Multicenter-Based Population Pharmacokinetic Analysis of Ciclosporin in Hematopoietic Stem Cell Transplantation Patients.

PURPOSE: To explore the contribution of physiological characteristics to variability in ciclosporin pharmacokinetics in hematopoietic stem cell transplantation patients. METHODS: Clinical data from 563 patients were collected from centers in three regions. Ciclosporin concentrations were measured using immunoassays. The patients' demographics, hematological and biological indicators, coadministered drugs, region, and disease diagnosis were recorded from medical records. Data analysis was performed using NONMEM based on a one-compartment model to describe the pharmacokinetics of ciclosporin. The reliability and stability of the final model were evaluated using bootstrap resampling, goodness-of-fit plots, and prediction-corrected visual predictive checks. RESULTS: The population estimate of the clearance (CL) was 30.4 L/h, the volume of distribution (V) was 874.0 L and the bioavailability (F) was 81.1%. The between-subject variability in these parameters was 26.3, 68.0, and 110.8%, respectively. Coadministration of fluconazole, itraconazole, or voriconazole decreased CL by 17.6%, 28.4%, and 29.2%, respectively. Females' CL increased by approximately 12.0%. In addition, CL and V decreased with hematocrit, total protein, and uric acid increase, and CL also decreased with age and aspartate aminotransferase increase. However, CL increased with creatinine clearance increase. CONCLUSIONS: A multicenter-based population pharmacokinetic model of ciclosporin was established. The pharmacokinetics of ciclosporin exhibited discrepancies among different regions.

Metabolism and disposition of pyrotinib in healthy male volunteers: covalent binding with human plasma protein.

Pyrotinib is a novel irreversible EGFR/HER2 dual tyrosine kinase inhibitor that is used to treat HER2-positive breast cancer. In this study we investigated the metabolism and disposition of pyrotinib in six healthy Chinese men after a single oral dose of 402 mg of [14C]pyrotinib. At 240 h postdose, the mean cumulative excretion of the dose radioactivity was 92.6%, including 1.7% in urine and 90.9% in feces. In feces, oxidative metabolites were detected as major drug-related materials and the primary metabolic pathways were O-depicoline (M1), oxidation of pyrrolidine (M5), and oxidation of pyridine (M6-1, M6-2, M6-3, and M6-4). In plasma, the major circulating entities identified were pyrotinib, SHR150980 (M1), SHR151468 (M2), and SHR151136 (M5), accounting for 10.9%, 1.9%, 1.0%, and 3.0%, respectively, of the total plasma radioactivity based on the AUC0-∞ ratios. Approximately 58.3% of the total plasma radioactivity AUC0-∞ was attributed to covalently bound materials. After incubation of human plasma with [14C]pyrotinib at 37 °C for 2, 5, 8, and 24 h, the recovery of radioactivity by extraction was 97.4%, 91.8%, 69.6%, and 46.7%, respectively, revealing covalent binding occurred independently of enzymes. A group of pyrotinib adducts, including pyrotinib-lysine and pyrotinib adducts of the peptides Gly-Lys, Lys-Ala, Gly-Lys-Ala, and Lys-Ala-Ser, was identified after HCl hydrolysis of the incubated plasma. Therefore, the amino acid residue Lys190 of human serum albumin was proposed to covalently bind to pyrotinib via Michael addition. Finally, the covalently bound pyrotinib could dissociate from the human plasma protein and be metabolized by oxidation and excreted via feces.

Theory-based pharmacokinetics and pharmacodynamics of S- and R-warfarin and effects on international normalized ratio: influence of body size, composition and genotype in cardiac surgery patients.

AIMS: The aims of this study are to apply a theory-based mechanistic model to describe the pharmacokinetics (PK) and pharmacodynamics (PD) of S- and R-warfarin. METHODS: Clinical data were obtained from 264 patients. Total concentrations for S- and R-warfarin were measured by ultra-high performance liquid tandem mass spectrometry. Genotypes were measured using pyrosequencing. A sequential population PK parameter with data method was used to describe the international normalized ratio (INR) time course. Data were analyzed with NONMEM. Model evaluation was based on parameter plausibility and prediction-corrected visual predictive checks. RESULTS: Warfarin PK was described using a one-compartment model. CYP2C9 *1/*3 genotype had reduced clearance for S-warfarin, but increased clearance for R-warfarin. The in vitro parameters for the relationship between prothrombin complex activity (PCA) and INR were markedly different (A = 0.560, B = 0.386) from the theory-based values (A = 1, B = 0). There was a small difference between healthy subjects and patients. A sigmoid Emax PD model inhibiting PCA synthesis as a function of S-warfarin concentration predicted INR. Small R-warfarin effects was described by competitive antagonism of S-warfarin inhibition. Patients with VKORC1 AA and CYP4F2 CC or CT genotypes had lower C50 for S-warfarin. CONCLUSION: A theory-based PKPD model describes warfarin concentrations and clinical response. Expected PK and PD genotype effects were confirmed. The role of predicted fat free mass with theory-based allometric scaling of PK parameters was identified. R-warfarin had a minor effect compared with S-warfarin on PCA synthesis. INR is predictable from 1/PCA in vivo.

Population pharmacokinetics and individualized dosage prediction of cyclosporine in allogeneic hematopoietic stem cell transplant patients.

BACKGROUND: Cyclosporine (CsA), a potent immunosuppressive agent used to prevent rejection, is characterized by large individual variability. The purpose of this study was to explore the pharmacokinetic characteristics of CsA and establish a CsA population pharmacokinetic model that could be used for personalized therapy in allogeneic hematopoietic stem cell transplant (allo-HSCT) patients. METHODS: Clinical data were obtained from 117 allo-HSCT patients. The data analysis was performed using NONMEM software. A first-order conditional estimation with interaction (FOCE-I) method within NONMEM was used to estimate the parameters. The covariates, including demographics, hematological indices, biochemical levels, concurrent drugs, and genetic polymorphisms of CYP3A4, CYP3A5, and ABCB1, were evaluated quantitatively. The stability of the final model was validated by a nonparametric bootstrap procedure. RESULTS: A total of 1,571 observed concentrations were collected. A 1-compartment model with first-order absorption and elimination adequately described the pharmacokinetics of CsA. The typical values for clearance (CL), volume of distribution (V), and bioavailability were 29.6 L/hr, 605 L, and 0.619, respectively. The interindividual variability of these parameters was 20.4, 66.1, and 30.4%, respectively. The residual error was 31.4% and 23.7 ng/mL. The duration of CsA therapy, hematocrit, antifungal agent administration, triglycerides, and weight were identified as the main covariates that influenced CL, and hematocrit had a significant effect on V. The internal validation showed that the final model was stable and accurate. CONCLUSIONS: This study established a population pharmacokinetic model of CsA in allo-HSCT patients that could provide the foundation for personalized use of CsA in the clinic.