Interaction Analysis of Three Combination Drugs via a Modified Genetic Algorithm

Abstract

Few articles have been written on analyzing and visualizing three-way interactions between drugs. Although it may be quite straightforward to extend a statistical method from two-drugs to three-drugs, it is hard to visually illustrate which dose regions are synergistic, additive, or antagonistic, due to a four-dimensional (4-D) problem of plot- ting three-drug dose regions plus a response. This problem can be converted and solved by showing some dose regions of our interest in a 3-D, three-drug dose regions. We propose to apply a modified genetic algorithm (MGA) to construct the dose regions of interest after fitting the response surface to the interaction index (II) by a semiparametric method, the model robust regression method (MRR). A case study with three anti-cancer drugs in an in vitro experiment is employed to illustrate how to find the dose regions of interest. For example, suppose researchers are interested in visualizing where the synergistic areas with II ≤ 0:4 are in 3-D. After fitting a MRR model to the calculated II, the MGA procedure is used to collect those feasible points that satisfy the estimated values of II ≤ 0:4. All these feasible points are used to construct the approximate dose regions of interest in a 3-D.

Description

Keywords

Genetic Algorithm (GA), Interaction Index (II), Model Robust Regression (MRR), Synergism, Three-drug combination, Viability

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