alexandra B. Looky, Jon A. Arnot
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	in vitro bioactivity/toxicity distribution Q-IVIVE Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/852c45b01bc74d2ca5b94e5992b1a138
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spelling	oai:doaj.org-article:852c45b01bc74d2ca5b94e5992b1a1382021-11-25T19:08:21ZUpdate and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.010.3390/toxics91103152305-6304https://doaj.org/article/852c45b01bc74d2ca5b94e5992b1a1382021-11-01T00:00:00Zhttps://www.mdpi.com/2305-6304/9/11/315https://doaj.org/toc/2305-6304This study demonstrates the utility of an updated mass balance model for predicting the distribution of organic chemicals in in vitro test systems (IV-MBM EQP v2.0) and evaluates its performance with empirical data. The IV-MBM EQP v2.0 tool was parameterized and applied to four independent data sets with measured ratios of bulk medium or freely-dissolved to initial nominal concentrations (e.g., C24/C0 where C24 is the measured concentration after 24 h of exposure and C0 is the initial nominal concentration). Model performance varied depending on the data set, chemical properties (e.g., “volatiles” vs. “non-volatiles”, neutral vs. ionizable organics), and model assumptions but overall is deemed acceptable. For example, the r<sup>2</sup> was greater than 0.8 and the mean absolute error (<i>MAE</i>) in the predictions was less than a factor of two for most neutral organics included. Model performance was not as good for the ionizable organic chemicals included but the r<sup>2</sup> was still greater than 0.7 and the <i>MAE</i> less than a factor of three. The IV-MBM EQP v2.0 model was subsequently applied to several hundred chemicals on Canada’s Domestic Substances List (DSL) with nominal effects data (<i>AC</i>50s) reported for two in vitro assays. We report the frequency of chemicals with <i>AC</i>50s corresponding to predicted cell membrane concentrations in the baseline toxicity range (i.e., >20–60 mM) and tabulate the number of chemicals with “volatility issues” (majority of chemical in headspace) and “solubility issues” (freely-dissolved concentration greater than water solubility after distribution). In addition, the predicted “equivalent EQP blood concentrations” (i.e., blood concentration at equilibrium with predicted cellular concentration) were compared to the <i>AC</i>50s as a function of hydrophobicity (log octanol-water partition or distribution ratio). The predicted equivalent EQP blood concentrations exceed the <i>AC</i>50 by up to a factor of 100 depending on hydrophobicity and assay conditions. The implications of using <i>AC</i>50s as direct surrogates for human blood concentrations when estimating the oral equivalent doses using a toxicokinetic model (i.e., reverse dosimetry) are then briefly discussed.James M. ArmitageAlessandro SangionRohan ParmarAlexandra B. LookyJon A. ArnotMDPI AGarticlein vitrobioactivity/toxicitydistributionQ-IVIVEChemical technologyTP1-1185ENToxics, Vol 9, Iss 315, p 315 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	in vitro bioactivity/toxicity distribution Q-IVIVE Chemical technology TP1-1185
spellingShingle	in vitro bioactivity/toxicity distribution Q-IVIVE Chemical technology TP1-1185 James M. Armitage Alessandro Sangion Rohan Parmar Alexandra B. Looky Jon A. Arnot Update and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.0
description	This study demonstrates the utility of an updated mass balance model for predicting the distribution of organic chemicals in in vitro test systems (IV-MBM EQP v2.0) and evaluates its performance with empirical data. The IV-MBM EQP v2.0 tool was parameterized and applied to four independent data sets with measured ratios of bulk medium or freely-dissolved to initial nominal concentrations (e.g., C24/C0 where C24 is the measured concentration after 24 h of exposure and C0 is the initial nominal concentration). Model performance varied depending on the data set, chemical properties (e.g., “volatiles” vs. “non-volatiles”, neutral vs. ionizable organics), and model assumptions but overall is deemed acceptable. For example, the r<sup>2</sup> was greater than 0.8 and the mean absolute error (<i>MAE</i>) in the predictions was less than a factor of two for most neutral organics included. Model performance was not as good for the ionizable organic chemicals included but the r<sup>2</sup> was still greater than 0.7 and the <i>MAE</i> less than a factor of three. The IV-MBM EQP v2.0 model was subsequently applied to several hundred chemicals on Canada’s Domestic Substances List (DSL) with nominal effects data (<i>AC</i>50s) reported for two in vitro assays. We report the frequency of chemicals with <i>AC</i>50s corresponding to predicted cell membrane concentrations in the baseline toxicity range (i.e., >20–60 mM) and tabulate the number of chemicals with “volatility issues” (majority of chemical in headspace) and “solubility issues” (freely-dissolved concentration greater than water solubility after distribution). In addition, the predicted “equivalent EQP blood concentrations” (i.e., blood concentration at equilibrium with predicted cellular concentration) were compared to the <i>AC</i>50s as a function of hydrophobicity (log octanol-water partition or distribution ratio). The predicted equivalent EQP blood concentrations exceed the <i>AC</i>50 by up to a factor of 100 depending on hydrophobicity and assay conditions. The implications of using <i>AC</i>50s as direct surrogates for human blood concentrations when estimating the oral equivalent doses using a toxicokinetic model (i.e., reverse dosimetry) are then briefly discussed.
format	article
author	James M. Armitage Alessandro Sangion Rohan Parmar Alexandra B. Looky Jon A. Arnot
author_facet	James M. Armitage Alessandro Sangion Rohan Parmar Alexandra B. Looky Jon A. Arnot
author_sort	James M. Armitage
title	Update and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.0
title_short	Update and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.0
title_full	Update and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.0
title_fullStr	Update and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.0
title_full_unstemmed	Update and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.0
title_sort	update and evaluation of a high-throughput in vitro mass balance distribution model: iv-mbm eqp v2.0
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/852c45b01bc74d2ca5b94e5992b1a138
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Update and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.0

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