Scaling Factor Variability and Toxicokinetic Outcomes in Children
Citation:
Kenyon, E., R. Pegram, AND R. Hines. Scaling Factor Variability and Toxicokinetic Outcomes in Children. Childrens Environmental Health Network Research Conference, Washington, DC, April 05 - 07, 2017.
Impact/Purpose:
Our initial findings suggest the need to evaluate age-dependency of variation in scaling factors used for in vitro to in vivo extrapolation of biotransformation rates. In particular, further analyses of specific-age groups, especially neonates and exposure of the fetus due to maternal exposure encompassing periods of “hypervariability” in development of biotransformation enzymes is warranted. Such analyses can provide a through and systematic understanding of the basis for variability in pharmacokinetics due to age-dependent differences in maturation of biotransformation enzymes.
Description:
Abstract title: Scaling Factor Variability and Toxicokinetic Outcomes in ChildrenBackgroundBiotransformation rates (Vmax) extrapolated from in vitro data are used increasingly in human physiologically based pharmacokinetic (PBPK) models. PBPK models are widely used in human health risk assessment to provide an integrated estimate of internal dose from multiple exposure pathways. Extrapolation of Vmax from in vitro data requires use of scaling factors, including mg of microsomal protein/g liver (MPPGL), nmol of cytochrome P450 form/g liver (CYP) and liver volume fraction (FVL).Objective Previous analyses indicated that variability in scaling factors can have a large effect on measures of internal dose that are both exposure route-dependent, and dose metric-dependent in adult populations for the drinking water disinfection byproduct (DBP), bromodichloromethane (BDCM). Because lifetime exposure to DBPs is an important public health concern, we have extended this analysis to pediatric populations.Strategy/Methodology Our multi-route BDCM PBPK model (oral, dermal, inhalation) was re-parameterized for a 10 kg child and Monte Carlo analysis was used to assess the impact of variation in pediatric scaling factors on model-derived estimates of internal dose, which was compared with findings from a similar analysis conducted using our adult BDCM PBPK model. BDCM dose metrics, including venous blood concentration (CV), area under the curve (AUCv), and amount metabolized in liver (AML) were estimated following a single 0.05 liter drink of water or a 20 minute bath, under typical (5 ppb) and plausible higher level (20 ppb) BDCM water concentrations for each exposure scenario. MPPGL, CYP and FVL values used in the pediatric analysis reflect the range of values reported for pediatric populations (3 months to 3 years).ResultsThe impact of variability in scaling factors on variation in internal dose estimates was different for oral versus bathing exposure, but similar for each BDCM water concentration. When the bathing scenario was modeled, scaling factor variability produced differences between maximum and minimum values of all dose metrics of ~ 2-fold. For oral exposure, differences were approximately 30-fold in AUCv and CV, but only 1.5-fold in AML. The small change in AML is attributable to metabolism not being saturated at these exposure levels. For a similar analysis conducted using the adult PBPK model and adult scaling factor values, variation in dose metrics was less than 10% for the bathing scenario and for the oral scenario, ~15-fold for CV and AUCv, and less than 5% for AML.Conclusions and Next StepsOur initial findings suggest the need to evaluate age-dependency of variation in scaling factors used for in vitro to in vivo extrapolation of biotransformation rates. In particular, further analyses of specific-age groups, especially neonates and exposure of the fetus due to maternal exposure encompassing periods of “hypervariability” in development of biotransformation enzymes is warranted. Such analyses can provide a through and systematic understanding of the basis for variability in pharmacokinetics due to age-dependent differences in maturation of biotransformation enzymes.AcknowledgementsThis abstract does not reflect U.S. EPA policy. We appreciate valuable advice and consultation provided by John C. Lipscomb of the U.S. EPA, National Homeland Security Research Center, Cincinnati, OH.