Yu-peng Ren

Application of Model-Based Methods to Characterize Exenatide-Loaded Double-Walled Microspheres: In Vivo Release, Pharmacokinetic/Pharmacodynamic Model, and In Vitro and In Vivo Correlation

The objective of this study was to characterize exenatide double-walled microspheres (DWMS) using model-based methods. Exenatide DWMS were prepared using oil-in-oil-in-water method, and physicochemical characterization and in vitro release and degradation of DWMS were evaluated. The pharmacokinetics (PK) and pharmacodynamics (PD) were investigated after subcutaneous injection to diabetic rats. Transit compartment model was used to describe the in vivo release of exenatide from DWMS successfully. On the basis of the insulinotropic effects of exenatide and hypoglycemic effects of insulin, PK/PD model was developed and nicely described the concentration-effect relationship of exenatide. Moreover, on the basis of the transit compartment model, a simulation method was applied to predict in vivo release, and in vitro and in vivo correlation was established. In conclusion, DWMS was a promising vehicle for delivery of exenatide, and the proposed PK/PD model allowed a better understanding of the pharmacological properties of exenatide DWMS. Transit compartment model-based modeling and simulation methods provided more options for the description and prediction of the in vivo exenatide release from DWMS.

Pharmacokinetic/pharmacodynamic studies on exenatide in diabetic rats.

Aim:To quantitatively evaluate the blood glucose-lowering effect of exenatide in diabetic rats.Methods:Male Harlan-Sprague-Dawley rats were treated with high-fat diet/streptozotocin to induce type 2 diabetes. After subcutaneous administration of a single dose of exenatide (4.2, 42, or 210 μg/kg), serum exenatide, insulin concentration and blood glucose were measured. The pharmacokinetics of exenatide was characterized by a two-compartment model with first-order absorption. Insulin turnover was characterized by an effect compartment and indirect response combined model. Glucose turnover was described using an indirect response model with insulin (in effect compartment) stimulating glucose disposition and insulin (in insulin compartment) inhibiting glucose production simultaneously. The model parameters were estimated using nonlinear mixed-effects model program. Visual predictive check and model evaluation were used to make assessments.Results:Exenatide exhibited rapid absorption with ka=4.45 h-1, and the two-compartment model well described its pharmacokinetic profile. For the pharmacodynamic model, exenatide increased insulin release with the estimated Sm1 of 0.822 and SC50 of 4.02 μg/L. It was demonstrated that insulin stimulated glucose dissipation (Sm2=0.0513) and inhibited the production of glucose (Im=0.0381). Visual predictive check and model evaluation study indicated that a credible model was developed.Conclusion:The glucose-lowering effect of exenatide in diabetic rats is reliably described and predicted by the combined effect compartment/indirect response model.

Population pharmacokinetics of clozapine and its primary metabolite norclozapine in Chinese patients with schizophrenia

Aim:To develop a combined population pharmacokinetic model (PPK) to assess the magnitude and variability of exposure to both clozapine and its primary metabolite norclozapine in Chinese patients with refractory schizophrenia via sparse sampling with a focus on the effects of covariates on the pharmacokinetic parameters.Methods:Relevant patient concentration data (eg, demographic data, medication history, dosage regimen, time of last dose, sampling time, concentrations of clozapine and norclozapine, etc) were collected using a standardized data collection form. The demographic characteristics of the patients, including sex, age, weight, body surface area, smoking status, and information on concomitant medications as well as biochemical and hematological test results were recorded. Persons who had smoked 5 or more cigarettes per day within the last week were defined as smokers. The concentrations of clozapine and norclozapine were measured using a HPLC system equipped with a UV detector. PPK analysis was performed using NONMEM. Age, weight, sex, and smoking status were evaluated as main covariates. The model was internally validated using normalized prediction distribution errors.Results:A total of 809 clozapine concentration data sets and 808 norclozapine concentration data sets from 162 inpatients (74 males, 88 females) at multiple mental health sites in China were included. The one-compartment pharmacokinetic model with mixture error could best describe the concentration-time profiles of clozapine and norclozapine. The population-predicted clearance of clozapine and norclozapine in female nonsmokers were 21.9 and 32.7 L/h, respectively. The population-predicted volumes of distribution for clozapine and norclozapine were 526 and 624 L, respectively. Smoking was significantly associated with increases in the clearance (clozapine by 45%; norclozapine by 54.3%). The clearance was significantly greater in males than in females (clozapine by 20.8%; norclozapine by 24.2%). The clearance of clozapine and norclozapine did not differ significantly between Chinese patients and American patients.Conclusion:Smoking and male were significantly associated with a lower exposure to clozapine and norclozapine due to higher clearance. This model can be used in individualized drug dosing and therapeutic drug monitoring.

Semi-Mechanism-Based Pharmacokinetic/Pharmacodynamic Model for the Combination Use of Dexamethasone and Gemcitabine in Breast Cancer

Our study aimed at the investigation of in vivo anticancer effect of the combination use of dexamethasone (DEX) and gemcitabine (GM) as well as the development of pharmacokinetic/pharmacodynamic (PK/PD) models in MCF-7 xenograft model. Further, simulations were conducted to optimize doses and administration schedules. The inhibitory effect of different doses and administration schedules were investigated in MCF-7 xenograft model. Semi-mechanism-based PK/PD models were established based on the preclinical data to characterize the relationship between plasma concentration and the time course of the drug response quantitatively. The PK/PD models were further applied to predict and optimize doses and administration schedules, which would lead to tumor stasis by the end of the treatment. Synergistic effect was observed in the PD study in vivo and further confirmed by the estimated combination index ψ obtained from PK/PD models. The optimum dose regimen was selected as DEX 2 mg/kg, qd and GM 10 mg/kg, q2d based on the simulation results. In summary, the PD interaction between DEX and GM was demonstrated as synergism by both experimental results and modeling approach. Dosage regimens were optimized as predicted by modeling and simulations, which would provide reference for preclinical study and translational research as well.

A population pharmacokinetic study of tacrolimus in healthy Chinese volunteers and liver transplant patients

Aim:To develop a population pharmacokinetic (PopPK) model of tacrolimus in healthy Chinese volunteers and liver transplant recipients for investigating the difference between the populations, and for potential individualized medication.Methods:A set of 1100 sparse trough concentration data points from 112 orthotopic liver transplant recipients, as well as 851 dense data points from 40 healthy volunteers receiving a single dose of tacrolimus (2 mg, po) were collected. PopPK model of tacrolimus was constructed using the program NONMEM. Related covariates such as age, hepatic and renal functions that were potentially associated with tacrolimus disposition were evaluated. The final model was validated using bootstrapping and a visual predictive check.Results:A two-compartment model of tacrolimus could best describe the data from the two populations. The final model including two covariates, population (liver transplant recipients or volunteers) and serum ALT (alanine aminotransferase) level, was verified and adequately described the pharmacokinetic characteristics of tacrolimus. The estimates of V2/F, Q/F and V3/F were 22.7 L, 76.3 L/h and 916 L, respectively. The estimated CL/F in the volunteers and liver transplant recipients was 32.8 and 18.4 L/h, respectively. Serum ALT level was inversely related to CL/F, whereas age did not influence CL/F. Thus, the elderly (≥65 years) and adult (<65 years) groups in the liver transplant recipients showed no significant difference in the clearance of tacrolimus.Conclusion:Compared with using the sparse data only, the integrating modeling technique combining sparse data from the patients and dense data from the healthy volunteers improved the PopPK analysis of tacrolimus.

Population pharmacokinetic/pharmacodynamic model of clozapine for characterizing the relationship between accumulated exposure and PANSS scores in patients with schizophrenia.

Background: The aim of this study was to characterize the relationship between accumulated exposure of clozapine and changes in Positive and Negative Syndrome Scale (PANSS) score in Chinese patients with schizophrenia by pharmacokinetic/pharmacodynamic (PK/PD) modeling. Methods: Sparse clozapine PK data and PANSS scores were collected from 2 clinical studies of Chinese inpatients with schizophrenia. Two other rich PK data sets were included for more accurate assessment of clozapine PK characteristics. The relationship between clozapine-accumulated exposure and PANSS score was investigated using linear, log-linear, Emax, and sigmoid models, and each model was evaluated using visual predictive condition and normalized prediction distribution error methods. Simulations based on the final PK/PD model were preformed to investigate the effect of clozapine on PANSS scores under different dose regimens. Results: A total of 1391 blood clozapine concentrations from 198 subjects (180 patients and 18 healthy volunteers) and 576 PANSS scores from 137 patients were included for PK and PK/PD analysis. A first-order 2-compartment PK model with covariates gender and smoking status influencing systemic clearance adequately described the PK profile of clozapine. The decrease in total PANSS score during treatment was best characterized using cumulated clozapine area under the curve (AUC) data in the Emax model. The maximum decrease in PANSS during clozapine treatment (Emax) was 55.4%, and the cumulated AUC50 (cAUC50) required to attain half of Emax was 296 mg·L−1·h−1·d−1. The simulations demonstrated that the accelerated dose titration and constant dose regimens achieved a similar maximum drug response but with a slower relief of symptoms in dose titration regimen. Conclusions: The PK/PD model can describe the clinical response as measured by decreasing PANSS score during treatment and may be useful for optimizing the dose regimen for individual patients.

Antitumor effect of axitinib combined with dopamine and PK-PD modeling in the treatment of human breast cancer xenograft

Rising evidence has shown the development of resistance to vascular endothelial growth factor receptor (VEGFR) inhibitors in the practices of cancer therapy. It is reported that the efficacy of axitinib (AX), a VEGFR inhibitor, is limited in the treatment of breast cancer as a single agent or in combination with other chemotherapeutic drugs due to the probability of rising population of cancer stem-like cells (CSCs) caused by AX. The present study evaluated the effect of dopamine (DA) improving AX’s efficacy on MCF-7/ADR breast cancer in vitro and in vivo, and developed a pharmacokinetic-pharmacodynamic (PK-PD) model describing the in vivo experimental data and characterizing the interaction of effect between AX and DA. The results showed that AX up-regulated the expression of breast CSC (BCSC) markers (CD44+/CD24−/low) in vivo, and DA significantly synergized the inhibitory effect on tumor growth by deducting the BCSC frequency. The PK-PD model quantitatively confirmed the synergistic interaction with the parameter estimate of interaction factor ψ 2.43. The dose regimen was optimized as 60 mg/kg AX i.g. b.i.d. combined with 50 mg/kg DA i.p. q3d in the simulation study on the basis of the PK-PD model. The model where DA synergistically enhances the effect of AX in an all-or-none manner provides a possible solution in modeling the agents like DA. Moreover, the outcome of AX and DA combination therapy in MCF-7/ADR breast cancer provided further insight of co-administering DA in the treatment of the possible CSC-causing AX-resisting breast cancer. And this combination therapy has the prospect of clinical translation.

Integrated pharmacokinetic/viral dynamic model for daclatasvir/asunaprevir in treatment of patients with genotype 1 chronic hepatitis C

In order to develop an integrated pharmacokinetic/viral dynamic (PK/VD) model to predict long-term virological response rates to daclatasvir (DCV) and asunaprevir (ASV) combination therapy in patients infected with genotype 1 (GT1) chronic hepatitis C virus (HCV), a systematic publication search was conducted for DCV and ASV administered alone and/or in combination in healthy subjects or patients with GT1 HCV infection. On the basis of a constructed meta-database, an integrated PK/VD model was developed, which adequately described both DCV and ASV PK profiles and viral load time curves. The IC50 values of DCV and ASV were estimated to be 0.041 and 2.45 μg/L, respectively, in GT1A patients. A sigmoid Emax function was applied to describe the antiviral effects of DCV and ASV, depending on the drug concentrations in the effect compartment. An empirical exponential function revealed that IC50 changing over time described drug resistance in HCV GT1A patients during DCV or ASV monotherapy. Finally, the PK/VD model was evaluated externally by comparing the expected and observed virological response rates during and post-treatment with DCV and ASV combination therapy in HCV GT1B patients. Both the rates were in general agreement. Our PK/VD model provides a useful platform for the characterization of pharmacokinetic/pharmacodynamic relationships and the prediction of long-term virological response rates to aid future development of direct acting antiviral drugs.