Literature DB >> 28498972

Development of a Combined In Vitro Physiologically Based Kinetic (PBK) and Monte Carlo Modelling Approach to Predict Interindividual Human Variation in Phenol-Induced Developmental Toxicity.

Marije Strikwold1,2, Bert Spenkelink1, Ruud A Woutersen1,3,4, Ivonne M C M Rietjens1,4, Ans Punt1.   

Abstract

With our recently developed in vitro physiologically based kinetic (PBK) modelling approach, we could extrapolate in vitro toxicity data to human toxicity values applying PBK-based reverse dosimetry. Ideally information on kinetic differences among human individuals within a population should be considered. In the present study, we demonstrated a modelling approach that integrated in vitro toxicity data, PBK modelling and Monte Carlo simulations to obtain insight in interindividual human kinetic variation and derive chemical specific adjustment factors (CSAFs) for phenol-induced developmental toxicity. The present study revealed that UGT1A6 is the primary enzyme responsible for the glucuronidation of phenol in humans followed by UGT1A9. Monte Carlo simulations were performed taking into account interindividual variation in glucuronidation by these specific UGTs and in the oral absorption coefficient. Linking Monte Carlo simulations with PBK modelling, population variability in the maximum plasma concentration of phenol for the human population could be predicted. This approach provided a CSAF for interindividual variation of 2.0 which covers the 99th percentile of the population, which is lower than the default safety factor of 3.16 for interindividual human kinetic differences. Dividing the dose-response curve data obtained with in vitro PBK-based reverse dosimetry, with the CSAF provided a dose-response curve that reflects the consequences of the interindividual variability in phenol kinetics for the developmental toxicity of phenol. The strength of the presented approach is that it provides insight in the effect of interindividual variation in kinetics for phenol-induced developmental toxicity, based on only in vitro and in silico testing.
© The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Keywords:  Monte Carlo simulation; PBK or PBPK modelling; UGT; alternatives for animal testing; in vitro–in vivo extrapolation (IVIVE); interindividual differences

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Year:  2017        PMID: 28498972     DOI: 10.1093/toxsci/kfx054

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  9 in total

1.  In vitro-in silico-based prediction of inter-individual and inter-ethnic variations in the dose-dependent cardiotoxicity of R- and S-methadone in humans.

Authors:  Miaoying Shi; Yumeng Dong; Hans Bouwmeester; Ivonne M C M Rietjens; Marije Strikwold
Journal:  Arch Toxicol       Date:  2022-05-23       Impact factor: 6.168

Review 2.  IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making.

Authors:  Xiaoqing Chang; Yu-Mei Tan; David G Allen; Shannon Bell; Paul C Brown; Lauren Browning; Patricia Ceger; Jeffery Gearhart; Pertti J Hakkinen; Shruti V Kabadi; Nicole C Kleinstreuer; Annie Lumen; Joanna Matheson; Alicia Paini; Heather A Pangburn; Elijah J Petersen; Emily N Reinke; Alexandre J S Ribeiro; Nisha Sipes; Lisa M Sweeney; John F Wambaugh; Ronald Wange; Barbara A Wetmore; Moiz Mumtaz
Journal:  Toxics       Date:  2022-05-01

3.  Variability in Human In Vitro Enzyme Kinetics.

Authors:  Christopher R Gibson; Ying-Hong Wang; Ninad Varkhede; Bennett Ma
Journal:  Methods Mol Biol       Date:  2021

Review 4.  Challenges Associated With Applying Physiologically Based Pharmacokinetic Modeling for Public Health Decision-Making.

Authors:  Yu-Mei Tan; Rachel R Worley; Jeremy A Leonard; Jeffrey W Fisher
Journal:  Toxicol Sci       Date:  2018-04-01       Impact factor: 4.849

5.  Use of Physiologically Based Kinetic Modeling to Predict Rat Gut Microbial Metabolism of the Isoflavone Daidzein to S-Equol and Its Consequences for ERα Activation.

Authors:  Qianrui Wang; Bert Spenkelink; Rungnapa Boonpawa; Ivonne M C M Rietjens; Karsten Beekmann
Journal:  Mol Nutr Food Res       Date:  2020-02-25       Impact factor: 5.914

6.  Derivation of a Human In Vivo Benchmark Dose for Bisphenol A from ToxCast In Vitro Concentration Response Data Using a Computational Workflow for Probabilistic Quantitative In Vitro to In Vivo Extrapolation.

Authors:  George Loizou; Kevin McNally; Alicia Paini; Alex Hogg
Journal:  Front Pharmacol       Date:  2022-02-11       Impact factor: 5.810

7.  Inter-individual variation in chlorpyrifos toxicokinetics characterized by physiologically based kinetic (PBK) and Monte Carlo simulation comparing human liver microsome and Supersome cytochromes P450 (CYP)-specific kinetic data as model input.

Authors:  Shensheng Zhao; Sebastiaan Wesseling; Ivonne M C M Rietjens; Marije Strikwold
Journal:  Arch Toxicol       Date:  2022-03-16       Impact factor: 5.153

8.  A Computational Workflow for Probabilistic Quantitative in Vitro to in Vivo Extrapolation.

Authors:  Kevin McNally; Alex Hogg; George Loizou
Journal:  Front Pharmacol       Date:  2018-05-18       Impact factor: 5.810

9.  Integrating biokinetics and in vitro studies to evaluate developmental neurotoxicity induced by chlorpyrifos in human iPSC-derived neural stem cells undergoing differentiation towards neuronal and glial cells.

Authors:  Emma Di Consiglio; Francesca Pistollato; Emilio Mendoza-De Gyves; Anna Bal-Price; Emanuela Testai
Journal:  Reprod Toxicol       Date:  2020-10-01       Impact factor: 3.143

  9 in total

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