PBTK Workshop EPAA -Ispra (I)
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This document describes a generic physiologically-based toxicokinetic (PBTK) model called IndusChemFate that can be used to estimate the absorption, distribution, metabolism and excretion of chemicals in humans and other species. The model uses quantitative structure-property relationship algorithms to estimate partitioning and uses Michaelis-Menten kinetics to model saturable metabolism. It is implemented in Microsoft Excel for easy use. The document provides examples of using the model to simulate worker exposure to pyrene and dermal absorption of ethanol after hand disinfection. It also discusses how this generic PBTK model differs from other models and its potential applications.
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PBTK Workshop EPAA -Ispra (I)
- 1. Frans Jongeneelen & Wil ten Berge EPAA workshop, Ispra (I), 13-14 October 2011 A generic, cross-chemical predictive PBTK-model
- 2. PBTK-model in exposure/dose assessment Schematic from: Georgopoulos
- 3. What were the demands for our generic PBTK-model? Simple and easy model To be used for occupational and/or environmental exposures ( Variability of environmental exposure is higher than biological variability) 1 st tier estimate accuracy (one order of magnitude) Minimum of data input Free open source model Choices made QSPR prediction of partitioning metabolism data of in vitro metabolism kinetics MS Excel software platform Species: man (in rest or light activity ), rat, mouse
- 4. Result: Overview of the PBTK-model IndusChemFate Exposure scenario Three routes of uptake: Inhalation - concentration Dermal dose rate Oral - dose Duration of exposure Personal Protective Equipment Species Physical activity level (rest/ light) PBTK-model Compound data Physical-chemical properties: Density Molecular weight Vapour pressure Log(K ow ) at pH 5.5 and 7.4 Water Solubility Biochemical parameters : Metabolism (k M and V max ) Renal tubulair resorption Enterohepatic circulation ratio
- 5. Scheme of the physiology of the PBTK-model
- 6. Routing of chemicals and metabolites in the PBTK-model Absorption Inhalation Oral uptake Dermal uptake Distribution over the body QSPR algorithm for estimate of blood:air partitioning QSPR algorithm for estimate of tissue:blood partitioning Metabolism Saturable metabolism according to Michaelis-Menten kinetics Excretion Urine Exhaled air
- 7. Dermal absorption module of the model = New model of AIHA-EASC named IH SKINPERM
- 8. Distribution over compartments in the body Blood:air partition coefficient QSPR Algorithm for estimation of blood:air partitioning based on Henry coefficient and K oa Blood:tissue partition coefficient QSPR Algorithm for estimation of blood:tissue partitioning taken from De Jong et al (1997), based on lipid content and K ow
- 9. Metabolism Metabolism can be modeled in all tissues Default is metabolism in liver only Sequential metabolism Parent, 1st metabolite, 2nd metabolite and so on Stoichiometric yield in every step Rate of loss of parent and appearance of metabolite Difference gives stoichimetric yield of specific metabolite K M and V max from in experiments in microsomal liver fraction or hepatocytes Scaled to liver weight of individual/species
- 10. Other aspects Excretion in urine and alveolair air With enterohepatic circulation fase 2 metabolites
- 11. The PBTK-model is build as application in MS-Excel, called IndusChemFate The differential equations of the PBTK-model are written in speadsheet syntax (visual basic) The file IndusChemFate contains 4 sheets: Tutorial with instructions in short Worksheet For data entry (exposure scenario, properties of chemical under study) For numerical output Database of phys-chemical and biochemical properties of various chemicals Graphical output sheet
- 12. Simulation example 1 Average and individual variation in workers Paper: Inhaled dosimetry and biomonitoring of coal liquefaction workers (Quinlan et al, 1995) At coal liquefaction plants PAH occur as pollutants 5 workers were followed during 4 shift on and 96h off work Average pyrene in breathing zone was 1.3 袖g/m 3 pyrene. 1-hydroxypyrene in urine was measured during 8 days = 192 h
- 13. Simulation example 1 Metabolism of pyrene Figure taken from: Luukkanen et al, 2001
- 14. Simulation example 1 Kinetics of in vitro metabolism of pyrene in human hepatic fractions Step Tissue Parameter and value ref Pyrene to 1-OH-pyrene Hepatic 9000*g fraction of 12 individuals V max = 180 袖 mol/hr/kg tissue K M = 4.4 袖 M Jongeneelen (1987) 1-OH-Pyrene to 1-OH-pyrene- glucuronide Hepatic microsomal fraction of 3 individuals V max = 6,900 袖 mol/hr/kg tissue K M = 7.7 袖 M Luukkanen et al (2001)
- 15. Simulation example 1 Modeling: Data to be entered Enter phys-chemical properties and biochemical parameters of parent compound and metabolites under study Enter exposure scenario Inhalation: concentration and duration Dermal: dose rate and duration Oral: bolus dose
- 16. Simulation example 1 Entering properties & biochem data of pyrene and metabolites Pyrene 1-OH-Pyrene 1-OH-Pyrene-glucuronide
- 17. Simulation example 1 Entering exposure scenario of the coal liquefaction workers Airborne exposure scenario Dermal exposure scenario Oral intake scenario
- 18. Simulation example 1 Run program - Results as table with levels and amounts in fluids and tissues
- 19. Simulation example 1 Run program- Results as graphs Figure 3: Urine Figure 2: Blood Figure 1: Alveolair air
- 20. Simulation Example 1 Result: predicted concentration total 1-OHP in urine of the coal liquefaction workers (in umol/L)
- 21. Simulation example 1 Comparison measured 1-OHP in urine versus predicted Note: Dermal exposure was not measured and set at zero in simulation
- 22. Simulation Example 1 Result: Estimated fate of mass of pyrene + metabolites
- 23. Simulation example 1 Conclusion The average level of hydroxypyrene can be predicted when the exposure scenario is known A rough predictive model does when we realise that differences of external exposure between workers are large
- 24. Simulation example 2: dermal uptake after desinfection of hands with ethanol Nr. Compound Type of study Exposure route Exposure scenario Reference 1 Pyrene Observa-tional study of workers Inhalation + dermal 4*12 on work, 96 hr off work Quinlan, 1995 2 Ethanol Volunteer study Application on skin, dermal 10 times disinfection of hands and arms. Rubbing during 80 min. Kramer, 2007
- 25. Simulation example 2 Ethanol in blood after disinfecting of hands and arms (Kramer et al, 2007) Dermal + inhalation of evaporated ethanol! Solid line: dermal only exposure scenario
- 26. Simulation example 2 Conclusion Dermal uptake of ethanol can be predicted Evaporation of ethanol seems to be a significant extra route of uptake of ethanol after handrubbing
- 27. What are the differences between this PBTK-model and other PBTK-models? GENERIC MODEL Distribution of the chemical/metabolite in the body is estimated by algorithms, thus model can easily can be used for many different volatile and semi-volatile chemicals RUNS IN WIDELY AVAILABLE SOFTWARE The software application is running in MS EXCEL, a software platform that is widely available
- 28. Suggested application of this PBTK-model IndusChemFate Chemical health risk assessors Volatile and semi-volatile compounds A prior i (= 1st tier) estimation of concentration in body tisues and/or body fluids at specific exposure scenarios Screening of absorpion and fate of data-poor substances in the human body In vivo extrapolation of in vitro ADME data Comparisons of toxicokinetics in different species (in-vivo to in vivo extrapolation) Assessment of contribution of dermal uptake to body burden Student and non-experts Educational tool to understand toxicokinetics of chemicals in human body in relation to phys-chem properties
- 29. Download EXCEL-application file and user manual : Website CEFIC LRI, webpage IndusChemFate http://www.cefic-lri.org/lri-toolbox/induschemfate Read Paper (in Annals Occupational Hygiene 2011) See at our website: www.industox.nl Ask us to do a live-demonstration Where to get more info?
- 30. Acknowledgement Funding from CEFIC-LRI Thank you Any questions ?