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 (AUC
0–12
) is associated with increased incidence of biopsy-proven acute rejection although AUC
0–12
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.
Tacrolimus is a pivotal immunosuppressant agent used in solid-organ transplantation. It was originally formulated for oral administration as Prograf(®), a twice-daily immediate-release capsule. In an ...attempt to improve patient adherence, retain manufacturer market share and/or reduce health care costs, newer once-daily prolonged-release formulations of tacrolimus (Advagraf(®) and Envarsus(®) XR) and various generic versions of Prograf(®) are becoming available. Tacrolimus has a narrow therapeutic index. Small variations in drug exposure due to formulation differences can have a significant impact on patient outcomes. The aim of this review is to critically analyse the published data on the clinical pharmacokinetics of once-daily tacrolimus in solid-organ transplant patients. Forty-three traditional (non-compartmental) and five population pharmacokinetic studies were identified and evaluated. On the basis of the stricter criteria for narrow-therapeutic-index drugs, Prograf(®), Advagraf(®) and Envarsus(®) XR are not bioequivalent in terms of the area under the concentration-time curve from 0 to 24 h (AUC0-24) or the minimum concentration (C min). Patients may require a daily dosage increase if converted from Prograf(®) to Advagraf(®), while a daily dosage reduction appears necessary for conversion from Prograf(®) to Envarsus(®) XR. Prograf(®) itself, or generic immediate-release tacrolimus, can be administered in a once-daily regimen with a lower than double daily dose being reported to give 24-h exposure equivalent to that of a twice-daily regimen. Intense clinical and concentration monitoring is prudent in the first few months after any conversion to once-daily tacrolimus dosing; however, there is no guarantee that therapeutic drug monitoring strategies applicable to one formulation (or twice-daily dosing) will be equally applicable to another. The correlation between the tacrolimus AUC0-24 and C min is variable and not strong for all three formulations, indicating that trough measurements may not always give a good indication of overall drug exposure. Further investigation is required into whether the prolonged-release formulations have reduced within-subject pharmacokinetic variability, which would be a distinct advantage. Whether the effects of factors that influence tacrolimus absorption and pre-systemic metabolism (patient genotype status; gastrointestinal disease and disorders) and drug interactions differ across the formulations needs to be further elucidated. Most pharmacokinetic comparison studies to date have involved relatively stable patients, and many have been sponsored by the pharmaceutical companies manufacturing the new formulations. Larger randomized, controlled trials are needed in different transplant populations to determine whether there are differences in efficacy and toxicity across the formulations and whether formulation conversion is worthwhile in the longer term. While it has been suggested that once-daily administration of tacrolimus may improve patient compliance, further studies are required to demonstrate this. Mistakenly interchanging different tacrolimus formulations can lead to serious patient harm. Once-daily tacrolimus is now available as an alternative to twice-daily tacrolimus and can be used de novo in solid-organ transplant recipients or as a different formulation for existing patients, with appropriate dosage modifications. Clinicians need to be fully aware of pharmacokinetic and possible outcome differences across the different formulations of tacrolimus.
This review aims to provide an extensive overview of the literature on the clinical pharmacokinetics of mycophenolate in solid organ transplantation and a briefer summary of current pharmacodynamic ...information. Strategies are suggested for further optimisation of mycophenolate therapy and areas where additional research is warranted are highlighted. Mycophenolate has gained widespread acceptance as the antimetabolite immunosuppressant of choice in organ transplant regimens. Mycophenolic acid (MPA) is the active drug moiety. Currently, two mycophenolate compounds are available, mycophenolate mofetil and enteric-coated (EC) mycophenolate sodium. MPA is a potent, selective and reversible inhibitor of inosine monophosphate dehydrogenase (IMPDH), leading to eventual arrest of T- and B-lymphocyte proliferation. Mycophenolate mofetil and EC-mycophenolate sodium are essentially completely hydrolysed to MPA by esterases in the gut wall, blood, liver and tissue. Oral bioavailability of MPA, subsequent to mycophenolate mofetil administration, ranges from 80.7% to 94%. EC-mycophenolate sodium has an absolute bioavailability of MPA of approximately 72%. MPA binds 97-99% to serum albumin in patients with normal renal and liver function. It is metabolised in the liver, gastrointestinal tract and kidney by uridine diphosphate gluconosyltransferases (UGTs). 7-O-MPA-glucuronide (MPAG) is the major metabolite of MPA. MPAG is usually present in the plasma at 20- to 100-fold higher concentrations than MPA, but it is not pharmacologically active. At least three minor metabolites are also formed, of which an acyl-glucuronide has pharmacological potency comparable to MPA. MPAG is excreted into the urine via active tubular secretion and into the bile by multi-drug resistance protein 2 (MRP-2). MPAG is de-conjugated back to MPA by gut bacteria and then reabsorbed in the colon. Mycophenolate mofetil and EC-mycophenolate sodium display linear pharmacokinetics. Following mycophenolate mofetil administration, MPA maximum concentration usually occurs in 1-2 hours. EC-mycophenolate sodium exhibits a median lag time in absorption of MPA from 0.25 to 1.25 hours. A secondary peak in the concentration-time profile of MPA, due to enterohepatic recirculation, often appears 6-12 hours after dosing. This contributes approximately 40% to the area under the plasma concentration-time curve (AUC). The mean elimination half-life of MPA ranges from 9 to 17 hours. MPA displays large between- and within-subject pharmacokinetic variability. Dose-normalised MPA AUC can vary more than 10-fold. Total MPA concentrations should be interpreted with caution in patients with severe renal impairment, liver disease and hypoalbuminaemia. In such individuals, MPA and MPAG plasma protein binding may be altered, changing the fraction of free MPA available. Apparent oral clearance (CL/F) of total MPA appears to increase in proportion to the increased free fraction, with a reduction in total MPA AUC. However, there may be little change in the MPA free concentration. Ciclosporin inhibits biliary excretion of MPAG by MRP-2, reducing enterohepatic recirculation of MPA. Exposure to MPA when mycophenolate mofetil is given in combination with ciclosporin is approximately 30-40% lower than when given alone or with tacrolimus or sirolimus. High dosages of corticosteroids may induce expression of UGT, reducing exposure to MPA. Other co-medications can interfere with the absorption, enterohepatic recycling and metabolism of mycophenolate. Most pharmacokinetic investigations of MPA have involved mycophenolate mofetil rather than EC-mycophenolate sodium therapy. In population pharmacokinetic studies, MPA CL/F in adults ranges from 14.1 to 34.9 L/h (ciclosporin co-therapy) and from 11.9 to 25.4 L/h (tacrolimus co-therapy). Patient bodyweight, serum albumin concentration and immunosuppressant co-therapy have a significant influence on CL/F. The majority of pharmacodynamic data on MPA have been obtained in patients receiving mycophenolate mofetil therapy in the first year after kidney transplantation. Low MPA AUC is associated with increased incidence of biopsy-proven acute rejection. Gastrointestinal adverse events may be dose related. Leukopenia and anaemia have been associated with high MPA AUC, trough concentration and metabolite concentrations in some, but not all, studies. High free MPA exposure has been identified as a risk factor for leukopenia in some investigations. Targeting a total MPA AUC from 0 to 12 hours (AUC12) of 30-60 mg.hr/L is likely to minimise the risk of acute rejection and may reduce toxicity. IMPDH monitoring is in the early experimental stage. Individualisation of mycophenolate therapy should lead to improved patient outcomes. MPA AUC12 appears to be the most useful exposure measure for such individualisation. Limited sampling strategies and Bayesian forecasting are practical means of estimating MPA AUC12 without full concentration-time profiling. Target concentration intervention may be particularly useful in the first few months post-transplant and prior to major changes in anti-rejection therapy. In patients with impaired renal or hepatic function or hypoalbuminaemia, free drug measurement could be valuable in further interpretation of MPA exposure.
The calcineurin inhibitors ciclosporin (cyclosporine) and tacrolimus are immunosuppressant drugs used for the prevention of organ rejection following transplantation. Both agents are metabolic ...substrates for cytochrome P450 (CYP) 3A enzymes--in particular, CYP3A4 and CYP3A5--and are transported out of cells via P-glycoprotein (ABCB1). Several single nucleotide polymorphisms (SNPs) have been identified in the genes encoding for CYP3A4, CYP3A5 and P-glycoprotein, including CYP3A4 -392A>G (rs2740574), CYP3A5 6986A>G (rs776746), ABCB1 3435C>T (rs1045642), ABCB1 1236C>T (rs1128503) and ABCB1 2677G>T/A (rs2032582). The aim of this review is to provide the clinician with an extensive overview of the recent literature on the known effects of these SNPs on the pharmacokinetics of ciclosporin and tacrolimus in solid-organ transplant recipients. Literature searches were performed, and all relevant primary research articles were critiqued and summarized. Influence of the CYP3A4 -392A>G SNP on the pharmacokinetics of either ciclosporin or tacrolimus appears limited. Variability in CYP3A4 expression due to environmental factors is likely to be more important than patient genotype. Influence of the CYP3A5 6986A>G SNP on the pharmacokinetics of ciclosporin is also uncertain and likely to be small. CYP3A4 may play a more dominant role than CYP3A5 in the metabolism of ciclosporin. The CYP3A5 6986A>G SNP has a well established influence on the pharmacokinetics of tacrolimus. Several studies in kidney, heart and liver transplant recipients have reported an approximate halving of tacrolimus dose-adjusted trough concentrations and doubling of tacrolimus dose requirements in heterozygous or homozygous carriers of a CYP3A5*1 wild-type allele compared with homozygous carriers of a CYP3A5*3 variant allele. Carriers of a CYP3A5*1 allele take a longer time to reach target blood tacrolimus concentrations. Influence of ABCB1 3435C>T, 1236C>T and 2677G>T/A SNPs on the pharmacokinetics of ciclosporin and tacrolimus remains uncertain, with inconsistent results. Genetic linkage between the three variant genotypes suggests that the pharmacokinetic effects are complex and not related to any one ABCB1 SNP. It is likely that these polymorphisms exert a small but combined effect, which is additive to the effects of the CYP3A5 6986A>G SNP. In liver transplant patients, recipient and donor liver genotypes may act together in determining overall drug disposition, hence the importance of assessing both. Studies with low patient numbers may account for many inconsistent results to date. Meta-analyses of the current data should help resolve some discrepancies. The majority of studies have only evaluated the effects of individual SNPs; however, multiple polymorphisms may interact to produce a combined effect. Further haplotype analyses are likely to be useful. It is not yet clear whether pharmacogenetic profiling of calcineurin inhibitors will be a useful clinical tool for personalizing immunosuppressant therapy.
The aim of this review is to analyse critically the recent literature on the clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplant recipients. Dosage and target ...concentration recommendations for tacrolimus vary from centre to centre, and large pharmacokinetic variability makes it difficult to predict what concentration will be achieved with a particular dose or dosage change. Therapeutic ranges have not been based on statistical approaches. The majority of pharmacokinetic studies have involved intense blood sampling in small homogeneous groups in the immediate post-transplant period. Most have used nonspecific immunoassays and provide little information on pharmacokinetic variability. Demographic investigations seeking correlations between pharmacokinetic parameters and patient factors have generally looked at one covariate at a time and have involved small patient numbers. Factors reported to influence the pharmacokinetics of tacrolimus include the patient group studied, hepatic dysfunction, hepatitis C status, time after transplantation, patient age, donor liver characteristics, recipient race, haematocrit and albumin concentrations, diurnal rhythm, food administration, corticosteroid dosage, diarrhoea and cytochrome P450 (CYP) isoenzyme and P-glycoprotein expression. Population analyses are adding to our understanding of the pharmacokinetics of tacrolimus, but such investigations are still in their infancy. A significant proportion of model variability remains unexplained. Population modelling and Bayesian forecasting may be improved if CYP isoenzymes and/or P-glycoprotein expression could be considered as covariates. Reports have been conflicting as to whether low tacrolimus trough concentrations are related to rejection. Several studies have demonstrated a correlation between high trough concentrations and toxicity, particularly nephrotoxicity. The best predictor of pharmacological effect may be drug concentrations in the transplanted organ itself. Researchers have started to question current reliance on trough measurement during therapeutic drug monitoring, with instances of toxicity and rejection occurring when trough concentrations are within 'acceptable' ranges. The correlation between blood concentration and drug exposure can be improved by use of non-trough timepoints. However, controversy exists as to whether this will provide any great benefit, given the added complexity in monitoring. Investigators are now attempting to quantify the pharmacological effects of tacrolimus on immune cells through assays that measure in vivo calcineurin inhibition and markers of immunosuppression such as cytokine concentration. To date, no studies have correlated pharmacodynamic marker assay results with immunosuppressive efficacy, as determined by allograft outcome, or investigated the relationship between calcineurin inhibition and drug adverse effects. Little is known about the magnitude of the pharmacodynamic variability of tacrolimus.
The calcineurin inhibitors ciclosporin (cyclosporine) and tacrolimus are immunosuppressant drugs used for the prevention of organ rejection following transplantation. Both agents are metabolic ...substrates for cytochrome P450 (CYP) 3A enzymes - in particular, CYP3A4 and CYP3A5 - and are transported out of cells via P-glycoprotein (ABCB1). Several single nucleotide polymorphisms (SNPs) have been identified in the genes encoding for CYP3A4, CYP3A5 and P-glycoprotein, including CYP3A4 -392A>G (rs2740574), CYP3A5 6986A>G (rs776746), ABCB1 3435C>T (rs1045642), ABCB1 1236C>T (rs1128503) and ABCB1 2677G>T/A (rs2032582). The aim of this review is to provide the clinician with an extensive overview of the recent literature on the known effects of these SNPs on the pharmacodynamics of ciclosporin and tacrolimus in solid-organ transplant recipients. Literature searches were performed and all relevant primary research articles were critiqued and summarized. There is no evidence that the CYP3A4 -392A>G SNP has an effect on the pharmacodynamics of either ciclosporin or tacrolimus; however, studies have been limited. For patients prescribed ciclosporin, the CYP3A5 6986A>G SNP may influence long-term survival, possibly because of a different metabolite pattern over time. This SNP has no clear association with acute rejection during ciclosporin therapy. Despite a strong association between the CYP3A5 6986A>G SNP and tacrolimus pharmacokinetics, there is no consistent evidence of organ rejection as a result of genotype-related under-immunosuppression. This is likely to be explained by the practice of performing tacrolimus dose adjustments in the early phase after transplantation. The effect of the CYP3A5 6986A>G SNP on ciclosporin- and tacrolimus-related nephrotoxicity and development of hypertension is unclear. Similarly, the ABCB1 SNPs exert no clear influence on either ciclosporin or tacrolimus pharmacodynamics, with studies showing conflicting results in regard to the main parameters of acute rejection and nephrotoxicity. In kidney transplant patients, consideration of the donor kidney genotype rather than the recipient genotype may be more important when assessing development of nephrotoxicity. Studies with low patient numbers may account for many inconsistent results to date. The majority of studies have only evaluated the effects of individual SNPs; however, multiple polymorphisms may interact to produce a combined effect. Further haplotype analyses are likely to be useful, particularly ones that consider both donor and recipient genotype. The effects of polymorphisms associated with the pregnane X receptor, organic anion transporting polypeptides, calcineurin inhibitor target sites and immune response pathways need to be further investigated. A large standardized clinical trial is now required to evaluate the relationship between the pharmacokinetics and pharmacodynamics of CYP3A5-mediated tacrolimus metabolism, particularly in regard to the outcomes of acute rejection and nephrotoxicity. It is not yet clear whether pharmacogenetic profiling of calcineurin inhibitors will be a useful clinical tool for personalizing immunosuppressant therapy.
This review summarises the available data on the population pharmacokinetics of tacrolimus and use of Maximum A Posteriori (MAP) Bayesian estimation to predict tacrolimus exposure and subsequent drug ...dosage requirements in solid organ transplant recipients. A literature search was conducted which identified 56 studies that assessed the population pharmacokinetics of tacrolimus based on non-linear mixed effects modelling and 14 studies that assessed the predictive performance of MAP Bayesian estimation of tacrolimus area under the plasma concentration-time curve (AUC) from time zero to the end of the dosing interval. Studies were most commonly undertaken in adult kidney transplant recipients and investigated the immediate-release formulation. The pharmacokinetics of tacrolimus were described using one- and two-compartment disposition models with first-order elimination in 61 and 39 % of population pharmacokinetic studies, respectively. Variability in tacrolimus whole blood apparent clearance amongst transplant recipients was most commonly related to cytochrome P450 (CYP) 3A5 genotype (rs776746), patient haematocrit, patient weight, post-operative day and hepatic function (aspartate aminotransferase). Bias, as calculated using estimation of the mean predictive error (MPE) or mean percentage predictive error (MPPE) associated with prediction of the tacrolimus AUC, ranged from -15 to 9.95 %. Imprecision, as calculated through estimation of the root mean squared error (RMSE) or mean absolute prediction error (MAPE), was generally much poorer overall, ranging from 0.81 to 40. r
values ranged from 0.27 to 0.99 %. Of the Bayesian forecasting strategies that used two or more tacrolimus concentrations, 71 % showed bias of 10 % or less; however, only 39 % showed imprecision of 10 % or less. The combination of sampling times at 0, 1 and 3 h post-dose consistently showed bias and imprecision values of less than 15 %. No studies to date have examined how closely MAP Bayesian dosage predictions of tacrolimus actually achieve target AUC by comparing dosage prediction from one occasion with a future measured AUC. Further research involving larger prospective studies including more diverse transplant groups and the extended-release formulation of tacrolimus is needed. Several questions require further examination, including the following. Do Bayesian forecasting methods currently use the most appropriate population pharmacokinetic models and optimal sampling times for dosage prediction? Does Bayesian forecasting perform well when applied to make dosage predictions on a subsequent occasion? How can Bayesian forecasting be simplified for use in the clinical setting? And, are patient outcomes improved with dosage prediction based on Bayesian forecasting compared with trough concentration monitoring?
Population model analyses have shifted from using the first order (FO) to the first-order with conditional estimation (FOCE) approximation to the true model. However, the weighted residuals (WRES), a ...common diagnostic tool used to test for model misspecification, are calculated using the FO approximation. Utilizing WRES with the FOCE method may lead to misguided model development/evaluation. We present a new diagnostic tool, the conditional weighted residuals (CWRES), which are calculated based on the FOCE approximation.
CWRES are calculated as the FOCE approximated difference between an individual's data and the model prediction of that data divided by the root of the covariance of the data given the model.
Using real and simulated data the CWRES distributions behave as theoretically expected under the correct model. In contrast, in certain circumstances, the WRES have distributions that greatly deviate from the expected, falsely indicating model misspecification. CWRES/WRES comparisons can also indicate if the FOCE estimation method will improve the results of an FO model fit to data.
Utilization of CWRES could improve model development and evaluation and give a more accurate picture of if and when a model is misspecified when using the FO or FOCE methods.
PDF
