Compound noise factors

Poor aqueous solubility, a compound-related factor rather than an assay-related factor, has a major effect by introducing noise into absorption screening and thus has an effect on making computational model building very difficult. It must be stressed that the compound solubility factor virtually never appears as an explicit consideration in the published permeability literature. Compound sets are published that are used to validate in vitro cell-based absorption assays. Validation usually means obtaining an acceptable... 

Example 60 If compound samples that were actually composed of five individual tablets had been analyzed instead of the spiked matrix, the CV would be expected to be larger than 0.5% on account of the additional manufacturing error, but by a factor Vs = 2.2 lower than the content uniformity CV. (Cf. Eq. (1.5).) Since the average CV for CU was found to be -1.76% ( 1.97, 1.28, resp. 1.95%), this would have to be in the region of about 1.76/2.2 = 0.8, which is still well within the range of accepted instrumental noise. 

The number of columns equals the number of significant factors in the data, and can be any number from 1 upwards. Ideally it equals the number of compounds in the original dataset but noise and spectral similarity combine to distort this number. Each column corresponds to a principal component. 

Refractive Index Detectors These detectors respond to changes in refractive index (positive or negative) arising from the presence of a compound in the eluent. All the factors which can affect refractive index must be carefully controlled (e.g. temperature, eluent composition, pressure) otherwise noise and drift will limit the sensitivity. Thus the chromatograph is best placed in a thermostatically-controlled cabinet and good pumps are desirable to minimise pressure fluctuations. Changes in eluent composition will also cause spurious changes in refractive index. 

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