Population pharmacokinetics and Bayesian estimators for intravenous mycophenolate mofetil in haematopoietic stem cell transplant patients

Predicting the exposure of mycophenolic acid in children with autoimmune diseases using a limited sampling strategy: A retrospective study

Mycophenolic acid (MPA) is commonly used to treat autoimmune diseases in children, and therapeutic drug monitoring is recommended to ensure adequate drug exposure. However, multiple blood sampling is required to calculate the area under the plasma concentration-time curve (AUC), causing patient discomfort and waste of human and financial resources. This study aims to use machine learning and deep learning algorithms to develop a prediction model of MPA exposure for pediatric autoimmune diseases with optimizing sampling frequency. Pediatric autoimmune patients' data were collected at Nanfang Hospital between June 2018 and June 2023. Univariate analysis was applied for feature selection. Ten algorithms, including Random Forest, XGBoost, LightGBM, Gradient Boosting Decision Tree, CatBoost, Artificial Neural Network, Grandient Boosting Machine, Transformer, Wide&Deep, and TabNet, were employed for modeling based on two, three, or four concentrations of MPA. A total of 614 MPA AUC0-12h samples from 209 patients were enrolled. Among the 10 models evaluated, the Wide&Deep model exhibited the best predictive performance. The predictive performance of the Wide&Deep model using four and three blood concentration points was similar (R 2 ≈ 1 for four points; R 2 = 0.95 for three points). No significant difference in accuracy within ±30% was observed between models utilizing three and four blood concentration points (p = 0.06). This study demonstrates that in the Wide&Deep model, MPA exposure can be accurately estimated with three sampling points in children with autoimmune diseases. This model could help reduce discomfort in pediatric patients without reducing the accuracy of MPA exposure estimates in clinical practice.

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 of Mycophenolate Mofetil for Indian Patients With Lupus Nephritis

BACKGROUND

Mycophenolic acid is widely used to treat lupus nephritis (LN). However, it exhibits complex pharmacokinetics with large interindividual variability. This study aimed to develop a population pharmacokinetic (popPK) model and a 3-sample limited sampling strategy (LSS) to optimize therapeutic drug monitoring in Indian patients with LN.

METHODS

Five blood samples from each LN patient treated with mycophenolic acid were collected at steady-state predose and 1, 2, 4, and 6 hours postdose. Demographic parameters were tested as covariates to explain interindividual variability. PopPK analysis was performed using Monolix and the stochastic approximation expectation-maximization algorithm. An LSS was derived from 500 simulated pharmacokinetic (PK) profiles using maximum a posteriori Bayesian estimation to estimate individual PK parameters and area under the curve (AUC). The LSS-calculated AUC was compared with the AUC calculated using the trapezoidal rule and all the simulated samples.

RESULTS

A total of 51 patients were included in this study. Based on the 245 mycophenolic acid concentrations, a 1-compartmental model with double absorption using gamma distributions best fitted the data. None of the covariates improved the model significantly. The model was internally validated using diagnostic plots, prediction-corrected visual predictive checks, and bootstrapping. The best LSS included samples at 1, 2, and 4 hours postdose and exhibited good performances in an external dataset (root mean squared error, 21.9%; mean bias, -4.20%).

CONCLUSIONS

The popPK model developed in this study adequately estimated the PK of mycophenolic acid in adult Indian patients with LN. This simple LSS can optimize TDM based on the AUC in routine practice.

Body Surface Area-Based Dosing of Mycophenolate Mofetil in Pediatric Hematopoietic Stem Cell Transplant Recipients: A Prospective Population Pharmacokinetic Study

Mycophenolate mofetil (MMF) is commonly used for acute graft-versus-host disease (aGVHD) after allogeneic hematopoietic stem cell transplantation (HSCT). However, limited population pharmacokinetic (PPK) data are available for pediatric HSCT patients. This study aimed to develop a PPK model and recommend optimal oral MMF dosage in pediatric HSCT patients. This prospective study involved pediatric HSCT patients at a tertiary academic institution. Patients received oral MMF 15-20 mg/kg twice daily for aGVHD prophylaxis and treatment. The PPK analysis was conducted using a nonlinear mixed-effects modeling method. Simulation was performed considering different body surface areas (BSAs) (0.5 m2, 1.0 m2, 1.5 m2) and dosing (400 mg/m2, 600 mg/m2, 900 mg/m2 twice daily). Based on the simulation, an optimal dosage of oral MMF was suggested. A total of 20 patients and 80 samples were included in the PPK model development. A one-compartment model with first-order absorption adequately described the pharmacokinetics of mycophenolic acid (MPA). BSA was a statistically significant covariate on Vd/F. Simulation suggested the optimal dosage of oral MMF as 900 mg/m2 twice daily, respectively. A reliable PPK model was developed with good predictive performance. This model-informed optimal MMF dosage in pediatric HSCT patients can provide valuable dosing guidance in real-world clinical practice.

Tacrolimus population pharmacokinetics in adult heart transplant patients

INTRODUCTION

Tacrolimus is an immunosuppressant largely used in heart transplantation. However, the calculation of its exposure based on the area under the curve (AUC) requires the use of a population pharmacokinetic (PK) model. The aims of this work were (i) to develop a population PK model for tacrolimus in heart transplant patients, (ii) to derive a maximum a posteriori Bayesian estimator (MAP-BE) based on a limited sampling strategy (LSS) and (iii) to estimate probabilities of target attainment (PTAs) for AUC and trough concentration (C0).

MATERIAL AND METHODS

Forty-seven PK profiles (546 concentrations) of 18 heart transplant patients of the Pharmacocinétique des Immunosuppresseurs chez les patients GREffés Cardiaques study receiving tacrolimus (Prograf®) were included. The database was split into a development (80%) and a validation (20%) set. PK parameters were estimated in MONOLIX® and based on this model a Bayesian estimator using an LSS was built. Simulations were performed to calculate the PTA for AUC and C0.

RESULTS

The best model to describe the tacrolimus PK was a two-compartment model with a transit absorption and a linear elimination. Only the CYP3A5 covariate was kept in the final model. The derived MAP-BE based on the LSS (0-1-2 h postdose) yielded an AUC bias ± SD = 2.7 ± 10.2% and an imprecision of 9.9% in comparison to the reference AUC calculated using the trapezoidal rule. PTAs based on AUC or C0 allowed new recommendations to be proposed for starting doses (0.11 mg·kg-1 ·12 h-1 for the CYP3A5 nonexpressor and 0.22 mg·kg1 ·12 h-1 for the CYP3A5 expressor).

CONCLUSION

The MAP-BE developed should facilitate estimation of tacrolimus AUC in heart transplant patients.

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.

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.

Parametric and Nonparametric Methods in Population Pharmacokinetics: Experts' Discussion on Use, Strengths, and Limitations

Population pharmacokinetics consists of analyzing pharmacokinetic (PK) data collected in groups of individuals. Population PK is widely used to guide drug development and to inform dose adjustment via therapeutic drug monitoring and model-informed precision dosing. There are 2 main types of population PK methods: parametric (P) and nonparametric (NP). The characteristics of P and NP population methods have been previously reviewed. The aim of this article is to answer some frequently asked questions that are often raised by scholars, clinicians, and researchers about P and NP population PK methods. The strengths and limitations of both approaches are explained, and the characteristics of the main software programs are presented. We also review the results of studies that compared the results of both approaches in the analysis of real data. This opinion article may be informative for potential users of population methods in PK and guide them in the selection and use of those tools. It also provides insights on future research in this area.

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.

Population pharmacokinetics of mycophenolic acid in paediatric patients

Mycophenolic acid (MPA) is widely used in paediatric kidney transplant patients and sometimes prescribed for additional indications. Population pharmacokinetic or pharmacodynamic modelling has been frequently used to characterize the fixed, random and covariate effects of MPA in adult patients. However, MPA population pharmacokinetic data in the paediatric population have not been systematically summarized. The objective of this narrative review was to provide an up-to-date critique of currently available paediatric MPA population pharmacokinetic models, with emphases on modelling techniques, pharmacological findings and clinical relevance. PubMed and EMBASE were searched from inception of database to May 2020, where a total of 11 studies have been identified representing kidney transplant (n = 4), liver transplant (n = 1), haematopoietic stem cell transplant (n = 1), idiopathic nephrotic syndrome (n = 2), systemic lupus erythematosus (n = 2), and a combined population consisted of kidney, liver and haematopoietic stem cell transplant patients (n = 1). Critical analyses were provided in the context of MPA absorption, distribution, metabolism, excretion and bioavailability in this paediatric database. Comparisons to adult patients were also provided. With respect to clinical utility, Bayesian estimation models (n = 6) with acceptable accuracy and precision for MPA exposure determination have also been identified and systematically evaluated. Overall, our analyses have identified unique features of MPA clinical pharmacology in the paediatric population, while recognizing several gaps that still warrant further investigations. This review can be used by pharmacologists and clinicians for improving MPA pharmacokinetic-pharmacodynamic modelling and patient care.

Population pharmacokinetics and Bayesian estimators for intravenous mycophenolate mofetil in haematopoietic stem cell transplant patients

AIMS

Intravenous mycophenolate mofetil (IV MMF), a prodrug of mycophenolic acid (MPA), is used during nonmyeloablative and reduced-intensity conditioning haematopoetic stem cell transplantation (HCT) to improve engraftment and reduce graft-versus-host disease. The aims of this study were to develop population pharmacokinetic models and Bayesian estimators based on limited sampling strategies to allow for individual dose adjustment of intravenous mycophenolate mofetil administered by infusion in haematopoietic stem cell transplant patients.

METHODS

Sixty-three MPA concentration-time profiles (median [min-max] = 6 [4-7] samples) were collected from 34 HCT recipients transplanted for 14 (1-45) days and administered IV MMF every 8 hours, concomitantly with cyclosporine. The database was split into development (75%) and validation (25%) datasets. Pharmacokinetic models characterized by a single compartment with first-order elimination, combined with two gamma distributions to describe the transformation of MMF into mycophenolic acid, were developed using in parallel nonparametric (Pmetrics) and parametric (ITSIM) approaches. The performances of the models and the derived Bayesian estimators were evaluated in the validation set.

RESULTS

The best limited sampling strategy led to a bias (min, max), root mean square error between observed and modeled interdose areas under the curve in the validation dataset of -11.72% (-31.08%, 5.00%), 14.9% for ITSIM and -2.21% (-23.40%, 30.01%), 12.4% for Pmetrics with three samples collected at 0.33, 2 and 3 hours post dosing.

CONCLUSION

Population pharmacokinetic models and Bayesian estimators for IV MMF in HCT have been developed and are now available online (https://pharmaco.chu-limoges.fr) for individual dose adjustment based on the interdose area under the curve.