Potency vs Efficacy: EDAIC Dose–Response Curves

Potency asks how much drug is needed for a specified effect. Efficacy concerns the maximum response achievable in the system being studied. A curve further to the left can indicate greater potency without a higher maximum response.

For EDAIC revision, always name the endpoint and read the axes before comparing curves. The fictional experiments here are educational models, not clinical dose comparisons.

Read the graph in a fixed order

First inspect the horizontal axis. Is it administered dose or concentration, and is the scale linear or logarithmic? Next inspect the vertical axis. Is it an absolute change, a percentage of a shared reference maximum, or a percentage of each drug's own maximum?

Emax is the maximum response in the specified assay. EC50 is the concentration producing half of that drug's Emax. A lower EC50 commonly indicates greater potency within a comparable experiment, but different endpoints or differently normalised curves can make a simple visual ranking misleading. MSD describes the main dose–response features.

Do not identify EC50 with receptor-binding affinity. A response also depends on receptor activation and downstream signalling. Binding and response experiments measure different things; this pharmacology review examines the distinction between affinity and efficacy.

Worked example: two equal ceilings

Consider two fictional agonists tested in the same tissue preparation. The endpoint is a response recorded in arbitrary units. Both have Emax 100 units. Drug A has EC50 2 nmol/L; drug B has EC50 20 nmol/L.

For a deliberately simple model with Hill coefficient one and no baseline response:

Response = Emax × C ÷ (EC50 + C).

At C = 2 nmol/L:

• A gives 100 × 2 ÷ (2 + 2) = 50 units.
• B gives 100 × 2 ÷ (20 + 2) = 9.1 units.

At C = 20 nmol/L:

• A gives 100 × 20 ÷ 22 = 90.9 units.
• B gives 100 × 20 ÷ 40 = 50 units.

A reaches the same half-maximum response at one-tenth the concentration: it is more potent in this assay. Both approach the same 100-unit maximum, so these data do not show greater maximal efficacy for A.

The nmol/L units are essential. Comparing an axis in mol/L with another in mg/L requires additional information, including molecular mass. A visually smaller numerical concentration is not automatically a more potent drug when the units differ.

Add a lower maximum and watch the denominator

Introduce drug C with Emax 40 units and EC50 1 nmol/L in the same preparation. At 1 nmol/L, it produces 20 units: half of its own maximum. At 9 nmol/L, its response is 40 × 9 ÷ 10 = 36 units.

It cannot reach 50 units in this model, regardless of concentration. Calling it “the strongest” because it has the lowest EC50 mixes two separate properties. A useful comparison states both facts: low EC50, lower maximal response.

Now imagine each curve is separately scaled so its own Emax becomes 100%. C's ceiling would appear identical to A's on that normalised plot. The displayed percentages would conceal the difference in absolute responses. Check the figure legend before judging efficacy.

Antagonists and partial agonists

In the ideal reversible competitive-antagonism model, more agonist is required for a given response, producing a rightward shift while the achievable maximum is preserved. That is a statement about a controlled concentration–response experiment, not permission to escalate a drug indefinitely in a patient. IUPHAR explains the model and its assumptions.

A partial agonist produces a lower maximal response than a full agonist in the same system. Its behaviour depends on the receptor and signalling context; a simple graph should not be turned into a universal claim about every tissue. When two ligands compete at the same site, a lower-efficacy ligand can reduce the response to a higher-efficacy agonist. This is why “agonist” and “increases every existing response” are not equivalent descriptions. See the receptor-theory review.

Original statement practice

1. Drug A is more potent than B for the measured endpoint. True: its EC50 is lower under matched conditions.
2. Drug A has twice the maximal efficacy of B. False: both maxima are 100 units.
3. Drug C produces 50 units at its EC50. False: it produces 20 units, half its own 40-unit maximum.
4. Equal separately normalised maxima prove equal absolute responses. False: normalisation can hide the difference.
5. The EC50 values alone establish which drug is clinically safest. False: no adverse-effect or therapeutic-window information is provided.

For a retrieval exercise, sketch A and B from memory on the same concentration axis, label the two EC50 values, then add C without rescaling the response axis. Explain each comparison aloud using “for this endpoint in this system”. That phrase keeps the conclusion tied to the evidence. Revisit the pharmacology study map, then use EDAIC-style practice to test the distinction without relying on a familiar graph.

Sources

• MSD Manual: Dose-Response Relationships.
• IUPHAR Pharmacology Education Project: Pharmacodynamics.
• Making Sense of Pharmacology: Inverse Agonism and Functional Selectivity.

Prepared with AI assistance for examination revision; this article is not a patient-care protocol or a substitute for current primary guidance. Sources checked 7 October 2026.