Lujin Li

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.

Quantitative efficacy of soy isoflavones on menopausal hot flashes

AIM This study aimed to quantitate the efficacy of soy isoflavones in the treatment of menopausal hot flashes. METHODS Model based meta-analysis (MBMA) was used to quantitate the efficacy of soy isoflavones. We conducted a systemic literature search to build a time-effect model for placebo and soy isoflavones in treating menopausal hot flashes. Studies were identified, subjected to inclusion and exclusion criteria, and reviewed. RESULTS From 55 articles, 16 studies of soy isoflavones met the inclusion criteria, and contained 65 and 66 mean effect values in placebo and soy isoflavone groups, respectively, from about 1710 subjects. Interestingly, the developed model was found to describe adequately the time course of hot flashes reduction after administration of placebo and soy isoflavones. Using this model, we found that the maximal percentage change of hot flashes reduction by soy isoflavones was 25.2% after elimination of the placebo effect, accounting for 57% of the maximum effects of estradiol (Emax-estradiol  = 44.9%). However, a time interval of 13.4 weeks was needed for soy isoflavones to achieve half of its maximal effects, much longer than estradiol, which only required 3.09 weeks. These results suggest that treatment intervals of 12 weeks are too short for soy isoflavones, which require at least 48 weeks to achieve 80% of their maximum effects. CONCLUSIONS Soy isoflavones show slight and slow effects in attenuating menopausal hot flashes compared with estradiol.

Comparative efficacy of five long-term weight loss drugs: quantitative information for medication guidelines

Quantitative information is scarce in current obesity medication guidelines, and they do not clearly reflect the differences in the efficacy characteristics among various drugs. This study quantitatively assessed the efficacy characteristics of five FDA‐approved long‐term weight loss drugs. Potentially eligible studies were obtained from public databases. Using the differences in the weight change from baseline between the drug group and the corresponding placebo group as the major indicator of efficacy, a time‐effect model was established, and crucial pharmacodynamic parameters, such as the maximal efficacy, drug onset time and rate of body weight regain after the maximal efficacy point, were used to reflect the differences in efficacy among the five drugs. Finally, 50 reports (involving 43,443 participants) were included. After deducting the placebo effects, the maximal efficacies (95% CI) of orlistat (120 mg), lorcaserin, naltrexone–bupropion, phentermine–topiramate (PT, 7.5/46 mg) and liraglutide were −2.94 (−5.82, −1.27), −3.06 (−4.39, −1.71), −6.15 (−9.78, −3.25), −7.45 (−9.76, −3.88) and −5.50 (−10.62, −2.97) kg at weeks 60, 54, 67, 59 and 65 respectively, and their rates of body weight regain were 0.51, 0.48, 0.91, 1.27and 0.43 kg per year respectively. The 1‐year dropout rates of orlistat, lorcaserin, naltrexone‐bupropion, PT and liraglutide were 29.0, 40.9, 49.1, 34.9 and 24.3% respectively. In addition, a significant dose–effect correlation was observed for orlistat and PT. This study provides valid quantitative information for medication guidelines.

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.

Bioequivalence evaluation of two formulations of pidotimod using a limited sampling strategy

The aim of this study was to develop a limited sampling strategy (LSS) to assess the bioequivalence of two formulations of pidotimod. A randomized, two-way, cross-over study was conducted in healthy Chinese volunteers to compare two formulations of pidotimod. A limited sampling model was established using regression models to estimate the pharmacokinetic parameters and assess the bioequivalence of pidotimod. The model was internally validated by the Jack-knife method and graphical methods. The traditional non-compartmental method was also used to analyze the data and compared with LSS method. The results indicate that following oral administration of a single 800 mg dose, the plasma AUC(0-12 h) and C(max) of pidotimod can be predicted accurately using only two to four plasma samples. The bioequivalence assessment based on the LSS models provided results very similar to that obtained using all the observed concentration-time data points and indicate that the two pidotimod formulations were bioequivalent. A LSS method for assessing the bioequivalence of pidotimod formulations was established and proved to be applicable and accurate. This LSS method could be considered appropriate for a pidotimod bioequivalence study, providing an inexpensive cost of sampling acquisition and analysis. And the methodology presented here may also be applicable to bioequivalence evaluation of other medications.

Quantitative analysis of placebo response and factors associated with menopausal hot flashes

Objective: The aim of the study was to quantitatively analyze the placebo response and the factors associated with menopausal hot flashes. Methods: The PubMed and Cochrane Library databases were searched for placebo-controlled trials that reported the treatment of menopausal hot flashes, with a retrieval deadline of December 31, 2015. The clinical and demographic characteristics of participants and placebo responses, defined as the percentage of reduction in hot flashes at each observation time point compared with that of baseline values, were extracted from the studies. Model-based meta-analysis was used to describe the time course of placebo response and identify the related factors. Results: Eighty-five trials in 78 articles, involving 8,302 women, were included in the analysis. Of these, 47 trials were about hormonal drugs, 37 were about nonhormonal drugs, and 1 included both hormonal and nonhormonal drugs. Our results indicated that the placebo responses for hot flashes increased in a time-dependent manner and reached a plateau after week 12. Additionally, the placebo responses were significantly higher in the trials of hormonal drugs than in the trials of nonhormonal drugs at week 24 (−51.2% vs -40.4%; P < 0.05), and the difference between them was comparable with the effect of paroxetine. Conclusions: The placebo response for menopausal hot flashes was related to the active comparator; a higher response rate was observed in trials of hormonal drugs than in trials of nonhormonal drugs. These findings suggest that subjective expectations affect the treatment efficacy of menopausal hot flashes.

Population pharmacokinetics of rhTNFR-Fc in Chinese patients with rheumatic arthritis.

OBJECTIVE We aimed to investigate the population pharmacokinetics (PK) of soluble recombinant human tumor necrosis factor receptor fusion protein (rhTNFR- Fc) in Chinese patients with rheumatic arthritis (RA). The PK differences between Chinese patients with RA and healthy Chinese subjects were also compared. METHODS 40 patients were randomized to a single subcutaneous (SC) injections of 12.5 mg (n = 10), 25 mg (n = 10), and 50 mg (n = 10) of rhTNFR-Fc, and six SC injection of rhTNFR- Fc at 25 mg once in 3 days (n = 10) respectively. A total of 550 serum concentration data points were collected in the RA patients. The population PK analysis was performed by NONMEM. Based on the population PK parameters obtained herein and those reported in healthy Chinese subjects, simulation was conducted to compare the difference of rhTNFR-Fc exposure between these populations. RESULTS The PK data of Chinese patients with RA were best described by a one compartment model with lag time. A higher CL/F was noted in RA patients compared with that of the healthy Chinese subjects (1.64 L/h vs. 1.10 L/h), and a lower Ka was noticed in the RA patients compared with that of the healthy subjects (0.0317 h-1 vs. 0.0605 h-1). The simulate results showed that rhTNFR-Fc exposure in Chinese patients with RA was significantly lower than that in healthy subjects. The mean patients/healthy subjects C(max) and AUC(ss) ratios were 0.870 and 0.890, respectively. CONCLUSIONS A population PK model of rhTNFR- Fc was developed in Chinese patients with RA. Statistical difference was noted in the PK of rhTNFR-Fc between Chinese patients with RA and healthy Chinese subjects.

Population pharmacokinetics of adefovir dipivoxil tablets in healthy Chinese volunteers.

AIM To develop a population pharmacokinetic model of adefovir dipivoxil in healthy volunteers and evaluate the effect of individual factors on the pharmacokinetics of adefovir dipivoxil. METHODS Plasma concentration data collected from 32 healthy Chinese subjects in a Phase I clinical study was pooled. Subjects received a single oral dose of 10 mg, 20 mg, or 30 mg adefovir dipivoxil, or multiple doses of 10 mg once a day for 9 days. Plasma concentrations of adefovir dipivoxil were measured using a validated liquid chromatography-mass spectrometric method. A nonlinear mixed-effect model was used to analyze the plasma concentration data of adefovir dipivoxil in healthy volunteers and to calculate the relevant parameters as well as inter- and intra-individual variability. RESULTS The time course of adefovir dipivoxil concentration is best described by a first-order absorption and first-order elimination two-compartment model with lag time. The final estimate of total body clearance (CL) is 56.9 L/h and 78.7 L/h for single and multiple dosing regimen, respectively; the volume distribution of the central compartment (V2) is 106 L; inter-compartmental clearance (Q) is 220 L/h; volume distribution of the peripheral compartment (V3) is 498 L and 800 L for single and multiple dosing regimen, respectively; absorption rate is 0.509 h-1; and lag time is 0.315 hours. The inter-individual variabilities of CL and V2 were 22.4% and 58.9%, respectively. The proportional error of residual variability is 14.1% and the additive error is 0.30 ng/L. The final pharmacokinetic model was evaluated using a bootstrap method. CONCLUSIONS A nonlinear mixed effect model for oral adefovir dipivoxil formulations was developed in healthy Chinese subjects. A multiple dosing regimen may significantly increase the body clearance and volume distribution of the peripheral compartment compared to a single dosing regimen. *These authors contribute equally to this work.

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.

Model-based comparing efficacy of fluoxetine between elderly and non-elderly participants with major depressive disorder

BACKGROUND The high heterogeneity was existed among the studies of the elderly participants with major depressive disorder (MDD), which may lead to incorrect conclusions in the previous meta-analysis. This study used model based meta-analysis to compare the efficacy of fluoxetine between the elderly and non-elderly participants with MDD and to explain the heterogeneity among the studies. METHODS A comprehensive literature search was conducted in the public databases, involving utilization of fluoxetine for treating MDD in the acute-phase. The time-efficacy model was established based on the changes of the Hamilton Depression Rating Scale (HDRS) score compared to baseline level. The efficacy features and related factors of fluoxetine in the elderly participants were investigated by comparing with the non-elderly population. RESULTS Sixty-one studies encompassing 4058 participants were included in the analysis. We found the trial design of placebo controlled vs. comparator controlled was a significant impact factor for the efficacy of fluoxetine. The typical decrease rate of HDRS score in the elderly participants was strikingly lower than that of the non-elderly participants at week 8, with 39.9% vs. 49.1% in the placebo controlled trial and 46.5% vs. 57.2% in the comparator controlled trial. LIMITATION The efficacy of other antidepressants except fluoxetine in the elderly participants need to be explored in the future study. CONCLUSIONS The efficacy of fluoxetine in the elderly participants was lower than that of the non-elderly participants. The heterogeneity of the trial design should be distinguished when comparing the efficacy of antidepressants between the elderly and non-elderly MDD participants.