Drug synergy calculator

Chou–Talalay combination index for two-drug combinations from IC50 values and dose–effect data.

Single agentsSame units as the doses below
CombinationsEffect as % affected

Combination index

Dose ADose BEffectDxADxBCIInterpretation

What is drug synergy?

Two drugs are synergistic when their combined effect is greater than expected from each drug's own dose–response curve, additive when it equals the expectation andantagonistic when it falls short. The expectation has to come from a model. The most widely used one in pharmacology and cancer biology is the median-effect principle of Chou and Talalay, which summarises a whole combination experiment in one number, thecombination index (CI).

How is the combination index calculated?

CI = dA / DxA + dB / DxB

dA and dB are the doses of drug A and drug B used together that produced a given effect. DxA and DxB are the doses of A alone and B alone that would produce the same effect, read off each single-agent curve with the median-effect equation:

Dx = IC50 × ( fa / (1 − fa) )^(1/m)

fa is the fraction affected (effect ÷ 100), 1 − fa the fraction unaffected, IC50 the dose giving 50 % effect (Chou's Dm) and m the Hill-type slope of the median-effect plot. With m = 1 the equation reduces to Dx = IC50 × fa/(1 − fa), which is what the calculator uses unless you enter a fitted slope. Each combination point gets its own CI; the headline shows the mean over all evaluable points.

Worked example. IC50 A = 3.2, IC50 B = 1.5, m = 1. A combination of 1 + 0.5 gives 50 % effect, so fa/(1 − fa) = 1 and DxA = 3.2, DxB = 1.5. CI = 1/3.2 + 0.5/1.5 = 0.313 + 0.333 = 0.65, which is synergism.

How to interpret CI values

CIInterpretation
< 0.3Strong synergism
0.3 – 0.7Synergism
0.7 – 0.85Moderate synergism
0.85 – 0.9Slight synergism
0.9 – 1.1Additive effect
1.1 – 1.2Slight antagonism
1.2 – 1.45Moderate antagonism
> 1.45Antagonism

CI depends on the effect level, so a pair can be synergistic at high effect and additive at low effect. Report CI at the effect levels that matter, typically fa = 0.5, 0.75 and 0.9, rather than a single averaged value, and look at the table above the result for the trend.

How to run a combination experiment for CI

  1. Measure a dose–response curve for each drug alone and fit its IC50, and if possible the Hill slope m.
  2. Test combinations, usually at a constant dose ratio such as the ratio of the two IC50s, across several dilutions.
  3. Enter the IC50 values, the slope, and each combination's doses and effect. The calculator returns DxA, DxB and CI for every point.

When to use CI and when to use other models

  • Chou–Talalay CI is the standard when both drugs have a measurable dose–response and you can fit an IC50. It is dose-based (Loewe additivity).
  • Bliss independence compares the observed combined effect with EA + EB − EAEB, and suits drugs acting through independent mechanisms or when a single-agent curve cannot be fitted.
  • Highest single agent asks only whether the combination beats the better drug alone; it is the least demanding and the least informative.

This page implements the combination index. Doses and IC50 values must be in the same unit, and the calculation is only defined for combination points with an effect between 0 and 100 percent.

Frequently asked questions

How is the combination index (CI) calculated?

CI = dA/DxA + dB/DxB, where dA and dB are the doses of the two drugs in the combination that produced an effect, and DxA and DxB are the doses of each drug alone that would produce the same effect. Dx comes from the median-effect equation: Dx = IC50 × (fa/(1 − fa))^(1/m), where fa is the fraction affected and m the Hill slope.

What CI value means synergy?

CI below 1 indicates synergism, CI around 1 (0.9 to 1.1) an additive effect and CI above 1 antagonism. The finer bands used here follow Chou: below 0.3 strong synergism, 0.3 to 0.7 synergism, 0.7 to 0.85 moderate, 0.85 to 0.9 slight; 1.1 to 1.2 slight antagonism, 1.2 to 1.45 moderate, above 1.45 antagonism.

What is the Hill slope m and what should I enter?

m is the slope of the median-effect plot and describes the shape of each dose–response curve: m = 1 is hyperbolic, m > 1 sigmoidal. If you have not fitted it, leave it at 1, which reproduces the common simplified CI. For a rigorous analysis fit m from the single-agent dose–response data.

Can I enter the effect as inhibition or as viability?

Enter the effect as the percentage affected, for example percent inhibition or percent cell kill. If you measured viability, convert it first: effect = 100 − viability.

Why are some data points skipped?

Only combination points with both doses above zero and an effect strictly between 0 and 100 percent have a defined CI. Single-agent points and points at 0 percent or 100 percent effect are listed but cannot be evaluated.