Forecasting of Blood Tacrolimus Concentrations Based on the Bayesian Method in Adult Patients Receiving Living-Donor Liver Transplantation

Plasma metabolomic profiling reveals factors associated with dose-adjusted trough concentration of tacrolimus in liver transplant recipients

Inter- and intrapatient variability of tacrolimus exposure is a vital prognostic risk factor for the clinical outcome of liver transplantation. New factors or biomarkers characterizing tacrolimus disposition is essential for optimal dose prediction in recipients of liver transplant. The aim of the study was to identify potential plasma metabolites associated with the dose-adjusted trough concentration of tacrolimus in liver transplant recipients by using a global metabolomic approach. A total of 693 plasma samples were collected from 137 liver transplant recipients receiving tacrolimus and regular therapeutic drug monitoring. Untargeted metabolomic analysis was performed by ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. Univariate and multivariate analyses with a mixed linear model were conducted, and the results showed that the dose-adjusted tacrolimus trough concentration was associated with 31 endogenous metabolites, including medium- and long-chain acylcarnitines such as stearoylcarnitine (β = 0.222, p = 0.001), microbiota-derived uremic retention solutes such as indolelactic acid (β = 0.194, p = 0.007), bile acids such as taurohyodeoxycholic acid (β = -0.056, p = 0.002), and steroid hormones such as testosterone (β = 0.099, p = 0.001). A multiple linear mixed model including 11 metabolites and clinical information was established with a suitable predictive performance (correlation coefficient based on fixed effects = 0.64 and correlation coefficient based on fixed and random effects = 0.78). These data demonstrated that microbiota-derived uremic retention solutes, bile acids, steroid hormones, and medium- and long-chain acylcarnitines were the main metabolites associated with the dose-adjusted trough concentration of tacrolimus in liver transplant recipients.

Population pharmacokinetics and dosage optimization of tacrolimus coadministration with Wuzhi capsule in adult liver transplant patients

1. This study aimed to establish a population pharmacokinetic model of tacrolimus coadministration with Wuzhi capsule and optimize the dosage regimen in adult liver transplant patients.2. Totally 1327 tacrolimus trough concentrations from 116 adult liver transplant patients were obtained for model development. A one-compartment model with first-order absorption and elimination was used to analyse the data, and the final model was internally verified using a goodness-of-fit diagnostic plot, bootstrap methods, and visual prediction test. A total of 29 patients with 250 tacrolimus trough concentrations was used for external validation via prediction-based diagnostics. Additionally, the simulation was used to optimize the recommended dose of tacrolimus and Wuzhi capsules.3. The estimated apparent clearance and volume of the distribution of tacrolimus were 15.4 L/h and 1210 L, respectively. The tacrolimus daily dose, Wuzhi capsule daily dose, postoperative time, alanine transaminase, haemoglobin, total bilirubin, direct bilirubin, estimated glomerular filtration rate, and urea, concomitant with voriconazole and fluconazole, were identified as significant covariates affecting the pharmacokinetic parameters. Internal and external validation showed that the final model was stable and reliable for predicting performance.4. The final model could provide guidance for dosage optimization of tacrolimus coadministered with Wuzhi capsules in adult liver transplantation patients.

Population Pharmacokinetic Models of Tacrolimus in Adult Transplant Recipients: A Systematic Review

BACKGROUND AND OBJECTIVES

Numerous population pharmacokinetic (PK) models of tacrolimus in adult transplant recipients have been published to characterize tacrolimus PK and facilitate dose individualization. This study aimed to (1) investigate clinical determinants influencing tacrolimus PK, and (2) identify areas requiring additional research to facilitate the use of population PK models to guide tacrolimus dosing decisions.

METHODS

The MEDLINE and EMBASE databases, as well as the reference lists of all articles, were searched to identify population PK models of tacrolimus developed from adult transplant recipients published from the inception of the databases to 29 February 2020.

RESULTS

Of the 69 studies identified, 55% were developed from kidney transplant recipients and 30% from liver transplant recipients. Most studies (91%) investigated the oral immediate-release formulation of tacrolimus. Few studies (17%) explained the effect of drug-drug interactions on tacrolimus PK. Only 35% of the studies performed an external evaluation to assess the generalizability of the models. Studies related variability in tacrolimus whole blood clearance among transplant recipients to either cytochrome P450 (CYP) 3A5 genotype (41%), days post-transplant (30%), or hematocrit (29%). Variability in the central volume of distribution was mainly explained by body weight (20% of studies).

CONCLUSION

The effect of clinically significant drug-drug interactions and different formulations and brands of tacrolimus should be considered for any future tacrolimus population PK model development. Further work is required to assess the generalizability of existing models and identify key factors that influence both initial and maintenance doses of tacrolimus, particularly in heart and lung transplant recipients.

Can We Predict Individual Concentrations of Tacrolimus After Liver Transplantation? Application and Tweaking of a Published Population Pharmacokinetic Model in Clinical Practice

BACKGROUND

Various population pharmacokinetic models have been developed to describe the pharmacokinetics of tacrolimus in adult liver transplantation. However, their extrapolated predictive performance remains unclear in clinical practice. The purpose of this study was to predict concentrations using a selected literature model and to improve these predictions by tweaking the model with a subset of the target population.

METHODS

A literature review was conducted to select an adequate population pharmacokinetic model (L). Pharmacokinetic data from therapeutic drug monitoring of tacrolimus in liver-transplanted adults were retrospectively collected. A subset of these data (70%) was exploited to tweak the L-model using the $PRIOR subroutine of the NONMEM software, with 2 strategies to weight the prior information: full informative (F) and optimized (O). An external evaluation was performed on the remaining data; bias and imprecision were evaluated for predictions a priori and Bayesian forecasting.

RESULTS

Seventy-nine patients (851 concentrations) were enrolled in the study. The predictive performance of L-model was insufficient for a priori predictions, whereas it was acceptable with Bayesian forecasting, from the third prediction (ie, with ≥2 previously observed concentrations), corresponding to 1 week after transplantation. Overall, the tweaked models showed a better predictive ability than the L-model. The bias of a priori predictions was -41% with the literature model versus -28.5% and -8.73% with tweaked F and O models, respectively. The imprecision was 45.4% with the literature model versus 38.0% and 39.2% with tweaked F and O models, respectively. For Bayesian predictions, whatever the forecasting state, the tweaked models tend to obtain better results.

CONCLUSIONS

A pharmacokinetic model can be used, and to improve the predictive performance, tweaking the literature model with the $PRIOR approach allows to obtain better predictions.

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.

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.

Prediction of tacrolimus dosage in the early period after heart transplantation: a population pharmacokinetic approach

Aim: The aim of this study was to evaluate tacrolimus population pharmacokinetics and investigate factors that explain tacrolimus variability in adult heart transplant patients. Methods: A total of 707 tacrolimus concentrations from 107 adult heart transplant patients were included in model development. The effects of demographic, clinical factors and CYP3A5 genotype on tacrolimus clearance were evaluated using a nonlinear mixed-effects modeling. 24 patients with 106 tacrolimus concentrations were used for external validation. Results: The pharmacokinetic data were adequately described by a one-compartment model with first-order absorption and elimination. The estimated apparent clearance and volume of distribution of tacrolimus were 13.7 l/h and 791 l, respectively. Tacrolimus apparent clearance was significantly reduced in CYP3A5 nonexpressers (CYP3A5*3/*3), concomitant with azole antifungal drugs and Wuzhi capsule (WZ). A predictive performance was further confirmed in an external validation by Bayesian estimation. Recommended dose regimens were obtained by simulations based on the established model. Conclusion: This is the first population pharmacokinetic study conducted in Chinese heart transplant recipients. These findings are of great importance with regards to tacrolimus dose optimization in heart transplantation patients.

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.

CYP3A5 genotype-based model to predict tacrolimus dosage in the early postoperative period after living donor liver transplantation

Purpose

Liver transplantation is the treatment of choice for patients with end-stage liver disease. Due to the between- and within-individual pharmacokinetic variability in tacrolimus, used to prevent rejection after transplantation, it is difficult to predict the dose needed achieve the target levels in the blood. This study aimed to construct a population pharmacokinetic model of tacrolimus dosage prediction for therapeutic drug monitoring in clinical settings for Korean adult patients receiving living donor liver transplantation (LDLT).

Methods

A total of 58 Korean adult patients receiving LDLT with tacrolimus administration were enrolled. Demographic, clinical, and CYP3A5*1/*3 polymorphism data were collected. Population pharmacokinetic modeling of tacrolimus during the first 14 days after transplantation was performed using NONMEM program. Parameters were estimated by the first-order conditional estimation with interaction method. The internal validation of the final model was assessed by the bootstrap and visual predictive check methods using 500 samples from the original data.

Results

One-compartmental model was selected as a base model. After the stepwise covariate model building process, postoperative day (POD) and combinational CYP3A5 genotype of the recipient and donor were incorporated into clearance (CL/F). The estimated typical values of CL/F and volume of distribution (V/F) were 6.33 L/h and 465 L, respectively. The final model was CL/F =6.33× POD^0.257×2.314 (if CYP3A5 expresser recipient grafted from CYP3A5 expresser donor) ×1.523 (if CYP3A5 expresser recipient grafted from CYP3A5 nonexpresser donor) and V/F =465× POD^0.322.

Conclusion

A population pharmacokinetic model for tacrolimus was established successfully in Korean adult patients receiving LDLT. This model is expected to contribute to improving patient outcomes by optimizing tacrolimus dose adjustment for liver transplant patients.

Predicting tacrolimus concentrations in children receiving a heart transplant using a population pharmacokinetic model

OBJECTIVE

Immunosuppressant therapy plays a pivotal role in transplant success and longevity. Tacrolimus, a primary immunosuppressive agent, is well known to exhibit significant pharmacological interpatient and intrapatient variability. This variability necessitates the collection of serial trough concentrations to ensure that the drug remains within therapeutic range. The objective of this study was to build a population pharmacokinetic (PK) model and use it to determine the minimum number of trough samples needed to guide the prediction of an individual's future concentrations.

DESIGN SETTING AND PATIENTS

Retrospective data from 48 children who received tacrolimus as inpatients at Primary Children's Hospital in Salt Lake City, Utah were included in the study. Data were collected within the first 6 weeks after heart transplant.

OUTCOME MEASURES

Data analysis used population PK modelling techniques in NONMEM. Predictive ability of the model was determined using median prediction error (MPE, a measure of bias) and median absolute prediction error (MAPE, a measure of accuracy). Of the 48 children in the study, 30 were used in the model building dataset, and 18 in the model validation dataset.

RESULTS

Concentrations ranged between 1.5 and 37.7 μg/L across all collected data, with only 40% of those concentrations falling within the targeted concentration range (12 to 16 μg/L). The final population PK model contained the impact of age (on volume), creatinine clearance (on elimination rate) and fluconazole use (on elimination rate) as covariates. Our analysis demonstrated that as few as three concentrations could be used to predict future concentrations, with negligible bias (MPE (95% CI)=0.10% (-2.9% to 3.7%)) and good accuracy (MAPE (95% CI)=24.1% (19.7% to 27.7%)).

CONCLUSIONS

The use of PK in dose guidance has the potential to provide significant benefits to clinical care, including dose optimisation during the early stages of therapy, and the potential to limit the need for frequent drug monitoring.

In vitro immune cell monitoring as a guide for long-term immunosuppression in adult liver transplant recipients

Backgrounds/Aims

We evaluated the clinical usability of immune cell monitoring in adult liver transplantation (LT) recipients.

Methods

This study was composed of two parts as using calcineurin phosphatase (CNP) activity assay and ImmuKnow assay independently as in vitro monitoring tools of immune cell function in adult LT recipients.

Results

There was a rough correlation between CNP activity and tacrolimus concentration in 33 patients. This association was evident in patients who were only administered tacrolimus, but disappeared after the co-administration of mycophenolate. In 118 healthy individuals, the mean proportion of helper T-cells was 37.4±8.1%. According to ImmuKnow assay, their immune responses were strong in 12 patients (10.2%), moderate in 92 patients (78.0%), and low in 14 patients (11.9%). In 85 patients waiting for LT, there was a rough correlation between the ImmuKnow ATP level and age. Their immune responses were strong in 0 patients (0%), moderate in 8 patients (9.4%), and low in 77 patients (90.6%). There was a difference in the ImmuKnow ATP levels between healthy individuals and patients with liver disease. In 137 LT recipients, there was no correlation between the ImmuKnow ATP levels and tacrolimus concentration. This trend did not change after grouping the patients according to co-administration with mycophenolate. Eight recipients experienced acute rejection, but none showed strong immune response.

Conclusions

We think that both CNP activity assay and ImmuKnow assay are too limited to objectively determine the level of immunosuppression. Further studies should be performed to identify other methods for immune function monitoring.

Determination of the most influential sources of variability in tacrolimus trough blood concentrations in adult liver transplant recipients: a bottom-up approach

Tacrolimus, an immunosuppressant drug, presents a narrow therapeutic window and a large pharmacokinetic variability with poor correlation between drug dosing regimen and blood concentration. The objective was to identify predictive factors influencing tacrolimus trough concentrations (C0) using a bottom-up approach. A physiologically based pharmacokinetic (PBPK) model of tacrolimus was proposed, taking into account the body weight, the proportion of fat (P(fat)), hematocrit, lipid fraction of organs, typical intrinsic clearance (CLi(typ)), CYP3A5 genotype of liver donor, plasma unbound fraction of tacrolimus (fu(p)), and concomitant drugs (CYP3A4 inhibitors). For the evaluation of the PBPK model, mean C0 and concentrations 2 h after oral dose of tacrolimus were compared with those from 66 liver transplant recipients included in a multicentric pharmacokinetic study and were found very close. Tacrolimus concentration profiles were simulated in a virtual population defined by a set of covariate values similar to those from the real population. The sensitivity of tacrolimus C0 with respect to each covariate has been tested to identify the most influential ones. With the range of covariate values tested, the impact of each covariate on tacrolimus C0 may be ranked as follows: fu(p), CLi(typ), bioavailability, body weight, hematocrit, CYP3A5 polymorphism, P(fat), and CYP3A4 inhibitory drug-drug interactions. Values for initial dosing regimen of tacrolimus in order to reach a C0 of 10 ng/ml at day 5 (assuming a constant dosing schedule) as a function of CYP3A5 donor genotype and patient's hematocrit and body weight are proposed.

Significance of trough monitoring for tacrolimus blood concentration and calcineurin activity in adult patients undergoing primary living-donor liver transplantation

PURPOSE

Tacrolimus pharmacokinetics and calcineurin activity in peripheral blood mononuclear cells (PBMCs) were investigated in adult patients undergoing primary living-donor liver transplantation (LDLT) in order to clarify the significance of monitoring the tacrolimus blood trough concentration during the early post-transplantation period.

METHODS

Fourteen patients were enrolled in this study, and time-course data following the oral administration of a conventional tacrolimus formulation twice daily were obtained at 1 and 3 weeks post-transplantation. The concentration of tacrolimus in whole blood and calcineurin activity in PBMCs were measured.

RESULTS

The apparent clearance of tacrolimus significantly increased at 3 weeks versus 1 week post-transplantation, although the trough concentration did not significantly differ at these time points. The concentration at each sampling time, except at 1 h post-dose, correlated well with the area under the concentration-time curve from 0 to 12 h (AUC(0-12)). Neither the concentration at the trough time point nor AUC(0-12) was correlated with the area under the calcineurin activity-time curve from 0 to 12 h; however, calcineurin activity at the trough time point was strongly correlated with the latter (r (2) > 0.92).

CONCLUSIONS

Based on these results, trough concentration monitoring can be considered an appropriate procedure for routine tacrolimus dosage adjustment in adult LDLT patients. Monitoring of calcineurin activity at the trough time point was also found to be potentially useful for predicting the immunological status of the patient during the tacrolimus dosing interval.

Pharmacokinetic-pharmacodynamic assessment of tacrolimus in liver-transplant recipients during the early post-transplantation period

During the early post-transplantation period, the limitations of monitoring current tacrolimus dose with classic pharmacokinetics (PK) have been demonstrated in liver-transplant recipients. Evaluation of the pharmacodynamics (PD) using calcineurin activity (CNA) has been proposed to optimize tacrolimus dosing. The aim of the present study was to determine the time of maximal inhibition of CNA, to explore the relation between exposure to tacrolimus and CNA, and to analyze its variability. Blood was drawn from 14 patients 0, 2, 3, 4, 6, and 9 hours after tacrolimus intake on post-transplantation days 8, 21, and 90 to measure blood tacrolimus concentrations using the EMIT 2000 assay and CNA in peripheral blood mononuclear cells. Tacrolimus and CNA data were obtained for 33 blood-sample collection sessions and analyzed using a population approach. Three models were built to describe tacrolimus PK, CNA kinetics, and the relationships between the area under the CNA-time curve (AUC12effCNA) and AUC12Tacrolimus or CminTacrolimus. Coagulation factor V and whole/split liver graft were identified as covariates influencing tacrolimus clearance. Indeed, apparent tacrolimus clearance rose by 14% when factor V increased by 10% and was threefold higher in patients with whole-liver grafts. The median maximal inhibition of CNA was reached 4 hours after tacrolimus intake on days 8, 21, and 90 and represented an 18% drop in CNA compared with activity at drug intake. The variability of the PK-PD relationship was minimal when using AUC12Tacrolimus. The large variability of the PD parameters (coefficient of variation was 89%) that linked AUC12effCNA to AUC12Tacrolimus indicates that monitoring tacrolimus concentrations may not be adequate to control CNA. Measuring CNA in peripheral blood mononuclear cells 4 hours after tacrolimus intake during the first 3 months after liver transplantation could be a means to improve tacrolimus monitoring and thereby avoid acute graft-rejection episodes.

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.

A novel approach for prediction of tacrolimus blood concentration in liver transplantation patients in the intensive care unit through support vector regression

Introduction

Tacrolimus is an important immunosuppressive drug for organ transplantation patients. It has a narrow therapeutic range, toxic side effects, and a blood concentration with wide intra- and interindividual variability. Hence, it is of the utmost importance to monitor tacrolimus blood concentration, thereby ensuring clinical effect and avoiding toxic side effects. Prediction models for tacrolimus blood concentration can improve clinical care by optimizing monitoring of these concentrations, especially in the initial phase after transplantation during intensive care unit (ICU) stay. This is the first study in the ICU in which support vector machines, as a new data modeling technique, are investigated and tested in their prediction capabilities of tacrolimus blood concentration. Linear support vector regression (SVR) and nonlinear radial basis function (RBF) SVR are compared with multiple linear regression (MLR).

Methods

Tacrolimus blood concentrations, together with 35 other relevant variables from 50 liver transplantation patients, were extracted from our ICU database. This resulted in a dataset of 457 blood samples, on average between 9 and 10 samples per patient, finally resulting in a database of more than 16,000 data values. Nonlinear RBF SVR, linear SVR, and MLR were performed after selection of clinically relevant input variables and model parameters. Differences between observed and predicted tacrolimus blood concentrations were calculated. Prediction accuracy of the three methods was compared after fivefold cross-validation (Friedman test and Wilcoxon signed rank analysis).

Results

Linear SVR and nonlinear RBF SVR had mean absolute differences between observed and predicted tacrolimus blood concentrations of 2.31 ng/ml (standard deviation [SD] 2.47) and 2.38 ng/ml (SD 2.49), respectively. MLR had a mean absolute difference of 2.73 ng/ml (SD 3.79). The difference between linear SVR and MLR was statistically significant (p < 0.001). RBF SVR had the advantage of requiring only 2 input variables to perform this prediction in comparison to 15 and 16 variables needed by linear SVR and MLR, respectively. This is an indication of the superior prediction capability of nonlinear SVR.

Conclusion

Prediction of tacrolimus blood concentration with linear and nonlinear SVR was excellent, and accuracy was superior in comparison with an MLR model.

[Individualized dosage regimen of immunosuppressive drugs based on pharmacokinetic and pharmacodynamic analysis]

The calcineurin inhibitors cyclosporine and tacrolimus are widely used to prevent allograft rejection after transplantation. Since these drugs have narrow therapeutic windows and show considerable pharmacokinetic variability, therapeutic drug monitoring (TDM) is essential to avoid adverse effects such as nephrotoxicity while maximizing immunosuppressive efficacy. On the other hand, some patients experience acute rejection episodes or postoperative complications despite achieving therapeutic blood drug levels. Therefore, pharmacokinetic and pharmacodynamic factors by which to establish individualized dosage adjustment for these drugs should be identified. Recently, it was recognized that pharmacogenomics has the potential to facilitate personalized medicine by translating knowledge of human genome variability into rational therapeutics. In this paper, we review the population pharmacokinetic and pharmacogenomic analysis of tacrolimus, focusing on an efflux transporter P-glycoprotein (multidrug resistance 1 [MDR1/ABCB1]) and drug-metabolizing enzymes cytochrome P450 (CYP) 3A4 and 3A5, and describe Bayesian forecasting to individualize the tacrolimus dose in de novo living-donor liver transplant recipients. Furthermore, the pharmacodynamic properties of tacrolimus and cyclosporine, which were evaluated by measuring calcineurin phosphatase activity in peripheral blood mononuclear cells, are reviewed in relation to an optimal monitoring strategy as well as a rational dosage regimen for these drugs.

Beyond cyclosporine: a systematic review of limited sampling strategies for other immunosuppressants

Therapeutic drug monitoring has gained much attention in the management of immunosuppressive therapy. Area under the plasma drug concentration-time curve (AUC) is the pharmacokinetic (PK) parameter most commonly used to assess total exposure to a drug. However, estimation of AUC requires multiple blood samples throughout the dosing period, which is often inconvenient and expensive. Limited sampling strategies (LSSs) are therefore developed to estimate AUC and other PK parameters accurately and precisely while minimizing the number of blood samples needed. This greatly reduces costs, labor and inconvenience for both patients and clinical staff. In the therapeutic management of solid organ transplantation, LSSs for cyclosporine are commonplace and have been extensively reviewed. Thus, this systematic review paper focuses on other immunosuppressive agents and categorizes the 24 pertinent citations according to the U.S. Preventive Services Task Force rating scale. Thirteen articles (3 level I, 1 level II-1, 2 level II-2, and 7 level III) involved LSSs for mycophenolate, 7 citations (1 level I and 6 level III) for tacrolimus (TAC), and 3 citations (all level III) for other drugs (sirolimus) or multiple drugs. The 2 main approaches to establishing LSSs, multiple regression and Bayesian analyses, are also reviewed. Important elements to consider for future LSS studies, including proper validation of LSSs, convenient sampling times, and application of LSSs to the appropriate patient population and drug formulation are discussed. Limited sampling strategies are a useful tool to help clinicians make decisions on drug therapy. However, patients' pathophysiology, environmental and genetic factors, and pharmacologic response to therapy, in conjunction with PK profiling tools such as LSSs, should be considered collectively for optimal therapy management.

Pharmacokinetic study of tacrolimus in cystic fibrosis and non-cystic fibrosis lung transplant patients and design of Bayesian estimators using limited sampling strategies

OBJECTIVES

To: (i) test different pharmacokinetic models to fit full tacrolimus concentration-time profiles; (ii) estimate the tacrolimus pharmacokinetic characteristics in stable lung transplant patients with or without cystic fibrosis (CF); (iii) compare the pharmacokinetic parameters between these two patient groups; and (iv) design maximum a posteriori Bayesian estimators (MAP-BE) for pharmacokinetic forecasting in these patients using a limited sampling strategy.

METHODS

Tacrolimus blood concentration-time profiles obtained on three occasions within a 5-day period in 22 adult lung transplant recipients (11 with CF and 11 without CF) were retrospectively studied. Three different one-compartment models with first-order elimination were tested to fit the data: one with first-order absorption, one convoluted with a gamma distribution to describe the absorption phase, and one convoluted with a double gamma distribution able to describe secondary concentration peaks. Finally, Bayesian estimation using the best model and a limited sampling strategy was tested in the two groups of patients for its ability to provide accurate estimates of the main tacrolimus pharmacokinetic parameters and exposure indices.

RESULTS

The one-compartment model with first-order elimination convoluted with a double gamma distribution gave the best results in both CF and non-CF lung transplant recipients. The patients with CF required higher doses of tacrolimus than those without CF to achieve similar drug exposure, and population modelling had to be performed in CF and non-CF patients separately. Accurate Bayesian estimates of area under the blood concentration-time curve from 0 to 12 hours (AUC12), AUC from 0 to 4 hours, peak blood concentration (Cmax) and time to reach Cmax were obtained using three blood samples collected at 0, 1 and 3 hours in non-CF patients (correlation coefficient between observed and estimated AUC12, R2 = 0.96), and at 0, 1.5 and 4 hours in CF patients (R2 = 0.91).

CONCLUSION

A particular pharmacokinetic model was designed to fit the complex and highly variable tacrolimus blood concentration-time profiles. Moreover, MAP-BE allowing tacrolimus therapeutic drug monitoring based on AUC12 were developed.

Delayed effect of grapefruit juice on pharmacokinetics and pharmacodynamics of tacrolimus in a living-donor liver transplant recipient

Tacrolimus is a calcineurin inhibitor that has been widely used to prevent allograft rejection after transplantation. We report a case of a living-donor liver transplant recipient experiencing a considerable increase in the trough blood concentration of tacrolimus after concomitant ingestion of grapefruit juice (250 mL) 4 times for 3 days. The trough blood concentrations of tacrolimus were not changed during or immediate after the repeated intake of grapefruit juice. However, almost 1 week after the final ingestion, the blood concentration of tacrolimus markedly increased to as much as 47.4 ng/mL from 4.7 ng/mL before the ingestion, resulting in a profound reduction of calcineurin phosphatase activity in peripheral blood mononuclear cells. Furthermore, headache and nausea, but not nephrotoxicity or hyperglycemia, took place throughout the period of the elevated blood concentrations. Grapefruit juice may have a clinically significant effect on the pharmacokinetics and pharmacodynamics of tacrolimus. It is recommended to avoid the consumption of grapefruit juice in transplant recipients treated with tacrolimus.

An up-date review on individualized dosage adjustment of calcineurin inhibitors in organ transplant patients

Calcineurin inhibitors, tacrolimus (FK506) and cyclosporine (ciclosporin A), are the primary immunosuppressive agents used on recipients of organ transplantations. The hepatic metabolism of these drugs by cytochrome P450 IIIA (CYP3A) subfamilies is considered a major eliminating process. The intestinal efflux-pump P-glycoprotein (Pgp) (multidrug resistance 1 [MDR1], ATP-binding cassette B1 [ABCB1]) and CYP3A4 have been demonstrated as important for the bioavailability of drugs, so called "absorptive barriers". Recently, an important role for CYP3A5 in the intestine for the oral clearance of drugs has been identified. Both tacrolimus and cyclosporine are substrates of Pgp, CYP3A4 and CYP3A5, and therefore, these molecules are potential pharmacokinetic factors with which to establish personalized dosage regimens for these drugs. Although the effect of single nucleotide polymorphisms in the MDR1/ABCB1 and CYP3A5 genes on the pharmacokinetics of immunosuppressant has been widely examined, some contradictions have been emerged. In living-donor liver transplant (LDLT) patients, the intestinal mRNA expression level of MDR1 and CYP3A5 genotyping both in the native intestine and in the grafted liver are suggested to be potential pharmacokinetic factors for adjusting initial dosage and predicting post-operative variation in the pharmacokinetics of tacrolimus. We review the pharmacokinetic and pharmacodynamic characteristics of these drugs including the large pharmacokinetic variation and potential individualized dosage adjustments based on the genomic information of transporters and metabolic enzymes as well as classical pharmacokinetic analyses based on therapeutic drug monitoring (TDM).

Effect of intestinal CYP3A5 on postoperative tacrolimus trough levels in living-donor liver transplant recipients

It has been reported that hepatic and intestinal cytochrome P450 (CYP) 3A4, CYP3A5 and P-glycoprotein affect the pharmacokinetics of tacrolimus, and that these proteins are associated with the large inter-individual variation in the pharmacokinetics of this drug. We previously showed that the concentration/dose ratio of tacrolimus tended to be lower in recipients of living-donor liver transplantation (LDLT) with a CYP3A5*1/*1-carrying graft. However, the effect of intestinal CYP3A5 remains to be elucidated. In the present study, we examined the CYP3A5 genotype in both recipients and donors, and the effect of the recipients' polymorphism on the concentration/dose ratio of tacrolimus in patients after LDLT. The CYP3A5*3 allele frequency was 80% in recipients and 77% in donors. The intestinal CYP3A5 mRNA expression level was significantly associated with genotype. The tacrolimus concentration/dose ratio was lower in recipients with the CYP3A5*1/*1 and *1/*3 genotype (CYP3A5 expressors) compared to the CYP3A5*3/*3 genotype (non-expressors). Amongst the combination of CYP3A5 genotypes between the graft liver and the native intestine, CYP3A5 expressors in both the graft liver and the native intestine had the lowest concentration/dose ratio of tacrolimus during 35 days after LDLT. Patients with the intestinal CYP3A5*1 genotype tended to require a higher dose of tacrolimus compared to the other group with the same hepatic CYP3A5 genotype. These results indicate that intestinal CYP3A5, as well as hepatic CYP3A5, plays an important role in the first-pass effect of orally administered tacrolimus.

Cyclosporine exposure and calcineurin phosphatase activity in living-donor liver transplant patients: twice daily vs. once daily dosing

We have compared the pharmacokinetics and pharmacodynamics of cyclosporine between once- and twice-daily dosing regimens in de novo patients of living-donor liver transplantation (LDLT). A total of 14 patients were enrolled in this study, who had received cyclosporine microemulsion (Neoral) twice a day (BID, n = 5) or once daily in the morning (QD, n = 9) after transplantation. On postoperative day (POD) 6, the QD regimen significantly increased cyclosporine exposure; the blood concentration at 2 hours postdose (C2) and area under the concentration-time curve (AUC) for 4 hours (AUC(0-4)), compared with the BID regimen. Moreover, the area under the calcineurin (CaN) activity in peripheral blood mononuclear cells time-curve (AUA) for 12 hours (AUA(0-12)) and 24 hours (AUA(0-24)) were decreased by approximately 42 and 25% with the QD regimen relative to the BID regimen, respectively. The C2 level was significantly correlated with the AUC(0-4) (r2 = 0.95), which was negatively related to the AUA(0-12) with a large interindividual variability (r(2) = 0.59). However, a significant correlation was found between the AUA(0-12) or AUA(0-24) and CaN activity at trough time points. According to a maximum inhibitory effect attributable to the drug (E(max)) model, the mean estimates of E(max) and the C(b) value that gives a half-maximal effect (EC50) for CaN inhibition were not significantly different between the 2 groups, respectively. These findings suggest that a once daily morning administration of cyclosporine may improve oral absorption and help to provide an effective CaN inhibition early after LDLT. Furthermore, CaN activity at trough time points would be a single surrogate predictor for the overall CaN activity throughout dosing intervals following cyclosporine administration.

Immunosuppressant Drug Monitoring: Is the Laboratory Meeting Clinical Expectations?

OBJECTIVE:

To review the literature relating to immunosuppressant drug measurement as performed in therapeutic drug monitoring laboratories associated with transplantation centers and consider whether the assay methods widely used for patient dosage management achieve acceptable quality criteria in the context of other sources of variability with these drugs.

DATA SOURCES:

Articles used were accessed primarily through MEDLINE, as well as references cited in related publications. Searches were restricted to organ transplantation in humans.

STUDY SELECTION AND DATA EXTRACTION:

Emphasis was placed on the literature relating to the quality of immunosuppressant drug assays, their limitations, and evidence of clinical benefit in dosage individualization.

DATA SYNTHESIS:

There is a dilemma evident between the quality of the analytical services offered by some diagnostic immunoassay manufacturers and the ability of a significant number of clinical laboratories globally to select only appropriate assay methods.

CONCLUSIONS:

In many cases, clinical laboratories fail to meet the reasonable clinical expectations required for interpretation of immunosuppressant drug assay results as an adjunct to optimal dosage individualization and patient care.

Progress in living donor liver transplantation

Living donor liver transplantation (LDLT) has the capacity to reduce the current discrepancy between the number of patients on the transplant waiting list and the number of available organ donors. For pediatric patients, LDLT has clearly reduced the number of waiting list deaths, providing compelling evidence for an increase in LDLT programs. This review discusses many of the recent advances in LDLT.