Using response surface models to analyze drug combinations. Issue 8 (August 2021)

• Record Type: Journal Article
• Authors: Twarog, Nathaniel R.; Martinez, Nancy E.; Gartrell, Jessica; Xie, Jia; Tinkle, Christopher L.; Shelat, Anang A.
• Is Part Of: Drug discovery today. Volume 26:Issue 8(2021)
• Page Start: 2014
• Page End: 2024
• Publication Date: 2021-08
• Subjects: Combination therapy -- Synergy -- Response surface models; Drugs -- Design -- Periodicals; Drugs -- Research -- Periodicals; 615.1
• DOI: 10.1016/j.drudis.2021.06.002
• Languages: English
• ISSNs: 1359-6446

Abstract

Highlights: Index methods for identifying synergy produce structured patterns of bias. Response surface methods (RSMs) more reliably identify synergy and antagonism. RSMs can quantify two-drug therapeutic windows. Discrete and probabilistic endpoints can be evaluated using RSMs. RSMs can be extended to triplet combinations and atypical drug combination responses. Abstract: Quantitative evaluation of how drugs combine to elicit a biological response is crucial for drug development. Evaluations of drug combinations are often performed using index-based methods, which are known to be biased and unstable. We examine how these methods can produce misleadingly structured patterns of bias, leading to erroneous judgments of synergy or antagonism. By contrast, response surface models are less prone to these defects and can be applied to a wide range of data that have appeared in recent literature, including the measurement of combination therapeutic windows and the analysis of discrete experimental measures, three-way drug combinations, and atypical response behaviors.