AI Article Synopsis

  • Mycophenolic acid is commonly used to treat lupus nephritis but has varying effects among individuals, prompting researchers to create a population pharmacokinetic (popPK) model and limited sampling strategy (LSS) for better drug monitoring in Indian patients.
  • The study involved collecting blood samples from 51 patients at different times after taking the medication to analyze how their bodies process it and to find key factors affecting variability.
  • The results showed that a 1-compartmental model was the best fit for the data, and the optimal LSS involving samples taken at 1, 2, and 4 hours postdose effectively estimated drug levels, improving therapeutic drug monitoring practices.

Article Abstract

Background: Mycophenolic acid is widely used to treat lupus nephritis (LN). However, it exhibits complex pharmacokinetics with large interindividual variability. This study aimed to develop a population pharmacokinetic (popPK) model and a 3-sample limited sampling strategy (LSS) to optimize therapeutic drug monitoring in Indian patients with LN.

Methods: Five blood samples from each LN patient treated with mycophenolic acid were collected at steady-state predose and 1, 2, 4, and 6 hours postdose. Demographic parameters were tested as covariates to explain interindividual variability. PopPK analysis was performed using Monolix and the stochastic approximation expectation-maximization algorithm. An LSS was derived from 500 simulated pharmacokinetic (PK) profiles using maximum a posteriori Bayesian estimation to estimate individual PK parameters and area under the curve (AUC). The LSS-calculated AUC was compared with the AUC calculated using the trapezoidal rule and all the simulated samples.

Results: A total of 51 patients were included in this study. Based on the 245 mycophenolic acid concentrations, a 1-compartmental model with double absorption using gamma distributions best fitted the data. None of the covariates improved the model significantly. The model was internally validated using diagnostic plots, prediction-corrected visual predictive checks, and bootstrapping. The best LSS included samples at 1, 2, and 4 hours postdose and exhibited good performances in an external dataset (root mean squared error, 21.9%; mean bias, -4.20%).

Conclusions: The popPK model developed in this study adequately estimated the PK of mycophenolic acid in adult Indian patients with LN. This simple LSS can optimize TDM based on the AUC in routine practice.

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Source
http://dx.doi.org/10.1097/FTD.0000000000001213DOI Listing

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