Authors:
Marillia Castilho Silva Toti Postgraduate in Pharmaceutical Sciences, Faculty of Pharmaceutical Sciences, Federal University of Alfenas, Alfenas, MG, Brazil

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Rudy Bonfilio Quality Control Laboratory, Faculty of Pharmaceutical Sciences, Federal University of Alfenas, Alfenas, MG, Brazil

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Magali Benjamim de Araújo Quality Control Laboratory, Faculty of Pharmaceutical Sciences, Federal University of Alfenas, Alfenas, MG, Brazil

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https://orcid.org/0000-0002-3564-4338
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Abstract

In this study, a multivariate optimization strategy was used to develop and validate a simple, rapid, accurate, cost-effective, and stability-indicative RP-HPLC analytical method for quantifying hydroxychloroquine sulphate (HCQ) in coated tablets. The validation conditions involved isocratic elution mode, using a mixture of buffer solution at pH 2.2 and methanol (74:26, v/v) as the mobile phase, an Agilent® reverse phase column, model Zorbax Eclipse Plus C18 (250 cm × 4.6 mm × 5 μm), a flow rate of 1.3 mL min−1, column temperature 40 °C and detection at 343 nm. The method showed linearity in the range of 4–44 μg mL−1, with a correlation coefficient (R) of 0.9998. Recovery obtained average values of between 99.71 and 100.84% and precision with average RSD values of <2%. The robustness demonstrated by assessing the effect of seven variables (pH of the mobile phase buffer; percentage of methanol; filter brand; mobile phase flow rate; wavelength; column temperature and sample agitation time), with effect values for each variable lower than the calculated value of s√2 (1.43), showed that none of these factors had a significant influence on the analytical response. The method was applied to samples of the reference medicine Plaquinol® 400 mg and similar Reuquinol 400 mg, nomenclature established by the National Health Surveillance Agency (Anvisa), law no. 978 of 10 February 1999, purchased from local pharmacies. Results showed advantages and benefits in relation to the official method and those reported in the literature. The application of the multivariate strategy, the choice of methanol, in a lower proportion in the organic phase, due to its low toxicity, economy and easier availability compared to acetonitrile, and the other organic solvents used was a promising and important alternative for the analytical method. Furthermore, the use of reversed stationary phase, common in quality control laboratories, provided an analyte retention time of 4.595 min, demonstrating good performance and speed in routine analyses.

Abstract

In this study, a multivariate optimization strategy was used to develop and validate a simple, rapid, accurate, cost-effective, and stability-indicative RP-HPLC analytical method for quantifying hydroxychloroquine sulphate (HCQ) in coated tablets. The validation conditions involved isocratic elution mode, using a mixture of buffer solution at pH 2.2 and methanol (74:26, v/v) as the mobile phase, an Agilent® reverse phase column, model Zorbax Eclipse Plus C18 (250 cm × 4.6 mm × 5 μm), a flow rate of 1.3 mL min−1, column temperature 40 °C and detection at 343 nm. The method showed linearity in the range of 4–44 μg mL−1, with a correlation coefficient (R) of 0.9998. Recovery obtained average values of between 99.71 and 100.84% and precision with average RSD values of <2%. The robustness demonstrated by assessing the effect of seven variables (pH of the mobile phase buffer; percentage of methanol; filter brand; mobile phase flow rate; wavelength; column temperature and sample agitation time), with effect values for each variable lower than the calculated value of s√2 (1.43), showed that none of these factors had a significant influence on the analytical response. The method was applied to samples of the reference medicine Plaquinol® 400 mg and similar Reuquinol 400 mg, nomenclature established by the National Health Surveillance Agency (Anvisa), law no. 978 of 10 February 1999, purchased from local pharmacies. Results showed advantages and benefits in relation to the official method and those reported in the literature. The application of the multivariate strategy, the choice of methanol, in a lower proportion in the organic phase, due to its low toxicity, economy and easier availability compared to acetonitrile, and the other organic solvents used was a promising and important alternative for the analytical method. Furthermore, the use of reversed stationary phase, common in quality control laboratories, provided an analyte retention time of 4.595 min, demonstrating good performance and speed in routine analyses.

Introduction

Hydroxychloroquine sulfate (HCQ) is a white or slightly yellowish crystalline compound derived from 4-aminoquinolones with molecular formula C18H26ClN3O.H2SO4 and molecular weight of 434.0, highly soluble in water and practically insoluble in ethanol (96%) and methylene hydrochloride [1, 2].

Originally HCQ was used as an antimalarial agent, but it has also been used in the treatment of rheumatoid arthritis (acute or chronic refractory) and lupus erythematosus (chronic or systemic discoid) [3–5]. More recent studies investigated new potential applications for hydroxychloroquine sulfate, including its use in the treatment of dengue virus infection and in the inhibition of maternal-fetal transmission of Zika virus through modulation of the placental autophagy pathway [6, 7].

The analytical methods described in the literature for the quantification of HCQ are mostly applied to biological matrices. However, there have been a few publications for pharmaceutical matrices and for the drug in isolation (Table 1). Current methods involve both sample preparation and separation using organic solvents that have longer extraction times and are potentially harmful to the environment. Acetonitrile, formic acid, trifluoracetic acid, diethylamine and n-hexane are generally used in the composition of mobile phases [8–30], such as that described for tablets in the American Pharmacopoeia [31] which uses a mobile phase composed of solution A and solution B (97:3), where solution A is composed of acetonitrile: water: phosphoric acid (10:90:0.2) and solution B is acetonitrile: water: phosphoric acid (80:20:0.1). In addition, an electrochemical study using differential impulse voltammetry for the determination of HCQ on the product Plaquenil has been reported in the literature [32]. The method showed a detection limit of 11.2 µg mL−1 with a RSD of 0.46% and adequate accuracy and precision.

Table 1.

Analytical methods applied to the quantification of hydroxychloroquine sulphate in biological and pharmaceutical matrices by high performance liquid chromatography

YearConditionAnalytical methodologyMatricesRetention time (min)Run time (min)Reference
2011C8 column (50 × 2.1 mm, 5 μm), mobile phase 0.1% formic acid in water added acetonitrile (94:6 v/v), isocratic elusion, flow 0.5 mL min−1, temperature 25 °C.LC-MS/MSHuman plasma1.83.0[8]
2013C8 column (50 × 2.1 mm, 5 μm), mobile phase 0.1% formic acid, methanol and water added ammonium formate, gradient elusion, flow 2.0 mL min−1, temperature 70 °C.LC- ESI + MS/MSSerum2.17.0[9]
2013C18 column (250 × 4.6 mm, 5 µm), mobile phase acetonitrile, methanol and ammonium formate (5:5:90 v/v), flow 0.8 mL min−1, temperature 30 °C.LC-PDA, ESI-MSn, LC-MS-TOFPharmaceutical≈20.040.0[10]
2014C18 column (50 × 3.0 mm, 3 µm), mobile phase formic acid, methanol and water, gradient elution, flow 0.5 mL min−1, room temperature.LC-MS/MSHuman blood3.39.5[11]
2015C18 column (250 × 6.0 mm, 5 µm), mobile phase orthophosphoric acid, acetonitrile, methanol, water and sodium 1-petanesulphonate, isocratic elution, flow 2 mL min−1, temperature 30 °C.HPLC-UV

343 nm
Animal plasma5.810.0[12]
2015XTerra phenyl® hybrid column (250 × 4.6 mm, 5 µm), mobile phase glycine buffer, sodium chloride and methanol, isocratic elution, flow 1.2 mL min−1, temperature 50 °C.HPLC-FLHuman blood≈7.018.0[13]
2015C18 column (50 × 2.1 mm, 2.6 µm), mobile phase 0.6% formic acid in water and methanol (80:20 v/v), flow 0.5 mL min−1, room temperature.LC- MS/MSHuman plasma≈1.5≈2.0[14]
2017BEH Phenyl® RP column (50 × 2.1 mm, 1.7 µm), mobile phase 1% triethylamine aqueous solution added to 1 mM oxalic acid and methanol, gradient elution, flow 0.5 mL min−1, temperature 35 °C.UHPLC-UV a 343 nmHuman serum1.23.0[15]
2018C18 column (50 × 4.6 mm, 3 µm), mobile phase 0.2% formic acid in water and 0.1% formic acid in methanol, gradient elution, flow 0.5 mL min−1, temperature 40 °C.LC-ESI-MS/MSAnimal serum or tissue homogenates4.77.5[16]
2018C18 column (150 × 4.6 mm, 5 µm), mobile phase water, methanol, acetonitrile and sodium dodecyl sulphate, isocratic elution, flow 1.0 mL min−1, temperature 40 °C.HPLC-FLHuman whole blood≈8.020.0[17]
2019RP-UHPLC column (100 × 2.1 mm, 1.7 µm), mobile phase piperazine buffer (pH 9.8) and acetonitrile (68:32 v/v), isocratic elution, flow 0.4 mL min−1, temperature 40 °C.UHPLC-FLHuman whole blood3.77.0[18]
2020C18 column (250 × 4.6 mm, 5 µm), mobile phase sodium phosphate buffer (pH 8.0) and acetonitrile (60:40 v/v), isocratic elution, flow 1.0 mL min−1, temperature 40 °C.HPLC-FLHuman blood≈5.09.0[19]
2020Xterra Phenyl® column (250 × 4.6 mm, 5 µm), mobile phase potassium phosphate buffer (pH 2.5) and acetonitrile (70:30 v/v), gradient elution, flow 1.5 mL min−1, temperature 25 °C.LC-UV

220 nm
Pharmaceutical13.050.0[20]
2020RP-UPLC C18 column (50 × 2.1 mm, 2.6 µm), mobile phase 0.4% aqueous formic acid solution added to 10 mM ammonium formate and 0.4% formic acid in acetonitrile, gradient elution, flow 0.5 mL min−1.LC-HRMSHuman plasma

Human blood

Human serum
4.0[21]
2021μ-Bondapack® C18 RP-HPLC column (250 × 4.6 mm), mobile phase acetonitrile:methanol: aqueous solution of monopotassium phosphate (1.5 g. L−1, 10:10:80 v/v) with 0.01% triethylamine, isocratic elution, flow 1.5 mL min−1.HPLC-UV

340 nm
Human blood5.77.0[22]
2021Oasis HLB column (30 × 2.1 mm, 20 µm), mobile phase water, formic acid, acetonitrile and Mass Tox® TDM, gradient elution, flow 1.5 mL min−1, temperature 25 °C.LC-MS/MSHuman serum2.35.0[23]
2021Pursuit pentafluorophenyl column (PFP, 50 × 2.0 mm, 3.0 µm), mobile phase 0.5% trifluoroacetic acid aqueous solution and 0.5% trifluoroacetic acid in acetonitrile, gradient elution, flow 0.5 mL min−1.LC-MS/MSHuman plasma0.93.5[24]
2021Chiralpak AD-H® normal phase chiral column (150 × 4.6 mm, 5 µm), mobile phase 0.5% diethylamine solution in n-hexane with isopropanol (93:7 v/v), isocratic elution, flow 0.8 mL min−1, temperature 20 °C.HPLC-chiral

UV

343 nm
Human plasma26.0 (R-HCQ)

29.0 (S-HCQ)
35.0[25]
2022Agilent® Zorbax SB-C8 RP-HPLC column (150 × 2.1 mm, 3.5 µm), mobile phase A: 10 mM ammonium acetate aqueous solution with 0.2% formic acid, mobile phase B: methane, gradient elution, flow 0.25 mL min−1, temperature 40 °C.LC-MS/MSRat blood≈3.04.0[26]
2022Thermo Scientific® Accucore Phenyl Hexyl column (100 × 2.1 mm, 2.6 µm), mobile phase A: 2 mM ammonium formate aqueous solution and 0.1% formic acid, mobile phase B: 2 mM ammonium formate and 0.1% formic acid in methanol and acetonitrile (50:50 v/v), gradient elution, flow 0.5 mL min−1, temperature 40 °C.LC-HRMS/MSHuman plasma Culture medium15.0[27]
2022Agilent® Eclipse XDB-C18 RP column (150 × 3 mm, 3.5 µm), mobile phase phosphate buffer (pH 3.6) and acetonitrile (96:6% v/v), isocratic elution, flow 1.0 mL min−1, temperature 30 °C.LC-DAD

343 nm
Human blood≈15.017.5[28]
2022Symmetry® C18 RP column (250 × 4.6 mm, 5 µm), mobile phase 20 mM monopotassium phosphate aqueous solution, acetonitrile (85:15 v/v), flow 0.8 mL min−1.UHPLC-MS/MS

254 nm
Human blood[29]
2023Symmetry® C18 column (4.6 mm × 250 mm, 5 μm), mobile phase of 20 mmol L−1 KH2PO4-acetonitrile (85:15, ν/ν, pH adjusted to 3 by H3PO4), flow 0.8 mL min−1, temperature 35 °C.HPLC

254 nm
Human blood[30]

Abbreviations: LC-MS/MS, liquid chromatography-mass spectrometry; HPLC-MS/MS, high performance liquid chromatography-mass spectrometry; UHPLC-MS/MS; ultra-high performance liquid chromatography-mass spectrometry; HPLC-FL, high performance liquid chromatography-fluorecense; LC-DAD, liquid chromatography diode array detector; HPLC-UV, high performance liquid chromatography-ultravioleta detector.

Multivariate optimization is an important tool for the development of high-performance analytical methods. Among the experimental design techniques for multivariate optimization, 2k factorial design, Doehlert matrix and response surface methodology have received more attention, since the number of experiments to be performed is greatly reduced [33–36].

The analytical study described in this work was conducted with samples of the reference medicine Plaquinol® 400 mg and the similar medicine Reuquinol 400 mg, nomenclature established by the National Health Surveillance Agency – Anvisa in law no. 9.978 of February 10, 1999, purchased from local pharmacies. This law defines a “reference medicine” as “an innovative product registered with the federal body responsible for health surveillance and marketed in the country, whose efficacy, safety and quality have been scientifically proven to the competent federal body at the time of registration”. The same law defines a “similar medicine” as “one that contains the same active ingredient(s), has the same concentration, pharmaceutical form, route of administration, dosage and therapeutic, preventive or diagnostic indication as the reference medicine registered with the federal body responsible for health surveillance, and may differ only in characteristics relating to the size and shape of the product, shelf life, packaging, labelling, excipients and vehicles, and must always be identified by trade name or brand” [37, 38].

In this context, the aim of this study was to apply the multivariate optimization strategy to develop and validate a stability-indicating RP-HPLC analytical method for the quantification of HCQ on its own and in tablet pharmaceutical form, with the lowest possible proportion of organic solvent in the mobile phase, with rapid separation, and which met the validation criteria of the official guidelines.

Experimental

Instruments

Analyses were performed in a high-performance liquid chromatography system, Shimadzu® Class - VP (Kyoto, Japan), equipped with LC-10AD VP pump, CTO 10-A VP oven, DGU-14A degasser, SPD-10A detector and SCL-10A VP controller. Manual injections were performed with a 710 SNR 100 µL fixed needle syringe from Hamilton® (Reno, USA) and Shimadzu® Liquid Chromatography System (Kyoto, Japan), with LC-Solution Integration System, LC-20AD pump, DGU-20A 3r degasser, SIL-20AC HT auto-injector, model SPD-M20A DAD detector, CTO-20A oven and CBM-20A controller and Statistica® software version 7.0 (StatSoft Inc.®, Tulsa, Oklahoma, USA). HPLC-grade ultrapure water was prepared using the Gehaka® OS20LXE reverse osmosis system. The pH was measured using a Marconi® PA 200 pH meter equipped with a glass electrode. The ultrasound bath was carried out using an Ultronic - Unique® (Indaiatuba, Brazil) model USC – 2800 A.

Reagent and chemicals

Standard hydroxychloroquine sulphate with a purity of 100.20% was purchased from Fagron®. The reference medicine Plaquinol® 400 mg and the similar medicine Reuquinol 400 mg, both coated tablets with a declared hydroxychloroquine sulphate content of 400 mg, were purchased from local drugstores. A single batch of each medicine was used. All reagents were of analytical grade, namely: phosphoric acid (ortho) from Vetec Química Fina® (Rio de Janeiro, Brazil), sodium hydroxide from Neon Comercial® (Suzano, Brazil) and methanol from Dinâmica Química Contemporânea® (São Paulo, Brazil). High-quality HPLC water was used in all the tests to prepare the pH 2.2 buffer.

Coefficient of distribution and solubility

For the development of the analytical method, analysis of the variation of the distribution coefficient (LogD) of HCQ as a function of pH variation was performed using ACD/ChemsketchTM Freeware software (Advanced Chemistry Development Inc., ACD/Labs). The solubility of HCQ in different solvents was obtained from literature [1, 2]. For this study, the mobile phase components were selected: diluent (pH 2.2 buffer solution) and methanol. The proportions of the mobile phase components were changed according to each step of the multivariate optimization. All the tests in the optimization stage were carried out with HCQ solutions theoretically with a final concentration of 40.0 μg mL−1.

Wavelength selection

In order to select the most suitable wavelength for developing the HPLC method, a spectral scan was carried out in the 400 and 200 nm range with standard HCQ solutions at concentrations of 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 40.0 and 50.0 μg mL−1.

Planning of experiments oriented to method optimization

Multivariate optimization for the HPLC method was based on the quality by design (QbD) tool approach. Initially, the full factorial design 23 was used to evaluate the potentially significant factors of the method. Three factors with two levels were evaluated: percentage of methanol in the mobile phase, mobile phase flow rate and chromatographic column temperature. The analytical response adopted in this experimental design was based on the desirability function approach established by Derringer and Suich [35], which was used to simultaneously optimize the analyte retention time, peak asymmetry and capacity factor. After defining the functions to be applied to each response of interest, an overall desirability function (D) was calculated using the average of the individual desirability functions, with each attribute given the same degree of importance. A D value close to 1 indicates that the combination of different factors is optimal and that the responses are close to the target values. Optimization was carried out using the Doehlert matrix [34].

Preparation of solutions

Diluent and mobile phase

A pH 2.2 buffer solution from the European Pharmacopoeia [1] was prepared by mixing 6.7 mL of phosphoric acid with 50 mL of 4% (v/v) sodium hydroxide solution, topped to 1,000 mL with HPLC grade water, and used as a diluent. The mobile phase was obtained by mixing 74% of the diluent solution with 26% of methanol.

Standard solution

The HCQ standard stock solution (100 μg mL−1) was prepared using pH 2.2 buffer solution. Working solutions were obtained by diluting them to concentrations of 2, 12, 20, 28, 36 and 44 μg mL−1 with the same diluent. All solutions were prepared using amber glassware.

Tablets sample

Twenty units of Plaquinol ® tablets were weighed to determine the average weight and crushed into a fine powder. The equivalent of 10 mg of HCQ was weighed out and solubilized in approximately 50 mL of pH 2.2 buffer used as a diluent and taken to the ultrasonic bath at a frequency of 40 kHz at room temperature (25 °C) for 5 min. The volume was completed with the diluent in a 100 mL volumetric flask (100 μg mL−1) and filtered through quantitative filter paper. The solutions were prepared and diluted in pH 2.2 buffer to theoretically obtain a final concentration of 40.0 μg mL−1. The samples were filtered with a syringe and hydrophilic PTFE filter (0.45 µm pore size). The similar medicine (Reuquinol) was prepared similarly, but only used in the application of the analytical method. All the solutions were prepared in amber glass.

Forced degradation study

The forced degradation study was conducted in accordance with Anvisa guidelines (RDC n°. 318/2019) and ICH Q1A (R2) analyzing the effects of temperature, humidity, oxidation and light over a wide pH range [39, 40]. Samples of the standard hydroxychloroquine (HCQ) and the pulverized reference® medicine were subjected to degradation conditions by acid hydrolysis (HCl 0.1 M for 72 h), alkaline hydrolysis (NaOH 0.01 M for 5 h), oxidation (H2O2 3% for 5 h), metal ion (FeSO4 0.05 M for 24 h), thermal degradation (60 °C for 24 h), humid thermal degradation (40 °C/75% Relative Humidity for 24 h) and photolysis (UV radiation chamber for 24 h). These conditions were established by means of preliminary tests, with the aim to obtain a degradation (reduction) of between 10 and 20 per cent of the HCQ content. After incubating the samples in each degradation condition, the solutions were prepared and diluted in pH 2.2 buffer to theoretically obtain a final concentration of 40.0 μg mL−1. The samples were filtered through a hydrophilic PTFE filter (0.45 μm) and immediately analyzed in a chromatograph equipped with a DAD (Diode Array Detector) detector.

Method validation

The method was validated according to the United States Pharmacopeia (USP) [31], International Council for Harmonisation (ICH) [41], Food and Drug Administration (FDA) [42], National Health Surveillance Agency (Anvisa) [43] for the parameters of selectivity, linearity, precision, accuracy, limit of detection (LOD), limit of quantification (LOQ) and robustness.

System suitability

HCQ standard solutions with a theoretical concentration of 40 μg mL−1 using a pH 2.2 buffer solution as a diluent, were injected into the chromatographic system at short, regular time intervals. The peak area, retention time, tailing factor and number of theoretical plates were recorded on the chromatograms. The RSD (%) values of the peak areas and retention times were calculated for six injections.

Selectivity

The selectivity of the method was evaluated by the purity of the peaks and the matrix effect, using a diode-array detector (DAD) chromatograph. Standard solutions of HCQ, samples (tablets) and the degraded samples (HCQ) were prepared using pH 2.2 buffer solution as a diluent and diluted to obtain final theoretical concentrations of 40 μg mL−1. The chromatograms were compared, and the percentages of degradation were calculated.

Linearity

The linearity of the method was assessed by constructing three independent analytical curves with HCQ standard solutions at five different concentrations (4, 12, 20, 28, 36 and 44 μg mL−1). The solutions were prepared using a pH 2.2 buffer solution as a diluent, as described in the standard solutions section and injected into the chromatographic system. The analytical curve was constructed from the mean values of the peak areas of the standard as a function of the respective concentrations. To statistically assess the linearity of the method, the Cochran test (to assess the equality of variances), the Shapiro-Wilk test (to assess the distribution of residuals) and the standardized residual analysis (to check for outliers) were used to obtain the equation of the line, the coefficient of determination (R2) and the linear correlation coefficient (R), as well as the regression F-test (ANOVA) (to assess the angular coefficient).

Precision and accuracy

The precision of the analytical method was assessed by the RSD (%) of the test for repeatability (intra-day) and intermediate precision (inter-day), from three concentrations (low, medium and high) of the linearity curve (4, 20, 44 μg mL−1), in triplicate for each concentration. Accuracy was checked using the recovery performed by adding the standard (HCQ) to the tablet sample solution. The recovery test was carried out at three concentration levels of the linearity curve (4, 20, 44 μg mL−1), in triplicate, and the percentage of recovery was calculated.

Limit of detection (LOD) and limit of quantification (LOQ)

The detection and quantification limits were calculated from the equations (LOD = 3.3 σ/S and LOQ = 10 σ/S), where σ is the standard deviation of the response and S the slope of the of the calibration curve.

Robustness

The robustness of the method was assessed using the Youden and Steiner test [44] which consists of the multivariate analysis of small, deliberate changes that can have an impact on the analytical response. In the present study, the robustness of the method was assessed by changing the pH of the buffer, the percentage of methanol in the mobile phase, the brand of PTFE hydrophilic filter, the flow of the mobile phase, the wavelength, the temperature of the chromatographic column and the sample stirring time. The areas obtained from the samples were compared with the area obtained by standard HCQ solutions. The solutions were prepared using a pH 2.2 buffer solution as a diluent and diluted to obtain final theoretical concentrations of 40 μg mL−1.

Method application

The validated method was applied to determine the dosages of Plaquinol® and Reuquinol medicines with declared dosages of 400 mg of HCQ. Twenty tablet units of each product were tested and, after determining the average weight, solutions were prepared using a pH 2.2 buffer solution and diluted to obtain final theoretical concentrations of 40 μg mL−1 of each medicine. The test was carried out in sextuplicate. The area values obtained for each product were compared with the areas of the HCQ standard solutions prepared at the same concentration, in sextuplicate, and used to calculate the true dosage of HCQ in the reference and similar medicines.

Results and discussion

Analysis of LogD and solubility oriented to selection of solvents for method development

The graph of the variation in the distribution coefficient (logD) as a function of pH variation (Fig. 1) shows that at pH values above 9 the drug molecule is completely deprotonated (non-ionized form), with a logD of 2.7. On the other hand, at pH values below 2.5 the molecule is completely protonated (ionized form), with logD = −2.4. Thus, the ideal working range would be at pH values above 9.0 for greater interaction between the drug and the apolar stationary phase. However, chromatographic columns have efficiency limitations at certain pH values (<2 and >8). Therefore, pH < 3 was selected, avoiding the pH range between 3 and 9, to guarantee complete ionization of the molecule. HCQ is a drug that is easily soluble in aqueous solutions in the pH range between 2 and 8 and poorly soluble in organic solvents [1, 2]. Based on this data, a mixture of pH 2.2 buffer solution and methanol was defined as the mobile phase.

Fig. 1.
Fig. 1.

LogD of hydroxychloroquine (HCQ)

Citation: Acta Chromatographica 2024; 10.1556/1326.2023.01193

Wavelength selection

Five absorption maxima were identified at the following wavelengths: 343, 331, 257, 236 and 221 nm (Fig. 2). Although the 221 nm wavelength showed the highest absorbance rate, it was discarded as the peak suffered deformation at the highest concentration. Therefore, the wavelength of 343 nm was selected, as it presented a high absorbance rate without suffering peak deformation at high concentrations.

Fig. 2.
Fig. 2.

Spectral scan in the ultraviolet region for the HCQ standard in HPLC-grade water at different concentrations.

Concentrations: (a) 5.0 μg mL−1, (b) 10.0 μg mL−1, (c) 15.0 μg mL−1, (d) 20.0 μg mL−1, (e) 25.0 μg mL−1, (f) 30.0 μg mL−1, (g) 40.0 μg mL−1, (h) 50.0 μg mL−1. Solutions were prepared and diluted using pH 2.2 buffer solution.

Absorption maxima: (1) 343 nm, (2) 331 nm, (3) 257 nm, (4) 236 nm and (5) 221 nm

Citation: Acta Chromatographica 2024; 10.1556/1326.2023.01193

Experiment planning oriented to method optimization

To optimize the analytical method, the full factorial design 23 was used to calculate the analytical response (D), as shown in Table 2, and in the construction of the Pareto diagram (Fig. 3) relating the variable percentage of methanol in the mobile phase, flow and temperature, which was constructed using Statistica® software version 7 (StatSoft Inc.®, Tulsa, Oklahoma, USA). The Pareto diagram showed that the flow of the mobile phase is the factor that causes the greatest influence on the analytical response, with this influence being directly proportional. It can also be seen that the percentage of methanol in the mobile phase significantly influences the analytical response, in an indirectly proportional way, i.e. the higher the concentration of methanol, the worse the result of the analytical method. It can also be seen that the results of the method are also influenced by the interactions between the factors (columns 1by3, 1by2 and 2by3). Based on the results presented in the Pareto diagram, the final optimization was carried out using the Doehlert matrix for three variables: the percentage of methanol in the mobile phase (23, 24, 25, 26 and 27%), the flow rate of the mobile phase (1, 1.1, 1.2, 1.3, 1.4, 1.5 and 1.6 mL min−1) and the temperature of the chromatographic column (38, 40 and 42 °C). Also in this study, the results obtained for retention time (lowest is best), peak asymmetry (lowest is best), theoretical plates (highest is best) and capacity factor (highest is best) were evaluated to calculate the overall desirability function (D). The results are shown in Table 3 and the response surface graph (Fig. 4).

Table 2.

Factorial design 23 employed in the optimization of the analytical method HPLC for the quantification of HCQ

Assay*F1F2F3Analytical response (D)
−(24) +(35)−(0.7) +(1.3)−(30) +(40)Response 1Response 2
10.000.00
2+0.000.00
3+0.460.47
4++0.340.34
5+0.120.17
6++0.000.00
7++0.540.53
8+++0.070.00

F1 – percentage of methanol in mobile phase (%), F2 – mobile phase flow rate (mL.min−1), F3 – chromatographic column temperature (°C), D – overall desirability result. The experiment highlighted in bold indicates the condition that presented the best result.

Fig. 3.
Fig. 3.

Paretto's diagram

Citation: Acta Chromatographica 2024; 10.1556/1326.2023.01193

Table 3.

Doehlert matrix for analytical method optimization

Assay*Methanol (%)Flow (mL.min−1)T (°C)Analytical response (D)
123
1251.3400.700.700.69
2271.3400.58
3261.6400.00
4261.4420.48
5231.3400.44
6241.0400.00
7241.2380.00
8261.0400.23
9261.2380.26
10241.6400.00
11251.5380.00
12241.4420.00
13251.1420.22

* triplicate. The experiment highlighted in bold indicates the condition that presented the best result.

Fig. 4.
Fig. 4.

Response surface methodology

Citation: Acta Chromatographica 2024; 10.1556/1326.2023.01193

Observing the response surface allows us to conclude that there is a region of maximum analytical response in relation to the factors studied. Therefore, to obtain the best view of the conditions that provide the most favorable analytical response (D), the adjusted surface function was constructed using Statistica® software version 7 (StatSoft Inc.®, Tulsa, Oklahoma, USA), as shown in Fig. 5. Analysis of the level curve shows that there is a region of maximum analytical response with flow rates between 1.2 and 1.4 mL min−1 and a percentage of methanol between 25 and 27%. At a flow of 1.3 mL min−1 the maximum response was obtained with 26% methanol and temperature of 40 °C. Therefore, after finalizing the optimization of the analytical method, the conditions established for the chromatographic method were mobile phase with phosphoric acid buffer pH 2.2: methanol (74:26 v/v), flow rate of 1.3 mL min−1, temperature 40 °C, reverse phase chromatographic column C18 (250 mm × 4.6 mm; 5.0 µm), wavelength at 343 nm and injection volume of 20 µL. The chromatographic profile (Fig. 6) shows a retention time of 4.595 min, a run time of 6 min, with theoretical plate values of 6.552.40, a capacity factor of 3.74, a base asymmetry of 1.41 and an asymmetry at 10% of the peak height of 1.35.

Fig. 5.
Fig. 5.

Level curve for standard HCQ by high-performance liquid chromatography (40 μg mL−1)

Citation: Acta Chromatographica 2024; 10.1556/1326.2023.01193

Fig. 6.
Fig. 6.

Chromatogram for standard HCQ by the high-performance liquid chromatography (40 μg mL−1)

Citation: Acta Chromatographica 2024; 10.1556/1326.2023.01193

Validation

Selectivity

The forced degradation study (Table 4) revealed that, for the HCQ standard, peak purity index was 1.000000, the single point threshold was 0.998403 and the minimum peak purity index was 1,596. In the tablet samples either, as the peak purity index was 1.000000, the single point threshold was 0.998344 and the minimum peak purity index was 1,655. The selectivity study, carried out on the degraded samples during the forced degradation study revealed that the HCQ molecule did not undergo significant degradation, since all the peaks obtained in the tests reached a degradation of around 10–20% of the HCQ content in the sample and with proven purity except in acid hydrolysis. This phenomenon is since HCQ is a weak base and, in the presence of 0.1 M HCl (strong acid), can generate an anion capable of forming a strong acid that does not undergo hydrolysis (pH < 7).

Table 4.

Selectivity of the analytical method for HCQ in the forced degradation study

HydrolysisDegraded percentage (%)Presence of impurityPeak purity indexSingle point thresholdMinimum peak purity index
Acid2.1No1.0000000.999824175
Alkaline12.7No0.9999990.9975592,439
Oxidative13.0No0.9999990.9978752,124
Fe2+10.2No1.0000000.999817183
Thermal11.0No1.0000000.999812188
Humidity13.1No1.0000000.999833166
Photolysis10.4No1.0000000.999816184

Linearity

Linearity was assessed by regression analysis with HCQ standard solutions prepared independently, in triplicate, and showed a linear correlation between concentrations and peak areas (Fig. 7). Data from the linearity study were used to verify homoscedasticity (equality of variance) using the Cochran test (C = greatest variation in Y/sum of total variations in Y), with a value of C = 0.403 lower than the value of C tabulated for 6 concentrations in triplicates (0.616). Therefore, the null hypothesis that the variances are statistically equal is accepted. With the linearity data, an analysis of the distribution of residues was also carried out demonstrating that there is a random behavior, and no trend was observed in the residue graph (Fig. 8). Subsequently, the Shapiro-Wilk test, presented in Table 5, was performed, revealing that the P value obtained (0.5801) was higher than the significance level of α = 0.05. Therefore, the null hypothesis that the analyzed data follows a normal distribution is accepted. Regression analysis of variance (ANOVA) was performed (Table 6) using the F test, obtaining calculated values ​​higher than those in the table. Thus, the analytical method showed linearity in the range of 4–44 μg mL−1 with equation y = 38.272x + 1.064.1, correlation coefficient = 0.9998 and determination coefficient with R2 = 0.9996.

Fig. 7.
Fig. 7.

Graphical representation of the linearity study of the method for determining HCQ by high performance liquid chromatography (HPLC)

Citation: Acta Chromatographica 2024; 10.1556/1326.2023.01193

Fig. 8.
Fig. 8.

Graphical representation of the distribution of residues obtained in the linearity study of the method for determining HCQ by high performance liquid chromatography (HPLC)

Citation: Acta Chromatographica 2024; 10.1556/1326.2023.01193

Table 5.

Values ​​obtained in the Shapiro-Wilk test to study the linearity of the high-performance liquid chromatography (HPLC) method for determining HCQ

Sample size18
Average−0.1111
Standard deviation10.763,2255
W0.9604
P0.5801
Table 6.

Analysis of variance (ANOVA) of the regression for linearity study of the high performance liquid chromatography (HPLC) method for determining HCQ

GlSQMQFF Significance
Regression14.92156E+124.92156E+1239.980,91.288E−28
Residue161969557847123097365,4
Total174.92352E+12

F value = 4.49 (tabulated).

Precision and accuracy

Precision was evaluated for repeatability and intermediate precision. Method repeatability and accuracy were evaluated by analyzing, on the same day, working standard solutions of HCQ at 3 concentrations: low (4.0 μg mL−1), medium (20 μg mL−1) and high (44 μg mL−1). Intermediate precision was assessed by repeating the assays on 2 different days by two analysts. The mean recovery and standard deviation values ​​obtained for repeatability and accuracy (n = 3) for low, medium and high concentrations were, respectively, 100.84% (RSD = 1.43%); 100.29% (RSD = 0.95%); 99.71% (RSD = 1.20%); and for intermediate precision were, in the same sequence, 101.00% (RSD = 1.28%); 99.56% (RSD = 1.06%); 99.32% (RSD = 0.89%), demonstrating the precision and accuracy of the method.

Detection limit (LOD) and quantification limit (LOQ)

The limit of detection and limit of quantification were calculated by relating the standard deviation of the regression line residuals (σ) and the slope of the calibration curve, respectively. The values obtained for LOD were 0.93 μg mL−1 and LOQ 2.81 μg mL−1.

Robustness

The robustness of the method was evaluated using the Youden and Steiner test [44] testing the variables: pH of mobile phase buffer; percentage of methanol in the mobile phase; brand of hydrophilic PTFE filter; mobile phase flow rate; wavelength; column temperature; sample stirring time. The effect value of each variable was determined from the recovery results obtained in each of the 8 experiments. Effects with values ​​greater than the value of s√2 (standard deviation of the effects multiplied by the square root of two) were indicative of factors that significantly influence the method's results. The effect values ​​obtained for each variable were lower than the calculated s√2 value (1.43), demonstrating that none of the factors evaluated had significant influence on the analytical response and, therefore, demonstrating the robustness of the method (Table 7).

Table 7.

Results of the robustness test, using the Youden and Steiner test, for analysis of the chromatographic method for HCQ

VariableExperimental conditions√2 *Effect
12345678
Buffer pHAAAAaAAa0.58
% methanol in mobile phaseBBbBBBBb0.63
PTFE hydrophilic filter brandCcCCCCCc−0.28
Mobile phase flowDDdDdDDD1.38
WavelengthEeEEeEeE0.79
Column temperatureFffFFFfF−0.46
Sample agitation timeGggGgGGg0.01
Results (% recovery)100.83100.7799.2798.3198.0799.6199.2999.901.43

*s√2 = Standard deviation multiplied by the square root of 2. concentration of 40 μg mL−1.

Method application

The validated method was applied to commercial products (Plaquinol ® and Rouquinol). The average content values ​​for the reference medicine were 100.03% with DPR of 1.23%, and for the similar product it was 100.01% with DPR = 1.25%, showing dosages of 400.12 mg for reference and 400.04 mg for similar, with dosages declared on the label of 400 mg each.

Conclusion

The application of computational tools to optimise technical parameters in the development and validation of analytical methods aims to reduce the number of experiments, unnecessary expenses with solvents, analysis time and minimize the generation of environmental waste. In this study, the results obtained in the validation of an analytical method for the quantification of HCQ in pharmaceutical products demonstrated an innovative and advantageous approach compared to the official method and others reported in the literature. The application of the multivariate strategy, the choice of methanol, in a lower proportion in the organic phase, due to its low toxicity, economy and greater availability compared to acetonitrile and the other organic solvents used, was a promising and important alternative, leading to the development of the method with good performance characteristics, with average recovery values between 99.71% and 100.84%, RSD <2% in both intra-day and inter-day procedures and robust. In addition, the use of a reverse stationary phase, common in quality control laboratories, provided a retention time of 4.595 min for the analyte, demonstrating good performance and speed for routine analyses. The method was successfully applied to samples of the reference Plaquinol® 400 mg and similar Reuquinol 400 mg purchased in commercial pharmacies, confirming the theoretical dosages of these.

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that may have influenced the work reported in this article.

Acknowledgements

This study was financed with a master's scholarship, by the Coordination for the Improvement of Higher Education Personnel (CAPES) through the Social Demand Program [88882.429856/2019-01] and institutional support through the Pharmaceutical Equivalence Center of the Nucleus of Quality Control of the Faculty of Pharmaceutical Sciences, Federal University of Alfenas.

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    Wang, L.; Lin, Y.; Huang, N.; Yu, C.; Tsai, W.; Chen, J.; Kubota, T.; Matsuoka, M.; Chen, S.; Yang, C.; Lu, R.; Lin, Y.; Chang, T. Hydroxychloroquine-Inhibited dengue virus is associated with host defense machinery. J. Interferon Cytokine Res. 2015, 35(3), 143156. https://doi.org/10.1089/jir.2014.0038.

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Senior editors

Editor(s)-in-Chief: Kowalska, Teresa (1946-2023)

Editor(s)-in-Chief: Sajewicz, Mieczyslaw

Editors(s)

  • Danica Agbaba (University of Belgrade, Belgrade, Serbia)
  • Łukasz Komsta (Medical University of Lublin, Lublin, Poland)
  • Ivana Stanimirova-Daszykowska (University of Silesia, Katowice, Poland)
  • Monika Waksmundzka-Hajnos (Medical University of Lublin, Lublin, Poland)

Editorial Board

  • R. Bhushan (The Indian Institute of Technology, Roorkee, India)
  • J. Bojarski (Jagiellonian University, Kraków, Poland)
  • B. Chankvetadze (State University of Tbilisi, Tbilisi, Georgia)
  • M. Daszykowski (University of Silesia, Katowice, Poland)
  • T.H. Dzido (Medical University of Lublin, Lublin, Poland)
  • A. Felinger (University of Pécs, Pécs, Hungary)
  • K. Glowniak (Medical University of Lublin, Lublin, Poland)
  • B. Glód (Siedlce University of Natural Sciences and Humanities, Siedlce, Poland)
  • A. Gumieniczek (Medical University of Lublin, Lublin, Poland)
  • U. Hubicka (Jagiellonian University, Kraków, Poland)
  • K. Kaczmarski (Rzeszow University of Technology, Rzeszów, Poland)
  • H. Kalász (Semmelweis University, Budapest, Hungary)
  • K. Karljiković Rajić (University of Belgrade, Belgrade, Serbia)
  • I. Klebovich (Semmelweis University, Budapest, Hungary)
  • A. Koch (Private Pharmacy, Hamburg, Germany)
  • P. Kus (Univerity of Silesia, Katowice, Poland)
  • D. Mangelings (Free University of Brussels, Brussels, Belgium)
  • E. Mincsovics (Corvinus University of Budapest, Budapest, Hungary)
  • Á. M. Móricz (Centre for Agricultural Research, Budapest, Hungary)
  • G. Morlock (Giessen University, Giessen, Germany)
  • A. Petruczynik (Medical University of Lublin, Lublin, Poland)
  • R. Skibiński (Medical University of Lublin, Lublin, Poland)
  • B. Spangenberg (Offenburg University of Applied Sciences, Germany)
  • T. Tuzimski (Medical University of Lublin, Lublin, Poland)
  • Y. Vander Heyden (Free University of Brussels, Brussels, Belgium)
  • A. Voelkel (Poznań University of Technology, Poznań, Poland)
  • B. Walczak (University of Silesia, Katowice, Poland)
  • W. Wasiak (Adam Mickiewicz University, Poznań, Poland)
  • I.G. Zenkevich (St. Petersburg State University, St. Petersburg, Russian Federation)

 

KOWALSKA, TERESA (1946-2023)
E-mail: kowalska@us.edu.pl

SAJEWICZ, MIECZYSLAW
E-mail:msajewic@us.edu.pl

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2022  
Web of Science  
Total Cites
WoS
647
Journal Impact Factor 1.9
Rank by Impact Factor

Chemistry, Analytical (Q3)

Impact Factor
without
Journal Self Cites
1.9
5 Year
Impact Factor
1.4
Journal Citation Indicator 0.41
Rank by Journal Citation Indicator

Chemistry, Analytical (Q3)

Scimago  
Scimago
H-index
29
Scimago
Journal Rank
0.28
Scimago Quartile Score

Chemistry (miscellaneous) (Q3)

Scopus  
Scopus
Cite Score
3.1
Scopus
CIte Score Rank
General Chemistry 211/407 (48th PCTL)
Scopus
SNIP
0.549

2021  
Web of Science  
Total Cites
WoS
652
Journal Impact Factor 2,011
Rank by Impact Factor Chemistry, Analytical 66/87
Impact Factor
without
Journal Self Cites
1,789
5 Year
Impact Factor
1,350
Journal Citation Indicator 0,40
Rank by Journal Citation Indicator Chemistry, Analytical 72/99
Scimago  
Scimago
H-index
29
Scimago
Journal Rank
0,27
Scimago Quartile Score Chemistry (miscellaneous) (Q3)
Scopus  
Scopus
Cite Score
2,8
Scopus
CIte Score Rank
General Chemistry 210/409 (Q3)
Scopus
SNIP
0,586

2020
 
Total Cites
650
WoS
Journal
Impact Factor
1,639
Rank by
Chemistry, Analytical 71/83 (Q4)
Impact Factor
 
Impact Factor
1,412
without
Journal Self Cites
5 Year
1,301
Impact Factor
Journal
0,34
Citation Indicator
 
Rank by Journal
Chemistry, Analytical 75/93 (Q4)
Citation Indicator
 
Citable
45
Items
Total
43
Articles
Total
2
Reviews
Scimago
28
H-index
Scimago
0,316
Journal Rank
Scimago
Chemistry (miscellaneous) Q3
Quartile Score
 
Scopus
393/181=2,2
Scite Score
 
Scopus
General Chemistry 215/398 (Q3)
Scite Score Rank
 
Scopus
0,560
SNIP
 
Days from
58
submission
 
to acceptance
 
Days from
68
acceptance
 
to publication
 
Acceptance
51%
Rate

2019  
Total Cites
WoS
495
Impact Factor 1,418
Impact Factor
without
Journal Self Cites
1,374
5 Year
Impact Factor
0,936
Immediacy
Index
0,460
Citable
Items
50
Total
Articles
50
Total
Reviews
0
Cited
Half-Life
6,2
Citing
Half-Life
8,3
Eigenfactor
Score
0,00048
Article Influence
Score
0,164
% Articles
in
Citable Items
100,00
Normalized
Eigenfactor
0,05895
Average
IF
Percentile
20,349
Scimago
H-index
26
Scimago
Journal Rank
0,255
Scopus
Scite Score
226/167=1,4
Scopus
Scite Score Rank
Chemistry (miscellaneous) 240/398 (Q3)
Scopus
SNIP
0,494
Acceptance
Rate
41%

 

Acta Chromatographica
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Acta Chromatographica
Language English
Size A4
Year of
Foundation
1988
Volumes
per Year
1
Issues
per Year
4
Founder Institute of Chemistry, University of Silesia
Founder's
Address
PL-40-007 Katowice, Poland, Bankowa 12
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2083-5736 (Online)

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