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Quantification of the Immunosuppressant Tacrolimus on Dried Blood Spots Using LC-MS/MS
Published on: November 8, 2015
Population Pharmacokinetic Modelling of Unbound Mycophenolic Acid and its Glucuronide in Adult Kidney Transplant
Yan Rong1, Ala'A Al-Dajani1, Jinal Adhiya1
1Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada.
Background And Objective:
The first-line immunosuppressant mycophenolic acid (MPA) is characterised by complex, variable pharmacokinetics (PK) with high protein binding, where the relationship between total and unbound drug can be difficult to predict early post-transplant. We developed a novel population pharmacokinetic (popPK) model for unbound MPA and its major glucuronide (MPAG) in adult kidney transplant recipients to characterise the pharmacologically relevant unbound drug.
Methods:
This prospective, observational study included de novo adult kidney transplant recipients on steady-state oral mycophenolate mofetil with tacrolimus (±prednisone). The PopPK modelling was performed using stochastic approximation expectation-maximisation, and simulations evaluated the impact of significant covariates on unbound MPA area-under the concentration-time curves (AUC)0-12h.
Results:
Forty-one participants (aged 48.3±12.1 years, mean±SD) from 63 occasions representing three study visits (~1, ~3, and ~6 months post-transplant) were enrolled. A structural model based on first-order absorption (ka=4 h-1, fixed) with lag time (Tlag=0.38 [0.11-0.56] h; estimate [95% confidence interval]), two-compartments for unbound MPA (volume V1=4213.41 [2675.47-8337.53] L; V2=23321.08 [4334.80-54459.85] L; clearance=4.87 L h-1, fixed), one-compartment for unbound MPAG (transfer rate=0.18 [0.15-0.21] h-1; V3=18.23 [12.40-32.77] L; clearance=5.64 [4.14-10.70] L h-1), and constant error with between-subject and between-occasion effects best described the data. Of 19 covariates, "age" and "alkaline phosphatase" influenced unbound MPA V2 (β=3.62 [-0.61-8.13]) and unbound MPAG clearance (β=-0.98 [-1.51-(-)0.21]), respectively. Simulations showed age-dependent reductions in unbound MPA AUC0-12h and age/dose-dependent shifts in the proportions of patients within the theoretical unbound MPA target range.
Conclusions:
A popPK model simultaneously characterising unbound MPA and MPAG was developed and evaluated. Simulations indicated that age-dependent MPA dosing may be warranted to optimise unbound therapeutic exposures.
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