Dispersive liquid-liquid microextraction of quinolones in porcine blood: Validation of a CE method using univariate calibration or multivariate curve resolution-alternating least squares for overlapped peaks.

In the previously published part of this study, we detailed a novel strategy based on dispersive liquid-liquid microextraction to extract and preconcentrate nine fluoroquinolones in porcine blood. Moreover, we presented the optimized experimental conditions to obtain complete CE separation between target analytes. Consequently, this second part reports the validation of the developed method to determine flumenique, difloxacin, enrofloxacin, marbofloxacin, ofloxacin, ciprofloxacin, through univariate calibration, and enoxacin, danofloxacin, and gatifloxacin through multivariate curve resolution analysis. The validation was performed according to FDA guidelines for bioanalytical assay procedures and the European Directive 2002/657 to demonstrate that the results are reliable. The method was applied for the determination of fluoroquinolones in real samples. Results indicated a high selectivity and excellent precision characteristics, with RSD less than 11.9% in the concentrations, in intra- and interassay precision studies. Linearity was proved for a range from 4.00 to 30.00 mg/L and the recovery has been investigated at four different fortification levels, from 89 to 113%. Several approaches found in the literature were used to determinate the LODs and LOQs. Though all strategies used were appropriate, we obtained different values when using different methods. Estimating the S/N ratio with the mean noise level in the migration time of each fluoroquinolones turned out as the best studied method for evaluating the LODs and LOQs, and the values were in a range of 1.55 to 4.55 mg/L and 5.17 to 9.62 mg/L, respectively.

Dispersive liquid-liquid microextraction of quinolones in porcine blood: Optimization of extraction procedure and CE separation using experimental design.

A dispersive liquid-liquid microextraction procedure was developed to extract nine fluoroquinolones in porcine blood, six of which were quantified using a univariate calibration method. Extraction parameters including type and volume of extraction and dispersive solvent and pH, were optimized using a full factorial and a central composite designs. The optimum extraction parameters were a mixture of 250 µL dichloromethane (extract solvent) and 1250 µL ACN (dispersive solvent) in 500 µL of porcine blood reached to pH 6.80. After shaking and centrifugation, the upper phase was transferred in a glass tube and evaporated under N2 steam. The residue was resuspended into 50 µL of water-ACN (70:30, v/v) and determined by CE method with DAD, under optimum separation conditions. Consequently, a tenfold enrichment factor can potentially be reached with the pretreatment, taking into account the relationship between initial sample volume and final extract volume. Optimum separation conditions were as follows: BGE solution containing equal amounts of sodium borate (Na2 B4 O7 ) and di-sodium hydrogen phosphate (Na2 HPO4 ) with a final concentration of 23 mmol/L containing 0.2% of poly (diallyldimethylammonium chloride) and adjusted to pH 7.80. Separation was performed applying a negative potential of 25 kV, the cartridge was maintained at 25.0°C and the electropherograms were recorded at 275 nm during 4 min. The hydrodynamic injection was performed in the cathode by applying a pressure of 50 mbar for 10 s.

Multiple responses optimization in the development of a headspace gas chromatography method for the determination of residual solvents in pharmaceuticals.

An efficient generic static headspace gas chromatography (HSGC) method was developed, optimized and validated for the routine determination of several residual solvents (RS) in drug substance, using a strategy with two sets of calibration. Dimethylsulfoxide (DMSO) was selected as the sample diluent and internal standards were used to minimize signal variations due to the preparative step. A gas chromatograph from Agilent Model 6890 equipped with flame ionization detector (FID) and a DB-624 (30 m×0.53 mm i.d., 3.00 µm film thickness) column was used. The inlet split ratio was 5:1. The influencing factors in the chromatographic separation of the analytes were determined through a fractional factorial experimental design. Significant variables: the initial temperature (IT), the final temperature (FT) of the oven and the carrier gas flow rate (F) were optimized using a central composite design. Response transformation and desirability function were applied to find out the optimal combination of the chromatographic variables to achieve an adequate resolution of the analytes and short analysis time. These conditions were 30 °C for IT, 158 °C for FT and 1.90 mL/min for F. The method was proven to be accurate, linear in a wide range and very sensitive for the analyzed solvents through a comprehensive validation according to the ICH guidelines.

Rapid determination of retinoic acid and its main isomers in plasma by second-order high-performance liquid chromatography data modeling.

This paper reports the development of a method based on high-performance liquid chromatography (HPLC) coupled to second-order data modeling with multivariate curve resolution-alternating least-squares (MCR-ALS) for quantification of retinoic acid and its main isomers in plasma in only 5.5 min. The compounds retinoic acid (RA), 13-cis-retinoic acid, 9-cis-retinoic acid, and 9,13-di-cis-retinoic acid were partially separated by use of a Poroshell 120 EC-C18 (3.0 mm × 30 mm, 2.7 µm particle size) column. Overlapping not only among the target analytes but also with the plasma interferents was resolved by exploiting the second-order advantage of the multi-way calibration. A validation study led to the following results: trueness with recoveries of 98.5-105.9 % for RA, 95.7-110.1 % for 13-cis-RA, 97.1-110.8 % for 9-cis-RA, and 99.5-110.9 % for 9,13-di-cis-RA; repeatability with RSD of 3.5-3.1 % for RA, 3.5-1.5 % for 13-cis-RA, 4.6-2.7 % for 9-cis-RA, and 5.2-2.7 % for 9,13-di-cis-RA (low and high levels); and intermediate precision (inter-day precision) with RSD of 3.8-3.0 % for RA, 2.9-2.4 % for 13-cis-RA, 3.6-3.2 % for 9,13-di-cis-RA, and 3.2-2.9 % for 9-cis-RA (low and high levels). In addition, a robustness study revealed the method was suitable for monitoring patients with dermatological diseases treated with pharmaceutical products containing RA and 13-cis-RA.

Experimental design and multiple response optimization. Using the desirability function in analytical methods development.

A review about the application of response surface methodology (RSM) when several responses have to be simultaneously optimized in the field of analytical methods development is presented. Several critical issues like response transformation, multiple response optimization and modeling with least squares and artificial neural networks are discussed. Most recent analytical applications are presented in the context of analytLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, ArgentinaLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, Argentinaical methods development, especially in multiple response optimization procedures using the desirability function.

Development and validation of a simple stability-indicating high performance liquid chromatographic method for the determination of miconazole nitrate in bulk and cream formulations.

A simple and stability-indicating high performance liquid chromatographic method was developed and validated for the determination of miconazole nitrate in bulk and cream preparations. The extraction step for cream samples consisted in a warming, cooling and centrifugation procedure that assures the elimination of the lipophilic matrix component, in order to avoid further precipitation in the chromatographic system. Separation was achieved on a ZORBAX Eclipse XDB - C18 (4.6 mm x 150 mm, 5 microm particle size) column, using a mobile phase consisting of water, methanol and acetonitrile, in a flow and solvent gradient elution for 15 min. The column was maintained at 25 degrees C and 10 microL of solutions were injected. UV detection was performed at 232 nm, although employment of a diode array detector allowed selectivity confirmation by peak purity evaluation. The method was validated reaching satisfactory results for selectivity, precision and accuracy. Degradation products in naturally aged samples could be simultaneously evaluated, without interferences in the quantitative analysis.

Chemometrics-assisted simple UV-spectroscopic determination of carbamazepine in human serum and comparison with reference methods.

In the present report, carbamazepine is determined on serum samples of real patients by a procedure completely assisted by chemometric tools. First, a response surface methodology based on a mixture design was applied in order to select the best conditions for the extraction step. Finally, partial least squares multivariate calibration (PLS-1) was applied to second-derivative UV spectra, eliminating a shift baseline effect that originated in the extraction procedure. The performance assessment included: (a) a three-level precision study, (b) a recovery study analyzing spiked samples, and (c) a method comparison with high-performance liquid chromatography (HPLC) and fluorescence polarization immunoassay (FPIA) applied on real patient samples. The obtained results show the potentiality of the presently studied methodology for the monitoring of patients treated with this anticonvulsant.

Sustained modelling ability of artificial neural networks in the analysis of two pharmaceuticals (dextropropoxyphene and dipyrone) present in unequal concentrations.

An improvement is presented on the simultaneous determination of two active ingredients present in unequal concentrations in injections. The analysis was carried out with spectrophotometric data and non-linear multivariate calibration methods, in particular artificial neural networks (ANNs). The presence of non-linearities caused by the major analyte concentrations which deviate from Beer's law was confirmed by plotting actual vs. predicted concentrations, and observing curvatures in the residuals for the estimated concentrations with linear methods. Mixtures of dextropropoxyphene and dipyrone have been analysed by using linear and non-linear partial least-squares (PLS and NPLSs) and ANNs. Notwithstanding the high degree of spectral overlap and the occurrence of non-linearities, rapid and simultaneous analysis has been achieved, with reasonably good accuracy and precision. A commercial sample was analysed by using the present methodology, and the obtained results show reasonably good agreement with those obtained by using high-performance liquid chromatography (HPLC) and a UV-spectrophotometric comparative methods.