This paper includes the development of a novel, systematic, quality by design (QbD)-based high-performance thin-layer chromatography (HPTLC) method for the simultaneous estimation of torsemide and eplerenone. Chromatographic separation was carried out on aluminum-backed silica gel 60 F254 plates using toluene–ethyl acetate–glacial acetic acid (7:3:0.1, V/V) as the mobile phase. UV detection was carried out at 297 nm for torsemide and 247 nm for eplerenone. A 3-factor 17-run regular 3-level factorial design was applied to factor screening studies, and Box-Behnken design was utilized for optimization of the experimental parameters of HPTLC for obtaining anticipated chromatographic conditions. Risk assessment was executed to understand the basic method parameters. From the risk assessment, 3 independent parameters, such as band length, saturation time, and wavelength, were selected and studied for the impact of these 3 parameters on the responses. The method yields compact and well-resolved band at RF = 0.24 ± 0.02 for torsemide and RF = 0.50 ± 0.02 for eplerenone. In the linear regression analysis carried out for torsemide and eplerenone, the regression coefficient was found to be r2 = 0.999 for torsemide and r2 =0.995 for eplerenone. The method was validated for validation parameters like accuracy, precision, robustness, limit of detection, and limit of quantification as per the International Conference on Harmonization (ICH) guidelines.

Summary In the present study, a design of experiment (DoE) approach was used to optimize chromatographic conditions for the development of a high-performance thin-layer chromatography (HPTLC) method for the simultaneous estimation of metformin hydrochloride (MET) and ursodeoxycholic acid (URSO) in pharmaceutical dosage form. The critical factors were identified using a Taguchi design, and after identification of critical factors, optimization was done using Box-Behnken design (BBD). BBD was used to optimize the compositional parameters and to evaluate the main effect, interaction effects, and quadratic effects of the mobile phase compositions, development distance, and saturation time on the retardation factor (RF) of both drugs. HPTLC separation was performed on aluminum plates pre-coated with silica gel 60 F254 as the stationary phase, using toluene–ethanol–acetone–formic acid (4.5:2:2.5:0.85, V/V) as the mobile phase at a wavelength of 234 nm and 700 nm for MET and URSO, respectively. A sharp and well-resolved peak was obtained for MET and URSO at RF values of 0.19 and 0.80 min, respectively. The calibration curve was in the range of 5000–40000 ng per spot and 1500–12000 ng per spot for MET and URSO, with r2 = 0.984 and r2 = 0.980, respectively. The method was validated for linearity, accuracy, precision, limit of detection, limit of quantification, and specificity. To provide a better visualization of the statistically significant factors derived from the statistical analysis, the perturbation plot and response surface plot for the effect of independent variables on the RF of MET and URSO were evaluated. Stability study was performed under different stress conditions such as acid and alkali hydrolysis, oxidation, and temperature. The developed method was able to resolve drugs and their degradation products formed under the afore-mentioned conditions.

Summary The presented study describes the development, optimization, and validation of a method for the determination of four structurally different anthelmintics (benzimidazole, diphenyl sulfide, imidazothiazole, hexahydropyrazine, and tetrahydropyrimidine) in water samples. The studied compounds were albendazole, febantel, levamisole, praziquantel, and pyrantel pamoate. The method involves solid-phase extraction and preconcentration of the anthelmintics, separation by thin-layer chromatography (TLC), and quantification by videodensitometry. TLC and preparative TLC separation was performed on silica gel 60 F254 plates with chloroform-methanol-formic acid as the mobile phase. Spots were detected and quantified at λ = 254 nm by videodensitometry. The method provides a linear response over a concentration range of 200–1500 µg L−1, depending on the anthelmintic with a correlation coefficient of 0.9888 in most cases, except for albendazole (0.9634) and pamoic acid (0.9654) as a secondary component of pyrantel pamoate. Also, the method has revealed limits of detection (100–300 µg L−1), good precision (intra- and inter-day) with a relative standard deviation below 13%, and recoveries above 95% for all investigated pharmaceuticals. The developed method has been successfully applied to the analysis of anthelmintics in production wastewater samples obtained from the local pharmaceutical industry. In order to determine the structures of two compounds detected by TLC of pyrantel pamoate, the spots were separated by preparative TLC, and the structures of the isolated samples were analyzed using 1H and 13C nuclear magnetic resonance (NMR) spectroscopy.

Summary A simple, sensitive, specific, rapid, and accurate high-performance thin-layer chromatographic (HPTLC) method has been developed and validated for the simultaneous estimation of quercetin (QCT) and resveratrol (RSV). Chromatographic separation was performed over pre-coated TLC plates (60 F254, 20 × 10 cm, 250 µm thickness, Merck, Darmstadt, Germany) through a linear ascending technique. Among the different combinations of the mobile phases used, the best separation was achieved in the toluene-ethyl acetate-formic acid (6:2.5:1.5, V/V) mixture. Detection and quantification were achieved at 286 nm through the spectrodensitometric analysis. Analytical performance of the proposed HPTLC method was validated according to the International Conference for Harmonization (ICH) guidelines with respect to linearity, accuracy, precision, detection, and quantitation limits, robustness, and specificity. The calibration curves were linear in the range of 50–2500 ng per spot for both QCT and RSV, with a correlation coefficient (R2) of 0.998 and 0.997 for the QCT and RSV, respectively. The detection limits were 122.33 and 370.7 for QCT and RSV, respectively, and the quantitation limits were 27.35 and 82.93 for QCT and RSV, respectively. Additionally, forced degradation studies of QCT and RSV were established. The validated HPTLC method was successfully applied to the simultaneous determination of QCT and RSV in the nanoformulation.

Two validated, simple, and precise chromatographic methods were described for the determination of vildagliptin (VIL) and metformin (MET) in the presence of metformin toxic impurity, melamine (MEL). Method 1 is thin-layer chromatography (TLC)—densitometric method, at which methanol—chloroform—formic acid (7:3:0.3, by volume) was used as the developing system, and separation was carried out on Merck TLC silica gel 60 F254 aluminum sheets. The developed plates were air-dried and scanned at 215 nm. Linearity was constructed in the range of 0.2–2.6, 0.4–4.5, and 0.05–1.4 µg per band of VIL, MET, and MEL, respectively. Method 2 is reversed-phase ultra-performance liquid chromatography (RP-UPLC), where the separation was performed on a C18 column using methanol-acetonitrile—0.01 m sodium dihydrogen phosphate solution containing 50% 0.01 m sodium lauryl sulfate, pH = 5 with H3PO4 as the mobile phase at a flow rate of 1 mL min−1 at 205 nm. The calibration curves showed good linear relationships in the concentration ranges of 1–50, 2–70, and 0.5–30 µg mL−1 of VIL, MET, and MEL, respectively. The developed methods were applied to Galvus Met® tablets, and no interference from excipients was observed. The methods were validated as per the International Conference on Harmonisation (ICH) guidelines, and they compared favorably with the reported one.

A sensitive and simple high-performance thin-layer chromatographic method is developed and validated according to the International Conference on Harmonisation (ICH) guidelines. The procedure was applied for the estimation of orlistat in different pharmaceutical preparations. In the proposed method, thin-layer chromatography aluminum sheets pre-coated with silica gel were employed as the stationary phase. A number of solvent mixtures were used as the mobile phase for trials to obtain compact bands of orlistat. The solvent mixture consisting of chloroform and methanol (98:2) was found to be the best. The data obtained from the calibration curves of standard orlistat showed a good linear relationship over the concentration range of 1000–3800 ng per band with respect to the area. Scanning was performed at λ = 200 nm, where the correlation coefficient (R2) was 0.970, and the linear regression equation was found to be: y = 4.1419x − 4181.1. After revealing of the spots by anisaldehyde—conc. sulfuric acid, compact violet bands were obtained and, accordingly, scanning was performed at λ = 600 nm, where a good linear relationship over the concentration range of 600–4000 ng per band with respect to the area was obtained. The correlation coefficient (R2) was 0.991 with a linear regression equation: y = 4.025x − 1159.3. The method was evaluated regarding accuracy, precision, limits of detection and quantification, and robustness. Revealing of the spots by anisaldehyde—conc. sulfuric acid improved the sensitivity of the method and increased the range within which a linear relationship between concentration and response occurs.

The potential of high-performance thin-layer chromatographic (HPTLC) fingerprinting in identifying differences in sandalwood essential oils from 5 sandalwood species, namely, Santalum album, Santalum spicatum, Santalum austrocaledonicum, Santalum paniculatum, Santalum lanceolatum, and a natural substitute for sandalwood, Osyris lanceolata, was explored. Variation was observed in the profile of bands (RF values and color) and peak intensity profiles displayed by the essential oils across and within the essential oils studied with some bands being unique to the individual species. The potential of HPTLC fingerprinting as a quality control tool in authenticating sandalwood oils in the sandalwood industry was demonstrated in the present study.

High-performance thin-layer chromatography, which is a quick qualitative and quantitative method, was used to determine 3 kinds of organic acids, namely, ellagic acid, gallic acid, and ferulic acid, in Elaeagnus angustifolia L. leaves originating from 10 regions in Xinjiang Uygur Autonomous Region and 7 different growth stages in Urumqi, China. The developing solvent was toluene‒ethyl formate‒formic acid (5:6.55:1.49), the temperature was 25 ± 1°C, the humidity was 10%, and the detection wavelength was 290 nm. The linear ranges of ellagic acid, gallic acid, and ferulic acid were 0.0564–0.6768, 0.1006–1.2072, and 0.1004–1.2048 μg, respectively, and the linear correlation coefficients were 0.9953, 0.9993, and 0.9970, respectively. The results showed good linear relationships. Precision analyses revealed a relative standard deviation (RSD) of <2.00%. The sample was stable within 24 h at room temperature at RSD ≤3.00%. The average recoveries of ellagic acid, gallic acid, and ferulic acid were 101.4%, 100.9%, and 100.2%, respectively. This method is reliable and can be used to determine three organic acids in the leaves of E. angustifolia L. from different regions and different growth stages.

Fenugreek is one of the oldest medicinal plants known by mankind. The aim of this study is to evaluate the effect of environmental conditions on the saponin contents of the plant. The amount of diosgenin in different samples of fenugreek was estimated by high-performance thin-layer chromatography (HPTLC). The developed method was validated, in accordance with the International Conference on Harmonization (ICH) guidelines for precision, accuracy, and robustness. HPTLC was carried out using hexane-acetone (8:2%, v/v) on 20 cm × 10 cm glass coated silica gel 60 F254 plates. The developed plates were scanned and quantified densitometrically at λ = 430 nm. Linear regression analysis revealed a good linear relationship between the area under the peak and the amount of diosgenin in the range of 50–400 ng per band. The amount of diosgenin which reflects the total saponin contents varied according to the country of origin. The sample obtained from Yemen showed the highest amount of diosgenin followed by the Saudi sample. Both locations represent areas with the highest altitude (Yemen) and the highest temperature (Saudi).