Validated Stability-Indicating Methods for Determination of Mometasone Furoate in Presence of its Alkaline Degradation Product

Validated Stability-Indicating Methods for Determination of Mometasone Furoate in Presence of its... Abstract Two novel stability-indicating TLC densitometric and chemometric methods were developed for the determination of mometasone furoate (MF) in the presence of its alkaline degradation product (MF Deg). The developed TLC densitometric method (Method A) is based on the quantitative densitometric separation of MF from its alkaline degradation product on silica gel 60 F254 and measurement of the bands at 250 nm. The separation was carried out using hexane–chloroform–methanol–acetonitrile (6:6:1:0.3, by volume) as a developing system. A well-resolved and compact bands for (MF) and (MF Deg) at retention factors 0.36 and 0.66, respectively. Good resolution between (MF) and (MF Deg) assured the specificity of the proposed method. The method showed good linearity in the concentration range 0.5–5 μg/band with r2 = 0.9998. The method validation was performed according to ICH guidelines demonstrating to be accurate, precise, robust and sensitive. The LOD and LOQ were found to be 0.21 and 0.63 μg/band for MF, respectively. The developed TLC-densitometric method can be applied for identification and quantitative determination of MF in bulk drug and pharmaceutical dosage forms without any interference from excipients and degradates. Method B is a multivariate chemometric-assisted spectrophotometry, where classical least squares, principal component regression and partial least squares were applied. Statistical analysis of the results has been carried out revealing high accuracy and good precision. Introduction Glucocorticoids are potent anti-inflammatory drugs used for the treatment of allergic diseases such as allergic rhinitis and asthma (1). Mometasone furoate (MF) is (11β,16α)-9,21-dichloro-11-hydroxy-16-methyl-3,20-dioxopregna-1,4-dien-17-yl 2-furoate (Figure 1) (2). It is a synthetic 17-heterocyclic glucocorticoid available in nasal, cutaneous and oral inhaled preparations. It has high topical potency and a low risk of systemic absorption (3). It is highly absorbed due to its ester side chains which make it highly lipophilic molecule (4). Its anti-inflammatory effect is due to inhibition of the production of three inflammatory cytokines: IL-1, IL-6 and TNF-alpha (5). So, It is indicated for a number of conditions such as eczema, psoriasis and allergic reactions. Figure 1. View largeDownload slide Chemical structure of MF. Figure 1. View largeDownload slide Chemical structure of MF. A literature search revealed that different techniques were reported for the analysis of MF. HPLC and HPTLC methods were reported for quantitative determination of MF in mixture with other drugs (6–8). Also, stability-indicating HPLC method was developed for MF (9). Other methods were reported either in pharmaceutical preparations and biological fluids (10, 11). The aim of the present work was to develop two stability-indicating TLC densitometric and chemometric methods for determination of MF in the presence of its alkaline degradation product (MF Deg). The developed methods were simple, sensitive, cost effective and accurate. They can be used in routine analysis of MF in quality control laboratories. Materials and Methods Instrumentation - The absorption spectra for all measurements were carried out using Shimadzu recording spectrophotometer UV 1201 equipped with 10 mm matched quartz cells over the range 220–350 nm. The data points were collected at 1 nm intervals. The data were saved in ASCII data-file format by UV-probe personal spectroscopy software version 2.43. - Densitometric evaluation was done using Camag TLC scanner 3 S/N 130319 with winCATS software (Muttenz, Switzerland). - Camag-Linomat V auto sampler (Switzerland). - Camag microsyringe (100 μL) (Switzerland). - Precoated silica gel aluminum plates 60 F254 (Merck, Germany), 20 cm × 20 cm with 0.25 mm thickness. - UV lamp with short wavelength 254 nm (USA) was used for spot detection. - The following requirements are taken into consideration: - Source of radiation: deuterium lamp. - Scan mode: absorption mode. - Slit dimensions: 3 mm × 0.45 mm. - Scanning speed: 20 mm/s. - Result output: chromatogram and integrated peak area. - Wavelength: 250 nm. - Digital analyzer pH meter (USA) was employed for pH measurement. Software Classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS) were modeled using Matlab 8.2.0.701 (R2013b). PLS-Toolbox 2.1 under MATLABTM version 6.5 was used. Materials and reagents All chemicals and reagents used throughout this work were of pure analytical grade. Methanol and water, HPLC-grade, Fischer Scientific UK, Bishop Meadow Road, UK. Chloroform, HPLC-grade, Fluka AG, Chemische Fabrik, CH-9470 Buchs, Switzerland. Hexane, acetonitrile, ethyl acetate, sodium hydroxide and hydrochloric acid, 0.1 N aqueous solutions, El-Nasr Pharmaceutical Chemicals Co., Abu-Zabaal, Cairo, Egypt. Samples Pure standard MF was kindly supplied from SIGMA Pharmaceutical Industries, Cairo, Egypt. Its purity was found to be 99.5% according to the official method (2). Pharmaceutical preparations Elocon® cream Each gram of cream contains 1 mg MF. Batch No. 0416264 produced by South Egypt Drug Industries Company, SEDICO, under licence of Merck Sharp and Dohme (MSD), Belgium. Borgasone® lotion Each gram of lotion contains 1 mg MF. Batch No. 015047 produced by Borg Pharmaceutical Industries, Alexandria, Egypt. Alkaline degradation product (MF Deg) To 5 mL stock solution (2 mg/mL), 5 mL of 0.1 N NaOH were added. This mixture was kept at room temperature for 150 min. The degradation process was followed by TLC through the disappearance of the spot corresponding to the drug and appearance of one new spot corresponding to the formed degradation product using hexane–chloroform–methanol–acetonitrile (6:6:1:0.3, by volume) as a developing system. The solution was adjusted to pH 7 with 0.1 N HCl. Then, the solution was evaporated to dryness under vacuum. The residue was extracted with 9 mL of methanol, filtered and the volume of the extract was completed to 10 mL with methanol to obtain a stock solution labeled to contain alkaline degradation product derived from 1 mg/mL of MF. Analysis of the degradation product by the proposed procedures specified under general assay procedure was carried out. Preparation of sample solutions Stock solutions of MF (2 mg/mL) A stock solution of MF was prepared by dissolving 200 mg of the drug powder in 50 mL of methanol and the volume was completed to 100 mL with the same solvent. Stock solutions of MF Deg (1 mg/mL) A stock solution of the alkaline degradation product (1 mg/mL) was prepared as mentioned before under “Alkaline degradation product (MF Deg)”. Working standard solutions of MF and MF Deg For Method A (TLC densitometric method): Working standard solutions of MF were prepared in methanol in the concentration of 1 mg/mL. For Method B (chemometric method): Working standard solutions were prepared in methanol in the concentration of 0.5 mg/mL for both MF and MF Deg. Laboratory prepared mixtures Different aliquots of MF working standard solution (1 mg/mL) for Method A and (0.5 mg/mL) for Method B were mixed with different aliquots MF Deg working solution (1 mg/mL) for Method A and (0.5 mg/mL) for Method B to prepare mixtures of different ratios of MF and its degradation product. Procedures Method A (TLC densitometric method) Construction of calibration curve About 50 mL of the mobile phase (hexane–chloroform–methanol–acetonitrile (6:6:1:0.3), by volume) were poured into the TLC tank. The TLC tank was lined with a filter paper to help saturation of TLC chamber. The tank was presaturated with the vapors of the mobile phase system for 30 min at room temperature (25°C) before development of the plates. Accurately measured aliquots equivalent to (0.5–5 μL) of working standard MF solution (1 mg/mL) were applied in the form of bands on the marked start edge of the TLC plate using a Camag-Linomat V applicator. The bands were applied 14 mm apart from each other and 15 mm from the bottom edge of the plate with a band length of 3 mm. The plates were allowed to be air dried for 5 min, then transferred to the TLC tank allowing linear ascending development of the mobile phase. After development, the plates were removed, air dried for ~5 min then scanned at 250 nm. A calibration curve relating the optical density of each band to the corresponding concentration of MF was constructed (Figure 2). Figure 2. View largeDownload slide (3D) Densitogram of MF (Rf = 0.36) in the concentration range 0.5–5 μg/band at 250 nm using hexane–chloroform–methanol–acetonitrile (6:6:1:0.3, by volume) as a developing system. Figure 2. View largeDownload slide (3D) Densitogram of MF (Rf = 0.36) in the concentration range 0.5–5 μg/band at 250 nm using hexane–chloroform–methanol–acetonitrile (6:6:1:0.3, by volume) as a developing system. Analysis of laboratory prepared mixtures containing different ratios of MF and MF Deg Accurately measured aliquots of working standard MF solution (1 mg/mL) and MF Deg solution (1 mg/mL) were mixed to prepare different mixtures containing 10–50% of MF Deg. Then the general procedures were carried out as mentioned before under “Construction of calibration curve”. The concentrations were calculated from the corresponding regression equations. Method B (chemometric method) Spectral characteristics The absorption spectra of MF and MF Deg were scanned in the range 220–350 nm using methanol as a blank. The noisy region from 200 nm to 220 nm and the near zero absorbance region after 350 nm were rejected. Construction of the calibration set A calibration set of 14 different laboratory prepared mixtures were prepared using multilevel multifactor experimental design (12). The mixtures were prepared by transferring different aliquots from the working standard solution of MF and MF Deg (0.5 mg/mL) into a series of 10 mL volumetric flasks then the volume was completed with methanol (Table I). The absorption spectra of the mixtures were scanned over the range of 220–350 nm with respect to a blank of methanol. Table I. The Concentration of Different Mixtures of MF and its Degradation Product Used in the Training and Validation Sets Sample number  Intact MF(μg/mL)  MF deg (μg/mL)  1a  15  15  2a  15  10  3a  10  10  4a  10  20  5  20  12.5  6  12.5  20  7a  20  15  8a  15  12.5  9a  12.5  12.5  10  12.5  17.5  11  17.5  20  12a  20  17.5  13  17.5  15  14a  15  20  15  20  20  16a  20  10  17  10  17.5  18  17.5  10  19a  10  15  20  15  17.5  21  17.5  17.5  22  17.5  12.5  23a  12.5  10  24a  10  12.5  25a  12.5  15  Sample number  Intact MF(μg/mL)  MF deg (μg/mL)  1a  15  15  2a  15  10  3a  10  10  4a  10  20  5  20  12.5  6  12.5  20  7a  20  15  8a  15  12.5  9a  12.5  12.5  10  12.5  17.5  11  17.5  20  12a  20  17.5  13  17.5  15  14a  15  20  15  20  20  16a  20  10  17  10  17.5  18  17.5  10  19a  10  15  20  15  17.5  21  17.5  17.5  22  17.5  12.5  23a  12.5  10  24a  10  12.5  25a  12.5  15  aThe concentrations of mixtures used in the training set. Constructing the models To build the CLS model, the computer was fed with the absorbance and concentration matrices for the calibration set using Matlab 8.2.0.701 (R2013b). Calculations were carried out to obtain the “K” matrix. For the PCR and PLS models, the training set absorbance and concentration matrices together with PLS-Toolbox 2.1 software were used. Selection of the optimum number of factors to build the PCR and PLS models To select the number of factors for PLS and PCR methods, the cross validation method, leaving out one sample at a time, was applied (13). Given a set of 14 calibration samples, the PCR and PLS calibrations were performed on 13 samples, then the concentration of the sample left out during calibration was predicted. This process was repeated 14 times until each sample had been left out once. The predicted concentrations were compared with the known concentrations and the root mean square error of calibration (RMSEC) was then calculated. The RMSEC was calculated in the same manner each time a new factor was added to the model. Visual inspection was used for selecting the optimum number of factors. Assay of the validation set The absorption spectra of different 11 mixtures containing different ratios of MF and MF Deg (Table I) were scanned over the range of 220–350 nm with respect to a blank of methanol. The developed models were applied to predict the concentration of MF in each mixture. Assay of pharmaceutical formulations Elocon® cream An accurately measured amount of cream (20 g) equivalent to 20 mg MF was transferred into a beaker followed by addition of 9 mL methanol. The solution was covered with aluminum foil and sonicated for 30 min. In between, the flask was occasionally swirled. The solution was filtered using whatman paper 0.45 mm. The clear filtrates were collected in 10 mL volumetric flask and the volume was made up to the mark with methanol to get 2 mg/mL MF solution. Appropriate dilutions were made using methanol to get samples having concentrations within the range of each method and then the proposed methods were followed. Borgasone® lotion The 20 mL of lotion equivalent to 20 mg MF were transferred into rounded bottom flask, then evaporated to dryness under vacuum. The residue was extracted with 9 mL of methanol, filtered and the volume of the extract was completed to 10 mL with methanol to obtain 2 mg/mL MF solution. Appropriate dilutions were made using methanol to get samples having concentrations within the range of each method and then the proposed methods were followed. Results Many pharmaceutical compounds undergo degradation during storage affecting quality, safety and efficacy of the formulation. If safety and efficacy values decline, stability studies are the main judge that determines when the product should be withdrawn from the market. The ICH guidelines (14) on “Stability Testing of New Drug Substances” suggests testing the features change during storage by validated stability-indicating methods. Forced degradation was reported for MF, it was found to be susceptible to alkaline hydrolysis and photodegradation but resistant to acid hydrolysis, oxidation and dry heat degradation (9). So, the determination of MF in the presence of its alkaline degradate was important. In alkaline condition, the ester undergoes hydrolysis. The chemical structure of MF Deg is shown in Figure 3. Figure 3. View largeDownload slide Suggested degradation product results from alkaline degradation of mometasone furoate. Figure 3. View largeDownload slide Suggested degradation product results from alkaline degradation of mometasone furoate. Hence, the focus of the proposed work was to develop specific, accurate, reproducible and sensitive stability-indicating methods for the determination of MF in pure form or in pharmaceutical formulations in the presence of its alkaline degradation product. The MF band was well resolved from MF Deg band and not shifted significantly showing the stability-indicating advantage of the developed method. Also, the UV absorption spectra of MF and MF Deg shows considerable overlap, where the application of conventional spectrophotometry, its direct derivative and derivative ratio techniques failed to resolve these overlapping spectra. So, another chemometric method was applied for determination of MF and MF Deg by resolving their spectral overlap that cannot be resolved by any other direct or indirect spectrophotometric method. The suggested methods were validated and compared to the official method (2). TLC densitometric method TLC-densitometry is an important technique in the field of separation and analysis of drug mixtures and closely related compounds due to its high resolution power. It overcomes the problem of overlapping absorption spectra of closely related compounds by separating them on TLC plates and determining each ingredient by scanning the corresponding chromatogram. The proposed method shows good results regarding accuracy and precision. It could be used for determination of MF in presence of MF Deg without prior separation. To improve separation of bands, different experimental conditions were studied and optimized to provide better separation and accurate results as follows. Mobile phase Different solvent systems were tried, e.g., ethyl acetate–benzene (1:1, by volume), chloroform–ethanol (18:12, by volume), chloroform–ethyl acetate–methanol–toluene (5:2:2:2, by volume), ethyl acetate–toluene–methanol–acetonitrile–triethylamine (2.5:6:1:0.3:0.1, by volume) and hexane–chloroform–methanol–acetonitrile (6:6:1:0.3, by volume). Complete separation without tailing was obtained by using the last system where Rf = 0.36 and 0.66 for MF and MF Deg, respectively (Figure 4). Figure 4. View largeDownload slide TLC chromatogram of MF (4.5 μg/band, Rf = 0.36) and its alkaline degradation products (0.50 μg/band, Rf = 0.66). Figure 4. View largeDownload slide TLC chromatogram of MF (4.5 μg/band, Rf = 0.36) and its alkaline degradation products (0.50 μg/band, Rf = 0.66). Scanning wavelength Different scanning wavelengths were tried (230 nm, 240 nm, 250 nm and 260 nm). The wavelength of 250 nm gave the best results (Figure 4), with sharp and symmetrical peaks. Minimum noise was obtained. Band dimensions Samples were applied as bands. Thus, the band width should be chosen carefully to avoid spread of bands outside the scanning tracks due to ordinary diffusion. Also, the interspaces between bands were optimized to prevent interference between adjacent bands. Narrow band width should be avoided to prevent overloading of silica especially if higher volumes are applied resulting in tailing of the peaks. The optimum band width was found to be 3 mm and the inter-space between bands was 14 mm. Slit dimensions of scanning light beam The slit dimensions of the scanning light beam should ensure complete coverage of band dimensions on the scanned track without interference of adjacent bands. The optimum slit dimensions were found to be 3 mm × 0.45 mm. System suitability Parameters including resolution (Rs), peak symmetry, capacity factor (K′) and selectivity factor (α) were calculated. The resolution was always above 1.5, the selectivity more than one and an accepted value for symmetry factor was obtained (Table II). Table II. Parameters of System Suitability of the Developed TLC-Densitometric Method for the Determination of MF in the Presence of its Degradation Product Parameters  MF  MF Deg  Resolution (Rs)  3    Separation factor (α)  3.42    Tailing factor (T)  0.94  0.92  Capacity factor (K΄)  1.78  0.52  Parameters  MF  MF Deg  Resolution (Rs)  3    Separation factor (α)  3.42    Tailing factor (T)  0.94  0.92  Capacity factor (K΄)  1.78  0.52  The linearity of MF was checked at the selected wavelength 250 nm in the concentration range of 0.5–5 μg/band. Calibration curve relating the integrated peak areas to the corresponding concentrations of MF was constructed. The regression equation and analytical parameters of the developed method were calculated (Table III). Table III. Regression and Validation Parameters of the Developed TLC-Densitometric Method for the Determination of MF Parameters  TLC densitomertic method  Linearity range  0.5–5 μg/band  Slope (b)  1,751.4  Intercept (a)  8,057.94  Correlation coefficient (r2)  0.9998  Accuracy (mean ± SD)  99.99 ± 0.65  LODa (μg/band)  0.21  LOQa (μg/band)  0.63  Parameters  TLC densitomertic method  Linearity range  0.5–5 μg/band  Slope (b)  1,751.4  Intercept (a)  8,057.94  Correlation coefficient (r2)  0.9998  Accuracy (mean ± SD)  99.99 ± 0.65  LODa (μg/band)  0.21  LOQa (μg/band)  0.63  aLimit of detection and quantitation were determined via calculations. LOD = (SD of the intercept/slope of the standard curve) × 3.3; LOQ = (SD of the intercept/slope of the standard curve) × 10. Stability indication To assess the stability-indicating efficiency of the proposed method, it was applied to laboratory prepared mixtures containing MF and MF Deg in different ratios (10–50%). Table IV shows that the proposed method was valid for determination of intact MF in presence of up to 50% of its alkaline degradation product with good selectivity. Table IV. Determination of MF in Laboratory Prepared Mixtures by the Developed TLC Densitomertic Method Degradation products %  Concentration (μg/band)  Recovery % of MF  MF Deg  MF  10  0.5  4.5  100.77  20  1  4  99.09  30  1.5  3.5  100.2  40  2  3  100.72  50  2.5  2.5  101.45  Mean ± SD    100.45 ± 0.88  Degradation products %  Concentration (μg/band)  Recovery % of MF  MF Deg  MF  10  0.5  4.5  100.77  20  1  4  99.09  30  1.5  3.5  100.2  40  2  3  100.72  50  2.5  2.5  101.45  Mean ± SD    100.45 ± 0.88  Application of TLC densitometric method to the pharmaceutical formulations The suggested TLC densitometric method was successfully applied for the determination of MF in its pharmaceutical formulations, showing good percentage recoveries without excipients interference (Table VIII). Table VIII. Application of the Proposed Methods to the Determination of MF in Dosage Formsa Pharmaceutical formulation  TLC densitomertic method  Chemometric methods  CLS  PCR  PLS  Taken (μg/band)  Found (μg/band)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Elocon® cream  1  1.01  101.33  10  9.85  98.47  10  9.89  98.85  10  9.89  98.93  1.5  1.53  102  12.5  12.37  98.99  12.5  12.20  97.59  12.5  12.23  97.83  2  2.01  100.3  15  15.14  100.9  15  14.96  99.73  15  14.77  98.46  2.5  2.50  100.18  17.5  17.74  101.37  17.5  17.10  97.71  17.5  17.22  98.41  3  3.05  101.61  20  20.13  100.65  20  19.77  98.87  20  19.84  99.18  Mean  101.08    100.08    98.55    98.56  SD  0.81  1.27  0.89  0.52  SE  0.36  0.57  0.4  0.23  RSD  0.80  1.27  0.91  0.53  Variance  0.65  1.61  0.80  0.27  Borgasone® lotion  2  2.02  100.98  10  9.97  99.72  10  9.98  99.75  10  9.90  99.01  2.5  2.53  101.05  12.5  12.33  98.66  12.5  12.54  100.29  12.5  12.62  100.98  3  2.1  99.89  15  14.77  98.45  15  14.94  99.63  15  15.24  101.58  3.5  3.5  100.1  17.5  17.07  97.55  17.5  17.10  97.71  17.5  17.97  102.66  4  4.01  100.25  20  19.73  98.65  20  19.84  99.22  20  20.21  101.07  Mean  100.45    98.61    99.32    101.06  SD  0.53  0.77  0.98  1.32  SE  0.24  0.34  0.44  0.59  RSD  0.52  0.78  0.98  1.31  Variance  0.28  0.60  0.95  1.76  Pharmaceutical formulation  TLC densitomertic method  Chemometric methods  CLS  PCR  PLS  Taken (μg/band)  Found (μg/band)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Elocon® cream  1  1.01  101.33  10  9.85  98.47  10  9.89  98.85  10  9.89  98.93  1.5  1.53  102  12.5  12.37  98.99  12.5  12.20  97.59  12.5  12.23  97.83  2  2.01  100.3  15  15.14  100.9  15  14.96  99.73  15  14.77  98.46  2.5  2.50  100.18  17.5  17.74  101.37  17.5  17.10  97.71  17.5  17.22  98.41  3  3.05  101.61  20  20.13  100.65  20  19.77  98.87  20  19.84  99.18  Mean  101.08    100.08    98.55    98.56  SD  0.81  1.27  0.89  0.52  SE  0.36  0.57  0.4  0.23  RSD  0.80  1.27  0.91  0.53  Variance  0.65  1.61  0.80  0.27  Borgasone® lotion  2  2.02  100.98  10  9.97  99.72  10  9.98  99.75  10  9.90  99.01  2.5  2.53  101.05  12.5  12.33  98.66  12.5  12.54  100.29  12.5  12.62  100.98  3  2.1  99.89  15  14.77  98.45  15  14.94  99.63  15  15.24  101.58  3.5  3.5  100.1  17.5  17.07  97.55  17.5  17.10  97.71  17.5  17.97  102.66  4  4.01  100.25  20  19.73  98.65  20  19.84  99.22  20  20.21  101.07  Mean  100.45    98.61    99.32    101.06  SD  0.53  0.77  0.98  1.32  SE  0.24  0.34  0.44  0.59  RSD  0.52  0.78  0.98  1.31  Variance  0.28  0.60  0.95  1.76  aMean of three different experiments. TLC densitometric method validation Method validation was performed according to the ICH guidelines (14). Tables III and V show the obtained results were accurate, precise and sensitive. The method showed good linear relationship as revealed by the correlation coefficient (Table III). Table V. Precision Data for the Determination of MF by the Developed TLC Densitomertic Method Intradaya  Interdayb  Added (μg/band)  Found (μg/band)  Recovery %  RSD%d  Er%c  Added (μg/band)  Found (μg/band)  Recovery %  RSD%d  Er%c  0.5  0.51  101.1  2.07  1.1  0.5  0.49  98.2  1.85  −1.8  3  3.09  102.84  0.6  2.84  3  3.03  100.99  0.06  0.99  5  4.92  98.3  0.74  −1.7  5  5.09  101.74  0.25  1.74  Intradaya  Interdayb  Added (μg/band)  Found (μg/band)  Recovery %  RSD%d  Er%c  Added (μg/band)  Found (μg/band)  Recovery %  RSD%d  Er%c  0.5  0.51  101.1  2.07  1.1  0.5  0.49  98.2  1.85  −1.8  3  3.09  102.84  0.6  2.84  3  3.03  100.99  0.06  0.99  5  4.92  98.3  0.74  −1.7  5  5.09  101.74  0.25  1.74  aThe intraday (n = 9), average of three different concentrations repeated three times within the day. bThe interday (n = 9), average of three concentrations repeated three times in three successive days. cEr %, percentage relative error. dRSD%, percentage relative standard deviation. Robustness Robustness was examined by evaluating the influence of small variations in the experimental parameters on the analytical performance of the proposed method. The studied parameters were the mobile phase composition and development distance (±0.3 cm) which were tried at one concentration level 3 μg/band for three times (Table VI). Table VI. Robustness of the Developed TLC Densitomertic Method Using Concentration of 3 μg/band of MF Parameter  Recovery (%) ± SDa  Mobile phase composition hexane–chloroform–methanol–acetonitrile   6.1:6:1:0.3  101.70 ± 0.69   6:6.1:1:0.3  102.30 ± 0.27   6.1:6.1:1:0.3  100.43 ± 1.59  Development distance   7.7 cm  99.89 ± 1.97   8.3 cm  101.1 ± 1.12  Parameter  Recovery (%) ± SDa  Mobile phase composition hexane–chloroform–methanol–acetonitrile   6.1:6:1:0.3  101.70 ± 0.69   6:6.1:1:0.3  102.30 ± 0.27   6.1:6.1:1:0.3  100.43 ± 1.59  Development distance   7.7 cm  99.89 ± 1.97   8.3 cm  101.1 ± 1.12  aAverage of three determinations. Method B (chemometric method) Chemometrics is the art of processing data with various numerical techniques in order to extract useful information (13). It is the application of mathematical and statistical methods to design optimum procedures and to provide maximum chemical information through the analysis of chemical data. Multivariate calibrations are useful in spectral analysis because the simultaneous inclusion of multiple spectral intensities can greatly improve the precision and applicability of quantitative spectral analysis (15). Unlike univariate spectrophotometry, which depends on measuring the amplitude at one wavelength. So any shift in wavelength scale will lead to false results. Also, it may be affected by several factors such as noise, scanning speed and λ. The UV absorption spectra of MF and MF Deg displays considerable overlap, where the application of conventional spectrophotometry is very difficult. In this work, three multivariate methods, CLS, PCR and PLS, were applied for the determination of MF in the presence of MF Deg. CLS model CLS model or (K) matrix was constructed using the training set (i.e., absorptivity at different wavelengths). The CLS method requires that all the components in the calibration samples must be known. The absorbance matrix of the calibration samples (14 × 131) and their corresponding concentration matrix (14 × 2) were used to find the absorptivity matrix (K-matrix).Then, the predicted concentration of MF in both the validation and pharmaceutical formulation samples were calculated using the obtained K-matrix. PCR and PLS models Unlike CLS, PCR and PLS methods have the advantage that they could determine the components under investigation even in the presence of unknown components (interfering substance) (16). The selection of the optimum number of latent variables was a very important pre-construction step. Because if the number of factors retained was more than required, more noise would be added to the data. On the other hand, if the number retained was too small, meaningful data that could be necessary for the calibration might be discarded. In this work, the cross validation method, leaving out one sample at a time and RMSECV, was calculated and used to select the optimum number of factors (13). After the PCR and PLS models were constructed, it was found that the optimum number of latent variables described by the developed models was two factors for both PCR and PLS methods as shown in Figures 5 and 6. Figure 5. View largeDownload slide RMSECV plot of the cross validation results of the calibration set as a function of the number of latent variables used to construct the PCR model. Figure 5. View largeDownload slide RMSECV plot of the cross validation results of the calibration set as a function of the number of latent variables used to construct the PCR model. Figure 6. View largeDownload slide RMSECV plot of the cross validation results of the calibration set as a function of the number of latent variables used to construct the PLS model. Figure 6. View largeDownload slide RMSECV plot of the cross validation results of the calibration set as a function of the number of latent variables used to construct the PLS model. All models were applied successfully for analysis of MF in training set and validation set (Table VII). The recoveries mean recoveries, standard deviation, root mean square of calibration (RMSEC) and root mean square of prediction (RMSEP) values were calculated (Table VII). The chemometric methods (CLS, PCR and PLS) were applied successfully to the analysis of MF in pharmaceutical applications (Table VIII). The recoveries were found to be satisfactory indicating that the additives in the pharmaceutical formulations did not interfere (Table VIII). Table VII. Analysis Results for the Prediction of the Training Set and Validation Set by the Proposed Multivariate Calibration Methods Concentration (μg/mL)a  MF recovery %  Concentration (μg/mL)b  MF recovery %  MF  MF Deg  CLS  PCR  PLS  MF  MF Deg  CLS  PCR  PLS  15  15  101.99  101.92  101.92  20  12.5  96.62  97.50  97.82  15  10  101.25  100.57  100.25  12.5  20  99.65  97.88  98.22  10  10  103.75  100.78  102.56  12.5  17.5  96.84  97.66  96.75  10  20  98.97  97.49  97.49  17.5  20  98.62  98.62  97.55  20  15  99.58  97.71  97.72  17.5  15  98.66  97.45  96.01  15  12.5  101.39  101.33  101.33  20  20  98.45  97.82  98.62  12.5  12.5  100.19  100.12  100.12  10  17.5  96.21  96.09  96.10  20  17.5  98.32  98.64  99.45  17.5  10  96.76  96.72  96.73  15  20  98.65  98.62  99.52  15  17.5  97.21  97.13  97.13  20  10  98.36  98.33  98.33  17.5  17.5  96.42  96.35  97.45  10  15  103.24  100.89  100.25  17.5  12.5  97.68  98.65  97.22  12.5  10  101.86  101.81  101.80            10  12.5  101.36  101.27  101.25            12.5  15  100.94  100.86  100.86            Mean    100.70  100.02  100.20  Mean    97.56  97.44  97.24  SD  1.75  1.54  1.51  S.D.  1.13  0.83  0.82  RMSEC  0.003  0.003  0.002  RMSEP  0.03  0.03  0.04  Concentration (μg/mL)a  MF recovery %  Concentration (μg/mL)b  MF recovery %  MF  MF Deg  CLS  PCR  PLS  MF  MF Deg  CLS  PCR  PLS  15  15  101.99  101.92  101.92  20  12.5  96.62  97.50  97.82  15  10  101.25  100.57  100.25  12.5  20  99.65  97.88  98.22  10  10  103.75  100.78  102.56  12.5  17.5  96.84  97.66  96.75  10  20  98.97  97.49  97.49  17.5  20  98.62  98.62  97.55  20  15  99.58  97.71  97.72  17.5  15  98.66  97.45  96.01  15  12.5  101.39  101.33  101.33  20  20  98.45  97.82  98.62  12.5  12.5  100.19  100.12  100.12  10  17.5  96.21  96.09  96.10  20  17.5  98.32  98.64  99.45  17.5  10  96.76  96.72  96.73  15  20  98.65  98.62  99.52  15  17.5  97.21  97.13  97.13  20  10  98.36  98.33  98.33  17.5  17.5  96.42  96.35  97.45  10  15  103.24  100.89  100.25  17.5  12.5  97.68  98.65  97.22  12.5  10  101.86  101.81  101.80            10  12.5  101.36  101.27  101.25            12.5  15  100.94  100.86  100.86            Mean    100.70  100.02  100.20  Mean    97.56  97.44  97.24  SD  1.75  1.54  1.51  S.D.  1.13  0.83  0.82  RMSEC  0.003  0.003  0.002  RMSEP  0.03  0.03  0.04  aThe concentrations of mixtures used in the training set. bThe concentrations of mixtures used in the validation set. Statistical analysis The proposed TLC densitometric and chemometric methods were statistically compared to the reference method (2) using Student’s t-test and variance ratio F-test at 95% confidence level. Table IX shows the calculated t and F values were less than the theoretical ones, indicating no significant differences between the proposed methods and the official one (2). Table IX. Statistical Comparison of the Results Obtained by the Proposed Methods and the Official Method (2) for the Determination of Mometasone Furoate   TLC densitomertic method  Chemometric methods  Official method (2)  CLS  PCR  PLS  Mean  100.45  98.61  99.32  101.06  99.5  SD  0.53  0.77  0.98  1.32  0.98  RSD%  0.52  0.78  0.98  1.31  0.99  Variance  0.28  0.6  0.95  1.76  0.95  n  6  5  5  5  5  F-test  3.39(5.19)a  1.58 (8.39)a  1.03 (8.39)a  1.85 (8.39)a    Student’s t-test  2.06(2.202)a  1.6 (2.306)a  0.29(2.306)a  2.13(2.306)a      TLC densitomertic method  Chemometric methods  Official method (2)  CLS  PCR  PLS  Mean  100.45  98.61  99.32  101.06  99.5  SD  0.53  0.77  0.98  1.32  0.98  RSD%  0.52  0.78  0.98  1.31  0.99  Variance  0.28  0.6  0.95  1.76  0.95  n  6  5  5  5  5  F-test  3.39(5.19)a  1.58 (8.39)a  1.03 (8.39)a  1.85 (8.39)a    Student’s t-test  2.06(2.202)a  1.6 (2.306)a  0.29(2.306)a  2.13(2.306)a    aFigures between parenthesis represent the corresponding tabulated values of t and F at P = 0.05. Discussion This study aims to develop two new stability-indicating methods for the determination of MF in the presence of its alkaline degradation product. In the TLC densitometric method, sharp and symmetric peak of MF was obtained with good resolution from excipients and degradate peaks. Also, a three multivariate chemometric-assisted spectrophotometric methods were applied. The developed methods can be applied for the determination of MF in bulk or in pharmaceutical preparations without any interference from excipients and alkaline degradation product. Results of validation parameters indicate that both methods are linear, accurate, precise and robust. Conclusion The objective of the present work was achieved by quantitative determination of MF in the presence of its alkaline degradate in bulk and in pharmaceuticals. New TLC densitometric method was developed and validated for MF determination without any interference from excipients and degradation products. The proposed method has the merits of high sensitivity, less time consuming and more economical than other separation methods. Also, the chemometric methods studied in this work can be performed easily with software support showing high resolving power. They have the advantage of speed due to avoiding the separation step. The proposed methods can be used in the routine quality control analysis without interference of commonly encountered pharmaceutical formulation additives or the degradation products. References 1 Melton, B.A., Francis, C., Desmond, P., Mark, W., Sudhakar, P, Robert, P.C., et al.  .; Bioavailability and metabolism of mometasone furoate following administration by metered-dose and dry-powder inhalers in healthy human volunteers; Journal of Clinical Pharmacology , ( 2000); 40: 1227– 1236. Google Scholar PubMed  2 The British Pharmacopeia.; Her majesty’s . The Stationary Office, London, ( 2007). 3 Courtney, C., Lisa, N.P., Peter, T.D.; A review of the pharmacology and pharmacokinetics of inhaled fluticasone propionate and mometasone furoate; Clinical Therapeutics , ( 2001); 23( 9): 1339– 1354. Google Scholar CrossRef Search ADS PubMed  4 Derendorf, H., Meltzer, E.O.; Molecular and clinical pharmacology of intranasal corticosteroids: clinical and therapeutic implications; European Journal of Allergy and Clinical Immunology , ( 2008); 63( 10): 1292– 1300. Google Scholar CrossRef Search ADS PubMed  5 Naazneen, S., Sachin, N., Tamishraha, B., Dwarkanath, B.S., Ambikanandan, M.; Intracellular delivery of nanoparticles of an antiasthmatic drug; American Association of Pharmaceutical Scientists , ( 2008); 9( 1): 217– 223. 6 Hanan, A.M., Sally, S.E., Nagiba, Y.H., Badr, A.E.; Validated chromatographic methods for the simultaneous determination of Mometasone furoate and Formoterol fumarate dihydrate in a combined dosage form; Bulletin of Faculty of Pharmacy, Cairo University , ( 2016); 54: 99– 106. Google Scholar CrossRef Search ADS   7 Kalpana, G.P., Pratik, M.S., Purvi, A.S., Tejal, R.G.; Validated high-performance thin-layer chromatographic (HPTLC) method for simultaneous determination of nadifloxacin, mometasone furoate, and miconazole nitrate cream using fractional factorial design; Journal of Food and Drug Analysis , ( 2016); 24: 610– 619. Google Scholar CrossRef Search ADS PubMed  8 Devanshi, G., Ankit, B., Bhoomi, D.; Method development and validation for estimation of clotrimazole, fusidic acid and mometasone furoate in cream by RP-HPLC; World Journal of Pharmacy and Pharmaceutical Sciences , ( 2017); 6( 5): 1204– 1219. 9 Ramzia, I.E., Marwa, A.F., Manal, A.E., Enas, H.T.; Forced degradation of mometasone furoate and development of two RP-HPLC methods for its determination with formoterol fumarate or salicylic acid; Arabian Journal of Chemistry , ( 2016); 9: 493– 505. Google Scholar CrossRef Search ADS   10 Sahasranaman, S., Tang, Y, Biniasz, D., Hochhaus, G.; A sensitive liquid chromatography-tandem mass spectrometry method for the quantification of mometasone furoate in human plasma; Journal of Chromatography B , ( 2005); 819( 1): 175– 179. Google Scholar CrossRef Search ADS   11 Patel, H.D., Patel, M.M.; Development and validation of UV spectrophotometric method for simultaneous estimation of terbinafine hydrochloride and mometasone furoate in combined dosage form; Asian Journal of Research in Chemistry , ( 2013); 6( 1): 29– 34. 12 Richard, G.B.; Multilevel multifactor designs for multivariate calibration; Analyst , ( 1997); 122: 1521– 1529. Google Scholar CrossRef Search ADS   13 Kramer, R.; Chemometric techniques for quantitative analysis . Marcel Dekker, Inc, NY, USA, ( 1998); pp. 51– 142. Google Scholar CrossRef Search ADS   14 ICH, Q1A (R2). Stability testing of new drug substances and products. In International Conference on Harmonization. Geneva, Switzerland, IFPMA, ( 2003). 15 Ni, Y., Gong, X.; Simultaneous spectrophotometric determination of mixtures of food colorants; Analytica Chimica Acta , ( 1997); 354: 163– 171. Google Scholar CrossRef Search ADS   16 Edward, V.T., David, M.H.; Comparison of multivariate calibration methods for quantitative spectral analysis; Analytical Chemistry , ( 1990); 62: 1091– 1099. Google Scholar CrossRef Search ADS   © The Author(s) 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Chromatographic Science Oxford University Press

Validated Stability-Indicating Methods for Determination of Mometasone Furoate in Presence of its Alkaline Degradation Product

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0021-9665
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Abstract

Abstract Two novel stability-indicating TLC densitometric and chemometric methods were developed for the determination of mometasone furoate (MF) in the presence of its alkaline degradation product (MF Deg). The developed TLC densitometric method (Method A) is based on the quantitative densitometric separation of MF from its alkaline degradation product on silica gel 60 F254 and measurement of the bands at 250 nm. The separation was carried out using hexane–chloroform–methanol–acetonitrile (6:6:1:0.3, by volume) as a developing system. A well-resolved and compact bands for (MF) and (MF Deg) at retention factors 0.36 and 0.66, respectively. Good resolution between (MF) and (MF Deg) assured the specificity of the proposed method. The method showed good linearity in the concentration range 0.5–5 μg/band with r2 = 0.9998. The method validation was performed according to ICH guidelines demonstrating to be accurate, precise, robust and sensitive. The LOD and LOQ were found to be 0.21 and 0.63 μg/band for MF, respectively. The developed TLC-densitometric method can be applied for identification and quantitative determination of MF in bulk drug and pharmaceutical dosage forms without any interference from excipients and degradates. Method B is a multivariate chemometric-assisted spectrophotometry, where classical least squares, principal component regression and partial least squares were applied. Statistical analysis of the results has been carried out revealing high accuracy and good precision. Introduction Glucocorticoids are potent anti-inflammatory drugs used for the treatment of allergic diseases such as allergic rhinitis and asthma (1). Mometasone furoate (MF) is (11β,16α)-9,21-dichloro-11-hydroxy-16-methyl-3,20-dioxopregna-1,4-dien-17-yl 2-furoate (Figure 1) (2). It is a synthetic 17-heterocyclic glucocorticoid available in nasal, cutaneous and oral inhaled preparations. It has high topical potency and a low risk of systemic absorption (3). It is highly absorbed due to its ester side chains which make it highly lipophilic molecule (4). Its anti-inflammatory effect is due to inhibition of the production of three inflammatory cytokines: IL-1, IL-6 and TNF-alpha (5). So, It is indicated for a number of conditions such as eczema, psoriasis and allergic reactions. Figure 1. View largeDownload slide Chemical structure of MF. Figure 1. View largeDownload slide Chemical structure of MF. A literature search revealed that different techniques were reported for the analysis of MF. HPLC and HPTLC methods were reported for quantitative determination of MF in mixture with other drugs (6–8). Also, stability-indicating HPLC method was developed for MF (9). Other methods were reported either in pharmaceutical preparations and biological fluids (10, 11). The aim of the present work was to develop two stability-indicating TLC densitometric and chemometric methods for determination of MF in the presence of its alkaline degradation product (MF Deg). The developed methods were simple, sensitive, cost effective and accurate. They can be used in routine analysis of MF in quality control laboratories. Materials and Methods Instrumentation - The absorption spectra for all measurements were carried out using Shimadzu recording spectrophotometer UV 1201 equipped with 10 mm matched quartz cells over the range 220–350 nm. The data points were collected at 1 nm intervals. The data were saved in ASCII data-file format by UV-probe personal spectroscopy software version 2.43. - Densitometric evaluation was done using Camag TLC scanner 3 S/N 130319 with winCATS software (Muttenz, Switzerland). - Camag-Linomat V auto sampler (Switzerland). - Camag microsyringe (100 μL) (Switzerland). - Precoated silica gel aluminum plates 60 F254 (Merck, Germany), 20 cm × 20 cm with 0.25 mm thickness. - UV lamp with short wavelength 254 nm (USA) was used for spot detection. - The following requirements are taken into consideration: - Source of radiation: deuterium lamp. - Scan mode: absorption mode. - Slit dimensions: 3 mm × 0.45 mm. - Scanning speed: 20 mm/s. - Result output: chromatogram and integrated peak area. - Wavelength: 250 nm. - Digital analyzer pH meter (USA) was employed for pH measurement. Software Classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS) were modeled using Matlab 8.2.0.701 (R2013b). PLS-Toolbox 2.1 under MATLABTM version 6.5 was used. Materials and reagents All chemicals and reagents used throughout this work were of pure analytical grade. Methanol and water, HPLC-grade, Fischer Scientific UK, Bishop Meadow Road, UK. Chloroform, HPLC-grade, Fluka AG, Chemische Fabrik, CH-9470 Buchs, Switzerland. Hexane, acetonitrile, ethyl acetate, sodium hydroxide and hydrochloric acid, 0.1 N aqueous solutions, El-Nasr Pharmaceutical Chemicals Co., Abu-Zabaal, Cairo, Egypt. Samples Pure standard MF was kindly supplied from SIGMA Pharmaceutical Industries, Cairo, Egypt. Its purity was found to be 99.5% according to the official method (2). Pharmaceutical preparations Elocon® cream Each gram of cream contains 1 mg MF. Batch No. 0416264 produced by South Egypt Drug Industries Company, SEDICO, under licence of Merck Sharp and Dohme (MSD), Belgium. Borgasone® lotion Each gram of lotion contains 1 mg MF. Batch No. 015047 produced by Borg Pharmaceutical Industries, Alexandria, Egypt. Alkaline degradation product (MF Deg) To 5 mL stock solution (2 mg/mL), 5 mL of 0.1 N NaOH were added. This mixture was kept at room temperature for 150 min. The degradation process was followed by TLC through the disappearance of the spot corresponding to the drug and appearance of one new spot corresponding to the formed degradation product using hexane–chloroform–methanol–acetonitrile (6:6:1:0.3, by volume) as a developing system. The solution was adjusted to pH 7 with 0.1 N HCl. Then, the solution was evaporated to dryness under vacuum. The residue was extracted with 9 mL of methanol, filtered and the volume of the extract was completed to 10 mL with methanol to obtain a stock solution labeled to contain alkaline degradation product derived from 1 mg/mL of MF. Analysis of the degradation product by the proposed procedures specified under general assay procedure was carried out. Preparation of sample solutions Stock solutions of MF (2 mg/mL) A stock solution of MF was prepared by dissolving 200 mg of the drug powder in 50 mL of methanol and the volume was completed to 100 mL with the same solvent. Stock solutions of MF Deg (1 mg/mL) A stock solution of the alkaline degradation product (1 mg/mL) was prepared as mentioned before under “Alkaline degradation product (MF Deg)”. Working standard solutions of MF and MF Deg For Method A (TLC densitometric method): Working standard solutions of MF were prepared in methanol in the concentration of 1 mg/mL. For Method B (chemometric method): Working standard solutions were prepared in methanol in the concentration of 0.5 mg/mL for both MF and MF Deg. Laboratory prepared mixtures Different aliquots of MF working standard solution (1 mg/mL) for Method A and (0.5 mg/mL) for Method B were mixed with different aliquots MF Deg working solution (1 mg/mL) for Method A and (0.5 mg/mL) for Method B to prepare mixtures of different ratios of MF and its degradation product. Procedures Method A (TLC densitometric method) Construction of calibration curve About 50 mL of the mobile phase (hexane–chloroform–methanol–acetonitrile (6:6:1:0.3), by volume) were poured into the TLC tank. The TLC tank was lined with a filter paper to help saturation of TLC chamber. The tank was presaturated with the vapors of the mobile phase system for 30 min at room temperature (25°C) before development of the plates. Accurately measured aliquots equivalent to (0.5–5 μL) of working standard MF solution (1 mg/mL) were applied in the form of bands on the marked start edge of the TLC plate using a Camag-Linomat V applicator. The bands were applied 14 mm apart from each other and 15 mm from the bottom edge of the plate with a band length of 3 mm. The plates were allowed to be air dried for 5 min, then transferred to the TLC tank allowing linear ascending development of the mobile phase. After development, the plates were removed, air dried for ~5 min then scanned at 250 nm. A calibration curve relating the optical density of each band to the corresponding concentration of MF was constructed (Figure 2). Figure 2. View largeDownload slide (3D) Densitogram of MF (Rf = 0.36) in the concentration range 0.5–5 μg/band at 250 nm using hexane–chloroform–methanol–acetonitrile (6:6:1:0.3, by volume) as a developing system. Figure 2. View largeDownload slide (3D) Densitogram of MF (Rf = 0.36) in the concentration range 0.5–5 μg/band at 250 nm using hexane–chloroform–methanol–acetonitrile (6:6:1:0.3, by volume) as a developing system. Analysis of laboratory prepared mixtures containing different ratios of MF and MF Deg Accurately measured aliquots of working standard MF solution (1 mg/mL) and MF Deg solution (1 mg/mL) were mixed to prepare different mixtures containing 10–50% of MF Deg. Then the general procedures were carried out as mentioned before under “Construction of calibration curve”. The concentrations were calculated from the corresponding regression equations. Method B (chemometric method) Spectral characteristics The absorption spectra of MF and MF Deg were scanned in the range 220–350 nm using methanol as a blank. The noisy region from 200 nm to 220 nm and the near zero absorbance region after 350 nm were rejected. Construction of the calibration set A calibration set of 14 different laboratory prepared mixtures were prepared using multilevel multifactor experimental design (12). The mixtures were prepared by transferring different aliquots from the working standard solution of MF and MF Deg (0.5 mg/mL) into a series of 10 mL volumetric flasks then the volume was completed with methanol (Table I). The absorption spectra of the mixtures were scanned over the range of 220–350 nm with respect to a blank of methanol. Table I. The Concentration of Different Mixtures of MF and its Degradation Product Used in the Training and Validation Sets Sample number  Intact MF(μg/mL)  MF deg (μg/mL)  1a  15  15  2a  15  10  3a  10  10  4a  10  20  5  20  12.5  6  12.5  20  7a  20  15  8a  15  12.5  9a  12.5  12.5  10  12.5  17.5  11  17.5  20  12a  20  17.5  13  17.5  15  14a  15  20  15  20  20  16a  20  10  17  10  17.5  18  17.5  10  19a  10  15  20  15  17.5  21  17.5  17.5  22  17.5  12.5  23a  12.5  10  24a  10  12.5  25a  12.5  15  Sample number  Intact MF(μg/mL)  MF deg (μg/mL)  1a  15  15  2a  15  10  3a  10  10  4a  10  20  5  20  12.5  6  12.5  20  7a  20  15  8a  15  12.5  9a  12.5  12.5  10  12.5  17.5  11  17.5  20  12a  20  17.5  13  17.5  15  14a  15  20  15  20  20  16a  20  10  17  10  17.5  18  17.5  10  19a  10  15  20  15  17.5  21  17.5  17.5  22  17.5  12.5  23a  12.5  10  24a  10  12.5  25a  12.5  15  aThe concentrations of mixtures used in the training set. Constructing the models To build the CLS model, the computer was fed with the absorbance and concentration matrices for the calibration set using Matlab 8.2.0.701 (R2013b). Calculations were carried out to obtain the “K” matrix. For the PCR and PLS models, the training set absorbance and concentration matrices together with PLS-Toolbox 2.1 software were used. Selection of the optimum number of factors to build the PCR and PLS models To select the number of factors for PLS and PCR methods, the cross validation method, leaving out one sample at a time, was applied (13). Given a set of 14 calibration samples, the PCR and PLS calibrations were performed on 13 samples, then the concentration of the sample left out during calibration was predicted. This process was repeated 14 times until each sample had been left out once. The predicted concentrations were compared with the known concentrations and the root mean square error of calibration (RMSEC) was then calculated. The RMSEC was calculated in the same manner each time a new factor was added to the model. Visual inspection was used for selecting the optimum number of factors. Assay of the validation set The absorption spectra of different 11 mixtures containing different ratios of MF and MF Deg (Table I) were scanned over the range of 220–350 nm with respect to a blank of methanol. The developed models were applied to predict the concentration of MF in each mixture. Assay of pharmaceutical formulations Elocon® cream An accurately measured amount of cream (20 g) equivalent to 20 mg MF was transferred into a beaker followed by addition of 9 mL methanol. The solution was covered with aluminum foil and sonicated for 30 min. In between, the flask was occasionally swirled. The solution was filtered using whatman paper 0.45 mm. The clear filtrates were collected in 10 mL volumetric flask and the volume was made up to the mark with methanol to get 2 mg/mL MF solution. Appropriate dilutions were made using methanol to get samples having concentrations within the range of each method and then the proposed methods were followed. Borgasone® lotion The 20 mL of lotion equivalent to 20 mg MF were transferred into rounded bottom flask, then evaporated to dryness under vacuum. The residue was extracted with 9 mL of methanol, filtered and the volume of the extract was completed to 10 mL with methanol to obtain 2 mg/mL MF solution. Appropriate dilutions were made using methanol to get samples having concentrations within the range of each method and then the proposed methods were followed. Results Many pharmaceutical compounds undergo degradation during storage affecting quality, safety and efficacy of the formulation. If safety and efficacy values decline, stability studies are the main judge that determines when the product should be withdrawn from the market. The ICH guidelines (14) on “Stability Testing of New Drug Substances” suggests testing the features change during storage by validated stability-indicating methods. Forced degradation was reported for MF, it was found to be susceptible to alkaline hydrolysis and photodegradation but resistant to acid hydrolysis, oxidation and dry heat degradation (9). So, the determination of MF in the presence of its alkaline degradate was important. In alkaline condition, the ester undergoes hydrolysis. The chemical structure of MF Deg is shown in Figure 3. Figure 3. View largeDownload slide Suggested degradation product results from alkaline degradation of mometasone furoate. Figure 3. View largeDownload slide Suggested degradation product results from alkaline degradation of mometasone furoate. Hence, the focus of the proposed work was to develop specific, accurate, reproducible and sensitive stability-indicating methods for the determination of MF in pure form or in pharmaceutical formulations in the presence of its alkaline degradation product. The MF band was well resolved from MF Deg band and not shifted significantly showing the stability-indicating advantage of the developed method. Also, the UV absorption spectra of MF and MF Deg shows considerable overlap, where the application of conventional spectrophotometry, its direct derivative and derivative ratio techniques failed to resolve these overlapping spectra. So, another chemometric method was applied for determination of MF and MF Deg by resolving their spectral overlap that cannot be resolved by any other direct or indirect spectrophotometric method. The suggested methods were validated and compared to the official method (2). TLC densitometric method TLC-densitometry is an important technique in the field of separation and analysis of drug mixtures and closely related compounds due to its high resolution power. It overcomes the problem of overlapping absorption spectra of closely related compounds by separating them on TLC plates and determining each ingredient by scanning the corresponding chromatogram. The proposed method shows good results regarding accuracy and precision. It could be used for determination of MF in presence of MF Deg without prior separation. To improve separation of bands, different experimental conditions were studied and optimized to provide better separation and accurate results as follows. Mobile phase Different solvent systems were tried, e.g., ethyl acetate–benzene (1:1, by volume), chloroform–ethanol (18:12, by volume), chloroform–ethyl acetate–methanol–toluene (5:2:2:2, by volume), ethyl acetate–toluene–methanol–acetonitrile–triethylamine (2.5:6:1:0.3:0.1, by volume) and hexane–chloroform–methanol–acetonitrile (6:6:1:0.3, by volume). Complete separation without tailing was obtained by using the last system where Rf = 0.36 and 0.66 for MF and MF Deg, respectively (Figure 4). Figure 4. View largeDownload slide TLC chromatogram of MF (4.5 μg/band, Rf = 0.36) and its alkaline degradation products (0.50 μg/band, Rf = 0.66). Figure 4. View largeDownload slide TLC chromatogram of MF (4.5 μg/band, Rf = 0.36) and its alkaline degradation products (0.50 μg/band, Rf = 0.66). Scanning wavelength Different scanning wavelengths were tried (230 nm, 240 nm, 250 nm and 260 nm). The wavelength of 250 nm gave the best results (Figure 4), with sharp and symmetrical peaks. Minimum noise was obtained. Band dimensions Samples were applied as bands. Thus, the band width should be chosen carefully to avoid spread of bands outside the scanning tracks due to ordinary diffusion. Also, the interspaces between bands were optimized to prevent interference between adjacent bands. Narrow band width should be avoided to prevent overloading of silica especially if higher volumes are applied resulting in tailing of the peaks. The optimum band width was found to be 3 mm and the inter-space between bands was 14 mm. Slit dimensions of scanning light beam The slit dimensions of the scanning light beam should ensure complete coverage of band dimensions on the scanned track without interference of adjacent bands. The optimum slit dimensions were found to be 3 mm × 0.45 mm. System suitability Parameters including resolution (Rs), peak symmetry, capacity factor (K′) and selectivity factor (α) were calculated. The resolution was always above 1.5, the selectivity more than one and an accepted value for symmetry factor was obtained (Table II). Table II. Parameters of System Suitability of the Developed TLC-Densitometric Method for the Determination of MF in the Presence of its Degradation Product Parameters  MF  MF Deg  Resolution (Rs)  3    Separation factor (α)  3.42    Tailing factor (T)  0.94  0.92  Capacity factor (K΄)  1.78  0.52  Parameters  MF  MF Deg  Resolution (Rs)  3    Separation factor (α)  3.42    Tailing factor (T)  0.94  0.92  Capacity factor (K΄)  1.78  0.52  The linearity of MF was checked at the selected wavelength 250 nm in the concentration range of 0.5–5 μg/band. Calibration curve relating the integrated peak areas to the corresponding concentrations of MF was constructed. The regression equation and analytical parameters of the developed method were calculated (Table III). Table III. Regression and Validation Parameters of the Developed TLC-Densitometric Method for the Determination of MF Parameters  TLC densitomertic method  Linearity range  0.5–5 μg/band  Slope (b)  1,751.4  Intercept (a)  8,057.94  Correlation coefficient (r2)  0.9998  Accuracy (mean ± SD)  99.99 ± 0.65  LODa (μg/band)  0.21  LOQa (μg/band)  0.63  Parameters  TLC densitomertic method  Linearity range  0.5–5 μg/band  Slope (b)  1,751.4  Intercept (a)  8,057.94  Correlation coefficient (r2)  0.9998  Accuracy (mean ± SD)  99.99 ± 0.65  LODa (μg/band)  0.21  LOQa (μg/band)  0.63  aLimit of detection and quantitation were determined via calculations. LOD = (SD of the intercept/slope of the standard curve) × 3.3; LOQ = (SD of the intercept/slope of the standard curve) × 10. Stability indication To assess the stability-indicating efficiency of the proposed method, it was applied to laboratory prepared mixtures containing MF and MF Deg in different ratios (10–50%). Table IV shows that the proposed method was valid for determination of intact MF in presence of up to 50% of its alkaline degradation product with good selectivity. Table IV. Determination of MF in Laboratory Prepared Mixtures by the Developed TLC Densitomertic Method Degradation products %  Concentration (μg/band)  Recovery % of MF  MF Deg  MF  10  0.5  4.5  100.77  20  1  4  99.09  30  1.5  3.5  100.2  40  2  3  100.72  50  2.5  2.5  101.45  Mean ± SD    100.45 ± 0.88  Degradation products %  Concentration (μg/band)  Recovery % of MF  MF Deg  MF  10  0.5  4.5  100.77  20  1  4  99.09  30  1.5  3.5  100.2  40  2  3  100.72  50  2.5  2.5  101.45  Mean ± SD    100.45 ± 0.88  Application of TLC densitometric method to the pharmaceutical formulations The suggested TLC densitometric method was successfully applied for the determination of MF in its pharmaceutical formulations, showing good percentage recoveries without excipients interference (Table VIII). Table VIII. Application of the Proposed Methods to the Determination of MF in Dosage Formsa Pharmaceutical formulation  TLC densitomertic method  Chemometric methods  CLS  PCR  PLS  Taken (μg/band)  Found (μg/band)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Elocon® cream  1  1.01  101.33  10  9.85  98.47  10  9.89  98.85  10  9.89  98.93  1.5  1.53  102  12.5  12.37  98.99  12.5  12.20  97.59  12.5  12.23  97.83  2  2.01  100.3  15  15.14  100.9  15  14.96  99.73  15  14.77  98.46  2.5  2.50  100.18  17.5  17.74  101.37  17.5  17.10  97.71  17.5  17.22  98.41  3  3.05  101.61  20  20.13  100.65  20  19.77  98.87  20  19.84  99.18  Mean  101.08    100.08    98.55    98.56  SD  0.81  1.27  0.89  0.52  SE  0.36  0.57  0.4  0.23  RSD  0.80  1.27  0.91  0.53  Variance  0.65  1.61  0.80  0.27  Borgasone® lotion  2  2.02  100.98  10  9.97  99.72  10  9.98  99.75  10  9.90  99.01  2.5  2.53  101.05  12.5  12.33  98.66  12.5  12.54  100.29  12.5  12.62  100.98  3  2.1  99.89  15  14.77  98.45  15  14.94  99.63  15  15.24  101.58  3.5  3.5  100.1  17.5  17.07  97.55  17.5  17.10  97.71  17.5  17.97  102.66  4  4.01  100.25  20  19.73  98.65  20  19.84  99.22  20  20.21  101.07  Mean  100.45    98.61    99.32    101.06  SD  0.53  0.77  0.98  1.32  SE  0.24  0.34  0.44  0.59  RSD  0.52  0.78  0.98  1.31  Variance  0.28  0.60  0.95  1.76  Pharmaceutical formulation  TLC densitomertic method  Chemometric methods  CLS  PCR  PLS  Taken (μg/band)  Found (μg/band)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Taken (μg/mL)  Found (μg/mL)  Recovery %  Elocon® cream  1  1.01  101.33  10  9.85  98.47  10  9.89  98.85  10  9.89  98.93  1.5  1.53  102  12.5  12.37  98.99  12.5  12.20  97.59  12.5  12.23  97.83  2  2.01  100.3  15  15.14  100.9  15  14.96  99.73  15  14.77  98.46  2.5  2.50  100.18  17.5  17.74  101.37  17.5  17.10  97.71  17.5  17.22  98.41  3  3.05  101.61  20  20.13  100.65  20  19.77  98.87  20  19.84  99.18  Mean  101.08    100.08    98.55    98.56  SD  0.81  1.27  0.89  0.52  SE  0.36  0.57  0.4  0.23  RSD  0.80  1.27  0.91  0.53  Variance  0.65  1.61  0.80  0.27  Borgasone® lotion  2  2.02  100.98  10  9.97  99.72  10  9.98  99.75  10  9.90  99.01  2.5  2.53  101.05  12.5  12.33  98.66  12.5  12.54  100.29  12.5  12.62  100.98  3  2.1  99.89  15  14.77  98.45  15  14.94  99.63  15  15.24  101.58  3.5  3.5  100.1  17.5  17.07  97.55  17.5  17.10  97.71  17.5  17.97  102.66  4  4.01  100.25  20  19.73  98.65  20  19.84  99.22  20  20.21  101.07  Mean  100.45    98.61    99.32    101.06  SD  0.53  0.77  0.98  1.32  SE  0.24  0.34  0.44  0.59  RSD  0.52  0.78  0.98  1.31  Variance  0.28  0.60  0.95  1.76  aMean of three different experiments. TLC densitometric method validation Method validation was performed according to the ICH guidelines (14). Tables III and V show the obtained results were accurate, precise and sensitive. The method showed good linear relationship as revealed by the correlation coefficient (Table III). Table V. Precision Data for the Determination of MF by the Developed TLC Densitomertic Method Intradaya  Interdayb  Added (μg/band)  Found (μg/band)  Recovery %  RSD%d  Er%c  Added (μg/band)  Found (μg/band)  Recovery %  RSD%d  Er%c  0.5  0.51  101.1  2.07  1.1  0.5  0.49  98.2  1.85  −1.8  3  3.09  102.84  0.6  2.84  3  3.03  100.99  0.06  0.99  5  4.92  98.3  0.74  −1.7  5  5.09  101.74  0.25  1.74  Intradaya  Interdayb  Added (μg/band)  Found (μg/band)  Recovery %  RSD%d  Er%c  Added (μg/band)  Found (μg/band)  Recovery %  RSD%d  Er%c  0.5  0.51  101.1  2.07  1.1  0.5  0.49  98.2  1.85  −1.8  3  3.09  102.84  0.6  2.84  3  3.03  100.99  0.06  0.99  5  4.92  98.3  0.74  −1.7  5  5.09  101.74  0.25  1.74  aThe intraday (n = 9), average of three different concentrations repeated three times within the day. bThe interday (n = 9), average of three concentrations repeated three times in three successive days. cEr %, percentage relative error. dRSD%, percentage relative standard deviation. Robustness Robustness was examined by evaluating the influence of small variations in the experimental parameters on the analytical performance of the proposed method. The studied parameters were the mobile phase composition and development distance (±0.3 cm) which were tried at one concentration level 3 μg/band for three times (Table VI). Table VI. Robustness of the Developed TLC Densitomertic Method Using Concentration of 3 μg/band of MF Parameter  Recovery (%) ± SDa  Mobile phase composition hexane–chloroform–methanol–acetonitrile   6.1:6:1:0.3  101.70 ± 0.69   6:6.1:1:0.3  102.30 ± 0.27   6.1:6.1:1:0.3  100.43 ± 1.59  Development distance   7.7 cm  99.89 ± 1.97   8.3 cm  101.1 ± 1.12  Parameter  Recovery (%) ± SDa  Mobile phase composition hexane–chloroform–methanol–acetonitrile   6.1:6:1:0.3  101.70 ± 0.69   6:6.1:1:0.3  102.30 ± 0.27   6.1:6.1:1:0.3  100.43 ± 1.59  Development distance   7.7 cm  99.89 ± 1.97   8.3 cm  101.1 ± 1.12  aAverage of three determinations. Method B (chemometric method) Chemometrics is the art of processing data with various numerical techniques in order to extract useful information (13). It is the application of mathematical and statistical methods to design optimum procedures and to provide maximum chemical information through the analysis of chemical data. Multivariate calibrations are useful in spectral analysis because the simultaneous inclusion of multiple spectral intensities can greatly improve the precision and applicability of quantitative spectral analysis (15). Unlike univariate spectrophotometry, which depends on measuring the amplitude at one wavelength. So any shift in wavelength scale will lead to false results. Also, it may be affected by several factors such as noise, scanning speed and λ. The UV absorption spectra of MF and MF Deg displays considerable overlap, where the application of conventional spectrophotometry is very difficult. In this work, three multivariate methods, CLS, PCR and PLS, were applied for the determination of MF in the presence of MF Deg. CLS model CLS model or (K) matrix was constructed using the training set (i.e., absorptivity at different wavelengths). The CLS method requires that all the components in the calibration samples must be known. The absorbance matrix of the calibration samples (14 × 131) and their corresponding concentration matrix (14 × 2) were used to find the absorptivity matrix (K-matrix).Then, the predicted concentration of MF in both the validation and pharmaceutical formulation samples were calculated using the obtained K-matrix. PCR and PLS models Unlike CLS, PCR and PLS methods have the advantage that they could determine the components under investigation even in the presence of unknown components (interfering substance) (16). The selection of the optimum number of latent variables was a very important pre-construction step. Because if the number of factors retained was more than required, more noise would be added to the data. On the other hand, if the number retained was too small, meaningful data that could be necessary for the calibration might be discarded. In this work, the cross validation method, leaving out one sample at a time and RMSECV, was calculated and used to select the optimum number of factors (13). After the PCR and PLS models were constructed, it was found that the optimum number of latent variables described by the developed models was two factors for both PCR and PLS methods as shown in Figures 5 and 6. Figure 5. View largeDownload slide RMSECV plot of the cross validation results of the calibration set as a function of the number of latent variables used to construct the PCR model. Figure 5. View largeDownload slide RMSECV plot of the cross validation results of the calibration set as a function of the number of latent variables used to construct the PCR model. Figure 6. View largeDownload slide RMSECV plot of the cross validation results of the calibration set as a function of the number of latent variables used to construct the PLS model. Figure 6. View largeDownload slide RMSECV plot of the cross validation results of the calibration set as a function of the number of latent variables used to construct the PLS model. All models were applied successfully for analysis of MF in training set and validation set (Table VII). The recoveries mean recoveries, standard deviation, root mean square of calibration (RMSEC) and root mean square of prediction (RMSEP) values were calculated (Table VII). The chemometric methods (CLS, PCR and PLS) were applied successfully to the analysis of MF in pharmaceutical applications (Table VIII). The recoveries were found to be satisfactory indicating that the additives in the pharmaceutical formulations did not interfere (Table VIII). Table VII. Analysis Results for the Prediction of the Training Set and Validation Set by the Proposed Multivariate Calibration Methods Concentration (μg/mL)a  MF recovery %  Concentration (μg/mL)b  MF recovery %  MF  MF Deg  CLS  PCR  PLS  MF  MF Deg  CLS  PCR  PLS  15  15  101.99  101.92  101.92  20  12.5  96.62  97.50  97.82  15  10  101.25  100.57  100.25  12.5  20  99.65  97.88  98.22  10  10  103.75  100.78  102.56  12.5  17.5  96.84  97.66  96.75  10  20  98.97  97.49  97.49  17.5  20  98.62  98.62  97.55  20  15  99.58  97.71  97.72  17.5  15  98.66  97.45  96.01  15  12.5  101.39  101.33  101.33  20  20  98.45  97.82  98.62  12.5  12.5  100.19  100.12  100.12  10  17.5  96.21  96.09  96.10  20  17.5  98.32  98.64  99.45  17.5  10  96.76  96.72  96.73  15  20  98.65  98.62  99.52  15  17.5  97.21  97.13  97.13  20  10  98.36  98.33  98.33  17.5  17.5  96.42  96.35  97.45  10  15  103.24  100.89  100.25  17.5  12.5  97.68  98.65  97.22  12.5  10  101.86  101.81  101.80            10  12.5  101.36  101.27  101.25            12.5  15  100.94  100.86  100.86            Mean    100.70  100.02  100.20  Mean    97.56  97.44  97.24  SD  1.75  1.54  1.51  S.D.  1.13  0.83  0.82  RMSEC  0.003  0.003  0.002  RMSEP  0.03  0.03  0.04  Concentration (μg/mL)a  MF recovery %  Concentration (μg/mL)b  MF recovery %  MF  MF Deg  CLS  PCR  PLS  MF  MF Deg  CLS  PCR  PLS  15  15  101.99  101.92  101.92  20  12.5  96.62  97.50  97.82  15  10  101.25  100.57  100.25  12.5  20  99.65  97.88  98.22  10  10  103.75  100.78  102.56  12.5  17.5  96.84  97.66  96.75  10  20  98.97  97.49  97.49  17.5  20  98.62  98.62  97.55  20  15  99.58  97.71  97.72  17.5  15  98.66  97.45  96.01  15  12.5  101.39  101.33  101.33  20  20  98.45  97.82  98.62  12.5  12.5  100.19  100.12  100.12  10  17.5  96.21  96.09  96.10  20  17.5  98.32  98.64  99.45  17.5  10  96.76  96.72  96.73  15  20  98.65  98.62  99.52  15  17.5  97.21  97.13  97.13  20  10  98.36  98.33  98.33  17.5  17.5  96.42  96.35  97.45  10  15  103.24  100.89  100.25  17.5  12.5  97.68  98.65  97.22  12.5  10  101.86  101.81  101.80            10  12.5  101.36  101.27  101.25            12.5  15  100.94  100.86  100.86            Mean    100.70  100.02  100.20  Mean    97.56  97.44  97.24  SD  1.75  1.54  1.51  S.D.  1.13  0.83  0.82  RMSEC  0.003  0.003  0.002  RMSEP  0.03  0.03  0.04  aThe concentrations of mixtures used in the training set. bThe concentrations of mixtures used in the validation set. Statistical analysis The proposed TLC densitometric and chemometric methods were statistically compared to the reference method (2) using Student’s t-test and variance ratio F-test at 95% confidence level. Table IX shows the calculated t and F values were less than the theoretical ones, indicating no significant differences between the proposed methods and the official one (2). Table IX. Statistical Comparison of the Results Obtained by the Proposed Methods and the Official Method (2) for the Determination of Mometasone Furoate   TLC densitomertic method  Chemometric methods  Official method (2)  CLS  PCR  PLS  Mean  100.45  98.61  99.32  101.06  99.5  SD  0.53  0.77  0.98  1.32  0.98  RSD%  0.52  0.78  0.98  1.31  0.99  Variance  0.28  0.6  0.95  1.76  0.95  n  6  5  5  5  5  F-test  3.39(5.19)a  1.58 (8.39)a  1.03 (8.39)a  1.85 (8.39)a    Student’s t-test  2.06(2.202)a  1.6 (2.306)a  0.29(2.306)a  2.13(2.306)a      TLC densitomertic method  Chemometric methods  Official method (2)  CLS  PCR  PLS  Mean  100.45  98.61  99.32  101.06  99.5  SD  0.53  0.77  0.98  1.32  0.98  RSD%  0.52  0.78  0.98  1.31  0.99  Variance  0.28  0.6  0.95  1.76  0.95  n  6  5  5  5  5  F-test  3.39(5.19)a  1.58 (8.39)a  1.03 (8.39)a  1.85 (8.39)a    Student’s t-test  2.06(2.202)a  1.6 (2.306)a  0.29(2.306)a  2.13(2.306)a    aFigures between parenthesis represent the corresponding tabulated values of t and F at P = 0.05. Discussion This study aims to develop two new stability-indicating methods for the determination of MF in the presence of its alkaline degradation product. In the TLC densitometric method, sharp and symmetric peak of MF was obtained with good resolution from excipients and degradate peaks. Also, a three multivariate chemometric-assisted spectrophotometric methods were applied. The developed methods can be applied for the determination of MF in bulk or in pharmaceutical preparations without any interference from excipients and alkaline degradation product. Results of validation parameters indicate that both methods are linear, accurate, precise and robust. Conclusion The objective of the present work was achieved by quantitative determination of MF in the presence of its alkaline degradate in bulk and in pharmaceuticals. New TLC densitometric method was developed and validated for MF determination without any interference from excipients and degradation products. The proposed method has the merits of high sensitivity, less time consuming and more economical than other separation methods. Also, the chemometric methods studied in this work can be performed easily with software support showing high resolving power. They have the advantage of speed due to avoiding the separation step. The proposed methods can be used in the routine quality control analysis without interference of commonly encountered pharmaceutical formulation additives or the degradation products. References 1 Melton, B.A., Francis, C., Desmond, P., Mark, W., Sudhakar, P, Robert, P.C., et al.  .; Bioavailability and metabolism of mometasone furoate following administration by metered-dose and dry-powder inhalers in healthy human volunteers; Journal of Clinical Pharmacology , ( 2000); 40: 1227– 1236. Google Scholar PubMed  2 The British Pharmacopeia.; Her majesty’s . The Stationary Office, London, ( 2007). 3 Courtney, C., Lisa, N.P., Peter, T.D.; A review of the pharmacology and pharmacokinetics of inhaled fluticasone propionate and mometasone furoate; Clinical Therapeutics , ( 2001); 23( 9): 1339– 1354. Google Scholar CrossRef Search ADS PubMed  4 Derendorf, H., Meltzer, E.O.; Molecular and clinical pharmacology of intranasal corticosteroids: clinical and therapeutic implications; European Journal of Allergy and Clinical Immunology , ( 2008); 63( 10): 1292– 1300. 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Google Scholar CrossRef Search ADS PubMed  8 Devanshi, G., Ankit, B., Bhoomi, D.; Method development and validation for estimation of clotrimazole, fusidic acid and mometasone furoate in cream by RP-HPLC; World Journal of Pharmacy and Pharmaceutical Sciences , ( 2017); 6( 5): 1204– 1219. 9 Ramzia, I.E., Marwa, A.F., Manal, A.E., Enas, H.T.; Forced degradation of mometasone furoate and development of two RP-HPLC methods for its determination with formoterol fumarate or salicylic acid; Arabian Journal of Chemistry , ( 2016); 9: 493– 505. Google Scholar CrossRef Search ADS   10 Sahasranaman, S., Tang, Y, Biniasz, D., Hochhaus, G.; A sensitive liquid chromatography-tandem mass spectrometry method for the quantification of mometasone furoate in human plasma; Journal of Chromatography B , ( 2005); 819( 1): 175– 179. Google Scholar CrossRef Search ADS   11 Patel, H.D., Patel, M.M.; Development and validation of UV spectrophotometric method for simultaneous estimation of terbinafine hydrochloride and mometasone furoate in combined dosage form; Asian Journal of Research in Chemistry , ( 2013); 6( 1): 29– 34. 12 Richard, G.B.; Multilevel multifactor designs for multivariate calibration; Analyst , ( 1997); 122: 1521– 1529. Google Scholar CrossRef Search ADS   13 Kramer, R.; Chemometric techniques for quantitative analysis . Marcel Dekker, Inc, NY, USA, ( 1998); pp. 51– 142. Google Scholar CrossRef Search ADS   14 ICH, Q1A (R2). Stability testing of new drug substances and products. In International Conference on Harmonization. Geneva, Switzerland, IFPMA, ( 2003). 15 Ni, Y., Gong, X.; Simultaneous spectrophotometric determination of mixtures of food colorants; Analytica Chimica Acta , ( 1997); 354: 163– 171. 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Journal of Chromatographic ScienceOxford University Press

Published: Mar 1, 2018

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