Importance of hematocrit for a tacrolimus target concentration strategy

Prospective study of the changes in pharmacokinetics of immunosuppressive medications after laparoscopic sleeve gastrectomy

Laparoscopic sleeve gastrectomy induces weight loss via the creation of a restrictive gastric tube for early satiety and is associated with an accelerated gastric transit time. A prospective, single-dose pharmacokinetic study was performed, prior to and after laparoscopic sleeve gastrectomy, for tacrolimus, extended-release tacrolimus, mycophenolate mofetil, and enteric-coated mycophenolate sodium. The study included 12 morbidly obese patients in chronic renal failure. The median decrease in body mass index was 8.8 kg/m² with an excess body weight loss of 54.9%. The AUC₂₄ of all drugs were increased after laparoscopic sleeve gastrectomy by 46%, 55%, 77%, and 74%, respectively. The maximum concentrations were increased for tacrolimus, extended-release tacrolimus, and mycophenolate mofetil by 43%, 46%, and 65%. The apparent total clearances were decreased for tacrolimus, mycophenolate mofetil, and enteric-coated mycophenolate sodium by 36%, 57%, and 38%. Laparoscopic sleeve gastrectomy can be associated with significant changes in pharmacokinetics of the drugs evaluated. The mechanism is likely decreased apparent drug clearance due to an increased drug exposure (from a more distal site of intestinal absorption with decreased intestinal metabolism), or decreased clearance (liver metabolism). Adapting the monitoring of immunosuppression will be important to avoid overdosing and potential side effects.

Toward a robust tool for pharmacokinetic-based personalization of treatment with tacrolimus in solid organ transplantation: A model-based meta-analysis approach

AIMS

The objective of this study is to develop a generic model for tacrolimus pharmacokinetics modelling using a meta-analysis approach, that could serve as a first step towards a prediction tool to inform pharmacokinetics-based optimal dosing of tacrolimus in different populations and indications.

METHODS

A systematic literature review was performed and a meta-model developed with NONMEM software using a top-down approach. Historical (previously published) data were used for model development and qualification. In-house individual rich and sparse tacrolimus blood concentration profiles from adult and paediatric kidney, liver, lung and heart transplant patients were used for model validation. Model validation was based on successful numerical convergence, adequate precision in parameter estimation, acceptable goodness of fit with respect to measured blood concentrations with no indication of bias, and acceptable performance of visual predictive checks. External validation was performed by fitting the model to independent data from 3 external cohorts and remaining previously published studies.

RESULTS

A total of 76 models were found relevant for meta-model building from the literature and the related parameters recorded. The meta-model developed using patient level data was structurally a 2-compartment model with first-order absorption, absorption lag time and first-time varying elimination. Population values for clearance, intercompartmental clearance, central and peripheral volume were 22.5 L/h, 24.2 L/h, 246.2 L and 109.9 L, respectively. The absorption first-order rate and the lag time were fixed to 3.37/h and 0.33 hours, respectively. Transplanted organ and time after transplantation were found to influence drug apparent clearance whereas body weight influenced both the apparent volume of distribution and the apparent clearance. The model displayed good results as regards the internal and external validation.

CONCLUSION

A meta-model was successfully developed for tacrolimus in solid organ transplantation that can be used as a basis for the prediction of concentrations in different groups of patients, and eventually for effective dose individualization in different subgroups of the population.

Population Pharmacokinetic Analysis of Immediate-Release Oral Tacrolimus Co-administered with Mycophenolate Mofetil in Corticosteroid-Free Adult Kidney Transplant Recipients

BACKGROUND AND OBJECTIVE

Tacrolimus is the mainstay calcineurin inhibitor frequently administered with mycophenolic acid with or without corticosteroids to prevent graft rejection in adult kidney transplant recipients. The primary objective of this study was to develop and evaluate a population pharmacokinetic model characterizing immediate-release oral tacrolimus co-administered with mycophenolate mofetil (a pro-drug of mycophenolic acid) in adult kidney transplant recipients on corticosteroid-free regimens. The secondary objective was to investigate the effects of clinical covariates on the pharmacokinetics of tacrolimus, emphasizing the interacting effects of mycophenolic acid.

METHODS

Population modeling and evaluation were conducted with Monolix (Suite-2018R1) using the stochastic approximation expectation-maximization algorithm in 49 adult subjects (a total of 320 tacrolimus whole-blood concentrations). Effects of clinical variables on tacrolimus pharmacokinetics were determined by population covariate modeling, regression modeling, and categorical analyses.

RESULTS

A two-compartment, first-order absorption with a lag-time, linear elimination, and constant error model best represented the population pharmacokinetics of tacrolimus. The apparent clearance value for tacrolimus was 17.9 l/h (6.95% relative standard error) in our model, which is lower compared with similar subjects on corticosteroid-based therapy. The glomerular filtration rate had significant effects on the apparent clearance and central compartment volume of distribution. Conversely, mycophenolic acid did not affect the apparent clearance of tacrolimus.

CONCLUSION

We have developed and internally evaluated a novel population pharmacokinetic model for tacrolimus co-administered with mycophenolate mofetil in corticosteroid-free adult kidney transplant patients. These findings are clinically important and provide further reasons for conducting therapeutic drug monitoring in this specific population.

Tacrolimus Levels in the Prophylaxis of Acute Graft-Versus-Host Disease in the Chinese Early After Hematopoietic Stem Cell Transplantation

BACKGROUND

Tacrolimus has been widely accepted as the backbone of acute graft-versus-host disease (aGVHD) prophylaxis in allogeneic hematopoietic stem cell transplantation (alloHSCT). The present work evaluated whether tacrolimus concentrations early after transplant correlate with the incidence of aGVHD in Chinese alloHSCT recipients.

METHODS

One hundred four Chinese alloHSCT recipients were included in this retrospective study. All patients received standard prophylaxis with tacrolimus and short-term methotrexate. Blood samples were taken at steady-state for those on i.v. tacrolimus (Cv) or predose (C0) and 2 hours after the last oral dose (C2).

RESULTS

In the first 8 weeks after alloHSCT, significant variability in Cv, C0, and C2 of Chinese patients was observed. It was found that higher tacrolimus C0 and C2 values tended to be associated with a reduced risk of aGVHD, although this was a nonsignificant trend due to the small sample size involved. Receiver operating characteristic curve analysis indicated that Cv levels of ≥16.52 ng/mL, C0 levels of ≥5.56 ng/mL, and C2 levels of ≥7.83 ng/mL minimized the incidence of treatment failure during weeks 3-4 with intravenous administration and weeks 5-6 with oral administration. There was no statistically significant association of the patient liver and kidney function with the blood concentration of tacrolimus in the desired range of 5-20 ng/mL.

CONCLUSIONS

Tacrolimus therapeutic drug monitoring improved treatment outcomes of Chinese alloHSCT recipients. Cv measurements during weeks 3-4 and C0 or C2 measurements during weeks 5-6 better predicted aGVHD (I-IV) than the concentrations measured at other time points during the first 6 weeks after alloHSCT.

A Minimal Physiologically-Based Pharmacokinetic Model for Tacrolimus in Living-Donor Liver Transplantation: Perspectives Related to Liver Regeneration and the cytochrome P450 3A5 (CYP3A5) Genotype

In adult patients after living‐donor liver transplantation, postoperative days and the cytochrome P450 3A5 (CYP3A5) genotype are known to affect tacrolimus pharmacokinetics. In this study, we constructed a physiologically‐based pharmacokinetic model adapted to the clinical data and evaluated the contribution of liver regeneration as well as hepatic and intestine CYP3A5 genotypes on tacrolimus pharmacokinetics. As a result, liver function recovered immediately and affected the total body clearance of tacrolimus only during a limited period after living‐donor liver transplantation. The clearance was about 1.35‐fold higher in the recipients who had a liver with the CYP3A5*1 allele than in those with the CYP3A5*3/*3 genotype, whereas bioavailability was ~0.7‐fold higher in the recipients who had intestines with the CYP3A5*1 allele than those with CYP3A5*3/*3. In conclusion, the constructed physiologically‐based pharmacokinetic model clarified that the oral clearance of tacrolimus was affected by the CYP3A5 genotypes in both the liver and intestine to the same extent.

Population pharmacokinetics of immediate- and prolonged-release tacrolimus formulations in liver, kidney and heart transplant recipients

Aims

Develop a population pharmacokinetics model of tacrolimus in organ transplant recipients receiving twice‐daily, immediate‐release (IR‐T; Prograf) and/or once‐daily, prolonged‐release (PR‐T; Advagraf or Astagraf XL) tacrolimus.

Methods

Tacrolimus concentration–time profiles were analysed from 8 Phase II studies in adult and paediatric liver, kidney and heart transplant patients receiving IR‐T and/or PR‐T. A tacrolimus population pharmacokinetic model, including identification of significant covariates, was developed using NONMEM.

Results

Overall, 23,176 tacrolimus concentration records were obtained from 408 patients. A 2‐compartment model with first‐order absorption and elimination described the concentration–time profiles. Tacrolimus absorption rate was 50% slower with PR‐T vs IR‐T. Tacrolimus apparent oral clearance was 44.3 L/h in Whites and 59% higher in Asians. Tacrolimus central volume of distribution was 108 L in males and 55% lower in females; trough concentrations were similar between formulations. Tacrolimus relative bioavailability was similar between formulations (geometric mean ratio PR‐T:IR‐T 95%, 90% confidence intervals: 89%, 101%). Asians had 83% and 51% higher relative bioavailability than Whites and Blacks, respectively, for IR‐T and PR‐T. Whites had 49% and 77% higher relative bioavailability than Blacks for PR‐T and IR‐T, respectively. Blacks had 52% lower relative bioavailability than Whites and Asians for IR‐T and PR‐T. Type of organ transplanted and patient population (adult/paediatric) did not have a significant effect on tacrolimus pharmacokinetics.

Conclusions

This population pharmacokinetic model described data from transplant recipients who received IR‐T and/or PR‐T. Tacrolimus trough concentrations and relative bioavailability were similar between formulations, supporting 1 mg:1 mg conversion from Prograf to Advagraf/Astagraf XL in clinical practice.

Characterizing the pharmacokinetics and pharmacodynamics of immunosuppressant medicines and patient outcomes in elderly renal transplant patients

This review examines what is currently known about the pharmacokinetics and pharmacodynamics of commonly prescribed immunosuppressant medicines, tacrolimus, cyclosporine, mycophenolate and prednisolone, in elderly renal transplant recipients, and reported patient outcomes in this cohort. Renal transplantation is increasing rapidly in the elderly, however, currently, long-term patient outcomes are relatively poor compared to younger adults. Some studies have suggested that elderly recipients may have higher dose-adjusted exposure and/or lower clearance of the calcineurin inhibitors tacrolimus and cyclosporine; with one study reporting up to 50% reduction in tacrolimus exposure in the elderly. Elderly transplant recipients do not appear to have higher dosage-adjusted exposure to mycophenolic acid (MPA). The effects of ageing on the pharmacokinetics of prednisolone are unknown. Only one study has examined how aging effects drug target enzymes, reporting no difference in baseline inosine 5'-monophosphate dehydrogenase (IMPDH) activity and MPA-induced IMPDH activity in elderly compared to younger adult renal transplant recipients. In elderly transplant recipients, immunosenescence likely lowers the risk of acute rejection, but increases the risk of drug-related adverse effects. Currently, the three main causes of death in elderly renal transplant recipients are cardiovascular disease, infection and malignancy. One study has showed that renal transplant recipients aged over 65 years are seven times more likely to die with a functioning graft compared with young adults (aged 18-29 years). This suggests that an optimal balance between immunosuppressant medicine efficacy and toxicity is not achieved in elderly recipients, and further studies are needed to foster long-term graft and patient survival. Lower maintenance immunosuppressant targets in elderly recipients may decrease patient susceptibility to drug side effects, however, further studies are required and appropriate targets need to be established.

Intra-patient variability in tacrolimus exposure in pediatric liver transplant recipients: Evolution, risk factors, and impact on patient outcomes

BACKGROUND

This study aims to investigate the evolution and factors associated with TAC IPV and its impact on patient outcomes in pediatric LT recipients.

METHODS

This is a retrospective study including 41 children. The TAC IPV was expressed as the coefficient of variation and was calculated for years 1-5 following LT. The number of missed clinic appointments was used as a surrogate marker for therapy adherence.

RESULTS

We identified a decrease in the TAC IPV during the first 3 years after LT (P < 0.01). Serum albumin in the first year (P = 0.03), hematocrit (P = 0.02) and total bilirubin (P = 0.04) in the third year, and therapy adherence (P < 0.01) in the fifth year were associated with TAC IPV. High TAC IPV was associated with biopsy-proven acute allograft rejection (P = 0.04) and the need for biopsy during the first year (P = 0.02). There was a borderline association between TAC IPV and donor-specific antibodies (P = 0.08) and CMV viremia (P = 0.07). High TAC IPV was a predictor of need for liver biopsy and AR with an odds ratio of 1.04 (95% CI 1.0-1.1; P = 0.03) and 1.04 (95% CI 1.0-1.1; P = 0.05), respectively.

CONCLUSIONS

Our results highlight the impact of biological factors on TAC IPV during the early LT follow-up and later also therapy adherence. High TAC IPV may be associated with adverse patient outcomes.

Tacrolimus exposure early after lung transplantation and exploratory associations with acute cellular rejection

AIMS

To (i) describe tacrolimus (TAC) pre-dose concentrations (C₀), (ii) calculate apparent oral TAC clearance (CL/F_HCT) adjusted for measured haematocrit (HCTi) and standardised to a HCT of 45%, across three observation time points and (iii) explore if low TAC C₀ or high mean CL/F_HCT are associated with an increased risk of rejection episodes early after lung transplantation.

METHODS

TAC whole blood concentration-time profiles and transbronchial biopsies were performed prospectively at weeks 3, 6 and 12 after lung transplantation. The TAC pre-dose concentration (C₀) was measured, and CL/F_HCT was determined using non-compartmental analysis. The associations between TAC C₀ and CL/F_HCT and rejection status were explored using repeated measures logistic regression.

RESULTS

Eighteen patients provided 377 TAC whole blood concentrations. Considerable variability around the median (IQR) CL/F_HCT 6.8 (4.2-15.9) L h^-1, and the median C₀ 12.7 (9.9-16.6) μg L^-1 was noted. Despite adjustment for haematocrit, a significant decrease was observed in CL/F_HCT in all patients over time: CL/F_HCT 14 (5.4-23) at week 3, CL/F_HCT 7.7 (4.5-12) at week 6 and CL/F_HCT 3.9 (2.4-11) L h^-1 at week 12 (p < 0.01). Seven (38.9%) patients experienced a single grade 2 rejection, whilst 11 (61.1%) patients experienced no rejection. Higher TAC C₀ were associated with a reduced risk of rejection OR 0.68 (95% CI 0.51-0.91, p = 0.02), and greater mean CL/F_HCT was associated with an increased risk of rejection OR 1.34 (95% CI 1.01-1.81 p = 0.04).

CONCLUSION

Monitoring TAC C₀, HCT and CL/F_HCT in patients after lung transplantation may assist clinicians in detecting patients at risk of acute rejection and may guide future research into TAC and HCT monitoring after lung transplantation.

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

Aims

The aims of this study were to describe the pharmacokinetics of tacrolimus immediately after kidney transplantation, and to develop a clinical tool for selecting the best starting dose for each patient.

Methods

Data on tacrolimus exposure were collected for the first 3 months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed‐effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates.

Results

A total of 4527 tacrolimus blood samples collected from 337 kidney transplant recipients were available. Data were best described using a two‐compartment model. The mean absorption rate was 3.6 h⁻¹, clearance was 23.0 l h^–1 (39% interindividual variability, IIV), central volume of distribution was 692 l (49% IIV) and the peripheral volume of distribution 5340 l (53% IIV). Interoccasion variability was added to clearance (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower haematocrit levels were identified as covariates enhancing tacrolimus clearance. Cytochrome P450 (CYP) 3A5 expressers had a significantly higher tacrolimus clearance (160%), whereas CYP3A4*22 carriers had a significantly lower clearance (80%). From these significant covariates, age, BSA, CYP3A4 and CYP3A5 genotype were incorporated in a second model to individualize the tacrolimus starting dose: Dosemg=222nghml–1*22.5lh–1*1.0ifCYP3A5*3/*3or1.62ifCYP3A5*1/*3orCYP3A5*1/*1*1.0ifCYP3A4*1or unknownor0.814ifCYP3A4*22*Age56−0.50*BSA1.930.72/1000Both models were successfully internally and externally validated. A clinical trial was simulated to demonstrate the added value of the starting dose model.

Conclusions

For a good prediction of tacrolimus pharmacokinetics, age, BSA, CYP3A4 and CYP3A5 genotype are important covariates. These covariates explained 30% of the variability in CL/F. The model proved effective in calculating the optimal tacrolimus dose based on these parameters and can be used to individualize the tacrolimus dose in the early period after transplantation.

The potential impact of hematocrit correction on evaluation of tacrolimus target exposure in pediatric kidney transplant patients

BACKGROUND

Tacrolimus is an important immunosuppressive agent with high intra- and inter-individual pharmacokinetic variability and a narrow therapeutic index. As tacrolimus extensively accumulates in erythrocytes, hematocrit is a key factor in the interpretation of tacrolimus whole blood concentrations. However, as hematocrit values in pediatric kidney transplant patients are highly variable after kidney transplantation, translating whole blood concentration targets without taking hematocrit into consideration is theoretically incorrect. The aim of this study is to evaluate the potential impact of hematocrit correction on tacrolimus target exposure in pediatric kidney transplant patients.

METHODS

Data were obtained from 36 pediatric kidney transplant patients. Two hundred fifty-five tacrolimus whole blood samples were available, together responsible for 36 area under the concentration-time curves (AUCs) and trough concentrations. First, hematocrit corrected concentrations were derived using a formula describing the relationship between whole blood concentrations, hematocrit, and plasma concentrations. Subsequently, target exposure was evaluated using the converted plasma target concentrations. Ultimately, differences in interpretation of target exposure were identified and evaluated.

RESULTS

In total, 92% of our patients had lower hematocrit (median 0.29) than the reference value of adult kidney transplant patients. A different evaluation of target exposure for either trough level, AUC, or both was defined in 42% of our patients, when applying hematocrit corrected concentrations.

CONCLUSION

A critical role for hematocrit in therapeutic drug monitoring of tacrolimus in pediatric kidney transplant patients is suggested in this study. Therefore, we believe that hematocrit correction could be a step towards improvement of tacrolimus dose individualization.

Clinical aspects of tacrolimus use in paediatric renal transplant recipients

The calcineurin inhibitor tacrolimus, cornerstone of most immunosuppressive regimens, is a drug with a narrow therapeutic window: underexposure can lead to allograft rejection and overexposure can result in an increased incidence of infections, toxicity and malignancies. Tacrolimus is metabolised in the liver and intestine by the cytochrome P450 3A (CYP3A) isoforms CYP3A4 and CYP3A5. This review focusses on the clinical aspects of tacrolimus pharmacodynamics, such as efficacy and toxicity. Factors affecting tacrolimus pharmacokinetics, including pharmacogenetics and the rationale for routine CYP3A5*1/*3 genotyping in prospective paediatric renal transplant recipients, are also reviewed. Therapeutic drug monitoring, including pre-dose concentrations and pharmacokinetic profiles with the available "reference values", are discussed. Factors contributing to high intra-patient variability in tacrolimus exposure and its impact on clinical outcome are also reviewed. Lastly, suggestions for future research and clinical perspectives are discussed.

Retrospective analysis of the correlation between tacrolimus concentrations measured in whole blood and variations of blood cell counts in patients undergoing allogeneic haematopoietic stem cell transplantation

Objective

Tacrolimus is administered to patients undergoing haematopoietic stem cell transplantation (HSCT) as prophylaxis for graft-versus-host disease. As a high blood tacrolimus concentration within a narrow therapeutic range must be maintained after HSCT, therapeutic drug monitoring (TDM) is necessary. We investigated the correlation between blood tacrolimus concentration and blood cell count in HSCT patients to assess how changes in blood cell count affect tacrolimus TDM.

Methods

A retrospective analysis was performed for 24 patients who underwent allogeneic HSCT and received tacrolimus. The correlation between variations in blood tacrolimus concentration and blood cell count was evaluated for three consecutive weeks, starting 1 week after HSCT.

Results

Variations in blood tacrolimus concentration were significantly correlated with variations in red blood cell (RBC) count, haemoglobin level and haematocrit value, but not with variations in white blood cell or platelet counts. Further, the above variations were significantly correlated in patients undergoing cord blood transplantation and peripheral blood stem cell transplantation, but not in those undergoing bone marrow transplantation.

Conclusions

These findings demonstrate that RBC count is associated with variations in blood tacrolimus concentration, with the relevance of this association depending on the source of transfused stem cells. Thus, variations in RBC count might be useful for tacrolimus TDM.

Population Pharmacokinetics of Tacrolimus in Transplant Recipients: What Did We Learn About Sources of Interindividual Variabilities?

Tacrolimus, a calcineurin inhibitor, is a common immunosuppressant prescribed after organ transplantation and has notable inter- and intrapatient pharmacokinetic variability. The sources of variability have been investigated using population pharmacokinetic modeling over the last 2 decades. This article provides an updated synopsis on published nonlinear mixed-effects analyses developed for tacrolimus in transplant recipients. The objectives were to establish a detailed overview of the current data and to investigate covariate relationships determined by the models. Sixty-three published analyses were reviewed, and data regarding the study design, modeling approach, and resulting findings were extracted and summarized. Most of the studies investigated tacrolimus pharmacokinetics in adult and pediatric renal and liver transplants after administration of the immediate-release formulation. Model structures largely depended on the study sampling strategy, with ∼50% of studies developing a 1-compartment model using trough concentrations and a 2-compartment model with delayed absorption from intensive sampling. The CYP3A5 genotype, as a covariate, consistently impacted tacrolimus clearance, and dosing adjustments were required to achieve similar drug exposure among patients. Numerous covariates were identified as sources of interindividual variability on tacrolimus pharmacokinetics with limited consistency across these studies, which may be the result of the study designs. Additional analyses are required to further evaluate the potential impact of these covariates and the clinical implementation of these models to guide tacrolimus dosing recommendations. This article may be useful for guiding the design of future population pharmacokinetic studies and provides recommendations for the selection of an existing optimal model to individualize tacrolimus therapy.

Evaluating tacrolimus pharmacokinetic models in adult renal transplant recipients with different CYP3A5 genotypes

PURPOSE

Numerous studies have been conducted on the population pharmacokinetics of tacrolimus in adult renal transplant recipients. It has been reported that the cytochrome P450 (CYP) 3A5 genotype is an important cause of variability in tacrolimus pharmacokinetics. However, the predictive performance of population pharmacokinetic (PK) models of tacrolimus should be evaluated prior to their implementation in clinical practice. The aim of the study reported here was to test the predictive performance of these published PK models of tacrolimus.

METHODS

A literature search of the PubMed and Web of Science databases ultimately led to the inclusion of eight one-compartment models in our analysis. We collected a total of 1715 trough concentrations from 174 patients. Predictive performance was assessed based on visual and numerical comparison bias and imprecision and by the use of simulation-based diagnostics and Bayesian forecasting.

RESULTS

Of the eight one-compartment models assessed, seven showed better predictive performance in CYP3A5 extensive metabolizers in terms of bias and imprecision. Results of the simulation-based diagnostics also supported the findings. The model based on a Chinese population in 2013 (model 3) showed the best and most stable predictive performance in all the tests and was more informative in CYP3A5 extensive metabolizers. As expected, Bayesian forecasting improved model predictability. Diversity among models and between different CYP3A5 genotypes of the same model was also narrowed by Bayesian forecasting.

CONCLUSIONS

Based on our results, we recommend using model 3 in CYP3A5 extensive metabolizers in clinical practice. All models had a poor predictive performance in CYP3A5 poor metabolizers, and they should be used with caution in this patient population. However, Bayesian forecasting improved the predictability and reduced differences, and thus the models could be applied in this latter patient population for the design of maintenance dose.

A New CYP3A5*3 and CYP3A4*22 Cluster Influencing Tacrolimus Target Concentrations: A Population Approach

BACKGROUND

Single nucleotide polymorphisms (SNPs) in the CYP3A5 and CYP3A4 genes have been reported to be an important cause of variability in the pharmacokinetics of tacrolimus in renal transplant patients. The aim of this study was to merge all of the new genetic information available with tacrolimus pharmacokinetics to generate a more robust population model with data from renal transplant recipients.

METHODS

Tacrolimus exposure data from 304 renal transplant recipients were collected throughout the first year after transplantation and were simultaneously analyzed with a population pharmacokinetic approach using NONMEM^® version 7.2.

RESULTS

The tacrolimus whole-blood concentration versus time data were best described by a two-open-compartment model with inter-occasion variability assigned to plasma clearance. The following factors led to the final model, which significantly decreased the minimum objective function value (p < 0.001): a new genotype cluster variable combining the CYP3A5*3 and CYP3A4*22 SNPs defined as extensive, intermediate, and poor metabolizers; the standardization of tacrolimus whole blood concentrations to a hematocrit value of 45%; and age included as patients <63 years versus patients ≥63 years. External validation confirmed the prediction ability of the model with median bias and precision values of 1.17 ng/mL (95% confidence interval [CI] -3.68 to 4.50) and 1.64 ng/mL (95% CI 0.11-5.50), respectively. Simulations showed that, for a given age and hematocrit at the same fixed dose, extensive metabolizers required the highest doses followed by intermediate metabolizers and then poor metabolizers.

CONCLUSIONS

Tacrolimus disposition in renal transplant recipients was described using a new population pharmacokinetic model that included the CYP3A5*3 and CYP3A4*22 genotype, age, and hematocrit.

Which Kidney Transplant Recipients Can Benefit from the Initial Tacrolimus Dose Reduction?

Background

Observational data suggest that the fixed initial recommended tacrolimus (Tc) dosing (0.2 mg/kg/day) results in supratherapeutic drug levels in some patients during the early posttransplant period. The aim of the study was to analyze a wide panel of patient-related factors and their interactions which increase the risk for first Tc blood level > 15 ng/ml.

Materials and Methods

We performed a retrospective analysis of 488 consecutive adult kidney transplant recipients who were initially treated with triple immunosuppressive regimen containing tacrolimus twice daily. The analysis included the first assessment of Tc trough blood levels and several demographic, anthropometric, laboratory, and comedication data.

Results

The multiple logistic regression analysis showed that age > 55 years, BMI > 24.6 kg/m², blood hemoglobin concentration > 9.5 g/dl, and the presence of anti-HCV antibodies independently increased the risk for first Tc level > 15 ng/ml. The relative risk (RR) for first tacrolimus level > 15 ng/ml was 1.88 (95% CI 1.35–2.64, p < 0.001) for patients with one risk factor and 2.81 (2.02–3.89, p < 0.001) for patients with two risk factors.

Conclusions

Initial tacrolimus dose reduction should be considered in older, overweight, or obese kidney transplant recipients and in subjects with anti-HCV antibodies. Moreover, dose reduction of tacrolimus is especially important in patients with coexisting multiple risk factors.

The Effect of Weight and CYP3A5 Genotype on the Population Pharmacokinetics of Tacrolimus in Stable Paediatric Renal Transplant Recipients

BACKGROUND

The aim of this study was to develop a population pharmacokinetic model of tacrolimus in paediatric patients at least 1 year after renal transplantation and simulate individualised dosage regimens.

PATIENTS AND METHODS

We included 54 children with median age of 11.1 years (range 3.8-18.4 years) with 120 pharmacokinetic profiles performed over 2 to 4 h. The pharmacokinetic analysis was performed using the non-linear mixed-effects modelling software (NONMEM(®)). The impact of covariates including concomitant medications, age, the cytochrome P450 (CYP) CYP3A5*3 gene and the adenosine triphosphate binding cassette protein B1 (ABCB1) 3435 C→T gene polymorphism on tacrolimus pharmacokinetics was analysed. The final model was externally validated on an independent dataset and dosing regimens were simulated.

RESULTS

A two-compartment model adequately described tacrolimus pharmacokinetics. Apparent oral clearance (CL/F) was associated with weight (allometric scaling) but not age. Children with lower weight and CYP3A5 expressers required higher weight-normalised tacrolimus doses. CL/F was inversely associated with haematocrit (P < 0.05) and γ-glutamyl transpeptidase (γGT) (P < 0.001) and was increased by 45 % in carriers of the CYP3A5*1 allele (P < 0.001). CL/F was not associated with concomitant medications. Dose simulations show that a daily tacrolimus dose of 0.2 mg/kg generates a pre-dose concentration (C 0) ranging from 5 to 10 µg/L depending on the weight and CYP3A5 polymorphism. The median area under the plasma concentration-time curve (AUC) corresponding with a tacrolimus C 0 of 4-8 µg/L was 97 h·µg/L (interquartile range 80-120).

CONCLUSIONS

In patients beyond the first year after transplantation, there is a cumulative effect of CYP3A5*1 polymorphism and weight on the tacrolimus C 0. Children with lower weight and carriers of the CYP3A5*1 allele have higher weight-normalised tacrolimus dose requirements.

Recovery of CYP3A Phenotype after Kidney Transplantation

End-stage renal disease impairs drug metabolism via cytochrome P450 CYP3A; however, it is unclear whether CYP3A activity recovers after kidney transplantation. Therefore, the aim of this study was to evaluate the change in CYP3A activity measured as 4β-hydroxycholesterol (4βOHC) concentration after kidney transplantation. In total, data from 58 renal transplant recipients with 550 prospective 4βOHC measurements were included in the study. One sample per patient was collected before transplantation, and 2-12 samples per patient were collected 1-82 days after transplantation. The measured pretransplant 4βOHC concentrations ranged by >7-fold, with a median value of 22.8 ng/ml. Linear mixed-model analysis identified a 0.16-ng/ml increase in 4βOHC concentration per day after transplantation (P < 0.001), indicating a regain in CYP3A activity. Increasing estimated glomerular filtration rate after transplantation was associated with increasing 4βOHC concentration (P < 0.001), supporting that CYP3A activity increases with recovering uremia. In conclusion, this study indicates that CYP3A activity is regained subsequent to kidney transplantation.

Population pharmacokinetics and Bayesian estimation of tacrolimus exposure in Chinese liver transplant patients

WHAT IS KNOWN AND OBJECTIVES

Tacrolimus (TAC) is widely used as part of immunosuppressive regimens. There is great interindividual variation on the disposition of TAC. The aim of this study was to develop a population pharmacokinetic (PPK) model for Chinese liver transplant patients and evaluate genetic polymorphism and other possible factors on the PK parameters. The exposure of TAC is to be estimated through Bayesian modelling.

METHODS

A total of 47 sets of rich-time PK and 1234 conventional therapeutic drug monitoring (TDM) data were collected from 125 Chinese liver transplant patients. The pathophysiological data of these patients were recorded. CYP3A5*3 and ABCB1 genotypes were determined for each patient. The PPK model for TAC was established by nonlinear mixed-effects modelling (nonmem). The impact of pathophysiology and genotype on PPK parameters was evaluated. Bayesian estimators for the area under concentration-time curve (AUC) of TAC were validated.

RESULTS

A two-compartment model with lag time was found to be the most suitable model for the pooled full PK and TDM data for Chinese liver transplant patients. The CL/F, V₂ /F, Q/F, V₃ /F, K_a and lag time were 17.4±0.81 L/h, 165±44.1 L, 54.9±25.8L/h, 594±87.5 L, 0.51±0.095 L/h and 1.57±0.34 h. Post-operative day (POD), creatinine clearance (CLcr) and ABCB1 C3435T genotypes were found to have significant influences on CL/F (P<.01). ABCB1 C3435T genotypes showed a significant correlation with V₂ /F (P<.01). C₀ -C₂ and C₀ -C₂ -C₄ were shown to be suitable for the estimation of AUC in Chinese liver transplant patients.

WHAT IS NEW AND CONCLUSION

A PPK model for TAC was established successfully in Chinese liver transplant patients. POD, CLcr and ABCB1 C3435T genotypes were shown to have significant effects on CL/F. The AUC of TAC in Chinese liver transplant patients could be estimated through Bayesian modelling, based on which individualized immunosuppressive regimens can be designed.

NFAT-regulated cytokine gene expression during tacrolimus therapy early after renal transplantation

AIMS

Despite pharmacokinetic monitoring of calcineurin inhibitors, the long-term outcome after transplantation (Tx) is still hampered by the side effects of these drugs. The aim of the present study was to characterize nuclear factor of activated T cells (NFAT)-regulated gene expression as a potential pharmacodynamic biomarker for further individualization of tacrolimus (Tac) therapy.

METHODS

In 29 renal allograft recipients, samples were drawn once pre-Tx, and before and 1.5 h after Tac dosing at approximately 1 week, 6 weeks and 1 year post-Tx. Tac concentrations were measured by immunoassay, while the expression of genes encoding NFAT-regulated cytokines [interleukin 2 (IL2), interferon gamma (IFNG), colony stimulating factor 2 (CSF2)] and cytochrome P450 3A5 (CYP3A5) genotyping were determined by real-time polymerase chain reaction.

RESULTS

The cytokine response after Tac dosing varied up to 46-fold between patients and changed significantly with time post-engraftment. Tac concentrations 1.5 h postdose (C_1.5 ) >15 μg l^-1 were associated with strong cytokine inhibition and residual gene expression (RGE) ≤10%, while lower Tac C_1.5 resulted in more variable responses (RGE 2.5-68.7%). Patients with ongoing subclinical acute rejection (n = 5) demonstrated limited cytokine inhibition (RGE 39.7-72.6%), while patients with polyoma virus viraemia (n = 3) had relatively strong inhibition of cytokines (RGE 2.5-32.5%). By contrast, there was no association between Tac exposure and rejection or viraemia.

CONCLUSIONS

The findings of our study support the potential of NFAT-regulated gene expression measurements as a pharmacodynamic tool for additional monitoring of Tac therapy, especially in the context of overimmunosuppression and viraemia.

Tacrolimus Updated Guidelines through popPK Modeling: How to Benefit More from CYP3A Pre-emptive Genotyping Prior to Kidney Transplantation

Tacrolimus (Tac) is a profoundly effective immunosuppressant that reduces the risk of rejection after solid organ transplantation. However, its use is hampered by its narrow therapeutic window along with its highly variable pharmacological (pharmacokinetic [PK] and pharmacodynamic [PD]) profile. Part of this variability is explained by genetic polymorphisms affecting the metabolic pathway. The integration of CYP3A4 and CY3A5 genotype in tacrolimus population-based PK (PopPK) modeling approaches has been proven to accurately predict the dose requirement to reach the therapeutic window. The objective of the present study was to develop an accurate PopPK model in a cohort of 59 kidney transplant patients to deliver this information to clinicians in a clear and actionable manner. We conducted a non-parametric non-linear effects PopPK modeling analysis in Pmetrics^®. Patients were genotyped for the CYP3A4^∗22 and CYP3A5^∗3 alleles and were classified into 3 different categories [poor-metabolizers (PM), Intermediate-metabolizers (IM) or extensive-metabolizers (EM)]. A one-compartment model with double gamma absorption route described very accurately the tacrolimus PK. In covariate analysis, only CYP3A genotype was retained in the final model (Δ-2LL = -73). Our model estimated that tacrolimus concentrations were 33% IC_95%[20–26%], 41% IC_95%[36–45%] lower in CYP3A IM and EM when compared to PM, respectively. Virtually, we proved that defining different starting doses for PM, IM and EM would be beneficial by ensuring better probability of target concentrations attainment allowing us to define new dosage recommendations according to patient CYP3A genetic profile.

The CYP3A biomarker 4β-hydroxycholesterol does not improve tacrolimus dose predictions early after kidney transplantation

AIMS

Tacrolimus is a cornerstone in modern immunosuppressive therapy after kidney transplantation. Tacrolimus dosing is challenged by considerable pharmacokinetic variability, both between patients and over time after transplantation, partly due to variability in cytochrome P450 3A (CYP3A) activity. The aim of this study was to assess the value of the endogenous CYP3A marker 4β-hydroxycholesterol (4βOHC) for tacrolimus dose individualization early after kidney transplantation.

METHODS

Data were obtained from 79 adult kidney transplant recipients who contributed a total of 625 4βOHC measurements and 1999 tacrolimus whole blood concentrations during the first 2 months after transplantation. The relationships between 4βOHC levels and individual estimates of tacrolimus apparent plasma clearance (CL/F_plasma ) at different time points after transplantation were investigated using scatterplots and population pharmacokinetic modelling.

RESULTS

There was no significant correlation between pre-transplant 4βOHC levels and tacrolimus CL/F_plasma the first week (r = 0.19 [95% CI -0.03-0.40]) or between 4βOHC and tacrolimus CL/F_plasma 1 week (r = 0.20 [-0.11-0.47]), 4 weeks (r = 0.21 [-0.07-0.46]) or 2 months (r = 0.24 [-0.03-0.48]) after transplantation (P ≥ 0.06). In the population analysis, time-varying 4βOHC was not a statistically significant covariate on tacrolimus CL/F_plasma , neither in terms of absolute values (P = 0.11) nor in terms of changes from baseline (P = 0.17). 4βOHC values increased between 1 week and 2 months after transplantation (median change +57% [IQR +22-83%], P < 0.001), indicating increasing CYP3A activity. Contradictorily, tacrolimus CL/F_plasma decreased over the same period (median change -13% [IQR -3 to -26%], P < 0.001).

CONCLUSIONS

4βOHC does not appear to have a clinical potential to improve individualization of tacrolimus doses early after kidney transplantation.

Comparative performance of oral midazolam clearance and plasma 4β-hydroxycholesterol to explain interindividual variability in tacrolimus clearance

AIMS

We compared the CYP3A4 metrics weight-corrected midazolam apparent oral clearance (MDZ Cl/F/W) and plasma 4β-hydroxycholesterol/cholesterol (4β-OHC/C) as they relate to tacrolimus (TAC) Cl/F/W in renal transplant recipients.

METHODS

For a cohort of 147 patients, 8 h area under the curve (AUC) values for TAC and oral MDZ were calculated besides measurement of 4β-OHC/C. A subgroup of 70 patients additionally underwent intravenous erythromycin breath test (EBT) and were administered the intravenous MDZ probe. All patients were genotyped for common polymorphisms in CYP3A4, CYP3A5 and P450 oxidoreductase, among others.

RESULTS

MDZ Cl/F/W, 4β-OHC/C/W, EBT and TAC Cl/F/W were all moderately correlated (r = 0.262-0.505). Neither MDZ Cl/F/W nor 4β-OHC/C/W explained variability in TAC Cl/F/W in CYP3A5 expressors (n = 29). For CYP3A5 non-expressors (n = 118), factors explaining variability in TAC Cl/F/W in a MDZ-based model were MDZ Cl/F/W (R²  = 0.201), haematocrit (R²  = 0.139), TAC formulation (R²  = 0.107) and age (R²  = 0.032; total R²  = 0.479). In the 4β-OHC/C/W-based model, predictors were 4β-OHC/C/W (R²  = 0.196), haematocrit (R²  = 0.059) and age (R²  = 0.057; total R²  = 0.312). When genotype information was ignored, predictors of TAC Cl/F/W in the whole cohort were 4β-OHC/C/W (R²  = 0.167), MDZ Cl/F/W (R²  = 0.045); Tac QD formulation (R²  = 0.036), and haematocrit (R²  = 0.032; total R²  = 0.315). 4β-OHC/C/W, but not MDZ Cl/F/W, was higher in CYP3A5 expressors because it was higher in CYP3A4*1b carriers, which were almost all CYP3A5 expressors.

CONCLUSIONS

A MDZ-based model explained more variability in TAC clearance in CYP3A5 non-expressors. However, 4β-OHC/C/W was superior in a model in which no genotype information was available, likely because 4β-OHC/C/W was influenced by the CYP3A4*1b polymorphism.

A Rationale for Age-Adapted Immunosuppression in Organ Transplantation

Demographic changes are associated with a steady increase of older patients with end-stage organ failure in need for transplantation. As a result, the majority of transplant recipients are currently older than 50 years, and organs from elderly donors are more frequently used. Nevertheless, the benefit of transplantation in older patients is well recognized, whereas the most frequent causes of death among older recipients are potentially linked to side effects of their immunosuppressants.Immunosenescence is a physiological part of aging linked to higher rates of diabetes, bacterial infections, and malignancies representing the major causes of death in older patients. These age-related changes impact older transplant candidates and may have significant implications for an age-adapted immunosuppression. For instance, immunosenescence is linked to lower rates of acute rejections in older recipients, whereas the engraftment of older organs has been associated with higher rejection rates. Moreover, new-onset diabetes mellitus after transplantation is more frequent in the elderly, potentially related to corticosteroids, calcineurin inhibitors, and mechanistic target of rapamycin inhibitors.This review presents current knowledge for an age-adapted immunosuppression based on both, experimental and clinical studies in and beyond transplantation. Recommendations of maintenance and induction therapy may help to improve graft function and to design future clinical trials in the elderly.

Improved Tacrolimus Target Concentration Achievement Using Computerized Dosing in Renal Transplant Recipients--A Prospective, Randomized Study

BACKGROUND

Early after renal transplantation, it is often challenging to achieve and maintain tacrolimus concentrations within the target range. Computerized dose individualization using population pharmacokinetic models may be helpful. The objective of this study was to prospectively evaluate the target concentration achievement of tacrolimus using computerized dosing compared with conventional dosing performed by experienced transplant physicians.

METHODS

A single-center, prospective study was conducted. Renal transplant recipients were randomized to receive either computerized or conventional tacrolimus dosing during the first 8 weeks after transplantation. The median proportion of tacrolimus trough concentrations within the target range was compared between the groups. Standard risk (target, 3-7 μg/L) and high-risk (8-12 μg/L) recipients were analyzed separately.

RESULTS

Eighty renal transplant recipients were randomized, and 78 were included in the analysis (computerized dosing (n = 39): 32 standard risk/7 high-risk, conventional dosing (n = 39): 35 standard risk/4 high-risk). A total of 1711 tacrolimus whole blood concentrations were evaluated. The proportion of concentrations per patient within the target range was significantly higher with computerized dosing than with conventional dosing, both in standard risk patients (medians, 90% [95% confidence interval {95% CI}, 84-95%] vs 78% [95% CI, 76-82%], respectively, P < 0.001) and in high-risk patients (medians, 77% [95% CI, 71-80%] vs 59% [95% CI, 40-74%], respectively, P = 0.04).

CONCLUSIONS

Computerized dose individualization improves target concentration achievement of tacrolimus after renal transplantation. The computer software is applicable as a clinical dosing tool to optimize tacrolimus exposure and may potentially improve long-term outcome.

Understanding alterations in drug handling with aging: a focus on the pharmacokinetics of maintenance immunosuppressants in the elderly

PURPOSE OF REVIEW

This review presents current knowledge of the impact of age on the pharmacokinetics of maintenance immunosuppressants.

RECENT FINDINGS

Over the past decade, there has been a steady increase in older patients on organ transplant waiting lists. As a result, the average age of transplant recipients has significantly increased. The survival and quality-of-life benefits of transplantation in the elderly population have been demonstrated. Advancing age is associated with changes in immune responses, as well as changes in drug handling. Immunosenescence is a physiological part of aging and is linked to reduced rejection rates, but also higher rates of diabetes, infections and malignancies. Physiologic changes associated with age can have a significant impact on the pharmacokinetics of the maintenance immunosuppressive agents. Taken together, these age-related changes impact older transplant candidates and may have significant implications for managing immunosuppression in the elderly.

SUMMARY

Despite the lack of formal efficacy, safety and pharmacokinetic studies of individual immunosuppressants in the elderly transplant population, there are enough data available for practitioners to be able to adequately manage their older patients. A proficient understanding of the factors that impact the pharmacokinetics of the immunosuppressants in the elderly is essential to managing these patients successfully.

Improved prediction of tacrolimus concentrations early after kidney transplantation using theory-based pharmacokinetic modelling

Aims

The aim was to develop a theory-based population pharmacokinetic model of tacrolimus in adult kidney transplant recipients and to externally evaluate this model and two previous empirical models.

Methods

Data were obtained from 242 patients with 3100 tacrolimus whole blood concentrations. External evaluation was performed by examining model predictive performance using Bayesian forecasting.

Results

Pharmacokinetic disposition parameters were estimated based on tacrolimus plasma concentrations, predicted from whole blood concentrations, haematocrit and literature values for tacrolimus binding to red blood cells. Disposition parameters were allometrically scaled to fat free mass. Tacrolimus whole blood clearance/bioavailability standardized to haematocrit of 45% and fat free mass of 60 kg was estimated to be 16.1 l h⁻¹ [95% CI 12.6, 18.0 l h⁻¹]. Tacrolimus clearance was 30% higher (95% CI 13, 46%) and bioavailability 18% lower (95% CI 2, 29%) in CYP3A5 expressers compared with non-expressers. An E_max model described decreasing tacrolimus bioavailability with increasing prednisolone dose. The theory-based model was superior to the empirical models during external evaluation displaying a median prediction error of −1.2% (95% CI −3.0, 0.1%). Based on simulation, Bayesian forecasting led to 65% (95% CI 62, 68%) of patients achieving a tacrolimus average steady-state concentration within a suggested acceptable range.

Conclusion

A theory-based population pharmacokinetic model was superior to two empirical models for prediction of tacrolimus concentrations and seemed suitable for Bayesian prediction of tacrolimus doses early after kidney transplantation.

Pharmacokinetics and pharmacodynamics of immunosuppressive drugs in elderly kidney transplant recipients

Elderly patients are a fast growing population among transplant recipients over the past decades. Both the innate and adaptive immune reactivity decrease with age, which is believed to contribute to the decreased incidence of acute rejection and increased infectious death rate in elderly transplant recipients. In contrast to recipient age, donor age is associated with a higher incidence of acute rejection. Pharmacokinetic studies in renal transplant recipients show that CNI troughs are >5% higher in elderly compared to younger patients given the same dose normalized by body weight. This may impact the starting dose of tacrolimus and cyclosporine. Possibly in elderly patients the intracellular (in lymphocyte) concentrations are relatively high in relation to the whole blood concentration, resulting in a stronger pharmacodynamic effect at the same whole blood trough concentration. For cyclosporine this has been shown, but it is not clear if the same is true for other immunosuppressive drugs. Pharmacodynamic studies have compared the inhibition of target enzymes, or more downstream effects of immunosuppressive drugs, in younger and older patients. Measurement of nuclear factor of activated T-cell (NFAT)-regulated gene expression (RGE), a pharmacodynamic read-out of CNI, is a promising biomarker of immunosuppression. Low levels of NFAT RGE are associated with increased risk of infection and non-melanoma skin cancer in elderly patients. Clinical trials to evaluate the safety and efficacy of immunosuppression regimens in this specific patient population, which is underrepresented in published trials, are lacking. More studies in elderly patients are needed to investigate the impact of age on the pharmacokinetics or pharmacodynamics of immunosuppressive drugs, and to decide on the optimal regimen and target levels for elderly transplant recipients.

The influence of CYP3A, PPARA, and POR genetic variants on the pharmacokinetics of tacrolimus and cyclosporine in renal transplant recipients

Purpose

Tacrolimus (Tac) and cyclosporine (CsA) are mainly metabolized by CYP3A4 and CYP3A5. Several studies have demonstrated an association between the CYP3A5 genotype and Tac dose requirements. Recently, CYP3A4, PPARA, and POR gene variants have been shown to influence CYP3A metabolism. The present study investigated potential associations between CYP3A5*3, CYP3A4*22, PPARA c.209-1003G>A and c.208 + 3819A>G, and POR*28 alleles and dose-adjusted concentrations (C/D) of Tac and CsA in 177 renal transplant patients early post-transplant.

Methods

All patients (n = 177) were genotyped for CYP3A4*22, CYP3A5*3, POR*28, PPARA c.209-1003G>A, and PPARA c.208 + 3819A>G using real-time polymerase chain reaction (PCR) and melting curve analysis with allele-specific hybridization probes or PCR restriction fragment length polymorphisms (RFLP) methods. Drug concentrations and administered doses were retrospectively collected from patient charts at Oslo University Hospital, Rikshospitalet, Norway. One steady-state concentration was collected for each patient.

Results

We confirmed a significant impact of the CYP3A5*3 allele on Tac exposure. Patients with POR*28 and PPARA variant alleles demonstrated 15 % lower (P = 0.04) and 19 % higher (P = 0.01) Tac C₀/D respectively. CsA C₂/D was 53 % higher among CYP3A4*22 carriers (P = 0.03).

Conclusion

The results support the use of pre-transplant CYP3A5 genotyping to improve initial dosing of Tac, and suggest that Tac dosing may be further individualized by additional POR and PPARA genotyping. Furthermore, initial CsA dosing may be improved by pre-transplant CYP3A4*22 determination.

Electronic supplementary material

The online version of this article (doi:10.1007/s00228-014-1656-3) contains supplementary material, which is available to authorized users

Inclusion of CYP3A5 genotyping in a nonparametric population model improves dosing of tacrolimus early after transplantation

Following organ engraftment, initial dosing of tacrolimus is based on recipient weight and adjusted by measured C₀ concentrations. The bioavailability and elimination of tacrolimus are affected by the patients CYP3A5 genotype. Prospective data of the clinical advantage of knowing patient's CYP3A5 genotype prior to transplantation are lacking. A nonparametric population model was developed for tacrolimus in renal transplant recipients. Data from 99 patients were used for model development and validation. A three-compartment model with first-order absorption and lag time from the dosing compartment described the data well. Clearances and volumes of distribution were allometrically scaled to body size. The final model included fat-free mass, body mass index, hematocrit, time after transplantation, and CYP3A5 genotype as covariates. The bias and imprecision were 0.35 and 1.38, respectively, in the external data set. Patients with functional CYP3A5 had 26% higher clearance and 37% lower bioavailability. Knowledge of CYP3A5 genotype provided an initial advantage, but only until 3-4 tacrolimus concentrations were known. After this, a model without CYP3A5 genotype predicted just as well. The present models seem applicable for clinical individual dose predictions but need a prospective evaluation.