To answer this question we need to review the basics of the inhibitory constant (Ki) and I value mean. The
inhibitory constant (Ki) is the concentration of the inhibitor that is required
in order to decrease the maximal rate of the reaction by half.(1,2)
Therefore, the smaller the Ki, the smaller amount of medication needed in order
to inhibit the activity of that enzyme. If a Ki is much larger than the
maximal plasma drug concentrations a patient is typically exposed to from
typical dosing, then that drug is not likely to inhibit the activity of that
enzyme. The Ki can be used in the determining the
[I]/Ki ratio as a tool for predicting drug-drug interactions.
The
[I] represents the mean steady-state Cmax value of the inhibitor exposed to the
active site of the enzyme in question (such as a cytochrome P-450 (CYP)
enzyme).(1,2) The closer the drug concentration is to the Ki the greater
chance that the medication in question will inhibit that enzyme and cause drug
interactions with medications that are substrates of that enzyme.
Therefore, as the ratio increases so is the likelihood of a drug
interaction. The United States Food and Drug Administration (FDA) has
suggested the following approach for determining the likelihood of an
interaction. If the [I]/Ki ratio is < 0.1 the prediction for a drug
interaction is remote, if > 0.1 but < 1 it is possible and if the ratio
is > 1 it is likely.(1) As an example, let us consider the ability of proton pump inhibitors (PPI) to inhibit CYP3A4. It has been reported that the Ki's ranged from 42 to 51 mM for most PPIs and
that their respective maximum concentrations ranged from 1 to 5.2 mM in
patients who are either extensive metabolizers or poor metabolizers of 2C219
and have also received doses of PPIs commonly seen in practice.(3-9) A
basic assessment of the range in [I]/Ki ratios (0.02 - 0.11) would suggest that
they are not likely to inhibit CYP3A4 and result in drug-drug interactions of
substrates for CYP3A4. This turns out to also be true clinically as well.
The
use of the [I] and the Ki is a good example for how clinicians can make
predictions about the likelihood for a drug-drug interaction when no other
information is available or that have not been classified appropriately in
various drug interaction databases. This will be easier for clinicians to
also consider or evaluate as this continues to get incorporated into the
product package inserts for various medications.(2,10)