This paper deals with optimization of a liquid-liquid extraction procedure for simultaneous HPLC analysis of domperidone and pantoprazole in human plasma. Central composite design and Derringer’s desirability function were used to optimize the concentration of KOH and the volume of ethyl acetate as the main factors affecting the liquid-liquid extraction procedure. After extraction, the analytes were separated quantitatively on a C 18 column with 10 mM pH 7.0 phosphate buffer-methanol-acetonitrile 48.46:20:31.54 ( υ / υ ) as mobile phase at a flow rate of 1.20 mL min -1 and with UV detection at 285 nm. It was concluded that extraction recovery of both the analytes was affected by KOH concentration and that recovery of pantoprazole was affected by ethyl acetate (extraction solvent) volume. Extraction recovery under optimum extraction conditions was 93.52% for domperidone and 92.72% for pantoprazole. The optimized extraction method was validated. Linearity was established for six levels in the ranges 10–1000 ng mL -1 for pantoprazole and 15–1000 ng mL -1 for domperidone. The lower limit of quantitation (LLOQ) and detection (LOD) were estimated as 9.84 and 5.91 ng mL -1 , respectively, for pantoprazole and 14.56 and 8.79 ng mL -1 for domperidone. The optimized method was linear, specific, accurate, and precise; the high recovery (>92%) and low relative standard deviation (<2.5%) enable reliable quantification of these analytes in spiked human plasma.
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A reversed-phase high-performance liquid chromatographic method for separation of the enantiomers of ketoprofen in formulations and in plas-ma matrices has been developed and optimized. A central composite design was used to develop response models and Derringer’s desirability function was then used for simultaneous optimization of chiral resolution and analysis time. This procedure enabled discovery of two separate sets of opti-mum conditions for analysis of quality-control samples and plasma samples within the experimental domain. The optimum conditions predicted for quality-control samples were acetonitrile–dipotassium hydrogen phosphate buffer (10 mΜ, pH 6.5)–triethylamine 56:44:0.05 (/ν) as νmobile phase and 1.13 mL min-1 as flow rate. Use of these conditions enabled baseline separation of the enantiomers of ketoprofen in approximately 4.2 min, which is quicker than the previously optimized method. The method was suitable for routine analysis of the enantiomers of ketoprofen in a commercial pharmaceutical preparation and in plasma samples.
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A simple reversed-phase high-performance liquid chromatographic (RP-HPLC) method has been developed and validated for simultaneous determination of domperidone and pantoprazole in capsules. The compounds were separated on an ODS analytical column with a mixture of methanol, acetonitrile, and triethylamine solution (10 mM, pH 7.0 ± 0.05 adjusted with 85% phosphoric acid) in the ratio 20:33:47 (v/v) as mobile phase at a flow rate of 1.0 mL min-1. UV detection was performed at 285 nm. The method was validated for accuracy, precision, specificity, linearity, and sensitivity. The developed and validated method was successfully used for quantitative analysis of Pantop-D capsules. Total chromatographic analysis time per sample was approximately 10 min with pantoprazole, acetophenone (internal standard), and domperidone eluting with retention times of 4.34, 5.52, and 9.46 min, respectively. Validation studies revealed the method is specific, rapid, reliable, and reproducible. Calibration plots were linear over the concentration ranges 0.5–5 µg mL-1 and 1–10 žg mL-1 for domperidone and pantoprazole, respectively. The LODs were 15.3 and 3.0 ng mL-1 and the LOQs were 51.0 and 10.1 ng mL-1 for domperidone and pantoprazole, respectively. The high recovery and low relative standard deviation confirm the suitability of the method for determination of domperidone and pantoprazole in capsules.
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Simultaneous determination of all drug components in multicomponent pharmaceutical dosage form has been performed applying UV spectra photometry and calibration models based on artificial neural networks. The proposed approach is a simple alternative to using separate models for each component. A novel approach for calibration using computed spectral dataset derived from three spectra of each component has been described. Spectra of Atenolol and Losartan potassium were recorded in the wavelength range 2! 5-275 nm, interval 1 nm, at several concentrations of both analytcs within their linear calibration range and were subsequently used to compute the composition of the calibration mixture. Neural networks trained by Levenberg-Marquardt algorithm were used for building and optimizing calibration models utilizing MATLAB® Neural Network Toolbox. Two types of neural network models were compared to the principal component regression model. Calibration model was thoroughly evaluated at several concentration levels using the spectra obtained for 76 synthetic binary mixtures prepared using orthogona-1 designs. The optimized model has shown sufficient robustness even if the calibration sets were constructed from different sets of pure spectra of the components. Althougłrthc spectra of the components overlapped significantly, the drugs were determined accurately and precisely using the model. No interference from tablet excipients was observed.
PL
Opracowano metodę równoczesnego oznaczania wszystkich komponentów w wieloskładnikowym preparacie farmaceutycznym wykorzystując spektrometrie UV i model kalibra-cyjny oparty na sztucznych sieciach neuronowych. Proponowana metodą jest prosta alternatywą względem stosowania odrębnego modelu dla każdego związku- Metoda ta przedstawia nowy sposób kalibrowania, w którym wykorzystuje się zestaw obliczonych danych Opracowano metodę równoczesnego oznaczania wszystkich komponentów w wieloskładnikowym preparacie farmaceutycznym wykorzystując spektrometrie UV i model kalibra-cyjny oparty na sztucznych sieciach neuronowych. Proponowana metodą jest prosta alternatywą względem stosowania odrębnego modelu dla każdego związku- Metoda ta przedstawia nowy sposób kalibrowania, w którym wykorzystuje się zestaw obliczonych danych spektralnych otrzymanych z trzech widm każdego składnika. Widma atenololu i losartanu rejestrowano w zakresie 215-217 nm, co l nm, przy różnych stężeniach obu analitów, w liniowym zakresie kalibracji i wykorzystano do obliczenia składu miesznin kalibracyjnych. Do zbudowania i optymalizowania modelu kalibracji zastosowano sieci neuronowe trenowane algorytmem Levenberga-Marquardt'a za pomocą programu MATLAB Neu-ronal Network Toolbox. Dwa rodzaje takich modeli porównano z modelem regresji skianika głównego. Opracowany model kalibracji został szczegółowo zbadany dla wielu poziomów stężeń. Badania prowadzono przy użyciu widni 76 dwuskładnikowych mieszanin przygotowanych według modelu ortogonalnego. Zoptymalizowany model okazał się przydatny nawet wówczas gdy mieszaniny kalibracyjne były pr/ygotowane z różnych zestawów spek-tralnie czystych składników. Chociaż widma poszczególnych składników nakładały się w znacznym stopniu opracowany model pozwalał na dokładne i precyzyjne oznaczenie stężeń badanych leków. Nie zaobserwowano wpiywu substancji pomocniczych na jakość oznaczeń.
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