Dataset Information

Estimation of Mycophenolic Acid Exposure in Heart Transplant Recipients by Population Pharmacokinetic and Limited Sampling Strategies.

ABSTRACT: Purpose: The aim of this study is i) to establish a strategy to estimate the area under the curve of the dosing interval (AUC_0-12h) of mycophenolic acid (MPA) in the heart transplant recipients and ii) to find the covariates that significantly affect the pharmacokinetics of MPA exposure. Methods: This single-center, prospective, open-label, observational study was conducted in 91 adult heart transplant recipients orally taking mycophenolate mofetil dispersible tablets. Samples collected intensively and sparsely were analyzed by the enzyme-multiplied immunoassay technique, and all the data were used in PPK modeling. Potential covariates were tested stepwise. The goodness-of-fit plots, the normalized prediction distribution error, and prediction-corrected visual predictive check were used for model evaluation. Optimal sampling times by ED-optimal strategy and multilinear regression (MLR) were analyzed based on the simulated data by the final PPK model. Moreover, using intensive data from 14 patients, the accuracy of AUC_0-12h estimation was evaluated by Passing-Bablok regression analysis and Bland-Alman plots for both the PPK model and MLR equation. Results: A two-compartment model with first-order absorption and elimination with a lag time was chosen as the structure model. Co-medication of proton pump inhibitors (PPIs), estimated glomerular filtration rate (eGFR), and albumin (ALB) were found to significantly affect bioavailability (F), clearance of central compartment (CL/F), and the distribution volume of the central compartment (V₂/F), respectively. Co-medication of PPIs decreased F by 27.6%. When eGFR decreased by 30 ml/min/1.73 m², CL/F decreased by 23.7%. However, the impact of ALB on V₂/F was limited to MPA exposure. The final model showed an adequate fitness of the data. The optimal sampling design was pre-dose and 1 and 4 h post-dose for pharmacokinetic estimation. The best-fit linear equation was finally established as follows: AUC_0-12h = 3.539 × C₀ + 0.288 × C_0.5 + 1.349 × C₁ + 6.773 × C_4.5. Conclusion: A PPK model was established with three covariates in heart transplant patients. Co-medication of PPIs and eGFR had a remarkable impact on AUC_0-12h of MPA. A linear equation was also concluded with four time points as an alternative way to estimate AUC_0-12h for MPA.

SUBMITTER: Wang X

PROVIDER: S-EPMC8640522 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description: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-AUC0-12h) 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-AUC0-12h 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-AUC0-12h prediction with multivariate stepwise regression analysis. Results: A large inter-individual variability was observed in AUC0-12h, Tmax, Cmax, MRT0-12h, t1/2 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-AUC0-12h was achieved with four points: MPA-AUC0-12h = 8.424 + 0.781 × C0.5 + 1.263 × C2 + 1.660 × C4 + 3.022 × C6 (R 2 = 0.844). The mean prediction error (MPE) and mean absolute prediction error (MAPE) of MPA-AUC0-12h 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-AUC0-12h 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.

Project description: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.

Project description:ObjectivesThe 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.MethodsA 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.ResultsThe 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.ConclusionsThe 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.

Project description:Mycophenolic acid (MPA), an immunosuppressive drug widely used in kidney transplantation, has been suggested to have anti-fibrotic effects. To analyze at a genomic level these effects, we prospectively studied a group of stable kidney transplant recipients (n=35) on cyclosporine (CyA) and azathioprine treatment. Twenty patients were converted from azathioprine to MPA (MPA group) and 15 patients continued on azathioprine (AZA group). RNA was extracted by peripheral blood mononuclear cells at baseline and 3 months thereafter. Genomic analysis, performed on 5 randomly-selected MPA patients, revealed that 17 genes discriminated the transcriptomic profile after conversion. Neutral endopeptidase (NEP), an enzyme degrading angiotensin-II, was the most significant up-regulated gene. NEP expression level was inversely correlated to proteinuria at baseline and after conversion. Immunohistochemistry on graft biopsy of 33 independent patients demonstrated higher glomerular and tubular NEP protein expression in CyA+MPA (n=13) compared to CyA+AZA (n=12) and CyA alone (n=8). Glomerular NEP levels were inversely correlated to proteinuria and glomerulosclerosis. Tubular NEP expression was inversely correlated to interstitial fibrosis. Incubation of proximal tubular cells with MPA led to a dose- and time-dependent increase of NEP gene expression. The direct influence of MPA on NEP expression may suggest a novel therapeutic effect of this drug. For microarray analysis, we studied 5 randomly selected patients included in the training group. Patients included in this group were, at the time of enrollment (T0), on standard maintenance immunosuppression with Cyclosporine (Neoral, Novartis, Basel, mean±SD of daily dose: 160.1±37.1mg), prednisone (5 mg daily) and Azathioprine (50 mg daily). Twenty patients, at T0, were switched from Azathioprine to EC-MPS (Myfortic, Novartis, Basel, 720 mg bid) for their need of allopurinol therapy (EC-MPS group). However, to avoid confounding factors, allopurinol treatment did not start until the end of our study (3 months). For the microarray analysis, we randomly selected 5 patients from the EC-MPS group. PBMC both at T0 and at T1 (3 months after the switching of the therapy) were immediately isolated from 20 ml of whole blood by Ficoll–Hypaque (Flow Laboratories, Irvine, UK) density gradient centrifugation. Total RNA was extracted by RNeasy mini kit (QIAGEN Inc., Valencia, CA) according the manufacturer’s instructions. Total RNA was processed and hybridized to the Affymetrix GeneChips Human Genome U133 Array Set HG-U133A (Affymetrix)(Affymetrix, Santa Clara, CA)

Project description:BackgroundThe optimal dose of mycophenolate mofetil (MMF) in renal transplant patients has been recommended to be decided on the basis of area under the concentration-time curve (AUC0-12) of mycophenolic acid (MPA). Although meta-analysis has revealed that postoperative day (POD) is an influencing factor in MPA pharmacokinetics, there are no reports regarding a limited sampling strategy (LSS) for MPA AUC in consideration of POD. The aim of this study was to construct of an LSS considering POD that appropriately expresses the MPA AUC following renal transplantation and evaluation of the usefulness.MethodsSerum concentration-time profiles (measured AUC0-12) comprising nine sampling points over 12 h were analyzed in 36 living-donor renal transplant recipients after MMF administration with concomitant once-daily prolonged-release tacrolimus. Two LSSs were developed by stepwise multiple regression analysis (Method A: not classified by PODs; Method B: classified by PODs into POD?<?31 and POD???31). Each LSS comprised four blood-sampling points within 6 h after MMF administration. Precision and reliability were verified by using root-mean-square error (RMSE), correlation coefficient (R2), and coefficient of determination (q2) by using leave-one-out cross-validation. The absolute values of the difference between measured and estimated AUCs (delta AUC) were compared for both estimating equations.ResultsOne-hundred samples obtained from 36 recipients for AUC0-12 comprised POD?<?31 (n?=?39) and POD???31 (n?=?61). Estimation of AUC0-12 by Method B resulted in better accuracy and reliability (Method A: RMSE?=?5.5, R2?=?0.85, q2?=?0.83; Method B: POD?<?31: RMSE?=?5.5, R2?=?0.86, q2?=?0.83; POD???31: RMSE?=?3.9, R2?=?0.92, q2?=?0.89) and significantly lower median delta AUC compared with that by Method A (delta AUC: 2.6 (0.0-11.6) v.s. 3.9 (0.1-18.1), p?=?0.032).ConclusionThese results suggest that LSS, classified as POD?<?31 or POD?>?31, would provide more accurate and reliable estimation of MPA AUC0-12 in Japanese living-donor renal transplant patients.

Dataset Information

Estimation of Mycophenolic Acid Exposure in Heart Transplant Recipients by Population Pharmacokinetic and Limited Sampling Strategies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets