Limited sampling strategies for therapeutic drug monitoring of mycophenolate mofetil therapy in patients with autoimmune disease

Population pharmacokinetics of mycophenolate in patients treated for interstitial lung disease (EVER-ILD study)

BACKGROUND

Mycophenolate mofetil (MMF) has been used to treat interstitial lung disease (ILD), but mycophenolate (MPA) pharmacokinetics was not reported for this use. This ancillary study of the EVER-ILD protocol aimed at describing the pharmacokinetic variability of MPA using population modelling in ILD.

METHODS

Concentrations of MPA were measured during an 8-h course for 27 ILD patients treated with 1000 mg MMF b.i.d. Absorption, distribution and elimination of MPA were described using population compartment models with first-order transfer and elimination rate constants, while accounting for both absorption peaks using gamma absorption models.

RESULTS

The pharmacokinetics of MPA was best described using a two-compartment model and two gamma absorption models, model performances of this model were still similar to those of a one gamma absorption model. This pharmacokinetics seemed to be notably influenced by body weight, renal function and inflammatory status. The distribubtion value area under the concentration curve between two administrations of MMF was AUC12 = 52.5 mg.h/L in median (interquartile range: 42.2-58.0 mg.h/L).

CONCLUSION

This is the first study reporting MPA pharmacokinetics in ILD. This pharmacokinetics appears to be similar to other indications and should be further investigated in future studies.

Population pharmacokinetics and limited sampling strategy for therapeutic drug monitoring of mycophenolate mofetil in Japanese patients with lupus nephritis

BACKGROUND

Mycophenolate mofetil (MMF), a prodrug of the immunosuppressive agent mycophenolic acid (MPA), is difficult to administer because of the pharmacokinetic complexity of MPA. Although dosage adjustment according to the 12-h area under the concentration-time curve (AUC0-12) is thought to be desirable, multiple blood samplings for AUC calculation may pose a clinical challenge. A limited sampling strategy (LSS) would provide a solution; however, little is known about MPA pharmacokinetics in lupus nephritis patients, especially in those with Asian backgrounds, or few, if any, LSSs are reported for them.

METHODS

Thirty-four adult Japanese patients receiving MMF for lupus nephritis were examined retrospectively. MPA pharmacokinetics were investigated, and a PPK model was developed using Phoenix® NLME™ software. Single and double blood sampling strategies from Bayesian estimation using the PPK model and from multiple linear regression were compared. Tolerability was also evaluated.

RESULTS

In the pharmacokinetic analysis, renal function and serum albumin had significant effects on dose-normalized AUC0-12; and serum albumin, concomitant proton pump inhibitor (PPI) and iron/magnesium oxide did on dose-normalized maximum concentration. As a PPK model, a two-compartment model was developed with a transit absorption model and first-order elimination, in which creatinine clearance and serum albumin were covariates for MPA clearance. The double sampling strategy at 1 and 4 h by multiple linear regression showed the best agreement with the observed AUC0-12 (r2 = 0.885). Of the single sampling strategies, the one at 6 h by Bayesian estimation performed best (r2 = 0.769). The tolerability evaluation showed that correlations were suggested for gastrointestinal involvement.

CONCLUSIONS

The present study developed the first PPK model of MPA for Japanese lupus nephritis patients. As for LSSs, a double sampling strategy at 1 and 4 h by multiple linear regression would work best; when only a single blood sampling is allowed, a strategy at 6 h by Bayesian estimation using the PPK model developed in this study would be best. The LSSs good enough for clinical use may facilitate safer, more effective, and individualized therapy.

Population Pharmacokinetics And Bayesian Estimation of Mycophenolate Mofetil In Patients With Autoimmune Hepatitis

BACKGROUND

Mycophenolate mofetil (MMF) is the most widely used second-line agent in auto-immune hepatitis (AIH). Individual dose adjustment of MMF may avoid adverse outcomes while maximizing efficacy. The aim of the present study was to develop population pharmacokinetic (popPK) models and Maximum A-Posteriori Bayesian estimators (MAP-BEs) to estimate MPA inter-dose area under the curve (AUC_0-12h ) in AIH patients administered MMF using nonlinear mixed effect modelling.

METHODS

We analyzed 50 MPA PK profiles from 34 different patients, together with some demographic, clinical, and laboratory test data. The median number of plasma samples per profile, immediately preceding and following the morning MMF dose, was 7 [4 - 10]. PopPK modeling was performed using parametric, top-down, nonlinear mixed effect modelling with NONMEM 7.3. MAP-BEs were developed based on the best popPK model and the best limited sampling strategy (LSS) selected among several.

RESULTS

The pharmacokinetic data were best described by a 2-compartment model, Erlang distribution to describe the absorption phase, and a proportional error. The mean (RSE) of popPK parameter estimates of clearance, intercompartmental clearance, central volume and absorption rate with the final model were: 21.6 L.h^-1 (11%), 22.7 L.h^-1 (19%), 35.9 L (21%) and 8.7 h^-1 (9%), respectively. The peripheral volume was fixed to 300 L. The best MAP-BE relied on the LSS at 0.33, 1 and 3 hours after mycophenolate mofetil dose administration and was very accurate (bias=5.6%) and precise (RMSE<20%).

CONCLUSION

The precise and accurate Bayesian estimator developed in this study for AIH patients on MMF can be used to improve the therapeutic management of these patients.

Pharmacokinetics of mycophenolic acid and external evaluation of two limited sampling strategies of drug exposure in patients with juvenile systematic lupus erythematosus

INTRODUCTION

Mycophenolate mofetil (MMF), a pro-drug of mycophenolic acid (MPA), has become a major therapeutic option in juvenile systemic lupus erythematosus (jSLE). Monitoring MPA exposure using area under curve (AUC) has proved its value to increase efficacy and safety in solid organ transplantation both in children and adults, but additional data are required in patients with autoimmune diseases. In order to facilitate MMF therapeutic drug monitoring (TDM) in children, Bayesian estimators (BE) of MPA AUC_0-12 h using limited sampling strategies (LSS) have been developed. Our aim was to conduct an external validation of these LSS using rich pharmacokinetics and compare their predictive performance.

METHODS

Pharmacokinetic blood samples were collected from jSLE treated by MMF and MPA plasma concentrations were determined using high-performance liquid chromatography system with ultraviolet detection (HPLC-UV). Individual AUC_0-12 h at steady state was calculated using the trapezoid rule and compared with two LSS: (1) ISBA, a two-stage Bayesian approach developed for jSLE and (2) ADAPT, a non-linear mixed effects model with a parametric maximum likelihood approach developed with data from renal transplanted adults.

RESULTS

We received 41 rich pediatric PK at steady state from jSLE and calculated individual AUC_0-12 h. The external validation MPA AUC_0-12 h was conducted by selecting the concentration-time points adapted to ISBA and ADAPT: (1) ISBA showed good accuracy (bias: - 0.8 mg h/L), (2) ADAPT resulted in a bias of 6.7 mg L/h. The corresponding relative root mean square prediction error (RSME) was 23% and 43% respectively.

CONCLUSION

According to our external validation of two LSS of drug exposure, the ISBA model is recommended for Bayesian estimation of MPA AUC_0-12 h in jSLE. In the literature focusing on MMF TDM, an efficacy cut-off for MPA AUC_0-12 h between 30 and 45 mg h/L is proposed in jSLE but this requires additional validation.

Recent lessons learned from population pharmacokinetic studies of mycophenolic acid: physiological, genomic, and drug interactions leading to the prediction of drug effects

INTRODUCTION

Mycophenolic acid (MPA) is a widely used immunosuppressant in transplantation and autoimmune disease. Highly variable pharmacokinetics have been observed with MPA, but the exact mechanisms remain largely unknown.

AREAS COVERED

The current review provided a critical, comprehensive update of recently published population pharmacokinetic/dynamic models of MPA (n=16 papers identified from PubMed and Embase, inclusive from January 2017 to August 2021), with specific emphases on the intrinsic and extrinsic factors influencing the pharmacology of MPA. The significance of the identified covariates, potential mechanisms, and comparisons to historical literature have been provided.

EXPERT OPINION

While select covariates affecting the population pharmacokinetics of MPA are consistently observed and mechanistically supported, some variables have not been regularly reported and/or lacked mechanistic explanation. Very few pharmacodynamic models were available, pointing to the need to extrapolate pharmacokinetic findings. Ideal models of MPA should consist of: i) utilizing optimal sampling points to allow the characterizations of absorption, re-absorption, and elimination phases; ii) characterizing unbound/total MPA, MPA metabolites, plasma/urinary concentrations, and genetic polymorphisms to facilitate mechanistic interpretations; and iii) incorporating actual outcomes and pharmacodynamic data to establish clinical relevance. We anticipate the field will continue to expand in the next 5 to 10 years.

A Systematic Review of Multiple Linear Regression-Based Limited Sampling Strategies for Mycophenolic Acid Area Under the Concentration-Time Curve Estimation

Background and Objective

One approach of therapeutic drug monitoring in the case of mycophenolic acid (MPA) is a limited sampling strategy (LSS), which allows the evaluation of the area under the concentration–time curve (AUC) based on few concentrations. The aim of this systematic review was to review the MPA LSSs and define the most frequent time points for MPA determination in patients with different indications for mycophenolate mofetil (MMF) administration.

Methods

The literature was comprehensively searched in July 2021 using PubMed, Scopus, and Medline databases. Original articles determining multiple linear regression (MLR)-based LSSs for MPA and its free form (fMPA) were included. Studies on enteric-coated mycophenolic sodium, previously established LSS, Bayesian estimator, and different than twice a day dosing were excluded. Data were analyzed separately for (1) adult renal transplant recipients, (2) adults with other than renal transplantation indication, and (3) for pediatric patients.

Results

A total of 27, 17, and 11 studies were found for groups 1, 2, and 3, respectively, and 126 MLR-based LSS formulae (n = 120 for MPA, n = 6 for fMPA) were included in the review. Three time-point equations were the most frequent. Four MPA LSSs: 2.8401 + 5.7435 × C0 + 0.2655 × C0.5 + 1.1546 × C1 + 2.8971 × C4 for adult renal transplant recipients, 1.783 + 1.248 × C1 + 0.888 × C2 + 8.027 × C4 for adults after islet transplantation, 0.10 + 11.15 × C0 + 0.42 × C1 + 2.80 × C2 for adults after heart transplantation, and 8.217 + 3.163 × C0 + 0.994 × C1 + 1.334 × C2 + 4.183 × C4 for pediatric renal transplant recipients, plus one fMPA LSS, 34.2 + 1.12 × C1 + 1.29 × C2 + 2.28 × C4 + 3.95 × C6 for adult liver transplant recipients, seemed to be the most promising and should be validated in independent patient groups before introduction into clinical practice. The LSSs for pediatric patients were few and not fully characterized. There were only a few fMPA LSSs although fMPA is a pharmacologically active form of the drug.

Conclusions

The review includes updated MPA LSSs, e.g., for different MPA formulations (suspension, dispersible tablets), generic form, and intravenous administration for adult and pediatric patients, and emphasizes the need of individual therapeutic approaches according to MMF indication. Five MLR-based MPA LSSs might be implemented into clinical practice after evaluation in independent groups of patients. Further studies are required, e.g., to establish fMPA LSS in pediatric patients.

The Evaluation of Multiple Linear Regression-Based Limited Sampling Strategies for Mycophenolic Acid in Children with Nephrotic Syndrome

We evaluated mycophenolic acid (MPA) limited sampling strategies (LSSs) established using multiple linear regression (MLR) in children with nephrotic syndrome treated with mycophenolate mofetil (MMF). MLR-LSS is an easy-to-determine approach of therapeutic drug monitoring (TDM). We assessed the practicability of different LSSs for the estimation of MPA exposure as well as the optimal time points for MPA TDM. The literature search returned 29 studies dated 1998–2020. We applied 53 LSSs (n = 48 for MPA, n = 5 for free MPA [fMPA]) to predict the area under the time-concentration curve (AUC_pred) in 24 children with nephrotic syndrome, for whom we previously determined MPA and fMPA concentrations, and compare the results with the determined AUC (AUC_total). Nine equations met the requirements for bias and precision ±15%. The MPA AUC in children with nephrotic syndrome was predicted the best by four time-point LSSs developed for renal transplant recipients. Out of five LSSs evaluated for fMPA, none fulfilled the ±15% criteria for bias and precision probably due to very high percentage of bound MPA (99.64%). MPA LSS for children with nephrotic syndrome should include blood samples collected 1 h, 2 h and near the second MPA maximum concentration. MPA concentrations determined with the high performance liquid chromatography after multiplying by 1.175 may be used in LSSs based on MPA concentrations determined with the immunoassay technique. MPA LSS may facilitate TDM in the case of MMF, however, more studies on fMPA LSS are required for children with nephrotic syndrome.

Pharmacokinetic Model Analysis of Supralingual, Oral and Intravenous Deliveries of Mycophenolic Acid

Mycophenolic acid (MPA) is commonly used for organ rejection prophylaxis via oral administration in the clinic. Recent studies have shown that MPA also has anticancer activities. To explore new therapeutic options for oral precancerous/cancerous lesions, MPA was designed to release topically on the dorsal tongue surface via a mucoadhesive patch. The objective of this study was to establish the pharmacokinetic (PK) and tongue tissue distribution of mucoadhesive MPA patch formulation after supralingual administration in rats and also compare the PK differences between oral, intravenous, and supralingual administration of MPA. Blood samples were collected from Sprague Dawley rats before and after a single intravenous bolus injection, a single oral dose, or a mucoadhesive patch administration on the dorsal tongue surface for 4 h, all with a dose of 0.5 mg/kg of MPA. Plots of MPA plasma concentration versus time were obtained. As multiple peaks were found in all three curves, the enterohepatic recycling (EHR) model in the Phoenix software was adapted to describe their PK parameters with an individual PK analysis method. The mean half-lives of intravenous and oral administrations were 10.5 h and 7.4 h, respectively. The estimated bioavailability after oral and supralingual administration was 72.4% and 7.6%, respectively. There was a 0.5 h lag-time presented after supralingual administration. The results suggest that the systemic plasma MPA concentrations were much lower in rats receiving supralingual administration compared to those receiving doses from the other two routes, and the amount of MPA accumulated in the tongue after patch application showed a sustained drug release pattern. Studies on the dynamic of drug retention in the tongue after supralingual administration showed that ~3.8% of the dose was accumulated inside of tongue right after the patch removal, ~0.11% of the dose remained after 20 h, and ~20.6% of MPA was not released from the patches 4 h after application. The data demonstrate that supralingual application of an MPA patch can deliver a high amount of drug at the site of administration with little systemic circulation exposure, hence lowering the potential gastrointestinal side effects associated with oral administration. Thus, supralingual administration is a potential alternative route for treating oral lesions.

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.

Mycophenolate mofetil for systemic sclerosis: drug exposure exhibits considerable inter-individual variation-a prospective, observational study

Objective

Mycophenolate mofetil (MMF) is an established therapy for systemic sclerosis (SSc), but its pharmacokinetics in this disease remains unexplored. We have investigated drug exposure in MMF-treated patients with SSc in relation to clinical features of the disease and common concomitant drugs.

Methods

This study was predefined to include 35 MMF-treated SSc patients who were using MMF at a fixed dose of 0.5, 1.0 or 1.5 g twice daily since at least 3 months. The 12-h drug exposure of the active MMF metabolite mycophenolic acid (MPA) was estimated by repeated analysis of plasma MPA over a 6-h period. This 12-h drug exposure was dose normalised to a daily intake of 3 g MMF (MPA_AUC_3g) in order to compare subjects using MMF at different doses. Drug exposure was analysed in reference to the clinical characteristics including body weight, renal function, autoantibodies, intestinal dysbiosis, intestinal inflammation assessed by faecal (F)-calprotectin, intestinal symptoms assessed by the University of California Los Angeles Scleroderma Trial Consortium Gastrointestinal Tract Instrument 2.0 and concomitant drug usage including proton-pump inhibitors (PPI).

Results

Thirty-four out of 35 study participants completed the study. The mean daily MMF dose was 2.1 g. Drug exposure expressed as MPA_AUC_3g varied up to 8-fold between patients (median 115, range 27–226 mg h/L).

MPA_AUC_3g was inversely related to body weight (r_s = − 0.58, p < 0.001) and renal function (r_s = − 0.34, p = 0.054). Anti-topoisomerase-1 antibodies and male sex were associated with lower MPA_AUC_3g (87 vs 123 and 71 vs 141; p = 0.008 and p = 0.015, respectively). MPA_AUC_3g was inversely related to the intestinal abundance of lactobacilli and to F-calprotectin (r_s = − 0.54, p = 0.004; r_s = − 0.36, p = 0.034), but not to gastrointestinal symptoms. MPA_AUC_3g was inversely related to PPI usage (r_s = − 0.45, p = 0.007). We found no association between MPA_AUC_3g and disease subtype, disease duration or disease activity.

Conclusion

MMF-treated SSc patients exhibit considerable inter-individual variation in drug exposure, and lower MPA levels were primarily found in PPI users with poor prognostic factors. Body weight, renal function, sex, serology, gastrointestinal manifestations and/or measuring individual MPA exposure should be considered when using MMF for SSc.

Therapeutic drug monitoring of β-lactam antibiotics in the ICU

INTRODUCTION

Individualizing antibiotic therapy is paramount to improve clinical outcomes while minimizing the risk of toxicity and antimicrobial therapy. β-lactam antibiotics are amongst the drugs most commonly prescribed in the Intensive Care Unit (ICU). The pharmacokinetics of β-lactam antibiotics are profoundly altered in critically ill patients, leading to the failure of standard drug dosing regimens to result in adequate drug concentrations. Therapeutic Drug Monitoring (TDM) of β-lactam antibiotics is a promising tool to help optimize β-lactam antibiotic therapy.

AREAS COVERED

The rationale behind TDM for β-lactam antibiotics is explained, as well as some more practical aspects such as when to sample, what concentrations to strive for and how to use it in clinical practice. We also discuss microbiological and analytical considerations, knowledge gaps, and future perspectives of β-lactam antibiotics TDM in ICU patients.

EXPERT OPINION

TDM of β-lactam antibiotics has been studied intensively in recent years. While TDM may not yet be widely available, and targets need to be further refined, TDM of β-lactam antibiotics will help to optimize antibiotic therapy in the critically ill patient, as an integrated part of an antimicrobial stewardship program.

Population pharmacokinetics of mycophenolic acid in Mexican patients with lupus nephritis

Background

Mycophenolic acid (MPA) is an effective oral immunosuppressive drug used to treat lupus nephritis (LN), which exhibits large pharmacokinetic variability. This study aimed to characterize MPA pharmacokinetic behaviour in Mexican LN patients and to develop a population pharmacokinetic model which identified factors that influence MPA pharmacokinetic variability.

Methods

Blood samples from LN patients treated with mycophenolate mofetil (MMF) were collected pre dose and up to six hours post dose. MPA concentrations were determined by a validated ultra-performance liquid chromatography tandem mass spectrometry technique. Patients were genotyped for polymorphisms in enzymes (UGT1A8, 1A9 and 2B7) and transporters (ABCC2 and SLCO1B3). The anthropometric, clinical, genetic and co-medication characteristics of each patient were considered as potential covariates to explain the variability.

Results

A total of 294 MPA concentrations from 40 LN patients were included in the development of the model. The data were analysed using NONMEM software and were best described by a two-compartment linear model. MPA CL, Vc, Vp, Ka and Q were 15.4 L/h, 22.86 L, 768 L, 1.28 h−1and 20.3 L/h, respectively. Creatinine clearance and prednisone co-administration proved to have influence on clearance, while body weight influenced Vc. The model was internally validated, proving to be stable. MMF dosing guidelines were obtained through stochastic simulations performed with the final model.

Conclusions

This is the first MPA population pharmacokinetic model to have found that co-administration of prednisone results in a considerable increase on clearance. Therefore, this and the other covariates should be taken into account when prescribing MMF in order to optimize the immunosuppressant therapy in patients with LN.

Model-Based Evaluation of Linear Limited and Bayesian Sparse Sampling for Therapeutic Monitoring of Recombinant Coagulation Factor IX

Dosing of coagulation factor products is mainly determined based on a patient's body weight; however, several studies have reported high interindividual variability in their pharmacokinetics (PK). The objective of this study was to develop and evaluate 2 sparse sampling methods for the estimation of AUC of recombinant factor IX (BeneFIX) as proof of concept for dose individualization. A population pharmacokinetic model was used to generate the plasma factor IX activity-versus-time data. The linear limited sampling model (LLSM) was developed based on the correlation of factor IX activity versus AUC_0-72 hours following screening of several blood sampling times in adolescent and adult subjects (n = 90 subjects). Factor IX trough concentrations were predicted from a relationship established from AUC versus factor IX activity measured 72 hours postdosing. Using the best selected sampling time, the LLSM and Bayesian model were validated in separate data sets (n = 75 subjects). Using the LLSM and Bayesian analysis, a blood sample at 24 hours predicted AUC with bias and root mean square error < 5% and < 15%, respectively. The predicted trough concentrations were ≥1 IU/dL in 99% and 100% of subjects by the LLSM and Bayesian model, respectively. The average factor IX dose for a target AUC of 800 IU·h/dL was 61, 60, and 63 IU/kg using the extensive (reference), LLSM and Bayesian model, respectively. Overall, the AUC, trough concentrations and individualized dosing of recombinant factor IX could be reasonably predicted using the LLSM and Bayesian model.

Pharmacokinetic Characteristics and Limited Sampling Strategies for Therapeutic Drug Monitoring of Colistin in Patients With Multidrug-Resistant Gram-Negative Bacterial Infections

BACKGROUND

Colistin is increasingly used as the last therapeutic option for the treatment of multidrug-resistant, Gram-negative bacterial infections. To ensure safe and efficacious use of colistin, therapeutic drug monitoring (TDM) is needed due to its narrow therapeutic window. This study aimed to evaluate the pharmacokinetic (PK) characteristics of colistin and to guide TDM in colistin-treated patients in Korea.

METHODS

In a prospective study, we analyzed PK characteristics in 15 patients who intravenously received colistin methanesulfonate twice per day. Colistin methanesulfonate doses were adjusted based on renal function of the subjects. The appropriate blood sampling points for TDM were evaluated by analyzing the correlations between the PK parameters and the plasma concentrations at each time point.

RESULTS

The mean values for the minimum, maximum, and average concentrations (Cmin, Cmax, and Caverage) of colistin at steady state were 2.29, 5.5, and 3.38 mg/L, respectively. The dose-normalized Cmin, Cmax, Caverage, and area under the plasma concentration-time curve from 0 to the last measurable concentration (AUClast) showed negative correlations with the creatinine clearance. The combination of the 0- and 2-hour post-dose plasma concentrations was evaluated as the appropriate sampling point for TDM. Two patients reported nephrotoxic adverse events during colistin administration.

CONCLUSIONS

Our study clarifies the PK characteristics of successful colistin treatment using TDM. Further evaluations in a larger patient population are needed to confirm the clinical usefulness of colistin TDM.

Pharmacokinetics, Pharmacodynamics, and Pharmacogenomics of Immunosuppressants in Allogeneic Hematopoietic Cell Transplantation: Part II

Part I of this article included a pertinent review of allogeneic hematopoietic cell transplantation (alloHCT), the role of postgraft immunosuppression in alloHCT, and the pharmacokinetics, pharmacodynamics, and pharmacogenomics of the calcineurin inhibitors and methotrexate. In this article (Part II), we review the pharmacokinetics, pharmacodynamics, and pharmacogenomics of mycophenolic acid (MPA), sirolimus, and the antithymocyte globulins (ATG). We then discuss target concentration intervention (TCI) of these postgraft immunosuppressants in alloHCT patients, with a focus on current evidence for TCI and on how TCI may improve clinical management in these patients. Currently, TCI using trough concentrations is conducted for sirolimus in alloHCT patients. Several studies demonstrate that MPA plasma exposure is associated with clinical outcomes, with an increasing number of alloHCT patients needing TCI of MPA. Compared with MPA, there are fewer pharmacokinetic/dynamic studies of rabbit ATG and horse ATG in alloHCT patients. Future pharmacokinetic/dynamic research of postgraft immunosuppressants should include '-omics'-based tools: pharmacogenomics may be used to gain an improved understanding of the covariates influencing pharmacokinetics as well as proteomics and metabolomics as novel methods to elucidate pharmacodynamic responses.

Pharmacokinetic modeling of therapies for systemic lupus erythematosus

With the increasing use of different types of therapies in treating autoimmune diseases such as systemic lupus erythematosus (SLE), there is a need to utilize pharmacokinetic (PK) strategies to optimize the clinical outcome of these treatments. Various PK analysis approaches, including population PK modeling and physiologically based PK modeling, have been used to evaluate drug PK characteristics and population variability or to predict drug PK profiles in a mechanistic manner. This review outlines the PK modeling of major SLE therapies including immunosuppressants (methotrexate, azathioprine, mycophenolate and cyclophosphamide, among others) and immunomodulators (intravenous immunoglobulin). It summarizes the population PK modeling, physiologically based PK modeling and model-based individualized dosing strategies to improve the therapeutic outcomes in SLE patients.

Optimal design in pediatric pharmacokinetic and pharmacodynamic clinical studies

It is not trivial to conduct clinical trials with pediatric participants. Ethical, logistical, and financial considerations add to the complexity of pediatric studies. Optimal design theory allows investigators the opportunity to apply mathematical optimization algorithms to define how to structure their data collection to answer focused research questions. These techniques can be used to determine an optimal sample size, optimal sample times, and the number of samples required for pharmacokinetic and pharmacodynamic studies. The aim of this review is to demonstrate how to determine optimal sample size, optimal sample times, and the number of samples required from each patient by presenting specific examples using optimal design tools. Additionally, this review aims to discuss the relative usefulness of sparse vs rich data. This review is intended to educate the clinician, as well as the basic research scientist, whom plan on conducting a pharmacokinetic/pharmacodynamic clinical trial in pediatric patients.

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.

Concentration-controlled treatment of lupus nephritis with mycophenolate mofetil

Background:

Mycophenolate mofetil (MMF) has recently been established as a potent drug in maintenance treatment for lupus nephritis. However, there is no consensus on the optimal dosing regimen because of a high inter-individual variability of mycophenolic acid (MPA), the active metabolite of MMF. This retrospective study aimed to investigate the effect of an individualized dosing regimen through concentration-controlled treatment on MPA exposure and renal outcome in patients with lupus nephritis.

Methods:

Sixteen patients with lupus nephritis and treatment with low-dose intravenous cyclophosphamide followed by MMF were included. MPA area under the plasma concentration-time curve from 0 to 12 hours (MPA-AUC0–12) was assessed within a month after MMF initiation. After determination of MPA-AUC0–12, MMF doses were titrated to achieve a target MPA-AUC0–12 of 60–90 mg*h/l. After on average six months, MPA-AUC0–12 measures were repeated to assess the effect of dose adjustment.

Results:

One month after introducing MMF, MPA-AUC0–12 was low and showed a high inter-individual variability. Dose adjustment with a target MPA-AUC0–12 of 60–90 mg*h/l resulted in individualized MMF dosing, significantly higher MPA-AUC0–12 levels, and a non-significant reduction in variability of MPA-AUC0–12. Adverse effects were reported by 37.5% of patients, which resulted in a switch to azathioprine in two patients. There was no significant relationship between the occurrence of adverse effects and MPA-AUC0–12. At 12 months of follow-up 87.5% of patients had achieved either partial (18.7%) or complete (68.8%) remission.

Conclusion:

Concentration-controlled dose adjustments with a target MPA-AUC0–12 of 60–90 mg*h/l was associated with optimized MPA exposure and an excellent renal outcome at 12 months of follow-up in a small sample of SLE patients with lupus nephritis.

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.

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?

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.

Population pharmacokinetics of mycophenolic acid and metabolites in patients with glomerulonephritis

Mycophenolic acid (MPA) is an inosine monophosphate dehydrogenase inhibitor used for glomerulonephritis treatment. The objective of the current study was to develop a population pharmacokinetic model for MPA and metabolites in glomerulonephritis to enable appropriate design of MPA regimens in these patients with alterations in kidney structure and function. Thirty-nine patients with glomerulonephritis and receiving mycophenolate mofetil were recruited to participate in a 24-hour pharmacokinetic study. Blood was collected at times 0, 0.5, 1.0, 1.5, 2, 3, 4, 6, 8, 12, and 24 hours and urine was collected over the intervals of 0 to 6, 6 to 12, and 12 to 24 hours. Plasma and urine samples were assayed for MPA and MPA glucuronide (MPAG) by high-performance liquid chromatography and for acyl-MPA glucuronide (AcMPAG) by liquid chromatography/mass spectrometry. Population pharmacokinetic analysis and covariate model building were evaluated using Non-linear Mixed Effect Modeling software (NONMEM, Version 6.2.0; ICON Development Solutions, Ellicott City, MD). The final model for MPA and its metabolites consisted of nine discrete compartments; 1) depot gastrointestinal; 2) central MPA; 3) peripheral MPA; 4) gallbladder; 5) MPA urine; 6) MPAG central; 7) MPAG urine; 8) AcMPAG central; and 9) AcMPAG urine compartment. The MPA population mean estimates for apparent nonrenal clearance (ClNR/F) and apparent central volume of distribution were 14.3 L/hr and 21.1 L, respectively. The mean population estimate for apparent renal clearance (ClR/F) was dependent on estimated creatinine clearances (eClcr); 0.0975 L/hr for eClcr 80 mL/min or less and 0.157 L/hr for eClcr greater than 80 mL/min. Covariate analyses identified: eClcr on CLNR,MPA/F (P < 0.001), eClcr (with a cutoff value at 80 mL/min) on CLR,MPA/F (P < 0.025), serum albumin on CLNR,MPA/F (P < 0.01), eClcr on CLR,MPAG/F (P < 0.001), and eClcr on CLR,AcMPAG/F (P < 0.001). Evaluation of the final model by visual predictive check showed that most of the observed values were within the 95th percent prediction interval generated from 100 simulations of the final model. The current population pharmacokinetic model demonstrated eClcr and serum albumin influenced the renal and nonrenal components of Cl/F, suggesting patients with glomerulonephritis would have highly altered MPA exposures.

Nonlinear relationship between mycophenolate mofetil dose and mycophenolic acid exposure: implications for therapeutic drug monitoring

BACKGROUND AND OBJECTIVES

Mycophenolate mofetil (MMF) is an immunosuppressive drug used in renal transplant patients. Upon oral administration it is hydrolyzed to the active agent mycophenolic acid (MPA). In renal transplant recipients, MMF therapy is optimal when the area under the curve of MPA is 30 to 60 mg·h/L. When MMF doses are adjusted, a linear relationship between dose and MPA exposure is assumed. In this study, the linearity of MMF pharmacokinetics was investigated.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

MPA concentration-time profiles from renal transplant recipients cotreated with cyclosporine (n = 140) or tacrolimus (n = 101) were analyzed retrospectively using nonlinear mixed-effects modeling. The correlation between the MMF dose and the pharmacokinetics parameters was evaluated.

RESULTS

In the developed population pharmacokinetics model MPA clearance and the central volume of distribution were correlated with cyclosporine coadministration and time posttransplantation. The pharmacokinetics of MPA were not linear. Bioavailability decreased with increasing MMF doses. Compared with an MMF dose of 1000 mg (=100%), relative bioavailability was 123%, 111%, 94%, and 90% in patients receiving MMF doses of 250, 500, 1500, and 2000 mg in combination with cyclosporine (P < 0.001); respective values in tacrolimus-cotreated patients were 176%, 133%, 85%, and 76% (P < 0.001). Because of the decreasing relative bioavailability, MPA exposure will increase less than proportionally with increasing MMF doses.

CONCLUSIONS

MMF exhibits nonlinear pharmacokinetics. This should be taken into account when performing therapeutic drug monitoring.

Proton pump inhibitors interfere with the immunosuppressive potency of mycophenolate mofetil

OBJECTIVES

MMF is cleaved in the acidic milieu of the gastric compartment. However, its absorption might be impeded by proton pump inhibitors (PPIs), which suppress acid production and thus increase stomach pH. Since PPIs are widely used, it is useful to clarify whether the total drug amount of MMF is available in patients undergoing PPI treatment.

METHODS

We analysed 36 patients with autoimmune diseases under stable MMF maintenance therapy. Twenty-three patients received co-medication with pantoprazole; 13 patients received no treatment with PPIs or antacids. To assess the immunosuppressive potency, we measured mycophenolic acid levels and inosin monophosphate dehydrogenase (IMPDH) activity with a validated HPLC method in plasma samples collected pre-dose and at 0.5, 1, 1.5, 2, 3, 4, 5, 6, 8, 10 and 12 h after oral administration.

RESULTS

The mean MMF dosage of the non-PPI patients was 770 (249) mg/12 h and 771 (291) mg/12 h in pantoprazole-treated patients (NS). The total area under the curve of MMF showed a 37% reduction in PPI patients vs those treated with no PPIs (P < 0.01), and the maximum peak concentration of MMF was 60% lower in the pantoprazole patients (P < 0.001). The MMF exposure correlated with the inhibition of IMPDH activity. The area of enzyme activity curve was 42% higher in the PPI patients (P < 0.01).

CONCLUSIONS

The co-medication of pantoprazole with MMF significantly influences the drug exposure and immunosuppressive potency of MMF in patients with autoimmune diseases. This finding might at least partly explain the different outcomes in studies using MMF for maintenance therapy.

Pharmacokinetic role of protein binding of mycophenolic acid and its glucuronide metabolite in renal transplant recipients

Mycophenolic acid (MPA), the active compound of mycophenolate mofetil (MMF), is used to prevent graft rejection in renal transplant recipients. MPA is glucuronidated to the metabolite MPAG, which exhibits enterohepatic recirculation (EHC). MPA binds for 97% and MPAG binds for 82% to plasma proteins. Low plasma albumin concentrations, impaired renal function and coadministration of cyclosporine have been reported to be associated with increased clearance of MPA. The aim of the study was to develop a population pharmacokinetic model describing the relationship between MMF dose and total MPA (tMPA), unbound MPA (fMPA), total MPAG (tMPAG) and unbound MPAG (fMPAG). In this model the correlation between pharmacokinetic parameters and renal function, plasma albumin concentrations and cotreatment with cyclosporine was quantified. tMPA, fMPA, tMPAG and fMPAG concentration-time profiles of renal transplant recipients cotreated with cyclosporine (n = 48) and tacrolimus (n = 45) were analyzed using NONMEM. A 2- and 1-compartment model were used to describe the pharmacokinetics of fMPA and fMPAG. The central compartments of fMPA and fMPAG were connected with an albumin compartment allowing competitive binding (bMPA and bMPAG). tMPA and tMPAG were modeled as the sum of the bound and unbound concentrations. EHC was modeled by transport of fMPAG to a separate gallbladder compartment. This transport was decreased in case of cyclosporine cotreatment (P < 0.001). In the model, clearance of fMPAG decreased when creatinine clearance (CrCL) was reduced (P < 0.001), and albumin concentration was correlated with the maximum number of binding sites available for MPA and MPAG (P < 0.001). In patients with impaired renal function cotreated with cyclosporine the model adequately described that increasing fMPAG concentrations decreased tMPA AUC due to displacement of MPA from its binding sites. The accumulated MPAG could also be reconverted to MPA by the EHC, which caused increased tMPA AUC in patients cotreated with tacrolimus. Changes in CrCL had hardly any effect on fMPA exposure. A decrease in plasma albumin concentration from 0.6 to 0.4 mmol/l resulted in ca. 38% reduction of tMPA AUC, whereas no reduction in fMPA AUC was seen. In conclusion, a pharmacokinetic model has been developed which describes the relationship between dose and both total and free MPA exposure. The model adequately describes the influence of renal function, plasma albumin and cyclosporine co-medication on MPA exposure. Changes in protein binding due to altered renal function or plasma albumin concentrations influence tMPA exposure, whereas fMPA exposure is hardly affected.