Population Pharmacokinetics Study Of Mycophenolic Acid In Renal Transplant Patients And Individualized Therapy

Mycophenolic acid (MPA), the active immunosuppressant form of the pro-drug mycophenolate mofetil (MMF, Cellcept(?)), is widely used in the prevention of acute organ rejection. After oral administration, MMF undergoes rapid and complete hydrolysis to MPA in vivo. MPA is extensively metabolized by uridine diphosphate-glucuronosyltransferase (UGT) into the major inactive metabolite mycophenolate acid 7-O-glucuronide (MPAG) that is primarily excreted by the kidneys, and which also undergoes enterohepatic circulation (EHC) to be converted back to MPA. Considerable intra- and inter- patient variability in pharmacokinetics (PK) parameters has been observed in renal allograft recipients. Co-administrated with calcineruin inhibitors or antibiotics, renal functions and liver disease were reported to influence MPA PK. More and more clinical pharmacists and clinicians recommended performing MPA therapeutic drug monitoring and individualized therapy.First of all, an isocratic high performance liquid chromatographic assay with online postcolumn derivation was established for determining total and free concentration of MPA and its glucuronide MPAG in human plasma. Plasma samples were treated by ultra-filtration and protein precipitation for the determination of free and total analytes respectively. Kromasil C₈(150×4.6mm, 5μm) was used as the analytical column and maintained at 30℃. The mobile phase consisted of a mixture of methanol: 0.1% trifluoroacetic acid (55:45, v/v) pumped at a flow rate of 1.2 mL/min. Regarding to the postcolumn derivatization, another HPLC pump was added to deliver 0.2 mol/L NaOH at a flow rate of 0.2 mL/min. MPAG was determined by UV absorbance and detection wavelength was set at 295nm while MPA was measured by fluorescence detection withλ_ex 342 nm andλ_em 425 nm. The endogenous interference and commonly co-medicated drugs did not interfere with the analytes determination. Calibration curves of total and free MPA and MPAG were in the range of 0.1～40μg/mL and 10～250μg/mL, as well as 0.01～1.0μg/mL and 2.5～100μg/mL respectively. The precision of within-day and between-day was less than 10%. The established method can be used to determine the concentrations of total and free MPA and MPAG in human plasma and it can also be applied to the PK research and routine therapeutic drug monitoring.Secondly, we investigated the PK profile of MPA and MPAG in 42 healthy Chinese volunteers, who took a single oral dose of 500 mg MMF. A PK model that describes EHC of the MPA based on physiological consideration was established using nonlinear mixed effect model (NONMEM). The influence of UGT1A9 polymorphisms on PK of MPA was also investigated. Based on physiological consideration, the chain compartment model included intestinal compartment, gallbladder compartment, central and peripheral compartment for MPA and central compartment for MPAG. The proposed model could well define the multiple peaks of MPA and MPAG due to EHC and the bootstrap validation results showed the model were stable and reliable. The typical population apparent clearance (CL/F) estimation of MPA was 0.153 L/hr/kg, which is close to the values reported in Caucasians. In terms of MPAG, typical population CL/F was 0.0283 L/hr/kg, 47% higher than that of Caucasians. The amount of MPA recycled into body estimated to be 23% of the total amount absorbed, which was also in consistent with previous reports. Polymorphisms of UGT1A9 did not show any effect on the PK of MPA.Thirdly, the PK characteristic of total and free MPA and MPAG in 12 adult Chinese de novo renal transplant recipients administrated with MMF (750 mg b.i.d.), cyclosporine and corticosteroids at the 10th day after operation was investigated. In addition, limited sampling strategies were developed to estimate the individual area under concentration-time curve (AUC) of total and free MPA. The pattern of total and free MPA and MPAG plasma concentration-time curve in current cohort of patients taking lower doses of MMF was consistent with previous reports conducted in Caucasians patients taking MMF 1g b.i.d., except that dose-normalized exposure of total and free MPAG was much lower in current study than those in Caucasians. The mean AUC_0-12 of total and free MPA was (20.2±6.5) mg/L and (0.7±0.5) mg·h/L, respectively, whereas those of total and free MPAG were (656±148) mg/L and (222±58.1) mg·h/L respectively. The mean fraction of free MPA and MPAG was (3.5±2.0) % and (34.6±8.0) %, respectively. The combination of C₂=C₃-C₄ and C₁-C₂-C₄, estimated by multi-linear regression model, was the best limited sampling strategies to simultaneously predict both free and total MPA AUC_0-12.Lastly, population PK characteristic of MPA in adult renal transplant recipients during the period of 3-126 day of post-transplantation was investigated. Totally 550 samples from 61 patients with the information of demographic, UGT1A9 polymorphism, comedications as well as renal, liver and blood test results were collected. Population analysis was performed using NONMEM and the final model was evaluated by an independent study performed in the first Shanghai People's Hospital. The validation dataset included 189 samples from 21 renal transplant patients in the 21st day of post-transplantation. The two compartment model with first order absorption and elimination combined lag time best fit the data. The population model for the CL/F of MPA and apparent volume of MPA central compartment (V₂/F) were listed below.where CsA represents daily dose of cyclosporine (unit: mg/d), ALB represents albumin (unit: g/L), CLcr represents clearance of creatinine estimated by Cockcroft-Gault formula (unit: mL/min). Cyclosporine daily dose, albumin and clearance of creatinine could influence the MPA CL/F, whereas albumin was screened as the determinants of V₂/F. UGT1A9 polymorphism and other factors did not affect the MPA PK in current study. The typical population CL/F of MPA was 26.7 L/h, close to the previously published studies. External validation of the final model showed that the established model was reliable. The optimal sampling combination was C_1.5-C₄ based on the external validation dataset and Bayesian estimation. The methodology based on Bayesian estimation using NONMEM employed more complicated alogorithm than that of multi-linear regression model previously proposed, but it requires less samples and no need of accurate control of the time at which the samples are obtained. It could predict all the individual PK parameters based on the patient' characterics and help to optimize the MMF therapy, reduce the adverse drug effects and improve the efficacy.