Abstract
In synergy studies, one focuses on compound combinations that promise a synergistic or antagonistic effect. With the help of high-throughput techniques, a huge amount of compound combinations can be screened and filtered for suitable candidates for a more detailed analysis. Those promising candidates are chosen based on the deviance between a measured response and an expected non-interactive response. A non-interactive response is based on a principle of no interaction, such as Loewe Additivity or Bliss Independence. In a previous study, we introduced, an explicit formulation of the hitherto implicitly defined Loewe Additivity, the so-called Explicit Mean Equation. In the current study we show that this Explicit Mean Equation outperforms the original implicit formulation of Loewe Additivity and Bliss Independence when measuring synergy in terms of the deviance between measured and expected response, called the lack-of-fit. Further, we show that computing synergy as lack-of-fit outperforms a parametric approach. We show this on two datasets of compound combinations that are categorized into synergistic, non-interactive, and antagonistic.
Highlights
When combining a substance with other substances, one is generally interested in interaction effects
Using the two methods of computing the synergy score, the parametric one (Parametrized Synergy) and the lack-of-fit one (Lack-of-Fit Synergy), we compute synergy scores for all records of the two datasets introduced in Material
This coefficient computes the rank correlation between the data as originally categorized by Yadav et al (2015) and Cokol et al (2011) and the computed synergy scores resulting from the two methods introduced in Parametrized Synergy and Lack-ofFit Synergy
Summary
When combining a substance with other substances, one is generally interested in interaction effects. From data generated with high-throughput techniques, one is confronted with massive compound interaction screens. From those screens, one needs to filter for interesting candidates that exhibit an interaction effect. Based on that preprocessing scan, those filtered combination candidates can be examined in greater detail. In such a quick scan, one focuses uniquely on the measured response and not on possible mechanisms of action of each compound
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