The Use of Exposure Reconstruction to Link Exposure, Internal Dose, and Health Outcomes

Transcription

1 The Use of Exposure Reconstruction to Link Exposure, Internal Dose, and Health Outcomes Harvey Clewell Director, Center for Human Health Assessment CIIT Centers for Health Research Research Triangle Park, NC

2 Linking Internal Dose to Health Outcomes CDC Evaluation of Mercury in Blood blood Hg levels in young children and women of childbearing age usually are below levels of concern. However, approximately 6% of childbearing-aged aged women had levels at or above a reference dose, an estimated level assumed to be without appreciable harm (>5.8( µg/l). -- CDC MMWR (NHANES )

3 Types of Information Needed to Link Internal Dose to Health Outcomes n Relationship of internal dose to health outcome from human studies Lead in blood Methylmercury in hair or blood n Relationship of internal dose to health outcome from animal studies Direct measurement (PFOA in blood) Pharmacokinetic (PK) modeling (in experimental animal) n Relationship of external dose to health outcome from animal studies Most common situation Need to link internal dose to external dose

4 Linking Internal Dose to Health Outcome The Big Problem is Lack of Toxicity Data 5 25 CDC s Third National Report on Human Exposure to Environmental Chemicals (2006) No known toxicity values Established Biological Exposure Indicies Established toxicity values 118

5 Linking Human Biomonitoring Data to Animal Toxicity Data Margin of safety Chemical concentrations in human blood from biomonitoring studies Chemical concentrations in animal blood in toxicity studies Pharmacokinetic Modeling Human exposures (Chemical concentrations in environment) Reverse dosimetry Forward dosimetry Pharmacokinetic modeling Animal exposures (Administered doses in toxicity studies) Traditional risk assessment

6 Alternative Approaches for Linking Biomonitoring Data to Health Outcomes n Animal Dosimetry: Compare blood concentration in population with blood concentration at NOAEL/LOAEL in animal to obtain Margin of Exposure (MOE) Requires: measurement of blood concentrations in toxicity studies or availability of PK model/data in animal to predict blood concentrations from external dose Issue: how to determine adequacy of MOE Complication: may also require data on relationship of human biomarker (e.g., urinary metabolite) to blood concentration

7 Warning: Not all Biomarkers are Equal Human Target Tissue Dose PBPK Human Blood Concentrations MoS MoIE Animal Target Tissue Dose PBPK Animal Blood Concentrations PK Human Urinary Metabolite Concentrations PK Animal Urinary Metabolite Concentrations BEI PK Human exposures Administered doses in toxicity studies

8 Alternative Approaches for Linking Biomonitoring Data to Health Outcomes n Forward Dosimetry: Compare biomonitoring data with predicted biomarker at toxicity value (RfD,, MCL, etc.) Requires: human PK model Complication: dealing with multiple-route exposures Issue: Ignores temporal relationship of exposures and biomarker sampling Appropriate use: initial screen

9 Linking Exposure to Biomonitoring Data Temporal Relationship of Exposures and Sampling Time of the day

10 Alternative Approaches for Linking Biomonitoring Data to Health Outcomes n Reverse Dosimetry: Estimate external exposure in population from biomonitoring data and compare with toxicity value (RfD( RfD,, MCL, etc.) Requires: human PK model to describe relationship of biomarker to external dose Complication: may also require information on the nature (sources, frequency, duration, etc.) of potential exposures Issue: dealing with uncertainty and variability in human exposures and pharmacokinetics Appropriate Use: for chemicals of concern

11 Linking Biomonitoring Data to External Exposure Physiologically Based Pharmacokinetic (PBPK) Modeling CV QC CVF PBPK Model for Chloroform CVR CVS CI QP Lung CX Fat Tissue PF CF VF Rapidly Perfused Tissues PR CR VR Slowly Perfused Tissues PS CS VS CA QC QF QR QS Air out Mass Transfer of VOC from Shower Water to Air Q A C A Hot water in V A C A H C l Q W Cl Cl C W,i n y H Cl H Cl Cl C l Cl C l Q A C A,in Air in CVSkn Surface P Skin QSkn KTD CVL Duodenum KAD KTSD Stomach KAS Gut Tissue PG CG VG Liver Tissue PL CL VL KF CVG (Corley et al. 2000) VMAX, KM PDOSE QG QL Q w C W,out Water out (Weisel et al. 1999)

12 Exposure Reconstruction Using a PBPK Model Iraqi woman exposed during pregnancy to grain contaminated with methylmercury M a t e r n a l E x p o s u r e 4 2 µ g / k g / d a y d a y s M a t e r n a l h a i r M a t e r n a l b l o o d I n f a n t b l o o d MeHg in Hair (ppm) MeHg in Blood (ppm) P r e g n a n c y D a y s (Clewell et al. 2000)

13 Exposure Reconstruction is an Ill-Posed Problem (Many possible solutions) Comparison of PBPK Predicted Blood Concentrations with Experimental Data Comparison of Reconstructed Exposure Conditions with Actual Exposure Conditions (Sohn et al. 2004) Requires population-level, level, probabilistic approach

14 Illustration of a Monte Carlo Analysis for the Time Course of Blood Concentrations from Household Exposures Time-cours e Monte Carlo Simulation for Exhaled Breath Level Chloroform level in blood (ppt) Human subject # Time of the day (h)

15 Comparison of Measured Distribution of Blood Concentrations of Chloroform (from NHANES III) with PBPK/MC Predictions Based on Measured Distribution of Tap Water Concentrations of Chloroform (from TEAM) Measured distributions of chloroform concentrations in blood (pg/ml ml) Percentile NHANES III data Blood (pg/ml ml) 5% -- Assuming chloroform concentration in household air is independent dent of chloroform concentration in tap water % -- Predicted distributions of chloroform concentrations in blood (pg/ml ml) % 9.3 Assuming chloroform concentration in household air = chloroform concentration in tap water -- 50% % % % Blood (pg/ml ml)

16 Linking Human Biomonitoring Data to External Dose Using Reverse Dosimetry n Role of PBPK Correct integration of exposure routes n pre-systemic clearance n flow-limited limited metabolism Determine relationship of biomarker of internal exposure to target tissue dose for health effect (e.g., amount metabolized in the liver) n Role of Monte Carlo Analysis Reconstruct distribution of likely exposures across the population, not just average or worst-case Consider variability and uncertainty in exposure and sampling

17 Reverse Dosimetry Approach ppb of chemical in air or µg/l of chemical in water Monte Carlo analysis b ility a P rob Estimated distribution of chemical in blood Chloroform level in blood (ppt) Invert Distribution Exposure Conversion Factor distribution Convolute Distributions Estimated population exposure distribution Distribution of measured blood concentrations

18 Exposure Conversion Factor Distribution The distribution of exposure concentrations that could yield a unit blood concentration of chloroform: Percentile 5% 10% 25% 50% 75% 90% 95% ECF (µg/l in water per pg/ml in blood) e.g., If Mr. X has a blood concentration of 0.5 pg/ml, the concentration of chloroform in his water has a median estimate of = 1.33 µg/l, but could range from 0.25 to 2.26 µg/l with 90% confidence.

19 Predicted Distribution of Exposures to Chloroform in the Population Reported in NHANES III (mg/kg/day) Probability density function RfD E E E E E E E E E-01 Water intake (mg/kg/day)

20 Monte Carlo Analysis with QSAR-Estimated Partition Coefficients and Kinetic Parameters Exposure Parameters Time of the day CV QC CI QP Lung CX CA QC CVF Fat Tissue PF CF VF QF CVR CVS Rapidly Perfused Tissues PR CR VR Slowly Perfused Tissues PS CS VS QR QS TCE in blood Surface Physiological Parameters CVSkn KTD Duodenum P Skin KTSD Stomach QSkn PDOSE QSAR Bounding Partition Coefficients Kinetic Parameters CVL KAD KAS Gut Tissue PG CG VG CVG Liver Tissue PL CL VL KF VMAX, KM QG QL

21 Monte Carlo Simulation for TCE Concentrations in Blood Impact of Uncertainty in QSAR-derived PBPK Model QSAR-based Monte Carlo Published model-based Monte Carlo Frequency Detection limit from NHANES III 90 th percentile from NHANES III 90 th percentile: published model 90 th percentile: QSAR 100 Variability Variability + Uncertainty LOG10(TCE concentration in blood [mg/l])

22 Linking Human Biomonitoring Data to Exposure Problems Vary with the Nature of the Chemical n Volatiles Complex household exposures Rapid clearance n Blood levels highly sensitive to transient exposures n Intermediate persistence compounds Interpretation depends on rate of clearance n Need to consider timing of exposures vs. sampling May need to deal with multiple metabolites n Highly persistent compounds Slow approach to steady state Apparent clearance confounded by changes in body weight, fat content

23 Poorly Metabolized, Lipophilic Compounds Complicated Relationship of Internal Dose to Exposure Transplacental exposure to maternal stores of TCDD Different fractional volume of fat between male and female Dilution of TCDD stores by the rapid growth of neonate Continuous exposure (Clewell et al., 2004)

24 Linking Biomarkers to Exposure and Health Outcomes Problems Vary with the Nature of the Biomarker n Parent chemical / active metabolite in blood Often a good surrogate for target tissue dose Directly comparable to animal blood levels at NOAEL/LOAEL Use to estimate exposure requires PK information n Inactive metabolite in Blood Use requires PK information Not directly comparable to animal blood levels n Parent chemical or metabolite in urine More easily related to exposure (uptake) rather than internal (target tissue) dose Use of metabolite for exposure reconstruction requires information on fractional yield

25 Summary n Reverse dosimetry Probabilistic dose reconstruction at the population level Links biomarkers of internal dose to likely external exposures Useful in absence of direct link between biomarker and health outcomes Critically dependent on population exposure characterization

26 Acknowledgements CIIT Centers for Health Research EPA ACC Funding Cecilia Tan Ken Liao Mel Andersen Rory Conolly Rick Becker Chlorine Chemistry Council American Chemistry Council