Reconstructing exposures from small samples using physiologically based pharmacokinetic models and multiple biomarkers.
This study examines the use of physiologically based pharmacokinetic (PBPK) models for inferring exposure when the number of biomarker observations per individual is limited, as commonly occurs in population exposure surveys. The trade-off between sampling multiple biomarkers at a specific time versus fewer biomarkers at multiple time points was investigated, using a simulation-based approach based on a revised and updated chlorpyrifos PBPK model originally published. Two routes of exposure, oral and dermal, were studied as were varying levels of analytic measurement error. It is found that adding an additional biomarker at a given time point adds substantial additional information to the analysis, although not as much as the addition of another sampling time. Furthermore, the precision of the estimates of exposed dose scaled approximately with the analytic precision of the biomarker measurement. For acute exposure scenarios such as those considered here, the results of this study suggest that the number of biomarkers can be balanced against the number of sampling times to obtain the most efficient estimator after consideration of cost, intrusiveness, and other relevant factors.
Mosquin
Paul L
PL
RTI International, Research Triangle Park, North Carolina, USA.
Licata
Amy Collins
AC
Liu
Bing
B
Sumner
Susan C J
SC
Okino
Miles S
MS
D015415:Biomarkers / Q000097:blood / Q000378:metabolism* / Q000652:urine; D004390:Chlorpyrifos / Q000097:blood / Q000493:pharmacokinetics* / Q000652:urine; D006801:Humans; D007306:Insecticides / Q000097:blood / Q000493:pharmacokinetics* / Q000652:urine; D016013:Likelihood Functions; D008962:Models, Theoretical; D015203:Reproducibility of Results
D015415:Biomarkers; D007306:Insecticides; D004390:Chlorpyrifos