Similar to SynergyFinder 1.0, version2.0 supports interactive analysis of two-drug combination data, based on the user-uploaded dose–response matrices (Figure 1A). As a result, interactive synergy distribution plots, together with summary synergy scores, are generated for each pair of drugs. In addition, SynergyFinder 2.0 supports the analysis of higher-order drug combinations by implementing interactive dose–response tensors for each triplet of the drugs (Figure 1B). Furthermore, barplots of synergy scores are produced separately for each sub-combination (pairs, triplets, etc.), depending on the number of drugs in the combinations. For more systematic analysis of the contribution of each drug to the joint higher-order combination effect, 3D synergy landscape plots for each of the two-drug sub-combinations are visualized enabling their further investigation (Figure 1C).
SynergyFinder 2.0. implements four reference synergy models (HSA, Bliss, Loewe and ZIP), and their extensions to calculate synergy scores for higher-order combination data. These models quantify the degree of synergy either as the excess over the maximum single drug response (HSA), multiplicative effect of single drugs as if they acted independently (Bliss), expected response corresponding to an additive effect as if the single drugs were the same compound (Loewe), and expected response corresponding to the effect as if the single drugs did not affect the potency of each other (ZIP). More specifically, the following higher-order formulations were used to quantify the drug combination synergy (S) for the measured multi-drug combination effect between N drugs :
Here, are the measured responses of the single drugs, while a, b and n are the doses of the single drugs required to produce the combination effect . For the ZIP model, is the dose of Nth drug fitted with four-parameter log-logistic (4PL) function, whereas is the dose that produces the half-maximum effect (also known as relative or , depending on the readout), and is the shape parameter indicating the slope of the dose–response curve.
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