The plasma protein binding of drugs, particularly those that are highly bound, may have significant clinical implications. Although protein binding is a major determinant of drug action, it is only one of a myriad of factors that influence drug disposition. The extent of protein binding is a function of drug and protein concentrations, the affinity constant for the drug-protein interaction and the number of protein binding sites per class of binding site. Age-related changes in protein binding are usually not clinically important in drug therapy. Albumin levels are generally decreased in the elderly, whereas alpha1-acid glycoprotein levels are not altered by age per se. Alterations in plasma protein binding that occur in the elderly are generally not attributed to age, but rather to physiological and pathophysiological changes or disease states that may occur more frequently in the elderly and most often account for altered protein binding. Age-related physiological changes, such as decreased renal function, decreased hepatic function and decreased cardiac output, generally produce more clinically significant alterations in drug disposition than that seen with alterations in drug plasma protein binding. An understanding of the inter-relationships between drug concentrations, protein binding, the physiology of aging, disease, pharmacokinetics and pharmacodynamics is necessary for effective therapeutic monitoring. Monitoring of unbound drug concentrations simplifies these relationships and provides the fundamental information needed for dosage regimen development and adjustment. Drug therapy in the elderly should be individualised taking into account all of these factors.
Background The purpose of this analysis was to investigate the influence of dose and key demographic parameters on the population pharmacokinetics (PPK) of rimonabant. Methods PK data were combined from 7 similar phase I studies consisting of 141 young healthy subjects (3874 observations), including 52 Japanese, 89 non Japanese, 8 female, 133 male, obese and non obese[body mass index (BMI): 18.2 ‐ 41.6 kg/m2, body weight: 50.4 ‐ 135 kg] and doses of 3 to 120 mg. Subjects received either a single dose or once‐daily doses for 21 days of rimonabant. The PPK model was developed using a non‐linear mixed effect model (WinNonMix, v2.0.1). Model verification was performed by an examination of the goodness of fit plots, mean weighted residuals and by estimation of the prediction error and its 95% confidence interval. Results Rimonabant PPK was described by a two‐compartment model in terms of volume (Vc/F and Vp/F) and clearance (CL/F and CLd/F) parameters with a first‐order absorption rate constant (ka) and a lag time (tlag). Individual parameter values were log‐normally distributed. The final model included significant relationship between BMI and Vp/F, between rimonabant dose and ka, Vc/F, CL/F, and Vp/F, and between dose regimen and tlag. No effect of race was observed. Conclusions BMI appears to be the major determinant of rimonabant PK within the doses used in phase III trials, reflecting extensive distribution in the peripheral target tissues. Clinical Pharmacology & Therapeutics (2005) 77, P43–P43; doi:
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