Literature DB >> 27768849

Use of Physiologically Based Kinetic Modeling-Based Reverse Dosimetry to Predict in Vivo Toxicity from in Vitro Data.

Jochem Louisse1, Karsten Beekmann1, Ivonne M C M Rietjens1.   

Abstract

The development of reliable nonanimal based testing strategies, such as in vitro bioassays, is the holy grail in current human safety testing of chemicals. However, the use of in vitro toxicity data in risk assessment is not straightforward. One of the main issues is that concentration-response curves from in vitro models need to be converted to in vivo dose-response curves. These dose-response curves are needed in toxicological risk assessment to obtain a point of departure to determine safe exposure levels for humans. Recent scientific developments enable this translation of in vitro concentration-response curves to in vivo dose-response curves using physiologically based kinetic (PBK) modeling-based reverse dosimetry. The present review provides an overview of the examples available in the literature on the prediction of in vivo toxicity using PBK modeling-based reverse dosimetry of in vitro toxicity data, showing that proofs-of-principle are available for toxicity end points ranging from developmental toxicity, nephrotoxicity, hepatotoxicity, and neurotoxicity to DNA adduct formation. This review also discusses the promises and pitfalls, and the future perspectives of the approach. Since proofs-of-principle available so far have been provided for the prediction of toxicity in experimental animals, future research should focus on the use of in vitro toxicity data obtained in human models to predict the human situation using human PBK models. This would facilitate human- instead of experimental animal-based approaches in risk assessment.

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Year:  2016        PMID: 27768849     DOI: 10.1021/acs.chemrestox.6b00302

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


  21 in total

1.  Towards best use and regulatory acceptance of generic physiologically based kinetic (PBK) models for in vitro-to-in vivo extrapolation (IVIVE) in chemical risk assessment.

Authors:  Abdulkarim Najjar; Ans Punt; John Wambaugh; Alicia Paini; Corie Ellison; Styliani Fragki; Enrica Bianchi; Fagen Zhang; Joost Westerhout; Dennis Mueller; Hequn Li; Quan Shi; Timothy W Gant; Phil Botham; Rémi Bars; Aldert Piersma; Ben van Ravenzwaay; Nynke I Kramer
Journal:  Arch Toxicol       Date:  2022-09-05       Impact factor: 6.168

2.  Pluripotent stem cell assays: Modalities and applications for predictive developmental toxicity.

Authors:  Aldert H Piersma; Nancy C Baker; George P Daston; Burkhard Flick; Michio Fujiwara; Thomas B Knudsen; Horst Spielmann; Noriyuki Suzuki; Katya Tsaioun; Hajime Kojima
Journal:  Curr Res Toxicol       Date:  2022-05-13

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

Authors:  Yu-Mei Tan; Hugh A Barton; Alan Boobis; Rachel Brunner; Harvey Clewell; Rhian Cope; Jeffrey Dawson; Jeanne Domoradzki; Peter Egeghy; Pankaj Gulati; Brandall Ingle; Nicole Kleinstreuer; Kelly Lowe; Anna Lowit; Elizabeth Mendez; David Miller; Jeffrey Minucci; James Nguyen; Alicia Paini; Monique Perron; Katherine Phillips; Hua Qian; Tharacad Ramanarayanan; Fiona Sewell; Philip Villanueva; John Wambaugh; Michelle Embry
Journal:  Regul Toxicol Pharmacol       Date:  2021-10-28       Impact factor: 3.598

4.  Physiologically based kinetic modelling based prediction of in vivo rat and human acetylcholinesterase (AChE) inhibition upon exposure to diazinon.

Authors:  Shensheng Zhao; Sebastiaan Wesseling; Bert Spenkelink; Ivonne M C M Rietjens
Journal:  Arch Toxicol       Date:  2021-03-14       Impact factor: 5.153

Review 5.  Exposure assessment of process-related contaminants in food by biomarker monitoring.

Authors:  Ivonne M C M Rietjens; P Dussort; Helmut Günther; Paul Hanlon; Hiroshi Honda; Angela Mally; Sue O'Hagan; Gabriele Scholz; Albrecht Seidel; James Swenberg; Justin Teeguarden; Gerhard Eisenbrand
Journal:  Arch Toxicol       Date:  2018-01-04       Impact factor: 5.153

6.  Towards a generic physiologically based kinetic model to predict in vivo uterotrophic responses in rats by reverse dosimetry of in vitro estrogenicity data.

Authors:  Mengying Zhang; Bennard van Ravenzwaay; Eric Fabian; Ivonne M C M Rietjens; Jochem Louisse
Journal:  Arch Toxicol       Date:  2017-12-12       Impact factor: 5.153

7.  Integrating in vitro data and physiologically based kinetic modeling-facilitated reverse dosimetry to predict human cardiotoxicity of methadone.

Authors:  Miaoying Shi; Hans Bouwmeester; Ivonne M C M Rietjens; Marije Strikwold
Journal:  Arch Toxicol       Date:  2020-05-04       Impact factor: 5.153

8.  Predicting the Acute Liver Toxicity of Aflatoxin B1 in Rats and Humans by an In Vitro-In Silico Testing Strategy.

Authors:  Ixchel Gilbert-Sandoval; Sebastiaan Wesseling; Ivonne M C M Rietjens
Journal:  Mol Nutr Food Res       Date:  2020-06-02       Impact factor: 5.914

9.  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

10.  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

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