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.