A BAYESIAN FORMULATION OF THE KALMAN FILTER APPLIED TO THE ESTIMATIONOF INDIVIDUAL PHARMACOKINETIC PARAMETERS

A general method of Bayesian forecasting employing the dynamic linear model has been adapted to the problem of estimating individual pharmac okinetic parameters. The Bayesian forecasting method incorporates an e fficient Kalman filter algorithm for updating pharmacokinetic paramete r estimates when further observations are made. The Kalman filter is m ore general and flexible than other Bayesian methods currently used an d simulation studies have demonstrated its practicality for three diff erent pharmacokinetic models. The method serves as the basis for a com puter program for general clinical use. (C) 1997 Academic Press.