title: Reconstructing exposures from biomarkers using exposure-pharmacokinetic modeling--A case study with carbaryl.
abstract: Sources of uncertainty involved in exposure reconstruction for short half-life chemicals were characterized using computational models that link external exposures to biomarkers. Using carbaryl as an example, an exposure model, the Cumulative and Aggregate Risk Evaluation System (CARES), was used to generate time-concentration profiles for 500 virtual individuals exposed to carbaryl. These exposure profiles were used as inputs into a physiologically based pharmacokinetic (PBPK) model to predict urinary biomarker concentrations. These matching dietary intake levels and biomarker concentrations were used to (1) compare three reverse dosimetry approaches based on their ability to predict the central tendency of the intake dose distribution; and (2) identify parameters necessary for a more accurate exposure reconstruction. This study illustrates the trade-offs between using non-iterative reverse dosimetry methods that are fast, less precise and iterative methods that are slow, more precise. This study also intimates the necessity of including urine flow rate and elapsed time between last dose and urine sampling as part of the biomarker sampling collection for better interpretation of urinary biomarker data of short biological half-life chemicals. Resolution of these critical data gaps can allow exposure reconstruction methods to better predict population-level intake doses from large biomonitoring studies.
authors.affiliation: U.S. Environmental Protection Agency, National Exposure Research Laboratory, Durham, NC, USA.
authors.forename: Kathleen
authors.initials: K
authors.lastname: Brown
authors.affiliation: Minnesota Department of Health, St. Paul, MN, USA.
authors.forename: Martin
authors.initials: M
authors.lastname: Phillips
authors.affiliation: Lockheed Martin, Durham, NC, USA.
authors.forename: Christopher
authors.initials: C
authors.lastname: Grulke
authors.affiliation: The Hamner Institutes for Health Sciences, Durham NC, USA.
authors.forename: Miyoung
authors.initials: M
authors.lastname: Yoon
authors.affiliation: Bayer CropScience, Durham NC, USA.
authors.forename: Bruce
authors.initials: B
authors.lastname: Young
authors.affiliation: Astra Zeneca, Boston MA, USA.
authors.forename: Robin
authors.initials: R
authors.lastname: McDougall
authors.affiliation: Oak Ridge Institute for Science and Education, Oak Ridge, TN, USA.
authors.forename: Jeremy
authors.initials: J
authors.lastname: Leonard
authors.affiliation: Oak Ridge Institute for Science and Education, Oak Ridge, TN, USA.
authors.forename: Jingtao
authors.initials: J
authors.lastname: Lu
authors.affiliation: Meemir Consulting, Durham, NC, USA.
authors.forename: William
authors.initials: W
authors.lastname: Lefew
authors.affiliation: U.S. Environmental Protection Agency, National Exposure Research Laboratory, Durham, NC, USA. Electronic address: tan.cecilia@epa.gov.
authors.forename: Yu-Mei
authors.initials: YM
authors.lastname: Tan
mesh_terms: D001499:Bayes Theorem; D015415:Biomarkers / Q000652:urine; D012721:Carbaryl / Q000009:adverse effects / Q000493:pharmacokinetics* / Q000652:urine*; D003198:Computer Simulation; D004032:Diet; D004305:Dose-Response Relationship, Drug; D004781:Environmental Exposure / Q000009:adverse effects; D004784:Environmental Monitoring / Q000379:methods*; D005506:Food Contamination; D006207:Half-Life; D006801:Humans; D007306:Insecticides / Q000009:adverse effects / Q000493:pharmacokinetics* / Q000652:urine*; D008390:Markov Chains; D008954:Models, Biological; D009010:Monte Carlo Method; D018570:Risk Assessment; D016482:Urinalysis; D014874:Water Pollutants, Chemical / Q000009:adverse effects / Q000493:pharmacokinetics* / Q000652:urine*; D014877:Water Pollution, Chemical; D060753:Water Quality
chemical_list: D015415:Biomarkers; D007306:Insecticides; D014874:Water Pollutants, Chemical; D012721:Carbaryl
keywords: Biomarker interpretation; CARES; Carbaryl; Discretized Bayesian; Exposure conversion factor; Exposure reconstruction; Markov Chain Monte Carlo; Pharmacokinetic modeling; Physiologically based pharmacokinetic model; Population-based biomonitoring