Advertisement

Modelling the Fate of Chemicals in Humans Using a Lifetime Physiologically Based Pharmacokinetic (PBPK) Model in MERLIN-Expo

Chapter
Part of the The Handbook of Environmental Chemistry book series (HEC, volume 57)

Abstract

This chapter presents the human model implemented in MERLIN-Expo. This model is a physiologically based pharmacokinetic (PBPK) model that describes the relationship between an external dose and an internal dosimetry using parameters related to the anatomy and physiology of individuals and the physico-chemical properties of the contaminants. The goal of the PBPK model is to simulate the toxicokinetics of contaminants in humans, e.g. the amounts or concentrations of contaminants in different organs/tissues, under various exposure conditions. The generic PBPK model is based on a detailed compartmentalisation of the human body and parameterised with relationships describing the time evolution of the physiology and anatomy of the individuals. In this chapter, we present the detailed description of the human model and the conditions to apply it in MERLIN-Expo. Finally, the model predictability is evaluated by a direct comparison between computational predictions and experimental data on small case studies.

Keywords

Childhood Environmental chemicals Humans Lifetime exposure PBPK model 

References

  1. 1.
    Andersen ME (1991) Physiological modelling of organic compounds. Ann Occup Hyg 35(3):309–321Google Scholar
  2. 2.
    Brochot C, Smith TJ, Bois FY (2007) Development of a physiologically based toxicokinetic model for butadiene and four major metabolites in humans: global sensitivity analysis for experimental design issues. Chem Biol Interact 167(3):168–183CrossRefGoogle Scholar
  3. 3.
    Nestorov I (2003) Whole body pharmacokinetic models. Clin Pharmacokinet 42(10):883–908CrossRefGoogle Scholar
  4. 4.
    Reddy MB, Yang RSH, Clewell III HJ, et al (2005) Physiologically based pharmacokinetic modelling: science and applications. Wiley, HobokenCrossRefGoogle Scholar
  5. 5.
    Teorell T (1937) Kinetics of distribution of substances administered to the body. Arch Int Pharmacodyn Ther 57:205–240Google Scholar
  6. 6.
    Beaudouin R, Micallef S, Brochot C (2010) A stochastic whole-body physiologically based pharmacokinetic model to assess the impact of inter-individual variability on tissue dosimetry over the human lifespan. Regul Toxicol Pharmacol 57(1):103–116CrossRefGoogle Scholar
  7. 7.
    Clewell HJ, Gentry PR, Covington TR, et al (2004) Evaluation of the potential impact of age- and gender-specific pharmacokinetic differences on tissue dosimetry. Toxicol Sci 79(2):381–393CrossRefGoogle Scholar
  8. 8.
    Edginton AN, Schmitt W, Willmann S (2006) Development and evaluation of a generic physiologically based pharmacokinetic model for children. Clin Pharmacokinet 45(10):1013–1034CrossRefGoogle Scholar
  9. 9.
    Kerger BD, Leung HW, Scott P, et al (2006) Age- and concentration-dependent elimination half-life of 2,3,7,8-tetrachlorodibenzo-p-dioxin in Seveso children. Environ Health Perspect 114(10):1596–1602CrossRefGoogle Scholar
  10. 10.
    Haddad S, Restieri C, Krishnan K (2001) Characterization of age-related changes in body weight and organ weights from birth to adolescence in humans. J Toxicol Environ Health A 64(6):453–464CrossRefGoogle Scholar
  11. 11.
    Price K, Haddad S, Krishnan K (2003) Physiological modeling of age-specific changes in the pharmacokinetics of organic chemicals in children. J Toxicol Environ Health A 66(5):417–433CrossRefGoogle Scholar
  12. 12.
    Yang F, Tong XP, McCarver DG, et al (2006) Population-based analysis of methadone distribution and metabolism using an age-dependent physiologically based pharmacokinetic model. J Pharmacokinet Pharmacodyn 33(4):485–518CrossRefGoogle Scholar
  13. 13.
    Environmental Protection Agency (US EPA) (2006) Approaches for the application of physiologically based pharmacokinetic (PBPK) models and supporting data in risk assessment (final report). Environmental Protection Agency (US EPA), Washington, DCGoogle Scholar
  14. 14.
    International Programme on Chemical Safety (IPCS) (2010) Characterization and application of physiologically based pharmacokinetic models in risk assessment. World Health Organization, GenevaGoogle Scholar
  15. 15.
    Peters SA (2012) Physiologically-based pharmacokinetic (PBPK) modeling and simulations: principles, methods, and applications in the pharmaceutical industry. Wiley, HobokenCrossRefGoogle Scholar
  16. 16.
    Andersen ME (2003) Toxicokinetic modeling and its applications in chemical risk assessment. Toxicol Lett 138(1–2):9–27CrossRefGoogle Scholar
  17. 17.
    Clewell HJ, Tan YM, Campbell JL, et al (2008) Quantitative interpretation of human biomonitoring data. Toxicol Appl Pharmacol 231(1):122–133CrossRefGoogle Scholar
  18. 18.
    Ulaszewska MM, Ciffroy P, Tahraoui F, et al (2012) Interpreting PCB levels in breast milk using a physiologically based pharmacokinetic model to reconstruct the dynamic exposure of Italian women. J Exposure Sci Environ Epidemiol 22(6):601–609CrossRefGoogle Scholar
  19. 19.
    Zeman FA, Boudet C, Tack K, et al (2013) Exposure assessment of phthalates in French pregnant women: results of the ELFE pilot study. Int J Hyg Environ Health 216(3):271–279CrossRefGoogle Scholar
  20. 20.
    Gerlowski LE, Jain RK (1983) Physiologically based pharmacokinetic modeling: principles and applications. J Pharm Sci 72:1103–1127CrossRefGoogle Scholar
  21. 21.
    Sharma M, Maheshwari M, Morisawa S (2005) Dietary and inhalation intake of lead and estimation of blood lead levels in adults and children in Kanpur, India. Risk Anal 25(6):1573–1588CrossRefGoogle Scholar
  22. 22.
    Pelkonen O, Turpeinen M (2007) In vitro-in vivo extrapolation of hepatic clearance: biological tools, scaling factors, model assumptions and correct concentrations. Xenobiotica 37(10–11):1066–1089CrossRefGoogle Scholar
  23. 23.
    Barter ZE, Bayliss MK, Beaune PH, et al (2007) Scaling factors for the extrapolation of in vivo metabolic drug clearance from in vitro data: Reaching a consensus on values of human microsomal protein and hepatocellularity per gram of liver. Curr Drug Metab 8(1):33–45CrossRefGoogle Scholar
  24. 24.
    National Health and Nutrition Examination Survey (1995) Third national health and nutrition examination survey, 1988–1991. Selected laboratory and mobile examination center data. version 1, September 1995Google Scholar
  25. 25.
    Altman PL, Dittmer DS (1962) Growth, including reproduction and morphological development. Federation of American Societies for Experimental Biology, Washington, DCGoogle Scholar
  26. 26.
    International Commission on Radiological Protection (2002) Basic anatomical and physiological data for use in radiological protection: reference values. Valentin J, StockholmGoogle Scholar
  27. 27.
    Lexell J, Taylor CC, Sjostrom M (1988) What is the cause of the aging atrophy – total number, size and proportion of different fiber types studied in Whole vastus lateralis muscle from 15-year-old to 83-year-old men. J Neurol Sci 84(2–3):275–294CrossRefGoogle Scholar
  28. 28.
    Luisada AA, Bhat PK, Knighten V (1980) Changes of cardiac-output caused by aging – an impedance cardiographic study. Angiology 31(2):75–81CrossRefGoogle Scholar
  29. 29.
    Johnson TN, Rostami-Hodjegan A, Tucker GT (2006) Prediction of the clearance of eleven drugs and associated variability in neonates, infants and children. Clin Pharmacokinet 45(9):931–956CrossRefGoogle Scholar
  30. 30.
    Vinegar A, Jepson GW, Overton JH (1998) PBPK modeling of short-term (0 to 5 min) human inhalation exposures to halogenated hydrocarbons. Inhal Toxicol 10(5):411–429CrossRefGoogle Scholar
  31. 31.
    Darwich AS, Neuhoff S, Jamei M, et al (2010) Interplay of metabolism and transport in determining oral drug absorption and gut wall metabolism: a simulation assessment using the “advanced dissolution, absorption, metabolism (ADAM)” model. Curr Drug Metab 11(9):716–729CrossRefGoogle Scholar
  32. 32.
    Yu LX, Lipka E, Crison JR, et al (1996) Transport approaches to the biopharmaceutical design of oral drug delivery systems: prediction of intestinal absorption. Adv Drug Deliv Rev 19(3):359–376CrossRefGoogle Scholar
  33. 33.
    Bois FY, Jamei M, Clewell HJ (2010) PBPK modelling of inter-individual variability in the pharmacokinetics of environmental chemicals. Toxicology 278(3):256–267CrossRefGoogle Scholar
  34. 34.
    Kalow W (2001) Chapter 1: genetic factors that cause variability in human drug metabolism. In: Pacifici GM, Pelkonen O (eds) Interindividual variability in human drug metabolism. Taylor & Francis, London, pp. 1–14Google Scholar
  35. 35.
    Zeise L, Bois FY, Chiu WA, et al (2013) Addressing human variability in next-generation human health risk assessments of environmental chemicals. Environ Health Perspect 121(1):23–31Google Scholar
  36. 36.
    Johns DO, Owens EO, Thompson CM, et al (2010) Physiological parameters and databases for PBPK modeling. In: Kannan K, Andersen ME (eds) Quantitative modeling in toxicology. Wiley, Chichester, pp. 107–134CrossRefGoogle Scholar
  37. 37.
    Price PS, Conolly RB, Chaisson CF, et al (2003) Modeling interindividual variation in physiological factors used in PBPK models of humans. Crit Rev Toxicol 33(5):469–503CrossRefGoogle Scholar
  38. 38.
    Dorne JL, Walton K, Renwick AG (2003) Human variability in CYP3A4 metabolism and CYP3A4-related uncertainty factors for risk assessment. Food Chem Toxicol 41(2):201–224CrossRefGoogle Scholar
  39. 39.
    Mezzetti M, Ibrahim JG, Bois FY, et al (2003) A Bayesian compartmental model for the evaluation of 1,3-butadiene metabolism. J R Stat Soc Ser C Appl Stat 52:291–305CrossRefGoogle Scholar
  40. 40.
    Poulin P, Krishnan K (1996) A tissue composition-based algorithm for predicting tissue: air partition coefficients of organic chemicals. Toxicol Appl Pharmacol 140(2):521–522CrossRefGoogle Scholar
  41. 41.
    Plowchalk DR, Andersen ME, deBethizy JD (1992) A physiologically based pharmacokinetic model for nicotine disposition in the Sprague-Dawley rat. Toxicol Appl Pharmacol 116(2):177–188CrossRefGoogle Scholar
  42. 42.
    Shin BS, Hong SH, Bulitta JB, et al (2009) Physiologically based pharmacokinetics of zearalenone. J Toxicol Environ Health A 72(21–22):1395–1405CrossRefGoogle Scholar
  43. 43.
    Bjorkman S, Fyge A, Qi Z (1996) Determination of the steady state tissue distribution of midazolam in the rat. J Pharm Sci 85(8):887–889CrossRefGoogle Scholar
  44. 44.
    Ichimura F, Yokogawa K, Yamana T, et al (1983) Physiological pharmacokinetic model for pentazocine. 1. Tissue distribution and elimination in the rat. Int J Pharm 15(3):321–333CrossRefGoogle Scholar
  45. 45.
    Bjorkman S, Stanski DR, Verotta D, et al (1990) Comparative tissue concentration profiles of fentanyl and alfentanil in humans predicted from tissue/blood partition data obtained in rats. Anesthesiology 72(5):865–873CrossRefGoogle Scholar
  46. 46.
    Ebling WF, Wada DR, Stanski DR (1994) From piecewise to full physiologic pharmacokinetic modeling: applied to thiopental disposition in the rat. J Pharmacokinet Biopharm 22(4):259–292CrossRefGoogle Scholar
  47. 47.
    Csanady GA, Oberste-Frielinghaus HR, Semder B, et al (2002) Distribution and unspecific protein binding of the xenoestrogens bisphenol A and daidzein. Arch Toxicol 76(5–6):299–305Google Scholar
  48. 48.
    Gearhart JM, Mahle DA, Greene RJ, et al (1993) Variability of physiologically based pharmacokinetic (PBPK) model parameters and their effects on PBPK model predictions in a risk assessment for perchloroethylene (PCE). Toxicol Lett 68(1–2):131–144CrossRefGoogle Scholar
  49. 49.
    Van der Molen GW, Kooijman SALM, Slob W (1996) A generic toxicokinetic model for persistent lipophilic compounds in humans: an application to TCDD. Fundam Appl Toxicol 31:83–94CrossRefGoogle Scholar
  50. 50.
    Maruyama W, Yoshida K, Tanaka T, et al (2003) Simulation of dioxin accumulation in human tissues and analysis of reproductive risk. Chemosphere 53(4):301–313CrossRefGoogle Scholar
  51. 51.
    Environment Agency (2000) Report of survey on the exposure of dioxins in human (in Japanese)Google Scholar
  52. 52.
    Iida T, Hirakawa H, Matsueda T, et al (1999) Recent trend of polychlorinated dibenzo-p-dioxins and their related compounds in the blood and sebum of Yusho and Yu-Cheng patients. Chemosphere 38(5):981–993CrossRefGoogle Scholar
  53. 53.
    Milbrath MO, Wenger Y, Chang CW, et al (2009) Apparent half-lives of dioxins, furans, and polychlorinated biphenyls as a function of age, body fat, smoking status, and breast-feeding. Environ Health Perspect 117(3):417–425CrossRefGoogle Scholar
  54. 54.
    Toyoda M, Uchibe H, Yanagi T, et al (1999) Dietary daily intake of PCDDs, PCDFs and coplanar PCBs by total diet study in Japan. J Food Hyg Soc Jpn 40(1):98–110CrossRefGoogle Scholar
  55. 55.
    Houde M, De Silva AO, Muir DC, et al (2011) Monitoring of perfluorinated compounds in aquatic biota: an updated review. Environ Sci Technol 45(19):7962–7973CrossRefGoogle Scholar
  56. 56.
    Noorlander CW, van Leeuwen SPJ, Biesebeek JDT, et al (2011) Levels of perfluorinated compounds in food and dietary intake of PFOS and PFOA in The Netherlands. J Agric Food Chem 59(13):7496–7505CrossRefGoogle Scholar
  57. 57.
    Cornelis C, D’Hollander W, Roosens L, et al (2012) First assessment of population exposure to perfluorinated compounds in Flanders, Belgium. Chemosphere 86(3):308–314CrossRefGoogle Scholar
  58. 58.
    Perez F, Nadal M, Navarro-Ortega A, et al (2013) Accumulation of perfluoroalkyl substances in human tissues. Environ Int 59:354–362CrossRefGoogle Scholar
  59. 59.
    Domingo JL, Ericson-Jogsten I, Perello G, et al (2012) Human exposure to perfluorinated compounds in Catalonia, Spain: contribution of drinking water and fish and shellfish. J Agric Food Chem 60(17):4408–4415CrossRefGoogle Scholar
  60. 60.
    Haug LS, Huber S, Becher G, et al (2011) Characterisation of human exposure pathways to perfluorinated compounds–comparing exposure estimates with biomarkers of exposure. Environ Int 37(4):687–693CrossRefGoogle Scholar
  61. 61.
    Shoeib M, Harner T, Webster GM, et al (2011) Indoor sources of poly- and perfluorinated compounds (PFCS) in Vancouver, Canada: implications for human exposure. Environ Sci Technol 45(19):7999–8005CrossRefGoogle Scholar
  62. 62.
    Olsen GW, Burris JM, Ehresman DJ, et al (2007) Half-life of serum elimination of perfluorooctanesulfonate, perfluorohexanesulfonate, and perfluorooctanoate in retired fluorochemical production workers. Environ Health Perspect 115(9):1298–1305CrossRefGoogle Scholar
  63. 63.
    Emmett EA, Shofer FS, Zhang H, et al (2006) Community exposure to perfluorooctanoate: relationships between serum concentrations and exposure sources. J Occup Environ Med 48(8):759–770CrossRefGoogle Scholar
  64. 64.
    Ericson I, Gomez M, Nadal M, et al (2007) Perfluorinated chemicals in blood of residents in Catalonia (Spain) in relation to age and gender: a pilot study. Environ Int 33(5):616–623CrossRefGoogle Scholar
  65. 65.
    Domingo JL, Jogsten IE, Eriksson U, et al (2012) Human dietary exposure to perfluoroalkyl substances in Catalonia, Spain. Temporal trend. Food Chem 135(3):1575–1582CrossRefGoogle Scholar
  66. 66.
    Ericson I, Nadal M, van Bavel B, et al (2008) Levels of perfluorochemicals in water samples from Catalonia, Spain: is drinking water a significant contribution to human exposure? Environ Sci Pollut R 15(7):614–619CrossRefGoogle Scholar
  67. 67.
    EFSA (2011) European Food Safety Authority database in exposure assessmentGoogle Scholar
  68. 68.
    Loccisano AE, Campbell Jr JL, Andersen ME, et al (2011) Evaluation and prediction of pharmacokinetics of PFOA and PFOS in the monkey and human using a PBPK model. Regul Toxicol Pharmacol 59(1):157–175CrossRefGoogle Scholar
  69. 69.
    Azar A, Snee RD, Habibi K (1975) An epidemiologic approach to community air lead exposure using personal air samplers. Environ Qual Saf Suppl 2:254–290Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Institut National de l’Environnement Industriel et des Risques (INERIS), Unité Modèles pour l’Ecotoxicologie et la Toxicologie (METO)Verneuil en HalatteFrance

Personalised recommendations