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Pharmacokinetic Covariates Influencing Mycophenolate Area Under the Curve in a Danish Renal Transplant Population
Svend Buus1, Eva Greibe1,2, Lara Aygen Øzbay3
1Department of Clinical Biochemistry, Aarhus University Hospital, 8200 Aarhus, Denmark.
Abstract:
Background/Objectives: Mycophenolic acid (MPA) monitoring may improve organ transplant outcomes, yet clinical implementation is hindered by the complex pharmacokinetics of MPA and a lack of clarity regarding the influence of specific patient factors on drug exposure. While the area under the curve (AUC) is the gold standard for MPA monitoring, it is not easily validated or implemented in routine practice. This pilot project aimed to identify key clinical and biochemical covariates driving pharmacokinetic variability in a renal transplant population. Methods: This prospective study analyzed 103 samples from 66 kidney transplant recipients. To estimate total drug exposure (AUC), a limited sampling strategy was used with plasma samples collected at trough, and then 30 and 120 min post-dose. We performed linear univariate and multivariate regressions to evaluate the impact of patient characteristics (age, sex, body mass index (BMI)) and biochemical measurements (P-albumin, P-creatinine, estimated glomerular filtration rate (eGFR), B-tacrolimus) on MPA-AUC, peak concentrations (Cmax) and trough levels. Results: At 750 mg twice daily, the median MPA-AUC was 43.5 mg·h/L (IQR: 34.5-53.5). After adjusting for dose, P-albumin and age were independent predictors of AUC: P-albumin levels were positively associated with AUC (β = 1.849, p < 0.001), while age showed a modest negative association (β = -0.282). BMI was significantly and inversely associated with trough concentrations (β = -0.137, p = 0.011), indicating that higher BMI is linked to lower trough concentrations. Male sex was associated with significantly lower AUC and Cmax compared to females. Notably, eGFR and B-tacrolimus levels did not significantly influence MPA exposure in this cohort. Conclusions: The covariates BMI, sex, age, and P-albumin significantly influence MPA-AUC. LSS-based AUC monitoring, using 30-60 mg·h/L as a target and with consideration of a few patient-specific factors, could be a pragmatic and feasible approach to improve MMF dosing strategies in kidney transplant recipients.
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