Literature DB >> 24935252

Prediction of in vivo developmental toxicity of all-trans-retinoic acid based on in vitro toxicity data and in silico physiologically based kinetic modeling.

Jochem Louisse1, Sieto Bosgra, Bas J Blaauboer, Ivonne M C M Rietjens, Miriam Verwei.   

Abstract

The use of laboratory animals for toxicity testing in chemical safety assessment meets increasing ethical, economic and legislative constraints. The development, validation and application of reliable alternatives for in vivo toxicity testing are therefore urgently needed. In order to use toxicity data obtained from in vitro assays for risk assessment, in vitro concentration-response data need to be translated into in vivo dose-response data that are needed to obtain points of departure for risk assessment, like a benchmark dose (BMD). In the present study, we translated in vitro concentration-response data of the retinoid all-trans-retinoic acid (ATRA), obtained in the differentiation assay of the embryonic stem cell test, into in vivo dose-response data using a physiologically based kinetic model for rat and human that is mainly based on kinetic model parameter values derived using in vitro techniques. The predicted in vivo dose-response data were used for BMD modeling, and the obtained BMDL10 values [lower limit of the 95 % confidence interval on the BMD at which a benchmark response equivalent to a 10 % effect size (BMR10) is reached (BMD10)] for rat were compared with BMDL10 values derived from in vivo developmental toxicity data in rats reported in the literature. The results show that the BMDL10 values from predicted dose-response data differ about sixfold from the BMDL10 values obtained from in vivo data, pointing at the feasibility of using a combined in vitro-in silico approach for defining a point of departure for toxicological risk assessment.

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Year:  2014        PMID: 24935252     DOI: 10.1007/s00204-014-1289-4

Source DB:  PubMed          Journal:  Arch Toxicol        ISSN: 0340-5761            Impact factor:   5.153


  17 in total

1.  Physiologically Based Pharmacokinetic Model of All-trans-Retinoic Acid with Application to Cancer Populations and Drug Interactions.

Authors:  Jing Jing; Cara Nelson; Jisun Paik; Yoshiyuki Shirasaka; John K Amory; Nina Isoherranen
Journal:  J Pharmacol Exp Ther       Date:  2017-03-08       Impact factor: 4.030

2.  In vitro-in silico-based analysis of the dose-dependent in vivo oestrogenicity of the soy phytoestrogen genistein in humans.

Authors:  Rungnapa Boonpawa; Albertus Spenkelink; Ans Punt; Ivonne M C M Rietjens
Journal:  Br J Pharmacol       Date:  2017-07-11       Impact factor: 8.739

3.  Extended evaluation on the ES-D3 cell differentiation assay combined with the BeWo transport model, to predict relative developmental toxicity of triazole compounds.

Authors:  Hequn Li; Burkhard Flick; Ivonne M C M Rietjens; Jochem Louisse; Steffen Schneider; Bennard van Ravenzwaay
Journal:  Arch Toxicol       Date:  2015-06-06       Impact factor: 5.153

4.  Integrating in vitro data and physiologically based kinetic (PBK) modelling to assess the in vivo potential developmental toxicity of a series of phenols.

Authors:  Marije Strikwold; Bert Spenkelink; Laura H J de Haan; Ruud A Woutersen; Ans Punt; Ivonne M C M Rietjens
Journal:  Arch Toxicol       Date:  2016-11-04       Impact factor: 5.153

5.  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

6.  Development and validation of a physiology-based model for the prediction of pharmacokinetics/toxicokinetics in rabbits.

Authors:  Panteleimon D Mavroudis; Helen E Hermes; Donato Teutonico; Thomas G Preuss; Sebastian Schneckener
Journal:  PLoS One       Date:  2018-03-21       Impact factor: 3.240

7.  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

8.  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

9.  Combining In Vitro Data and Physiologically Based Kinetic Modeling Facilitates Reverse Dosimetry to Define In Vivo Dose-Response Curves for Bixin- and Crocetin-Induced Activation of PPARγ in Humans.

Authors:  Suparmi Suparmi; Laura de Haan; Albertus Spenkelink; Jochem Louisse; Karsten Beekmann; Ivonne M C M Rietjens
Journal:  Mol Nutr Food Res       Date:  2020-01-07       Impact factor: 5.914

10.  Defining in vivo dose-response curves for kidney DNA adduct formation of aristolochic acid I in rat, mouse and human by an in vitro and physiologically based kinetic modeling approach.

Authors:  Rozaini Abdullah; Sebastiaan Wesseling; Bert Spenkelink; Jochem Louisse; Ans Punt; Ivonne M C M Rietjens
Journal:  J Appl Toxicol       Date:  2020-07-07       Impact factor: 3.446

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