Simulation of adaptive control of theophylline concentrations

Methods for adaptive control of drug delivery based on sparse measurements are described. Model-based open-loop control and Bayesian feedback control systems are reviewed, and an adaptive control algorithm that combines desirable features of both methods is outlined. Monte Carlo simulations are used to assess the performance of model-based open-loop control and adaptive control in the representative application of theophylline therapy. The simulation results demonstrate that adaptive control based on sparse measurements may be used to achieve and maintain a target theophylline concentration with a high degree of confidence.<>