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    Rights statement: This is the author’s version of a work that was accepted for publication in Environment International. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environment International, 92-93, 2016 DOI: 10.1016/j.envint.2016.03.035

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    Rights statement: This is the author’s version of a work that was accepted for publication in Environment International. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environment International, 92-93, 2016 DOI: 10.1016/j.envint.2016.03.035

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Using publicly available data, a physiologically-based pharmacokinetic model and Bayesian simulation to improve arsenic non-cancer dose-response

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Using publicly available data, a physiologically-based pharmacokinetic model and Bayesian simulation to improve arsenic non-cancer dose-response. / Dong, Zhaomin; Liu, CuiXia; Liu, Yanju; Yan, Kaihong; Semple, Kirk Taylor; Naidu, Ravi.

In: Environment International, Vol. 92-93, 07.2016, p. 239-246.

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Dong, Zhaomin ; Liu, CuiXia ; Liu, Yanju ; Yan, Kaihong ; Semple, Kirk Taylor ; Naidu, Ravi. / Using publicly available data, a physiologically-based pharmacokinetic model and Bayesian simulation to improve arsenic non-cancer dose-response. In: Environment International. 2016 ; Vol. 92-93. pp. 239-246.

Bibtex

@article{9133a1d234e9448b8bd27fdf4a3b2a86,
title = "Using publicly available data, a physiologically-based pharmacokinetic model and Bayesian simulation to improve arsenic non-cancer dose-response",
abstract = "Publicly available data can potentially examine the relationship between environmental exposure and public health, however, it has not yet been widely applied. Arsenic is of environmental concern, and previous studies mathematically parameterized exposure duration to create a link between duration of exposure and increase in risk. However, since the dose metric emerging from exposure duration is not a linear or explicit variable, it is difficult to address the effects of exposure duration simply by using mathematical functions. To relate cumulative dose metric to public health requires a lifetime physiologically-based pharmacokinetic (PBPK) model, yet this model is not available at a population level. In this study, the data from the U.S. total diet study (TDS, 2006–2011) was employed to assess exposure: daily dietary intakes for total arsenic (tAs) and inorganic arsenic (iAs) were estimated to be 0.15 and 0.028 μg/kg/day, respectively. Meanwhile, using National Health and Nutrition Examination Survey (NHANES, 2011–2012) data, the fraction of urinary As(III) levels (geometric mean: 0.31 μg/L) in tAs (geometric mean: 7.75 μg/L) was firstly reported to be approximately 4%. Together with Bayesian technique, the assessed exposure and urinary As(III) concentration were input to successfully optimize a lifetime population PBPK model. Finally, this optimized PBPK model was used to derive an oral reference dose (Rfd) of 0.8 μg/kg/day for iAs exposure. Our study also suggests the previous approach (by using mathematical functions to account for exposure duration) may result in a conservative Rfd estimation.",
keywords = "PBPK model, Dose response, Bayesian simulation, Arsenic, Publicly available data",
author = "Zhaomin Dong and CuiXia Liu and Yanju Liu and Kaihong Yan and Semple, {Kirk Taylor} and Ravi Naidu",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Environment International. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environment International, 92-93, 2016 DOI: 10.1016/j.envint.2016.03.035",
year = "2016",
month = jul
doi = "10.1016/j.envint.2016.03.035",
language = "English",
volume = "92-93",
pages = "239--246",
journal = "Environment International",
issn = "0160-4120",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Using publicly available data, a physiologically-based pharmacokinetic model and Bayesian simulation to improve arsenic non-cancer dose-response

AU - Dong, Zhaomin

AU - Liu, CuiXia

AU - Liu, Yanju

AU - Yan, Kaihong

AU - Semple, Kirk Taylor

AU - Naidu, Ravi

N1 - This is the author’s version of a work that was accepted for publication in Environment International. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environment International, 92-93, 2016 DOI: 10.1016/j.envint.2016.03.035

PY - 2016/7

Y1 - 2016/7

N2 - Publicly available data can potentially examine the relationship between environmental exposure and public health, however, it has not yet been widely applied. Arsenic is of environmental concern, and previous studies mathematically parameterized exposure duration to create a link between duration of exposure and increase in risk. However, since the dose metric emerging from exposure duration is not a linear or explicit variable, it is difficult to address the effects of exposure duration simply by using mathematical functions. To relate cumulative dose metric to public health requires a lifetime physiologically-based pharmacokinetic (PBPK) model, yet this model is not available at a population level. In this study, the data from the U.S. total diet study (TDS, 2006–2011) was employed to assess exposure: daily dietary intakes for total arsenic (tAs) and inorganic arsenic (iAs) were estimated to be 0.15 and 0.028 μg/kg/day, respectively. Meanwhile, using National Health and Nutrition Examination Survey (NHANES, 2011–2012) data, the fraction of urinary As(III) levels (geometric mean: 0.31 μg/L) in tAs (geometric mean: 7.75 μg/L) was firstly reported to be approximately 4%. Together with Bayesian technique, the assessed exposure and urinary As(III) concentration were input to successfully optimize a lifetime population PBPK model. Finally, this optimized PBPK model was used to derive an oral reference dose (Rfd) of 0.8 μg/kg/day for iAs exposure. Our study also suggests the previous approach (by using mathematical functions to account for exposure duration) may result in a conservative Rfd estimation.

AB - Publicly available data can potentially examine the relationship between environmental exposure and public health, however, it has not yet been widely applied. Arsenic is of environmental concern, and previous studies mathematically parameterized exposure duration to create a link between duration of exposure and increase in risk. However, since the dose metric emerging from exposure duration is not a linear or explicit variable, it is difficult to address the effects of exposure duration simply by using mathematical functions. To relate cumulative dose metric to public health requires a lifetime physiologically-based pharmacokinetic (PBPK) model, yet this model is not available at a population level. In this study, the data from the U.S. total diet study (TDS, 2006–2011) was employed to assess exposure: daily dietary intakes for total arsenic (tAs) and inorganic arsenic (iAs) were estimated to be 0.15 and 0.028 μg/kg/day, respectively. Meanwhile, using National Health and Nutrition Examination Survey (NHANES, 2011–2012) data, the fraction of urinary As(III) levels (geometric mean: 0.31 μg/L) in tAs (geometric mean: 7.75 μg/L) was firstly reported to be approximately 4%. Together with Bayesian technique, the assessed exposure and urinary As(III) concentration were input to successfully optimize a lifetime population PBPK model. Finally, this optimized PBPK model was used to derive an oral reference dose (Rfd) of 0.8 μg/kg/day for iAs exposure. Our study also suggests the previous approach (by using mathematical functions to account for exposure duration) may result in a conservative Rfd estimation.

KW - PBPK model

KW - Dose response

KW - Bayesian simulation

KW - Arsenic

KW - Publicly available data

U2 - 10.1016/j.envint.2016.03.035

DO - 10.1016/j.envint.2016.03.035

M3 - Journal article

VL - 92-93

SP - 239

EP - 246

JO - Environment International

JF - Environment International

SN - 0160-4120

ER -