In earlier work we assembled a database of classical pharmacokinetic parameters (e.g., elimination half-lives; volumes of distribution) in children and adults. These data were then analyzed to define mean differences between adults and children of various age groups. In this article, we first analyze the variability in half-life observations where individual data exist. The major findings are as follows. The age groups defined in the earlier analysis of arithmetic mean data (0-1 week premature; 0-1 week full term; 1 week to 2 months; 2-6 months; 6 months to 2 years; 2-12 years; and 12-18 years) are reasonable for depicting child/adult pharmacokinetic differences, but data for some of the earliest age groups are highly variable. The fraction of individual children's half-lives observed to exceed the adult mean half-life by more than the 3.2-fold uncertainty factor commonly attributed to interindividual pharmacokinetic variability is 27% (16/59) for the 0-1 week age group, and 19% (5/26) in the 1 week to 2 month age group, compared to 0/87 for all the other age groups combined between 2 months and 18 years. Children within specific age groups appear to differ from adults with respect to the amount of variability and the form of the distribution of half-lives across the population. The data indicate departure from simple unimodal distributions, particularly in the 1 week to 2 month age group, suggesting that key developmental steps affecting drug removal tend to occur in that period. Finally, in preparation for age-dependent physiologically-based pharmacokinetic modeling, nationally representative NHANES III data are analyzed for distributions of body size and fat content. The data from about age 3 to age 10 reveal important departures from simple unimodal distributional forms-in the direction suggesting a subpopulation of children that are markedly heavier than those in the major mode. For risk assessment modeling, this means that analysts will need to consider "mixed" distributions (e.g., two or more normal or log-normal modes) in which the proportions of children falling within the major versus highweight/fat modes in the mixture changes as a function of age. Biologically, the most natural interpretation of this is that these subpopulations represent children who have or have not yet received particular signals for change in growth pattern. These apparently distinct subpopulations would be expected to exhibit different disposition of xenobiotics, particularly those that are highly lipophilic and poorly metabolized.

Dietary exposure to acrylamide is common as a result of its formation during the cooking of carbohydrate foods. This leads to widespread human exposure in adults and children alike. Acrylamide is neurotoxic and is metabolized by cytochrome P-450 (CYP) 2E1 to a mutagenic epoxide, glycidamide. This article describes a modeling framework for assessing acrylamide and glycidamide dosimetry in rats and human adults and children. The challenges in building a physiologically based toxicokinetic (PBTK) model that is compatible with existing rat and human data are described, with an emphasis on calibration against the hemoglobin adduct database. This exploratory PBTK model was adapted to children by incorporating life-stage-specific parameters consistent with children's changing physiology and metabolic capacity for processes involved in acrylamide disposition in terms of CYP2E1, glutathione conjugation, and epoxide hydrolase. Monte Carlo analysis was used to simulate the distribution of internal doses to gain an initial understanding of the range of child/adult differences possible. This analysis suggests modest dosimetry differences between children and adults, with area-under-the-curve (AUC) doses for the 99th percentile child up to fivefold greater than the median adult for both acrylamide and glycidamide. Early life immaturities tended to exert a greater effect on acrylamide than glycidamide dosimetry because immaturities in CYP2E1 and glutathione counteract one another for glycidamide AUC, but both lead to greater acrylamide dose. The analysis points toward glutathione conjugation parameters as being particularly influential and uncertain in early life, making this a key area for future research.

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