A Bayesian pharmacometric approach for personalized medicine — A proof of concept study with simulated data

The objective of this research program is to optimize drug dose regimen for an individual, using minimally invasive clinical testing, in order to reduce both the total cost of treatment and the risk for over or under-medication using a Bayesian modeling approach. The challenge is to extract the PharmacoKinetic/PharmacoDynamic(PK/PD) parameters for an individual from population level plasma concentration information gathered in clinical trials along with one or two plasma samples from an individual and use these personalized parameters in determining most appropriate dose regimen for a specific patient. In this study we illustrate the plausibility of our methodology through a proof-of-concept study with simulated data.