Christine E. Staatz

Clinical Pharmacokinetics and Pharmacodynamics of Tacrolimus in Solid Organ Transplantation

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.

Clinical Pharmacokinetics and Pharmacodynamics of Mycophenolate in Solid Organ Transplant Recipients

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.

Effect of CYP3A and ABCB1 Single Nucleotide Polymorphisms on the Pharmacokinetics and Pharmacodynamics of Calcineurin Inhibitors: Part II

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 (rs1 128503) 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.

Conditional Weighted Residuals (CWRES): A Model Diagnostic for the FOCE Method

PurposePopulation 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.Materials and MethodsCWRES 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.ResultsUsing 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.ConclusionsUtilization 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.

Population pharmacokinetics of tacrolimus in adult kidney transplant recipients

The aims of this study were to investigate the population pharmacokinetics of tacrolimus in adult kidney transplant recipients and to identify factors that explain variability.

Predictors of new onset diabetes after renal transplantation

Abstract:  The development of new onset diabetes after transplantation (NODAT) is associated with increased cardiovascular morbidity and mortality. This study aimed at identifying risk factors for the development of NODAT. We performed a retrospective review of 787 renal transplants performed between 1994 and 2004 at a single centre. NODAT was diagnosed in patients who had two random plasma glucose concentrations >11.1 mmol/L after the first month post‐transplant or patients who required treatment for hyperglycaemia within the first month and continued treatment thereafter. The incidence of NODAT was 7.7%. The incidence of NODAT requiring either insulin or oral hypoglycaemic agents was 4.5%. Risk factors for the development of NODAT were older age (HR 1.04, 95% CI: 1.01–1.07, p < 0.01), heavier weight at time of transplantation (HR 1.04, 95% CI: 1.02–1.07, p < 0.01), higher mean pre‐transplant random plasma glucose concentrations (HR 1.54, 95% CI: 1.14–2.08, p < 0.01), higher plasma glucose within the first seven d post‐transplant (HR 1.27, 95% CI: 1.09–1.47, p < 0.01) and use of tacrolimus (HR 3.70, 95% CI: 1.61–8.46, p < 0.01). Ten yr actuarial patient survival was 67.1% in patients with NODAT compared with 81.9% for those without diabetes and 65.3% in patients known to have diabetes pre‐transplant. There was no difference in graft survival. We have identified a high‐risk group in which attempts should be made to reduce the incidence of NODAT by tailoring immunosuppression, lifestyle modification and selecting non‐diabetogenic medications. Improvements in management of patients at higher risk of NODAT may help reduce the incidence of deaths with a functioning graft.

PharmGKB summary: cyclosporine and tacrolimus pathways

Tacrolimus (FK506) and cyclosporine (cyclosporin A, CsA) are cornerstone immunosuppressive agents administered to solid organ transplant recipients to prevent and treat allograft rejection. The discovery of cyclosporine in the 1970s, and its entry into the collection of immunosuppressants in the early 1980s, was a major breakthrough in medicine. Cyclosporine was the most successful antirejection drug to date, and it radically improved the chance of survival for transplant recipients. In 1994, the Food and Drug Administration (FDA) approved tacrolimus, an effective alternative to cyclosporine [1]. Since then, tacrolimus and cyclosporine have become the principal immunosuppressive drugs for solid organ transplantation. The United States Organ Procurement and Transplantation Network and the Scientific Registry of Transplant Recipients showed that in 2011, 86% of the 16 055 patients who received a kidney transplant were prescribed tacrolimus upon discharge, and 2.4% were prescribed cyclosporine. One year after transplant, 84 and 4% of patients received tacrolimus and cyclosporine therapy, respectively [2]. Global differences exist in the usage of tacrolimus and cyclosporine: 2008 figures from the Australia and New Zealand Dialysis and Transplant Registry show that 61% of the 391 Australian patients who received a deceased kidney donor graft were prescribed tacrolimus, and 35% were prescribed cyclosporine. At 1-year post-transplant, these numbers changed to 55 and 33% for tacrolimus and cyclosporine, respectively [3]. Both drugs are also prescribed for liver, intestinal, lung, and heart transplant recipients [2], and can be used to manage severe autoimmune conditions, such as atopic dermatitis [4,5] and rheumatoid arthritis [6,7]. Tacrolimus and cyclosporine differ in their chemical structure: cyclosporine is a cyclic endecapeptide [8], whereas tacrolimus is a macrocyclic lactone [9]. However, they act in a similar manner. Both are calcineurin inhibitors; their main mechanism of action involves inhibition of this important phosphatase [1]. Tacrolimus exhibits similar effects to cyclosporine, but at concentrations 100 times lower [10]. Despite these differences in potency, tacrolimus and cyclosporine both show excellent survival rates for grafts across many comparative studies (summarized in Maes and Vanrenterghem [11]). However, several studies have shown that use of tacrolimus is associated with a lower allograft rejection rate compared with cyclosporine [12-14]. The principal adverse effects associated with tacrolimus and cyclosporine treatment are neurotoxicity, nephrotoxicity, hypertension, hyperglycemia, gastrointestinal disturbances, infections, and malignancy [15]. Although the two drugs have similar side-effect profiles, they may differ in the frequency of effects. For example, tacrolimus is more likely to cause alopecia [16], tremors [17], and new-onset diabetes mellitus [12], whereas cyclosporine is associated with hyperlipidemia [18], hypertrichosis, and gingival hyperplasia [19]. The idea that tacrolimus is less nephrotoxic than cyclosporine remains controversial [20], particularly as most studies of renal injury are based on evaluations in renal transplant patients, making it difficult to discriminate between drug-induced organ damage and other causes of organ dysfunction [21]. A recent study in pancreatic transplant recipients examined baseline kidney biopsies and 5-year post-transplant biopsies, and reported that the chronic nephrotoxic effects of tacrolimus and cyclosporine were similar [20]. Despite the success of both drugs, treatment is complicated by narrow therapeutic indices and large intrapatient and interpatient pharmacokinetic variability [22,23]. Although adequate exposure is essential to prevent rejection, overexposure can lead to toxicities that reduce tolerability and affect long-term allograft and patient survival [24]. Therapeutic drug monitoring (TDM), therefore, is mandatory for both drugs. However, because individual transplant recipients respond differently to similar immunosuppressant concentrations, achieving the recommended therapeutic target range does not guarantee absence of drug toxicity or complete immunosuppressant efficacy. A mechanistic understanding of the underlying factors affecting the pharmacokinetics and pharmacodynamics of calcinuerin inhibitors may prove useful in being able to further personalize these therapies. This review aims to provide a broad overview of recently published literature on the pharmacokinetics, pharmacodynamics, and pharmacogenetics of tacrolimus and cyclosporine in transplant patients, with the goals of clarifying current understanding and identifying areas of future research. In doing so, this review builds on the work of others in this field [1,8,24-27]. A particular emphasis is given to pharmacogenetics, as developments in this area may provide a way to optimize treatment with these drugs, potentially avoiding negative side effects while still maintaining efficacy.

Development and evaluation of vancomycin dosage guidelines designed to achieve new target concentrations

OBJECTIVES The aims of this study were to develop a population pharmacokinetic model of vancomycin in adult patients, to use this model to develop dosage guidelines targeting vancomycin trough concentrations of 10-15 mg/L and to evaluate the performance of these new guidelines. METHODS All data analyses were performed using NONMEM. A population pharmacokinetic model was first developed from vancomycin dosage and concentration data collected during routine therapeutic drug monitoring in 398 patients, then new vancomycin dosage guidelines were devised by using the model to predict vancomycin trough concentrations in a simulated dataset. Individual estimates of CL and V1 were then obtained in an independent group of 100 patients using the population model and the POSTHOC option. These individual estimates were used to predict vancomycin trough concentrations and steady-state AUC(24)/MIC ratios using the current and new dosage guidelines. RESULTS The population analysis found that the vancomycin data were best described using a bi-exponential elimination model with a typical CL of 3.0 L/h that changed by 15.4% for every 10 mL/min difference from a CL(CR) of 66 mL/min. V(ss) was 1.4 L/kg. The proposed dosage guidelines were predicted to achieve 55% of vancomycin troughs within 10-15 mg/L and 71% within 10-20 mg/L, which is significantly higher than current guidelines (19% and 22%, respectively). The proportion of AUC(24)/MIC ratios above 400 was also higher, 87% compared with 58%. CONCLUSIONS New vancomycin dosage guidelines have been developed that achieve trough concentrations of 10-15 mg/L earlier and more consistently than current guidelines.

Once- versus twice-daily tacrolimus: Are the formulations truly equivalent?

Tacrolimus is a cornerstone immunosuppressant agent in the prevention of organ rejection following transplantation. While typically administered twice daily (Prograf®), a modified-release once-daily formulation (Advagraf®) has recently been developed and licensed for use. To date, the majority of published data relating to the use of Advagraf® have arisen from industry-sponsored clinical trials. These have shown that conversion from Prograf® to Advagraf® on a 1 mg: 1 mg basis in both stable and de novo kidney and liver transplant recipients yields lower peak concentrations (Cmax) but equivalent overall drug exposure (area under the concentration-time curve from 0 to 24 hours post-dose; AUC24) and trough concentrations (Cmin). This has led to the proposal that the same total daily dose, target Cmin and therapeutic drug monitoring (TDM) strategies can be applied irrespective of preparation. However, while Advagraf® fulfils criteria for bioequivalence according to the European Medicines Agency and US FDA, lower tacrolimus exposure has been observed in the majority of clinical studies, particularly in the early post-transplant period. This has resulted in a need for higher doses of Advagraf® compared with Prograf® to achieve similar Cmin values. Significant between-subject variability in the Cmin/AUC24 relationship with Advagraf® has also been demonstrated, suggesting possible problems with TDM based on Cmin values. In non-comparative conversion studies, Advagraf® demonstrated similar efficacy and safety to Prograf®. However, phase III studies in de novo kidney and liver transplant recipients have shown higher rates of acute rejection with Advagraf®, possibly explained by the differing Cmax values achieved with the two preparations. While it has been suggested that once-daily administration may improve compliance, no studies have proven this to be the case. This article reviews the pharmacokinetics, efficacy, adverse effects and utility of Advagraf® in relation to its equivalence to Prograf®, and areas that require additional research are identified.

Mycophenolate, clinical pharmacokinetics, formulations, and methods for assessing drug exposure

UNLABELLED This article summarizes part of a consensus meeting about mycophenolate (MPA) therapeutic drug monitoring held in Rome under the auspices of The Transplantation Society in November 2008 (Clin J Am Soc Nephrol. 2010;5:341-358). This part of the meeting focused on the clinical pharmacokinetics of MPA and included discussion on how to measure MPA (active drug) exposure and the differences between the currently available formulations. SUMMARY POINTS Because of variability in the dose-concentration relationship, MPA exposure should be measured and doses should be adjusted accordingly to achieve optimal clinical outcomes. Suggested therapeutic exposures derived for MPA from mycophenolate mofetil (MMF) may differ to those that could be useful for MPA from enteric-coated mycophenolate sodium (EC-MPS), particularly if limited sampling strategies or single concentration, especially trough concentrations, is used, as the concentration-time profiles of MPA from the 2 formulations are quite different. The 2 MPA formulations cannot be considered as bioequivalent. The area under the concentration-time curve (AUC 0-12) is considered the criterion standard for monitoring of MPA, which is a reflection of exposure to the drug over the entire dosing period. If a limited sampling protocol coupled with multilinear regression or Bayesian estimation is used to estimate this parameter, it should be used only for the population in which the model has been developed and should preferably include at least one time point after 4 hours (preferably around 8 or 9 hours after MMF dosing). If a single time point is to be used as a surrogate for an AUC 0-12, trough concentration of MPA may be the most practical but, from a pharmacokinetic standpoint, is not the most informative time point to choose. Because limited sampling strategies to estimate MPA exposure from EC-MPS have not yet been well developed and fully evaluated, nor have accurate Bayesian estimators been reported, AUC 0-12 measurement is still necessary to obtain reliable estimates of MPA exposure in patients treated with EC-MPS. The measurement of MPA trough concentrations should not be used at all for MPA exposure assessment following administration of EC-MPS. Because limited sampling strategies to estimate MPA exposure from EC-MPS have not yet been well developed and fully evaluated, nor have accurate Bayesian estimators been reported, AUC 0-12 measurement is still necessary to obtain reliable estimates of MPA exposure in patients treated with EC-MPS. The measurement of MPA trough concentrations should not be used at all for MPA exposure assessment following administration of EC-MPS. Lower (or higher) than expected total MPA exposure in patients with severe renal impairment may still indicate sufficient free MPA exposure. Mycophenolate free exposure measurement/estimation is likely to be beneficial in patients with severe renal impairment (creatinine clearance b25 mL/min) to guide dosage estimation, especially because renal function changes over time after transplant, while recognizing that robust prospective studies to show the clinical advantage of measuring free MPA exposure are still required. Lower total measured MPA exposure in patients with hypoalbuminemia may still indicate sufficient free MPA exposure. Mycophenolate free concentration measurement and estimation of exposure are likely to be beneficial in patients with a serum albumin less than or equal to 31 g/L to guide interpretation of MPA exposure. A 1.5-g twice-daily starting dose of MMF rather than a 1-g twice-daily starting dose of MMF is more likely to achieve the minimum target MPA exposure in adult transplant recipients receiving concomitant cyclosporine therapy. Because the cyclosporine dose is progressively tapered following transplantation, MPA exposure should be measured repeatedly and MMF should be doses adjusted accordingly to achieve optimal clinical outcome. Mycophenolate exposure should be measured in the first week after transplant, then each week for the first month, each month until month 3, and subsequently every 3 months up to 1 year with appropriate dosage adjustment, as AUC is likely to increase over time. After 1 year, if dosage requirement has stabilized, MPA exposure can be assessed each time the immunosuppressive regimen is changed or a potentially interacting drug is introduced or withdrawn. Assessment of UGT1A9 single nucleotide polymorphisms (-275TNA, -2152CNT, -440CNT, -331TNC) should be considered before transplantation to assist in dosing decisions to achieve optimal MPA exposure immediately after transplant. Consideration of the points summarized above should lead to more effective dosage adjustment based on sound applied pharmacokinetic and pharmacodynamic principles.