Population pharmacokinetics of ciclosporin in allogeneic hematopoietic stem cell transplant recipients: C-reactive protein as a novel covariate for clearance.

WHAT IS KNOWN AND OBJECTIVES: Ciclosporin (CsA), a potent immunosuppressive agent used to prevent graft-versus-host disease in allogeneic hematopoietic stem cell transplant (allo-HSCT) recipients, is characterized by large inter-individual variability and a narrow therapeutic range. The aim of this study was to develop a population pharmacokinetic model for CsA in Chinese allo-HSCT recipients and to identify covariates influencing CsA pharmacokinetics. METHODS: A total of 758 retrospective drug monitoring data points were collected after intravenous infusion or oral administration of CsA from 59 patients. Population pharmacokinetic analysis was performed using nonlinear mixed effects modelling expressed by differential equations. Monte Carlo simulation was applied to optimize dosage regimens. The final model was validated using bootstrap and normalized prediction distribution errors. RESULTS AND DISCUSSION: The results showed that the daily CsA dose, haematocrit, total bile acid, C-reactive protein (CRP) and co-administration of triazole antifungal agent were identified as significant covariates for clearance (CL) of CsA. The typical value of CL was 19.8 L/h with an inter-individual variability of 13.1%. The volume of distribution was 1340 L. Bioavailability was 67.2% with an inter-individual variability of 8.5%. Dosing simulation based on the developed model indicated that patients with high CRP concentration required a higher daily dose to attain the therapeutic trough concentration. The influence of CRP ultimately on the therapy outcome of CsA is not clear, which needs further study. WHAT IS NEW AND CONCLUSION: CRP concentration was identified as a novel marker associated with CsA pharmacokinetics, which should be considered when determining the appropriate dosage of CsA in allo-HSCT recipients.

Effects of CYP3A5, ABCB1 and POR*28 polymorphisms on pharmacokinetics of tacrolimus in the early period after renal transplantation.

1. We aimed to establish a population pharmacokinetic (PK) model of tacrolimus and identify clinical covariates, especially the genetic polymorphisms of CYP3A5, ABCB1 and POR*28 that affected the PK to prevent fluctuation in the trough concentration of tacrolimus during the early period after renal transplantation. 2. Tacrolimus trough concentration, clinical data and CYP3A5/ABCB1/POR28 genotypes were retrospectively collected from 234 kidney transplant recipients during the first month post-transplantation. The population PK model was built using the non-linear mixed effects modeling software NONMEM. Dosing simulation was performed based on the final model. 3. A one-compartment model with first-order absorption and elimination was used to characterize the PK of tacrolimus. Among the genotypes, only CYP3A5 genotype was confirmed to have clinical significance. The final model describing CL/F (l/h) was as follows: 23.3 × ( HCT / 0.309 ) - 0.445   × [ ( 0.897 ,   i f   POD   > 10 ) o r   ( 1 , i f   POD   ≤ 10 ) ] × ( 0.657 , i f   CYP 3 A 5 * 3 / * 3   genotype ) . The inter-individual variability in CL/F was 21.9%. Monte Carlo simulation based on the final model was carried out to determine the optimal dosage regimen. 4. CYP3A5 genotype, post-operative day and hematocrit were confirmed as critical PK factors of tacrolimus. The model could be used to accurately predict individual PK parameters of tacrolimus and provide valuable insights into the dosage optimization.

Population Pharmacokinetics and Pharmacodynamics of Piperacillin/Tazobactam in Patients with Nosocomial Infections.

OBJECTIVE: The study was to establish a population pharmacokinetic (PPK) model of piperacillin (PIP) and tazobactam (TAZ) that explain pharmacokinetic variability and to propose optimized dosage regimens in patients with nosocomial infections. METHODS: In total, 310 PIP and 280 TAZ concentration-time points were collected at steady state over multiple dosing intervals from 50 patients who received PIP/TAZ infused within 30 min or over 3 h. Drug analysis was performed by high-performance liquid chromatography (HPLC). Nonlinear mixed effects modeling was employed to develop PPK model and 1000 Monte Carlo simulation was used to predict the probability of target attainment (PTA) with a target time of non-protein-bound concentration above MIC > 50 % of the dosing interval. RESULTS: A model with one-compartment model had the best predictive performance for the PPK model. The population estimates of PIP were 13.8 L/h (31.1 %) for clearance (CL) and 21.7 L (38 %) for volume of distribution (V). The population estimates of TAZ were 9.3 L/h (29.1 %) for CL and 16 L (35.3 %) for V. Influence of creatinine clearance (CLcr) and body weight were identified as important covariates for PIP/TAZ CL and V, respectively. A 30-min infusion of 4 g every 6 h achieved robust (≥90 %) PTAs for MIC ≤ 16 mg/L. As an alternative mode of administration, a 3-h infusion of 4 g every 6 h achieved robust PTAs for Pseudomonas aeruginosa and Klebsiella pneumoniae. CONCLUSIONS: Prolonged infusions achieved better PTAs compared with shorter infusions at similar daily doses. This benefit was most pronounced for MICs between 16 and 40 mg/L.

Cisplatin-based chronotherapy for advanced non-small cell lung cancer patients: a randomized controlled study and its pharmacokinetics analysis.

PURPOSE: We intended to evaluate the superiority of cisplatin-based chronotherapy in the treatment of patients with advanced non-small cell lung cancer (NSCLC) and investigate the relationship between the circadian rhythm and the variability of pharmacokinetics for cisplatin. METHODS: Forty-one patients with advanced NSCLC were divided into two groups with minimization randomization, including routine group (24 cases) and chronotherapy group (17 cases). The clinical effect and toxicity between the two groups were investigated. The population pharmacokinetics of cisplatin was calculated using nonlinear mixed-effects modeling method. RESULTS: There is no significant difference in total response rate between chronotherapy group (52.94%) and routine chemotherapy group (50.00%), p = 0.853. The rate of leucopenia (grade 3 or 4) in chronotherapy group (11.76%) is significantly lower than that in routine chemotherapy (37.50%), p < 0.05. The rate of neutropenia (grade 3 or 4) in chronotherapy group (11.76%) is significantly lower than that in routine chemotherapy group (33.33%), p < 0.05. The proportion of gastrointestinal toxicity (nausea, grade 1 vs 2) in chronotherapy group is significantly lower than that in routine chemotherapy, p < 0.05. When cisplatin was administered at 18:00, the CL was 1.38- and 1.22-fold higher than those administered at 6:00 for total and unbound cisplatin, respectively (p < 0.05). CONCLUSIONS: Cisplatin-based chronotherapy has advantage in relieving side effects of chemotherapy, and circadian could influence the metabolism of cisplatin, and more clinical researches are needed.

Circadian variability of pharmacokinetics of cisplatin in patients with non-small-cell lung carcinoma: analysis with the NONMEM program.

PURPOSE: The aim of this study was to describe the nonlinear pharmacokinetics of total and unbound plasma cisplatin under different administered time in patients with non-small-cell lung carcinoma. METHODS: Patients receiving chemotherapy with cisplatin were included in this analysis. Patients were divided into two groups depending on the administrated time of cisplatin: 6:00 (Group A) and 18:00 (Group B). The population pharmacokinetics of cisplatin was calculated using nonlinear mixed-effects modeling (NONMEM) method, and the possible influence of covariates on the population pharmacokinetics of cisplatin was also explored. RESULTS: The pharmacokinetics of total and unbound cisplatin could be described well by a linear two-compartment model. The mean population estimates for total and unbound drug were, respectively, 0.463 (17.0 %) and 25.4 (14.0 %) l h⁻¹ for clearance (CL), 24.2 (19.9 %) and 20.5 (27.1 %) l for central distribution volume (V1), 10.2 (18.2 %) and 9.82 (28.1) l h⁻¹ for intercompartmental clearance (Q) and 32.0 (24.1 %) and 6.77 (25.4 %) l for peripheral compartment volume (V2). The CL for total and unbound cisplatin was dependent on body surface area (BSA). When cisplatin was administered at 18:00, the CL was 1.38- and 1.22-fold higher than those administered at 6:00 for total and unbound cisplatin, respectively (P < 0.05). The mean parameter estimates from a nonparametric bootstrap procedure were comparable and within 5 % of the estimates from NONMEM. CONCLUSIONS: The results showed that circadian could influence the metabolism of cisplatin and suggested the conventional dose adjustment of cisplatin based on BSA.

Population pharmacokinetics of digoxin in elderly patients.

This study was aimed at determining the population pharmacokinetics of digoxin and identifying factors that explain pharmacokinetic variability in elderly patients. The data of 142 elderly patients and 448 samples were collected after repetitive oral digoxin. Blood samples were drawn at various times after administration. Population pharmacokinetic analysis was performed using nonlinear mixed effects modelling program (NONMEM). A one-compartment model with first-order absorption and elimination was selected as the base model. The influence of demographic characteristics, biochemical and haematological indices as well as other commonly used co-medications were explored. The typical values with interindividual variability for apparent clearance (CL/F) and apparent volume of distribution (V/F) were 8.9 L h(-1) (43.2 %) and 420 L (65.8 %), respectively. The residual variability was 31.6 %. CL/F decreased significantly with renal function, total body weight, calcium channel blockers or spironolactone co-therapy and symptom with congestive heart failure. The median parameter estimates from a nonparametric bootstrap procedure were comparable and within 5 % of the estimates from NONMEM. These results provide important information for clinicians to optimize digoxin regimens in elderly patients.