A Physiologically Based Pharmacokinetic Model for Arsenic Exposure

Mann, Sabine; Droz, Pierre‐Olivier; Vahter, Marie

doi:10.1006/taap.1996.0052

Cited by 71 publications

(35 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mann et al (1996aMann et al ( , 1996b extended an inorganic arsenic PBPK model developed for hamsters and rabbits to humans. Their model described the pharmacokinetics of arsenite, arsenate, methylarsonate and dimethylarsinate.…”

Section: Physiologically Based Pharmacokinetic (Pbpk) Modelsmentioning

confidence: 99%

Scientific Opinion on Arsenic in Food

2009

EFSA Journal

877

220

View full text Add to dashboard Cite

The EFSA Panel on Contaminants in the Food Chain (CONTAM Panel) assessed the risks to human health related to the presence of arsenic in food. More than 100,000 occurrence data on arsenic in food were considered with approximately 98 % reported as total arsenic. Making a number of assumptions for the contribution of inorganic arsenic to total arsenic, the inorganic arsenic exposure from food and water across 19 European countries, using lower bound and upper bound concentrations, has been estimated to range from 0.13 to 0.56 µg/kg bodyweight (b.w.) per day for average consumers, and from 0.37 to 1.22 µg/kg b.w. per day for 95 th percentile consumers. Dietary exposure to inorganic arsenic for children under three years of age is in general estimated to be from 2 to 3-fold that of adults. The CONTAM Panel concluded that the provisional tolerable weekly intake (PTWI) of 15 µg/kg b.w. established by the Joint FAO/WHO Expert Committee on Food Additives (JECFA) is no longer appropriate as data had shown that inorganic arsenic causes cancer of the lung and urinary bladder in addition to skin, and that a range of adverse effects had been reported at exposures lower than those reviewed by the JECFA. The CONTAM Panel modelled the dose-response data from key for providing consumption information and calculating exposure, the partners of the EFSA project on the "Individual food consumption data and exposure" coordinated by Ghent University (Department of Public Health, University Hospital, Ghent University, Belgium), and RIKILT (Institute of Food Safety, Wageningen, The Netherlands) for the accessibility of the exposure assessment tools. 4 Table of contents shows now the fourth level of subheadings. 5 An error in the interpretation of the total number of the population in the study of Rahman et al. (2006a) was discovered (Table 41). The BMDL was recalculated and as a consequence it was not considered a potential reference point. The text in the opinion, Table 43 and Appendix were revised accordingly. In addition, the header of the "total number of cases" was replaced by "total number of individuals" in Tables 40-42 and the erroneous units were corrected to µg/L in the text below SUMMARYArsenic is a metalloid that occurs in different inorganic and organic forms, which are found in the environment both from natural occurrence and from anthropogenic activity. The inorganic forms of arsenic are more toxic as compared to the organic arsenic but so far most of the occurrence data in food collected in the framework of official food control are still reported as total arsenic without differentiating the various arsenic species. The need for speciation data is evident because several investigations have shown that especially in seafood most of the arsenic is present in organic forms that are less toxic. Consequently, a risk assessment not taking into account the different species but considering total arsenic as being present exclusively as inorganic arsenic would lead to a considerable overestimation of the health risk rel...

show abstract

Section: Physiologically Based Pharmacokinetic (Pbpk) Modelsmentioning

confidence: 99%

Scientific Opinion on Arsenic in Food

2009

EFSA Journal

877

220

View full text Add to dashboard Cite

show abstract

“…There are also a large number of good examples of PBPK models which describe the kinetics of important environmental contaminants, including methylene chloride (8,44,45), trichloroethylene (46)(47)(48), chloroform (49, 50), 2-butoxyethanol (51), kepone (52), polybrominated biphenyls (53), polychlorinated biphenyls (54) and dibenzofurans (55), dioxins (56,57), lead (58)(59)(60)(61)(62), arsenic (63,64), methylmercury (65), atrazine (66,67), acrylonitrile (68)(69)(70), perchlorate (71)(72)(73)(74)(75)(76), and BTEX components (77)(78)(79)(80)(81). The U.S. EPA is currently compiling a compendium of PBPK models including source code.…”

Section: Physiologically Based Modelingmentioning

confidence: 99%

Physiologically Based Pharmacokinetic/Toxicokinetic Modeling

Campbell

Clewell

Gentry

et al. 2012

Methods in Molecular Biology

View full text Add to dashboard Cite

Physiologically based pharmacokinetic (PBPK) models differ from conventional compartmental pharmacokinetic models in that they are based to a large extent on the actual physiology of the organism. The application of pharmacokinetics to toxicology or risk assessment requires that the toxic effects in a particular tissue are related in some way to the concentration time course of an active form of the substance in that tissue. The motivation for applying pharmacokinetics is the expectation that the observed effects of a chemical will be more simply and directly related to a measure of target tissue exposure than to a measure of administered dose. The goal of this work is to provide the reader with an understanding of PBPK modeling and its utility as well as the procedures used in the development and implementation of a model to chemical safety assessment using the styrene PBPK model as an example.

show abstract

“…However, the approach of Yu has been evaluated with experimental observations from the literature for urinary biomarker levels of speciated arsenic (see e.g., Pomroy et al, 1980;Buchet et al, 1981;and Johnson and Farmer, 1991). The model employed in the present study is in fact a simplified flowlimited version of an "in-progress" arsenic model, which combines both "flow-limited" and "diffusion-limited" (as per the work of Mann et al (1996)) components and also incorporates developments presented in the work of El-Masri and Kenyon (2007). However, the use of either a fully flow-limited or diffusion-limited formulation results in very similar estimates of total urinary As, which was the "target biomarker" in the present analysis.…”

Section: Physiologically Based Pharmacokinetic Modeling For Arsenicmentioning

confidence: 99%

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

Georgopoulos

Wang

et al. 2007

J Expo Sci Environ Epidemiol

View full text Add to dashboard Cite

This article presents an integrated, biologically based, source-to-dose assessment framework for modeling multimedia/multipathway/multiroute exposures to arsenic. Case studies demonstrating this framework are presented for three US counties (Hunderton County, NJ; Pima County, AZ; and Franklin County, OH), representing substantially different conditions of exposure. The approach taken utilizes the Modeling ENvironment for TOtal Risk studies (MENTOR) in an implementation that incorporates and extends the approach pioneered by Stochastic Human Exposure and Dose Simulation (SHEDS), in conjunction with a number of available databases, including NATA, NHEXAS, CSFII, and CHAD, and extends modeling techniques that have been developed in recent years. Model results indicate that, in most cases, the food intake pathway is the dominant contributor to total exposure and dose to arsenic. Model predictions are evaluated qualitatively by comparing distributions of predicted total arsenic amounts in urine with those derived using biomarker measurements from the NHEXAS -Region V study: the population distributions of urinary total arsenic levels calculated through MENTOR and from the NHEXAS measurements are in general qualitative agreement. Observed differences are due to various factors, such as interindividual variation in arsenic metabolism in humans, that are not fully accounted for in the current model implementation but can be incorporated in the future, in the open framework of MENTOR. The present study demonstrates that integrated source-to-dose modeling for arsenic can not only provide estimates of the relative contributions of multipathway exposure routes to the total exposure estimates, but can also estimate internal target tissue doses for speciated organic and inorganic arsenic, which can eventually be used to improve evaluation of health risks associated with exposures to arsenic from multiple sources, routes, and pathways.

show abstract

A Physiologically Based Pharmacokinetic Model for Arsenic Exposure

Cited by 71 publications

References 0 publications

Scientific Opinion on Arsenic in Food

Scientific Opinion on Arsenic in Food

Physiologically Based Pharmacokinetic/Toxicokinetic Modeling

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

Contact Info

Product

Resources

About