| Objectives: In order to analyze the factors that would affect tacrolimus pharmacokinetics and provide population pharmacokinetics (Pop-PK) models which would pridict individuation dosage for patients with hematopoietic stem cell transplant in clinic, we established the Pop-PK models of tacrolimus through the analysis of tacrolimus population characteristics in Chinese health population and hematopoietic stem cell transplant patients, and analyze the discrepancy of model parameters.Methods: We measured tacrolimus concentrations from 587 blood samples of 43 health population, 671 blood samples of 68 hematopoietic stem cell transplant patients, 482 blood samples of 42 hematopoietic stem cell transplant patients with CYP3A5 polymorphism data and all corresponding clinical data were collected from the medical records of the population, retrospectively. The whole blood tacrolimus concentrations were measured by UPLC-MS/MS in health population. Population pharmacokinetics analyses were performed using the nonlinear mixed-effect model (NONMEM) program. The basic pharmacokinetic models were best described as two-compartment pharmacokinetic model with first-order absorption and elimination for health population, and single-compartment pharmacokinetic model with first-order absorption and elimination for hematopoietic stem cell transplant patients. A number of covariates including demographic characteristics, CYP3A5 polymorphism, biochemical and hematological index, combined drugs, IOV (inter-occasion variability) and other variables,e.g. primary disease, post operation days (POD), the type of transplantation and the sources of donor, were screened for their influence on the pharmacokinetic parameters of tacrolimus. The bootstrap was used to validate the final population pharmacokinetics models.Results: (1). The population typical values of tacrolimus in health population CL/F, V2/F, Q/F, V3/F, ka and ALAG1 were 32.5 L·h-1, 15.3 L, 32.3 L·h-1, 590 L, 0.765 h-1 and 0.226 h; and the inter-individual variability of these parameters were 58.0%, 69.2%, 78.9%, 223.0%, 34.4% and 0.12%, respectively. The intra-individual variability of observed concentration was 24.6%. The present study showed that Pop-PK model of tacrolimus was only included by one covariate of CYP3A5 polymorphism, and CYP3A5 polymorphism could significantly influence apparent clearance of tacrolimus in health population. The CL/F of CYP3A5*1/*3 population was lower about 23.8% than CYP3A5*1/*1 population, while the CL/F of CYP3A5*3/*3 population was lower about 63.4% than CYP3A5*1/*1 population.(2). Pop-PK models of tacrolimus by retrospective study showed that the population typical values of tacrolimus in hematopoietic stem cell transplant patients without CYP3A5 polymorphism data CL, V, F were 12.1 L·h-1, 686 L, 42.2%; and the inter-individual variability of these parameters were 23.5%, 96.4%, 43.8%, respectively. The absorption rate constant was fixed 4.3 h-1. The residual error between observed and model-predicted concentration was 3.03 ng·ml-1. The CYP enzyme inhibitor (INHI), POD and age were identified to be the main covariates that influence tacrolimus CL, and hemoglobulin (HGB) was the main covariate that may explain the variability in tacrolimus V. The IOV of CL, V, F were 22.2%, 6.23%, 30.3%,respectively.(3). The prospective study which individual pharmacokinetic parameters analyzed with the prior established Pop-PK models showed that CYP3A5 polymorphism could significantly influence individual pharmacokinetic parameters of tacrolimus. The patients'CL and V were higher for CYP3A5 *1/*1 or *1/*3 than *3/*3 (P<0.05), however, the patients'F, observed concentration, individual predicted concentration were lower for CYP3A5 *1/*1 or *1/*3 than *3/*3 (P<0.05).(4). We estabished Pop-PK models of tacrolimus included CYP3A5 polymorphism, and indicated that the population typical values of tacrolimus in hematopoietic stem cell transplant patients with CYP3A5 polymorphism data CL, V, F were 17.5 L·h-1, 191 L and 34.0%; and the inter-individual variability of these parameters were 32.4%,45.8% and 36.6%, respectively. The absorption rate constant was also fixed 4.3 h-1. The residual error between observed and model-predicted concentration was 3.55 ng·ml-1. The present study showed that CYP enzyme inhibitor (INHI), POD, CYP enzyme inductor (INDU) and CYP3A5 polymorphism were identified to be the main covariates that influence tacrolimus CL, and Cyclosporin A (CsA) and hematocrit (HCT) were the main covariate that may explain the variability in tacrolimus V. The IOV of CL, V, F were 18.6%, 11.2% and 30.4%, respectively.Conclusions: The tacrolimus population pharmacokinetics models'covariates included CYP3A5 polymorphism, combined drugs, POD, and red cell counts in patients with hematopoietic stem cell transplant. The models would provide reference for tacrolimus individualization therapy in clinic for the hematopoietic stem cell transplant patients.
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