Half maximal effective concentration () refers to the concentration of a drug, antibody or toxicant which induces a response halfway between the baseline and maximum after a specified exposure time. is also written as . It is commonly used as a measure of a drug's potency, and the use of is preferred over that of 'potency', which has been criticised for its vagueness. is a measure of concentration, expressed in molar units (M), where 1 M is equivalent to 1 mol/L.
The of a graded dose response curve therefore represents the concentration of a compound where 50% of its maximal effect is observed. The of a quantal dose response curve represents the concentration of a compound where 50% of the population exhibit a response, after a specified exposure duration.[clarification needed]
For competition binding assays and functional antagonist assays IC50 is the most common summary measure of the dose-response curve. For agonist/stimulator assays the most common summary measure is the .
The is also related to IC50 which is a measure of a compound's inhibition (50% inhibition).
Calculation of Edit
Biological responses to ligand concentrations typically following a sigmoidal function. The inflection point at which the increase in response with increasing ligand concentration begins to slow is the , which can be mathematically determined by derivation of the best-fit line. While relying on a graph for estimation is more convenient, this typical method yields less accurate results and less precise.
The response or effect, , is dependent on both the binding of the drug and the drug-bound receptor. The agonist that binds to the receptor and initiates the response is usually abbreviated or . At low agonist concentrations, , the response, is immeasurably low but at higher , becomes measurable. increases with until at sufficiently high , when plateaus towards an asymptotic maximum attainable response, . The at which is 50% of is termed the half maximal effective concentration and is abbreviated , or rarely . The term "potency" refers to the value. The lower the , the less the concentration of a drug is required to produce 50% of maximum effect and the higher the potency. The and concentrations to induce 10% and 90% maximal responses are defined similarly.
There is a wide range of values of drugs; they are typically anywhere from nM to mM. Hence, it is often more practical to refer to the logarithmically transformed values instead of , where: .
Relation to affinity and efficacyEdit
Affinity describes how well a drug can bind to a receptor. Faster or stronger binding is represented by a higher affinity, or equivalently a lower dissociation constant. The should not be confused with the affinity constant. While the former reflects the drug the drug concentration needed for a level of tissue response, the latter reflects the drug concentration needed for an amount of receptor binding.
Efficacy is the relationship between receptor occupancy and the ability to initiate a response at the molecular, cellular, tissue or system level.
Relation to the Hill EquationEdit
The relates to the Hill equation, which is a function of the agonist concentration, [A]:
The represents the point of inflection of the Hill equation, beyond which increases of [A] have less impact on E. In dose response curves, the logarithm of [A] is often taken, turning the Hill equation into a sigmoidal logistic function. In this case, the represents the rising section of the sigmoid curve.
The effects of a stressor or drug generally depend on the exposure time. Therefore, the (and similar statistics) will be a function of exposure time. The exact shape of this time function will depend upon the stressor (e.g., the specific toxicant), its mechanism of action, the organism exposed, etc. This time dependency hampers the comparison of potency or toxicity between compounds and between different organisms.
A drug will not have a single value of due to different tissues having different sensitivities to the drug (in part due to tissue specific receptor expression). Furthermore, is dependent on many factors including species, tissue and cell type and genetics.
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