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Journal articles on the topic 'Toxicokinetic model'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Dalaijamts, Chimeddulam, Joseph A. Cichocki, Yu-Syuan Luo, Ivan Rusyn, and Weihsueh A. Chiu. "Quantitative Characterization of Population-Wide Tissue- and Metabolite-Specific Variability in Perchloroethylene Toxicokinetics in Male Mice." Toxicological Sciences 182, no. 2 (2021): 168–82. http://dx.doi.org/10.1093/toxsci/kfab057.

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Abstract Quantification of interindividual variability is a continuing challenge in risk assessment, particularly for compounds with complex metabolism and multi-organ toxicity. Toxicokinetic variability for perchloroethylene (perc) was previously characterized across 3 mouse strains and in 1 mouse strain with various degrees of liver steatosis. To further characterize the role of genetic variability in toxicokinetics of perc, we applied Bayesian population physiologically based pharmacokinetic (PBPK) modeling to the data on perc and metabolites in blood/plasma and tissues of male mice from 45

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2

Poulin, Patrick, and Kannan Krishnan. "A Quantitative Structure-toxicokinetic Relationship Model for Highly Metabolised Chemicals." Alternatives to Laboratory Animals 26, no. 1 (1998): 45–55. http://dx.doi.org/10.1177/026119299802600109.

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The aim of the present study was to develop a quantitative structure-toxicokinetic relationship (QSTkR) model for highly metabolised chemicals (HMCs). The proposed QSTkR model is essentially a physiologically based toxicokinetic (PBTK) model, in which the blood:air and tissue:blood partition coefficients (PCs) are predicted from the molecular structure of chemicals, and the liver blood flow rate (Q1) is used to describe hepatic clearance. Molecular structure-based prediction of the blood:air and tissue:blood PCs was performed from the n-octanol:water and water:air PCs of chemicals obtained wit

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3

Johanson, Gunnar. "Use of Toxicokinetics in Risk Assessment Based on In Vitro Data." Alternatives to Laboratory Animals 21, no. 2 (1993): 173–80. http://dx.doi.org/10.1177/026119299302100209.

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This presentation addresses some aspects of the methodology, advantages and problems associated with toxicokinetic modelling based on in vitro data. By using toxicokinetic models, particularly physiologically-based ones, it is possible, in principle, to describe whole body toxicokinetics, target doses and toxic effects from in vitro data. Modelling can be divided into three major steps: 1) to relate external exposure (applied dose) of xenobiotic to target dose; 2) to establish the relationship between target dose and effect (in vitro data, e.g. metabolism in microsomes, partitioning in tissue

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4

Sweeney, Lisa M., Michelle R. Goodwin, Angela D. Hulgan, Chester P. Gut, and Desmond I. Bannon. "Toxicokinetic Model Development for the Insensitive Munitions Component 2,4-Dinitroanisole." International Journal of Toxicology 34, no. 5 (2015): 417–32. http://dx.doi.org/10.1177/1091581815594623.

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The Armed Forces are developing new explosives that are less susceptible to unintentional detonation (insensitive munitions [IMX]). 2,4-Dinitroanisole (DNAN) is a component of IMX. Toxicokinetic data for DNAN are required to support interpretation of toxicology studies and refinement of dose estimates for human risk assessment. Male Sprague-Dawley rats were dosed by gavage (5, 20, or 80 mg DNAN/kg), and blood and tissue samples were analyzed to determine the levels of DNAN and its metabolite 2,4-dinitrophenol (DNP). These data and data from the literature were used to develop preliminary physi

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5

Sweeney, Lisa M., Elizabeth A. Phillips, Michelle R. Goodwin, and Desmond I. Bannon. "Toxicokinetic Model Development for the Insensitive Munitions Component 3-Nitro-1,2,4-Triazol-5-One." International Journal of Toxicology 34, no. 5 (2015): 408–16. http://dx.doi.org/10.1177/1091581815589000.

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3-Nitro-1,2,4-triazol-5-one (NTO) is a component of insensitive munitions that are potential replacements for conventional explosives. Toxicokinetic data can aid in the interpretation of toxicity studies and interspecies extrapolation, but only limited data on the toxicokinetics and metabolism of NTO are available. To supplement these limited data, further in vivo studies of NTO in rats were conducted and blood concentrations were measured, tissue distribution of NTO was estimated using an in silico method, and physiologically based pharmacokinetic models of the disposition of NTO in rats and

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6

Sasso, Alan F., Panos G. Georgopoulos, Sastry S. Isukapalli, and Kannan Krishnan. "Bayesian Analysis of a Lipid-Based Physiologically Based Toxicokinetic Model for a Mixture of PCBs in Rats." Journal of Toxicology 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/895391.

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A lipid-based physiologically based toxicokinetic (PBTK) model has been developed for a mixture of six polychlorinated biphenyls (PCBs) in rats. The aim of this study was to apply population Bayesian analysis to a lipid PBTK model, while incorporating an internal exposure-response model linking enzyme induction and metabolic rate. Lipid-based physiologically based toxicokinetic models are a subset of PBTK models that can simulate concentrations of highly lipophilic compounds in tissue lipids, without the need for partition coefficients. A hierarchical treatment of population metabolic paramete

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7

Filser, J. G., C. Baur, A. Csan Ädy, W. Kessler, and P. E. Kreuzer. "Toxicokinetic Modeling as a Tool for Risk Estimation: 2,3,7,8-Tetrachlorodibenzo-P-Dioxin." International Journal of Toxicology 16, no. 4-5 (1997): 433–48. http://dx.doi.org/10.1080/109158197227053.

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Concepts of toxicokinetic modeling and the relevance of toxicokinetics for understanding dose-response relationships, species scaling, and risk estimation are broached. A physiological one-compartment model for 2,3,7,8-tetra-chlorodibenzo-p-dioxin (TCDD) is presented in detail. It describes the TCDD burden of the human body, which results from TCDD-contaminated food, in dependence of age. The model was validated using a series of measured values obtained by other authors and this group. They represent lipid-based concentrations of TCDD in liver, blood, adipose tissue, feces, and mother's milk

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8

Albert, C., R. Ashauer, H. R. Künsch, and P. Reichert. "Bayesian experimental design for a toxicokinetic–toxicodynamic model." Journal of Statistical Planning and Inference 142, no. 1 (2012): 263–75. http://dx.doi.org/10.1016/j.jspi.2011.07.014.

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9

Antonissen, Gunther, Siegrid De Baere, Barbara Novak, et al. "Toxicokinetics of Hydrolyzed Fumonisin B1 after Single Oral or Intravenous Bolus to Broiler Chickens Fed a Control or a Fumonisins-Contaminated Diet." Toxins 12, no. 6 (2020): 413. http://dx.doi.org/10.3390/toxins12060413.

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The toxicokinetics (TK) of hydrolyzed fumonisin B1 (HFB1) were evaluated in 16 broiler chickens after being fed either a control or a fumonisins-contaminated diet (10.8 mg fumonisin B1, 3.3 mg B2 and 1.5 mg B3/kg feed) for two weeks, followed by a single oral (PO) or intravenous (IV) dose of 1.25 mg/kg bodyweight (BW) of HFB1. Fumonisin B1 (FB1), its partially hydrolyzed metabolites pHFB1a and pHFB1b, and fully hydrolyzed metabolite HFB1, were determined in chicken plasma using a validated ultra-performance liquid chromatography–tandem mass spectrometry method. None of the broiler chicken show

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10

Larisch, Wolfgang, Trevor N. Brown, and Kai-Uwe Goss. "A toxicokinetic model for fish including multiphase sorption features." Environmental Toxicology and Chemistry 36, no. 6 (2016): 1538–46. http://dx.doi.org/10.1002/etc.3677.

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11

张, 益宁. "Construction of the Physiological Toxicokinetic Model of Bisphenol A." Hans Journal of Food and Nutrition Science 10, no. 03 (2021): 175–89. http://dx.doi.org/10.12677/hjfns.2021.103021.

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12

Vidal, Alice, Marc Babut, Jeanne Garric, and Rémy Beaudouin. "Temperature effect on perfluorooctane sulfonate toxicokinetics in rainbow trout (Oncorhynchus mykiss): Exploration via a physiologically based toxicokinetic model." Aquatic Toxicology 225 (August 2020): 105545. http://dx.doi.org/10.1016/j.aquatox.2020.105545.

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13

Liu, Teng, Weixin Cao, Qiannan Di, Meng Zhao, and Qian Xu. "Evaluation of toxicokinetics of nonylphenol in the adult female Sprague–Dawley rats using a physiologically based toxicokinetic model." Regulatory Toxicology and Pharmacology 105 (July 2019): 42–50. http://dx.doi.org/10.1016/j.yrtph.2019.03.019.

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14

Poulin, Patrick, and Kannan Krishnan. "Molecular Structure-Based Prediction of the Toxicokinetics of Inhaled Vapors in Humans." International Journal of Toxicology 18, no. 1 (1999): 7–18. http://dx.doi.org/10.1080/109158199225756.

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The objectives of the present study were: (1) to evaluate the adequacy of setting hepatic extraction ratio (E) equal to 0 or 1 in physiologically based toxicokinetic (PBTK) models to generate the theoretically plausible envelope of venous blood concentration (Cv) profiles, and (2) to couple this approach with molecular structure-based estimation of blood:air and tissue: blood partition coefficients (PCs) to predictthe Cv profiles of volatile organic chemicals (VOCs) in humans. Setting E= 0 or 1 in PBTK models provided simulations of Cv envelopes that contained the Cv values determined in human

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15

Hirose, Y., M. Kobayashi, K. Koyama, et al. "A toxicokinetic analysis in a patient with acute glufosinate poisoning." Human & Experimental Toxicology 18, no. 5 (1999): 305–8. http://dx.doi.org/10.1191/096032799678840110.

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Incidents of poisoning in humans caused by the ingestion of the glufosinate ammonium containing herbicides are gradually increasing in Japan. This poisoning is characterized by various neurological symptoms such as disturbances of consciousness, convulsions and apnea which appear after an asymptomatic interval of several hours. We studied the toxicokinetics of glufosinate in a patient with this poisoning successfully treated without extracorporeal hemopurification. A 65-year-old male ingested BASTA, which contains 20% w/v of glufosinate ammonium, about 300 ml, more than the estimated human tox

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16

Lien, Gregory J., James M. McKim, Alex D. Hoffman, and Correne T. Jenson. "A physiologically based toxicokinetic model for lake trout (Salvelinus namaycush)." Aquatic Toxicology 51, no. 3 (2001): 335–50. http://dx.doi.org/10.1016/s0166-445x(00)00117-x.

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17

Péry, Alexandre R. R., James Devillers, Céline Brochot, et al. "A Physiologically Based Toxicokinetic Model for the Zebrafish Danio rerio." Environmental Science & Technology 48, no. 1 (2013): 781–90. http://dx.doi.org/10.1021/es404301q.

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18

Roeben, Vanessa, Susanne Oberdoerster, Kim J. Rakel, et al. "Towards a spatiotemporally explicit toxicokinetic-toxicodynamic model for earthworm toxicity." Science of The Total Environment 722 (June 2020): 137673. http://dx.doi.org/10.1016/j.scitotenv.2020.137673.

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19

Passos, Carlos J. S., and Donna Mergler. "Data use in a toxicokinetic model to reconstruct methylmercury intake." Journal of Exposure Science & Environmental Epidemiology 16, no. 4 (2006): 299. http://dx.doi.org/10.1038/sj.jes.7500506.

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20

Law, F. C. P., S. Abedini, and C. J. Kennedy. "A biologically based toxicokinetic model for pyrene in rainbow trout." Toxicology and Applied Pharmacology 110, no. 3 (1991): 390–402. http://dx.doi.org/10.1016/0041-008x(91)90041-c.

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21

Sabourin, Patrick J., Christina L. Kobs, Seth T. Gibbs, et al. "Characterization of a Mouse Model of Oral Potassium Cyanide Intoxication." International Journal of Toxicology 35, no. 5 (2016): 584–603. http://dx.doi.org/10.1177/1091581816646973.

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Potassium cyanide (KCN) is an inhibitor of cytochrome C oxidase causing rapid death due to hypoxia. A well-characterized model of oral KCN intoxication is needed to test new therapeutics under the Food and Drug Administration Animal Rule. Clinical signs, plasma pH and lactate concentrations, biomarkers, histopathology, and cyanide and thiocyanate toxicokinetics were used to characterize the pathology of KCN intoxication in adult and juvenile mice. The acute oral LD50s were determined to be 11.8, 11.0, 10.9, and 9.9 mg/kg in water for adult male, adult female, juvenile male, and juvenile female

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22

Kretschmann, Andreas, Roman Ashauer, Thomas G. Preuss, Piet Spaak, Beate I. Escher, and Juliane Hollender. "Toxicokinetic Model Describing Bioconcentration and Biotransformation of Diazinon in Daphnia magna." Environmental Science & Technology 45, no. 11 (2011): 4995–5002. http://dx.doi.org/10.1021/es104324v.

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23

Klés, V., O. Hymen, P. Sanders, and J. M. Poul. "Elaboration of a predictive toxicokinetic model for in vivo micronucleus assay." Toxicology Letters 95 (July 1998): 43. http://dx.doi.org/10.1016/s0378-4274(98)80167-7.

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24

Celsie, Alena, Donald Mackay, J. Mark Parnis, and Jon A. Arnot. "A fugacity‐based toxicokinetic model for narcotic organic chemicals in fish." Environmental Toxicology and Chemistry 35, no. 5 (2016): 1257–67. http://dx.doi.org/10.1002/etc.3270.

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25

Park, Robert M. "A Simple Toxicokinetic Model Exhibiting Complex Dynamics and Nonlinear Exposure Response." Risk Analysis 40, no. 12 (2020): 2561–71. http://dx.doi.org/10.1111/risa.13547.

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26

Banks, H. T., and L. K. Potter. "Model predictions and comparisons for three toxicokinetic models for the systemic transport of trichloroethylene." Mathematical and Computer Modelling 35, no. 9-10 (2002): 1007–32. http://dx.doi.org/10.1016/s0895-7177(02)00067-5.

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27

Banks, H. T., and Laura K. Potter. "Probabilistic methods for addressing uncertainty and variability in biological models: application to a toxicokinetic model." Mathematical Biosciences 192, no. 2 (2004): 193–225. http://dx.doi.org/10.1016/j.mbs.2004.11.008.

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28

Jager, Tjalling, Carlo Albert, Thomas G. Preuss, and Roman Ashauer. "General Unified Threshold Model of Survival - a Toxicokinetic-Toxicodynamic Framework for Ecotoxicology." Environmental Science & Technology 45, no. 7 (2011): 2529–40. http://dx.doi.org/10.1021/es103092a.

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29

Tan, Qiao-Guo, and Wen-Xiong Wang. "Two-Compartment Toxicokinetic–Toxicodynamic Model to Predict Metal Toxicity in Daphnia magna." Environmental Science & Technology 46, no. 17 (2012): 9709–15. http://dx.doi.org/10.1021/es301987u.

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30

Hickie, Brendan E., Lynn S. McCarty, and George D. Dixon. "A residue-based toxicokinetic model for pulse-exposure toxicity in aquatic systems." Environmental Toxicology and Chemistry 14, no. 12 (1995): 2187–97. http://dx.doi.org/10.1002/etc.5620141224.

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31

Hethey, Christoph, Niklas Hartung, Gaby Wangorsch, Karin Weisser, and Wilhelm Huisinga. "Physiology-based toxicokinetic modelling of aluminium in rat and man." Archives of Toxicology 95, no. 9 (2021): 2977–3000. http://dx.doi.org/10.1007/s00204-021-03107-y.

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AbstractA sufficient quantitative understanding of aluminium (Al) toxicokinetics (TK) in man is still lacking, although highly desirable for risk assessment of Al exposure. Baseline exposure and the risk of contamination severely limit the feasibility of TK studies administering the naturally occurring isotope 27Al, both in animals and man. These limitations are absent in studies with 26Al as a tracer, but tissue data are limited to animal studies. A TK model capable of inter-species translation to make valid predictions of Al levels in humans—especially in toxicological relevant tissues like

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32

Jo, Seongil, Hae Woo, Ho-Jang Kwon, et al. "Estimation of the Biological Half-Life of Methylmercury Using a Population Toxicokinetic Model." International Journal of Environmental Research and Public Health 12, no. 8 (2015): 9054–67. http://dx.doi.org/10.3390/ijerph120809054.

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33

Reddyhoff, D., C. P. Fisher, and I. Gardner. "Incorporation of toxicodynamic feedback in a physiologically-based toxicokinetic model of acetaminophen overdose." Toxicology Letters 295 (October 2018): S246—S247. http://dx.doi.org/10.1016/j.toxlet.2018.06.1016.

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34

Zhu, Minghua, Zhongyu Wang, Jingwen Chen, Huaijun Xie, Hongxia Zhao, and Xiutang Yuan. "Bioaccumulation, Biotransformation, and Multicompartmental Toxicokinetic Model of Antibiotics in Sea Cucumber (Apostichopus japonicus)." Environmental Science & Technology 54, no. 20 (2020): 13175–85. http://dx.doi.org/10.1021/acs.est.0c04421.

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35

Pelkonen, O. "Building a toxicokinetic model using in vitro/in silico data: What is needed?" Toxicology Letters 238, no. 2 (2015): S47. http://dx.doi.org/10.1016/j.toxlet.2015.08.131.

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36

Adams, J. C., R. L. Dills, M. S. Morgan, D. A. Kalman, and C. H. Pierce. "A physiologically based toxicokinetic model of inhalation exposure to xylenes in Caucasian men." Regulatory Toxicology and Pharmacology 43, no. 2 (2005): 203–14. http://dx.doi.org/10.1016/j.yrtph.2005.07.005.

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37

NICHOLS, JOHN W., JAMES M. MCKIM, GREGORY J. LIEN, ALEX D. HOFFMAN, SHARON L. BERTELSEN, and COLLEEN M. ELONEN. "A Physiologically Based Toxicokinetic Model for Dermal Absorption of Organic Chemicals by Fish." Toxicological Sciences 31, no. 2 (1996): 229–42. http://dx.doi.org/10.1093/toxsci/31.2.229.

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38

Nichols, J. "A Physiologically Based Toxicokinetic Model for Dermal Absorption of Organic Chemicals by Fish." Fundamental and Applied Toxicology 31, no. 2 (1996): 229–42. http://dx.doi.org/10.1006/faat.1996.0095.

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39

Chen, Chu-Chih, Meng-Chiuan Shih, Kuen-Yuh Wu, and Pranab K. Sen. "Exterior exposure estimation using a one-compartment toxicokinetic model with blood sample measurements." Journal of Mathematical Biology 56, no. 5 (2007): 611–33. http://dx.doi.org/10.1007/s00285-007-0133-3.

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40

Tonnelier, Arnaud, Sandra Coecke, and José-Manuel Zaldívar. "Screening of chemicals for human bioaccumulative potential with a physiologically based toxicokinetic model." Archives of Toxicology 86, no. 3 (2011): 393–403. http://dx.doi.org/10.1007/s00204-011-0768-0.

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41

Bednarska, Agnieszka J., Peter Edwards, Richard Sibly, and Pernille Thorbek. "A toxicokinetic model for thiamethoxam in rats: implications for higher-tier risk assessment." Ecotoxicology 22, no. 3 (2013): 548–57. http://dx.doi.org/10.1007/s10646-013-1047-z.

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42

Sweeney, Lisa M., Matthew W. Himmelstein, and Michael L. Gargas. "Development of a preliminary physiologically based toxicokinetic (PBTK) model for 1,3-butadiene risk assessment." Chemico-Biological Interactions 135-136 (June 2001): 303–22. http://dx.doi.org/10.1016/s0009-2797(01)00177-6.

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43

Stamatelos, Spyros K., Ioannis P. Androulakis, Ah-Ng Tony Kong, and Panos G. Georgopoulos. "A semi-mechanistic integrated toxicokinetic–toxicodynamic (TK/TD) model for arsenic(III) in hepatocytes." Journal of Theoretical Biology 317 (January 2013): 244–56. http://dx.doi.org/10.1016/j.jtbi.2012.09.019.

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44

Goeden, Helen M., Christopher W. Greene, and James A. Jacobus. "A transgenerational toxicokinetic model and its use in derivation of Minnesota PFOA water guidance." Journal of Exposure Science & Environmental Epidemiology 29, no. 2 (2019): 183–95. http://dx.doi.org/10.1038/s41370-018-0110-5.

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45

VAN DER MOLEN, G. W., S. A. L. M. KOOIJMAN, and W. SLOB. "A Generic Toxicokinetic Model for Persistent Lipophilic Compounds in Humans: An Application to TCDD." Toxicological Sciences 31, no. 1 (1996): 83–94. http://dx.doi.org/10.1093/toxsci/31.1.83.

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46

VANDERMOLEN, G., S. KOOIJMAN, and W. SLOB. "A Generic Toxicokinetic Model for Persistent Lipophilic Compounds in Humans: An Application to TCDD." Fundamental and Applied Toxicology 31, no. 1 (1996): 83–94. http://dx.doi.org/10.1006/faat.1996.0079.

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47

Thomaseth, Karl, and Alberto Salvan. "Estimation of Occupational Exposure to 2,3,7,8-Tetrachlorodibenzo-p-Dioxin Using a Minimal Physiologic Toxicokinetic Model." Environmental Health Perspectives 106 (April 1998): 743. http://dx.doi.org/10.2307/3433829.

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48

Zhong, Guangbin, Shunhua Lu, Rong Chen, Nengwang Chen, and Qiao-Guo Tan. "Predicting Risks of Cadmium Toxicity in Salinity-Fluctuating Estuarine Waters Using the Toxicokinetic–Toxicodynamic Model." Environmental Science & Technology 54, no. 21 (2020): 13899–907. http://dx.doi.org/10.1021/acs.est.0c06644.

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49

Gundert-Remy, U. "Building a non-animal toxicokinetic model: What can be done? Case studies and lessons learned." Toxicology Letters 238, no. 2 (2015): S48. http://dx.doi.org/10.1016/j.toxlet.2015.08.132.

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50

Cooper, Alexander B., Manoj Aggarwal, Michael J. Bartels, et al. "PBTK model for assessment of operator exposure to haloxyfop using human biomonitoring and toxicokinetic data." Regulatory Toxicology and Pharmacology 102 (March 2019): 1–12. http://dx.doi.org/10.1016/j.yrtph.2018.12.004.

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