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

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:...

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Autores principales: Wang, Xipei, Wu, Yijin, Huang, Jinsong, Shan, Songgui, Mai, Mingjie, Zhu, Jiade, Yang, Min, Shang, Dewei, Wu, Zheng, Lan, Jinhua, Zhong, Shilong, Wu, Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640522/
https://www.ncbi.nlm.nih.gov/pubmed/34867352
http://dx.doi.org/10.3389/fphar.2021.748609
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author Wang, Xipei
Wu, Yijin
Huang, Jinsong
Shan, Songgui
Mai, Mingjie
Zhu, Jiade
Yang, Min
Shang, Dewei
Wu, Zheng
Lan, Jinhua
Zhong, Shilong
Wu, Min
author_facet Wang, Xipei
Wu, Yijin
Huang, Jinsong
Shan, Songgui
Mai, Mingjie
Zhu, Jiade
Yang, Min
Shang, Dewei
Wu, Zheng
Lan, Jinhua
Zhong, Shilong
Wu, Min
author_sort Wang, Xipei
collection PubMed
description 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 (V(2)/F), respectively. Co-medication of PPIs decreased F by 27.6%. When eGFR decreased by 30 ml/min/1.73 m(2), CL/F decreased by 23.7%. However, the impact of ALB on V(2)/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 × C(0) + 0.288 × C(0.5) + 1.349 × C(1) + 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.
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spelling pubmed-86405222021-12-04 Estimation of Mycophenolic Acid Exposure in Heart Transplant Recipients by Population Pharmacokinetic and Limited Sampling Strategies Wang, Xipei Wu, Yijin Huang, Jinsong Shan, Songgui Mai, Mingjie Zhu, Jiade Yang, Min Shang, Dewei Wu, Zheng Lan, Jinhua Zhong, Shilong Wu, Min Front Pharmacol Pharmacology 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 (V(2)/F), respectively. Co-medication of PPIs decreased F by 27.6%. When eGFR decreased by 30 ml/min/1.73 m(2), CL/F decreased by 23.7%. However, the impact of ALB on V(2)/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 × C(0) + 0.288 × C(0.5) + 1.349 × C(1) + 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. Frontiers Media S.A. 2021-11-19 /pmc/articles/PMC8640522/ /pubmed/34867352 http://dx.doi.org/10.3389/fphar.2021.748609 Text en Copyright © 2021 Wang, Wu, Huang, Shan, Mai, Zhu, Yang, Shang, Wu, Lan, Zhong and Wu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Wang, Xipei
Wu, Yijin
Huang, Jinsong
Shan, Songgui
Mai, Mingjie
Zhu, Jiade
Yang, Min
Shang, Dewei
Wu, Zheng
Lan, Jinhua
Zhong, Shilong
Wu, Min
Estimation of Mycophenolic Acid Exposure in Heart Transplant Recipients by Population Pharmacokinetic and Limited Sampling Strategies
title Estimation of Mycophenolic Acid Exposure in Heart Transplant Recipients by Population Pharmacokinetic and Limited Sampling Strategies
title_full Estimation of Mycophenolic Acid Exposure in Heart Transplant Recipients by Population Pharmacokinetic and Limited Sampling Strategies
title_fullStr Estimation of Mycophenolic Acid Exposure in Heart Transplant Recipients by Population Pharmacokinetic and Limited Sampling Strategies
title_full_unstemmed Estimation of Mycophenolic Acid Exposure in Heart Transplant Recipients by Population Pharmacokinetic and Limited Sampling Strategies
title_short Estimation of Mycophenolic Acid Exposure in Heart Transplant Recipients by Population Pharmacokinetic and Limited Sampling Strategies
title_sort estimation of mycophenolic acid exposure in heart transplant recipients by population pharmacokinetic and limited sampling strategies
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640522/
https://www.ncbi.nlm.nih.gov/pubmed/34867352
http://dx.doi.org/10.3389/fphar.2021.748609
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