The SD can be easily obtained from linear regression of the data used to create the
calibration curves. The most common way to present calibration data for the purpose of
linear regression is to graph the expected analyte concentration (spiked, blended) vs. the
recorded response (UV, Fl, OD etc). This type of plot is characteristic of analytical methods
for which the response is a linear function of the concentration (e.g. UV detection that
follows the Beer-Lambert law). In cases where the measured response does not follow a
linear dependency with respect to concentration (e.g., multi-parameter fit response of
immunoassays), the response should be transformed to a linear format, such as semilogarithmic
plots, so that the equations above can be utilized.
The slope used in these equations is equivalent to instrument sensitivity for the specific
analyte, reinforcing the fact that LOD/LOQ are expressed in units of analyte concentration
(e.g. mg/ml) or amount (e.g., mg). Since the LOD and LOQ are functions of instrument
sensitivity, these values, when defined this way, are not universal properties of the method
transferable from instrument to instrument, or from analyte to analyte.