Effect of Vorapaxar Alone and in Combination with Aspirin on Bleeding Time and Platelet Aggregation in Healthy Adult Subjects.

The effect of the protease-activated receptor-1 (PAR-1) antagonist vorapaxar on human bleeding time is not known. This was a randomized, two-period, open-label trial in healthy men (n = 31) and women (n = 5). In period 1, subjects received 81 mg aspirin q.d. or a vorapaxar regimen achieving steady-state plasma concentrations equivalent to chronic 2.5 mg q.d. doses, for 7 days. In period 2, each group added 7 days of the therapy alternate to that of period 1 without washout. Bleeding time and platelet aggregation using arachidonic acid, ADP, and TRAP agonists were assessed. Bleeding time geometric mean ratio (90% CI) for vorapaxar/baseline was 1.01 (0.88-1.15), aspirin/baseline was 1.32 (1.15-1.51), vorapaxar + aspirin/vorapaxar was 1.47 (1.26-1.70), and vorapaxar + aspirin/aspirin was 1.12 (0.96-1.30). Unlike aspirin, vorapaxar did not prolong bleeding time compared with baseline. Bleeding time following administration of vorapaxar with aspirin was similar to that following aspirin alone

Population pharmacokinetic studies in pediatrics: Issues in design and analysis

The current review addresses the following 3 frequently encountered challenges in the design and analysis of population pharmacokinetic studies in pediatrics: (1) body size adjustments during the development of pharmacostatistical models, (2) design and validation of limited sampling strategies, and (3) the integration of historical priors in data analysis and trial simulation. Size adjustments with empiric approaches based on body weight or body surface area have frequently proven as a pragmatic tool to overcome large size differences in a pediatric study population. Allometric size adjustments, however, provide a more mechanistic, physiologically based approach that, if used a priori, allows delineation of the effect of size from that of other covariates that show a high degree of collinearity. The frequent lack of dense data sets in pediatric clinical pharmacology because of ethical and logistic constraints in study design can be overcome with the application of D-optimality-based limited sampling schemes in combination with Bayesian and nonlinear mixed-effects modeling approaches. Empirically based dose selection and clinical trial designs for pediatric clinical pharmacology studies can be improved by applying clinical trial simulation techniques, especially if they integrate adult and pediatric in vitro and/or in vivo data as historic priors. Although integration of these concepts and techniques in population pharmacokinetic analyses is not only limited to pediatric research, their application allows researchers to overcome some major hurdles frequently encountered in pharmacokinetic studies in pediatrics and, thus, provides the basis for additional clinical pharmacology research in this previously insufficiently studied fraction of the general population