A possible simplification for the estimation of area under the curve (AUC₀₋₁₂) of enteric-coated mycophenolate sodium in renal transplant patients receiving tacrolimus

Post-transplant complications, patient, and graft survival in pediatric and adolescent kidney transplant recipients at a tropical tertiary care center across two immunosuppression eras

BACKGROUND

We report pediatric PAKT patient and graft outcomes at a large tropical tertiary center spanning two transplant eras.

METHODS

In this retrospective cohort study, all children ≤18 years who underwent kidney transplantation at our center between 1991 and 2016 were included. Data pertaining to their baseline characteristics, post-transplant events, and outcome were retrieved from transplant records and compared between transplant eras (1991-2005 and 2006-2016).

RESULTS

A total of 139 children (mean age 15.2 ± 2.9 years) underwent PAKT during this period. The incidence of UTIs, CMV disease, BKVN, invasive fungal infections, new-onset diabetes after transplant, leucopenia, and recurrent NKD was higher in the 2006-2016 era (P < .001 for all), while 1-year cumulative BPAR was comparable (P = .100). Five-year graft and patient survival in the two eras were 89.9% and 94.2% (P = .365) and 92.1% and 95.3% (P = .739), respectively. Incidence of CMV disease, BKVN, graft loss, and death was lower in the calcineurin withdrawal group. Non-adherence accounted for 36% of graft loss; infections caused 43.7% of deaths. On multivariate Cox proportional hazards analysis, independent predictors for graft loss were UTIs and blood transfusion naïve status and for death were serious infections and glomerular NKD.

CONCLUSIONS

PAKT in India has excellent long-term graft outcomes, though patient outcomes remain suboptimal owing to a high burden of infections. Current immunosuppression protocols need to be re-examined to balance infection risk, graft, and patient survival.

Personalized Therapy for Mycophenolate: Consensus Report by the International Association of Therapeutic Drug Monitoring and Clinical Toxicology

ABSTRACT

When mycophenolic acid (MPA) was originally marketed for immunosuppressive therapy, fixed doses were recommended by the manufacturer. Awareness of the potential for a more personalized dosing has led to development of methods to estimate MPA area under the curve based on the measurement of drug concentrations in only a few samples. This approach is feasible in the clinical routine and has proven successful in terms of correlation with outcome. However, the search for superior correlates has continued, and numerous studies in search of biomarkers that could better predict the perfect dosage for the individual patient have been published. As it was considered timely for an updated and comprehensive presentation of consensus on the status for personalized treatment with MPA, this report was prepared following an initiative from members of the International Association of Therapeutic Drug Monitoring and Clinical Toxicology (IATDMCT). Topics included are the criteria for analytics, methods to estimate exposure including pharmacometrics, the potential influence of pharmacogenetics, development of biomarkers, and the practical aspects of implementation of target concentration intervention. For selected topics with sufficient evidence, such as the application of limited sampling strategies for MPA area under the curve, graded recommendations on target ranges are presented. To provide a comprehensive review, this report also includes updates on the status of potential biomarkers including those which may be promising but with a low level of evidence. In view of the fact that there are very few new immunosuppressive drugs under development for the transplant field, it is likely that MPA will continue to be prescribed on a large scale in the upcoming years. Discontinuation of therapy due to adverse effects is relatively common, increasing the risk for late rejections, which may contribute to graft loss. Therefore, the continued search for innovative methods to better personalize MPA dosage is warranted.

Evaluation of Multiple Linear Regression-Based Limited Sampling Strategies for Enteric-Coated Mycophenolate Sodium in Adult Kidney Transplant Recipients

BACKGROUND

Although multiple linear regression-based limited sampling strategies (LSSs) have been published for enteric-coated mycophenolate sodium, none have been evaluated for the prediction of subsequent mycophenolic acid (MPA) exposure. This study aimed to examine the predictive performance of the published LSS for the estimation of future MPA area under the concentration-time curve from 0 to 12 hours (AUC0-12) in renal transplant recipients.

METHODS

Total MPA plasma concentrations were measured in 20 adult renal transplant patients on 2 occasions a week apart. All subjects received concomitant tacrolimus and were approximately 1 month after transplant. Samples were taken at 0, 0.33, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 6, and 8 hours and 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 2, 3, 4, 6, 9, and 12 hours after dose on the first and second sampling occasion, respectively. Predicted MPA AUC0-12 was calculated using 19 published LSSs and data from the first or second sampling occasion for each patient and compared with the second occasion full MPA AUC0-12 calculated using the linear trapezoidal rule. Bias (median percentage prediction error) and imprecision (median absolute prediction error) were determined.

RESULTS

Median percentage prediction error and median absolute prediction error for the prediction of full MPA AUC0-12 were <15% for 4 LSSs, using the data from the same (second) occasion. One equation (1.583C1 + 0.765C2 + 0.369C2.5 + 0.748C3 + 1.518C4 + 2.158C6 + 3.292C8 + 3.6690) showed bias and imprecision <15% for the prediction of future MPA AUC0-12, where the predicted AUC0-12 from the first occasion was compared with the full AUC0-12 from the second. All LSSs with an acceptable predictive performance included concentrations taken at least 6 hours after the dose.

CONCLUSIONS

Only one LSS had an acceptable bias and precision for future estimation. Accurate dosage prediction using a multiple linear regression-based LSS was not possible without concentrations up to at least 8 hours after the dose.

Estimation of Mycophenolic Acid Area Under the Curve With Limited-Sampling Strategy in Chinese Renal Transplant Recipients Receiving Enteric-Coated Mycophenolate Sodium

BACKGROUND

The enteric-coated mycophenolate sodium (EC-MPS), whose active constituent is mycophenolic acid (MPA), has been widely clinically used for organ transplant recipients. However, its absorption is delayed due to its special designed dosage form, which results in difficulty to monitor the exposure of the MPA in patients receiving the EC-MPS. This study was aimed at developing a relatively practical and precise model with limited sampling strategy to estimate the 12-hour area under the concentration-time curve (AUC0-12 h) of MPA for Chinese renal transplant recipients receiving EC-MPS.

METHODS

A total of 36 Chinese renal transplant recipients receiving the EC-MPS and tacrolimus were recruited in this study. The time point was 2 weeks after the transplantation for all the patients. The MPA concentrations were measured with enzyme-multiplied immunoassay technique for 11 blood specimens collected predose and at 0.5, 1, 1.5, 2, 2.5, 3, 4, 6, 8, and 12 hours after the morning dose of EC-MPS. The measured AUC was calculated with these 11 points of MPA concentrations with the linear trapezoidal rule. Limited sampling strategy was used to develop models for estimated AUC in the model group (n = 18). The bias and precision of different models were evaluated in the validation group (n = 18).

RESULTS

C4 showed the strongest correlation with the measured AUC. The best 3 time point equation was 6.629 + 8.029 × C0 + 0.592 × C3 + 1.786 × C4 (R = 0.910; P < 0.001), whereas the best 4 time point equation was 3.132 + 5.337 × C0 + 0.735 × C3 + 1.783 × C4 + 3.065 × C8 (R = 0.959; P < 0.001). When evaluated in the validation group, the 4 time point model had a much better performance than the 3 time point model: for the 4 time point model: R = 0.873, bias = 0.505 [95% confidence interval (CI), -10.159 to 11.170], precision = 13.370 (95% CI, 5.186-21.555), and 77.8% of estimated AUCs was within 85%-115% of the measured AUCs; for the 3 time point model: R = 0.573, bias = 6.196 (95% CI, -10.627 to 23.018), precision = 21.286 (95% CI, 8.079-34.492), and 50.0% of estimated AUCs was within 85%-115% of the measured AUCs.

CONCLUSIONS

It demanded at least 4 time points to develop a relatively reliable model to estimate the exposure of MPA in renal transplant recipients receiving the EC-MPS. The long time span needed restricted its application, especially for the outpatients, but it could be a useful tool to guide the personalized prescription for the inpatients.

Therapeutic drug monitoring of enteric-coated mycophenolate sodium by limited sampling strategies is associated with a high rate of failure

Background

Therapeutic drug monitoring of mycophenolic acid (MPA) is usually performed with a limited sampling strategy (LSS), which relies on a limited number of blood samples and subsequent extrapolation of the global exposure to MPA. LSS is usually performed successfully with mycophenolate mofetil (MMF), but data on enteric-coated mycophenolate sodium (EC-MPS) are scarce. Here, we evaluated the feasibility of 6-h LSS therapeutic drug monitoring with EC-MPS compared with MMF monitoring among kidney transplant recipients.

Methods

Sixty-two patients who received EC-MPS during the first 6 months of transplantation were compared with a matched group of 64 MMF-treated kidney transplant recipients. The area under the curve (AUC) was computed by LSS using multiple concentration time points (0, 1, 2, 3 and 6 h post-dose) and a trapezoidal rule. Patients had MPA therapeutic drug monitoring performed on two occasions, one within 2 weeks and the second after 3–4 months of transplantation.

Results

EC-MPS monitoring and MMF therapeutic drug monitoring were not interpretable in 34.5% (n = 40/116) and 1.8% (n = 2/112) of patients, respectively {relative risk [RR] 19.3 [95% confidence interval (CI) 4.8–78.0]; P < 0.0001}. The main cause of abnormal EC-MPS therapeutic drug monitoring was delayed absorption of both the previous evening and the morning dose, resulting in MPA plasma levels before the next morning dose being higher than MPA plasma levels measured at 1, 2 and 3 h after taking EC-MPS. Cyclosporin in association with MMF significantly increased the risk of low AUC values (<30 mg h/L) in comparison with tacrolimus [55% (n = 11/20) and 10% (n = 9/88), respectively; RR 5.4 (95% CI 2.6–11.2); P < 0.0001].

Conclusions

The risk of therapeutic drug monitoring failure with EC-MPS is >30% during the first 6 months of renal transplantation. Delayed pharmacokinetics was the main reason. In contrast, the risk of therapeutic drug monitoring failure was substantially lower with MMF.

Pharmacokinetics of mycophenolate sodium co-administered with tacrolimus in the first year after renal transplantation

We assessed the relations between MPA, free MPA (fMPA) and MPA glucuronide (MPAG) pharmacokinetics and the clinical condition of renal transplant recipients treated with EC-MPS and tacrolimus (Tac) in the first post-transplant year. In 18 adult patients blood samples were collected up to 12 h after EC-MPS oral administration. EC-MPS metabolites' plasma concentrations were determined using validated HPLC methods. All patients reached MPA area under the time-concentration curve (AUC0-12) above 30 µg h/mL. Most of the MPA, fMPA and all MPAG concentrations correlated significantly with respective AUC0-12 values. Some fMPA and all MPAG pharmacokinetic parameters correlated negatively with creatinine clearance and positively with creatinine concentration, whereas no such correlation was observed for MPA. Lower hemoglobin concentrations were observed in patients with higher MPA or fMPA C 0. The significant correlations between MPA C 3 as well as MPA C 4 and MPA AUC0-4 and MPA AUC0-12 may be of importance in further studies including larger number of patients in regard to establishing LSS. In patients treated with EC-MPS and Tac, monitoring MPA C 0 may be important, as too high MPA C 0 may contribute to anemia onset. In EC-MPS treated patients, MPAG concentration is related to renal function as MPAG pharmacokinetics were higher in patients with renal impairment.

How accurate and precise are limited sampling strategies in estimating exposure to mycophenolic acid in people with autoimmune disease?

Mycophenolic acid (MPA) is a potent immunosuppressant agent, which is increasingly being used in the treatment of patients with various autoimmune diseases. Dosing to achieve a specific target MPA area under the concentration-time curve from 0 to 12 h post-dose (AUC12) is likely to lead to better treatment outcomes in patients with autoimmune disease than a standard fixed-dose strategy. This review summarizes the available published data around concentration monitoring strategies for MPA in patients with autoimmune disease and examines the accuracy and precision of methods reported to date using limited concentration-time points to estimate MPA AUC12. A total of 13 studies were identified that assessed the correlation between single time points and MPA AUC12 and/or examined the predictive performance of limited sampling strategies in estimating MPA AUC12. The majority of studies investigated mycophenolate mofetil (MMF) rather than the enteric-coated mycophenolate sodium (EC-MPS) formulation of MPA. Correlations between MPA trough concentrations and MPA AUC12 estimated by full concentration-time profiling ranged from 0.13 to 0.94 across ten studies, with the highest associations (r (2) = 0.90-0.94) observed in lupus nephritis patients. Correlations were generally higher in autoimmune disease patients compared with renal allograft recipients and higher after MMF compared with EC-MPS intake. Four studies investigated use of a limited sampling strategy to predict MPA AUC12 determined by full concentration-time profiling. Three studies used a limited sampling strategy consisting of a maximum combination of three sampling time points with the latest sample drawn 3-6 h after MMF intake, whereas the remaining study tested all combinations of sampling times. MPA AUC12 was best predicted when three samples were taken at pre-dose and at 1 and 3 h post-dose with a mean bias and imprecision of 0.8 and 22.6 % for multiple linear regression analysis and of -5.5 and 23.0 % for maximum a posteriori (MAP) Bayesian analysis. Although mean bias was less when data were analysed using multiple linear regression, MAP Bayesian analysis is preferable because of its flexibility with respect to sample timing. Estimation of MPA AUC12 following EC-MPS administration using a limited sampling strategy with samples drawn within 3 h post-dose resulted in biased and imprecise results, likely due to a longer time to reach a peak MPA concentration (t max) with this formulation and more variable pharmacokinetic profiles. Inclusion of later sampling time points that capture enterohepatic recirculation and t max improved the predictive performance of strategies to predict EC-MPS exposure. Given the considerable pharmacokinetic variability associated with mycophenolate therapy, limited sampling strategies may potentially help in individualizing patient dosing. However, a compromise needs to be made between the predictive performance of the strategy and its clinical feasibility. An opportunity exists to combine research efforts globally to create an open-source database for MPA (AUC, concentrations and outcomes) that can be used and prospectively evaluated for AUC target-controlled dosing of MPA in autoimmune diseases.

Development and validation of limited sampling strategies for the estimation of mycophenolic acid area under the curve in adult kidney and liver transplant recipients receiving concomitant enteric-coated mycophenolate sodium and tacrolimus

BACKGROUND

Mycophenolic acid (MPA) is widely used in solid organ transplantation. MPA absorption from enteric-coated mycophenolate sodium (EC-MPS) is delayed, which results in a delayed enterohepatic recirculation and subsequently higher and more variable MPA 12-hour trough concentration and tmax values. Therefore, MPA trough level monitoring cannot be used to monitor MPA exposure in patients who are given EC-MPS. The aim of the study was to develop and validate a limited sampling strategy (LSS) for accurate prediction of the 12-hour area under the concentration-time curve (AUC0-12h) for MPA in patients who receive concomitant EC-MPS and Tacrolimus (Prograf or Advagraf) within 196 months posttransplantation. According to our knowledge, the LSS for MPA AUC estimation using high-performance liquid chromatography to determine MPA concentrations in plasma samples of kidney and liver transplant patients receiving EC-MPS and Tacrolimus (Advagraf) has not been previously evaluated.

METHODS

Seventy-four renal and liver transplant patients receiving EC-MPS and concomitant tacrolimus (either Prograf or Advagraf) provided a total of 74 pharmacokinetic profiles. MPA concentrations were measured using a validated high-performance liquid chromatography method for 9 plasma samples collected at predose and at 0.5, 1, 2, 3, 4, 6, 9, and 12 hours after the morning dose of EC-MPS after an overnight fast. LSS were developed and validated by stepwise multiple regression analysis with the use of a 2-group method (test, n = 37; and validation, n = 37).

RESULTS

The 3 and 4 time point equations using C1h, C3h, C9h and C1h, C2h, C3h, C6h, respectively, were found to be superior to all other models tested. When these LSS models were tested in the validation group, the results were acceptable [for 3 time points equation: r = 0.824, percentage of prediction error: 6.32 ± 25.75, 95% confidence interval (CI): -40.71 to 79.76; percentage of absolute prediction error: 27.45 ± 29.89, 95% CI: 0.04-199.92, predictive performance, 71% of estimated AUCs comprised within 85%-115% of the measured full MPA AUC, natural logarithmic residuals (ln) mean ± SD: -0.03 ± 0.24; for 4 time points equation: r = 0.898, percentage of prediction error: 3.32 ± 18.26, 95% CI: -49.35 to 51.06; percentage of absolute prediction error: 14.05 ± 11.89, 95% CI 0.13-49.86, percentage of predictive performance, 83% of estimated AUCs comprised within 85%-115% of the measured full MPA AUC, natural logarithmic residuals (ln) mean ± SD: -0.01 ± 0.19].

CONCLUSIONS

LSS equations using concentrations at 1, 3, and 9 hours or 1, 2, 3, and 6 hours time points provided the most reliable and accurate estimations of the MPA AUC in stable renal and liver transplant recipients treated with EC-MPS and tacrolimus. Further studies on independent groups of patients are required to confirm clinical utility of the presented LSS models.

Pharmacology and toxicology of mycophenolate in organ transplant recipients: an update

This review aims to provide an update of the literature on the pharmacology and toxicology of mycophenolate in solid organ transplant recipients. Mycophenolate is now the antimetabolite of choice in immunosuppressant regimens in transplant recipients. The active drug moiety mycophenolic acid (MPA) is available as an ester pro-drug and an enteric-coated sodium salt. MPA is a competitive, selective and reversible inhibitor of inosine-5'-monophosphate dehydrogenase (IMPDH), an important rate-limiting enzyme in purine synthesis. MPA suppresses T and B lymphocyte proliferation; it also decreases expression of glycoproteins and adhesion molecules responsible for recruiting monocytes and lymphocytes to sites of inflammation and graft rejection; and may destroy activated lymphocytes by induction of a necrotic signal. Improved long-term allograft survival has been demonstrated for MPA and may be due to inhibition of monocyte chemoattractant protein 1 or fibroblast proliferation. Recent research also suggested a differential effect of mycophenolate on the regulatory T cell/helper T cell balance which could potentially encourage immune tolerance. Lower exposure to calcineurin inhibitors (renal sparing) appears to be possible with concomitant use of MPA in renal transplant recipients without undue risk of rejection. MPA displays large between- and within-subject pharmacokinetic variability. At least three studies have now reported that MPA exhibits nonlinear pharmacokinetics, with bioavailability decreasing significantly with increasing doses, perhaps due to saturable absorption processes or saturable enterohepatic recirculation. The role of therapeutic drug monitoring (TDM) is still controversial and the ability of routine MPA TDM to improve long-term graft survival and patient outcomes is largely unknown. MPA monitoring may be more important in high-immunological recipients, those on calcineurin-inhibitor-sparing regimens and in whom unexpected rejection or infections have occurred. The majority of pharmacodynamic data on MPA has been obtained in patients receiving MMF therapy in the first year after kidney transplantation. Low MPA area under the concentration time from 0 to 12 h post-dose (AUC0-12) is associated with increased incidence of biopsy-proven acute rejection although AUC0-12 optimal cut-off values vary across study populations. IMPDH monitoring to identify individuals at increased risk of rejection shows some promise but is still in the experimental stage. A relationship between MPA exposure and adverse events was identified in some but not all studies. Genetic variants within genes involved in MPA metabolism (UGT1A9, UGT1A8, UGT2B7), cellular transportation (SLCOB1, SLCO1B3, ABCC2) and targets (IMPDH) have been reported to effect MPA pharmacokinetics and/or response in some studies; however, larger studies across different ethnic groups that take into account genetic linkage and drug interactions that can alter a patient's phenotype are needed before any clinical recommendations based on patient genotype can be formulated. There is little data on the pharmacology and toxicology of MPA in older and paediatric transplant recipients.

Maximum a posteriori Bayesian estimation of mycophenolic Acid area under the concentration-time curve: is this clinically useful for dosage prediction yet?

This review seeks to summarize the available data about Bayesian estimation of area under the plasma concentration-time curve (AUC) and dosage prediction for mycophenolic acid (MPA) and evaluate whether sufficient evidence is available for routine use of Bayesian dosage prediction in clinical practice. A literature search identified 14 studies that assessed the predictive performance of maximum a posteriori Bayesian estimation of MPA AUC and one report that retrospectively evaluated how closely dosage recommendations based on Bayesian forecasting achieved targeted MPA exposure. Studies to date have mostly been undertaken in renal transplant recipients, with limited investigation in patients treated with MPA for autoimmune disease or haematopoietic stem cell transplantation. All of these studies have involved use of the mycophenolate mofetil (MMF) formulation of MPA, rather than the enteric-coated mycophenolate sodium (EC-MPS) formulation. Bias associated with estimation of MPA AUC using Bayesian forecasting was generally less than 10%. However some difficulties with imprecision was evident, with values ranging from 4% to 34% (based on estimation involving two or more concentration measurements). Evaluation of whether MPA dosing decisions based on Bayesian forecasting (by the free website service https://pharmaco.chu-limoges.fr) achieved target drug exposure has only been undertaken once. When MMF dosage recommendations were applied by clinicians, a higher proportion (72-80%) of subsequent estimated MPA AUC values were within the 30-60 mg · h/L target range, compared with when dosage recommendations were not followed (only 39-57% within target range). Such findings provide evidence that Bayesian dosage prediction is clinically useful for achieving target MPA AUC. This study, however, was retrospective and focussed only on adult renal transplant recipients. Furthermore, in this study, Bayesian-generated AUC estimations and dosage predictions were not compared with a later full measured AUC but rather with a further AUC estimate based on a second Bayesian analysis. This study also provided some evidence that a useful monitoring schedule for MPA AUC following adult renal transplant would be every 2 weeks during the first month post-transplant, every 1-3 months between months 1 and 12, and each year thereafter. It will be interesting to see further validations in different patient groups using the free website service. In summary, the predictive performance of Bayesian estimation of MPA, comparing estimated with measured AUC values, has been reported in several studies. However, the next step of predicting dosages based on these Bayesian-estimated AUCs, and prospectively determining how closely these predicted dosages give drug exposure matching targeted AUCs, remains largely unaddressed. Further prospective studies are required, particularly in non-renal transplant patients and with the EC-MPS formulation. Other important questions remain to be answered, such as: do Bayesian forecasting methods devised to date use the best population pharmacokinetic models or most accurate algorithms; are the methods simple to use for routine clinical practice; do the algorithms actually improve dosage estimations beyond empirical recommendations in all groups that receive MPA therapy; and, importantly, do the dosage predictions, when followed, improve patient health outcomes?