Quantitative ANalysis of Hydrochlorothiazide and Losartan Potassium in A Binary Mixture by Artificial Neural Network
Erdal DINÇ*°, Özgür ÜSTÜNDAĞ*

* Ankara University, Faculty of Pharmacy, Department of Analytical Chemistry, Ankara, Turkey
° Corresponding Author E-mail: dinc@pharmacy.ankara.edu.tr

Summary

A chemometric calibration technique based on the artificial neural network (ANN) was proposed for losartan potassium (LST) and hydrochlorothiazide (HCT) in their mixture without using chemical separation and mathematical graphical treatment. A training set (or a concentration set) of 84 different mixtures containing LST and HCT in large concentration ranges between 0.0-40.0 μg/mL were prepared in methanol. The absorption spectra of the training sets were recorded in the spectral region of 200.0–300.0 nm. The ANN chemometric calibration was computed by using the relationship between the concentration set (x-block) and their corresponding absorption data (y-block). The ability of the proposed ANN calibration was validated by analyzing various synthetic mixtures of the related drugs, and by using standard addition technique. The ANN calibration approach was applied to the simultaneous quantitative evaluation of LST and HCT drugs in tablets and a good agreement was reported.

Key Words :
Artificial neural network, losartan potassium, hydrochlorothiazide, chemometry, quantitative analysis.