The concepts of IC50 & EC50 are fundamental lớn 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.quý khách vẫn xem: Ic50 là gì

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

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

**The ideal situation**

This figure shows an ikhuyễn mãi giảm giá 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) extkết thúc all the way between the two control values.

When fitting this curve, you need lớn decide how to lớn fit the top plateau of the curve sầu. You have three choices:

Fit the data only, ignoring the*Blank*control values.Average the

*Blank*control values, và phối the parameter

*Top*to lớn be a constant value equal to 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 khung a complete dose-response curve sầu with a clear top 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 lớn khuyễn mãi giảm giá with the bottom plateau: Fit the data only, phối Bottom khổng lồ be a constant equal to lớn theaverage of the NS controls, và put the NS controls inkhổng lồ the fit as if they were a very high concentration of inhibitor.

That is the igiảm giá khuyến mãi 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 sầu plateaus well above sầu the control values (NS) defined by a high concentration of a standard drug. This leads to alternative definitions of IC50.

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

The graph above shows two definitions of the IC50.

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The concentration that provokes a response halfway between the Blank & the NS value issometimes calledthe** absolute IC50**, The horizontal dotted lines show how 100% và 0% are defined, which then defines 1/2. 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 (và that term) is not useful (R. Neubig, personal communication). I agree.

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

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

**Incomplete dose-response curves**

Any attempt to determine an IC50 by fitting a curve lớn the data in the graph above will be useless. A curve sầu fitting program might, or might not, be able lớn fit a dose-response curve to lớn the data. But if the curve sầu fits, the value of the IC50 is likely khổng lồ be meaningless và have sầu a very wide confidence interval.The data simply don't form a top 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 sầu can be easily fit.The curve sầu below was created by fitting a dose response curve, but constraining the Top plateau lớn be a constant value equal lớn the mean of the Blanks values, & the Bottom plateau equal khổng lồ 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 khổng lồ the NS values. That is an assumption that can't be tested with the data at hand.

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

**Fitting normalized data**

As you can see from all the examples above, it is not necessary to lớn normalize the data khổng lồ run from100% down to 0%. You can fit curves using data in their natural units. A comtháng mistake is khổng lồ 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 (và document in methods sections of papers) how 100% và 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 và very high concentrations of the kiểm tra substance.From the plateaus of nonlinear regression. Fit the curve sầu first, & then use the best-fit values of the Top and Bottom plateau lớn normalize the data.See more: Nghĩa Của Từ Chân Thật Là Gì ? Tôn Giáo Chân Thật Là Gì

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

**Summary**

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

**Reference **

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

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