Bococizumab is a humanized monoclonal antibody binding proprotein convertase subtilisin/kexin type 9, which may be a potential therapeutic option for reducing low-density lipoprotein cholesterol (LDL-C) levels in patients with hypercholesterolemia. In this 24-week, multicenter, double-blind, placebo-controlled, dose-ranging study (NCT01592240), subjects with LDL-C levels≥80 mg/dl on stable statin therapy were randomized to Q14 days subcutaneous placebo or bococizumab 50, 100, or 150 mg or Q28 days subcutaneous placebo or bococizumab 200 or 300 mg. Doses of bococizumab were reduced if LDL-C levels persistently decreased to ≤25 mg/dl. The primary end point was the absolute change in LDL-C levels from baseline to week 12 after placebo or bococizumab administration. Continuation of bococizumab administration through to week 24 enabled the collection of safety data over an extended period. Of the 354 subjects randomized, 351 received treatment (placebo [n=100] or bococizumab [n=251]). The most efficacious bococizumab doses were 150 mg Q14 days and 300 mg Q28 days. Compared with placebo, bococizumab 150 mg Q14 days reduced LDL-C at week 12 by 53.4 mg/dl and bococizumab 300 mg Q28 days reduced LDL-C by 44.9 mg/dl; this was despite dose reductions in 32.5% and 34.2% of subjects at week 10 or 8, respectively. Pharmacokinetic/pharmacodynamic model-based simulation assuming no dose reductions predicted that bococizumab would lower LDL-C levels by 72.2 and 55.4 mg/dl, respectively. Adverse events were similar across placebo and bococizumab groups. Few subjects (n=7; 2%) discontinued treatment because of treatment-related adverse events. In conclusion, bococizumab significantly reduced LDL-C across all doses despite dose reductions in many subjects. Model-based simulations predicted greater LDL-C reduction in the absence of bococizumab dose reduction. The Q14 days regimen is being evaluated in phase 3 clinical trials.
1. An equal-dose combination of tiletamine and zolazepam (Telazol®) is used as a veterinary anesthetic. There also have been reports of human abuse of Telazol®. The pharmacokinetics and metabolic fate of tiletamine and zolazepam and the rationale for their administration as an equal-dose combination are unclear. 2. The single-dose pharmacokinetics of intramuscular tiletamine and zolazepam (3 mg/kg each) in 16 Yorkshire-crossbred pigs were determined. The metabolites of tiletamine and zolazepam in pig plasma and urine were identified by mass spectrometry. The metabolic stability of tiletamine and zolazepam and the kinetics of formation of their metabolites by pig- and human-liver microsomes were determined. 3. Higher concentrations of zolazepam were observed in pig plasma and it was cleared more slowly compared to tiletamine (apparent clearance: 11 versus 134 l/h; half-life: 2.76 versus 1.97 h). Three metabolites of zolazepam and one metabolite of tiletamine were identified in pig urine, plasma and in microsomal incubations. In vitro formation of each of these metabolites in microsomes was biphasic involving a high-affinity/low-capacity and a low-affinity/high-capacity enzyme. The in vitro metabolic stability of tiletamine was considerably lower compared to zolazepam. 4. These results collectively point to major pharmacokinetic and metabolic differences between the two components of this fixed-dose anesthetic combination.
Mixture models are applied in population pharmacometrics to characterize underlying population distributions that are not adequately approximated by a single normal or lognormal distribution. In addition to obtaining individualized maximum a posteriori Bayesian post hoc parameter estimates, the subpopulation to which an individual was classified can be determined. However, the accuracy of the classification of subjects to subpopulations is not well studied. We investigated the impact of several factors on the accuracy of classification in mixture models applied to pharmacokinetics using a simulation strategy. The availability of actual subject data allowed us to evaluate mixture model classification in a potentially common application, namely, the classification of clearance into poor metabolizer (PM) or extensive metabolizer (EM) subgroups with the known phenotype status in subjects receiving metoprolol. The factors explored in the simulation study were the magnitude of difference between the clearances in two subpopulations, the between subject variability in clearance, the mixing-fraction, and the population sample size. Populations were simulated at various levels of the above factors and analyzed with a mixture model using NONMEM. The population pharmacokinetics of metoprolol were modeled with the EM/PM phenotype as a known covariate, and without the phenotype covariate using a mixture model. Within the range of scenarios studied, the proportion of subjects classified into the correct subpopulation was high. The simulation-estimation study suggests that a greater separation between two subpopulations, a smaller variability in the parameter distribution, a larger sample size, and a smaller size subpopulation tend to be associated with a greater accuracy of subpopulation classification when a mixture model is applied to pharmacokinetic data. In a population pharmacokinetic analysis of metoprolol, a drug that undergoes polymorphic metabolism, it was possible to correctly identify phenotype status using a mixture model.
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