Literature DB >> 24863738

Use of in vitro data in developing a physiologically based pharmacokinetic model: Carbaryl as a case study.

Miyoung Yoon1, Gregory L Kedderis2, Grace Zhixia Yan3, Harvey J Clewell4.   

Abstract

In vitro-derived information has been increasingly used to support and improve human health risk assessment for exposure to chemicals. Physiologically based pharmacokinetic (PBPK) modeling is a key component in the movement toward in vitro-based risk assessment, providing a tool to integrate diverse experimental data and mechanistic information to relate in vitro effective concentrations to equivalent human exposures. One of the challenges, however, in the use of PBPK models for this purpose has been the need for extensive chemical-specific parameters. With the remarkable advances in in vitro methodologies in recent years, in vitro-derived parameters can now be easily incorporated into PBPK models. In this study we demonstrate an in vitro data based parameterization approach to develop a physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model, using carbaryl as a case study. In vitro experiments were performed to provide the chemical-specific pharmacokinetic (PK) and pharmacodynamic (PD) parameters for carbaryl in the PBPK model for this compound. Metabolic clearance and cholinesterase (ChE) interaction parameters for carbaryl were measured in rat and human tissues. These in vitro PK and PD data were extrapolated to parameters in the whole body PBPK model using biologically appropriate scaling. The PBPK model was then used to predict the kinetics and ChE inhibition dynamics of carbaryl in vivo. This case study with carbaryl provides a reasonably successful example of utilizing the in vitro to in vivo extrapolation (IVIVE) approach for PBPK model development. This approach can be applied to other carbamates with an anticholinesterase mode of action as well as to environmental chemicals in general with further refinement of the current shortcomings in the approach. It will contribute to minimizing the need for in vivo human data for PBPK model parameterization and evaluation in human risk assessments.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Carbaryl; Cholinesterase inhibition; Hepatocytes; In vitro to in vivo extrapolation; Metabolism; PBPK model

Mesh:

Substances:

Year:  2014        PMID: 24863738     DOI: 10.1016/j.tox.2014.05.006

Source DB:  PubMed          Journal:  Toxicology        ISSN: 0300-483X            Impact factor:   4.221


  10 in total

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3.  Opportunities and challenges related to saturation of toxicokinetic processes: Implications for risk assessment.

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Review 4.  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

5.  Prediction of metabolism-induced hepatotoxicity on three-dimensional hepatic cell culture and enzyme microarrays.

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6.  Analysis of biomarker utility using a PBPK/PD model for carbaryl.

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Journal:  Front Pharmacol       Date:  2014-11-18       Impact factor: 5.810

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Review 8.  The Combination of Cell Cultured Technology and In Silico Model to Inform the Drug Development.

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Journal:  Pharmaceutics       Date:  2021-05-12       Impact factor: 6.321

9.  Addressing Early Life Sensitivity Using Physiologically Based Pharmacokinetic Modeling and In Vitro to In Vivo Extrapolation.

Authors:  Miyoung Yoon; Harvey J Clewell
Journal:  Toxicol Res       Date:  2016-01-31

10.  High-throughput analysis using non-depletive SPME: challenges and applications to the determination of free and total concentrations in small sample volumes.

Authors:  Ezel Boyacı; Barbara Bojko; Nathaly Reyes-Garcés; Justen J Poole; Germán Augusto Gómez-Ríos; Alexandre Teixeira; Beate Nicol; Janusz Pawliszyn
Journal:  Sci Rep       Date:  2018-01-18       Impact factor: 4.379

  10 in total

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