The concepts of IC50 & EC50 are fundamental khổng lồ pharmacology. The EC50 is the concentration of a drug that gives half-maximal response. The IC50 is the concentration of an inhibitor where the response (or binding) is reduced by half.

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Seems simple enough. But when you actually go to lớn fit data khổng lồ determine these values,there are several complexities and ambiguities.

The rest of this article is about IC50 (I for inhibition, for downward sloping dose-response curves). All the ideas can be applied to stimulatory curves & EC50 (E for effective) as well. Just stand on your head when you view the figures.

The ideal situation

This figure shows an ideal situation:


The green symbols show measurements made with controls. The ones on the left (Blank) have no inhibitor, so define "100%". The ones on the right are in the presence of a maximal concentration of a standard inhibitor, so define "0%". The data of the experimental dose-response curve (red dots) extend all the way between the two control values.

When fitting this curve, you need khổng lồ decide how lớn fit the vị trí cao nhất plateau of the curve. You have three choices:

Fit the data only, ignoring the Blank control values.Average the Blank control values, and set the parameter Top khổng lồ be a constant value equal lớn the mean of the blanks.Enter the blank values as if they were part of the dose-response curve. Simply enter a low dose, perhaps 10-10 or 10-11. You can't enter zero, because zero is not defined on a log scale.

The results will be very similar with any of these methods, because the data form a complete dose-response curve with a clear đứng đầu plateau that is indistinguishable from the blank. I prefer the third method, as it analyzes all the data, but that is not a strong preference.

Similarly, there are three ways to giảm giá with the bottom plateau: Fit the data only, phối Bottom khổng lồ be a constant equal khổng lồ theaverage of the NS controls, and put the NS controls into the fit as if they were a very high concentration of inhibitor.

That is the ideal situation. There is no ambiguity about what IC50 means.

A situation where IC50 can be defined in two ways

This figure shows an unusual situation where the inhibition curve plateaus well above the control values (NS) defined by a high concentration of a standard drug. This leads to lớn alternative definitions of IC50.


Clearly, a single value cannot summarize such a curve. You'd need at least two values, one to quantify the middle of the curve (the drug's potency) & one to lớn quantify how low it gets (the drug's maximum effect).

The graph above shows two definitions of the IC50.

The relative IC50 is by far the most common definition, và the adjective relative is usually omitted. It is the concentration required to lớn bring the curve down to point half way between the top and bottom plateaus of the curve. The NS values are totally ignored with this definition of IC50. This definition is the one upon which classical pharmacological analysis of agonist & antagonist interactions is based. With appropriate consideration of the biological system và concentrations of interacting ligands, estimated Kd values can often be derived from the IC50 value defined this way (not so for the "so-called absolute IC50" mentioned below).

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The concentration that provokes a response halfway between the Blank and the NS value issometimes calledthe absolute IC50, The horizontal dotted lines show how 100% & 0% are defined, which then defines 50%. This term is not entirely standard. Since this value does not quantify the potency of a drug, the authors of the International Union of Pharmacology Committee on Receptor Nomenclature (1) think that the concept of absolute IC50 (and that term) is not useful (R. Neubig, personal communication). I agree.

The concept (but not the term "absolute IC50") is used to quantify drugs that slow cell growth. The abbreviation GI50 is used for what we điện thoại tư vấn here the absolute IC50. It is also used by the Environmental Protection Agency (EPA) in evaluatingendocrine disrupters(Appendix A).They use the term IC50 to refer to lớn the absolute IC50, & the term EC50 khổng lồ refer to the relative IC50. They don't use the terms relative & absolute.

If you really want khổng lồ use the absolute IC50, here are instructionsfor fitting a curve to lớn find it.

Incomplete dose-response curves


Any attempt lớn determine an IC50 by fitting a curve khổng lồ the data in the graph above will be useless. A curve fitting program might, or might not, be able to fit a dose-response curve to the data. But if the curve fits, the value of the IC50 is likely khổng lồ be meaningless and have a very wide confidence interval.The data simply don't form a vị trí cao nhất plateau (which would define 100) or a bottom plateau (which would define 0). If data haven't defined 100 or 0, then 50 is undefined too, as is the IC50.

If you also have control values that define 100 và 0, then the curve can be easily fit.The curve below was created by fitting a dose response curve, but constraining the đứng đầu plateau to lớn be a constant value equal to lớn the mean of the Blanks values, & the Bottom plateau equal lớn the mean of the NS values.


The value of the IC50 fit this way only makes sense if you assume that higher concentrations of the inhibitor would eventually inhibit down to lớn the NS values. That is an assumption that can't be tested with the data at hand.

The distinction between relative và absolute IC50 doesn't really apply to lớn these data. Because the data don't define a bottom plateau, the IC50 must be defined relative to lớn the NS control values.

Fitting normalized data

As you can see from all the examples above, it is not necessary lớn normalize the data khổng lồ run from100% down to lớn 0%. You can fit curves using data in their natural units. A common mistake is lớn assume that fitting dose-response curves requires that data first be normalized.

If you choose lớn normalize your data, it is essential that you think through carefully (and document in methods sections of papers) how 100% and 0% are defined. There are three strategies you can use:

From external controls (Blank & NS in the figures above). Since these values are so important, consider measuring these controls with more replicates than used for the rest of the experiment.From very low & very high concentrations of the test substance.From the plateaus of nonlinear regression. Fit the curve first, và then use the best-fit values of the Top and Bottom plateau khổng lồ normalize the data.

If you fit normalized data, you probably want Prism lớn force the curve to go from 100 down lớn 0. It won't know to bởi this, unless you tell it. Don't make the common mistake of normalizing your data, but not constraining the curve lớn go from 100 down to lớn 0. You can constrain the curve in two ways:

Choose lớn fit to lớn a normalized model. The normalized models built in to lớn Prism always go between 0 và 100.Use a more general model, go khổng lồ the Constrain tab, & set Bottom to a constant value of 0.0 & Top to a constant value of 100.0.

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The concept of IC50 (or EC50) is a bit ambiguous unless you clearly specify which values define 100% & 0%.


1. R. R. Neubig et al. International Union of Pharmacology Committee on Receptor Nomenclature and Drug Classification. XXXVIII. Update on terms & symbols in quantitative pharmacology. Pharmacol Rev (2003) vol. 55 (4) pp. 597-606