IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v23y2003i1p117-142.html
   My bibliography  Save this article

Differences in Pharmacokinetics Between Children and Adults—II. Children's Variability in Drug Elimination Half‐Lives and in Some Parameters Needed for Physiologically‐Based Pharmacokinetic Modeling

Author

Listed:
  • Dale Hattis
  • Gary Ginsberg
  • Bob Sonawane
  • Susan Smolenski
  • Abel Russ
  • Mary Kozlak
  • Rob Goble

Abstract

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.

Suggested Citation

  • Dale Hattis & Gary Ginsberg & Bob Sonawane & Susan Smolenski & Abel Russ & Mary Kozlak & Rob Goble, 2003. "Differences in Pharmacokinetics Between Children and Adults—II. Children's Variability in Drug Elimination Half‐Lives and in Some Parameters Needed for Physiologically‐Based Pharmacokinetic Modeling," Risk Analysis, John Wiley & Sons, vol. 23(1), pages 117-142, February.
  • Handle: RePEc:wly:riskan:v:23:y:2003:i:1:p:117-142
    DOI: 10.1111/1539-6924.00295
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1539-6924.00295
    Download Restriction: no

    File URL: https://libkey.io/10.1111/1539-6924.00295?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Dale Hattis & Paul White & Paul Koch, 1993. "Uncertainties in Pharmacokinetic Modeling for Perchloroethylene: II. Comparison of Model Predictions with Data for a Variety of Different Parameters," Risk Analysis, John Wiley & Sons, vol. 13(6), pages 599-610, December.
    2. Dale Hattis & J Prerna Banati & Rob Goble & David E. Burmaster, 1999. "Human Interindividual Variability in Parameters Related to Health Risks," Risk Analysis, John Wiley & Sons, vol. 19(4), pages 711-726, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Leona H. Clark & R. Woodrow Setzer & Hugh A. Barton, 2004. "Framework for Evaluation of Physiologically‐Based Pharmacokinetic Models for Use in Safety or Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1697-1717, December.
    2. Hilko Van Der Voet & Wout Slob, 2007. "Integration of Probabilistic Exposure Assessment and Probabilistic Hazard Characterization," Risk Analysis, John Wiley & Sons, vol. 27(2), pages 351-371, April.
    3. Ramya Chari & Thomas A. Burke & Ronald H. White & Mary A. Fox, 2012. "Integrating Susceptibility into Environmental Policy: An Analysis of the National Ambient Air Quality Standard for Lead," IJERPH, MDPI, vol. 9(4), pages 1-20, March.
    4. Lorenz R. Rhomberg, 2010. "Uncertainty Factor Conundrums: What Lessons Should We Draw?," Risk Analysis, John Wiley & Sons, vol. 30(3), pages 349-352, March.
    5. Kimberly M. Thompson & John S. Evans, 1997. "The Value of Improved National Exposure Information for Perchloroethylene (Perc): A Case Study for Dry Cleaners," Risk Analysis, John Wiley & Sons, vol. 17(2), pages 253-271, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:riskan:v:23:y:2003:i:1:p:117-142. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.