Pharmacokinetics of mycophenolic acid and estimation of exposure using multiple linear regression equations in Chinese renal allograft recipients

Influence of Calcineurin Inhibitors and Genetic Polymorphism of Transporters on Enterohepatic Circulation and Exposure of Mycophenolic Acid in Chinese Adult Renal Allograft Recipients

There is significant enterohepatic circulation (EHC) during the disposition of mycophenolic acid (MPA). The aim of this study was to elucidate factors influencing the EHC of MPA in Chinese adult renal allograft recipients. After 2 weeks of therapy with mycophenolate mofetil or enteric-coated mycophenolate sodium, blood samples were collected from 125 patients at 0 to 12 hours post-administration and MPA concentrations were determined. The influence of calcineurin inhibitors (CNIs) and genetic polymorphisms on MPA exposure and EHC was studied. The Shapley additive explanations method was used to estimate the impact of various factors on the area under the plasma drug concentration-time curve (AUC_0-12h ) for MPA. An extreme gradient boosting (XGboost) machine learning-based model was established to predict AUC_0-12h . Results showed that the dose-normalized AUC_6-12h (dn-AUC_6-12h ) of MPA was significantly lower in patients co-administered with cyclosporine (CsA) than in patients co-administered with tacrolimus (TAC) (P < .05). For patients co-administered with TAC, patients with ABCC2 C-24T CC or SLCO1B1 T521C TT genotypes had significantly higher values of dn-AUC_6-12h (P < .05). Patients with SLCO1B3 334T/699G alleles had significantly lower dn-AUC_6-12h values than homozygotes (P < .05). By introducing body weight, age, and EHC-related factors, including co-administered CNIs and genetic polymorphism of drug transporters, as covariates in the XGboost machine learning model, the prediction performance of AUC_0-12h for MPA in Chinese adult renal allograft recipients can be improved.

Estimation of Mycophenolic Acid Exposure in Chinese Renal Transplant Patients by a Joint Deep Learning Model

BACKGROUND

To predict mycophenolic acid (MPA) exposure in renal transplant recipients using a deep learning model based on a convolutional neural network with bilateral long short-term memory and attention methods.

METHODS

A total of 172 Chinese renal transplant patients were enrolled in this study. The patients were divided into a training group (n = 138, Ruijin Hospital) and a validation group (n = 34, Zhongshan Hospital). Fourteen days after renal transplantation, rich blood samples were collected 0-12 hours after MPA administration. The plasma concentration of total MPA was measured using an enzyme-multiplied immunoassay technique. A limited sampling strategy based on a convolutional neural network-long short-term memory with attention (CALS) model for the prediction of the area under the concentration curve (AUC) of MPA was established. The established model was verified using the data from the validation group. The model performance was compared with that obtained from multiple linear regression (MLR) and maximum a posteriori (MAP) methods.

RESULTS

The MPA AUC 0-12 of the training and validation groups was 54.28 ± 18.42 and 41.25 ± 14.53 µg·ml -1 ·h, respectively. MPA plasma concentration after 2 (C 2 ), 6 (C 6 ), and 8 (C 8 ) hours of administration was the most significant factor for MPA AUC 0-12 . The predictive performance of AUC 0-12 estimated using the CALS model of the validation group was better than the MLR and MAP methods in previous studies (r 2 = 0.71, mean prediction error = 4.79, and mean absolute prediction error = 14.60).

CONCLUSIONS

The CALS model established in this study was reliable for predicting MPA AUC 0-12 in Chinese renal transplant patients administered mycophenolate mofetil and enteric-coated mycophenolic acid sodium and may have good generalization ability for application in other data sets.

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 for Estimation of Mycophenolic Acid Exposure in Adult Chinese Heart Transplant Recipients

Background: With the increasing use of mycophenolic acid (MPA) formulations in organ transplantation, the need for personalized immunosuppressive therapy has become well recognized based on therapeutic drug monitoring (TDM) for avoidance of drug-related toxicity while maintaining efficacy. Few studies have assessed area under the 12 h concentration-time curve of MPA (MPA-AUC_0–12h) in heart transplant recipients who received mycophenolate mofetil (MMF) dispersible tablets (MMFdt). The aim of the study was to investigate the pharmacokinetics (PK) of MMFdt combined with tacrolimus and further to develop a practical method for estimation of MPA-AUC_0–12h using a limited sampling strategy (LSS).

Methods: A prospective study in a single center was performed in patients who continuously administrated with MMFdt or MMF capsule (MMFc) for at least 7 days after cardiac transplantation from 2018 to 2020. A total of 48 Chinese adult heart transplant recipients were enrolled. Blood samples were collected before and 0.5, 1, 1.5, 2, 4, 6, 8, 10 and 12 h after MMF administration. The validated high-performance liquid chromatography combined with tandem mass spectrometry method was used to measure MPA concentrations. Non-compartmental pharmacokinetic (PK) analysis was applied to calculate the data obtained from individual recipients by WinNonlin. LSS models were developed for MPA-AUC_0–12h prediction with multivariate stepwise regression analysis.

Results: A large inter-individual variability was observed in AUC_0–12h, T_max, C_max, MRT_0–12h, t_1/2 and CL/F after multiple dosing of MMFdt. However, no significant differences were observed between main PK parameters of MMFdt and MMFc. The best estimation of MPA-AUC_0–12h was achieved with four points: MPA-AUC_0–12h = 8.424 + 0.781 × C_0.5 + 1.263 × C₂ + 1.660 × C₄ + 3.022 × C₆ (R² = 0.844). The mean prediction error (MPE) and mean absolute prediction error (MAPE) of MPA-AUC_0–12h were 2.09 ± 14.05% and 11.17 ± 8.52%, respectively. Both internal and external validations showed good applicability for four-point LSS equation.

Conclusion: The results provide strong evidence for the use of LSS model other than a single time-point concentration of MPA when performing TDM. A four-point LSS equation using the concentrations at 0.5, 2, 4, 6 h is recommended to estimate MPA-AUC_0–12h during early period after transplantation in Chinese adult heart transplant recipients receiving MMFdt or MMFc. However, proper internal and external validations with more patients should be conducted in the future.

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.

Assessment of pharmacokinetic mycophenolic acid clearance models using Monte Carlo numerical analysis

Previously, we performed population pharmacokinetic analysis and indicated age, mycophenolate mofetil (MMF)/mycophenolic acid (MPA) daily dose, and presence of nifedipine in patient therapy as significant predictors of MPA apparent clearance (CL/F) variability. This study aimed to determine the reliability of previously published population pharmacokinetic models derived from similar studies. Furthermore, this study investigated correspondence between chosen population models from the literature.By means of the Monte Carlo simulation method, pharmacokinetic models from different studies are simulated and analysed in the range of standard deviations of measured system parameters as well as the range of observed model parameters taken from the comparison studies.The 1000 numerical simulations were performed for every analysed model in order to calculate the most possible MPA CL/F values according to the expected values from the performed experiment. Fitting our results with other models showed how the presence of nifedipine makes difference in MPA CL/F values.By testing the data from selected studies into our model, a similar range of expected CL/F values was obtained, which may confirm the validity of our model. The results of our population pharmacokinetic study are partially applicable in models by other researchers.

Effect of Protein Binding on Exposure of Unbound and Total Mycophenolic Acid: A Population Pharmacokinetic Analysis in Chinese Adult Kidney Transplant Recipients

OBJECTIVES

The population pharmacokinetic (popPK) characteristics of total mycophenolic acid (tMPA) have been investigated in various ethnic populations. However, investigations of popPK of unbound MPA (uMPA) are few. Thus, a popPK analysis was performed to: (1) characterize the PK of uMPA and tMPA and its 7-O-mycophenolic acid glucuronide (MPAG) metabolite in kidney transplant patients cotreated with cyclosporine (CsA), and (2) identify the clinically significant covariates that explain variability in the dose-exposure relationship.

METHODS

A total of 740 uMPA, 741 tMPA, and 734 total MPAG (tMPAG) concentration-time data from 58 Chinese kidney transplant patients receiving MPA in combination with CsA were analyzed using NONMEM® software with the stochastic approximation expectation maximization (SAEM) followed by the important sampling (IMP) method. The influence of covariates was tested using a stepwise procedure.

RESULTS

The PK of uMPA and unbound MPAG (uMPAG) were characterized by a two- and one-compartment model with first-order elimination, respectively. A linear protein binding model was used to link uMPA and tMPA. Apparent clearance (CL/F) and central volume of distribution (VC/F) of uMPA (CLuMPA/F and VCuMPA/F, respectively) and protein binding rate constant (k B) were estimated to be 851 L/h [relative standard error (RSE), 7.1%], 718 L (18.5%) and 53.4/h (2.3%), respectively. For uMPAG, the population values (RSE) of CL/F (CLuMPAG) and VC/F (VCuMPAG/F) were 5.71 L/h (4.4%) and 29.9 L (7.7%), respectively. Between-subject variability (BSVs) on CLuMPA/F, VCuMPA/F, CLuMPAG/F, and VCuMPAG/F were 51.0, 80.0, 31.8 and 48.4%, respectively, whereas residual unexplained variability (RUVs) for uMPA, tMPA, and uMPAG were 47.0, 45.9, and 22.0%, respectively. Significant relationships were found between k B and serum albumin (ALB) and between CLuMPAG/F and glomerular filtration rate (GFR). Additionally, model-based simulation showed that changes in ALB concentrations substantially affected tMPA but not uMPA exposure.

CONCLUSIONS

The established model adequately described the popPK characteristics of the uMPA, tMPA, and MPAG. The estimated CLuMPA/F and unbound fraction of MPA (FUMPA) in Chinese kidney transplant recipients cotreated with CsA were comparable to those published previously in Caucasians. We recommend monitoring uMPA instead of tMPA to optimize mycophenolate mofetil (MMF) dosing for patients with lower ALB levels.

Clinical pharmacy service practice in a Chinese tertiary hospital

Clinical pharmacy service is focused on the rationality and safety of medication therapy. Clinical pharmacists play an important role in designing therapeutic regimen, preventing medication errors, reducing the incidence of adverse drug reaction, and saving medical costs. Although clinical pharmacy service in China is in its early stage, its development is rapid. In this manuscript, the working model of clinical pharmacists in a Chinese tertiary hospital is introduced, including ward rounds, consultation, stewardship of antimicrobial therapy, drug adverse reaction monitoring, therapeutic drug monitoring, clinical pharmacokinetics and pharmacogenetics, and training system. With the efforts of clinical pharmacists, there will be a significant increase in the optimization of medication therapy and a notable reduction in preventable adverse drug events as well as health-care cost in China.

Variability of mycophenolic acid elimination in the renal transplant recipients – population pharmacokinetic approach

The aim of this study was to develop a population pharmacokinetic (PK) model for clearance of mycophenolic acid (MPA) in adult renal transplant recipients, to quantify the PK parameters and the influence of covariates on the MPA pharmacokinetic parameters. Parameters associated with plasma concentrations of MPA at steady-state were analyzed in 70 renal transplant recipients (mean age 42.97 years; mean total body weight 75.33 kg) using nonlinear mixed-effect modeling (NONMEM). Characteristics of patients screened for influence on the pharmacokinetic parameters were gender, age, body weight, time after transplantation, whether the patient was diagnosed as having diabetes mellitus, organ source (living or deceased donor), biochemical parameters and co-therapy (tacrolimus, cyclosporine, prednisolone, omeprazole, bisoprolol, carvedilol, nifedipine). A validation set of 25 renal transplant recipients was used to estimate the predictive performance of population pharmacokinetic model. Typical mean value of MPA oral clearance, estimated by base model (without covariates) was 0.741 L h(-1). During population modeling, the full model showed that clearance of the MPA was significantly influenced by age, total daily dose of MPA, creatinine clearance, albumin level, status and gender of a donor, and the nifedipine and tacrolimus co-therapy. In the final model, clearance of MPA was reported to be significantly influenced by age, total daily dose of MPA and thenifedipine co-therapy. The derived model describes adequately MPA clearance in terms of characteristics of our patients, offering basis for individual pharmacotherapy approach.

Mycophenolic acid AUC in Thai kidney transplant recipients receiving low dose mycophenolate and its association with UGT2B7 polymorphisms

Background

Despite use of a lower mycophenolate dose in Thai kidney transplant patients, acceptable graft and patient outcomes can be achieved. We therefore examined the pharmacokinetics of mycophenolic acid (MPA) by area under the curve (AUC) and investigated genetic contribution in mycophenolate metabolism in this population.

Methods

Kidney transplant recipients with stable graft function who were receiving mycophenolate mofetil 1,000 mg/d in combination with either cyclosporine or tacrolimus, and prednisolone were studied. The MPA concentration was measured by fluorescence polarization immunoassay (FPIA), at predose and 1, 1.5, 2, 4, 6, 8, 10, and 12 hours after dosing. Genetic polymorphisms in UGT1A8, UGT1A9, and UGT2B7 were examined by denaturing high-performance liquid chromatography (DHPLC)-based single-base extension (SBE) analysis.

Results

A total 138 patients were included in study. The mean AUC was 39.49 mg-h/L (28.39–89.58 mg-h/L), which was in the therapeutic range. The correlation between the predose MPA concentration and AUC was poor. The mean AUC in the tacrolimus group was higher than that in the cyclosporine group. Polymorphisms in UGT2B7 showed significant association with AUC.

Conclusion

Most of our patients with reduced mycophenolate dose had the AUC within the therapeutic range. Genetic polymorphisms in UGT2B7 may play a role in MPA metabolism in Thai kidney transplant patients.

Development and validation of limited sampling strategies for tacrolimus and mycophenolate in steroid-free renal transplant regimens

PURPOSE

1) To develop and validate limited sampling strategies (LSSs) for tacrolimus (TAC) and mycophenolic acid (MPA) in renal transplant recipients not receiving corticosteroids; and 2) to evaluate predictive performance of published LSSs (for steroid-based regimens) in a steroid-free population.

METHODS

On administration of steady-state morning TAC and mycophenolate mofetil doses, 12-hour serial blood samples from 28 stable renal transplant recipients were collected and measured by validated high-performance liquid chromatography methods and area under the curve (AUC) by trapezoidal rule. TAC LSSs were developed and validated by multiple regression analysis by a two-group method (index n = 18; validation n = 10) and MPA LSSs by the jackknife method (n = 28). Potential LSSs were those with r ≥ .8 (TAC) or r ≥ 0.7 (MPA) and < 3 time points within 2 hours (TAC) or 4 hours (MPA) postdose. Predictive performance was calculated and other published TAC and MPA LSSs tested using preset criteria for bias and precision of within ± 15%.

RESULTS

For TAC, three three-concentration, one two-concentration, and one one-concentration model met preset criteria. The best equations were: TAC AUC = 10.338 + 7.739C0 + 3.589C2 (r = 0.956, bias = -3.4%, precision = 4.7%) and TAC AUC = 29.479 + 5.016C2 (r = 0.862, bias = 3.2%, precision = 9.7%). For MPA, only one model was identified: MPA AUC = 9.328 + 1.311C1 + 1.455C2 + 2.901C4 (r = 0.838, bias = -3.8%, precision = 14.9%). One published TAC (and no MPA) LSS in renal transplant recipients on steroid-based regimens met criteria.

CONCLUSIONS

To the authors' knowledge, these LSSs are the first to be developed and validated in steroid-free renal transplant recipients and can be used to accurately predict TAC and MPA AUCs for steroid-free regimens. Because the commonly used MPA LSS is based on a steroid regimen and not predictive for steroid-free patients, the newly derived MPA LSS is being applied at the authors' institution. Other renal transplant centers may also wish to validate this equation in their own patients.

Early phase limited sampling strategy characterizing tacrolimus and mycophenolic acid pharmacokinetics adapted to the maintenance phase of renal transplant patients

The aim of this study was to examine whether a limited sampling strategy (LSS) to allow the simultaneous estimation of the area under the concentration-time curves (AUCs) of tacrolimus and mycophenolic acid (MPA) calculated in the early stage after renal transplantation could be applied to maintenance phase pharmacokinetics. Seventy Japanese patients were enrolled. One year after transplantation, samples were collected just before and 1, 2, 3, 4, 6, 9, and 12 hours after tacrolimus and mycophenolate mofetil administration at 9:00 am and at 9:00 pm. The prediction formulas on day 28 (tacrolimus AUC 0-12 = 7.04 x C 0h + 1.71 x C 2h + 3.23 x C 4h + 15.19 and 2.25 x C 2h + 1.92 x C 4h + 7.27 x C 9h + 6.61, and MPA AUC 0-12 = 0.26 x C 0h + 2.06 x C 2h + 3.82 x C 4h + 20.38 and 1.77 x C 2h + 2.34 x C 4h + 4.76 x C 9h + 15.94) were applied to pharmacokinetic data obtained at 1 year. Three error indices [percent mean prediction error (ME), % mean absolute error, and percent root mean squared prediction error (RMSE)] were used to evaluate the predictive bias, accuracy, and precision. The predicted AUC 0-12 of tacrolimus and MPA at 3 time points, C 2h-C 4h-C 9h, showed higher correlation with the measured AUC 0-12 of tacrolimus and MPA (r2 = 0.817 and 0.789, respectively) in comparison with those at C 0h-C 2h-C 4h. The values for the prediction formulas for tacrolimus AUC at 1 year using the C 2h-C 4h-C 9h combination yielded less than 5% for %ME and 15% for %RMSE. The %ME and %RMSE values of the prediction formulas for tacrolimus AUC using the C 0h-C 2h-C 4h combination were 6.3% and 15.9%, respectively. The %ME and %RMSE values of the prediction formulas for MPA AUC at 1 year using the C 0h-C 2h-C 4h combination were 5.9% and 25.8%, respectively, and those for the C 2h-C 4h-C 9h combination were 4.9% and 21.2%, respectively. AUC 6-12/AUC 0-12 of MPA 1 year after transplantation was significantly lower than 28 days after transplantation. An LSS using C 2h-C 4h-C 9h seems to be applicable for predicting the AUC of tacrolimus and MPA at either posttransplantation stage. The enterohepatic circulation of MPA was significantly reduced 1 year after transplantation. Therefore, 1 year after transplantation, the estimation of the AUC 0-12 of MPA for the C 0h-C 2h-C 4h equations was imprecise. It is important that the LSS includes C 9h because it contains information on the secondary plasma peak of MPA.

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.

Limited sampling strategy for simultaneous estimation of the area under the concentration-time curve of tacrolimus and mycophenolic acid in adult renal transplant recipients

The aim of this study was to develop a limited sampling strategy to allow the simultaneous estimation of the area under the concentration-time curves (AUCs) of tacrolimus and mycophenolic acid (MPA), the active metabolite of the prodrug mycophenolate mofetil, using a small number of samples from patients undergoing renal transplantation. Fifty Japanese patients were enrolled. On day 28 after transplantation, samples were collected just before and 1, 2, 3, 4, 6, 9, and 12 hours after tacrolimus and mycophenolate mofetil administration at 9:00 am and 9:00 pm. The full pharmacokinetic profiles obtained from these timed concentration data were used to choose the best sampling times. Three error indices (percent mean error, percent mean absolute error, and percent relative mean square error) were used to evaluate the predictive bias, accuracy, and precision. The predicted AUC0-12 of MPA calculated at the three time points of C2h-C4h-C9h best approximated the actual AUC0-12 of MPA (r = 0.877), and the AUC0-12 of tacrolimus calculated at the same time points predicted a good correlation with the actual AUC (r = 0.928). When the three sampling times of trough level (C0h) and two other points within 4 hours after administration were used, the three points of C0h-C2h-C4h were the best points for estimation of the AUC0-12 tacrolimus and MPA (AUC0-12 = 7.04.C0 + 1.71.C2 + 3.23.C4 + 15.19, r = 0.799, P < 0.001 and AUC0-12 = 0.26.C0 + 2.06.C2 + 3.82.C4 + 20.38, r = 0.693, P < 0.001, respectively). The percent mean error, percent mean absolute error, and percent relative mean square error of the prediction formula using the three time points of C0h-C2h-C4h were -0.3%, 8.8%, and 13.5% for tacrolimus and 2.9%, 17.1%, and 21.5% for MPA, respectively. A limited sampling strategy using C2h-C4h-C9h provides the most reliable and accurate simultaneous estimation of the AUC0-12 of tacrolimus and MPA in patients undergoing renal transplantation. In addition, a limited sampling strategy using C0h-C2h-C4h is recommended for the simultaneous estimation of the AUC0-12 of tacrolimus and MPA when focused on samples collected within 4 hours after administration for clinical expediency.