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The quantitative analysis is of an interesting issue for the analytical chemistry especially if the compounds of interest have been analyzed in term of sensitivity, low cost, without previous separation and saving analysis time; in this article simultaneous quantitative analysis of binary mixture of formoterol and fluticasone by four different spectrophotometric methods have been discussed and compared these methods namely, simultaneous equation, graphical absorbance ratio, absorbance subtraction and amplitude modulation. The proposed methods were simple, sensitive, accurate and precise. They do not need any sophisticated apparatus and could be easily applied in quality control laboratories. Linearity of the proposed methods was investigated in the range of 2-14µg/ml for formoterol and 5-40µg/ml for fluticasone. All the methods were validated according to the ICH guidelines, statistically compared with a reported method .Another statistical comparison of the obtained results by the proposed methods and the reported method were done using one-way ANOVA test. According to the results obtained by applying these methods there is no significant difference between all of them.

Objectives: Four multivariate chemometric methods have been developed for simultaneous determination of sofosbuvir and ledipasvir in their pure and pharmaceutical dosage forms. Methods: Firstly, partial least squares and artificial neural network have been applied for the quantitative analysis of the studied drugs. Results: Experimental design of different synthetic mixtures of sofosbuvir and ledipasvir in different ratios has been done. The zero-order absorption spectra of these prepared mixtures have been recorded over the wavelength range 200-400 nm with 1 nm interval. The obtained absorbance and concentration data matrix have been utilized to obtain calibration or regression analysis data which has been used for the prediction of the unknown concentrations of each drug in their mixtures. Alternatively, the application of genetic algorithm to partial least squares and artificial neural network has been done and greatly increased the precision and predictive ability of the methods. The four methods have been successfully applied to quantify sofosbuvir and ledipasvir in the real market sample. Conclusion: The investigated methods have been found to be accurate, precise and could resolve the overlapped spectra of the mixture without any preliminary separation steps.