Patient characteristics influencing ciclosporin pharmacokinetics and accurate Bayesian estimation of ciclosporin exposure in heart, lung and kidney transplant patients

The Impact of Spironolactone Co-administration on Cyclosporin Initial Dosage Optimization for Pediatric Refractory Nephrotic Syndrome

OBJECTIVES

Cyclosporin has been used for the treatment of pediatric refractory nephrotic syndrome (PRNS). However, the narrow therapeutic window and large pharmacokinetic variability make it difficult to individualize cyclosporin administration. Meanwhile, spironolactone has been reported to affect cyclosporin metabolism in PRNS patients. This study aims to explore the initial dosage optimization of cyclosporin in PRNS based on the impact of spironolactone co-administration.

METHODS

Monte Carlo simulation based on a previously established cyclosporin population pharmacokinetic model for PRNS was used to design cyclosporin dosing regimen.

RESULTS

In this study, the probability of drug concentration reaching the target and the convenience of times of administration were considered comprehensively. The optimal administration regimen in PRNS without spironolactone was 6, 5, 4 and 3 mg/kg cyclosporin split into two doses for the body weight of 5-8, 8-18, 18-46 and 46-70 kg, respectively. The optimal administration regimen in PRNS with spironolactone was 4, 3, 2 mg/kg cyclosporin split into two doses for body weight of 5-14, 14-65, and 65-70 kg, respectively.

CONCLUSION

The cyclosporin dosing regimen for PRNS based on Monte Carlo simulation was systematically developed and the initial dosage optimization of cyclosporin in PRNS was recommended for the first time.

Pharmacodynamic Monitoring of Ciclosporin and Tacrolimus: Insights From Nuclear Factor of Activated T-Cell-Regulated Gene Expression in Healthy Volunteers

BACKGROUND

Although therapeutic drug monitoring of calcineurin inhibitor (CNI) concentrations is performed routinely in clinical practice, an identical concentration may lead to different effects in different patients. Although the quantification of nuclear factor of activated T-cell-regulated gene expression (NFAT-RGE) is a promising method for measuring individual CNI effects, CNI pharmacodynamics are as of yet incompletely understood.

METHODS

CNI concentrations and NFAT-RGEs were quantified in 24 healthy volunteers receiving either ciclosporin or tacrolimus in 2 clinical trials. NFAT-RGE was measured using quantitative reverse transcription polymerase chain reaction tests of whole-blood samples. Pharmacokinetics and pharmacodynamics were analyzed using compartmental modeling and simulation. In addition, NFAT-RGE data from renal transplant patients were analyzed.

RESULTS

The average NFAT-RGE during a dose interval was reduced to approximately 50% with ciclosporin, considering circadian changes. The different effect-time course with ciclosporin and tacrolimus could be explained by differences in potency (IC 50 204 ± 41 versus 15.1 ± 3.2 mcg/L, P < 0.001) and pharmacokinetics. Residual NFAT-RGE at the time of maximum concentration (RGE tmax ) of 15% when using ciclosporin and of 30% when using tacrolimus was associated with similar average NFAT-RGEs during a dose interval. Renal transplant patients had similar but slightly stronger effects compared with healthy volunteers.

CONCLUSIONS

Ciclosporin and tacrolimus led to similar average suppression of NFAT-RGE in a dose interval, despite considerably different RGE tmax . Pharmacodynamic monitoring of average NFAT-RGE should be considered. When using NFAT-RGE at specific time points, the different effect-time courses and circadian changes of NFAT-RGEs should be considered.

Factors Affecting Time-Varying Clearance of Cyclosporine in Adult Renal Transplant Recipients: A Population Pharmacokinetic Perspective

AIM

The pharmacokinetic (PK) properties of cyclosporine (CsA) in renal transplant recipients are patient- and time-dependent. Knowledge of this time-related variability is necessary to maintain or achieve CsA target exposure. Here, we aimed to identify factors explaining variabilities in CsA PK properties and characterize time-varying clearance (CL/F) by performing a comprehensive analysis of CsA PK factors using population PK (popPK) modeling of long-term follow-up data from our institution.

METHODS

In total, 3674 whole-blood CsA concentrations from 183 patients who underwent initial renal transplantation were analyzed using nonlinear mixed-effects modeling. The effects of potential covariates were selected according to a previous study and well-accepted theoretical mechanisms. Model-informed individualized therapeutic regimens were also evaluated.

RESULTS

A two-compartment model adequately described the data and the estimated mean CsA CL/F was 32.6 L h^-1 (relative standard error: 5%). Allometrically scaled body size, hematocrit (HCT) level, CGC haplotype carrier status, and postoperative time may contribute to CsA PK variability. The CsA bioavailability in patients receiving a prednisolone dose (PD) of 80 mg was 20.6% lower than that in patients receiving 20 mg. A significant decrease (52.6%) in CL/F was observed as the HCT increased from 10.5% to 60.5%. The CL/F of the non-CGC haplotype carrier was 14.4% lower than that of the CGC haplotype carrier at 3 months post operation.

CONCLUSIONS

By monitoring body size, HCT, PD, and CGC haplotype, changes in CsA CL/F over time could be predicted. Such information could be used to optimize CsA therapy. CsA dose adjustments should be considered in different postoperative periods.

Impact of cyclosporine-A concentration in T-cell replete haploidentical allogeneic stem cell transplantation

This paper aims to study whether cyclosporine-A (CSA) levels have an impact on the clinical outcome of patients with T-cell replete haploidentical allogeneic hematopoietic stem cell transplantation (allo-HSCT). We analyzed 140 consecutive patients who had been given T-cell replete haploidentical allo-HSCT in our institute to assess the effect of CSA concentration in the early stages of allo-HSCT on clinical outcomes, such as hematopoietic recovery, acute graft vs host disease (aGVHD), infection, disease-free survival (DFS), and overall survival (OS). The median concentrations of CSA in the blood in the 1st, 2nd, 3rd, and 4th week after allo-HSCT were 218, 235, 263, and 270 ng/mL, respectively. Additionally, 46%, 40%, 27%, and 18% of the patients had CSA blood levels below 200 ng/mL during those weeks. In total, 39 patients developed aGVHD (grade II-IV), for a cumulative incidence of 27.8%, at a median of 32 days. Patients having a low CSA concentration (below 200 ng/mL) in the 3rd week had a higher cumulative incidence of grade II-IV aGVHD (P = .02). In addition, multivariate logistic regression analysis showed that low CSA concentration (below 200 ng/mL) in the 3rd week was an independent risk factor of grade II-IV aGVHD (P = .02; odds ratio = 2.66; 95% CI, 1.15-6.17). However, CSA levels during the first 4 weeks did not have a significant impact on the patients' hematopoietic recovery, infection, DFS, and OS. Our data indicated that adequate management of CSA levels during the peri-engraftment period might improve clinical outcomes for those with T-cell replete haploidentical allo-HSCT.

External evaluation of population pharmacokinetic models for ciclosporin in adult renal transplant recipients

AIMS

Several population pharmacokinetic (popPK) models for ciclosporin (CsA) in adult renal transplant recipients have been constructed to optimize the therapeutic regimen of CsA. However, little is known about their predictabilities when extrapolated to different clinical centres. Therefore, this study aimed to externally evaluate the predictive ability of CsA popPK models and determine the potential influencing factors.

METHODS

A literature search was conducted and the predictive performance was determined for each selected model using an independent data set of 62 patients (471 predose and 500 2-h postdose concentrations) from our hospital. Prediction-based diagnostics and simulation-based normalized prediction distribution error were used to evaluate model predictability. The influence of prior information was assessed using Bayesian forecasting. Additionally, potential factors influencing model predictability were investigated.

RESULTS

Seventeen models extracted from 17 published popPK studies were assessed. Prediction-based diagnostics showed that ethnicity potentially influenced model transferability. Simulation-based normalized prediction distribution error analyses indicated misspecification in most of the models, especially regarding variance. Bayesian forecasting demonstrated that the predictive performance of the models substantially improved with 2-3 prior observations. The predictability of nonlinear Michaelis-Menten models was superior to that of linear compartmental models when evaluating the impact of structural models, indicating the underlying nonlinear kinetics of CsA. Structural model, ethnicity, covariates and prior observations potentially affected model predictability.

CONCLUSIONS

Structural model is the predominant factor influencing model predictability. Incorporation of nonlinear kinetics in CsA popPK modelling should be considered. Moreover, Bayesian forecasting substantially improved model predictability.

Forensic science meets clinical pharmacology: pharmacokinetic model based estimation of alcohol concentration of a defendant as requested by a local prosecutor's office

Drunk driving is a serious social problem. We estimated the blood alcohol concentration of a defendant on the request of local prosecutor's office in Korea. Based on the defendant's history, and a previously constructed pharmacokinetic model for alcohol, we estimated the possible alcohol concentration over time during his driving using a Bayesian method implemented in NONMEM®. To ensure generalizability and to take the parameter uncertainty of the alcohol pharmacokinetic models into account, a non-parametric bootstrap with 1,000 replicates was applied to the Bayesian estimations. The current analysis enabled the prediction of the defendant's possible blood alcohol concentrations over time with a 95% prediction interval. The results showed a high probability that the alcohol concentration was ≥ 0.05% during driving. The current estimation of the alcohol concentration during driving by the Bayesian method could be used as scientific evidence during court trials.

Pharmacokinetic tools for the dose adjustment of ciclosporin in haematopoietic stem cell transplant patients

AIMS

Ciclosporin A (CsA) is used in the prophylaxis and treatment of acute and chronic graft vs. host disease after haematopoietic stem cell (HSCT) transplantation. Our objective was to build and compare three independent Bayesian estimators of CsA area under the curve (AUC) using a limited sampling strategy (LSS), to assist in dose adjustment.

METHODS

The Bayesian estimators were developed using in parallel: two independent parametric modelling approaches (nonmem® and iterative two stage (ITS) Bayesian modelling) and the non-parametric adaptive grid method (Pmetrics®). Seventy-two full pharmacokinetic profiles (at pre-dose and 0.33, 0.66, 1, 2, 3, 4, 6, 8 and 12h after dosing) collected from 40 HSCT patients given CsA were used to build the pharmacokinetic models, while 15 other profiles (n = 7) were kept for validation. For each Bayesian estimator, AUCs estimated using the full profiles were compared with AUCs estimated using three samples.

RESULTS

The pharmacokinetic profiles were well fitted using a two compartment model with first order elimination, combined with a gamma function for the absorption phase with ITS and Pmetrics or an Erlang distribution with nonmem. The derived Bayesian estimators based on a C0-C1 h-C4 h sampling schedule (best LSS) accurately estimated CsA AUC(0,12 h) in the validation group (n = 15; nonmem: bias (mean ± SD)/RMSE 2.05% ± 13.31%/13.02%; ITS: 4.61% ± 10.56%/11.20%; Pmetrics: 0.30% ± 10.12%/10.47%). The dose chosen confronting the three results led to a pertinent dose proposal.

CONCLUSIONS

The developed Bayesian estimators were all able to predict ciclosporin AUC(0,12 h) in HSCT patients using only three blood with minimal bias and may be combined to increase the reliability of CsA dose adjustment in routine.

Population pharmacokinetics of cyclosporine in hematopoietic stem cell transplant patients: consideration of genetic polymorphisms

BACKGROUND

Cyclosporine (CsA), which is used for graft-versus-host disease prophylaxis in allogeneic hematopoietic stem cell transplant (allo-HSCT), has a narrow therapeutic range and large interindividual and intraindividual pharmacokinetic variability. Nevertheless, population pharmacokinetic (PopPK) studies of CsA in allo-HSCT are scarce.

OBJECTIVE

The goal of our study was to build a PopPK model of CsA in allo-HSCT in consideration of demographic, clinical, and genetic polymorphisms data.

METHODS

A total of 34 adult allo-HSCT patients who received CsA were enrolled prospectively. Demographic, clinical, and CYP3A5 *1/*3, CYP2C19 *1/*2/*3, ABCB1 3435C>T, 1236C>T, 2677G>T/A, ABCC2 -24C>T, 1249G>A, VDR Bsml, Apal polymorphisms data were collected. A PopPK modeling was conducted with NONMEM program.

RESULTS

A 1-compartment model with a 2-transit absorption compartment model was developed. After the stepwise covariate model building process, weight was incorporated into clearance (CL) as a power function model with the exponent value of 0.419. The final typical estimate of CL was 21.2 L/h; volume of distribution was 430 L; logit-transformed bioavailability was 1.49 (bioavailability: 81%); and transit compartment rate was 2.87/h. None of the genetic polymorphisms in CYP3A5, CYP2C19, ABCB1, ABCC2, and VDR were significant covariates in the pharmacokinetics of CsA.

CONCLUSIONS

In our study, it was observed that weight had a significant effect on CL. Genetic polymorphisms did not affect CsA pharmacokinetics. Prospective studies with a larger number of participants is needed to validate the results of this study.

Population pharmacokinetics and individualized dosage prediction of cyclosporine in allogeneic hematopoietic stem cell transplant patients

BACKGROUND

Cyclosporine (CsA), a potent immunosuppressive agent used to prevent rejection, is characterized by large individual variability. The purpose of this study was to explore the pharmacokinetic characteristics of CsA and establish a CsA population pharmacokinetic model that could be used for personalized therapy in allogeneic hematopoietic stem cell transplant (allo-HSCT) patients.

METHODS

Clinical data were obtained from 117 allo-HSCT patients. The data analysis was performed using NONMEM software. A first-order conditional estimation with interaction (FOCE-I) method within NONMEM was used to estimate the parameters. The covariates, including demographics, hematological indices, biochemical levels, concurrent drugs, and genetic polymorphisms of CYP3A4, CYP3A5, and ABCB1, were evaluated quantitatively. The stability of the final model was validated by a nonparametric bootstrap procedure.

RESULTS

A total of 1,571 observed concentrations were collected. A 1-compartment model with first-order absorption and elimination adequately described the pharmacokinetics of CsA. The typical values for clearance (CL), volume of distribution (V), and bioavailability were 29.6 L/hr, 605 L, and 0.619, respectively. The interindividual variability of these parameters was 20.4, 66.1, and 30.4%, respectively. The residual error was 31.4% and 23.7 ng/mL. The duration of CsA therapy, hematocrit, antifungal agent administration, triglycerides, and weight were identified as the main covariates that influenced CL, and hematocrit had a significant effect on V. The internal validation showed that the final model was stable and accurate.

CONCLUSIONS

This study established a population pharmacokinetic model of CsA in allo-HSCT patients that could provide the foundation for personalized use of CsA in the clinic.

Population pharmacokinetics of ciclosporin in Chinese children with aplastic anemia: effects of weight, renal function and stanozolol administration

AIM

To develop a population pharmacokinetic model for the immunosuppressant ciclosporin in Chinese children with aplastic anemia and to identify covariates influencing ciclosporin pharmacokinetics.

METHODS

A total of 102 children with either acquired or congenital aplastic anemia aged 8.8±3.6 years (range 0.9-17.6 years) were included. Therapeutic drug monitoring (TDM) data for ciclosporin were collected. The population pharmacokinetic model of ciclosporin was described using the nonlinear mixed-effects modeling (NONMEM) VI software. The final model was validated using bootstrap and normalized prediction distribution errors.

RESULTS

A one-compartment model with first-order absorption and elimination was developed. The estimated CL/F was 15.1, which was lower than those of children receiving stem cell or kidney transplant reported in the West (16.9-29.3). The weight normalized CL/F was 0.45 (range: 0.27-0.70) Lh(-1)·kg(-1). The covariate analysis identified body weight, serum creatinine and concomitant administration of the anabolic steroid stanozolol as individual factors influencing the CL/F of ciclosporin.

CONCLUSION

Our model could be used to optimize the ciclosporin dosing regimen in Chinese children with aplastic anemia.

Population pharmacokinetics of cyclosporine in transplant recipients

A number of classical pharmacokinetic studies have been conducted in transplant patients. However, they suffer from some limitations, for example, (1) the study design was limited to intense blood sampling in small groups of patients during a certain posttransplant period, (2) patient factors were evaluated one at a time to identify their association with the pharmacokinetic parameters, and (3) mean pharmacokinetic parameters often cannot be precisely estimated due to large intraindividual variability. Population pharmacokinetics provides a potential means of addressing these limitations and is a powerful tool to evaluate the magnitude and consistency of drug exposure. Population pharmacokinetic studies of cyclosporine focused solely on developing limited sampling strategies and Bayesian estimators to estimate drug exposure, have been summarized before, and are, therefore, not a subject of this review. The major focus of this review is to describe factors (demographic factors, hepatic and gastrointestinal functions, drug-drug interactions, genetic polymorphisms of drug metabolizing enzymes and transporters) that have been identified to contribute to the large portion of observed variability in the pharmacokinetics of cyclosporine in transplant patients. This review summarizes and interprets the conclusions as well as the nonlinear mixed-effects modeling methodologies used in such studies. A highly diversified collection of structural models, variability models, and covariate submodels have been evaluated and validated using internal or external validation methods. This review also highlights areas where additional research is warranted to improve the models since a portion of model variability still remains unexplained.

Impact of tacrolimus intraindividual variability and CYP3A5 genetic polymorphism on acute rejection in kidney transplantation

BACKGROUND

Wide variation in tacrolimus concentrations and low tacrolimus exposure have been reported to be associated with poor renal graft outcomes in non-Asians. The CYP3A5 polymorphism is a representative genetic factor that might affect this association, together with environmental factors. We investigated whether tacrolimus variability or the mean tacrolimus trough concentration can influence kidney allograft outcomes in Asians and whether the CYP3A5 polymorphism (rs776746) can affect this relationship.

METHODS

Data from renal transplant patients between 2000 and 2010 were analyzed retrospectively. The tacrolimus intraindividual variability (IIV) and the mean tacrolimus trough concentration were calculated from the tacrolimus concentrations between 6 and 12 months after transplantation.

RESULTS

A total of 249 renal transplant patients were enrolled. The patients with higher tacrolimus IIV had shorter rejection-free survival (P = 0.002). However, there was no difference in rejection-free survival between CYP3A5 expressers and nonexpressers. The tacrolimus IIV was not associated with the CYP3A5 polymorphism. High IIV of tacrolimus was an independent risk factor of biopsy-proven acute rejection after adjusting for mean tacrolimus concentration, HLA mismatch, induction therapy, donor type, and CYP3A5 polymorphism (hazard ratio 2.655, 95% confidence interval 1.394-5.056). Interestingly, the impact of tacrolimus IIV on acute rejection was significant in CYP3A5 expressers, whereas it was not in CYP3A5 nonexpressers.

CONCLUSIONS

The IIV of tacrolimus trough concentrations had a significant impact on rejection-free survival. The effect was influenced by CYP3A5 polymorphism, although the tacrolimus variability itself was not determined by the CYP3A5 polymorphism.

Development of population PK model with enterohepatic circulation for mycophenolic acid in patients with childhood-onset systemic lupus erythematosus

AIM

This study aimed to develop a population pharmacokinetic (PK) enterohepatic recycling model for MPA in patients with childhood-onset systemic lupus erythematosus (cSLE).

METHODS

MPA concentration-time data were from outpatients on stable oral mycophenolate mofetil (MMF) and collected under fasting conditions, with standardized meals (1 and 4 h post-dose). Sampling times were pre-dose, 20, 40 min, 1, 1.5, 2, 3, 4, 6 and 9 h, post dose. The population PK analysis simultaneously modelled MPA and 7-O-MPA-β-glucuronide (MPAG) concentrations using nonlinear mixed effect modelling.

RESULTS

PK analysis included 186 MPA and MPAG concentrations (mg l(-1)) from 19 patients. cSLE patients, age range 10-28 years, median 16.5 years were included. Mean ± SD disease duration was 3.8 ± 3.7 years. The final PK model included a gallbladder compartment for enterohepatic recycling and bile release time related to meal times, with first order absorption and single series of transit compartments. The PK estimates for MPA were CL(1) /F 25.3 l h(-1), V(3) /F 20.9 l, V(4) /F 234 l and CL(2) /F 19.8 l h(-1).

CONCLUSION

The final model fitted the complex processes of absorption and enterohepatic circulation (EHC) in those treated with MMF for cSLE and could be applied in Bayesian dose optimization algorithms.

Optimal sampling strategy development methodology using maximum a posteriori Bayesian estimation

Maximum a posteriori Bayesian (MAPB) pharmacokinetic parameter estimation is an accurate and flexible method of estimating individual pharmacokinetic parameters using individual blood concentrations and prior information. In the past decade, many studies have developed optimal sampling strategies to estimate pharmacokinetic parameters as accurately as possible using either multiple regression analysis or MAPB estimation. This has been done for many drugs, especially immunosuppressants and anticancer agents. Methods of development for optimal sampling strategies (OSS) are diverse and heterogeneous. This review provides a comprehensive overview of OSS development methodology using MAPB pharmacokinetic parameter estimation, determines the transferability of published OSSs, and compares sampling strategies determined by MAPB estimation and multiple regression analysis. OSS development has the following components: 1) prior distributions; 2) reference value determination; 3) optimal sampling time identification; and 4) validation of the OSS. Published OSSs often lack all data necessary for the OSS to be clinically transferable. MAPB estimation is similar to multiple regression analysis in terms of predictive performance but superior in flexibility.

The evolution of population pharmacokinetic models to describe the enterohepatic recycling of mycophenolic acid in solid organ transplantation and autoimmune disease

With the increasing use of mycophenolic acid (MPA) as an immunosuppressant in solid organ transplantation and in treating autoimmune diseases such as systemic lupus erythematosus, the need for strategies to optimize therapy with this agent has become increasingly apparent. This need is largely based on MPA's significant between-subject and between-occasion (within-subject) pharmacokinetic variability. While there is a strong relationship between MPA exposure and effect, the relationship between drug dose, plasma concentration and exposure (area under the concentration-time curve [AUC]) is very complex and remains to be completely defined. Population pharmacokinetic models using various approaches have been proposed over the past 10 years to further evaluate the pharmacokinetic and pharmacodynamic behaviour of MPA. These models have evolved from simple one-compartment linear iterations to complex multi-compartment versions that try to include various factors, which may influence MPA's pharmacokinetic variability, such as enterohepatic recycling and pharmacogenetic polymorphisms. There have been major advances in the understanding of the roles transport mechanisms, metabolizing and other enzymes, drug-drug interactions and pharmacogenetic polymorphisms play in MPA's pharmacokinetic variability. Given these advances, the usefulness of empirical-based models and the limitations of nonlinear mixed-effects modelling in developing mechanism-based models need to be considered and discussed. If the goal is to individualize MPA dosing, it needs to be determined whether factors which may contribute significantly to variability can be utilized in the population pharmacokinetic models. Some pharmacokinetic models developed to date show promise in being able to describe the impact of physiological processes such as enterohepatic recycling. Most studies have historically been based on retrospective data or poorly designed studies which do not take these factors into consideration. Modelling typically has been undertaken using non-controlled therapeutic drug monitoring data, which do not have the information content to support the development of complex mechanistic models. Only a few recent modelling approaches have moved away from empiricism and have included mechanisms considered important, such as enterohepatic recycling. It is recognized that well thought-out sampling schedules allow for better evaluation of the pharmacokinetic data. It is not possible to undertake complex absorption modelling with very few samples being obtained during the absorption phase (which has often been the case). It is important to utilize robust AUC monitoring which is now being propagated in the latest consensus guideline on MPA therapeutic drug monitoring. This review aims to explore the biological factors that contribute to the clinical pharmacokinetics of MPA and how these have been introduced in the development of population pharmacokinetic models. An overview of the processes involved in the enterohepatic recycling of MPA will be provided. This will summarize the components that complicate absorption and recycling to influence MPA exposure such as biotransformation, transport, bile physiology and gut flora. Already published population pharmacokinetic models will be examined, and the evolution of these models away from empirical approaches to more mechanism-based models will be discussed.

Computer-assisted cyclosporine dosing performs better than traditional dosing in renal transplant recipients: results of a pilot study

Cyclosporine A (CsA) is widely used after organ transplantation. Its narrow therapeutic window and large pharmacokinetic variability makes therapeutic drug monitoring (TDM) demanding and frequent dose adjustments are needed, especially early after transplantation. The aim of the present pilot study was to compare accuracy of CsA TDM by experienced clinicians against a computer-assisted dosing model. Renal transplant recipients on CsA, prednisolone, and mycophenolate were included 2 weeks after transplantation, randomized (1:1) to either computer dosing (MAP-BE) or control (CONTR) and followed for at least 8 weeks. A maximum a posteriori probability Bayesian estimation method, applying a population pharmacokinetic model and the POSTHOC option in nonlinear mixed effects modeling, was used to individualize CsA doses in the MAP-BE group. Forty patients (31 men, 27.5% living donor) between 28 and 80 years were included. A total of 798 CsA concentration measurements and adherent dosing evaluations/adjustments were performed. During the entire study, blood concentrations were on average 10% +/- 5% from the predefined therapeutic target range in the MAP-BE group, as compared with 13% +/- 8% in the CONTR group (P = 0.042). However, there was no significant difference between groups regarding the percentage of CsA concentrations truly within the therapeutic windows [MAP-BE: 37% +/- 17%, CONTR: 33% +/- 15% (P = 0.57)] or in CsA dose [MAP-BE: 3.55 +/- 0.8, CONTR: 3.90 +/- 0.9 mg/kg/d (P = 0.26)]. Acute rejections were present in 4 and 3 patients, respectively (P = 1.00). The computer-assisted TDM-targeted CsA blood concentrations significantly better than experienced transplant physicians. A possible favorable effect on short- and long-term outcome needs to be verified in further, properly powered, clinical trials.

High within-patient variability in the clearance of tacrolimus is a risk factor for poor long-term outcome after kidney transplantation

BACKGROUND

We hypothesized that a high within-patient variability in clearance of tacrolimus and mycophenolate mofetil (MMF) would put patients at risk for periods of over- or underimmunosuppression and would thus lead to long-term chronic allograft nephropathy and graft loss after transplantation.

METHODS

From 297 patients transplanted between 1 January 2000 and 31 December 2004, the within-patient variability in clearance was calculated from tacrolimus whole-blood concentrations and mycophenolic acid (MPA) plasma concentrations drawn between 6 and 12 months post-transplantation. As a primary outcome, a composite end point consisting of graft loss, biopsy-proven chronic allograft nephropathy and 'doubling in plasma creatinine concentration in the period between t = 12 months post-transplantation and last follow-up' was used.

RESULTS

In the study population of 297 patients, 34 patients reached the primary end point of graft failure. The within-patient variability in the clearance of tacrolimus and three other covariates are significant risk factors for reaching the composite end point of failure [P-values for intraindividual tacrolimus variability = 0.003, biopsy-proven acute rejection (BPAR) = 0.003, recipient age at transplantation = 0.005]. The mean tacrolimus concentration for controls [7.4 (+/- 2.9) ng/mL] and for failures [6.9 (+/- 2.5) ng/mL] was similar. Within-patient variability in the clearance of MPA was not related to reaching the composite end point of failure.

CONCLUSIONS

This study shows a significant relationship between the high within-patient variability in the clearance of tacrolimus, but not for MPA, and long-term graft failure.

A population pharmacokinetic model of ciclosporin applicable for assisting dose management of kidney transplant recipients

BACKGROUND AND OBJECTIVE

The pharmacokinetic disposition of ciclosporin shows great intra- and interpatient variability, and that combined with a narrow therapeutic window makes therapeutic drug monitoring of ciclosporin necessary. The nonlinear mixed-effects population pharmacokinetic program NONMEM predicts individual pharmacokinetic parameters based not only on individual patient observations but also on population characteristics and the patient's covariates. The aim of this model development is to potentially use it in the clinical setting to optimize ciclosporin dosing in renal transplant recipients.

METHODS

A population pharmacokinetic model of ciclosporin has been developed with NONMEM using full 12-hour pharmacokinetic profiles from 29 renal transplant recipients, 3 months of daily follow-up data from an additional 11 recipients, and both 3 months of follow-up data and full 12-hour pharmacokinetic profiles from nine patients. The internal validation of the model was based on data splitting and jack-knife methods. In addition, the model was validated for its clinical applicability on standard trough and 2-hour post-dose concentration data from 12 additional patients with 3 months of follow-up.

RESULTS

The model that best described the ciclosporin data was a two-compartment model with first-order absorption process with lagged time. The population pharmacokinetic parameters were oral clearance (CL/F) = 26.9 L/h; central volume of distribution after oral administration (V(1)/F) = 24.4 L; absorption rate constant (k(a)) = 0.544 h-1; lag time = 0.460 h; peripheral volume of distribution = 1119 L and intercompartmental clearance after oral administration (Q/F) = 19.6 L/h. Three covariates had significant effect on a total of six pharmacokinetic parameters. These were bodyweight on V(1)/F and k(a), time after transplantation on k(a), and age on CL/F, k(a) and V(1)/F. Cytochrome P450 3A5 genotype was also a significant covariate but was not included in the final model since such information is not available in clinical practice. The external validation showed that the model was able to predict ciclosporin concentrations in the 12 new patients with an average predictive error of 17.4 +/- 14% when the standard sample concentrations from the previous week were given.

CONCLUSION

A NONMEM pharmacokinetic model for ciclosporin in renal transplant recipients was successfully developed and validated for the first 3 months post-transplantation. The model showed good predictability in a new patient cohort. After further clinical validation, the model may be applicable as a clinical tool for optimizing ciclosporin dosing in renal transplant recipients in the early post-transplant period.

Pharmacokinetic monitoring of intravenous cyclosporine A in pediatric stem-cell transplant recipients. The trough level is not enough

In order to monitor CsA serum levels after SCT, trough levels (C0) are widely used. The aim of this study was to estimate the population and individual PK parameters for patients receiving intravenous CsA after SCT. In 27 pediatric patients after SCT receiving CsA (3 mg/kg/day) every 12 h, a total of 289 CsA concentrations was obtained. To describe the PK parameters of CsA, a two-compartment model with first order elimination was used. Covariate analysis identified body weight, age, and the co-administration with itraconazole and tobramycine as factors influencing the Cl. The statistical comparison of AUC, trough level, and C2 indicates a correlation between AUC and C2, but no correlation between the AUC and C0, r = 0.24 (p = 0.146) vs. r = 0.526 (p = 0.000692), respectively. Our results underscore the fact that CsA trough levels do not reflect the drug exposure in patients receiving intravenous CsA after SCT. By contrast, CsA blood levels measured 2-6 h after CsA infusion showed a better correlation with the AUC. Our data provide new information to optimize the balancing act between GvHD-prophylaxis, graft vs. leukemia effect, and CsA side-effects after SCT.

Pharmacogenetic characterization of sulfasalazine disposition based on NAT2 and ABCG2 (BCRP) gene polymorphisms in humans

The role of breast cancer resistance protein (BCRP), an efflux ABC transporter, in the pharmacokinetics of substrate drugs in humans is unknown. We investigated the impact of genetic polymorphisms of ABCG2 (421C>A) and NAT2 on the pharmacokinetics of sulfasalazine (SASP), a dual substrate, in 37 healthy volunteers, taking 2,000 mg of conventional SASP tablets. In ABCG2, SASP AUC(0-48) of C/C, C/A, and A/A subjects was 171 +/- 85, 330 +/- 194, and 592 +/- 275 microg h/ml, respectively, with significant differences among groups. In contrast, AUC(0-48) of sulfapyridine (SP) tended to be lower in subjects with the ABCG2-A allele as homozygosity. In NAT2, AUC(AcSP)/AUC(SP) was significantly higher in rapid than in intermediate and slow acetylator (SA) genotypes. We successfully described the pharmacokinetics of SASP, SP, and N -acetylsulfapyridine (AcSP) simultaneously by nonlinear mixed-effects modeling (NONMEM) analysis with regard to both gene polymorphisms. The data indicate that SASP is a candidate probe of BCRP, particularly in its role in intestinal absorption.