Abstract
Purpose: The aim of this study is i) to establish a strategy to estimate the area under the curve of the dosing interval (AUC0–12h) 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 AUC0–12h 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: AUC0–12h = 3.539 × C0 + 0.288 × C0.5 + 1.349 × C1 + 6.773 × C4.5. Conclusion: A PPK model was established with three covariates in heart transplant patients. Co-medication of PPIs and eGFR had a remarkable impact on AUC0–12h of MPA. A linear equation was also concluded with four time points as an alternative way to estimate AUC0–12h for MPA.
Highlights
Mycophenolic acid (MPA) is the active metabolite of the prodrug mycophenolate mofetil (MMF), with a high oral bioavailability (95%) (Bullingham et al, 1996)
MPA is one of the most commonly prescribed drugs in immunosuppression therapy to prevent graft rejection after kidney, lung, liver, and heart transplantation (Bergan et al, 2021). It has a protein binding rate of about 97% and is mainly metabolized by uridine diphosphate glucuronosyltransferase (UGT) into the inactive 7-O-glucuronide (MPAG) metabolite (Bullingham et al, 1998). It exhibits enterohepatic circulation (EHC) during which MPAG returns to the small intestine and is degraded into MPA by microorganisms, and MPA is re-absorbed into the circulatory system
508 plasma samples with 507 above lower limit of quantification (LLOQ) were obtained from 91 adult heart transplant recipients with 105 pharmacokinetic sampling cycles
Summary
Mycophenolic acid (MPA) is the active metabolite of the prodrug mycophenolate mofetil (MMF), with a high oral bioavailability (95%) (Bullingham et al, 1996). MPA is one of the most commonly prescribed drugs in immunosuppression therapy to prevent graft rejection after kidney, lung, liver, and heart transplantation (Bergan et al, 2021). It has a protein binding rate of about 97% and is mainly metabolized by uridine diphosphate glucuronosyltransferase (UGT) into the inactive 7-O-glucuronide (MPAG) metabolite (Bullingham et al, 1998). The method to directly calculate AUC0–12h needs intensive sample collection, which is difficult to implement in clinical application
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
