Sampling Times for Monitoring Tacrolimus in Stable Adult Liver Transplant Recipients

External validation of population pharmacokinetic models of tacrolimus in Thai adult liver transplant recipients

OBJECTIVE

Several population pharmacokinetic models of tacrolimus in liver transplant patients were built, and their predictability was evaluated in their settings. However, the extrapolation in the prediction was unclear. This study aimed to evaluate the predictive performance of published tacrolimus models in adult liver transplant recipients using data from the Thai population as an external dataset.

METHODS

The selected published models were systematically searched and evaluated for their quality. The external dataset of patients who underwent the first liver transplant and received immediate-release tacrolimus was used to assess the predictive performance of each selected model. Trough concentrations between 3 and 6 months were retrospectively collected to evaluate the predictability of each model using prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting.

RESULTS

Sixty-seven patients with 360 trough concentrations and eight selected published models were included in this study. None of the models met the predictive precision criteria in prediction-based diagnostics. Meanwhile, four published population pharmacokinetic models showed a normal distribution in NPDE testing. Regarding Bayesian forecasting, all models improved their forecasts with at least one prior information data point.

CONCLUSION

Bayesian forecasting is more accurate and precise than other testing methods for predicting drug concentrations. However, none of the evaluated models provides satisfactory predictive performance for generalization to Thai liver transplant patients. This underscores the need for future research to develop population PK models tailored to the Thai population. Such efforts should consider the inclusion of nonlinear pharmacokinetics and region-specific factors, including genetic variability, to improve model accuracy and applicability.

Tacrolimus 4-hour monitoring in liver transplant patients is non-inferior to trough monitoring: The randomized controlled FK04 trial

BACKGROUND

After liver transplantation (LT), tacrolimus and ciclosporin treatment can lead to, partially concentration-dependent, chronic kidney disease. Monitoring ciclosporin with two-hour levels reduced overexposure and led to better renal function than trough-monitoring (C0). For tacrolimus, a 4-hour level (C4) can give a reasonable approximation of total drug exposure. We evaluated whether monitoring tacrolimus in stable patients after LT by C4 was superior to C0 regarding renal function, rejection and metabolic parameters.

METHODS

This open label randomized controlled trial compared C4 monitoring of tacrolimus BID (Prograft) to trough (C0) monitoring in stable LT recipients. The target range for C4 of 7.8-16 ng/ml was calculated to be comparable with target C0 of 4-8 ng/ml. Primary endpoint was the effect on renal function and secondary endpoints were the occurrence of treated biopsy-proven acute rejection, blood pressure and metabolic parameters, during 3 months of follow-up.

RESULTS

Fifty patients were randomized to C0 (n = 25) or C4 (n = 25) monitoring. There was no difference in renal function between the C0 and the C4 group (p = .98 and p = .13 for CG and MDRD at 3 months). Also, the amount of proteinuria was similar (p = .59). None of the patients suffered from graft loss or was treated for rejection. Metabolic parameters did not differ between the two groups.

CONCLUSION

Tacrolimus 4-hour monitoring in stable LT patients is not superior to trough monitoring, regarding the effect on renal function, but is safe for use to facilitate tacrolimus monitoring in an afternoon outpatient clinic.

High tacrolimus blood concentrations early after lung transplantation and the risk of kidney injury

PURPOSE

Lung transplant recipients often develop acute kidney injury (AKI) evolving into chronic kidney disease (CKD). The immunosuppressant tacrolimus might be associated with the emergence of AKI. We analyzed the development and recovery of kidney injury after lung transplantation and related AKI to whole-blood tacrolimus trough concentrations and other factors causing kidney injury.

METHODS

We retrospectively studied kidney injury in 186 lung-transplantation patients at the UMC Utrecht between 2001 and 2011. Kidney function and whole-blood tacrolimus trough concentrations were determined from day 1 to 14 and at 1, 3, 6, and 12 months postoperative. Systemic inflammatory response syndrome (SIRS), septic shock, and nephrotoxic medications were evaluated as covariates for AKI. We analyzed liver injury and drug-drug interactions.

RESULTS

AKI was present in 85 (46%) patients. Tacrolimus concentrations were supra-therapeutic in 135 of 186 patients (73%). AKI in the first week after transplantation was related to supra-therapeutic tacrolimus concentrations (OR 1.55; 95% CI 1.06-2.27), ≥3 other nephrotoxic drugs (OR 1.96; 95% CI 1.02-3.77), infection (OR 2.48; 95% CI 1.31-4.70), and cystic fibrosis (OR 2.17; 95% CI 1.16-4.06). Recovery rate of AKI was lower than expected (19%), and the cumulative incidence of severe CKD at 1 year was 15%.

CONCLUSIONS

After lung transplantation, AKI is common and often evolves into severe CKD, which is a known cause of morbidity and mortality. Supra-therapeutic whole-blood tacrolimus trough concentrations are related to the early onset of AKI. Conscientious targeting tacrolimus blood concentrations might be vital in the early phase after lung transplantation. What is known about this subject? • Lung transplant recipients often develop acute kidney injury evolving into chronic kidney disease increasing both morbidity and mortality. • To date, the pathophysiology of kidney injury after lung transplantation has not been fully elucidated. • The immunosuppressant tacrolimus is difficult to dose, especially in the unstable clinical setting, and is nephrotoxic.

WHAT THIS STUDY ADDS

• For the first time, supra-therapeutic whole-blood tacrolimus trough concentrations are related to the emergence of acute kidney injury in the first days after lung transplantation. • Supra-therapeutic whole-blood tacrolimus trough concentrations often occur early after lung transplantation. • AKI after lung transplantation shows low recovery rates.

Development of Limited Sampling Strategies for the Estimation of Tacrolimus Area Under the Curve in Adult Kidney Transplant Recipients According to the Posttransplantation Time

BACKGROUND

Limited sampling strategies (LSS), using few sampling times after dosing, have been used to reliably predict tacrolimus area under the 12-hour concentration-time curve (AUC). Because the pharmacokinetics of tacrolimus is subject to significant changes over the exposure time to this drug, it can be hypothesized that the reliability of the LSS would also change. This study aimed to develop a reliable and practical LSS allowing the estimation of tacrolimus AUC in Tunisian kidney transplant recipients taking into account the posttransplantation time.

METHODS

Thirty Tunisian patients were enrolled into 3 groups (10 in each group) according to the posttransplantation period: period 1: between 1 day and 3 months, period 2: between 3 and 12 months and period 3 over 12 months, as defined by the European consensus conference on the therapeutic drug monitoring of tacrolimus. Samples were collected just before and 0.5, 1, 2, 4, 6, 8, and 12 hours after tacrolimus administration. The full pharmacokinetic profiles obtained from these timed concentration data were used to choose the best sampling times. Error indices (mean absolute prediction error and the root mean squared prediction error) were used to evaluate the predictive performance.

RESULTS

Among the 1-point estimations, the C4-predicted AUC showed the highest correlation with the measured one during period 1 and period 2 (r = 0.94 and 0.91, respectively) but not period 3 (r = 0.76). The C0-predicted and the measured AUC become less and less correlated from period 1 to period 3 (r = 0.81, 0.75, and 0.66), respectively. Only the model including the C0/C2 provided a high correlation between predicted and measured tacrolimus AUC regardless of the posttransplant period (r = 0.95, 0.96, 0.98 and root mean squared prediction error = 4.1, 5.8, 4.2 during periods 1, 2, and 3, respectively).

CONCLUSIONS

Our data clearly indicate that the predictive performance of LSS is prone to change according to the posttransplantation time. A 2-time point LSS was found to be sufficient to predict tacrolimus AUC. The LSS using C0 and C2 is reliable, accurate, and practical to estimate the AUC of tacrolimus regardless of the posttransplantation time.

A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for monitoring drug exposure in hematopoietic stem cell transplant recipients

A liquid chromatography-tandem mass spectrometry method was developed for the quantification of circulating levels of multiple immunosuppressant drugs including cyclosporine (CsA), tacrolimus, methotrexate (Mtx), prednisone, prednisolone, methylprednisone, total and free mycophenolic acid (MPA), as well as MPA phenolic (MPAG) and acyl (AcMPAG) glucuronide metabolites. Linearity, precision and accuracy were validated within the typical therapeutic range of concentrations for each compound. The assay was linear over 0.125-25ng/mL for tacrolimus, 1-500ng/mL for prednisone/methylprednisone, 2-400ng/mL for Mtx, 2-1000ng/mL for prednisolone and from 7.5 to 1500ng/mL for CsA with the lowest limit of quantification (LLOQ) being 0.125, 1.00, 2.00, 2.00 and 7.5ng/mL, respectively. The calibration curve concentrations for MPA and MPAG ranged from 50 to 50,000ng/mL (LLOQ: 50ng/mL) and 10 to 10,000ng/mL (LLOQ: 10ng/mL) for AcMPAG. Mean recoveries in blood and plasma were 84%±5.7%. The method could measure individual drugs with high sensitivity, accuracy (bias≤14%), and reproducibility (CV≤12.8%). Its clinical application was validated by measuring levels of these drugs in samples obtained from hematopoietic stem cell transplant recipients treated with combined immunosuppressive drug therapy. Our results indicate that this approach is suitable for simultaneous determination of in vivo levels of immunosuppressive drugs commonly used in combined therapies.

Application of the optimal design approach to improve a pretransplant drug dose finding design for ciclosporin

A time and sampling intensive pretransplant test dose design was to be reduced, but at the same time optimized so that there was no loss in the precision of predicting the individual pharmacokinetic (PK) estimates of posttransplant dosing. The following variables were optimized simultaneously: sampling times, ciclosporin dose, time of second dose, infusion duration, and administration order, using a published ciclosporin population PK model as prior information. The original design was reduced from 22 samples to 6 samples/patient and both doses (intravenous oral) were administered within 8 hours. Compared with the prior information given by the published ciclosporin population PK model, the expected standard deviations (SDs) of the individual parameters for clearance and bioavailability could be reduced by, on average, 40% under the optimized sparse designs. The gain of performing the original rich design compared with the optimal reduced design, considering the standard errors of the parameter estimates, was found to be minimal. This application demonstrates, in a practical clinical scenario, how optimal design techniques may be used to improve diagnostic procedures given available software and methods.

Opportunities to optimize tacrolimus therapy in solid organ transplantation: report of the European consensus conference

In 2007, a consortium of European experts on tacrolimus (TAC) met to discuss the most recent advances in the drug/dose optimization of TAC taking into account specific clinical situations and the analytical methods currently available and drew some recommendations and guidelines to help clinicians with the practical use of the drug. Pharmacokinetic, pharmacodynamic, and more recently pharmacogenetic approaches aid physicians to individualize long-term therapies as TAC demonstrates a high degree of both between- and within-individual variability, which may result in an increased risk of therapeutic failure if all patients are administered a uniform dose. TAC has undoubtedly benefited from therapeutic drug monitoring, but interpretation of the blood concentration is confounded by the relative differences between the assays. Single time points, limited sampling strategies, and area under concentration-time curve have all been considered to determine the most appropriate sampling procedure that correlates with efficacy. Therapeutic trough TAC concentration ranges have changed since the initial introduction of the drug, while still maintaining adequate immunosuppression and avoiding drug-related adverse effects. Pharmacodynamic markers have also been considered advantageous to the clinician, which may better reflect efficacy and safety, taking into account the between-individual variability rather than whole blood concentrations. The choice of method, differences between methods, and potential pitfalls of the method should all be considered when determining TAC concentrations. The recommendations of this consensus meeting regarding the analytical methods include the following: encourage the development and promote the use of analytical methods displaying a lower limit of quantification (1 ng/mL), perform careful validation when implementing a new analytical assay, participate in external proficiency testing programs, promote the use of certified material as calibrators in high-performance liquid chromatography with mass spectrometric detection methods, and take account of the assay and intermethod bias when comparing clinical trial outcomes. It is also important to consider that TAC concentrations may also be influenced by other factors such as specific pharmacokinetic characteristics associated with the population, drug interactions, pharmacogenetics, adverse events that may alter TAC concentrations, and any change in the oral formulation that may result in pharmacokinetic changes. This meeting emphasized the importance of obtaining multicenter prospective trials to assess the efficacy of alternative strategies to TAC trough concentrations whether it is other single time points or area under the concentration-time curve Bayesian estimation using limited sampling strategies and to select, standardize, and validate routine biomarkers of TAC pharmacodynamics.

Flexible limited sampling model for monitoring tacrolimus in stable patients having undergone liver transplantation with samples 4 to 6 hours after dosing is superior to trough concentration

Trough (C0) monitoring is not optimal for therapeutic drug monitoring of tacrolimus. To better estimate systemic exposure of tacrolimus and achieve clinical benefit, an improved therapeutic drug monitoring strategy should be developed. The authors examined which single and combination of time points best estimated the empiric "gold standard" AUC0-12h and developed and validated a new, flexible, and accurate limited sampling model for monitoring tacrolimus in patients having undergone liver transplantation. Twenty-three stable patients with full AUC0-12h were divided into two groups based on area under the concentration-time curve/dose. With multiple regression analysis, limited sampling formulae were derived and population-pharmacokinetic-based limited sampling models were developed and validated. A regression analysis was performed between either area under the concentration-time curves calculated with formulae or models with the reference trapezoidal AUC0-12h. Both formulae and models based on single samples C4-C6 (r2 = 0.94 [MPE/MAPE 0/7]-0.90 [2/8] and 0.97 [0/7]-0.97 [1/5]) showed excellent performance. The calculated area under the concentration-time curve target range for tacrolimus was 90 to 130 h*microg/L. Multiple point sampling performed better, especially when using models (r2 > 0.94). C0 was a less precise predictor of AUC0-12h compared with both formulae and models (r2's 0.68 [5/17] and 0.87 [2/14]). In conclusion, trough concentration monitoring is not an accurate method for assessing systemic exposure to tacrolimus in stable patients having undergone liver transplantation. This new limited sampling model, based on single time points C4-C6, shows excellent performance in estimating the AUC0-12h.

[Therapeutic monitoring of immunosuppressive drugs: interest of calcineurin activity assessment in liver transplantation]

Therapeutic monitoring of calcineurin inhibitors (ciclosporin and tacrolimus) consists in pharmacokinetic monitoring. Pharmacodynamics based on calcineurin activity may be particularly interesting in liver transplantation due to the large intra- and interindividual variability of pharmacokinetics of ciclosporin and tacrolimus. A recent investigation on the pharmacokinetic-pharmacodynamic relationship of tacrolimus showed that monitoring of calcineurin activity in PBMC may be particularly relevant within the first three post-transplantation months. Thereafter, the monitoring of trough blood concentrations of tacrolimus remains adequate. Moreover, two clinical investigations carried out within the early and late post-transplantation periods reported a promising result which is a positive correlation between calcineurin activity and incidence of graft rejection, whatever graft type and calcineurin inhibitors. In each study, transplanted recipients with a graft rejection exhibited a greater trough calcineurin activity compared to patients without graft rejection. However, prospective investigations are required because of the small cohorts of patients enrolled in both studies. The aim of these investigations will be to confirm the interest of calcineurin activity monitoring as a marker of cellular immunity and its positive link with pharmacokinetic monitoring.

A Bayesian approach for population pharmacokinetic modelling of sirolimus

AIMS

To explore a Bayesian approach for the pharmacokinetic analysis of sirolimus concentration data arising from therapeutic drug monitoring (poorly informative concentration-time point design), and to explore possible covariate relationships for sirolimus pharmacokinetics.

METHODS

Sirolimus concentration-time data were available as part of routine clinical care from 25 kidney transplant recipients. Most samples were taken at or near the trough time point at steady state. The data were analyzed using a fully conditional Bayesian approach with PKBUGS (v 1.1)/WinBUGS (v 1.3). Features of the data included noncompliance and missing concentration measurements below the limit of sensitivity of the assay. Informative priors were used.

RESULTS

A two-compartment model with proportional residual error provided the best fit to the data (consisting of 315 sirolimus concentration-time points). The typical value for the apparent clearance (CL/F ) was 12.5 l h(-1) at the median age of 44 years. Apparent CL was found to be inversely related to age with a posterior probability of a clinically significant effect of 0.734.

CONCLUSIONS

A population pharmacokinetic model was developed for sirolimus using a novel approach. Bayesian modelling with informative priors allowed interpretation of a significant covariate relationship, even using poorly informative data.

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.

Relationships of tacrolimus pharmacokinetic measures and adverse outcomes in stable adult liver transplant recipients

BACKGROUND AND OBJECTIVES

Alternative measures to trough concentrations [non-trough concentrations and limited area under the concentration-time curve (AUC)] have been shown to better predict tacrolimus AUC. The aim of this study was to determine if these are also better predictors of adverse outcomes in long term liver transplant recipients.

METHODS

The associations between tacrolimus trough concentrations (C(0)), non-trough concentrations (C(1), C(2), C(4), C(6/8)), and AUC(0-12) and the occurrence of hypertension, hyperkalaemia, hyperglycaemia and nephrotoxicity were assessed in 34 clinically stable liver transplant patients.

RESULTS AND DISCUSSION

The most common adverse outcome was hypertension, prevalence of 36%. Hyperkalaemia and hyperglycaemia had a prevalence of 21% and 13%, respectively. A sequential population pharmacokinetic/pharmacodynamic approach was implemented. No significant association between predicted C(0), C(1), C(2), C(4), C(6/8) or AUC(0-12) and adverse effects could be found. Tacrolimus concentrations and AUC measures were in the same range in patients with and without adverse effects.

CONCLUSIONS

Measures reported to provide benefit, preventing graft rejection and minimizing acute adverse effects in the early post-transplant period, were not able to predict adverse effects in stable adult liver recipients whose trough concentrations were maintained in the notional target range.