Background:
Partial least squares (PLS) and principal component regression (PCR) are two well-known
chemometric methods based on dimension reduction techniques. They can be very practical analyzing a large
data set of multiple correlated predictor variables.
Objective:
In the presented work, the resolving power of spectrophotometric assisted mathematical techniques
was implemented for the simultaneous determination of two active ingredients; ephedrine hydrochloride (EPH)
and naphazoline nitrate (NAPH), in a matrix of excipients.
Methods:
To build the PLS and PCR models, a calibration set was prepared where the two drugs, in
combination with the interfering parabens, were modeled by multilevel multifactor design. The proposed models
successfully predicted the concentrations of both drugs in validation samples with low root mean squared error
of prediction (RMSEP).
Results:
The results revealed the ability of the mentioned multivariate calibration models to analyze EPH and
NAPH in presence of the interfering parabens with high selectivity in the concentration ranges of 4.00-20.00 µg
mL-1 and 1.00-9.00 µg mL-1, respectively.
Conclusion:
A commercially available nasal spray was successfully analyzed using the developed methods
without interfering with other dosage form additives.
Effect of ephedrine hydrochloride on regulation of body fluid metabolism and AQP1 and AQP2 in a rabbit model of mechanical ventilation
