Optimization of Mycophenolic Acid Therapy Using Clinical Pharmacometrics

Abstract

  Novel approaches applying quantitative clinical pharmacology or pharmacometrics have been increasingly embraced by the drug development community in the last decade. State-of-the-art population modeling and simulation enable better characterization and prediction of drug exposure. For narrow therapeutic index drugs such as mycophenolic acid (MPA) which exhibit large inter-individual variation in drug exposure, pharmacometric analysis can be of great clinical benefit. This review aims to summarize the recent progress of using pharmacometric tools toward individualized MPA therapeutics. The population pharmacokinetic models including those developed for special populations and Bayesian estimators for therapeutic drug management will be reviewed. Special attention will be given to new methodologies such as nonparametric population modeling and the physiological-based pharmacokinetics modeling (PBPK) that emerged recently as alternatives to the parametric population approach to predict MPA exposure. D-Optimal design strategies applied in clinical study design will also be reviewed. Lastly, the potential of using a pharmacodynamic based optimal treatment strategy by focusing on MPA's target enzyme inosine monophosphate dehydrogenase (IMPDH) will be discussed.