Clin Pharmacokinet
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Pharmacokinetics play an integral role in the pediatric drug development process. The determination of pharmacokinetic parameters, particularly clearance, in different age groups directly informs dosing strategies for subsequent efficacy trials. Allometric scaling for prediction of pediatric clearance from the observed clearance in adults has been used in this effort. Clinical trial simulation, a powerful tool used to inform clinical trial design, requires both an estimate of clearance along with an estimate of the expected pharmacokinetic variability. The standard deviations (SD) of individual clearance values for adults are typically used and may lead to inaccurate predictions by not taking into account the more widespread distribution of factors such as body weight in the pediatric population. The objective of this study was to assess the accuracy of allometric prediction of drug clearance as well as methods for predicting clearance variability in children 6 years of age and older. ⋯ Allometric scaling may be a useful tool during pediatric drug development to predict drug clearance and dosing requirements in children 6 years of age and older. A novel methodology is reported that employs virtual adult and pediatric populations and adult pharmacokinetic data to accurately predict clearance variability in specific pediatric subpopulations. This approach has important implications for both clinical trial simulations and sample size determination for pediatric pharmacokinetic studies.
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In almost 30 years since the introduction of HMG-CoA reductase inhibitors (statins), no other class of lipid modulators has entered the market. Elevation of high-density lipoprotein-cholesterol (HDL-C) via inhibiting cholesteryl ester transfer protein (CETP) is an attractive strategy for reducing the risk of cardiovascular events in high-risk patients. Transfer of triglyceride and cholesteryl ester (CE) between lipoproteins is mediated by CETP; thus inhibition of this pathway can increase the concentration of HDL-C. ⋯ In view of the heterogeneity in HDL particle size, charge, and composition, the mere concentration of HDL-C may not be a good surrogate marker for HDL functionality. Recent clinical studies have reported that increased HDL functionality inversely correlates with the development of atherosclerotic plaque. Future development of CETP inhibitors may therefore benefit from the use of biomarkers of HDL functionality.