INQUISUR   21779
INSTITUTO DE QUIMICA DEL SUR
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Green method based on a Flow-Batch -UV system applied to the simultaneous determination of ciprofloxacin and dexamethasone in pharmaceutical preparations applying genetic algorithm and successive projections algorithm
Autor/es:
M. F. RAZUC; M. GRÜNHUT; E. SAIDMAN; M. GARRIDO; B. S. FERNÁNDEZ BAND
Lugar:
Thessaloniki
Reunión:
Congreso; XII INTERNATIONAL CONFERENCE ON FLOW ANALYSIS; 2012
Resumen:
This study proposes a Flow-Batch (FB) method with UV detection applied to the simultaneous quantification of ciprofloxacin (CIP) and dexamethasone (DEX) in ophthalmic and otic suspensions. FB systems [1] constitute an excellent alternative to automate the quality control of pharmaceutical products because of their flexibility and versatility (multi-task characteristic). FB systems make it possible to implement different analytical processes [1] just by changing the operational parameters in the control software (i.e. no significant modifications have to be made in the system). Moreover, FB systems has several advantages such as easy implementation, sampling rate, high sensitivity, low cost, and the use of small amounts of reagents. Usually, CIP and DEX are quantified using high performance liquid chromatography (HPLC). In many cases, this technique has certain disadvantages such as expensive reagents which are often toxic for both humans and environment. The proposed method is a green alternative to HPLC, since the solvent used is water, no reagents are used, small volumes of solutions are required and low concentrations of CIP and DEX standard solutions are used (12.0 and 4.0 ppm, respectively). CIP and DEX present a strong absortion between 190 and 370 nm. In addition, the mixture of both analytes shows severe overlapping. Thus, some chemometric tools were required to resolve and quantify these analytes. A central composite experimental design was used in order to perform the calibration and validation sets. Selection of variables was conducted using Genetic Algorithm (GA) and Successive Projections Algorithm (SPA) [2] prior to the application of Multiple Linear Regression (MLR). The FB system was fully automated allowing the automatic preparation of the calibration and validation mixtures, reducing the amount of standard solutions and sample. Moreover, the mixing chamber, which includes a stirrer system, acts as detection cell at the same time. The regression error of calibration (REC) and regression error of prediction (REP) obtained were, in all cases, lower than 2%. The sample throughput was 10h-1 (including the data treatment). Commercial samples were analyzed and the results were in agreement with that obtained ones by a Pharmacopoeia method [3].