Department of Mathematics, Imperial College of Science, Technology and Medicine, London, UK
In this talk I will consider the situation where we wish to adjust the dosage regimen of a patient based on (in general) sparse concentration measurements taken 'on-line'. A Bayesian decision theory approach is taken which requires the specification of a prior distribution and an appropriate loss function. A method for obtaining samples from the posterior distribution of the pharmacokinetic parameters of the patient is given. In general, these samples are used to obtain a Monte Carlo estimate of the expected loss which is then minimized with respect to the dosage regimen.