ISSN:
1539-6924
Source:
Blackwell Publishing Journal Backfiles 1879-2005
Topics:
Energy, Environment Protection, Nuclear Power Engineering
Notes:
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 high-weight/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 to 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.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1111/1539-6924.00295
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