Drug Synergy

When two drugs are given together, the question is whether their combined effect is more than the sum of their parts. Synergy analysis takes a dose-by-dose response matrix and scores every combination against a null model of independent action.

What it measures

The difference between the response you observed and the response a reference model predicts if the two drugs acted independently. Positive scores are synergy, negative scores are antagonism, zero is additivity. Gradiance computes the major reference models:

• Bliss independence - for drugs with distinct mechanisms.
• Loewe additivity - for drugs assumed to share a mechanism (the dose-equivalence model).
• ZIP - the zero-interaction potency model, which blends the strengths of Bliss and Loewe.

Data you upload

• A dose-response matrix: drug A concentrations down the rows, drug B concentrations across the columns, response values in each cell. A long-format table (doseA, doseB, response) works just as well.
• The single-agent dose series for each drug (the matrix edges usually supply these).

What you get back

• A synergy heatmap over the dose grid, so you can see where the interaction lives.
• A summary synergy score for the whole matrix, plus the most synergistic region.
• The single-agent potencies (IC₅₀/EC₅₀) used as the baseline for the reference model.

Method note

Each model encodes a different assumption about what “no interaction” means, so they can disagree - reporting more than one is good practice. The agent fits the single-agent curves first (using the same machinery as a standalone dose-response fit), then scores each combination cell against the chosen null model and aggregates to a matrix-level synergy score.

Related

Single-compound potency lives in Dose-Response. For all-or-nothing endpoints rather than graded response, see Quantal Dose-Response.