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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: 92] [Impact Index Per Article: 30.7] [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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Evaluation of Multiple Linear Regression-Based Limited Sampling Strategies for Enteric-Coated Mycophenolate Sodium in Adult Kidney Transplant Recipients. Ther Drug Monit 2018; 40:195-201. [PMID: 29461443 DOI: 10.1097/ftd.0000000000000486] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Although multiple linear regression-based limited sampling strategies (LSSs) have been published for enteric-coated mycophenolate sodium, none have been evaluated for the prediction of subsequent mycophenolic acid (MPA) exposure. This study aimed to examine the predictive performance of the published LSS for the estimation of future MPA area under the concentration-time curve from 0 to 12 hours (AUC0-12) in renal transplant recipients. METHODS Total MPA plasma concentrations were measured in 20 adult renal transplant patients on 2 occasions a week apart. All subjects received concomitant tacrolimus and were approximately 1 month after transplant. Samples were taken at 0, 0.33, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 6, and 8 hours and 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 2, 3, 4, 6, 9, and 12 hours after dose on the first and second sampling occasion, respectively. Predicted MPA AUC0-12 was calculated using 19 published LSSs and data from the first or second sampling occasion for each patient and compared with the second occasion full MPA AUC0-12 calculated using the linear trapezoidal rule. Bias (median percentage prediction error) and imprecision (median absolute prediction error) were determined. RESULTS Median percentage prediction error and median absolute prediction error for the prediction of full MPA AUC0-12 were <15% for 4 LSSs, using the data from the same (second) occasion. One equation (1.583C1 + 0.765C2 + 0.369C2.5 + 0.748C3 + 1.518C4 + 2.158C6 + 3.292C8 + 3.6690) showed bias and imprecision <15% for the prediction of future MPA AUC0-12, where the predicted AUC0-12 from the first occasion was compared with the full AUC0-12 from the second. All LSSs with an acceptable predictive performance included concentrations taken at least 6 hours after the dose. CONCLUSIONS Only one LSS had an acceptable bias and precision for future estimation. Accurate dosage prediction using a multiple linear regression-based LSS was not possible without concentrations up to at least 8 hours after the dose.
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Development of an Abbreviated Mycophenolic Acid Area Under the Time-Concentration Curve for Renal Transplant Patients Under Enteric-Coated Mycophenolate Sodium: A Comparison With Critical Analysis of Available Equations. Ther Drug Monit 2018; 40:411-416. [PMID: 29746396 DOI: 10.1097/ftd.0000000000000529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Enteric-coated mycophenolate sodium is frequently used in renal transplantation. The pharmacokinetic profile of mycophenolic acid (MPA) shows a broad range of time-to-maximum concentration (Tmax) that limits the use of a single MPA concentration to calculate the area under the time-concentration curve (AUC). For both research and clinical MPA monitoring, measuring a complete AUC is troublesome to the center and patients. METHODS We obtained 171 complete MPA-AUC12h (0, 20, 40, 60, 90, 120, 180, 240, 360, 480, 600, and 720 minutes) from 59 adult (54 ± 16 years) patients (29 men and 43 whites) who have been receiving stable doses of tacrolimus/enteric-coated mycophenolate sodium and steroids. We used the 59 curves drawn at 31 ± 4 days after transplantation to develop the abbreviated equations, and the remaining 112 curves drawn at 109 ± 59 days were used to validate them. We used 5 other proposed equations to estimate MPA-AUC (eAUC) (4 with enzyme-multiplied immunoassay technique assay and one with high-performance liquid chromatography [HPLC]) and then used these results to compare with our measured AUC, the bias, and the 10% and 30% accuracy. MPA was measured by ultraperformance liquid chromatography coupled to a tandem mass spectrometry, and AUC was calculated by the trapezoidal rule. RESULTS For both MPA-measuring methods, enzyme-multiplied immunoassay technique and ultraperformance liquid chromatography coupled to a tandem mass spectrometry, the Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (HCFMUSP) equations, and others that measure MPA up to 6 hours after the dose had an acceptable low bias with more results in the 10%-30% range than those using data collected until 4 hours. A highly adequate eAUC is obtained using blood collected at 8 hours. CONCLUSIONS This analysis offers blood-sampling alternatives for MPA monitoring depending on the precision needed.
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Estimation of Mycophenolic Acid Area Under the Curve With Limited-Sampling Strategy in Chinese Renal Transplant Recipients Receiving Enteric-Coated Mycophenolate Sodium. Ther Drug Monit 2017; 39:29-36. [PMID: 27941535 PMCID: PMC5228625 DOI: 10.1097/ftd.0000000000000360] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND The enteric-coated mycophenolate sodium (EC-MPS), whose active constituent is mycophenolic acid (MPA), has been widely clinically used for organ transplant recipients. However, its absorption is delayed due to its special designed dosage form, which results in difficulty to monitor the exposure of the MPA in patients receiving the EC-MPS. This study was aimed at developing a relatively practical and precise model with limited sampling strategy to estimate the 12-hour area under the concentration-time curve (AUC0-12 h) of MPA for Chinese renal transplant recipients receiving EC-MPS. METHODS A total of 36 Chinese renal transplant recipients receiving the EC-MPS and tacrolimus were recruited in this study. The time point was 2 weeks after the transplantation for all the patients. The MPA concentrations were measured with enzyme-multiplied immunoassay technique for 11 blood specimens collected predose and at 0.5, 1, 1.5, 2, 2.5, 3, 4, 6, 8, and 12 hours after the morning dose of EC-MPS. The measured AUC was calculated with these 11 points of MPA concentrations with the linear trapezoidal rule. Limited sampling strategy was used to develop models for estimated AUC in the model group (n = 18). The bias and precision of different models were evaluated in the validation group (n = 18). RESULTS C4 showed the strongest correlation with the measured AUC. The best 3 time point equation was 6.629 + 8.029 × C0 + 0.592 × C3 + 1.786 × C4 (R = 0.910; P < 0.001), whereas the best 4 time point equation was 3.132 + 5.337 × C0 + 0.735 × C3 + 1.783 × C4 + 3.065 × C8 (R = 0.959; P < 0.001). When evaluated in the validation group, the 4 time point model had a much better performance than the 3 time point model: for the 4 time point model: R = 0.873, bias = 0.505 [95% confidence interval (CI), -10.159 to 11.170], precision = 13.370 (95% CI, 5.186-21.555), and 77.8% of estimated AUCs was within 85%-115% of the measured AUCs; for the 3 time point model: R = 0.573, bias = 6.196 (95% CI, -10.627 to 23.018), precision = 21.286 (95% CI, 8.079-34.492), and 50.0% of estimated AUCs was within 85%-115% of the measured AUCs. CONCLUSIONS It demanded at least 4 time points to develop a relatively reliable model to estimate the exposure of MPA in renal transplant recipients receiving the EC-MPS. The long time span needed restricted its application, especially for the outpatients, but it could be a useful tool to guide the personalized prescription for the inpatients.
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