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.     

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 and bioavailability of tacrolimus in kidney transplant patients

What is already known about this subject

• In spite of its success in ensuring graft survival, therapeutic use of tacrolimus is complicated by its narrow therapeutic index and wide intra- and interpatient variability.
• Some studies of population pharmacokinetics have already been conducted in liver transplant recipients and in paediatric patients.

What this study adds

• Our work determined population pharmacokinetic parameters, in particular bioavailability, in kidney transplant recipients and the relative importance of factors influencing the disposition of tacrolimus.
• Clearance was modelled and days postoperation and corticosteroids dose were significant covariates.

Aims

The use of tacrolimus is complicated by its narrow therapeutic index and wide intra- and interpatient variability. Tacrolimus population pharmacokinetics, including bioavailability, were investigated in an adult kidney transplant cohort to identify patient characteristics that influence pharmacokinetics.

Methods

The database (drug monitoring data) included 83 adult kidney transplant recipients and analysis was performed by a population approach with NONMEM. Data were collected during the first months after transplantation. Patients were administered oral or intravenous tacrolimus as part of a triple immunosuppressive regimen that also included mycophenolate mofetil and corticosteroids. Subsequent doses were adjusted on the basis of clinical evidence of efficacy and toxicity as in routine therapeutic drug monitoring.

Results

A one compartment open model with linear absorption and elimination adequately described the data. The typical value of minimal clearance was 1.8 ± 0.2 l h⁻¹. Clearance increased with time post transplantation to reach 50% of maximal value after 3.8 ± 0.5 days, with a maximal value of 5.6 l h⁻¹. Moreover clearance increased by approximately 1.6 fold (range 0.5–1.6) if the dose of prednisone was >25 mg. The typical value for volume of distribution, V, (98 ± 13 l kg⁻¹) was similar to reported values in kidney transplant patients. The oral bioavailability of tacrolimus was poor and ranged from 11.2 to 19.1%. No covariates significantly influenced V or F.

Conclusions

The number of days postoperation and corticosteroid dose were significant covariates influencing tacrolimus clearance.     

他克莫司在中国肾移植患者中的群体药物动力学研究

本研究旨在考察口服他克莫司(tacrolimus)在中国肾移植患者中的群体药物动力学特征并探讨群体药物动力学参数和相关因素间的关系。研究中回顾性搜集了58例肾移植患者的802份他克莫司稳态全血样本资料。患者随机分为模型建立组(41例)和模型验证组(17例)。用非线性混合效应模型(NONMEM)程序中的一级评估法(first-order estimation，FO)对模型建立组的数据进行分析。计算清除率(CL/F)、表观分布容积(V/F)的群体典型值，定量评价人口统计学指标、生化指标和合并用药等固定效应因素对药物动力学参数的影响。单室一级吸收和消除模型能够较好地拟合数据。最终模型包含了移植术后时间(POD)、红细胞压积(HCT)、谷草转氨酶(AST)、合并使用佩尔地平(NICA)和地尔硫(DIL)等对CL/F的影响。用模型验证组数据进行验证的结果表明观测值和模型预测值之间没有明显的偏倚，模型的稳定性和准确度较好。CL/F和V/F的群体典型值分别为21.7 L·h^-1和241 L；相应的个体间变异分别为41.6%和49.7%。观测值与预测值之间的残差SD为2.19 μg·L^-1。本文建立的模型可以为临床他克莫司剂量选择提供一定参考。     

Population pharmacokinetics of tamsulosin hydrochloride in paediatric patients with neuropathic and non-neuropathic bladder

AIMS

The main objective of this study was to characterize the population pharmacokinetics of tamsulosin hydrochloride (HCl) in paediatric patients with neuropathic and non-neuropathic bladder. A secondary objective was to compare the pharmacokinetics in paediatric patients and adults.

METHODS

Tamsulosin HCl plasma concentrations in 1082 plasma samples from 189 paediatric patients (age range 2–16 years) were analyzed with NONMEM, applying a one compartment model with first-order absorption. Based on the principles of allometry, body weight was incorporated in the base model, along with fixed allometric exponents. Covariate analysis was performed by means of a stepwise forward inclusion and backward elimination procedure. Simulations based on the final model were used to compare the pharmacokinetics with those in adults.

RESULTS

Beside the priori-implemented body weight, only α₁-acid glycoprotein had an effect on both apparent clearance and apparent volume of distribution. No other investigated covariates, including gender, age, race, patient population and concomitant therapy with anti-cholinergics, significantly affected the pharmacokinetics of tamsulosin HCl (P < 0.001). The results of simulations indicated that the exposure in 12.5 kg paediatric patients was 3.5–4.3 fold higher than that in 70.0 kg adults. After a weight-based dose administration, the exposure in paediatric patients was comparable with that in healthy adults.

CONCLUSIONS

A population pharmacokinetic model of tamsulosin HCl in paediatric patients was established and it described the data well. There was no major difference in the pharmacokinetics of tamsulosin HCl between paediatric patients (age range 2–16 years) and adults when the effect of body weight was taken into consideration.     

成人肝移植术后他克莫司群体药动学研究

目的：应用非线性混和效应模型考察中国肝移植患者他克莫司群体药动学特征。方法：回顾收集天津市第一中心医院成人肝移患者57例,1 094个他克莫司谷浓度点,验证组患者10例,183个谷浓度点。采用一房室模型,分析处理数据,采用NPDE、Bootstrap和外部验证的方法对模型进行评估。结果：最终模型显示血红蛋白（HGB）和术后时间（POD）为影响清除率的主要因素。药动学参数的群体典型值：清除率（CL/F）估算值为19.8 L·h^-1,表观分布容积估算值为597 L。模型评价显示该模型及所估算参数稳定。结论：本研究所建立的成人肝移植受者口服他克莫司的群体药动学模型能较好地估算患者的个体及群体药动学参数,为今后肝移植患者个体化给药方案的制订提供相关参考。     

Population pharmacokinetics of melphalan in paediatric blood or marrow transplant recipients

AIM: To develop a population pharmacokinetic model for melphalan in children with malignant diseases and to evaluate limited sampling strategies for melphalan. METHODS: Melphalan concentration data following a single intravenous dose were collected from 59 children with malignant diseases aged between 0.3 and 18 years. The data were split into two sets: the model development dataset (39 children, 571 concentration observations) and the model validation dataset (20 children, 277 concentration observations). Population pharmacokinetic modelling was performed with the NONMEM software. Stepwise multiple linear regression was used to develop a limited sampling model for melphalan. RESULTS: A two-compartment model was fitted to the concentration-vs.-time data. The following covariate population pharmacokinetic models were obtained: (i) Clearance (l h(-1)) = 0.34.WT - 3.17.CPT + 0.0377.GFR, where WT = weight (kg), CPT = prior carboplatin therapy (0 = no, 1 = yes), and GFR = glomerular filtration rate (ml min(-1) 1.73 m(-2)); (ii) Volume of distribution (l) = 1.12 + 0.178.WT. Interpatient variability (coefficient of variation) was 27.3% for clearance and 33.8% for volume of distribution. There was insignificant bias and imprecision between observed and model-predicted melphalan concentrations in the validation dataset. A three-sample limited sampling model was developed which adequately predicted the area under the concentration-time curve (AUC) in the development and validation datasets. CONCLUSIONS: A population pharmacokinetic model for melphalan has been developed and validated and may now be used in conjunction with pharmacodynamic data to develop safe and effective dosing guidelines in children with malignant diseases.     

Dosing recommendations based on population pharmacokinetics of tacrolimus in Mexican adult patients with kidney transplant

The aim of this study was to perform a population pharmacokinetic analysis of tacrolimus in Mexican adult kidney transplant patients to analyse the influence of clinical and genetic covariates to propose a dosage regimen. Kidney transplant patients (>18 years old) receiving oral tacrolimus treatment were included in the current study. The population pharmacokinetic model was built using a one‐compartment model and the First Order Conditional Estimation method with Interaction (FOCEI via NONMEM v.7.3.). A total of 600 tacrolimus trough blood concentrations from 52 kidney transplant patients were analysed. Tacrolimus clearances were 26, 18.8 and 12.3 L/h, for patients with genetic polymorphisms CYP3A5*1*1, *1*3 and *3*3, respectively. The influence of haematocrit was inversely related to tacrolimus clearance, following an allometric power function. Total volume of distribution was 604 L. Interindividual variability associated with tacrolimus clearance and distribution volume for the final model was 33 and 63%, respectively, with a residual error of 2.5 ng/mL. Relative bioavailability was calculated between generic formulations A (0.53) and B (1) of tacrolimus. Internal validation was performed through bootstrap analysis to evaluate the stability of the final model; external validation was performed in a new group of patients (n = 13) to estimate residual errors on basic (57.8%) and final (34.8%) models. Finally, stochastic simulations were performed to propose a dosage regimen based on haematocrit, CYP3A5 genotype and generic formulation of tacrolimus. A stable and predictive population pharmacokinetic model of tacrolimus was developed for Mexican adult kidney transplant patients; additionally, the proposed dosage regimen of tacrolimus should be prospectively validated.     

肝移植受者他克莫司治疗窗浓度的初步确定

目的寻求适合国人肝移植受者他克莫司理想治疗窗浓度范围.方法应用微粒子酶免分析法测定69例肝移植患者口服他克莫司后12 h的血药谷浓度,并观察排斥反应的发生及药物的不良反应.结果他克莫司的血药浓度,术后第1个月为(13.1±2.0)μg*L-1,第2,3个月为(9.2±1.7)μg*L-1,3个月后为(6.3±1.2)μg*L-1,比较各时期全血他克莫司谷浓度,差异均有极显著性(P＜0.01).术后发生排斥反应64例次,不良反应73例次.结论他克莫司治疗窗浓度范围术后第1个月为10～15 μg*L-1,第2、3个月为7.0～11 μg*L-1,3个月后为5.0～8.0 μg*L-1维持,此浓度范围既能达到满意的免疫抑制效果,又能减少他克莫司的不良反应.     

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.     

他克莫司群体药动学在儿童肝移植中的研究进展

他克莫司治疗窗窄，药动学个体差异大，临床难以建立儿童受者的个体化治疗方案。群体药动学（PPK）在个体化给药研究方面有巨大优势。为了实现他克莫司在儿童肝移植受者中的个体化治疗，国内外学者致力于儿童肝移植受者的PPK研究，但各研究的结果存在差异。本文通过检索PubMed、Web of Science及Scopus数据库中的相关文献，着重分析了既往他克莫司PPK在儿童肝移植受者中的研究，总结影响他克莫司PPK参数的主要因素，期望应用PPK方法为构建儿童肝移植受者的个体化治疗方案奠定基础。     

Pharmacokinetics of tacrolimus converted from twice-daily formulation to once-daily formulation in Chinese stable liver transplant recipients

Aim:

To evaluate the pharmacokinetics of tacrolimus in Chinese stable liver transplant recipients converted from immediate release (IR) tacrolimus-based immunosuppression to modified release (MR) tacrolimus-based immunosuppression.

Methods:

Open-label, multi-center study with a one-way conversion design was conducted. Eighty-three stable liver recipients (6–24 months post-transplant) with normal renal and stable hepatic function were converted from IR tacrolimus twice-daily treatment to MR tacrolimus once-daily treatment on a 1:1 (mg: mg) total daily dose basis. Twenty-four hour pharmacokinetic studies were carried out on d 0 (pre-conversion), d 1, and d 84 (post-conversion).

Results:

The area under the blood concentration–time curve of MR tacrolimus from 0 to 24 h (AUC_0–24) on d 1 was comparable to that of IR tacrolimus on d 0, with a 90% confidence interval (CI) for MR/IR tacrolimus of 92%–97%. The AUC_0–24 value for MR tacrolimus on d 84 with the daily dose increased by 14% was approximately 17% lower than that for IR tacrolimus. The 90% CI was 77%–90%, outside the bioequivalence range of 80%–125%. There was a good correlation between AUC_0–24 and concentration at 24 h (C₂₄) for IR tacrolimus (d 0, r=0.930) and MR tacrolimus (d 1, r=0.936; d 84, r=0.903).

Conclusion:

The exposure to tacrolimus when administered MR tacrolimus once daily is not equivalent to that for IR tacrolimus twice daily after an 84-day conversion in Chinese stable liver transplant recipients. The dose should be adjusted on the basis of trough levels. The therapeutic drug monitoring for patients treated with IR tacrolimus is considered to be applicable to MR tacrolimus.     

老年心衰患者口服地高辛群体药动学模型的建立

目的:应用非线性混合效应模型计算国人老年心衰患者口服地高辛(digxion)群体药动学参数,以促进个体化给药。方法:采用荧光偏振免疫法(FPIA)测定84例老年患者120例次地高辛的血清浓度并收集相关临床指标,运用NONMEM软件建立群体药动学模型。结果:地高辛的药动学符合一室线性开放模型,固定效应参数中,体质量、剂量、血肌酐及尿素氮对参数有影响。最终回归模型中地高辛血药浓度估算值与实测浓度间线性关系良好。结论:用群体药动学模型分析常规监测数据可为老年患者个体化给药提供依据。     

比较他克莫司缓释制剂与普通制剂在中国肾移植患者的药代动力学

目的比较中国肾移植患者重复剂量口服他克莫司(免疫抑制剂)缓释制剂和普通制剂的药代动力学。方法用多中心、随机、开放、平行对照的临床试验。受试者为18～70岁成年初次肾移植患者,按1∶1随机分成他克莫司缓释制剂组,每天1次;普通制剂组,每天2次。患者于术后分别口服他克莫司缓释胶囊,在连续给药后(56±5)d进行24 h的药代动力学比较研究,用液相色谱串联质谱法测定全血中他克莫司浓度。结果术后56 d,他克莫司缓释制剂组(n=17)和普通制剂组(n=15)给药剂量分别为(0.12±0.05)和(0.10±0.04)mg.kg-1.d-1,药代动力学参数tmax分别为(3.10±3.00),(1.80±0.90)h,Cmax分别为(13.20±4.20),(11.80±3.80)ng.mL-1,C24分别为(4.40±1.30),(4.50±1.20)ng.mL-1,AUC0-24分别为(171.70±49.90),(145.10±29.30)ng.mL-1.h。AUC0-24与C24的相关系数,缓释制剂为0.87,普通制剂为0.62。结论初次肾移植患者术后56 d,他克莫司缓释制剂的日剂量比普通制剂高23%,体内暴...     

Factors affecting variability in distribution of tacrolimus in liver transplant recipients

AIMS: Therapeutic 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. METHODS: Blood and plasma distribution of 3H-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. RESULTS: In 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 lymphocytes (0.8 +/- 0.4 vs 0.3 +/- 0.1%, P = 0.012) and estimated unbound concentration (0.42 +/- 0.21 ng l-1vs 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 alpha1-acid glycoprotein and high density lipoprotein cholesterol concentrations. CONCLUSIONS: Tacrolimus 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.     

Population pharmacokinetics of mycophenolic acid and dose optimization with limited sampling strategy in liver transplant children

AIMS

The aims were to estimate the mycophenolic acid (MPA) population pharmacokinetic parameters in paediatric liver transplant recipients, to identify the factors affecting MPA pharmacokinetics and to develop a limited sampling strategy to estimate individual MPA AUC(0,12 h).

METHODS

Twenty-eight children, 1.1 to 18.0 years old, received oral mycophenolate mofetil (MMF) therapy combined with either tacrolimus (n= 23) or ciclosporin (n= 5). The population parameters were estimated from a model-building set of 16 intensive pharmacokinetic datasets obtained from 16 children. The data were analyzed by nonlinear mixed effect modelling, using a one compartment model with first order absorption and first order elimination and random effects on the absorption rate (k_a), the apparent volume of distribution (V/F) and apparent clearance (CL/F).

RESULTS

Two covariates, time since transplantation (≤ and >6 months) and age affected MPA pharmacokinetics. k_a, estimated at 1.7 h⁻¹ at age 8.7 years, exhibited large interindividual variability (308%). V/F, estimated at 64.7 l, increased about 2.3 times in children during the immediate post transplantation period. This increase was due to the increase in the unbound MPA fraction caused by the low albumin concentration. CL/F was estimated at 12.7 l h⁻¹. To estimate individual AUC(0,12 h), the pharmacokinetic parameters obtained with the final model, including covariates, were coded in Adapt II® software, using the Bayesian approach. The AUC(0,12 h) estimated from concentrations measured 0, 1 and 4 h after administration of MMF did not differ from reference values.

CONCLUSIONS

This study allowed the estimation of the population pharmacokinetic MPA parameters. A simple sampling procedure is suggested to help to optimize pediatric patient care.     

初步探讨他克莫司(FK506)对肝移植受者的治疗窗浓度及其与年龄、性别的关系

目的:探讨适合我国肝移植受者他克莫司理想治疗窗浓度范围及其与年龄、性别的关系.方法:应用微粒子酶免分析法测定75例不同年龄、性别肝移植受者口服他克莫司后12h的血药谷浓度,并观察排斥反应的发生及药物不良反应.结果:他克莫司的血药浓度,术后第1个月为11.3～15.5 ngmL-1,第2、3个月为7.8～10.7 ngmL-1,3个月后为5.3～7.8 ngmL-1,比较不同时期全血他克莫司的谷浓度,均有显著差异(P<0.01).术后发生排斥反应64例次,不良反应73例次.结论:建议他克莫司治疗窗浓度范围改为:术后第1个月为10～15 ngmL-1,第2,3个月为7.0～11 ngmL-1,3月后为5.0～8.0 ngmL-1维持;此浓度范围既能达到满意的免疫抑制效果,又能减少他克莫司的不良反应,并观察到其浓度与年龄、性别有一定的相关性.     

Population pharmacokinetic analysis of tacrolimus in Mexican paediatric renal transplant patients: role of CYP3A5 genotype and formulation

Aims

The aims of this study were (i) to develop a population pharmacokinetic (PK) model of tacrolimus in a Mexican renal transplant paediatric population (n = 53) and (ii) to test the influence of different covariates on its PK properties to facilitate dose individualization.

Methods

Population PK and variability parameters were estimated from whole blood drug concentration profiles obtained at steady-state using the non-linear mixed effect modelling software NONMEM® Version 7.2.

Results

Tacrolimus PK profiles exhibited high inter-patient variability (IPV). A two compartment model with first order input and elimination described the tacrolimus PK profiles in the studied population. The relationship between CYP3A5 genotype and tacrolimus CL/F was included in the final model. CL/F in CYP3A5*1/*1 and *1/*3 carriers was approximately 2- and 1.5-fold higher than in CYP3A5*3/*3 carriers (non-expressers), respectively, and explained almost the entire IPV in CL/F. Other covariates retained in the final model were the tacrolimus dose and formulation type. Limustin® showed markedly lower concentrations than the rest of the formulations.

Conclusions

Population PK modelling of tacrolimus in paediatric renal transplant recipients identified the tacrolimus formulation type as a significant covariate affecting the blood concentrations and confirmed the previously reported significant effect of CYP3A5 genotype on CL/F. It allowed the design of a proposed dosage based on the final model that is expected to help to improve tacrolimus dosing.