Limited sampling strategy for predicting area under the concentration-time curve of mycophenolic acid in adult lung transplant recipients

An integrated sampling strategy for therapeutic mycophenolic acid monitoring in lung transplant recipients

BACKGROUND

Mycophenolic Acid (MPA) is the most used anti-proliferative in lung transplantation, but its pharmacokinetic (PK) variability has precluded therapeutic drug monitoring. Both genetic and clinical factors have been implicated in MPA variability. This study aimed to integrate genetic and clinical factors with PK measurements to quantify MPA exposure.

METHODS

We performed 12-hour pharmacokinetic analysis on 60 adult lung transplant recipients maintained on MPA for immunosuppression. We genotyped a SLCO1B3 polymorphisms previously associated MPA metabolism and collected relevant clinical data. We calculated area under the curve (AUC0-12) and performed univariate linear regression analysis to evaluate its association with genetic, clinical, and pharmacokinetic variables. We performed lasso regression analysis to create final AUC estimation tools.

RESULTS

PK-only measurements obtained 2, 3, and 8 hours after MPA administration (C2, C3, and C8) were strongly associated with MPA AUC0-12 (R267%, 67% and 68% respectively). Clinical and genetic factors associated with MPA AUC0-12 included the MPA dose (p = 0.001), transplant diagnosis (p = 0.015), SLCO1B3 genotype (p = 0.049), and body surface area (p = 0.050). The best integrated single-sampling strategy included C2 and achieved an R2 value of 80%. The best integrated limited-sampling strategy included C0, C0.25, and C2 and achieved an R2 value of 90%.

CONCLUSIONS

An integrated limited sampling strategy (LSS) for MPA allows increased accuracy in prediction of MPA AUC0-12 compared to PK-only modeling. Validation of this model will allow for clinically feasible MPA therapeutic drug monitoring and help advance precision management of MPA.

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.

Limited sampling strategy to predict mycophenolic acid area under the curve in pediatric patients with nephrotic syndrome: a retrospective cohort study

PURPOSE

Limited sampling strategy (LSS) is a precise and relatively convenient therapeutic drug monitoring method. We evaluated LSSs for mycophenolic acid (MPA) in children with nephrotic syndrome treated with mycophenolic mofetil (MMF) and validated the LSSs using two different approaches.

METHODS

We measured MPA plasma concentrations in 31 children using HPLC-UV method and received 37 MPA pharmacokinetic profiles (0-12 h). For six children, MPA profiles were estimated twice after two MMF doses. LSSs were developed using multilinear regression with STATISTICA and R software and validated using validation group and bootstrap method, respectively.

RESULTS

The best three time point equations included C₁, C₃, C₆ (good guess 83%, bias - 2.78%; 95% confidence interval (CI) - 9.85-0.46); C₁, C₂, C₆ (good guess 72%, bias 0.72%; 95% CI - 5.33-7.69); and C₁, C₂, C₄ (good guess 72%, bias 2.05%; 95% CI - 4.92-13.01) for STATISTICA software. For R software, the best equations consisted of C₁, C₃, C₆ (good guess 92%, bias - 2.69%; 95% CI - 27.18-33.75); C₀, C₁, C₃ (good guess 84%, bias - 2.11%; 95% CI - 24.19-22.29); and C₀, C₁, C₂ (good guess 84%, bias - 0.48%; 95% CI - 30.77-54.07). During validation, better results were obtained for R evaluations, i.e., bootstrap method.

CONCLUSIONS

The most useful equations included C₀, C₁, C₃ and C₀, C₁, C₂ time points; however, the most precise included C₁, C₃, C₆ time points because of MPA enterohepatic recirculation. Better results were obtained for bootstrap validation due to greater number of patients. Validated LSS should be used only in the population for which it was developed. As there is growing evidence that underexposure of MPA is associated with insufficient treatment response, we recommend the introduction of therapeutic drug monitoring for MPA in children with nephrotic syndrome.

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.

Immunosuppression in lung transplantation

Lung transplantation can be a life-saving procedure for those with end-stage lung diseases. Unfortunately, long term graft and patient survival are limited by both acute and chronic allograft rejection, with a median survival of just over 6 years. Immunosuppressive regimens are employed to reduce the rate of rejection, and while protocols vary from center to center, conventional maintenance therapy consists of triple drug therapy with a calcineurin inhibitor (cyclosporine or tacrolimus), antiproliferative agents [azathioprine (AZA), mycophenolate, sirolimus (srl), everolimus (evl)], and corticosteroids (CS). Roughly 50% of lung transplant centers also utilize induction therapy, with polyclonal antibody preparations [equine or rabbit anti-thymocyte globulin (ATG)], interleukin 2 receptor antagonists (IL2RAs) (daclizumab or basiliximab), or alemtuzumab. This review summarizes these agents and the data surrounding their use in lung transplantation, as well as additional common and novel therapies in lung transplantation. Despite the progression of the management of lung transplant recipients, they continue to be at high risk of treatment-related complications, and poor graft and patient survival. Randomized clinical trials are needed to allow for the development of better agents, regimens and techniques to address above mentioned issues and reduce morbidity and mortality among lung transplant recipients.

Prediction of area under the cyclosporine concentration versus time curve in children undergoing hematopoietic stem cell transplantation

This prospective study aimed to validate a previously developed first-dose limited sampling strategy (LSS) to predict the area under the cyclosporine concentration-versus-time curve (AUC) and to develop and then validate an LSS to predict cyclosporine AUC at steady state. This two-center Canadian study included children (ages .4 to 17.2 years) undergoing myeloablative allogeneic hematopoietic stem cell transplantation receiving cyclosporine for acute graft-versus-host disease prophylaxis. There were three cohorts, each incorporating 24 AUC determinations: first-dose LSS validation, steady-state LSS development, and steady-state LSS validation. Patients contributing data to either of the development cohorts were excluded from the corresponding validation group. Cyclosporine was given every 12 hours as a 2-hour infusion. Cyclosporine AUC was determined after administration of the first cyclosporine dose (8 samples) and then once weekly (9 samples) until engraftment. Steady-state LSSs were developed using stepwise multiple linear regression. An LSS was considered to provide an acceptable estimate of AUC if the lower limit of the 95% confidence limit (CL) of the intraclass coefficient was .8 or higher and both bias and precision were 15% or less. Fifty-three children age .4 to 18 years participated. Cyclosporine concentrations drawn up to 4 hours from the start of the infusion correlated most strongly with AUC. The previously developed first-dose LSSs and three steady-state LSSs met criteria for acceptability. The intraclass coefficients of the three-point first-dose LSS validation cohort, three-point steady-state LSS development cohort, and three-point steady-state LSS validation cohort were .974 (95% CL: .941 to .988), .984 (95% CL: .965 to .993), and .993 (95% CL: .984 to .997), respectively. The three-point first-dose (2, 6, and 8 hours) and steady-state (2, 2.5, and 8 hours) LSSs are valid measures of cyclosporine AUC after intravenous administration over 2 hours. Their use in a prospective evaluation of the relationship between cyclosporine AUC and hematopoietic stem cell transplantation clinical outcomes in children is suggested.

Estimation of Abbreviated Cyclosporine A Area under the Concentration-Time Curve in Allogenic Stem Cell Transplantation after Oral Administration

Measurements of Cyclosporine (CsA) systemic exposure permit its dose adjustment in allogenic stem cell transplantation recipients to prevent graft-versus-host disease. CsA LSSs were developed and validated from 60 ASCT patients via multiple linear regressions. All whole-blood samples were analyzed by fluorescence polarization immunoassay (FPIA-Axym). The 10 models that have used CsA concentrations at a single time point did not have a good fit with AUC_0–12 (R² < 0.90). C₂ and C₄ were the time points that correlated best with AUC_0–12 h, R² were respectively 0.848, and 0.897. The LSS equation with the best predictive performance (bias, precision and number of samples) utilized three sampling concentrations was AUC_0–12 h = 0.607 + 1.569 × C_0.5 + 2.098 × C₂ + 3.603 × C₄ (R² = 0.943). Optimal LSSs equations which limited to those utilizing three timed concentrations taken within 4 hours post-dose developed from ASCT recipient's patients yielded a low bias <5% ranged from 1.27% to 2.68% and good precision <15% ranged from 9.60% and 11.02%. We propose an LSS model with equation AUC_0–12 h = 0.82 + 2.766 × C₂ + 3.409 × C₄ for a practical reason. Bias and precision for this model are respectively 2.68% and 11.02%.

Mycophenolate monitoring in liver, thoracic, pancreas, and small bowel transplantation: a consensus report

Assessing the value of mycophenolic acid (MPA) monitoring outside renal transplantation is hindered by the absence of any trial comparing fixed-dose and concentration-controlled therapy. However, in liver and thoracic transplantation particularly, clinical trials, observational studies with comparison groups, and case series have described MPA efficacy, exposure/efficacy relationships, pharmacokinetic variability, and clinical outcomes relating to plasma MPA concentrations. On the basis of this evidence, this report identifies MPA as an immunosuppressant for which the combination of variable disposition, efficacy, and adverse effects contributes to interindividual differences seemingly in excess of those optimal for a fixed-dosage mycophenolate regimen. Combined with experiences of MPA monitoring in other transplant indications, the data have been rationalized to define circumstances in which measurement of MPA concentrations can contribute to improved management of mycophenolate therapy in nonrenal transplant recipients.

Pharmacokinetic optimization of immunosuppressive therapy in thoracic transplantation: part II

Part I of this article, which appeared in the previous issue of the Journal, reviewed calcineurin inhibitors--ciclosporin and tacrolimus. In part II, we review the pharmacokinetics and therapeutic drug monitoring of mycophenolate and mammalian target of rapamycin inhibitors--sirolimus and everolimus--in thoracic transplantation, and we provide an overall discussion and suggest various areas for future study.

Limited sampling strategies for mycophenolic acid in solid organ transplantation: a systematic review

BACKGROUND

Mycophenolic acid (MPA) is the active metabolite of mycophenolate mofetil, a widely used immunosuppressant. Numerous studies have developed limited sampling strategies (LSSs) to predict MPA AUC in solid organ transplant recipients.

OBJECTIVES

To systematically review and assess quality of literature pertaining to MPA LSSs, evaluate clinical implications and provide suggestions for future research.

METHODS

Literature searches of MEDLINE (1966 - May 2009) and EMBASE (1980 - May 2009) for English articles in solid organ transplantation, along with manual review of article references were conducted. Included articles were categorized according to criteria adapted from levels of evidence of the US Preventative Services Task Force.

RESULTS

Of a total of 29 studies identified, 20 were in kidney, 4 in heart, 4 in liver and 1 in lung transplantation and 7 were in pediatrics. A total of 14 studies were deemed to be Level I evidence studies, 3 were Level II-1, 1 was Level II-2 and 11 were Level III.

CONCLUSIONS

Although various LSSs that are well correlated to MPA AUC while being relatively unbiased and precise to predict MPA AUC have been developed, further research is needed to determine validity of these LSSs in a variety of patient populations and to determine if these LSSs improve patient outcomes.

Limited sampling strategies for predicting area under the concentration-time curve of mycophenolic acid in islet transplant recipients

BACKGROUND

Mycophenolate mofetil is widely used in islet transplant recipients and its active metabolite, mycophenolic acid (MPA), exhibits wide pharmacokinetic variability. However, to our knowledge, no limited sampling strategy (LSS) exists for monitoring MPA in this subpopulation.

OBJECTIVE

To define optimal LSSs for MPA monitoring and to test their predictive performance in islet transplant recipients.

METHODS

After written informed consent was obtained and upon administration of a steady-state morning mycophenolate mofetil dose, blood samples were collected at 0, 0.3, 0.6, 1, 1.5, 2, 3, 4, 6, 8, 10, and 12 hours from 16 stable islet transplant recipients. MPA concentrations were measured by a validated high-performance liquid chromatography method with ultraviolet detection and pharmacokinetic parameters analyzed by noncompartmental modeling. All 16 patients' profiles were used to develop the LSSs via multiple regression analysis. Potential LSSs were restricted to ones having R(2) 0.90 or greater and 3 or fewer time points within the first 4 hours postdose. Resulting equations were validated for their predictive performance using the jackknife method, with acceptable criteria for bias and precision preset to within +/-15%. In addition, 14 published LSSs (in the renal transplant population) were tested in our islet transplant patients.

RESULTS

Five LSSs met preset criteria and had conventional sampling times: AUC = 1.783 + 1.248C1 + 0.888C2 + 8.027C4 (R2 = 0.98, bias = -3.09%, precision = 9.53%) AUC = 2.778 + 1.413C1 + 0.963C3 + 7.511C4 (R2 = 0.97, bias = -3.22%, precision = 11.02%) AUC = 1.448 + 1.239C1 + 0.271C1.5 + 9.108 C4 (R2 = 0.96, bias = -1.90%, precision = 11.46) AUC = 1.410 - 0.259C0 + 1.443C1 + 9.622C4 (R2 = 0.96, bias = -2.68%, precision = 11.53%) AUC = 1.547 + 1.417C1 + 9.448C4 (R2 = 0.96, bias = -2.46%, precision = 11.14%) where AUC = area under the concentration-time curve. None of the other published LSSs in the renal transplant population met the preset criteria for bias and precision.

CONCLUSIONS

To our knowledge, these are the first precise and accurate LSSs for predicting MPA AUC developed specifically for islet transplant recipients. The LSS that we recommend is the one utilizing 2 concentrations: AUC = 1.547 + 1.417C1 + 9.448C4. This equation is convenient and clinically feasible. Other islet transplant centers may wish to validate our equation in their population or use our template as a guide to develop accurate and precise LSSs specific to their patient population.

Pharmacokinetic optimization of immunosuppressive therapy in thoracic transplantation: part I

Although immunosuppressive treatments and therapeutic drug monitoring (TDM) have significantly contributed to the increased success of thoracic transplantation, there is currently no consensus on the best immunosuppressive strategies. Maintenance therapy typically consists of a triple-drug regimen including corticosteroids, a calcineurin inhibitor (ciclosporin or tacrolimus) and either a purine synthesis antagonist (mycophenolate mofetil or azathioprine) or a mammalian target of rapamycin inhibitor (sirolimus or everolimus). The incidence of acute and chronic rejection and of mortality after thoracic transplantation is still high compared with other types of solid organ transplantation. The high allogenicity and immunogenicity of the lungs justify the use of higher doses of immunosuppressants, putting lung transplant recipients at a higher risk of drug-induced toxicities. All immunosuppressants are characterized by large intra- and interindividual variability of their pharmacokinetics and by a narrow therapeutic index. It is essential to know their pharmacokinetic properties and to use them for treatment individualization through TDM in order to improve the treatment outcome. Unlike the kidneys and the liver, the heart and the lungs are not directly involved in drug metabolism and elimination, which may be the cause of pharmacokinetic differences between patients from all of these transplant groups. TDM is mandatory for most immunosuppressants and has become an integral part of immunosuppressive drug therapy. It is usually based on trough concentration (C(0)) monitoring, but other TDM tools include the area under the concentration-time curve (AUC) over the (12-hour) dosage interval or the AUC over the first 4 hours post-dose, as well as other single concentration-time points such as the concentration at 2 hours. Given the peculiarities of thoracic transplantation, a review of the pharmacokinetics and TDM of the main immunosuppressants used in thoracic transplantation is presented in this article. Even more so than in other solid organ transplant populations, their pharmacokinetics are characterized by wide intra- and interindividual variability in thoracic transplant recipients. The pharmacokinetics of ciclosporin in heart and lung transplant recipients have been explored in a number of studies, but less is known about the pharmacokinetics of mycophenolate mofetil and tacrolimus in these populations, and there are hardly any studies on the pharmacokinetics of sirolimus and everolimus. Given the increased use of these molecules in thoracic transplant recipients, their pharmacokinetics deserve to be explored in depth. There are very few data, some of which are conflicting, on the practices and outcomes of TDM of immunosuppressants after thoracic transplantation. The development of sophisticated TDM tools dedicated to thoracic transplantation are awaited in order to accurately evaluate the patients' exposure to drugs in general and, in particular, to immunosuppressants. Finally, large cohort TDM studies need to be conducted in thoracic transplant patients in order to identify the most predictive exposure indices and their target values, and to validate the clinical usefulness of improved TDM in these conditions. In part I of the article, we review the pharmacokinetics and TDM of calcineurin inhibitors. In part II, we will review the pharmacokinetics and TDM of mycophenolate and mammalian target of rapamycin inhibitors, and provide an overall discussion along with perspectives.

Performance of limited sampling strategies for predicting mycophenolic acid area under the curve in thoracic transplant recipients

BACKGROUND AND METHODS

Eight limited sampling strategies (LSSs) for estimating mycophenolic acid area under the concentration-time curve (4 developed from lung transplant recipients at our center, 4 developed for heart transplant recipients from other research groups) were evaluated in 27 heart or heart-kidney transplant patients.

RESULTS

The LSSs from our lung transplant patients performed well when applied to the heart transplant population, with percent bias and percent precision within the acceptable limit of +/-15%.

CONCLUSIONS

The LSSs developed at our center are robust enough to be applied to both lung and heart transplant populations. Application of LSSs from other research groups yielded less optimal results, reinforcing the need to re-establish or re-validate LSSs for each specific center.