الفهرس 
AcknowledgementOnly 14 pages are availabe for public view
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Abstract
Aim of the work most preparations used in the management of cough and cold contain several active ingredients. In addition, they are formulated in different forms; nasal spray or DROPs, suppositories, aerosol inhalation and many oral preparations. Pharmaceutical products contain not only the active ingredients but also other inactive recipients such as colorants, preservatives, thickening agents and sugars that sometimes interfere with the simultaneous determination of active ingredients. Because of serious interference, most methods assaying these preparations would involve many tedious clean-up procedures such as distillation, liquid-liquid extraction and solid phase extraction. Accordingly, the aim of this work will be directed towards the analysis of these drugs in their pharmaceutical dosage forms using modern spectroscopic and chromatographic techniques to avoid serious interference encountered in these formulations. Orthogonal polynomials for unequal intervals has been used to eliminate interferences in multi-component analysis. The methods are particularly useful when the absorption spectra of the analyses show considerable overlap. The application of chemo metrics to the handling of HPLC response data has also been discussed. It has been found beneficial in eliminating different types of interferences. This was successfully applied to handle some of the most common chromatographic problems and non-ideal conditions, namely: very low drug concentrations, overlapping chromatographic peaks and baseline drift. Thiele’s method, a non-parametric regression method, has been applied to the handling of the response data and has been compared with the least squares parametric regression method. Thiele’s method has been found to be superior to the method of least squares as it assumes that errors could occur in both x- and y-directions and they might not be normally distributed. In addition, it could effectively circumvent any outlier data points. The use of artificial intelligence and artificial neural networks (Ann’s) is a very rapidly developing field in many areas of science and technology. In this work, the application of artificial neural networks for response surface modeling in HPLC method development has been adopted. Ann’s were able to predict the experimental responses more accurately than the multiple regression analysis.