Literature DB >> 17943421

Development of a human physiologically based pharmacokinetic (PBPK) model for inorganic arsenic and its mono- and di-methylated metabolites.

Hisham A El-Masri1, Elaina M Kenyon.   

Abstract

A physiologically-based pharmacokinetic (PBPK) model was developed to estimate levels of arsenic and its metabolites in human tissues and urine after oral exposure to arsenate (As(V)), arsenite (As(III)) or organoarsenical pesticides. The model consists of interconnected individual PBPK models for inorganic arsenic (As(V) and As(III)), monomethylarsenic acid (MMA(V)), and, dimethylarsenic acid (DMA(V)). Reduction of MMA(V) and DMA(V) to their respective trivalent forms also occurs in the lung, liver, and kidney including excretion in urine. Each submodel was constructed using flow limited compartments describing the mass balance of the chemicals in GI tract (lumen and tissue), lung, liver, kidney, muscle, skin, heart, and brain. The choice of tissues was based on physiochemical properties of the arsenicals (solubility), exposure routes, target tissues, and sites for metabolism. Metabolism of inorganic arsenic in liver was described as a series of reduction and oxidative methylation steps incorporating the inhibitory influence of metabolites on methylation. The inhibitory effects of As(III) on the methylation of MMA(III) to DMA, and MMA(III) on the methylation of As(III) to MMA were modeled as noncompetitive. To avoid the uncertainty inherent in estimation of many parameters from limited human data, a priori independent parameter estimates were derived using data from diverse experimental systems with priority given to data derived using human cells and tissues. This allowed the limited data for human excretion of arsenicals in urine to be used to estimate only parameters that were most sensitive to this type of data. Recently published urinary excretion data, not previously used in model development, are also used to evaluate model predictions.

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Year:  2007        PMID: 17943421     DOI: 10.1007/s10928-007-9075-z

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  75 in total

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2.  Urinary excretion of inorganic arsenic and its metabolites after repeated ingestion of sodium metaarsenite by volunteers.

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Authors:  M Vahter
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4.  Inorganic arsenic methylation by rat tissue slices.

Authors:  B Georis; A Cardenas; J P Buchet; R Lauwerys
Journal:  Toxicology       Date:  1990-07       Impact factor: 4.221

5.  Arsenate reductase II. Purine nucleoside phosphorylase in the presence of dihydrolipoic acid is a route for reduction of arsenate to arsenite in mammalian systems.

Authors:  Timothy R Radabaugh; Adriana Sampayo-Reyes; Robert A Zakharyan; H Vasken Aposhian
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6.  Glutathione modulates recombinant rat arsenic (+3 oxidation state) methyltransferase-catalyzed formation of trimethylarsine oxide and trimethylarsine.

Authors:  Stephen B Waters; Vicenta Devesa; Michael W Fricke; John T Creed; Miroslav Stýblo; David J Thomas
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8.  Elucidating the pathway for arsenic methylation.

Authors:  David J Thomas; Stephen B Waters; Miroslav Styblo
Journal:  Toxicol Appl Pharmacol       Date:  2004-08-01       Impact factor: 4.219

9.  Induction of oxidative DNA damage by arsenite and its trivalent and pentavalent methylated metabolites in cultured human cells and isolated DNA.

Authors:  Tanja Schwerdtle; Ingo Walter; Iris Mackiw; Andrea Hartwig
Journal:  Carcinogenesis       Date:  2003-05       Impact factor: 4.944

10.  Glutathione-dependent reduction of arsenate in human erythrocytes--a process independent of purine nucleoside phosphorylase.

Authors:  Balázs Németi; Zoltán Gregus
Journal:  Toxicol Sci       Date:  2004-10-06       Impact factor: 4.849

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  22 in total

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Review 3.  Cancer in experimental animals exposed to arsenic and arsenic compounds.

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Review 4.  Exposure to Mixtures of Metals and Neurodevelopmental Outcomes: A Multidisciplinary Review Using an Adverse Outcome Pathway Framework.

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Journal:  Risk Anal       Date:  2015-06-10       Impact factor: 4.000

5.  A pilot study: the importance of inter-individual differences in inorganic arsenic metabolism for birth weight outcome.

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6.  A semi-mechanistic integrated toxicokinetic-toxicodynamic (TK/TD) model for arsenic(III) in hepatocytes.

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7.  A generalized physiologically-based toxicokinetic modeling system for chemical mixtures containing metals.

Authors:  Alan F Sasso; Sastry S Isukapalli; Panos G Georgopoulos
Journal:  Theor Biol Med Model       Date:  2010-06-02       Impact factor: 2.432

8.  Biologically based modeling of multimedia, multipathway, multiroute population exposures to arsenic.

Authors:  Panos G Georgopoulos; Sheng-Wei Wang; Yu-Ching Yang; Jianping Xue; Valerie G Zartarian; Thomas McCurdy; Halûk Ozkaynak
Journal:  J Expo Sci Environ Epidemiol       Date:  2007-12-12       Impact factor: 5.563

9.  Bayesian hierarchical dose-response meta-analysis of epidemiological studies: Modeling and target population prediction methods.

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Review 10.  Physiologically based pharmacokinetic modeling: methodology, applications, and limitations with a focus on its role in pediatric drug development.

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