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Original Research Article
Artificial Neural Networks
and Concentration Residual Augmented Classical Least
Squares for the Simultaneous Determination of
Diphenhydramine, Benzonatate, Guaifenesin and
Phenylephrine in their Quaternary Mixture
Hany W Darwish1,2*,
Fadia H Metwally2,3, Abdelaziz El Bayoumi2,
Ahmed A Ashour4
1Department of Pharmaceutical
Chemistry, College of Pharmacy, King Saud University, PO
Box 2457, Riyadh 11451, Saudi Arabia, 2Department
of Analytical Chemistry, Faculty of Pharmacy, Cairo
University, Kasr El - Aini Street, ET 11562, Cairo,
Egypt, 3Ibn Sina National College for Medical
Studies, AlMahjer Road, Jeddah, Saudi Arabia, 4Department
of Analytical Chemistry, Faculty of Pharmacy, Misr
International University, Cairo, Egypt
*For correspondence:
Email:
hdarwish75@yahoo.com;
hdarwish@ksu.edu.sa
Received: 15 October 2014
Revised accepted: 12
November 2014
Tropical
Journal of Pharmaceutical Research, December 2014;
13(12):
2083-2090
http://dx.doi.org/10.4314/tjpr.v13i12.20
Abstract
Purpose: To develop two multivariate
calibration methods for the simultaneous
spectrophotometric determination of a quaternary mixture
composed of diphenhydramine HCl, benzonatate,
guaifenesin and phenylephrine HCl in Bronchofree ™
capsules in the ratio of 2.5 : 10 : 10 : 1,
respectively.
Methods: Novel artificial neural
networks (ANNs) and concentration residual augmented
classical least squares (CRACLS) methods were developed
for the quantitative determination of the quaternary
mixture. For proper analysis, a four-level, four-factor
experimental design was established resulting in a
training set of 16 mixtures containing different ratios
of the four analytes. A validation set consisting of six
mixtures was used to validate the prediction ability of
the suggested models.
Results: ANNs and CRACLS methods
were successfully applied for the analysis of raw
materials and capsules. For ANNs method, % recovery of
diphenhydramine HCl, benzonatate, guaifenesin and
phenylephrine HCl in the capsules was 102.21 ± 1.34,
100.30 ± 1.17, 99.31 ± 2.00 and 98.50 ± 1.27,
respectively. On the other hand, % recovery of the four
analytes by CRACLS was 99.84 ± 2.22, 100.07 ± 0.63,
98.37 ± 1.42 and 97.99 ± 0.96, respectively.
Conclusion: The proposed methods can be
applied for the quantitative determination of the four
components without interference from excipients, thus
obviating the need for preliminary extraction of
analytes from the pharmaceutical formulation. The
ability of the methods to deconvolute the highly
overlapped UV spectra of the four components’ mixtures
using low-cost and easy-to-handle instruments such as UV
spectrophotometer is also an advantage.
Keywords: Artificial neural networks,
Concentration residual augmented classical least
squares, Quaternary mixture, Simultaneous determination |
