Optimal Sampling Times for Population Pharmacokinetic Studies

Jonathan R. Stroud, Peter Müller, Gary L. Rosner

University of Chicago, MD Anderson Cancer Center, and Duke University

We propose a simulation-based approach to decision theoretic Bayesian optimal design. The underlying probability model is a population pharmacokinetic model which allows for correlated responses (drug concentrations) and patient-to-patient heterogeneity. We consider the problem of choosing sampling times for the anticancer agent paclitaxel, using criteria related to total area under the curve (AUC), time above a critical threshold, and sampling cost.

The manuscript is available in PDF format.