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Novum Peptides · For laboratory research only

EC50 and maximum response: comparing curves on a shared scale

See how normalisation changes the comparison between a curve’s relative midpoint and its ability to reach a common response level.

Two curves can have identical EC50 values while producing different responses at every tested concentration. To compare them meaningfully, preserve the maximum response and the scale used to define it.

Define the midpoint using both plateaus

GraphPad’s standard-slope stimulation model defines EC50 as the concentration halfway between that curve’s Bottom and Top. The response there is not necessarily 50 in the original measurement units.GraphPad — Concentration versus response, standard-slope model (opens in a new tab)

For example, a curve rising from 20 to 100 response units has a midpoint of 60 units. A curve rising from 20 to 60 units has a midpoint of 40 units. Both can reach their own midpoint at the same concentration.

These hypothetical numbers distinguish the horizontal location of the midpoint from the vertical size of the response. Neither should replace the other in a comparison table.

When a paper uses percentages, identify the denominator. A percentage of each compound’s own response range answers a different question from a percentage of one common reference response.

Compare two original model curves

Take two hypothetical curves with zero baseline, a Hill slope of one and EC50 = 10 nM. Let A approach 100 response units and B approach 40. Using the stated model, response = Top × concentration ÷ (EC50 + concentration).

Illustrative responses on the same scale
ConcentrationCurve ACurve B
10 nM50 units20 units
40 nM80 units32 units
Very high concentrationApproaches 100Approaches 40

At 10 nM, both curves reach half of their own response range. Yet A produces 2.5 times the response of B in these constructed units.

A shared target of 50 units is reached by A at 10 nM. B never reaches it in this model because its plateau is below 50. Reporting only the two EC50 values would conceal that distinction.

The example is mathematical, not a prediction for any peptide or cell preparation.

Understand what separate normalisation removes

If A and B are each divided by their own maximum, both become curves running from 0% to 100%. At the three illustrative points, their normalised responses coincide even though their original signals differ.

This transformation can help compare curve position, but it deliberately removes the information needed to compare response magnitude. Keep the original plateaus or a common-reference analysis alongside it.

GraphPad’s normalised-response documentation states that a fixed 0–100% model requires well-supported definitions of those endpoints. Forcing that range is not a substitute for establishing it experimentally.GraphPad — Normalised stimulation-response model (opens in a new tab)

Report enough information to reconstruct the comparison

A useful results record includes EC50, the baseline, the maximum or fitted plateau, the response units and the normalisation rule. It also distinguishes a plateau supported by observations from one mainly inferred by the fit.

If the research question concerns a common response threshold, analyse that question explicitly rather than calling every curve’s own midpoint equivalent. Some curves may not reach the selected threshold within the observed range, or at all under the fitted model.

The resulting summary can be concise: the curves have similar relative midpoints but different response ranges, or different midpoints while reaching comparable maxima. That wording preserves the two dimensions without compressing them into an ambiguous claim that one peptide is simply stronger.

Sources and further detail

  1. GraphPad — Concentration versus response, standard-slope model (opens in a new tab)

    Official equation and parameter definitions read. The two example curves and all values are independently constructed arithmetic, not experimental data.

  2. GraphPad — Normalised stimulation-response model (opens in a new tab)

    Official endpoint-normalisation assumptions read. No software-specific fitting workflow or unsupported experimental plateau imposed.

Sources checked 20 September 2026. Numerical examples are illustrative unless identified as published observations. This article has not undergone independent scientific peer review.