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

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

J Heart Lung Transplant

Division of Cardiothoracic Surgery, Department of Surgery, Washington University, St. Louis, Missouri; Department of Pathology and Immunology, Washington University, St. Louis, Missouri.

Published: January 2025

AI Article Synopsis

  • * A study of 60 lung transplant patients examined how genetic factors (like SLCO1B3 polymorphisms) and clinical data related to MPA levels, finding strong associations with dosage and other variables.
  • * The researchers developed a new limited sampling strategy for better predicting MPA exposure, which could enhance drug monitoring and personalized treatment for patients in the future.

Article Abstract

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) 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 (C, C and C) were strongly associated with MPA AUC (R67%, 67% and 68% respectively). Clinical and genetic factors associated with MPA AUC 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 C and achieved an R value of 80%. The best integrated limited-sampling strategy included C, C, and C and achieved an R value of 90%.

Conclusions: An integrated limited sampling strategy (LSS) for MPA allows increased accuracy in prediction of MPA AUC 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.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.healun.2024.09.007DOI Listing

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