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Frans Jongeneelen & Wil ten Berge X2012, Edinburgh (UK), 2-5 July 2012 A generic, cross-chemical predictive PBTK-model running in MS-Excel

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Page 1: X2012    F.Jongeneelen

Frans Jongeneelen & Wil ten Berge

X2012, Edinburgh (UK), 2-5 July 2012

A generic, cross-chemical predictive PBTK-model running in MS-Excel

Page 2: X2012    F.Jongeneelen

Physiologically Based ToxicoKinetic (PBTK) modeling in chemical risk assessment

2

Schematic from: Georgopoulos

Domain of PBTK modeling

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Overview PBTK-model IndusChemFate

3

Exposure scenario Three routes of uptake:

Inhalation - concentrationDermal – dose rateOral - dose

Duration of exposure Personal Protective Equipment Species / subgroup Physical activity level (rest/ light)

PBTK-model

Compound parameters Physical-chemical properties:

DensityMolecular weight Vapour pressure Log(Kow) at pH 5.5 and 7.4Water Solubility

Biochemical parameters :Metabolism (kM and Vmax) Renal tubulair resorption Enterohepatic circulation ratio

0,00E+00

5,00E-05

1,00E-04

1,50E-04

2,00E-04

2,50E-04

3,00E-04

3,50E-04

4,00E-04

4,50E-04

0,000 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000

Hours

Pyrene and metabolites (Venous Blood)

VenBl C0 µmol/l

VenBl C1 µmol/l

VenBl C2 µmol/l

1. Enter parameters

2. Run model and get result

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Physiology of the PBTK-model

4

Lungs

Excretion of parent compound in urine

InhalationExhalation

V

E

N

O

U

S

B

L

O

O

D

A

R

T

E

R

I

A

L

B

L

O

O

D

Oral

intake

Dermal

load

Heart

Brain

Dermis

Adipose

Muscle

Bone

Stomach +

intestine

Liver

Kidney

Evaporation

Parent compound

Cyclus of 1st metabolite

To 2nd

metabolite

cyclus

Bone marrow

Lungs

Excretion of 1st metabolitein urine

Exhalation

VENOUS

BLOOD

ARTERIAL

BLOOD

Heart

Brain

Dermis

Adipose

Muscle

Bone

Stomach +

intestine

Liver

Kidney

Bone marrow

Page 5: X2012    F.Jongeneelen

Routing of chemicals and metabolites• Absorption: 3 routes

1. Inhalation

2. Oral uptake

3. Dermal uptake

• Partitioning in the body» Algorithm for estimate of blood:air partitioning

» Algorithms for estimates of tissue:blood partitioning in 11 compartments

• Metabolism» Saturable metabolism according to Michaelis-Menten kinetics

• Excretion: 2 pathways1. Renal excretion: algorithm related to log (kow)

2. Exhaled air: related to blood:air partitioning coefficient

• Set of differential equations predict change of amount over time 5

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The PBTK-model is easy-to-use

• Well-known software platform MS Excel

• The file IndusChemFate.xls contains 4 sheets:

1. Tutorial with instructions in short

2. Worksheet– For parameter entry

– For listing of numerical output

3. Datasheet with physical-chemical and biochemical properties of chemicals

4. Sheet with output in graphs

6

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Examples of simulations compared with observations

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Example 1: metabolites in urine of men and women

after exposure to Methyl Tert-Butyl Ether (MTBE)

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Simulation example 1

Inhalation study of Methyl Tert-Butyl Ether (MTBE) in men & women (Dekant et al, 2001)

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• 3 male and 3 female volunteers were exposed in anexposure chamber during 4h to 140 mg/m3

• Three metabolites were measured in urine• Metabolite 1 = tert-butanol = TBA• Metabolite 2 = 2-methyl-1,2-propanediol = MPD• Metabolite 3 = 2-hydroxy isobutyrate = HIBA

• No differences were found between men and women

Question: Does modeling confirm the absence of genderdifferences?

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Simulation example 1

Metabolism of MTBE

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MTBE TBA MPD HIBAparent compound 1st- 2nd- 3rd-metabolite

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Simulation example 1

Modeling: parameterisation of MTBE and metabolites

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1) Physical-chemical properties MTBE + 3 metabolites

2) Biochemical parameters of MTBEMTBE + 3 metabolites

3) Exposure scenarioInhalation MTBE: 4 h of 140 mg/m3

Exposed subject: male or female in rest

Follow up time: 72 h

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Simulation example 1

Modeling: entering model parameters

MTBE

Tert-ButylAlcohol (TBA)

Methylpropanediol (MPD)

Page 12: X2012    F.Jongeneelen

Simulation example 1

Modeling: entering exposure scenario and selection of exposed subject

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Airborne

exposure

scenario

Select subject

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Simulation example 1

Modeling: predicted concentration of MTBE and metabolites in urine of men in rest

13

0

50

100

150

200

250

300

350

400

450

0 6 12 18 24 30 36 42 48 54 60 66 72

Hours

MTBE and metabolites in urine

C0 = MTBE (µmol/L)

C1 = TBA (µmol/L)

C2 = MPD (µmol/L)

C3 = HIBA (µmol/L)

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Simulation example 1

Observed and predicted concentrations in urine of men and women in rest

Page 15: X2012    F.Jongeneelen

Simulation example 2: Dermal uptake of ethanol at hygienic hand + arm disinfection

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Compound Exposureroute

Exposure scenario Measuredparameter

Reference

Ethanol Dermal Disinfection of hands + arms to elbow with 95% ethanol

10 Rubs with 20 ml in 80 min

Six male volunteers

In open room of 37 m3

Ethanol in blood

Kramer et al, 2007

Page 16: X2012    F.Jongeneelen

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Simulated dermal uptake + inhalation of 300 mg/m3!

Simulated : dermal uptake only

Simulation example 2Observed and predicted concentrations of ethanol in blood after disinfection of hands and arms

Page 17: X2012    F.Jongeneelen

Suggested application domain of the PBTK-model IndusChemFate

Biomonitoring provides a glimse of the personal dose. The PBTK-model can be of help for interpretation of results

Bridge the gap between external and internal exposure monitoring

1st tier assessment of the fate of data-poor chemicals in body

Educational tool to understand toxicokinetics of chemicals in human body in relation to physical-chemical properties

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Page 18: X2012    F.Jongeneelen

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Where to get more info?

• Download EXCEL-application file and user manual:

– Website CEFIC LRI, web page IndusChemFate

http://www.cefic-lri.org/lri-toolbox/induschemfate

• Two papers (Ann Occup Hyg, 2011; Int Arch Occup Environ Hlth, 2012)

• Ask us to do a live-demonstration

Page 19: X2012    F.Jongeneelen

Acknowledgement

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Funding from CEFIC-LRI

Thank you