Evaluation of child/adult pharmacokinetic differences from a database derived from the therapeutic drug literature
- PMID: 11896285
- DOI: 10.1093/toxsci/66.2.185
Evaluation of child/adult pharmacokinetic differences from a database derived from the therapeutic drug literature
Abstract
Pharmacokinetics (PK) of xenobiotics can differ widely between children and adults due to physiological differences and the immaturity of enzyme systems and clearance mechanisms. This makes extrapolation of adult dosimetry estimates to children uncertain, especially at early postnatal ages. While there is very little PK data for environmental toxicants in children, there is a wealth of such data for therapeutic drugs. Using published literature, a Children's PK Database has been compiled which compares PK parameters between children and adults for 45 drugs. This has enabled comparison of child and adult PK function across a number of cytochrome P450 (CYP) pathways, as well as certain Phase II conjugation reactions and renal elimination. These comparisons indicate that premature and full-term neonates tend to have 3 to 9 times longer half-life than adults for the drugs included in the database. This difference disappears by 2-6 months of age. Beyond this age, half-life can be shorter than in adults for specific drugs and pathways. The range of neonate/adult half-life ratios exceeds the 3.16-fold factor commonly ascribed to interindividual PK variability. Thus, this uncertainty factor may not be adequate for certain chemicals in the early postnatal period. The current findings present a PK developmental profile that is relevant to environmental toxicants metabolized and cleared by the pathways represented in the current database. The manner in which this PK information can be applied to the risk assessment of children includes several different approaches: qualitative (e.g., enhanced discussion of uncertainties), semiquantitative (age group-specific adjustment factors), and quantitative (estimation of internal dosimetry in children via physiologically based PK modeling).
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