Mixture Model for Individual and Combined Data Using Estimating Equations

When performing analysis of individual data on the application of a particular drug, it is useful to study the within variability. But when two drugs are used in combination, it is of more interest to study any combination effects on the subjects. In this paper we consider a new analytical framework that is a combination of the individual and combined data analyses, based on an estimating equation approach. The proposed analyses utilize a stochastic model for a two-drug combination and derive the mean and the variance terms based on Ito’s calculus. The proposed estimation methods are used to estimate model parameters from both individual and combined data, and they provide the basis for model free synergy tests. The strength of the fit of the model to the data is examined by statistical measures and the graphical method. Simulation studies were performed to show the strengths of the proposed approach in estimating the model parameters. A synergy test of the model fitted by the individual subjects confirmed that the combination of the isomers under study is synergistic in nature.