Longitudinal model-based meta-analysis for survival probabilities in patients with castration-resistant prostate cancer.

PURPOSE: The aims of this longitudinal model-based meta-analysis (MBMA) were to indirectly compare the time courses of survival probabilities and to identify corresponding potential significant covariates across approved drugs in patients with castration-resistant prostate cancer (CRPC). METHODS: A systematic literature review for monotherapy studies in patients with CRPC was conducted up to August 8, 2018. The time courses of progression-free survival (PFS) and overall survival (OS) were fitted with parametric survival models. Covariate analyses were performed to determine the impact of treatment drugs, dosing regimens, and patient characteristics on the survival probabilities. Simulations were carried out to quantify the magnitude of covariate effects. RESULTS: A total of 146 studies including clinical trials and real-world data on longitudinal survival probabilities in 20,712 patients with CRPC were included in our meta-database. The time courses of PFS and OS probabilities were best described by the log-logistic model. There was no significant difference in median OS and PFS between docetaxel, cabazitaxel, abiraterone acetate, and enzalutamide. There was no significant dose-response relationship in PFS or OS for docetaxel at 50 to 120 mg/m2 every 3 weeks (Q3W) and cabazitaxel at 20 to 25 mg/m2 Q3W. Model-based simulations indicated that PFS probability was associated with chemotherapy, Gleason score, and baseline prostate-specific antigen (BLPSA), while OS probability was associated with chemotherapy, Gleason score, visceral metastasis, Eastern Cooperative Oncology Group performance status, and BLPSA. CONCLUSION: Our modeling and simulation framework can be applied to support indirect comparison, dose selection, and go/no-go decision-making for new agents targeting CRPC.

Population pharmacokinetics of vancomycin in Chinese patients with augmented renal clearance.

BACKGROUND: Augmented renal clearance (ARC) refers to enhanced renal elimination of circulating solute has attracted attention widely and in recent years increasing attention has been paid to patients with ARC. A population pharmacokinetic (PPK) analysis was performed to provide a reference for clinical individual therapy of vancomycin in in ARC patients. METHODS: Patients hospitalized in the First Affiliated Hospital of China Medical University from July 2013 to December 2015 and suspected or confirmed infection caused by gram-positive bacteria were enrolled in this study. The serum concentrations were determined by enzyme multiplied immunoassay technique. A nonlinear mixed effects model (NONMEM) was used to evaluate the influence of covariates on vancomycin pharmacokinetics and obtain the PPK model. Bootstrap, visual predictive checks and normalized prediction distribution errors were used to evaluate the estabolishe model. RESULTS: A total of 186 vancomycin serum samples from 95 patients, including 24 females and 71 males were studied. The final model was as follows: [Formula: see text] and [Formula: see text] . The final PPK model in ARC patients was proved to be robust and reliable. Age was identified as the most significant covariate in the final model. CONCLUSIONS: In this study, a simple population pharmacokinetic (PPK) model of vancomycin in Chinese patients with ARC was established using a nonlinear mixed-effects model (NONMEM). The final PPK model could achieve a good predictive effect, which provides a reference for clinical individual therapy.

The Evolution of Population Pharmacokinetic Model of Oral Phenytoin for Early Seizure Prophylaxis Post-Craniotomy.

BACKGROUND: This study aimed to re-establish a Population Pharmacokinetic (PPK) model of oral phenytoin to further optimize the individualized medication regimen based on our previous research. METHODS: Patients with intracranial malignant tumor requiring craniotomy were prospectively enrolled according to the inclusion criteria. Genotypes of CYP2C9*1 or *3 and CYP2C19*1, *2 or *3 were determined by real time PCR (TaqMan probe) method. Serum concentrations of phenytoin on the 4th and 7th day after oral administration were determined using fluorescence polarization immunoassay. The PPK parameters were estimated using Nonlinear Mixed Effects Models (NONMEM) and internal validation was performed using bootstraps. The predictive performance of the final model was evaluated by Normalized Predictive Distribution Errors (NPDEs) and diagnostic goodness- of-fit plots. RESULTS: A total of 390 serum samples were collected from 170 patients in PPK model building group. The population typical values for Vm, Km and the apparent volume of distribution (V) in the final model were 17.5 mg/h, 6.41 mg/L and 54.8 L, respectively. Internal validation by bootstraps showed that the final model was stable and reliable. NPDEs with a normal distribution and a scatterplot with symmetrical distribution showed that the final model had good predictive capability. Individualized dose regimens of additional 40 patients in the external validation group were designed by the present final PPK model. The percentages of patients with serum concentrations within the therapeutic range were 61.53% (24/39) on the 4th day and 94.87% (37/39) on the 7th day, which were higher than the 39.33% (59/150) and 52.10% (87/167) of above 170 patients (P < 0.0001). CONCLUSION: The present PPK final model for oral phenytoin may be used to further optimize phenytoin individualized dose regimen to prevent early seizure in patients after brain injury if patient characteristics meet those of the population studied.

Evaluation of potential surrogate endpoints for prediction of overall survival in patients with castration-resistant prostate cancer: trial-level meta-analysis.

PURPOSE: Overall survival (OS) has traditionally been the primary endpoint to evaluate drug efficiency in oncology but is often limited by the long observation period and high cost. The aims of this study were to perform a comprehensive meta-analysis at a clinical trial level to investigate the potential surrogate endpoints of OS in patients with castration-resistant prostate cancer (CRPC), and to predict OS based on the relationships associated with the potential surrogate endpoints. METHODS: A systematic literature search was conducted in the PubMed database up to August 2018. Correlations between OS and potential surrogate endpoints were determined by linear regression analysis weighted by the square roots of sample size. Simulations were conducted to assess the effect of covariates on the relationships between OS and surrogate endpoints. RESULTS: A total of 233 studies including clinical trials and real-world data were included in our dataset. The correlations between median OS and potential surrogate endpoints for androgen-targeting therapy (R2 = 0.58-0.92) were generally stronger than those for taxane chemotherapy (R2 = 0.37-0.71). Median radiographic progression-free survival (rPFS) showed the strongest correlations with median OS (R2 = 0.94) in patients treated with novel androgen-targeting therapy. CONCLUSION: The meta-analysis demonstrated that rPFS might serve as a potential surrogate endpoint of OS and offer opportunity to facilitate the interim analyses and decision-making during the early stage of clinical trials for androgen-targeting agents.

Development of a population pharmacokinetic model of olanzapine for Chinese health volunteers and patients with schizophrenia.

OBJECTIVE: Olanzapine is an atypical antipsychotic drug commonly used for the treatment of schizophrenia. However, there are still many complications associated with the use of olanzapine, and researchers continually strive to improve the handling of data from regular therapeutic drug monitoring (TDM). The objective of this study is to optimise the individualised treatment of olanzapine by establishing a population pharmacokinetics (PopPK) model in Chinese patients with schizophrenia. METHODS: This study integrates an extensive collection of concentration data from healthy volunteers after a single dose and a less extensive collection of samples from patients undergoing TDM. A PopPK model was developed using non-linear mixed-effects modelling. Potential covariates, including the olanzapine manufacturer and patient gender and age, were assessed during model development. A total of 616 plasma concentration levels from 22 healthy male individuals in China and 458 concentration levels from 112 male and 122 female patients with schizophrenia undergoing TDM at 12 hospitals in China were included in the analysis. The concentration profile could be best described using a two-compartment model with first-order absorption and elimination. RESULTS: The absorption rate (Ka) of olanzapine ranged from 2.85 h-1 to 5.39 h-1 for the different formulations. The typical absorption time delay was 0.877 hour. Body weight had a considerable effect on the apparent volume of the centre compartment and showed a power relationship. CONCLUSIONS: A PopPK model of olanzapine in Chinese patients with schizophrenia was developed in this study. After determining the PK parameters of olanzapine, the results suggested that body weight exhibited a considerable impact effect on VC/F. The impact of subjects and formulations requires further study. The PopPK model established in this study is likely to provide some information for the individualised therapy of olanzapine. TRIAL REGISTRATION NUMBER: ChiCTR-TRC-10000934; Results.

Influences of renal function descriptors on population pharmacokinetic modeling of vancomycin in Chinese adult patients.

Vancomycin, a glycopeptide antibiotic for the treatment of grampositive infections, is mainly eliminated via glomerular filtration. Thus, its therapeutic effects are affected predominantly by renal function. The aim of this study was to develop a population pharmacokinetic model of vancomycin for Chinese adult patients and to investigate the influence of different renal function descriptors on the predictability of the model. A retrospective analysis was performed based on the blood concentrations of vancomycin in 218 Chinese adult patients. Among these patients, the data from 160 were used to establish the population pharmacokinetic model, and the data from the remaining 58 patients were used for external model validation. A simulation was employed to determine the appropriate initial vancomycin dosage regimens in adult Chinese patients for reaching the target steady-state trough concentrations of 10-15 mg/L and 15-20 mg/L. We developed a one-compartment model with first-order absorption to characterize the concentration-time profile of vancomycin. There was a positive correlation between the body clearance of vancomycin and renal function; both creatinine clearance (CLCr) and age were the covariates that influenced the PK of vancomycin, and the excretion of vancomycin decreased as renal function diminishing with age. The typical clearance (CL) value was 2.829 L/h for 75-year-old patients with CLCr values of 80 mL/min, and the rate constant of CL with the CLCr changing at 1 mL/min was 0.00842. The influence coefficient of age on CL was 0.08143. The external validation results revealed that the current different descriptors of renal function behaved similarly to the predicted performance of the models. In conclusion, the developed model is appropriate for Bayesian dose predictions of vancomycin concentrations in the population of Chinese adult patients. Furthermore, the simulation provides a reference for clinical optimized antibacterial therapy with vancomycin.

Population pharmacokinetic models of lamotrigine in different age groups of Chinese children with epilepsy.

PURPOSE: The study aims to establish population pharmacokinetic (PPK) models of lamotrigine (LTG) in different age groups of epileptic children by nonlinear mixed effect modelling(NONMEM), and provide essential tools and theoretical basis for individualised optimal drug dose. METHODS: Cases of 473 epileptic children were divided into infant, toddler and preschool age (≤6 years) (n = 211), school age (6-12 years) (n = 171) and adolescence age (>12 years) (n = 81). A total of 625 steady-state serum trough concentration samples were extracted. The clinical information included demography, medication, serum concentration data and blood biochemical parameters. PPK models of LTG were established by NONMEM program, using first-order absorption and elimination. Demography and drug combination was investigated for influence on apparent clearance (CL) and apparent volume of distribution (Vd). To assess the accuracy and precision of the different ages and whole-age model, the mean prediction error (MPE), mean absolute error (MAE) and root mean squared error (RMSE) were compared. RESULTS: The final model of LTG in different ages stage and whole age was as follows: (1) infant, toddler and preschool age CL = 0.715 × [(WEIG/16.25)0.655] × (0.458VPA) × (1.99IND), V = 10.4; (2) school age CL(L/h) = 1.01 × (WEIG/30)0.399 × 0.465VPA × 1.98IND, Vd(L) = 17.7; (3) adolescence age CL(L/h) = 1.49 × (WEIG/51.5)0.509 × 0.498VPA × 1.7IND, Vd(L) = 23.1; (4) whole age CL = 0.945 × [(WEIG/25)0.645] × (0.463VPA) × (1.94IND), V = 16.7 × (WEIG/25)0.919 (WEIG, total body weight; VPA, combination with valproate, yes = 1, no = 0; IND, combination with enzyme inducer, yes = 1, no = 0). The values of MPE, MAE and RMSE in age-stage-specific models were less than the ones in the whole-age model, which suggests the age-stage-specific models have better precision and accuracy than the whole-age model. CONCLUSION: PPK models of LTG in different age groups of epileptic children were successfully established. Weight and combination therapy were identified as significant covariates on LTG clearance. Compared with the whole-age model, the age-specific models are more reliable.

Dose-biomarker-response modeling of the anticancer effect of ethaselen in a human non-small cell lung cancer xenograft mouse model.

Thioredoxin reductase (TrxR) is a component of several redox-sensitive signaling cascades that mediate important biological processes such as cell survival, maturation, growth, migration and inhibition of apoptosis. The expression levels of TrxR1 in some human carcinoma cell lines are nearly 10 times higher than those in normal cells. Ethaselen is a novel antitumor candidate that exerts potent inhibition on non-small cell lung cancer (NSCLC) by targeting TrxR. In this study we explored the relationship between the ethaselen dose and TrxR activity level and the relationship between TrxR degradation and tumor apoptosis in a human lung carcinoma A549 xenograft model. BALB/c nude mice implanted with human NSCLC cell line A54 were administered ethaselen (36, 72, 108 mg·kg-1·d-1, ig) or vehicle for 10 d. The tumor size and TrxR activity levels in tumor tissues were daily recorded and detected. Based on the experimental data, NONMEM 7.2 was used to develop an integrated dose-biomarker-response model for describing the quantitative relationship between ethaselen dose and tumor eradication effects. The time course of TrxR activity levels was modeled using an indirect response model (IDR model), in which the influence of the tumor growth rates on Kin with the linear correction factor γ1 (0.021 d/mm). The drug binding-inhibition effects on Kout was described using a sigmoidal Emax model with Smax (5.95), SC50 (136 mg/kg) and Hill's coefficient γ2 (2.29). The influence of TrxR activity inhibition on tumor eradication was characterized by an Emax model with an Emax (130 mm3/d) and EC50 (0.0676). This model was further validated using a visual predictive check (VPC) and was used to predict the efficacy of different doses. In conclusion, the properties and characteristics of ethaselen acting on TrxR degradation and subsequently resulting in tumor apoptosis are characterized by the IDR model and integrated dose-biomarker-response model with high goodness-of-fit and great predicative ability. This approach shed new light on the detailed processes and mechanism of ethaselen action and may offer a valuable reference for an appropriate dosing regimen for use in further clinical applications.

Pharmacokinetic-pharmacodynamic modeling of the antitumor effect of TM208 and EGFR-TKI resistance in human breast cancer xenograft mice.

AIM: The novel anticancer compound TM208 is an EGFR tyrosine kinase inhibitor (EGFR-TKI). Since the development of resistance to EGFR-TKIs is a major challenge in their clinical usage, we investigated the profiles of resistance following continuous treatment with TM208 in human breast cancer xenograft mice, and identified the relationship between the tumor pEGFR levels and tumor growth inhibition. METHODS: Female BALB/c nude mice were implanted with human breast cancer MCF-7 cells, and the xenograft mice received TM208 (50 or 150 mg·kg(-1)·d(-1), ig) or vehicle for 18 d. The pharmacokinetics (PK) and pharmacodynamics (PD) of TM208 were evaluated. RESULTS: The PK properties of TM208 were described by a one-compartment model with first-order absorption kinetics. Our study showed the inhibitory effects of TM208 on tumor pEGFR levels gradually reached a maximum effect, after which it became weaker over time, which was characterized by a combined tolerance/indirect response PD model with an estimated EC50 (55.9 µg/L), as well as three parameters ('a' of 27.2%, 'b' of 2730%, 'c' of 0.58 h(-1)) denoting the maximum, extent and rate of resistance, respectively. The relationship between the tumor pEGFR levels and tumor growth inhibition was characterized by a combined logistic tumor growth/transit compartment model with estimated parameters associated with tumor growth characteristics kng (0.282 day(-1)), drug potency kTM208 (0.0499 cm(3)/day) and the kinetics of tumor cell death k1 (0.141 day(-1)), which provided insight into drug mechanisms and behaviors. CONCLUSION: The proposed PK/PD model provides a better understanding of the pharmacological properties of TM208 in the treatment of breast cancer. Furthermore, simulation based on a tolerance model allows prediction of the occurrence of resistance.

Preclinical PK/PD model for combined administration of erlotinib and sunitinib in the treatment of A549 human NSCLC xenograft mice.

AIM: Combined therapy of EGFR TKI and VEGFR TKI may produce a greater therapeutic benefit and overcome EGFR TKI-induced resistance. However, a previous study shows that a combination of EGFR TKI erlotinib (ER) with VEGFR TKI sunitinib (SU) did not improve the overall survival in patients with non-small-cell lung cancer (NSCLC). In this study we examined the anticancer effect of ER, SU and their combination in the treatment of A549 human NSCLC xenograft mice, and conducted PK/PD modeling and simulations to optimize the dose regimen. METHODS: ER (20, 50 mg·kg(-1)·d(-1)) or SU (5, 10, 20 mg·kg(-1)·d(-1)) alone, or their combination were administered to BALB/c nude mice bearing A549 tumors for 22 days. The tumor size and body weight were recorded daily. The experimental data were used to develop PK/PD models describing the quantitative relationship between the plasma concentrations and tumor suppression in different dose regimens. The models were further evaluated and validated, and used to predict the efficacy of different combination regimens and to select the optimal regimen. RESULTS: The in vivo anticancer efficacy of the combination groups was much stronger than that of either drug administered alone. A PK/PD model was developed with a combination index (φ) of 4.4, revealing a strong synergistic effect between ER and SU. The model simulation predicted the tumor growth in different dosage regimens, and showed that the dose of SU played a decisive role in the combination treatment, and suggested that a lower dose of ER (≤5 mg·kg(-1)·d(-1)) and adjusting the dose of SU might yield a better dosage regimen for clinical research. CONCLUSION: The experimental data and modeling confirm synergistic anticancer effect of ER and SU in the treatment of A549 xenograft mice. The optimal dosage regimen determined by the PK/PD modeling and simulation can be used in future preclinical study and provide a reference for clinical application.

Population pharmacokinetic-pharmacodynamic (PopPK/PD) modeling of risperidone and its active metabolite in Chinese schizophrenia patients.

PURPOSE: Risperidone is a second-generation antipsychotic agent commonly used in the treatment of ~ 31.1% of schizophrenia patients in China, it is the most commonly-prescribed antipsychotic agent. Despite the abundant use of risperidone, population pharmacokinetic-pharmacodynamic models of risperidone have not been performed in Chinese schizophrenia patients. The objective of this study was to develop a population pharmacokinetic-pharmacodynamic (PopPK/PD) model to describe the PK behavior and efficacy of risperidone and 9-hydroxy-risperidone (active metabolite) in Chinese patients. METHODS: Plasma concentration data (702 measurements from 131 patients) and positive and negative syndrome scale (PANSS) scores (258 observations from 56 patients) were analyzed using a nonlinear mixed-effects modeling (NONMEM) approach with first-order conditional estimation with interaction (FOCEI). The influence of potential covariates was evaluated. Model robustness was assessed using external validation, normalized prediction distribution error, nonparametric bootstrap, and visual predictive check approaches. RESULTS: Risperidone concentration data were well described by a one-compartmental model incorporating an additional compartment that refers to the concentration profiles of 9-hydroxy-risperidone. A complex absorption procedure was incorporated into the model to describe the metabolism of risperidone to 9-hydroxy-risperidone in the gastrointestinal (GI) tract. A binomial distribution in the estimated clearance (CL) of risperidone has been identified in our model. Decrease in PANSS score along with total AUC (AUCtotal) of risperidone and 9-hydroxy-risperidone was best characterized by an Emax model with 3 transit compartments describing the delay of drug effect. CONCLUSIONS: Considerable differences in PK behavior and drug effect of risperidone have been identified among Chinese extensive metabolizing (EM) and poor metabolizing (PM) patients. This PopPK/PD model may fulfill individualized treatment in clinical practice and may potentially be transferred to other antipsychotic therapies.

[Using the cumulative odds Logit model to explore the application of the questionnaire derived from PANSS].

Currently, aripiprazole, olanzapine and risperidone are three anti-psychiatry agents commonly used in the treatment of schizophrenia. Although the efficacy of these drugs is good, schizophrenia cannot be completely cured yet. Patients need long-term medication. The family members of patients may play a key role to understand the disease status of patients after patient discharge from hospital. PANSS is a commonly used scale in the clinic to evaluate the disease status and drug effects of anti-psychiatry agents. It was professionally written, and is not user friendly to amateurs. In the previous study, we developed a questionnaire for patient's family members to monitor the disease status. In this study, we explored the correlations between the results of questionnaire and 5 kinds of disease state corresponding to different PANSS score interval using the cumulative odds Logit model. The final results show that the model had relatively good prediction ability for aripiprazole, olanzapine and risperidone, suggesting that the questionnaire has an extensive prospect of clinical applications.

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.

Population pharmacokinetics of intravenous levofloxacin 500 mg/day dosage in infected patients.

The purpose of this study was to explore the population pharmacokinetic features of levofloxacin in Chinese infected patients. A total of 27 Chinese adult infected patients were treated with intravenous levofloxacin (500 mg/day). In total, 49 plasma samples of levofloxacin were collected immediately after intravenous dripping and before administration on the 3rd, 4th or 5th day. A nonlinear mixed effect model was used to model the population pharmacokinetic (PK) behavior of levofloxacin. The final population pharmacokinetic models were validated using the bootstrap method. Some covariates, including demographic characteristics and hematological and biological indicators, were analyzed. A structural model was developed based on a one-compartment model with intravenous infusion and first-order elimination. The typical population values for pharmacokinetic parameters of apparent clearance (CL) and apparent distribution volume (V) were 5.84 L/h and 43.3L, respectively. The inter-individual variabilities of CL and V were 7.75% and 6.4%, respectively, while the intra-individual variability of observed concentrations was 0.06 microg/mL. The covariates of age and AST influenced the CL and V values determined by the final model. The present study developed population pharmacokinetic models for levofloxacin in infected Chinese patients. The results detailed here could provide a reference for individualized levofloxacin therapy in the clinical setting.

Population pharmacokinetics of intravenous moxifloxacin 400 mg once-daily dosage in infected patients.

OBJECTIVE: The purpose of this study was to explore the population pharmacokinetic features of moxifloxacin in infected patients. METHOD: A total of 37 Chinese adult infected patients were treated with intravenous moxifloxacin (400 mg/day). In total, 67 plasma samples of moxifloxacin were collected immediately after intravenous dripping and before administration on the 3rd, 4th or 5th day. A nonlinear mixed effect model was used to model the population pharmacokinetic (PK) behavior of moxifloxacin. The final population pharmacokinetic models were validated using the bootstrap method. Some covariates, including demographic characteristics and hematological and biological indicators, were analyzed. RESULTS: A structural model was developed based on a one-compartment model with intravenous infusion and first-order elimination. The typical population values of moxifloxacin for the pharmacokinetic parameters of apparent clearance (CL) and apparent distribution volume (V) were 12.9 L/h and 115 L, respectively. The inter-individual variabilities of CL and V were 36% and 28%, respectively. The covariates of WT influenced the CL and V values determined by the final model. CONCLUSION: The present study developed population pharmacokinetic models for moxifloxacin in infected Chinese patients. The results detailed here could provide a reference for individualized moxifloxacin therapy in the clinical setting.

[Population pharmacokinetics of vancomycin and prediction of pharmacodynamics in the Chinese people].

Population pharmacokinetics of vancomycin (VAN) in the Chinese patients was described by using nonlinear mixed-effects modeling (NONMEM). 619 VAN serum concentrations data from 260 patients including 177 males and 83 females were collected separately from two centers. A one-compartment model was used to describe this sparse data. No significant difference was observed between two center datasets by introducing SID covariate. The final model was as CL= (θ (base0+ θ(max) x(1 -e(-θ(Age)(Age/72) and V = θ x θ (Age)(Age/72). The creatinine clearance (CL(Cr)) and Age were identified as the most significant covariate in the final model. Typical values of clearance (CL) and volume of distribution (V) in the final model were 2.91 L x h(-1) and 54.76 L, respectively. Internal model validation by Bootstrap and NPDE were performed to evaluate the robustness and prediction of the final model. The median and 95% confidence intervals for the final model parameters were based on 1000 Bootstraps. External model evaluation was conducted using an independent dataset that consisted of 34 patients to predict model performance. Pharmacodynamic assessment for VAN by AUC (0-24 h) to MIC ratios of over 400 was considered to be the best to predict treatment outcomes for patients. AUC (0-24 h) was calculated by clearance based on the above population model. The results indicate that the conventional dosing regimen probably being suboptimal concentrations in aged patients. The approach via population pharmacokinetic of VAN combined with the relationship of MIC, Age, CL(Cr) and AUC(0-24 h)/MIC can predict the rational dose for attaining efficacy.

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.