An integrated sampling strategy for therapeutic mycophenolic acid monitoring in lung transplant recipients

Background

Mycophenolic Acid (MPA) is the most used anti-proliferative in lung transplantation, but its pharmacokinetic (PK) variability has precluded therapeutic drug monitoring. Both genetic and clinical factors have been implicated in MPA variability. This study aimed to integrate genetic and clinical factors with PK measurements to quantify MPA exposure.

Methods

We performed 12-hour pharmacokinetic analysis on 60 adult lung transplant recipients maintained on MPA for immunosuppression. We genotyped a SLCO1B3 polymorphisms previously associated MPA metabolism and collected relevant clinical data. We calculated area under the curve (AUC_0–12) and performed univariate linear regression analysis to evaluate its association with genetic, clinical, and pharmacokinetic variables. We performed lasso regression analysis to create final AUC estimation tools.

Results

PK-only measurements obtained 2, 3, and 8 hours after MPA administration (C₂, C_3, and C₈) were strongly associated with MPA AUC_0–12 (R² 67%, 67% and 68% respectively). Clinical and genetic factors associated with MPA AUC_0–12 included the MPA dose (p = 0.001), transplant diagnosis (p = 0.015), SLCO1B3 genotype (p = 0.049), and body surface area (p = 0.050). The best integrated single-sampling strategy included C₂ and achieved an R² value of 80%. The best integrated limited-sampling strategy included C₀, C_0.25, and C₂ and achieved an R² value of 90%.

Conclusions

An integrated limited sampling strategy (LSS) for MPA allows increased accuracy in prediction of MPA AUC_0–12 compared to PK-only modeling. Validation of this model will allow for clinically feasible MPA therapeutic drug monitoring and help advance precision management of MPA.