Population pharmacokinetic estimation of tacrolimus apparent clearance in adult liver transplant recipients

The goal was to study the factors affecting tacrolimus apparent clearance (CL/F) in adult liver transplant recipients. Tacrolimus dose and concentration data (n = 694) were obtained from 67 liver transplant recipients (22 female and 45 male), and the data were analyzed using a nonlinear mixed-effect modeling (NONMEM) method. A 1-compartment pharmacokinetic model with first-order elimination, an absorption rate constant fixed at 4.5 hours, and first-order conditional estimation was used to describe tacrolimus disposition. The predictive performance of the final model was evaluated using data splitting and assessing bias and precision of the estimates. The population estimate of tacrolimus CL/F and apparent volume of distribution (V/F) were found to be 21.3 L/h (95% confidence interval, CI, 18.0-24.6 L/h) and 316.1 L (95% CI 133-495 L), respectively. Neither patient's age, weight, gender, nor markers of liver function influenced tacrolimus CL/F. The final model was TVCL = 21.3 + 9.8 x (1 - HEM) + 3.4 x (1 - ALB) - 2.1 x (1 - DIL) - 7.4 x (1 - FLU), where TVCL, typical estimate of apparent clearance, HEM = 0 if hematocrit <35%, otherwise 1; ALB = 0 if albumin <3.5 g/dL, otherwise 1; DIL = 0 if diltiazem is coadministered, otherwise 1; FLU = 0 if fluconazole is coadministered, otherwise 1. This study identified the factors that significantly affect tacrolimus disposition in adult liver transplant recipients during the early posttransplantation period. This information will be helpful to clinicians for dose individualization of tacrolimus in liver transplant recipients with different clinical conditions including anemia or hypoalbuminemia or in those patients receiving diltiazem or fluconazole.     

Factors affecting the apparent clearance of tacrolimus in Korean adult liver transplant recipients

STUDY OBJECTIVE: To identify the factors affecting tacrolimus apparent total body clearance (Cl/F [F = bioavailability]) in adult liver transplant recipients. DESIGN: Population pharmacokinetic analysis using data from a retrospective chart review. SETTING: University-affiliated hospital in Seoul, South Korea. PATIENTS: Fifty-one adult liver transplant recipients who had received tacrolimus after transplantation. MEASUREMENTS AND MAIN RESULTS: Data on 35 adult liver transplant recipients for model building and 16 patients for model validation were obtained retrospectively. Population average parameter estimates of Cl/F and apparent volume of distribution (V/F) were sought by using the nonlinear mixed-effect model (NONMEM) program. A number of clinical covariates were screened for their influence on these pharmacokinetic parameters. The final optimal population model related Cl/F to total bilirubin, early (< or = 3 days) and late (> 35 days) postoperative days, international normalized ratio (INR), and graft:recipient weight ratio (GRWR). The NONMEM estimates indicated that the Cl/F of tacrolimus was decreased in patients with a small graft, hyperbilirubinemia, and a high INR. In addition, the Cl/F of tacrolimus almost doubled 4 days after transplantation, but decreased with an increase in duration of therapy after day 35. Mean prediction error and mean absolute prediction error were 0.26 and 3.78 ng/ml, respectively, for the validation sample. A final analysis in all 51 patients, which consisted of 1775 blood samples for concentration measurements, identified the following regression model: Cl/F (L/hr) = (0.36 + 2.01/POD * L) * TBIL(-0.23 (TBIL = 1 if TBIL level < or = 1.2 mg/dl, otherwise TBIL = TBIL level)) *49((if POD < or = 3 days)) * 0.75((if INR > 1.4)) * 0.86((if GRWR < or = 1.25%)) * WT, where L was 1 if postoperative day (POD) was greater than 35 days, otherwise L was 0; V/F was 568 L, TBIL was total bilirubin, and WT was body weight. The interindividual variabilities (coefficients of variation) in Cl/F and V/F were 35.35% and 68.12%, respectively. The residual variability was 3.14 ng/ml. CONCLUSION: These findings could be useful to the health care provider for adjustment of tacrolimus dosage in adult liver transplant recipients with various clinical factors.     

Population pharmacokinetics of tacrolimus in Asian paediatric liver transplant patients

AIMS: The purpose of this study was to describe the population pharmacokinetics of intravenous and oral tacrolimus (FK506) in 20 Asian paediatric patients, aged 1-14 years, following liver transplantation and to identify possible relationships between clinical covariates and population parameter estimates. METHODS: Details of drug dosage histories, sampling times and concentrations were collected retrospectively from routine therapeutic drug monitoring data accumulated for at least 4 days after surgery. Before analysis, patients were randomly allocated to either the population data set (n = 16) or a validation data set (n = 4). The population data set was comprised of 771 concentration measurements of patients admitted over the last 3 years. Population modelling using the nonlinear mixed-effects model (NONMEM) program was performed on the population data set, using a one-compartment model with first-order absorption and elimination. Population average parameter estimates of clearance (CL), volume of distribution (V) and oral bioavailability (F) were sought; a number of clinical and demographic variables were tested for their influence on these parameters. RESULTS: The final optimal population models related clearance to age, volume of distribution to body surface area and bioavailability to body weight and total bilirubin concentration. Predictive performance of this model evaluated using the validation data set, which comprised 86 concentrations, showed insignificant bias between observed and model-predicted blood tacrolimus concentrations. A final analysis performed in all 20 patients identified the following relationships: CL (l h-1) = 1.46 *[1 + 0. 339 * (AGE (years) -2.25)]; V (l) = 39.1 *[1 + 4.57 * (BSA (m2)-0. 49)]; F = 0.197 *[1 + 0.0887 * (WT (kg) -11.4)] and F = 0.197 *[1 + 0.0887 * (WT (kg) -11.4)] * [1.61], if the total bilirubin > or = 200 micromol l-1. The interpatient variabilities (CV%) in CL, V and F were 33.5%, 33.0% and 24.1%, respectively. The intrapatient variability (s.d.) among observed and model-predicted blood concentrations was 5.79 ng ml-1. CONCLUSIONS: In this study, the estimates of the pharmacokinetic parameters of tacrolimus agreed with those obtained from conventional pharmacokinetic studies. It also identified significant relationships in Asian paediatric liver transplant patients between the pharmacokinetics of tacrolimus and developmental characteristics of the patients.     

Population pharmacokinetic and pharmacogenetic analysis of tacrolimus in paediatric liver transplant patients

Aims

To build a population pharmacokinetic model that describes the apparent clearance of tacrolimus and the potential demographic, clinical and genetically controlled factors that could lead to inter-patient pharmacokinetic variability within children following liver transplantation.

Methods

The present study retrospectively examined tacrolimus whole blood pre-dose concentrations (n = 628) of 43 children during their first year post-liver transplantation. Population pharmacokinetic analysis was performed using the non-linear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance and influential covariates.

Results

The final model identified time post-transplantation and CYP3A5*1 allele as influential covariates on tacrolimus apparent clearance according to the following equation:where TVCL is the typical value for apparent clearance, TPT is time post-transplantation in days and the CYP3A5 is 1 where *1 allele is present and 0 otherwise. The population estimate and inter-individual variability (%CV) of tacrolimus apparent clearance were found to be 0.977 l h⁻¹ kg⁻¹ (95% CI 0.958, 0.996) and 40.0%, respectively, while the residual variability between the observed and predicted concentrations was 35.4%.

Conclusion

Tacrolimus apparent clearance was influenced by time post-transplantation and CYP3A5 genotypes. The results of this study, once confirmed by a large scale prospective study, can be used in conjunction with therapeutic drug monitoring to recommend tacrolimus dose adjustments that take into account not only body weight but also genetic and time-related changes in tacrolimus clearance.     

Population pharmacokinetics of tacrolimus in full liver transplant patients: modelling of the post-operative clearance

Objective To investigate the population pharmacokinetics of tacrolimus in an adult liver transplant cohort using routine drug monitoring data and to identify patient characteristics that influence pharmacokinetic parameters.Methods Tacrolimus pharmacokinetics was studied in 37 adult patients using a population approach performed with NONMEM.Results A one-compartment open model with linear absorption and elimination adequately described the data. The apparent clearance (CL) was approximately zero in the immediate post-operative days (PODs) and then rapidly increased as a function of POD to reach a plateau. This was modelled as a sigmoid relationship with the characteristic parameters CL_max (plateau), TCL₅₀ (time to obtain 50% of the plateau) and gamma (coefficient of sigmoidicity). This clearance model was thought to describe the hepatic function regeneration after transplantation. Typical population estimates (percentage inter-individual variability) of CL_max, TCL₅₀, and gamma and apparent distribution volumes (V) were 36 l/h (43%), 6.3 days (33%), and 4.9 l and 1870 l (49%), respectively. The CL_max was negatively related to plasma albumin, and TCL₅₀ was positively related to aspartate amino transferase (ASAT). Bayesian estimations performed at different POD times indicated that acceptable precisions in individual pharmacokinetic predictions could be obtained after the 15th POD.Conclusion Tacrolimus clearance modelling showed that there was a large variation in individual CL estimates up to the 15th day post-surgery. After this period, the mean error resulting from the Bayesian estimation was strongly decreased and this estimation method could be applicable and should limit tacrolimus monitoring.     

肝移植患者术后口服他克莫司群体药动学研究

目的:考察肝移植患者术后口服他克莫司的群体药动学模型,为临床个体化用药提供参考。方法:回顾性收集天津市第一中心医院18例肝移植患者术后口服他克莫司12 h全血药浓度监测数据145个。运用非线性混合效应模型(nonlinear mixed effect model,NONMEM)建立他克莫司群体药动学模型,并考察了年龄、性别、移植术后天数、血清肌酐等固定效应对药动学参数的影响,得到最终模型方程,最后利用Bayesian反馈得到的个体药动学参数值进行个体化给药方案设计。结果:本次研究建立起了口服他克莫司一级吸收和消除的二房室群体药动学模型,并通过NONMEM模拟程序为1例患者进行了个体化给药设计。结论:NONMEM法建立的模型能较好地估算他克莫司的个体及群体药动学参数,为临床合理使用他克莫司提供参考依据。     

Population pharmacokinetics and Bayesian estimation of tacrolimus exposure in paediatric liver transplant recipients

Aims

The objectives of this study were to develop a population pharmacokinetic (PopPK) model for tacrolimus in paediatric liver transplant patients and determine optimal sampling strategies to estimate tacrolimus exposure accurately.

Methods

Twelve hour intensive pharmacokinetic profiles from 30 patients (age 0.4–18.4 years) receiving tacrolimus orally were analysed. The PopPK model explored the following covariates: weight, age, sex, type of transplant, age of liver donor, liver function tests, albumin, haematocrit, drug interactions, drug formulation and time post-transplantation. Optimal sampling strategies were developed and validated with jackknife.

Results

A two-compartment model with first-order absorption and elimination and lag time described the data. Weight was included on all pharmacokinetic parameters. Typical apparent clearance and central volume of distribution were 12.1 l h⁻¹ and 31.3 l, respectively. The PopPK approach led to the development of optimal sampling strategies, which allowed estimation of tacrolimus pharmacokinetics and area under the concentration–time curve (AUC) on the basis of practical sampling schedules (three or four sampling times within 4 h) with clinically acceptable prediction error limit. The mean bias and precision of the Bayesian vs. reference (trapezoidal) AUCs ranged from −2.8 to −1.9% and from 7.4 to 12.5%, respectively.

Conclusions

The PopPK of tacrolimus and empirical Bayesian estimates represent an accurate and convenient method to predict tacrolimus AUC_(0–12) in paediatric liver transplant recipients, despite high between-subject variability in pharmacokinetics and patient demographics. The developed optimal sampling strategies will allow the undertaking of prospective trials to define the tacrolimus AUC-based therapeutic window and dosing guidelines in this population.     

Evaluation of renal function in transplant patients on tacrolimus therapy

Glomerular filtration rate (GFR), as measured by 24-hour creatinine clearance and clearance of iothalamate, and effective renal plasma flow (ERPF), as measured by the clearance of para-aminohippuric acid (PAH), were evaluated at 2 weeks, 1 month, and 3 months after transplantation in 8 renal transplant patients and at 1 month and 1 year after transplantation in 9 liver transplant patients receiving tacrolimus (Prograf) therapy. In renal transplant patients, there was a significant increase in GFR after transplantation. There was no change in GFR at 1 and 3 months as compared to 2 weeks after transplantation, while ERPF (ml/min/1.73 m2) was lower (p < 0.05) at 3 months (212+/-42) compared to 1 month (306+/-118) after transplantation. In liver transplant patients, GFR and ERPF were below normal despite normal serum creatinine concentrations, but there was no difference in GFR or ERPF at 1 month and 1 year after transplantation. Although below normal, renal function was well preserved in transplant patients while receiving chronic tacrolimus therapy over the study period. Dosage alterations ofrenally eliminated drugs may be required for drugs with a narrow therapeutic index.     

肾移植患者他克莫司血药浓度影响因素的研究进展

他克莫司作为一种强效免疫抑制剂,被广泛应用于肾移植术后的抗排斥治疗。但其治疗窗窄,血药浓度个体差异大,且移植术后各时间段的目标浓度范围不同,需密切监测血药浓度,以期保证疗效,减少不良反应的发生。笔者全面探讨肾移植术后患者他克莫司血药浓度的影响因素,为他克莫司的治疗药物监测和剂量调整提供参考。     

Clinical utility of monitoring tacrolimus blood concentrations in liver transplant patients

The relationship between the dose of tacrolimus, trough tacrolimus blood concentration, and selected clinical endpoints (acute rejection, nephrotoxicity, and other toxicities) were examined in a prospective, multicenter clinical trial to validate the use of an enzyme-linked immunosorbent assay (ELISA) for monitoring whole-blood concentrations of tacrolimus in liver transplant patients. A total of 111 subjects from six transplant centers were evaluated over 12 weeks posttransplantation. In addition to trough tacrolimus blood concentrations, hematocrit, ALT, AST, GGTP, alkaline phosphatase, total bilirubin, serum creatinine, BUN, serum potassium, serum magnesium, blood glucose, and serum albumin were also measured. The relationship between trough tacrolimus blood concentrations and clinical endpoints was analyzed using both a logistic regression model and a Cox proportional hazard model. By logistic regression analysis, a statistically significant (p = 0.0465) relationship between increasing trough tacrolimus blood concentrations and decreasing risk of acute rejection was demonstrated over a 7-day time window. Nephrotoxicity and other toxicities also demonstrated statistically significant relationships with trough tacrolimus blood concentrations. The results of the Cox analysis were consistent with the logistic regression analysis. Using receiver operator characteristic curves, trough tacrolimus concentrations as measured by the ELISA method were able to differentiate the occurrence of nephrotoxicity and toxicity from nonevents. To minimize nephrotoxicity of tacrolimus, it is necessary to maintain trough blood concentrations below 15 ng/ml. This study demonstrates that the ELISA method used to measure tacrolimus blood concentrations in this study provides information of predictive value for managing the risk of nephrotoxicity, other toxicity, and rejection in liver transplant patients.     

Analysis of whole blood tacrolimus concentrations in liver transplant patients exhibiting impaired liver function

In transplant patients with impaired liver function, HPLC methodologies have been suggested for monitoring whole blood tacrolimus concentrations because of the reported inaccuracy of immunoassay for whole blood tacrolimus concentrations. One hundred fifty whole blood samples from 50 subjects enrolled in a multicenter liver transplant trial were chosen for HPLC/MS/MS analysis without consideration of the clinical status of the patient at the time of sampling. These samples were chosen to represent the sampling intervals during the 12-week posttransplantation period. Retrospectively, the authors identified a subset of 39 samples from 27 subjects exhibiting impaired liver function as demonstrated by bilirubin concentrations > 3.0 mg/dL (mean +/-SD = 7.5 +/- 5.6 mg/dL). The authors compared the agreement of concentrations obtained from the PRO-Trac II ELISA and HPLC/MS/MS by least squares linear regression analysis and Bland/Altman analysis, in this subset against the agreement of concentrations for 76 samples with normal bilirubin. In the samples obtained from patients with impaired liver function the resulting regression equation was: ELISA = 1.19(HPLC) + 0.7; r = 0.9. The mean difference (HPLC/MS/MS - ELISA) was -2.5 ng/mL +/- 2.9 ng/mL (mean +/- SD). While 71% of samples agreed within 3 ng/mL, 3% (n = 1) exhibited a difference >10 ng/ml. The corresponding evaluation of the samples with normal bilirubin concentrations resulted in the regression equation ELISA = 0.96(HPLC) + 0.9; r = 0.9, and a mean difference of -0.6 ng/mL +/- 2.3 ng/mL. The authors conclude that while a small subset of patients with cholestasis may require closer evaluation with a more specific methodology, the majority of the patients may be satisfactorily monitored with the PRO-Trac II ELISA.     

Schisandra extract elevates concentration of tacrolimus in blood of liver transplant patients

Jiang W, Wang X, Xu X, Kong L. Effect of Schisandra sphenanthera extract on the concentration of tacrolimus in the blood of liver transplant patients. Int J Clin Pharmacol Ther 2010; 48: 224–9.     

Immunosuppressive therapy for paediatric transplant patients: pharmacokinetic considerations

Immunosuppressive therapy in paediatric transplant recipients is changing as a consequence of the increasing number of available immunosuppressive agents. Generic and other new formulations are now emerging onto the market, clinical experience is growing, and it is expected that clinicians should tailor immunosuppressive protocols to individual patients by optimising dosages and drugs according to the maturation and clinical status of the child. Most information about the clinical pharmacokinetics of immunosuppressive drugs in paediatrics is centred on cyclosporin, tacrolimus and mycophenolate mofetil in renal and liver transplant recipients; data regarding other immunosuppressants and transplant types are limited. Although the clinical pharmacokinetics of these drugs in paediatric transplant recipients are still under investigation, it is evident that the pharmacokinetic parameters observed in adults may not be applicable to children, especially in younger age groups. In general, patients younger than 5 years old show higher clearance rates irrespective of the organ transplanted or drug used. Another important factor that frequently affects clearance in this patient population is the post-transplant time. In accordance with these findings, and in contrast with the usual under-dosage in children, the need for higher dosages in younger recipients and during the early post-transplant period seems evident. To achieve the best compromise between prevention of rejection and toxicity, dosage individualisation is required and this can be achieved through therapeutic drug monitoring (TDM). This approach is particularly useful to ensure the cost-effective management of paediatric transplant recipients in whom the pharmacokinetic behaviour, target concentrations for clinical use and optimal dosage strategies of a particular drug may not yet be well defined. Although TDM may be a tool for improving immunosuppressive therapy, there is little information concerning its positive contribution to clinical events, including outcomes, for paediatric patients. Substantial information to support the use of TDM exists for cyclosporin and, to a lesser extent, for tacrolimus, but a diversity of options affects their implementation in the clinical setting. The role of TDM in therapy with mycophenolate mofetil and sirolimus has yet to be defined regarding both methods and clinical indications. Pharmacodynamic monitoring appears more suited to other immunosuppressants such as azathioprine, corticosteroids and monoclonal or polyclonal antibodies. If coupled with pharmacokinetic measurements, such monitoring would allow earlier and more precise optimisation of therapy. Very few population pharmacokinetic studies have been carried out in paediatric transplant patients. This type of study is needed so that techniques such as Bayesian forecasting can be applied to optimise immunosuppressive therapy in paediatric transplant patients.     

Impact of MDR1 and CYP3A5 on the oral clearance of tacrolimus and tacrolimus-related renal dysfunction in adult living-donor liver transplant patients

OBJECTIVE: The potential influence of the multidrug resistance 1 (MDR1) gene and the cytochrome P450 (CYP) genes, CYP3A4 and CYP3A5, on the oral clearance (CL/F) of tacrolimus in adult living-donor liver transplant patients was examined. Furthermore, the development of renal dysfunction was analyzed in relation to the CYP3A5 genotype. METHODS: Sixty de novo adult liver transplant patients receiving tacrolimus were enrolled in this study. The effects of various covariates (including intestinal and hepatic mRNA levels of MDR1 and CYP3A4, measured in each tissue taken at the time of transplantation, and the CYP3A5*3 polymorphism) on CL/F during the first 50 days after surgery were investigated with the nonlinear mixed-effects modeling program. RESULTS: CL/F increased linearly until postoperative day 14, and thereafter reached a steady state. The initial CL/F immediately after liver transplantation was significantly affected by the intestinal MDR1 mRNA level (P<0.005). Furthermore, patients carrying the CYP3A5*1 allele in the native intestine, but not in the graft liver, showed a 1.47 times higher (95% confidence interval, 1.17-1.77 times, P<0.005) recovery of CL/F with time than patients having the intestinal CYP3A5*3/*3 genotype. The cumulative incidence of renal dysfunction within 1 year after transplantation, evaluated by the Kaplan-Meier method, was significantly associated with the recipient's but not donor's CYP3A5 genotype (*1/*1 and *1/*3 vs. *3/*3: recipient, 17 vs. 46%, P<0.05; donor, 35 vs. 38%, P=0.81). CONCLUSION: These findings suggest that the CYP3A5*1 genotype as well as the MDR1 mRNA level in enterocytes contributes to interindividual variation in the CL/F of tacrolimus in adult recipients early after living-donor liver transplantation. Furthermore, CYP3A5 in the kidney may play a protective role in the development of tacrolimus-related nephrotoxicity.     

Mycophenolate mofetil pharmacokinetics in transplant patients receiving cyclosporine or tacrolimus in combination therapy

Mycophenolate mofetil is a highly effective immunosuppressant drug used in the prophylaxis of organ rejection in combination with cyclosporine or tacrolimus and corticosteroids. The present study is a retrospective data analysis of the routinely estimated mycophenolic acid plasma trough levels in 60 transplant patients (kidney, n = 49; lung, n = 11) receiving mycophenolate mofetil in combination with prednisone and cyclosporine (n = 45) or tacrolimus (n = 15). Coadministration of cyclosporine instead of tacrolimus resulted in a significant increase of median (range) of the ratio of dose-to-concentration 0.92 (0.11-8.33) (n=167) versus 0.38 (0.11-14.28) (n = 66); P < 0.0001. No correlation was seen between mycophenolate mofetil dose and mycophenolic acid trough concentrations. The dose-to-concentration in cyclosporine-treated patients increased significantly (P<0.0001) as the cyclosporine level increased, suggesting a possible interaction between mycophenolate mofetil and cyclosporine. No correlation was seen between dose-to-concentration and tacrolimus blood levels (P x 0.215). Further studies are necessary to investigate this issue.     

Population pharmacokinetics of tacrolimus in whole blood and plasma in asian liver transplant patients

OBJECTIVES: The objectives of this study were to develop population pharmacokinetic models of tacrolimus in an Asian population with whole blood and plasma drug concentration data, to compare the variability of the pharmacokinetic parameters in these two matrices and to search for the main patient characteristics that explain the variability in pharmacokinetic parameters. STUDY DESIGN: Prospective pharmacokinetic assessment followed by model fitting. PATIENTS: Whole blood samples from 31 liver transplant patients in a local hospital receiving oral tacrolimus as part of their immunosuppressive therapy were assessed. Plasma samples from 29 of the 31 patients were also evaluated. Concentrations of tacrolimus in whole blood and plasma were determined by an electrospray high-performance liquid chromatography with tandem mass spectrometry. Two hundred and thirteen whole blood and 157 plasma tacrolimus concentrations were used for building two nonlinear mixed-effects population models to describe the disposition of tacrolimus in whole blood and plasma, respectively. Covariates that were investigated included demographic characteristics, biological markers of liver and renal functions, corticosteroid dose and haematological parameter. RESULTS: A one-compartment model was used to describe the whole blood and plasma concentration-time data of tacrolimus after oral administration. For the whole blood population model, the population estimates of the first-order absorption rate constant (k(a)), apparent clearance based on whole blood concentration after oral administration (CL(B)/F) and apparent volume of distribution based on whole blood concentrations after oral administration (V(d,B)/F) were 2.08h(-1), 14.1 L/h and 217L, respectively. The coefficient of variations (CVs) of interpatient variabilities in CL(B)/F and V(d,B)/F were 65.7% and 63.8%, respectively. Bodyweight, liver and renal function influenced CL(B)/F, while height and haematocrit influenced V(d,B)/F. The residual (unexplained) variability was 34.8%. For the plasma population model, the population estimates of the k(a), apparent clearance based on plasma concentrations after oral administration (CL(P)/F) and apparent volume of distribution based on plasma concentrations after oral administration (V(d,P)/F) were 5.21h(-1), 537 L/h and 563L, respectively. The CVs of interpatient variabilities in CL(P)/F and V(d,P)/F were 96.0% and 105.4%, respectively. Bodyweight was found to influence CL(P)/F, while the erythrocyte-to-plasma concentration ratio influenced V(d,P)/F. The residual (unexplained) variability was 49.8% at the mean plasma concentration of 1.1 ng/mL. CONCLUSIONS: Whole blood and plasma population pharmacokinetic models of tacrolimus in Asian adult and paediatric liver transplant patients were developed using prospective data in a clinical setting. This has identified and quantified sources of interindividual variability in CL(B)/F, V(d,B)/F, CL(P)/F and V(d,P)/F of tacrolimus in Asian liver transplant patients. Information derived from the whole blood population model may subsequently be used by clinicians for dosage individualisation through Bayesian forecasting.     

A population pharmacokinetic study of tacrolimus in healthy Chinese volunteers and liver transplant patients

Aim:

To develop a population pharmacokinetic (PopPK) model of tacrolimus in healthy Chinese volunteers and liver transplant recipients for investigating the difference between the populations, and for potential individualized medication.

Methods:

A set of 1100 sparse trough concentration data points from 112 orthotopic liver transplant recipients, as well as 851 dense data points from 40 healthy volunteers receiving a single dose of tacrolimus (2 mg, po) were collected. PopPK model of tacrolimus was constructed using the program NONMEM. Related covariates such as age, hepatic and renal functions that were potentially associated with tacrolimus disposition were evaluated. The final model was validated using bootstrapping and a visual predictive check.

Results:

A two-compartment model of tacrolimus could best describe the data from the two populations. The final model including two covariates, population (liver transplant recipients or volunteers) and serum ALT (alanine aminotransferase) level, was verified and adequately described the pharmacokinetic characteristics of tacrolimus. The estimates of V2/F, Q/F and V3/F were 22.7 L, 76.3 L/h and 916 L, respectively. The estimated CL/F in the volunteers and liver transplant recipients was 32.8 and 18.4 L/h, respectively. Serum ALT level was inversely related to CL/F, whereas age did not influence CL/F. Thus, the elderly (≥65 years) and adult (<65 years) groups in the liver transplant recipients showed no significant difference in the clearance of tacrolimus.

Conclusion:

Compared with using the sparse data only, the integrating modeling technique combining sparse data from the patients and dense data from the healthy volunteers improved the PopPK analysis of tacrolimus.     

A comparison of the pharmacokinetics of tacrolimus and microemulsified cyclosporin in paediatric renal transplant recipients

Objective Our objective was to identify common factors that determine the dose of tacrolimus and microemulsified cyclosporin in paediatric renal transplant recipients.Methods The concentration profiles of tacrolimus and cyclosporin in blood were determined in 68 children who had received a renal transplant. To avoid disruption of therapy, measurements were made at 2-h intervals over an 8-h period during normal dosing regimens. Direct comparisons of the two drugs were made in 14 of the subjects who were switched from cyclosporin to tacrolimus.Results The ratio of peak to trough levels for tacrolimus was approximately twofold compared with over threefold for cyclosporin. Area under the curve (AUC) for tacrolimus remained relatively constant in each 2-h period of the dosage interval compared with the AUC for cyclosporin, which varied by over twofold in the same time period. In the 14 subjects who received both drugs, there was a poor correlation between C₂/C₀, C₂, t_1/2 and AUC for tacrolimus and cyclosporin in the same individual. In a multivariate analysis, there were no significant associations for tacrolimus concentrations, AUC or C₂/C₀ with age, gender, calcium-channel blocker, quinolone or statin. For cyclosporin, there was some association for AUC with gender and quinolone use and a weak association with calcium-channel blocker or statin use.Conclusions Tacrolimus and microemulsified cyclosporin display a wide intra- and inter-individual variation in pharmacokinetic properties in young subjects. In the case of absorption represented by the peak-trough ratios, the values for tacrolimus are significantly less than those obtained with cyclosporin. The pharmacokinetic parameters obtained for one of these agents is not predictive for the behaviour of the other in young renal transplant recipients.