Journal of clinical pharmacy and therapeutics
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Therapeutic drug monitoring (TDM) of valproate (VAL) is important in the optimization of its therapy. The aim of the present work was to evaluate the ability of TDM using model-based, goal-oriented Bayesian adaptive control for help in planning, monitoring, and adjusting individualized VAL dosing regimens. USC*PACK software and routine TDM data were used to estimate population and individual pharmacokinetics of two commercially available VAL formulations in epileptic adult and pediatric patients on chronic VAL monotherapy. ⋯ These nonparametric expectation maximization (NPEM) population models thus provide a useful tool for planning an initial dosage regimen of VAL to achieve desired target peak and trough serum concentration goals, coupled with TDM soon thereafter, as a peak-trough pair of serum concentrations, and Bayesian fitting to individualize the PK model for each patient. The nonparametric PK parameter distributions in these NPEM population models also permit their use by the new method of 'multiple model' dosage design, which allows the target goals to be achieved specifically with maximum precision. Software for both types of Bayesian adaptive control is now available to employ these population models in clinical practice.