Asynergistic Regression Based on Maximized Rank Correlation

The property of synergy and its detection are discussed. A response surface is said to possess synergy if it is monotone in each argument and its level curves are convex. Detecting this property is particularly useful in the study of combination drug therapies where the goal is enhanced response or diminished side effect. One way to detect synergy is to fit a surface with linear level curves under the assumption of asynergy and observe the residuals. We explore an algorithm to accomplish this asynergistic regression via a reduction in dimensionality and connections to semiparametric monotonic linear index models. We see that the asynergistic model is a confounded version of the monotonic linear index model where the