Yucheng Sheng

Race differences: modeling the pharmacodynamics of rosuvastatin in Western and Asian hypercholesterolemia patients

Aim:To evaluate race differences in the pharmacodynamics of rosuvastatin in Western and Asian hypercholesterolemia patients using a population pharmacodynamic (PPD) model generated and validated using published clinical efficacy trials.Methods:Published studies randomized trials with rosuvastatin treatment for at least 4 weeks in hypercholesterolemia patients were used for model building and validation. Population pharmacodynamic analyses were performed to describe the dose-response relationship with the mean values of LDL-C reduction (%) from dose-ranging trials using NONMEM software. Baseline LDL-C and race were analyzed as the potential covariates. Model robustness was evaluated using the bootstrap method and the data-splitting method, and Monte Carlo simulation was performed to assess the predictive performance of the PPD model with the mean effects from the one-dose trials.Results:Of the 36 eligible trials, 14 dose-ranging trials were used in model development and 22 one-dose trials were used for model prediction. The dose-response of rosuvastatin was successfully described by a simple Emax model with a fixed E0, which provided a common Emax and an approximate twofold difference in ED50 for Westerners and Asians. The PPD model was demonstrated to be stable and predictive.Conclusion:The race differences in the pharmacodynamics of rosuvastatin are consistent with those observed in the pharmacokinetics of the drug, confirming that there is no significant difference in the exposure-response relationship for LDL-C reduction between Westerners and Asians. The study suggests that for a new compound with a mechanism of action similar to that of rosuvastatin, its efficacy in Western populations plus its pharmacokinetics in bridging studies in Asian populations may be used to support a registration of the new compound in Asian countries.

Systematic evaluation of non-inferiority and equivalence randomized trials of anti-infective drugs

The non-inferiority (NI) and equivalence (EQ) design is used widely in the clinical trials of anti-infective drugs, but still many arguments for, and against, conducting active control NI/EQ trials rather than simple placebo controlled trials. We searched Pubmed database and conducted a systematic literature review (1992–2011) to assess the methodological aspects of NI and EQ randomized trials of anti-infective drugs. A total of 335 publications with 337 trials were included. Of them, 235 trials reported a pre-specified margin of 10–15%. A proportion (e.g., cure, successful, failure) was used as the primary outcome in 316 trials (93.8%). Test treatments were non-inferior or equivalent to the control treatment in 325 trials (93.4%). The historical evidence for the effect of the control drug was specified in 38 trials (11.3%). For the literature of NI/EQ trials in anti-infective treatment, aspects that need improvement include the description of study participation, trial implementation, historical evidence and endpoint for the efficacy of control, inclusion of flow diagrams and figures that present margins and confidence intervals according to CONSORT criteria.

Pharmacokinetics and its relation to toxicity of pegylated-liposomal doxorubicin in Chinese patients with breast tumours.

Objectives:  Pegylated liposomal doxorubicin (PLD) is a formulation of doxorubicin encapsulated with polyethylene glycol‐coated liposomes, which has prolonged circulation time and unique toxicity profile. This study deals with the pharmacokinetics and its relation to toxicity in Chinese patients with breast tumours.

Systematic evaluation of dose accumulation studies in clinical pharmacokinetics.

The amount of drug remaining after previous doses, or drug accumulation, is closely related to drug efficacy and safety. An accurate calculation of the accumulation index or ratio (R(ac)) is crucial for dose finding. However, in drug accumulation studies little consensus exists with regard to experimental design or data analysis. We conducted a systematic review of the literature to produce a detailed profile of drug accumulation studies of the last 30 years (1980-2011). Ninety-six articles comprising 122 studies were analyzed. A typical drug accumulation study enrolled 10 to 20 subjects randomly assigned into treatment groups of 1 or 2 dose levels to observe pharmacokinetic behaviors. The median washout period between single and multiple dosing was 7 days, and the dose interval was 1-2 elimination half-lives in non- or one-compartmental models. Generally, the number of repeated times of administration for multiple dosing was 7-14, and the median number of sampling time points was 11. Eight different methods were used to calculate R(ac). The most frequently used method, in 72.9% of the studies, was to set R(ac) equal to the ratio of the area under a plasma concentration-time curve (AUC) during a dosage interval at steady state to the AUC of a dosage interval after the first dose, i.e., R(ac) = AUC(0-τ,ss) / AUC(0-τ,1). The values of R(ac) in the included studies ranged from 0.85 to 18.8, and 68.03% were <2. We suggest that sample size estimation for an accumulation study should be similar to that of a bioequivalence study, and in most studies, 18-24 subjects will be needed. Appropriate calculation methods for R(ac) should be selected based on the experimental design and data characteristics. The crucial values for non-, weak, moderate, and strong accumulation can be set at R(ac) < 1.2, 1.2 ≤ R(ac) < 2, 2 ≤ R(ac) < 5, and R(ac) ≥ 5, respectively. Accumulations studies should also give more regard to drug metabolism and increased accumulation in kidney or liver damaged patients.

Systematic evaluation of dose proportionality studies in clinical pharmacokinetics.

An understanding of dose proportionality is essential in drug development, and the results are of great clinical importance for predicting the effects of dose adjustments. However, little consensus exists with regard to study design and analysis. The aim of this paper was to produce a detailed profile of the information on dose proportionality studies in the last 10 years and to provide a foundation for reflection and debate on future priorities. A total of 147 publications comprising 156 studies were analyzed. The typical dose proportionality study enrolled 20 to 30 subjects and randomly allocated them into 3 to 4 dose levels to investigate pharmacokinetic behaviors within a dose ratio range of 2-6. The most common design was the crossover experiment (52.6%), and evaluating dose-adjusted pharmacokinetic parameters followed by hypothesis testing (43%) was the most frequent statistical approach. However, the alternative crossover design and equivalence criterion based on the power model represented only 4% and 8% of studies, respectively. The power model as a recommendable empirical relationship to assess dose proportionality was applied in 25 (16%) studies. This research suggests that the alternative crossover design and power model statistical method should be attracting more attention in order to obtain more information in studies with limited subjects.

Random sparse sampling strategy using stochastic simulation and estimation for a population pharmacokinetic study

The purpose of this study was to use the stochastic simulation and estimation method to evaluate the effects of sample size and the number of samples per individual on the model development and evaluation. The pharmacokinetic parameters and inter- and intra-individual variation were obtained from a population pharmacokinetic model of clinical trials of amlodipine. Stochastic simulation and estimation were performed to evaluate the efficiencies of different sparse sampling scenarios to estimate the compartment model. Simulated data were generated a 1000 times and three candidate models were used to fit the 1000 data sets. Fifty-five kinds of sparse sampling scenarios were investigated and compared. The results showed that, 60 samples with three points and 20 samples with five points are recommended, and the quantitative methodology of stochastic simulation and estimation is valuable for efficiently estimating the compartment model and can be used for other similar model development and evaluation approaches.

A cyclic fluctuation model for 24-h ambulatory blood pressure monitoring in Chinese patients with mild to moderate hypertension

Aim:The conventional method for analyzing 24-h ambulatory blood pressure monitoring (24-h ABPM) is insufficient to deal with the large amount of data collected. The aim of this study was to develop a novel cyclic fluctuation model for 24-h ABPM in Chinese patients with mild to moderate hypertension.Methods:The data were obtained from 4 independent antihypertensive drug clinical trials in Chinese patients with mild to moderate hypertension. The measurements of 24-h ABPM at the end of the placebo run-in period in study 1 were used to develop the cyclic fluctuation model. After evaluated, the structural model was used to analyze the measurements in the other 3 studies. Models were fitted using NONMEM software.Results:The cyclic fluctuation model, which consisted of 2 cosine functions with fixed-effect parameters for rhythm-adjusted 24-h mean blood pressure, amplitude and phase shift, successfully described the blood pressure measurements of study 1. Model robustness was validated by the bootstrap method. The measurements in the other 3 studies were well described by the same structural model. Moreover, the parameters from all the 4 studies were very similar. Visual predictive checks demonstrated that the cyclic fluctuation model could predict the blood pressure fluctuations in the 4 studies.Conclusion:The cyclic fluctuation model for 24-h ABPM deepens our understanding of blood pressure variability, which will be beneficial for drug development and individual therapy in hypertensive patients.