Quantitative analysis of hydrochlorothiazide and losartan potassium in a binary mixture by artificial neural network


DİNÇ E., ÜSTÜNDAĞ Ö.

Fabad Journal of Pharmaceutical Sciences, cilt.35, sa.3, ss.133-141, 2010 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 35 Sayı: 3
  • Basım Tarihi: 2010
  • Dergi Adı: Fabad Journal of Pharmaceutical Sciences
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.133-141
  • Anahtar Kelimeler: Artificial neural network, Chemometry, Hydrochlorothiazide, Losartan potassium, Quantitative analysis
  • Ankara Üniversitesi Adresli: Evet

Özet

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.