AimsTherapeutic drug monitoring (TDM) of tacrolimus is complicated by conflicting data on the correlation between tacrolimus trough blood concentrations and the incidence of rejection. The aim of this cross-sectional study was to investigate the blood distribution and protein binding of tacrolimus in liver transplant recipients to explore better predictors of clinical outcome. MethodsBlood and plasma distribution of 3 H-dihydro-tacrolimus was investigated in 40 liver transplant recipients using Ficoll Paque and density gradient ultracentrifugation, respectively, and equilibrium dialysis to investigate plasma protein binding. ResultsIn blood tacrolimus was mainly associated with the erythrocyte fraction (83.2%, range 74.6-94.9%), followed by diluted plasma (16.1%, range 4.5-24.9%), and lymphocyte fraction (0.61%, range: 0.11-1.53%). In plasma, lipoprotein deficient serum fraction (54.2%, range 38.5-68.2%) was the main reservoir of tacrolimus. The unbound fraction of tacrolimus was found to be 0.47 ± 0.18% (range 0.07-0.89%). The percentage of tacrolimus associated with the lymphocy tes (0.8 ± 0.4 vs 0.3 ± 0.1%, P = 0.012) and estimated unbound concentration (0.42 ± 0.21 ng l -1 vs 0.24 ± 0.08 ng l -1 , P < 0.001) of tacrolimus were significantly different in stable transplant recipients and those experiencing rejection. Haematocrit and red blood cell count significantly influenced the percentage of tacrolimus associated with erythrocytes. The fraction unbound of tacrolimus was correlated with a 1 -acid glycoprotein and high density lipoprotein cholesterol concentrations. ConclusionsTacrolimus unbound concentration was observed to be lower in liver transplant recipients experiencing rejection and further study is required to evaluate its utility in the TDM of tacrolimus.

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Therapeutic drug monitoring of tacrolimus is complicated by the conflicting evidence of a relationship between trough blood tacrolimus concentration and clinical outcome. This prospective study investigated the blood distribution and protein binding of tacrolimus in liver transplant recipients over the first 60 days after transplantation with a view to identifying possible predictors of clinical outcome. Blood samples were collected from 10 liver transplant recipients on days 1, 7, and 60 after the initiation of tacrolimus therapy, and the distribution of tacrolimus in blood and the plasma protein binding were investigated. The unbound concentration of tacrolimus in plasma was estimated. Graft status was assessed using liver function tests and liver biopsies. The association of tacrolimus with erythrocytes varied significantly (74.4 +/- 5.0% vs 80.4 +/- 3.4%; P = 0.034) from day 1 to day 60. In plasma, tacrolimus mainly associated with lipoprotein-deficient plasma (60.1 +/- 6.5%), followed by high-density lipoproteins (27.2 +/- 6.6%), low-density lipoproteins (10.0 +/- 4.2%), and very low-density lipoproteins (2.8 +/- 1.8%). The percentage of tacrolimus associated with leukocytes (1.10 +/- 0.40% vs 0.40 +/- 0.09%; P = 0.0003) and the unbound concentration of tacrolimus (0.70 +/- 0.19 vs 0.28 +/- 0.04 ng/L; P < 0.0001) were observed to be significantly lower during episodes of rejection. In patients experiencing tacrolimus-related side effects, only the unbound concentration of tacrolimus was found to be significantly higher (0.84 +/- 0.19 vs 0.53 +/- 0.19 ng/L; P < 0.0001), and blood concentrations were not different (9.2 +/- 2.2 vs 8.1 +/- 1.8 ng/mL; P = 0.1). Blood distribution and protein binding of tacrolimus vary significantly over the posttransplantation period, leading to changes in its unbound concentration. A prospective study in a larger cohort of patients is required to establish the role of blood distribution and protein binding of tacrolimus in its therapeutic drug monitoring.

Treatment response to clopidogrel is associated with CYP2C19 activity through the formation of the active H4 metabolite. The aims of this study were to develop a physiologically based pharmacokinetic (PBPK) model of clopidogrel and its metabolites for populations of European ancestry, to predict the pharmacokinetics in the Japanese population by CYP2C19 phenotype, and to investigate the effect of clinical and demographic factors. A PBPK model was developed and verified to describe the two metabolic pathways of clopidogrel (H4 metabolite, acyl glucuronide metabolite) for a population of European ancestry using plasma data from published studies. Subsequently, model predictions in the Japanese population were evaluated. The effects of CYP2C19 activity, fluvoxamine coadministration (CYP2C19 inhibitor), and population‐specific factors (age, sex, BMI, body weight, cancer, hepatic, and renal dysfunction) on the pharmacokinetics of clopidogrel and its metabolites were then characterized. The predicted/observed ratios for clopidogrel and metabolite exposure parameters were acceptable (twofold acceptance criteria). For all CYP2C19 phenotypes, steady‐state AUC0‐τ of the H4 metabolite was lower for the Japanese (e.g., EM, 7.69 [6.26–9.45] ng·h/ml; geometric mean [95% CI]) than European (EM, 24.8 [20.4–30.1] ng·h/ml, p < .001) population. In addition to CYP2C19‐poor metabolizer phenotype, fluvoxamine coadministration, hepatic, and renal dysfunction were found to reduce H4 metabolite but not acyl glucuronide metabolite concentrations. This is the first PBPK model describing the two major metabolic pathways of clopidogrel, which can be applied to populations of European and Japanese ancestry by CYP2C19 phenotype. The differences between the two populations appear to be determined primarily by the effect of varying CYP2C19 liver activity.

The spectrum of pharmacokinetic determinants for each drug substrate and their differences across ethnic groups must be considered on a case-by-case basis in addition to metabolism by CYP2C9, CYP2C19, or CYP2D6. This analysis has also highlighted the challenges which arise when comparing published datasets if consistent methods to assign polymorphic enzyme activity have not been used.