The pharmacokinetics and pharmacodynamics of mycophenolate mofetil in younger and elderly renal transplant recipients

Tang, Jiang Tao; Winter, Brenda C M de; Hesselink, Dennis A.; Sombogaard, Ferdi; Wang, Lan Lan; Gelder, Teun van

doi:10.1111/bcp.13154

Cited by 33 publications

(39 citation statements)

References 45 publications

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“…Concerning the influence of age and gender on the pharmacokinetics of MPA, Tang et al [54] reported that age did not significantly affect the pharmacokinetics or pharmacodynamics of MPA. However, Yoo et al [55] reported that MPA exposure was associated with developmental changes in children, and demonstrated that small children are at a significantly greater risk of low MPA trough levels than adolescents, highlighting the need for pharmacokinetic monitoring of MPA.…”

Section: Discussionmentioning

confidence: 99%

Population pharmacokinetics and Bayesian estimation of mycophenolic acid concentrations in Chinese adult renal transplant recipients

Zhou

Wang

et al. 2017

Acta Pharmacol Sin

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Mycophenolate mofetil (MMF) is an important immunosuppressant used in renal transplantation, and mycophenolic acid (MPA) is the active component released from the ester prodrug MMF. The objective of this study was to investigate the population pharmacokinetics of mycophenolic acid (MPA) following oral administration of MMF in Chinese adult renal transplant recipients and to identify factors that explain MPA pharmacokinetic variability. Pharmacokinetic data for MPA and covariate information were retrospectively collected from 118 patients (79 patients were assigned to the group for building the population pharmacokinetic model, while 39 patients were assigned to the validation group). Population pharmacokinetic data analysis was performed using the NONMEM software. The pharmacokinetics of MPA was best described by a two-compartment model with a first-order absorption rate with no lag time. Body weight and serum creatinine level were positively correlated with apparent clearance (CL/F). The polymorphism in uridine diphosphate glucuronosyltransferase gene, UGT2B7, significantly explained the interindividual variability in the initial volume of distribution (V/F). The estimated population parameters (and interindividual variability) were CL/F 18.3 L/h (34.2%) and V/F 27.9 L (21.3%). The interoccasion variability was 13.7%. These population pharmacokinetic data have significant clinical value for the individualization of MMF therapy in Chinese adult renal transplant patients.

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Section: Discussionmentioning

confidence: 99%

Population pharmacokinetics and Bayesian estimation of mycophenolic acid concentrations in Chinese adult renal transplant recipients

Zhou

Wang

et al. 2017

Acta Pharmacol Sin

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“…The use of tacrolimus is hampered by its narrow therapeutic index with large intra‐ and interpatient variability in its pharmacokinetics that requires therapeutic drug monitoring (TDM) to individualize the dose to prevent toxicity and rejection . Multiple factors influence the clearance (CL) of tacrolimus, including cytochrome P450 (CYP) 3A genotype , haematocrit , age , bodyweight, ethnicity and drug–drug interactions . In routine clinical practice, the tacrolimus starting dose is based solely on bodyweight, even though the available evidence is scarce .…”

Section: Introductionmentioning

confidence: 99%

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

Andrews

Hesselink

Schaik

et al. 2019

Brit J Clinical Pharma

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Aims The aims of this study were to describe the pharmacokinetics of tacrolimus immediately after kidney transplantation, and to develop a clinical tool for selecting the best starting dose for each patient. Methods Data on tacrolimus exposure were collected for the first 3 months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed‐effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. Results A total of 4527 tacrolimus blood samples collected from 337 kidney transplant recipients were available. Data were best described using a two‐compartment model. The mean absorption rate was 3.6 h−1, clearance was 23.0 l h–1 (39% interindividual variability, IIV), central volume of distribution was 692 l (49% IIV) and the peripheral volume of distribution 5340 l (53% IIV). Interoccasion variability was added to clearance (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower haematocrit levels were identified as covariates enhancing tacrolimus clearance. Cytochrome P450 (CYP) 3A5 expressers had a significantly higher tacrolimus clearance (160%), whereas CYP3A4*22 carriers had a significantly lower clearance (80%). From these significant covariates, age, BSA, CYP3A4 and CYP3A5 genotype were incorporated in a second model to individualize the tacrolimus starting dose: Dose0.25em()mg=2220.25emng0.25emnormalh0.25emml–1*0.5em22.50.25emnormall0.25emnormalh–1*[](),1.0if0.25emCYP3normalA5*3/*30.25emor0.25em(),1.62if0.25emCYP3normalA5*1/*30.25emor0.25emCYP3normalA5*1/*1*[](),1.0if0.25emCYP3normalA4*10.25emor unknown0.25emor0.25em(),0.814if0.25emCYP3normalA4*22*Age56−0.50*BSA1.930.72/1000 Both models were successfully internally and externally validated. A clinical trial was simulated to demonstrate the added value of the starting dose model. Conclusions For a good prediction of tacrolimus pharmacokinetics, age, BSA, CYP3A4 and CYP3A5 genotype are important covariates. These covariates explained 30% of the variability in CL/F. The model proved effective in calculating the optimal tacrolimus dose based on these parameters and can be used to individualize the tacrolimus dose in the early period after transplantation.

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“…Chiarelli et al 39 reported a similar increase in nonstimulated PBMC when stable renal transplant recipients were monitored for 15 months. Tang et al observed no increase in predose IMPDH-capacity from day 6 to week 20 after transplantation, 50 suggesting that this increase mainly occurs after week 20.…”

Section: Discussionmentioning

confidence: 99%

“…We have shown that adenine and guanine pools are highly regulated (Figure 3) indicating that adenine levels are also influenced by IMPDH activity. Several studies normalize the XMP production to AMP [50][51][52][53][54][55][56] since this is technically attractive. However, careful interpretation is suggested in light of coregulation between the guanine and adenine pools in lymphocytes.…”

Section: Discussionmentioning

confidence: 99%

Pharmacodynamic assessment of mycophenolic acid in resting and activated target cell population during the first year after renal transplantation

Klaasen

Bergan

Bremer

et al. 2020

Brit J Clinical Pharma

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Aims:To explore the pharmacodynamics of mycophenolic acid (MPA) through inosine monophosphate dehydrogenase (IMPDH) capacity measurement and purine levels in peripheral blood mononuclear cells (PBMC) longitudinally during the first year after renal transplantation (TX).Methods: PBMC were isolated from renal recipients 0-4 days prior to and 6-9 days, 5-7 weeks and 1 year after TX (before and 1.5 hours after dose). IMPDH capacity and purine (guanine and adenine) levels were measured in stimulated and nonstimulated PBMC.Results: Twenty-nine patients completed the follow-up period, of whom 24 received MPA. In stimulated PBMC, the IMPDH capacity (pmol 10 −6 cells min −1 ) was median (interquartile range) 127 (95.8-147) before TX and thereafter 44.9 (19.2-93.2) predose and 12.1 (4.64-23.6) 1.5 hours postdose across study days after TX. The corresponding IMPDH capacity in nonstimulated PBMC was 5.71 (3.79-6.93), 3.35(2.31-5.62) and 2.71 (1.38-4.08), respectively. Predose IMPDH capacity in nonstimulated PBMC increased with time, reaching pre-TX values at 1 year. In stimulated PBMC, both purines were reduced before (median 39% reduction across days after TX) and after (69% reduction) dose compared to before TX. No alteration in the purine levels was observed in nonstimulated PBMC. Patients needing dose reductions during the first year had lower pre-dose IMPDH capacity in nonstimulated PBMC (1.87 vs 3.00 pmol 10 −6 cells min −1 , P = .049) at 6-9 days. Conclusion:The inhibitory effect of MPA was stronger in stimulated PBMC. Nonstimulated PBMC became less sensitive to MPA during the first year after TX. Early IMPDH capacity appeared to be predictive of dose reductions.The authors confirm that the Principal Investigator for this paper is Karsten Midtvedt MD PhD and that he had direct clinical responsibility for patients.

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The pharmacokinetics and pharmacodynamics of mycophenolate mofetil in younger and elderly renal transplant recipients

Abstract: Age did not significantly affect the PK or PD of MPA. It is unlikely that the lower incidence of acute rejection in elderly patients, or the higher risk to die from a severe infection in elderly patients is due to different handling of MPA in the elderly.

Cited by 33 publications

References 45 publications

Population pharmacokinetics and Bayesian estimation of mycophenolic acid concentrations in Chinese adult renal transplant recipients

Population pharmacokinetics and Bayesian estimation of mycophenolic acid concentrations in Chinese adult renal transplant recipients

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

Pharmacodynamic assessment of mycophenolic acid in resting and activated target cell population during the first year after renal transplantation

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