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Rexiti K, Jiang X, Kong Y, Chen X, Liu H, Peng H, Wei X. Population pharmacokinetics of mycophenolic acid and dose optimisation in adult Chinese kidney transplant recipients. Xenobiotica 2023; 53:603-612. [PMID: 37991412 DOI: 10.1080/00498254.2023.2287168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 11/20/2023] [Indexed: 11/23/2023]
Abstract
1. This study aimed to establish a population pharmacokinetic (PPK) model of mycophenolic acid (MPA), quantify the effect of clinical factors and pharmacogenomics of MPA, and optimise the dosage for adult kidney transplant recipients.2. One-hundred and four adult renal transplant patients were enrolled. The PPK model was established using the Phoenix® NMLE software and the stepwise methods were filtered for significant covariates. Monte Carlo simulations were performed to optimise the dosage regimen.3. A two-compartment model with first-order absorption and elimination (including lag time) provided a more accurate description of MPA pharmacokinetics. Serum albumin (ALB) significantly affected the central apparent clearance (CL/F), whereas post-transplant time and creatinine clearance were associated with a central apparent volume of distribution (V/F). The estimated population values obtained by the final model were 17.5 L/h and 93.97 L for CL/F and V/F, respectively. Simulation results revealed that larger mycophenolate mofetil doses are required as the ALB concentration decreases. This study established a PPK model of MPA and validated it using various methods. ALB significantly affected CL/F and recommended optimal dose strategies were given based on the final model. These results provide a reference for the personalised therapy of MPA for kidney transplant patients.
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Affiliation(s)
- Kaisaner Rexiti
- School of Pharmacy, Nanchang University, Nanchang, China
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xuehui Jiang
- Department of Pharmacy, Quanzhou First Hospital affiliated to Fujian Medical University, Quanzhou, China
| | - Ying Kong
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xu Chen
- School of Pharmacy, Nanchang University, Nanchang, China
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Hong Liu
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Hongwei Peng
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xiaohua Wei
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
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Mizaki T, Nobata H, Banno S, Yamaguchi M, Kinashi H, Iwagaitsu S, Ishimoto T, Kuru Y, Ohnishi M, Sako KI, Ito Y. Population pharmacokinetics and limited sampling strategy for therapeutic drug monitoring of mycophenolate mofetil in Japanese patients with lupus nephritis. J Pharm Health Care Sci 2023; 9:1. [PMID: 36624529 PMCID: PMC9830922 DOI: 10.1186/s40780-022-00271-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 12/25/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Mycophenolate mofetil (MMF), a prodrug of the immunosuppressive agent mycophenolic acid (MPA), is difficult to administer because of the pharmacokinetic complexity of MPA. Although dosage adjustment according to the 12-h area under the concentration-time curve (AUC0-12) is thought to be desirable, multiple blood samplings for AUC calculation may pose a clinical challenge. A limited sampling strategy (LSS) would provide a solution; however, little is known about MPA pharmacokinetics in lupus nephritis patients, especially in those with Asian backgrounds, or few, if any, LSSs are reported for them. METHODS Thirty-four adult Japanese patients receiving MMF for lupus nephritis were examined retrospectively. MPA pharmacokinetics were investigated, and a PPK model was developed using Phoenix® NLME™ software. Single and double blood sampling strategies from Bayesian estimation using the PPK model and from multiple linear regression were compared. Tolerability was also evaluated. RESULTS In the pharmacokinetic analysis, renal function and serum albumin had significant effects on dose-normalized AUC0-12; and serum albumin, concomitant proton pump inhibitor (PPI) and iron/magnesium oxide did on dose-normalized maximum concentration. As a PPK model, a two-compartment model was developed with a transit absorption model and first-order elimination, in which creatinine clearance and serum albumin were covariates for MPA clearance. The double sampling strategy at 1 and 4 h by multiple linear regression showed the best agreement with the observed AUC0-12 (r2 = 0.885). Of the single sampling strategies, the one at 6 h by Bayesian estimation performed best (r2 = 0.769). The tolerability evaluation showed that correlations were suggested for gastrointestinal involvement. CONCLUSIONS The present study developed the first PPK model of MPA for Japanese lupus nephritis patients. As for LSSs, a double sampling strategy at 1 and 4 h by multiple linear regression would work best; when only a single blood sampling is allowed, a strategy at 6 h by Bayesian estimation using the PPK model developed in this study would be best. The LSSs good enough for clinical use may facilitate safer, more effective, and individualized therapy.
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Affiliation(s)
- Tomoko Mizaki
- Department of Pharmacy, Aichi Medical University Medical Center, 17-33 Nikkicho, Okazaki, Aichi, 444-2148, Japan
- Department of Nephrology and Rheumatology, Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195, Japan
| | - Hironobu Nobata
- Department of Nephrology and Rheumatology, Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195, Japan
| | - Shogo Banno
- Department of Nephrology and Rheumatology, Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195, Japan
| | - Makoto Yamaguchi
- Department of Nephrology and Rheumatology, Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195, Japan
| | - Hiroshi Kinashi
- Department of Nephrology and Rheumatology, Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195, Japan
| | - Shiho Iwagaitsu
- Department of Nephrology and Rheumatology, Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195, Japan
| | - Takuji Ishimoto
- Department of Nephrology and Rheumatology, Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195, Japan
| | - Yukiko Kuru
- Medical Education Center, Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195, Japan
| | - Masafumi Ohnishi
- Department of Pharmacy, Aichi Medical University Medical Center, 17-33 Nikkicho, Okazaki, Aichi, 444-2148, Japan
- Department of Pharmacy, Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195, Japan
| | - Ken-Ichi Sako
- Department of Clinical Pharmacy, Nihon Pharmaceutical University, 10281 Komuro, Kitaadachigun Inamachi, Saitama, 362-0806, Japan
| | - Yasuhiko Ito
- Department of Nephrology and Rheumatology, Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195, Japan.
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Song L, Huang CR, Pan SZ, Zhu JG, Cheng ZQ, Yu X, Xue L, Xia F, Zhang JY, Wu DP, Miao LY. A model based on machine learning for the prediction of cyclosporin A trough concentration in Chinese allo-HSCT patients. Expert Rev Clin Pharmacol 2023; 16:83-91. [PMID: 36373407 DOI: 10.1080/17512433.2023.2142561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cyclosporin A is a calcineurin inhibitor which has a narrow therapeutic window and high interindividual variability. Various population pharmacokinetic models have been reported; however, professional software and technical personnel were needed and the variables of the models were limited. Therefore, the aim of this study was to establish a model based on machine learning to predict CsA trough concentrations in Chinese allo-HSCT patients. METHODS A total of 7874 cases of CsA therapeutic drug monitoring data from 2069 allo-HSCT patients were retrospectively included. Sequential forward selection was used to select variable subsets, and eight different algorithms were applied to establish the prediction model. RESULTS XGBoost exhibited the highest prediction ability. Except for the variables that were identified by previous studies, some rarely reported variables were found, such as norethindrone, WBC, PAB, and hCRP. The prediction accuracy within ±30% of the actual trough concentration was above 0.80, and the predictive ability of the models was demonstrated to be effective in external validation. CONCLUSION In this study, models based on machine learning technology were established to predict CsA levels 3-4 days in advance during the early inpatient phase after HSCT. A new perspective for CsA clinical application is provided.
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Affiliation(s)
- Lin Song
- Department of Pharmacy, the First Affiliated Hospital of Soochow University, Suzhou, China.,College of Pharmaceutical Sciences, Soochow University, Suzhou, China
| | - Chen-Rong Huang
- Department of Pharmacy, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Shi-Zheng Pan
- Department of Pharmacy, the First Affiliated Hospital of Soochow University, Suzhou, China.,College of Pharmaceutical Sciences, Soochow University, Suzhou, China
| | - Jian-Guo Zhu
- Department of Pharmacy, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Zong-Qi Cheng
- Department of Pharmacy, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xun Yu
- Department of Pharmacy, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Ling Xue
- Department of Pharmacy, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Fan Xia
- Department of Pharmacy, the First Affiliated Hospital of Soochow University, Suzhou, China
| | | | - De-Pei Wu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Li-Yan Miao
- Department of Pharmacy, the First Affiliated Hospital of Soochow University, Suzhou, China.,College of Pharmaceutical Sciences, Soochow University, Suzhou, China.,National Clinical Research Center for Hematologic Diseases, The First Affiliated Hospital of Soochow University, Suzhou, China
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Catić‐Đorđević A, Stefanović N, Pavlović I, Pavlović D, Živanović S, Kundalić A, Veličković‐Radovanović R, Mitić B. Utility of salivary mycophenolic acid concentration monitoring: Modeling and Monte Carlo validation approach. Pharmacol Res Perspect 2022; 10:e01034. [PMID: 36440680 PMCID: PMC9703583 DOI: 10.1002/prp2.1034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 10/20/2022] [Accepted: 11/06/2022] [Indexed: 11/29/2022] Open
Abstract
The results of the previous studies demonstrated an association between mycophenolic acid (MPA) exposure, serum albumin level (ALB), and adverse effects in kidney transplant patients. The aim was the identification of mathematical correlation and association between both, total and unbound MPA concentration in relation to ALB, body mass (BM), age and estimated glomerular filtration rate (eGFR) in stable kidney transplant recipients. Furthermore, investigation was conducted with the aim to clarify the role of salivary concentration (CSAL ) of MPA in adverse effect profile. In order to analyze the association between total and salivary concentration of MPA in relation to ALB, BM, age and eGFR, a least squares method for determining the correlation between these parameters was performed. In addition, derived mathematical model based on experimental data can also be performed and simulated through the Monte Carlo (MC) approach. Adverse effects were grouped according to the nature of symptoms and scored by a previously published validated system. Numerically calculated values of CSAL from the models [CSAL = f(ALB, BM, age, eGFR, CP ) = a00 + a10 *(ALB, BM, age, eGFR) + a01 *CP ] were then compared with those from validation set of patients, where the best fitting model was for ALB [CSAL = 54.96-1.64*ALB +13.4*CP ]. Adverse effects estimation showed the difference in esthetic score, positively correlated with CSAL in the lower ALB group (145.41 ± 219.02 vs. 354.08 ± 262.19; with statistical significance p = .014) and almost significant for gastrointestinal score (167.69 ± 174.79 vs. 347.55 ± 320.95; p = .247). The study showed that CSAL MPA may contribute to management of adverse effects, but these findings require confirmation of clinical utility.
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Affiliation(s)
| | - Nikola Stefanović
- Faculty of Medicine, Department of PharmacyUniversity of NisNisSerbia
| | - Ivan Pavlović
- Faculty of Mechanical EngineeringUniversity of NisNisSerbia
| | - Dragana Pavlović
- Faculty of Medicine, Department of PharmacyUniversity of NisNisSerbia
| | - Slavoljub Živanović
- Faculty of Medicine, Research Center for BiomedicineUniversity of NisNisSerbia
| | - Ana Kundalić
- Faculty of Medicine, Department of PharmacyUniversity of NisNisSerbia
| | | | - Branka Mitić
- Faculty of MedicineUniversity of NisNisSerbia
- Clinic of NephrologyUniversity Clinical Center NisNisSerbia
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Significant Correlations between p-Cresol Sulfate and Mycophenolic Acid Plasma Concentrations in Adult Kidney Transplant Recipients. Clin Drug Investig 2022; 42:207-219. [PMID: 35182318 DOI: 10.1007/s40261-022-01121-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/23/2022] [Indexed: 11/03/2022]
Abstract
BACKGROUND AND OBJECTIVES Mycophenolic acid (MPA) is a commonly prescribed life-long immunosuppressant for kidney transplant recipients. The frequently observed large variations in MPA plasma exposure may lead to severe adverse outcomes; therefore, characterizations of contributing factors can potentially improve the precision dosing of MPA. Our group recently reported the potent inhibitory effects of p-cresol (a protein-bound uremic toxin that can be accumulated in kidney transplant patients) on the hepatic metabolism of MPA in human in vitro models. Based on these data, the hypothesis for this clinical investigation was that a direct correlation between p-cresol and MPA plasma exposure should be evident in adult kidney transplant recipients. METHODS Using a prospective and observational approach, adult kidney transplant recipients within the first year after transplant on oral mycophenolate mofetil (with tacrolimus ± prednisone) were screened for recruitment. The exclusion criteria were cold ischemia time > 30 h, malignancy, pregnancy, severe renal dysfunction (i.e., estimated glomerular filtration rate, eGFR, < 10 mL/min/1.73 m2), active graft rejection, or MPA intolerance. Patients' demographic and biochemistry data were collected. Total and free plasma concentrations of MPA, MPA glucuronide (MPAG), and total p-cresol sulfate (the predominant, quantifiable form of p-cresol in the plasma) were quantified using validated assays. Correlational and categorical analyses were performed using GraphPad Prism. RESULTS Forty patients (11 females) were included: donor type (living/deceased: 20/20), induction regimen (basiliximab/thymoglobulin/basiliximab followed by thymoglobulin: 35/3/2), post-transplant time (74 ± 60 days, mean ± standard deviation), age (53.7 ± 12.4 years), bodyweight (79.8 ± 18.5 kg), eGFR (51.9 ± 18.0 mL/min/1.73 m2), serum albumin (3.6 ± 0.5 g/dL), prednisone dose (18.5 ± 13.2 mg, n = 33), and tacrolimus trough concentration (9.4 ± 2.4 µg/L). Based on Spearman analysis, significant control correlations supporting the validity of our dataset were observed between total MPA trough concentration (C0) and total MPAG C0 (correlation coefficient [R] = 0.39), ratio of total MPAG C0-to-total MPA C0 and post-transplant time (R = - 0.56), total MPAG C0 and eGFR (R = - 0.35), and p-cresol sulfate concentration and eGFR (R = - 0.70). Our primary analysis indicated the novel observation that total MPA C0 (R = 0.39), daily dose-normalized total MPA C0 (R = 0.32), and bodyweight-normalized total MPA C0 (R = 0.32) were significantly correlated with plasma p-cresol sulfate concentrations. Consistently, patients categorized with elevated p-cresol sulfate concentrations (i.e., ≥ median of 3.2 µg/mL) also exhibited increased total MPA C0 (by 57 % vs those below median), daily dose-normalized total MPA C0 (by 89 %), and bodyweight-normalized total MPA C0 (by 62 %). Our secondary analyses with MPA metabolites, unbound concentrations, free fractions, and MPA metabolite ratios supported additional potential interacting mechanisms. CONCLUSION We have identified a novel, positive association between p-cresol sulfate exposure and total MPA C0 in adult kidney transplant recipients, which is supported by published mechanistic in vitro data. Our findings confirm a potential role of p-cresol as a significant clinical variable affecting the pharmacokinetics of MPA. These data also provide the justifications for conducting subsequent full-scale pharmacokinetic-pharmacodynamic studies to further characterize the cause-effect relationships of this interaction, which could also rule out potential confounding variables not adequately controlled in this correlational study.
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Rong Y, Patel V, Kiang TKL. Recent lessons learned from population pharmacokinetic studies of mycophenolic acid: physiological, genomic, and drug interactions leading to the prediction of drug effects. Expert Opin Drug Metab Toxicol 2022; 17:1369-1406. [PMID: 35000505 DOI: 10.1080/17425255.2021.2027906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Mycophenolic acid (MPA) is a widely used immunosuppressant in transplantation and autoimmune disease. Highly variable pharmacokinetics have been observed with MPA, but the exact mechanisms remain largely unknown. AREAS COVERED The current review provided a critical, comprehensive update of recently published population pharmacokinetic/dynamic models of MPA (n=16 papers identified from PubMed and Embase, inclusive from January 2017 to August 2021), with specific emphases on the intrinsic and extrinsic factors influencing the pharmacology of MPA. The significance of the identified covariates, potential mechanisms, and comparisons to historical literature have been provided. EXPERT OPINION While select covariates affecting the population pharmacokinetics of MPA are consistently observed and mechanistically supported, some variables have not been regularly reported and/or lacked mechanistic explanation. Very few pharmacodynamic models were available, pointing to the need to extrapolate pharmacokinetic findings. Ideal models of MPA should consist of: i) utilizing optimal sampling points to allow the characterizations of absorption, re-absorption, and elimination phases; ii) characterizing unbound/total MPA, MPA metabolites, plasma/urinary concentrations, and genetic polymorphisms to facilitate mechanistic interpretations; and iii) incorporating actual outcomes and pharmacodynamic data to establish clinical relevance. We anticipate the field will continue to expand in the next 5 to 10 years.
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Affiliation(s)
- Yan Rong
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Vrunda Patel
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Tony K L Kiang
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada
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Wang X, Wu Y, Huang J, Shan S, Mai M, Zhu J, Yang M, Shang D, Wu Z, Lan J, Zhong S, Wu M. Estimation of Mycophenolic Acid Exposure in Heart Transplant Recipients by Population Pharmacokinetic and Limited Sampling Strategies. Front Pharmacol 2021; 12:748609. [PMID: 34867352 PMCID: PMC8640522 DOI: 10.3389/fphar.2021.748609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 10/14/2021] [Indexed: 11/13/2022] Open
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.
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Affiliation(s)
- Xipei Wang
- Research Center of Medical Sciences, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Clinical Pharmacology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yijin Wu
- Department of Cardiac Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jinsong Huang
- Department of Cardiac Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Songgui Shan
- Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Mingjie Mai
- Department of Cardiac Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jiade Zhu
- Department of Cardiac Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Min Yang
- Guangdong Provincial Key Laboratory of Clinical Pharmacology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Dewei Shang
- Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zheng Wu
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Jinhua Lan
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Shilong Zhong
- Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangzhou, China
| | - Min Wu
- Department of Cardiac Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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Zwart TC, Guchelaar HJ, van der Boog PJM, Swen JJ, van Gelder T, de Fijter JW, Moes DJAR. Model-informed precision dosing to optimise immunosuppressive therapy in renal transplantation. Drug Discov Today 2021; 26:2527-2546. [PMID: 34119665 DOI: 10.1016/j.drudis.2021.06.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 04/21/2021] [Accepted: 06/04/2021] [Indexed: 12/18/2022]
Abstract
Immunosuppressive therapy is pivotal for sustained allograft and patient survival after renal transplantation. However, optimally balanced immunosuppressive therapy is challenged by between-patient and within-patient pharmacokinetic (PK) variability. This could warrant the application of personalised dosing strategies to optimise individual patient outcomes. Pharmacometrics, the science that investigates the xenobiotic-biotic interplay using computer-aided mathematical modelling, provides options to describe and quantify this PK variability and enables identification of patient characteristics affecting immunosuppressant PK and treatment outcomes. Here, we review and critically appraise the available pharmacometric model-informed dosing solutions for the typical immunosuppressants in modern renal transplantation, to guide their initial and subsequent dosing.
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Affiliation(s)
- Tom C Zwart
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, the Netherlands
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, the Netherlands; Leiden Network for Personalised Therapeutics, Leiden, the Netherlands
| | - Paul J M van der Boog
- Department of Internal Medicine (Nephrology), Leiden University Medical Center, Leiden, the Netherlands; LUMC Transplant Center, Leiden University Medical Center, Leiden, the Netherlands
| | - Jesse J Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, the Netherlands; Leiden Network for Personalised Therapeutics, Leiden, the Netherlands
| | - Teun van Gelder
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, the Netherlands
| | - Johan W de Fijter
- Department of Internal Medicine (Nephrology), Leiden University Medical Center, Leiden, the Netherlands; LUMC Transplant Center, Leiden University Medical Center, Leiden, the Netherlands
| | - Dirk Jan A R Moes
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, the Netherlands; Leiden Network for Personalised Therapeutics, Leiden, the Netherlands.
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Chakrabarti K, Frame D, Al Abbas M, McCune WJ. The use of mycophenolate mofetil area under the curve. Curr Opin Rheumatol 2021; 33:221-232. [PMID: 33741807 DOI: 10.1097/bor.0000000000000799] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW Although mycophenolate mofetil (MMF) has been used successfully to treat a myriad of autoimmune diseases, its complex pharmacokinetics make it difficult to determine the true drug exposure for an individual patient. This review summarizes the body of literature focused on the gold standard measurement of the area under the curve (AUC) of mycophenolic acid (MPA), the active metabolite of MMF. RECENT FINDINGS Fixed dosing of MMF leads to highly variable drug exposure. Retrospective series have reported improved clinical outcomes when a minimum AUC value from 0 to 12 h (AUC0-12h) ≥30 mg h/l is achieved. MPA levels are affected by various drug interactions, hypoalbuminemia, and renal insufficiency and the measurement of free rather than total MPA levels is prudent in some situations. A limited number of studies employing prospective dose adjustment of MMF based on AUC0-12h measurements have yielded mixed results. SUMMARY Given the wide range of MPA AUC encountered in autoimmune diseases, dose adjustments of MMF based on AUC rather than fixed dosing of MMF should be considered in both clinical practice and clinical trials. Limited sampling strategies have been proposed to improve clinical feasibility of measurements, but a standard is yet to be defined.
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Affiliation(s)
| | - David Frame
- Department of Clinical Pharmacy, University of Michigan, Ann Arbor, Michigan, USA
| | - Mousa Al Abbas
- Staff Rheumatologist, King Fahad Specialist Hospital, Dammam, Saudi Arabia
| | - W Joseph McCune
- Department of Internal Medicine, Division of Rheumatology, University of Michigan
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Bergan S, Brunet M, Hesselink DA, Johnson-Davis KL, Kunicki PK, Lemaitre F, Marquet P, Molinaro M, Noceti O, Pattanaik S, Pawinski T, Seger C, Shipkova M, Swen JJ, van Gelder T, Venkataramanan R, Wieland E, Woillard JB, Zwart TC, Barten MJ, Budde K, Dieterlen MT, Elens L, Haufroid V, Masuda S, Millan O, Mizuno T, Moes DJAR, Oellerich M, Picard N, Salzmann L, Tönshoff B, van Schaik RHN, Vethe NT, Vinks AA, Wallemacq P, Åsberg A, Langman LJ. Personalized Therapy for Mycophenolate: Consensus Report by the International Association of Therapeutic Drug Monitoring and Clinical Toxicology. Ther Drug Monit 2021; 43:150-200. [PMID: 33711005 DOI: 10.1097/ftd.0000000000000871] [Citation(s) in RCA: 98] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 01/29/2021] [Indexed: 12/13/2022]
Abstract
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.
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Affiliation(s)
- Stein Bergan
- Department of Pharmacology, Oslo University Hospital and Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Mercè Brunet
- Pharmacology and Toxicology Laboratory, Biochemistry and Molecular Genetics Department, Biomedical Diagnostic Center, Hospital Clinic of Barcelona, University of Barcelona, IDIBAPS, CIBERehd, Spain
| | - Dennis A Hesselink
- Department of Internal Medicine, Division of Nephrology and Transplantation, Erasmus MC, University Medical Center Rotterdam, The Netherlands
| | - Kamisha L Johnson-Davis
- Department of Pathology, University of Utah Health Sciences Center and ARUP Laboratories, Salt Lake City, Utah
| | - Paweł K Kunicki
- Department of Drug Chemistry, Faculty of Pharmacy, Medical University of Warsaw, Warszawa, Poland
| | - Florian Lemaitre
- Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail)-UMR_S 1085, Rennes, France
| | - Pierre Marquet
- INSERM, Université de Limoges, Department of Pharmacology and Toxicology, CHU de Limoges, U1248 IPPRITT, Limoges, France
| | - Mariadelfina Molinaro
- Clinical and Experimental Pharmacokinetics Lab, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Ofelia Noceti
- National Center for Liver Tansplantation and Liver Diseases, Army Forces Hospital, Montevideo, Uruguay
| | | | - Tomasz Pawinski
- Department of Drug Chemistry, Faculty of Pharmacy, Medical University of Warsaw, Warszawa, Poland
| | | | - Maria Shipkova
- Synlab TDM Competence Center, Synlab MVZ Leinfelden-Echterdingen GmbH, Leinfelden-Echterdingen, Germany
| | - Jesse J Swen
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Teun van Gelder
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Raman Venkataramanan
- Department of Pharmaceutical Sciences, School of Pharmacy and Department of Pathology, Starzl Transplantation Institute, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Eberhard Wieland
- Synlab TDM Competence Center, Synlab MVZ Leinfelden-Echterdingen GmbH, Leinfelden-Echterdingen, Germany
| | - Jean-Baptiste Woillard
- INSERM, Université de Limoges, Department of Pharmacology and Toxicology, CHU de Limoges, U1248 IPPRITT, Limoges, France
| | - Tom C Zwart
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Markus J Barten
- Department of Cardiac- and Vascular Surgery, University Heart and Vascular Center Hamburg, Hamburg, Germany
| | - Klemens Budde
- Department of Nephrology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Maja-Theresa Dieterlen
- Department of Cardiac Surgery, Heart Center, HELIOS Clinic, University Hospital Leipzig, Leipzig, Germany
| | - Laure Elens
- Integrated PharmacoMetrics, PharmacoGenomics and PharmacoKinetics (PMGK) Research Group, Louvain Drug Research Institute (LDRI), Université Catholique de Louvain (UCLouvain), Brussels, Belgium
| | - Vincent Haufroid
- Louvain Centre for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique, UCLouvain and Department of Clinical Chemistry, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Satohiro Masuda
- Department of Pharmacy, International University of Health and Welfare Narita Hospital, Chiba, Japan
| | - Olga Millan
- Pharmacology and Toxicology Laboratory, Biochemistry and Molecular Genetics Department, Biomedical Diagnostic Center, Hospital Clinic of Barcelona, University of Barcelona, IDIBAPS, CIBERehd, Spain
| | - Tomoyuki Mizuno
- Division of Clinical Pharmacology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | - Dirk J A R Moes
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Michael Oellerich
- Department of Clinical Pharmacology, University Medical Center Göttingen, Georg-August-University Göttingen, Göttingen, Germany
| | - Nicolas Picard
- INSERM, Université de Limoges, Department of Pharmacology and Toxicology, CHU de Limoges, U1248 IPPRITT, Limoges, France
| | | | - Burkhard Tönshoff
- Department of Pediatrics I, University Children's Hospital, Heidelberg, Germany
| | - Ron H N van Schaik
- Department of Clinical Chemistry, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Nils Tore Vethe
- Department of Pharmacology, Oslo University Hospital and Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Alexander A Vinks
- Department of Pharmacy, International University of Health and Welfare Narita Hospital, Chiba, Japan
| | - Pierre Wallemacq
- Clinical Chemistry Department, Cliniques Universitaires St Luc, Université Catholique de Louvain, LTAP, Brussels, Belgium
| | - Anders Åsberg
- Department of Transplantation Medicine, Oslo University Hospital-Rikshospitalet and Department of Pharmacy, University of Oslo, Oslo, Norway; and
| | - Loralie J Langman
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
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11
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Population Pharmacokinetic Model of Plasma and Cellular Mycophenolic Acid in Kidney Transplant Patients from the CIMTRE Study. Drugs R D 2021; 20:331-342. [PMID: 33025511 PMCID: PMC7691413 DOI: 10.1007/s40268-020-00319-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Background and Objective Mycophenolate mofetil is widely used in kidney transplant recipients. Mycophenolate mofetil is hydrolysed by blood esterases to mycophenolic acid (MPA), the active drug. Although MPA therapeutic drug monitoring has been recommended to optimise the treatment efficacy by the area under the plasma concentration vs time curve, little is known regarding MPA concentrations in peripheral blood mononuclear cells, where MPA inhibits inosine monophosphate dehydrogenase. This study aimed to build a pharmacokinetic model using a population approach to describe MPA total and unbound concentrations in plasma and into peripheral blood mononuclear cells in 78 adult kidney transplant recipients receiving mycophenolate mofetil therapy combined with tacrolimus and prednisone. Methods Total and unbound plasma concentrations and peripheral blood mononuclear cell concentrations were assayed. A three-compartment model, two for plasma MPA and one for peripheral blood mononuclear cell MPA, with a zero-order absorption and a first-order elimination was used to describe the data. Results Mycophenolic acid average concentrations in peripheral blood mononuclear cells were well above half-maximal effective concentration for inosine monophosphate dehydrogenase and no relationship was found with the occurrence of graft rejection. Three covariates affected unbound and intracellular MPA pharmacokinetics: creatinine clearance, which has an effect on unbound MPA clearance, human serum albumin, which influences fraction unbound MPA and the ABCB1 3435 C>T (rs1045642) genetic polymorphism, which has an effect on MPA efflux transport from peripheral blood mononuclear cells. Conclusion This population pharmacokinetic model demonstrated the intracellular accumulation of MPA, the efflux of MPA out of the cells being dependent on P-glycoprotein transporters. Nevertheless, further studies are warranted to investigate the relevance of MPA concentrations in peripheral blood mononuclear cells to dosing regimen optimisation. Electronic supplementary material The online version of this article (10.1007/s40268-020-00319-y) contains supplementary material, which is available to authorized users.
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12
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Rong Y, Jun H, Kiang TKL. Population pharmacokinetics of mycophenolic acid in paediatric patients. Br J Clin Pharmacol 2021; 87:1730-1757. [PMID: 33118201 DOI: 10.1111/bcp.14590] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 09/07/2020] [Accepted: 09/22/2020] [Indexed: 12/14/2022] Open
Abstract
Mycophenolic acid (MPA) is widely used in paediatric kidney transplant patients and sometimes prescribed for additional indications. Population pharmacokinetic or pharmacodynamic modelling has been frequently used to characterize the fixed, random and covariate effects of MPA in adult patients. However, MPA population pharmacokinetic data in the paediatric population have not been systematically summarized. The objective of this narrative review was to provide an up-to-date critique of currently available paediatric MPA population pharmacokinetic models, with emphases on modelling techniques, pharmacological findings and clinical relevance. PubMed and EMBASE were searched from inception of database to May 2020, where a total of 11 studies have been identified representing kidney transplant (n = 4), liver transplant (n = 1), haematopoietic stem cell transplant (n = 1), idiopathic nephrotic syndrome (n = 2), systemic lupus erythematosus (n = 2), and a combined population consisted of kidney, liver and haematopoietic stem cell transplant patients (n = 1). Critical analyses were provided in the context of MPA absorption, distribution, metabolism, excretion and bioavailability in this paediatric database. Comparisons to adult patients were also provided. With respect to clinical utility, Bayesian estimation models (n = 6) with acceptable accuracy and precision for MPA exposure determination have also been identified and systematically evaluated. Overall, our analyses have identified unique features of MPA clinical pharmacology in the paediatric population, while recognizing several gaps that still warrant further investigations. This review can be used by pharmacologists and clinicians for improving MPA pharmacokinetic-pharmacodynamic modelling and patient care.
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Affiliation(s)
- Yan Rong
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada
| | - Heajin Jun
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada.,College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Tony K L Kiang
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada
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13
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Fontova P, Rama I, Llaudó I, Vidal-Alabró A, Cerezo G, Manzano A, Bestard O, Cruzado JM, Torras J, Grinyó JM, Lloberas N. Mycophenolic acid interferes the transcriptional regulation and protein trafficking of maturation surface markers in dendritic cells. Int Immunopharmacol 2021; 91:107025. [PMID: 33360369 DOI: 10.1016/j.intimp.2020.107025] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 09/16/2020] [Accepted: 09/16/2020] [Indexed: 10/22/2022]
Abstract
BACKGROUND The ability of dendritic cells (DCs) to regulate adaptive immunity makes them interesting cells to be used as therapeutic targets modulating alloimmune responses. Mycophenolic acid (MPA) is an immunosuppressor commonly used in transplantation, and its effect on DCs has not been fully investigated. METHODS Monocyte-derived DCs were obtained from healthy volunteers and cultured for 7 days. Cells were treated with MPA on day 2 and matured by lipopolysaccharide (LPS) stimulation. Functionality of mature DC (mDCs) was evaluated by allogeneic mixed lymphocytes reaction. Surface expression of maturation markers (CD40, CD83, CD86, and ICAM-1) was analyzed in both immature DCs (iDCs) and mDCs by flow cytometry. To assess transcriptional regulation and protein subcellular location, RT-PCR and confocal microscopy were used, respectively. RESULTS MPA decreased surface expression of all maturation markers in mDCs and significantly abrogated DCs-induced allogeneic T-cell proliferation after MPA pre-treatment. In iDCs, the reduced surface protein expression after MPA paralleled with mRNA downregulation of their genes. In mDCs, the mRNA levels of ICAM-1, CD40 and CD83 were enhanced in MPA-treated mDCs with an increase in the expression of CD83 and ICAM-1 near the Golgi compared to non-treated mDCs. In contrast, mRNA levels of CD86 were diminished after MPA treatment. CONCLUSIONS The reduced surface markers expression in mDCs exerted by MPA produced a decline in their capacity to activate immune responses. Moreover, the inhibition of guanosine-derived nucleotide biosynthesis by MPA treatment leads to DC maturation interference by two mechanisms depending on the marker, transcriptional downregulation or disrupted intracellular protein trafficking.
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Affiliation(s)
- Pere Fontova
- Nephrology Department, Hospital Universitari de Bellvitge, IDIBELL, Universitat de Barcelona, Barcelona, Spain
| | - Inés Rama
- Nephrology Department, Hospital Universitari de Bellvitge, IDIBELL, Universitat de Barcelona, Barcelona, Spain
| | - Inés Llaudó
- Nephrology Department, Hospital Universitari de Bellvitge, IDIBELL, Universitat de Barcelona, Barcelona, Spain
| | - Anna Vidal-Alabró
- Nephrology Department, Hospital Universitari de Bellvitge, IDIBELL, Universitat de Barcelona, Barcelona, Spain
| | - Gema Cerezo
- Nephrology Department, Hospital Universitari de Bellvitge, IDIBELL, Universitat de Barcelona, Barcelona, Spain
| | - Anna Manzano
- Unitat de Bioquímica, Departament de Ciències Fisiològiques, IDIBELL, Universitat de Barcelona, Barcelona, Spain
| | - Oriol Bestard
- Nephrology Department, Hospital Universitari de Bellvitge, IDIBELL, Universitat de Barcelona, Barcelona, Spain
| | - Josep M Cruzado
- Nephrology Department, Hospital Universitari de Bellvitge, IDIBELL, Universitat de Barcelona, Barcelona, Spain
| | - Joan Torras
- Nephrology Department, Hospital Universitari de Bellvitge, IDIBELL, Universitat de Barcelona, Barcelona, Spain
| | - Josep M Grinyó
- Nephrology Department, Hospital Universitari de Bellvitge, IDIBELL, Universitat de Barcelona, Barcelona, Spain
| | - Núria Lloberas
- Nephrology Department, Hospital Universitari de Bellvitge, IDIBELL, Universitat de Barcelona, Barcelona, Spain.
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14
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Catić-Đorđević A, Pavlović I, Spasić A, Stefanović N, Pavlović D, Damnjanović I, Mitić B, Veličković-Radovanović R. Assessment of pharmacokinetic mycophenolic acid clearance models using Monte Carlo numerical analysis. Xenobiotica 2021; 51:387-393. [PMID: 33416418 DOI: 10.1080/00498254.2020.1871532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
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.
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Affiliation(s)
| | - Ivan Pavlović
- Faculty of Mechanical Engineering, University of Nis, Nis, Serbia
| | - Ana Spasić
- Faculty of Medicine, University of Nis, Nis, Serbia
| | | | | | | | - Branka Mitić
- Faculty of Medicine, University of Nis, Nis, Serbia.,Clinic of Nephrology, Clinical Center Nis, Nis, Serbia
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15
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Early prognostic performance of miR155-5p monitoring for the risk of rejection: Logistic regression with a population pharmacokinetic approach in adult kidney transplant patients. PLoS One 2021; 16:e0245880. [PMID: 33481955 PMCID: PMC7822507 DOI: 10.1371/journal.pone.0245880] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 01/10/2021] [Indexed: 12/29/2022] Open
Abstract
Previous results from our group and others have shown that urinary pellet expression of miR155-5p and urinary CXCL-10 production could play a key role in the prognosis and diagnosis of acute rejection (AR) in kidney transplantation patients. Here, a logistic regression model was developed using NONMEM to quantify the relationships of miR155-5p urinary expression, CXCL-10 urinary concentration and tacrolimus and mycophenolic acid (MPA) exposure with the probability of AR in adult kidney transplant patients during the early post-transplant period. Owing to the contribution of therapeutic drug monitoring to achieving target exposure, neither tacrolimus nor MPA cumulative exposure was identified as a predictor of AR in the studied population. Even though CXCL-10 urinary concentration showed a trend, its effect on AR was not significant. In contrast, urinary miR155-5p expression was prognostic of clinical outcome. Monitoring miR155-5p urinary pellet expression together with immunosuppressive drug exposure could be very useful during routine clinical practice to identify patients with a potential high risk of rejection at the early stages of the post-transplant period. This early risk assessment would allow for the optimization of treatment and improved prevention of AR.
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16
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Severe Mycophenolate Intoxication in a Solid Organ Transplant Recipient-No Intervention Actually Needed. Transplant Direct 2020; 6:e609. [PMID: 33062842 PMCID: PMC7523787 DOI: 10.1097/txd.0000000000001058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 07/31/2020] [Accepted: 08/15/2020] [Indexed: 11/26/2022] Open
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Sheng C, Zhao Q, Niu W, Qiu X, Zhang M, Jiao Z. Effect of Protein Binding on Exposure of Unbound and Total Mycophenolic Acid: A Population Pharmacokinetic Analysis in Chinese Adult Kidney Transplant Recipients. Front Pharmacol 2020; 11:340. [PMID: 32265712 PMCID: PMC7100081 DOI: 10.3389/fphar.2020.00340] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 03/09/2020] [Indexed: 01/31/2023] Open
Abstract
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.
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Affiliation(s)
- Changcheng Sheng
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Qun Zhao
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Wanjie Niu
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoyan Qiu
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Ming Zhang
- Department of Nephropathy, Huashan Hospital, Fudan University, Shanghai, China
| | - Zheng Jiao
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
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18
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Rong Y, Mayo P, Ensom MHH, Kiang TKL. Population Pharmacokinetics of Mycophenolic Acid Co-Administered with Tacrolimus in Corticosteroid-Free Adult Kidney Transplant Patients. Clin Pharmacokinet 2019; 58:1483-1495. [DOI: 10.1007/s40262-019-00771-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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19
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Zhang HX, Sheng CC, Liu LS, Luo B, Fu Q, Zhao Q, Li J, Liu YF, Deng RH, Jiao Z, Wang CX. Systematic external evaluation of published population pharmacokinetic models of mycophenolate mofetil in adult kidney transplant recipients co-administered with tacrolimus. Br J Clin Pharmacol 2019; 85:746-761. [PMID: 30597603 DOI: 10.1111/bcp.13850] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Revised: 12/03/2018] [Accepted: 12/19/2018] [Indexed: 12/15/2022] Open
Abstract
AIMS Various mycophenolate mofetil (MMF) population pharmacokinetic (popPK) models have been developed to describe its PK characteristics and facilitate its optimal dosing in adult kidney transplant recipients co-administered with tacrolimus. However, the external predictive performance has been unclear. Thus, this study aimed to comprehensively evaluate the external predictability of published MMF popPK models in such populations and investigate the potential influencing factors. METHODS The external predictability of qualified popPK models was evaluated using an independent dataset. The evaluation included prediction- and simulation-based diagnostics, and Bayesian forecasting. In addition, factors influencing model predictability, especially the impact of structural models, were investigated. RESULTS Fifty full PK profiles from 45 patients were included in the evaluation dataset and 11 published popPK models were identified and evaluated. In prediction-based diagnostics, the prediction error within ±30% was less than 50% in most published models. The prediction- and variability-corrected visual predictive check and posterior predictive check showed large discrepancies between the observations and simulations in most models. Moreover, the normalized prediction distribution errors of all models did not follow a normal distribution. Bayesian forecasting demonstrated an improvement in the model predictability. Furthermore, the predictive performance of two-compartment (2CMT) models incorporating the enterohepatic circulation (EHC) process was not superior to that of conventional 2CMT models. CONCLUSIONS The published models showed large variability and unsatisfactory predictive performance, which indicated that therapeutic drug monitoring was necessary for MMF clinical application. Further studies incorporating potential covariates need to be conducted to investigate the key factors influencing model predictability of MMF.
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Affiliation(s)
- Huan-Xi Zhang
- Organ Transplant Centre, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Chang-Cheng Sheng
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China.,Department of Pharmacy, Guizhou Provincial People's Hospital, Guiyang, China
| | - Long-Shan Liu
- Organ Transplant Centre, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Bi Luo
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Qian Fu
- Organ Transplant Centre, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qun Zhao
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Jun Li
- Organ Transplant Centre, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yan-Feng Liu
- Department of urology, Shenzhen People's Hospital, Shenzhen, China
| | - Rong-Hai Deng
- Organ Transplant Centre, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zheng Jiao
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Chang-Xi Wang
- Organ Transplant Centre, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory on Organ Donation and Transplant Immunology, Guangzhou, China
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