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DOI 10.1002/jssc.201700622

Медицинская библиотека · Journal of separation science · 2017

Green micellar HPLC analysis of three angiotensin-converting enzyme inhibitors in their mixtures with hydrochlorothiazide and modeling of their retention behavior by fitting to Foley's model.

Eid Manal, El-Shabrawy Yasser, El-Shaheny Rania

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Аннотация

We present an environmentally friendly method for the analysis of three angiotensin-converting enzyme inhibitors and hydrochlorothiazide simultaneously using a green micellar eluent for the first time. The chromatographic separation of enalapril maleate, lisinopril dihydrate, benazepril hydrochloride, and hydrochlorothiazide was implemented on an octadecyl silica column with a solution containing sodium dodecyl sulfate (0.12 M), 1-propyl alcohol (10% v/v), triethylamine (0.3% v/v), and H3 PO4 (0.02 M) at pH 3.6 as the mobile phase and UV detection at 210 nm. Validity of the method was confirmed and it exhibited good linearity within the ranges of 5.0-50.0 μg/mL for hydrochlorothiazide and 10.0-60.0 μg/mL for the three angiotensin-converting enzyme inhibitors with a limit of detection of 0.39 to 1.15 μg/mL for all the studied drugs. The developed micellar high-performance liquid chromatography method enables the quantification of the targeted angiotensin-converting enzyme inhibitors in combined tablets with hydrochlorothiazide by isocratic elution. There is no need for special precautions to prevent broadening and splitting of their chromatographic peaks. The method fulfills the society rights for safe and green analytical methods. The retention behavior of the four studied drugs was fitted to Foley's model and their association equilibria to the micelles (KAM ) and to the surface-modified stationary phase (KAS ) were calculated.

Для цитирования: Eid Manal, El-Shabrawy Yasser, El-Shaheny Rania. Green micellar HPLC analysis of three angiotensin-converting enzyme inhibitors in their mixtures with hydrochlorothiazide and modeling of their retention behavior by fitting to Foley's model.. Journal of separation science. 2017. DOI: 10.1002/jssc.201700622.

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