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Research Article
Simultaneous HPLC determination of remdesivir and dexamethasone in the presence of metformin, sitagliptin, and glimepiride in a synthetic mixture and spiked human plasma
expand article infoStanislav Bozhanov, Miglena Smerikarova, Vania Maslarska
‡ Medical University-Sofia, Sofia, Bulgaria
Open Access

Abstract

The COVID-19 pandemic has raised many questions regarding the control and therapy of type 2 diabetes and the higher risk of severe disease progression. One of the therapeutic regimens used in moderate and severe cases of COVID-19, endorsed by the World Health Organization, involves the administration of an antiviral medicinal product and a corticosteroid. The present study describes the development of a liquid chromatographic method for the simultaneous separation and quantification of Remdesivir and Dexamethasone in the presence of Metformin, Sitagliptin, and Glimepiride in a synthetic mixture. The developed method also allows determination of Remdesivir, Dexamethasone, and Glimepiride in spiked plasma samples, using Sitagliptin as internal standard. A mixture of acetonitrile and potassium dihydrogen phosphate buffer (pH 3) in a ratio of 45:55 v/v was used as а mobile phase on a C18 column. The recovery percentages from plasma ranged from 85.1 to 108.5%. The developed method can serve in routine quality control and clinical laboratory practice.

Keywords

antidiabetic drugs, bioanalysis, Covid-19, dexamethasone, remdesivir, synthetic mixture

Introduction

With its emergence and rapid spread, COVID-19 has fundamentally changed people’s lives worldwide. The consequences were serious – health problems (World Health Organization 2020) and also social and economic ones (Pak et al. 2020; Smit et al. 2023). Because of the deadly nature of the disease, researchers’ efforts have focused both on vaccine development and on the use and retargeting of appropriate drugs for prevention and treatment. Among these drugs, Remdesivir (RDV) and Dexamethasone (DXM) seem to have gained the most popularity. Their use, alone or in combination for moderate and severe cases of hospitalized patients with COVID-19, was approved by the World Health Organization (Spinner et al. 2020; Lin et al. 2021; Morris et al. 2021; Qureshi et al. 2021; Wong et al. 2022; National Institutes of Health 2023). To date, despite the containment of the infection and its impact, COVID-19 remains a major threat (World Health Organization 2023), especially in patients with chronic diseases. Accumulated epidemiological evidence indicates that diabetes and cardiovascular disease are major risk factors for the development of severe COVID-19 infection (Abu-Farha et al. 2020; Chakraborty et al. 2020; Liu et al. 2020; Muniangi-Muhitu et al. 2020; Peric and Stulnig 2020; Tadic et al. 2020; Wallia et al. 2020; Czupryniak et al. 2021; Fleming et al. 2021; Landstra and de Koning 2021) and increased mortality (Kumar et al. 2020; Dennis et al. 2021; Varikasuvu et al. 2021; Wu et al. 2021). Diabetes mellitus is one of the most significant diseases in the world and shows a tendency towards a constant increase in the number of patients (Saeedi et al. 2019). Diabetic patients have been found to have increased rates of severe disease and mortality during COVID-19 infection compared to non-diabetic individuals (Akbariqomi et al. 2020; Conway et al. 2020; Maddaloni et al. 2020; Czupryniak et al. 2021; Khunti et al. 2021). The specificity and individual approach in antidiabetic therapy and its combination with antiviral and/or corticosteroid antiviral therapy requires strict control, both in terms of the quality of the administered medications and in terms of monitoring their plasma concentrations. High-performance liquid chromatography (HPLC) is a versatile technique, achieving good resolution, high specificity, and sensitivity, and is the method of choice for the analysis of multicomponent mixtures and complex samples. In the literature, there are various publications on developed HPLC methods for the analysis of both RDV and DXM, as well as antidiabetic drugs alone (Garcia et al. 2003; Song et al. 2004; Rabbaa-Khabbaz et al. 2005; Kumar et al. 2006; Kar and Choudhury 2009; Dubala et al. 2012; Chhetri et al. 2013, 2014; Mohd et al. 2014; Iqbal et al. 2018; Sultana et al. 2018; Alvarez et al. 2020; Ibrahim et al. 2021; Jitta et al. 2021; Kishore et al. 2021; Samad et al. 2023), in combination (Jain et al. 2008; Bhende et al. 2012; El-Enany et al. 2012; Ramesh and Habibuddin 2014; Priya et al. 2016; Al Bratty et al. 2017; Kavitha et al. 2017; Sirigiri et al. 2018; Sebaiy et al. 2019, 2020; Sharma et al. 2019; Shakoor et al. 2020; Emam et al. 2022), in dosage forms (Garcia et al. 2003; Jain et al. 2008; Kar and Choudhury 2009; Bhende et al. 2012; El-Enany et al. 2012; Chhetri et al. 2013; Mohd et al. 2014; Ramesh and Habibuddin 2014; Priya et al. 2016; Kavitha et al. 2017; Sirigiri et al. 2018; Sultana et al. 2018; Sebaiy et al. 2019; Sharma et al. 2019; Shakoor et al. 2020; Ibrahim et al. 2021; Jitta et al. 2021; Samad et al. 2023) and in biological matrices (Song et al. 2004; Rabbaa-Khabbaz et al. 2005; Kumar et al. 2006; Dubala et al. 2012; El-Enany et al. 2012; Chhetri et al. 2014; Al Bratty et al. 2017; Iqbal et al. 2018; Alvarez et al. 2020; Sebaiy et al. 2020; Shakoor et al. 2020; Kishore et al. 2021; Emam et al. 2022), but (to the best of our knowledge) no method has been developed and validated for the simultaneous quantification of antidiabetic, antiviral and corticosteroid agents in a synthetic mixture or biological matrix. Thus, the aim of the present study is to make an attempt to develop an HPLC method for the simultaneous analysis of RDV and DXM in the presence of some antidiabetic medicinal substances, such as Metformin (MTF), Sitagliptin (STG) and Glimepiride (GLM) in a synthetic mixture, as well as to use the method for the analysis of spiked plasma samples. The chemical structures of the studied drugs are presented in Fig. 1.

Figure 1. 

Chemical structures of RDV, DXM, MTF, STG and GLM.

Materials and methods

Chemicals and reagents

All chemicals and reagents used for method development were HPLC grade. The analytical standards of RDV, DXM, MTF, STG, and GLM were purchased from Sigma-Aldrich Co. Acetonitrile, methanol, and potassium dihydrogen phosphate used for mobile phase and stock solutions preparation were of HPLC grade. A blank human plasma standard (Sigma-Aldrich Co.) was used for calibration curve construction. All additional reagents needed to develop the analytical method were suitable for HPLC analysis.

Preparation of stock solutions and mixed stock solutions

The stock solutions of RDV, DXM, MTF, STG (1 mg/ml), and GLM (0.2 mg/ml) were prepared by dissolving the required amount of each substance in methanol and diluting it to 20.0 ml with the same solvent. A mixed stock solution (solution A, 40 µg/ml) was prepared by transferring suitable aliquots of each stock solution to one and the same 50.0 ml volumetric flask and further diluted with methanol. For plasma studies stock solutions of RDV, DXM (4 mg/ml), and GLM (0.2 mg/ml) were prepared in methanol. A mixed stock solution containing RDV, DXM, and GLM (solution B, 160 µg/ml) was prepared by transferring the required aliquots of the RDV, DXM, and GLM stock solutions to a 20.0 ml volumetric flask and further diluted with methanol.

Preparation of working solutions

Six working solutions (RDMSG -SM1, RDMSG -SM2, RDMSG -SM3, RDMSG -SM4, RDMSG -SM5 and RDMSG -SM6) in the concentration range of 1–24 µg/ml and three working quality control solutions (RDMSG -QC1, RDMSG -QC2, and RDMSG -QC3) with concentrations 1.6, 6, and 20 µg/ml were prepared by appropriately diluting aliquots from the solution A with methanol. For plasma studies six working solutions (RDG-P1, RDG-P2, RDG-P3, RDG-P4, RDG-P5, and RDG-P6) in the concentration range of 5–120 µg/ml and three working quality control solutions (RDG-QC1, RDG-QC2, and RDG-QC3) with concentrations 8, 30, and 100 µg/ml were prepared by appropriately diluting aliquots from the solution B with methanol. All solutions were stored at 2–4 °C temperature before analysis.

Preparation of internal standard solution

For plasma analysis, STG was chosen as an internal standard (IS). The solution was prepared by dissolving 40 mg of the substance in methanol and diluting it to 50.0 ml with the same solvent. The obtained concentration was 0.8 mg/ml.

Preparation of calibration and quality control solutions for the plasma assay

Calibration and quality control solutions were prepared in standard human plasma. To 400 µl blank plasma a 100 µl of RDG-P1, RDG-P2, RDG-P3, RDG-P4, RDG-P5, RDG-P6, RDG-QC1, RDG-QC2 and RDG-QC3 were added, respectively. The resulting samples were vortexed for 2 min. The obtained concentrations were 1, 2, 4, 8, 16, and 24 µg/ml for the calibration standards and 1.6, 6, and 20 µg/ml for the quality control samples.

Sample preparation

Plasma protein precipitation was performed according to the previously published method (Smerikarova et al. 2023) with some modifications and adjustments. A plasma aliquot of 150 µl was mixed with 50 µl of the IS solution, then the sample was vortexed for 5 min. Further on, 600 µl of acetonitrile was added as a precipitating agent. After homogenization on a vortex mixer for 10 min, 15 min of sonication in an ultrasonic bath and 15 minutes of shaking at 500 rpm were applied. The supernatant was separated after 10 min of centrifugation at 13 000 rpm and 600 µl were filtered through a 0.45 µm syringe filter.

Chromatographic conditions

A SHIMADZU Corporation chromatographic system consisting of online degassing unit DGU-20A5, solvent delivery unit LC-20AD, autosampler Sil-20A, column oven CTO-20A, and UV-VIS detector SPD-20A was. The recording and processing of the results were done with Lab Solution Software. An RP-18 (250 × 4.6 mm, 5 µm) chromatographic column, equipped with a suitable guard column, was applied as a stationary phase. Isocratic elution was performed at a flow rate of 1.0 ml/min, and at ambient temperature. A mixture of acetonitrile and potassium dihydrogen phosphate buffer (pH 3) in a ratio of 45:55 v/v was used as а mobile phase. The mobile phase was filtrated and degassed in an ultrasonic bath before use. UV – VIS detector was set at 250 nm and the injection volume was 20 µl.

Results and discussion

Method development and optimization

During the development of the chromatographic method, columns with different hydrocarbon chain lengths were tested, namely – octadecylsilane (C18) and octylsilane (C8). Considering the very short MTF retention time on the C8 column as well as the better separation on the C18 column, the C18 column was chosen for further studies. The effect of column length was investigated (two columns of different lengths -150 × 4.6 mm and 250 × 4.6 mm were used) and the longer column was preferred as it showed some additional increase in MTF retention time.

To find a suitable mobile phase, experiments were carried out with different compositions and ratios of solutions. Acetonitrile was preferred as the organic solvent because the use of methanol resulted in broad, diffuse, and asymmetric peaks. However, the application of mixtures of acetonitrile and water in different ratios did not produce the desired result. As the percentage of acetonitrile increased, overlapping peaks were observed and conversely, as the acetonitrile content decreased, the peaks broadened and along with this, the retention time of the last eluting peak increased too much. The introduction of a phosphate buffer in the composition of the mobile phase led to an improvement in the results. The effect of pH in the range of 3 to 6 was investigated, with the best results obtained at pH 3. The effect of buffer concentration (concentrations from 0.5 mM to 20 mM) on the separation and peak shape was also investigated. A concentration of 20 mM was the most suitable. It should be noted that lowering the concentration of the buffer solution results in broader peaks especially for antidiabetic agents and also to an unacceptable increase in the retention time of the latter component. Finally, a mixture of acetonitrile and potassium dihydrogen phosphate buffer (pH 3) in a ratio of 45:55 v/v was used as а mobile phase. Varying the flow rate and temperature did not significantly improve the separation of the compounds, so 1 ml/min flow rate and room temperature were chosen. The absorption maxima of the investigated compounds vary in relatively wide ranges, approximately from 230 nm for GLM to 270 nm for STG. Therefore, considering the spectra of the compounds (Fig. 2), as a good compromise, the UV detection was performed at 250 nm.

Figure 2. 

UV spectra of RDV, DXM, MTF, STG and GLM.

Method validation

The developed method was validated according to the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines (International Council for Harmonisation 2022) by various parameters including selectivity, linearity, accuracy, precision, system suitability, limit of detection and limit of quantification.

Selectivity

A method is considered selective when it can distinguish the target compounds from other components in the sample. The selectivity of the proposed method was proven by its capability to determine RDV, DXM, MTF, STG, and GLM in their synthetic mixture without interference. As can be seen from the representative chromatograms (provided in Fig. 3A, B) there are no interferences from mobile phase components during the analysis of RDV, DXM, MTF, STG, and GLM in their synthetic mixture. The peaks of all five analyzed drug substances are well separated.

Figure 3. 

Representative chromatograms obtained from A. The mobile phase and B. Synthetic mixture. Legend: Peak numbers: MTF-1, DXM-2, STG-3, RDV-4, and GLM-5.

System suitability tests

System suitability tests were performed in order to evaluate the performance of the chromatographic system. Parameters like retention time, column efficiency (column theoretical plates), capacity factor, selectivity, resolution, and tailing factor were determined by a sixfold analysis of the test sample at the concentration of 8 µg/ml. The requirements of the European Pharmacopoeia were fulfilled, as can be seen from the detailed results, expressed as mean values in Table 1.

Table 1.

Results of the system suitability tests.

Parameter Compound
(Acceptance criteria, Ph. Eur.) MTF DXM STG RDV GLM
tR, min 3.65 5.55 7.98 10.91 27.21
N (NLT 2000) 2006 2282 2180 3021 3576
κ’ (NLT 2.0) 2.10 2.19 2.15 3.31 9.75
α (NLT 1.0) 1.62 2.70 1.81 1.54 2.95
RS (NLT 2.0) 2.08 3.94 4.24 3.96 12.47
Tf (NMT 2.0) 1.29 1.47 1.56 1.37 1.36

Linearity and range

Linearity studies were performed to track the dependence of the analytical signal on the concentration of the analytes in the samples. Six standard solutions containing the analyzed substances were used in a concentration range from 1 to 24 µg/ml. For calibration curve construction, peak areas against solution concentrations were plotted. The achieved high correlation coefficients (R2>0.999) showed good linearity of the proposed method. Detailed results are listed in Table 2.

Table 2.

Linearity, accuracy and precision results for the RDV, DXM, MTF, GLM and STG calibration curves.

Compound Concentration (µg/ml) Mean ± SD CV% d%
RDV 1 0.928 ± 0.015 1.634 -7.243
2 2.018 ± 0.008 0.400 0.897
4 4.190 ± 0.002 0.049 4.752
8 8.001 ± 0.036 0.447 0.013
16 15.969 ± 0.023 0.147 -0.193
24 23.994 ± 0.017 0.069 -0.024
Linear equation y = 41594x + 2187.3
R2 0.9998
DXM 1 0.977 ± 0.006 0.631 -2.324
2 2.028 ± 0.007 0.331 1.397
4 4.073 ± 0.025 0.623 1.826
8 8.056 ± 0.042 0.519 0.696
16 15.983 ± 0.042 0.266 -0.105
24 23.983 ± 0.030 0.124 -0.071
Linear equation y = 34037x + 426.62
R2 0.9999
MTF 1 0.934± 0.019 2.041 -6,551
2 2.119± 0.049 2.295 5.941
4 4.097 ± 0.079 1.918 2.414
8 8.218 ± 0.077 0.939 2.727
16 16.047 ± 0.067 0.419 0.294
24 23.886 ± 0.052 0.218 -0.477
Linear equation y = 30082x + 18279
R2 0.9995
GLM 1 1.009 ± 0.077 7.595 0.907
2 1.968 ± 0.033 1.694 -1.616
4 3.987 ± 0.076 1.908 -0.317
8 7.895 ± 0.060 0.762 -1.309
16 16.304 ± 0.007 0.041 1.902
24 23.837 ± 0.152 0.640 -0.680
Linear equation y = 20722x – 462.82
R2 0.9997
STG 1 0.929 ± 0.049 5.298 -7.116
2 2.014 ± 0.099 4.904 0.718
4 4.272 ± 0.039 0.923 6.807
8 8.028 ± 0.137 1.708 0.347
16 15.997 ± 0.085 0.533 -0.022
24 23.961 ± 0.311 1.299 -0.161
Linear equation y = 1649.7x – 191.77
R2 0.9999

Accuracy and precision

Quality control samples at three concentration levels within the range of the calibration curve were used for accuracy and precision studies. Three independently prepared samples were triplicate analyzed in one day or on three consecutive days, to assess the accuracy and precision within a run and between runs. Reproducibility and accuracy were assessed by a coefficient of variance (CV%) and by the percentage deviation of the average concentration compared to the weighted one (d%). The coefficients of variance were below 2.5% and d% ranged from -3.5 to 6.2%. Detailed results are listed in Table 3.

Table 3.

Accuracy, reliability and reproducibility in a run and in time (n=3).

Compound Concentration (µg/ml) Intraday Interday
Mean ± SD CV% d% Mean ± SD CV% d%
RDV 1.6 1.604 ± 0.006 0.402 0.240 1.580 ± 0.009 0.546 -1.221
6 5.988 ± 0.027 0.448 -0.207 6.205 ± 0.029 0.466 3.411
20 19.975 ± 0.029 0.147 -0.127 20.188 ± 0.089 0.440 0.938
DXM 1.6 1.620 ± 0.005 0.332 1.241 1.609 ± 0.005 0.284 0.585
6 6.039 ± 0.031 0.519 0.644 6.206 ± 0.025 0.396 3.441
20 19.982 ± 0.053 0.266 -0.089 20.110 ± 0.065 0.323 0.551
MTF 1.6 1.574 ± 0.039 2.472 -1.654 1.574 ± 0.020 1.291 -1.640
6 6.261 ± 0.058 0.924 4.350 6.369 ± 0.064 1.005 6.154
20 20.211 ± 0.084 0.415 1.053 20.517 ± 0.103 0.500 2.587
GLM 1.6 1.570 ± 0.005 0.306 -1.895 1.631 ± 0.010 0.635 1.961
6 5.872 ± 0.054 0.912 -2.139 5.788 ± 0.077 1.332 -3.537
20 19.881 ± 0.089 0.448 -0.595 20.136 ± 0.026 0.130 0.682
STG 1.6 1.590 ± 0.006 0.387 -0.611 1.587 ± 0.005 0.291 -0.794
6 5.855 ± 0.047 0.808 -2.421 6.008 ± 0.036 0.595 0.139
20 20.240 ± 0.018 0.090 1.198 20.450 ± 0.100 0.490 2.250

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

Limits of detection and limits of quantification were determined experimentally by the signal-to-noise ratio. The LODs achieved were 0.05 µg/ml for MTF, DXM, and RDV. For STG LOD was 0.5 µg/ml and for GLM 0.3 µg/ml. The limits of quantification were 0.2 µg/ml for MTF, DXM, and RDV, and 1.0 µg/ml for STG and GLM.

Plasma samples

A protein precipitation procedure was used as a simple and fast sample preparation method. Unfortunately, under specific chromatographic conditions, MTF cannot be determined in plasma samples due to its very short retention time. An overlap of the plasma and MTF peaks was observed. However, the proposed method allows the simultaneous determination of RDV and DXM in the presence of the GLM and IS. All drug substances were well separated and no interferences from the biological matrix components were observed (Fig. 4A, B).

Figure 4. 

Representative chromatograms obtained from A. The blank and B. Spiked plasma samples. Legend: Peak numbers: DXM-2, STG-3, RDV-4 and GLM-5.

The area ratio of the chromatographic peaks of each analyte and the IS was plotted against concentration for the calibration curve in plasma. Linear relationship over the studied concentration range (from 1 to 24 µg/ml) and satisfactory correlation coefficients (R2>0.997) were observed. The details are summarized in Table 4.

Table 4.

Linearity, accuracy and precision results for the RDV, DXM and GLM calibration curves in plasma.

Compound Concentration (µg/ml) Mean ± SD CV% d%
RDV 1 0.894 ± 0.004 0.403 -10.600
2 1.838 ± 0.026 1.390 -8.117
4 3.623 ± 0.022 0.612 -9.417
8 8.022 ± 0.023 0.280 0.279
16 14.698 ± 0.070 0.478 -8.140
24 23.898 ± 0.315 1.320 -0.424
Linear equation y = 0.1142x – 0.0444
R2 0.9971
DXM 1 0.891 ± 0.007 0.730 -10.867
2 1.799 ± 0.021 1.189 -10.067
4 3.556 ± 0.038 1.074 -11.108
8 8.018 ± 0.019 0.232 0.229
16 15.035 ± 0.057 0.382 -6.033
24 24.614 ± 0.126 0.513 2.557
Linear equation y = 0.0974x – 0.0348
R2 0.9972
GLM 1 1.062 ± 0.029 2.745 6.167
2 2.095 ± 0.190 9.081 4.733
4 3.952 ± 0.068 1.712 -1.200
8 7.968 ± 0.048 0.598 -0.396
16 15.122 ± 0.936 6.191 -5.490
24 24.669 ± 0.107 0.433 2.787
Linear equation y = 0.0395x – 0.0035
R2 0.9971

Three QC samples at different concentration levels were analyzed for within-run and between-run accuracy and precision studies. The coefficient of variance (CV%) and the percentage deviation of the average concentration compared to the weighted one (d%) were used for reproducibility and accuracy assessment. The coefficients of variance were below 3.7% and d% ranged from -7.3 to 8.5%. The results summarized in Table 5 confirmed the method as accurate and reproducible.

Table 5.

Accuracy, reliability and reproducibility in a run and in time (n=3).

Compound Spiked concentration (µg/ml) Intraday Interday
Mean ± SD CV% d% Mean ± SD CV% d%
RDV 1.6 1.544 ± 0.031 1.980 -3.521 1.533 ± 0.046 3.016 -4.208
6 5.806 ± 0.147 2.528 -3.228 5.764 ± 0.144 2.501 -3.933
20 18.543 ± 0.145 0.781 -7.283 18.600 ± 0.116 0.621 -7.002
DXM 1.6 1.565 ± 0.006 0.399 -2.188 1.575 ± 0.015 0.940 -1.563
6 6.165 ± 0.159 2.575 2.756 6.013 ± 0.140 2.331 0.217
20 19.085 ± 0.048 0.253 -4.575 19.084 ± 0.064 0.334 -4.578
GLM 1.6 1.611 ± 0.005 0.287 0.667 1.568 ± 0.014 0.905 -2.021
6 6.509 ± 0.141 2.169 8.483 6.318 ± 0.228 3.612 5.294
20 20.549 ± 0.046 0.223 2.747 20.603 ± 0.178 0.865 3.017

The recovery studies were performed by blank plasma samples which were spiked with a laboratory-prepared mixture (RVD, DXM, and GLM) and IS at three different concentration levels. The obtained recovery percentages, ranging from 85.1% to 108.5% are listed in Table 6.

Table 6.

Recoveries of RVD, DXM and GLM from spiked human plasma (n=3).

Compound Spiked concentration (µg/ml) Concentration found (µg/ml) Recovery (%) (mean ± SD) CV %
RDV 1.6 1.37 85.38 ± 3.19 3.74
6 5.75 95.79 ± 2.43 2.53
20 18.60 93.00 ± 0.58 0.62
DXM 1.6 1.36 85.08 ± 0.51 0.60
6 6.01 100.22 ± 2.34 2.33
20 19.08 95.42 ± 0.32 0.33
GLM 1.6 1.61 100.66 ± 0.30 0.29
6 6.51 108.49 ± 2.35 2.17
20 20.55 102.75 ± 0.23 0.23

Comparison with published methods

Table 7 presents comparative data for the proposed method and some previously published reports. It can be seen that in terms of limits of detection and quantification, as well as linearity, the results obtained are better in some cases. It can be said that the obtained retention time results occupy an intermediate position compared to the published ones. An exception is the retention time of GLM, which is higher than the published ones.

Table 7.

Comparison between the proposed method and some previously published reports.

Compound tR (min) Linearity (µg/ml) LOD (µg/ml) LOQ (µg/ml) Reference [№]
RDV 10.91 1–24 0.05 0.2 Proposed method
DXM 5.55 1–24 0.05 0.2
MTF 3.65 1–24 0.05 0.2
GLM 27.21 3–72 0.3 1.0
STG 7.98 3–72 0.5 1.0
Determination of studied compounds in bulk, mixtures and formulations
RDV 6 0.025–2.5 1.95×10-3 6.49×10-3 (Jitta et al. 2021)
RDV 16 5–50 0.9 2.76 (Samad et al. 2023)
RDV 8.5 5–100 0.5 2.00 (Ibrahim et al. 2021)
DXM 8.5 5–60 0.47 1.41 (Garcia et al. 2003)
MTF 2.66 10–5000 - - (Jain et al. 2008)
GLM 10.17 1–10 - -
MTF 3.06 5–100 0.05 0.17 (Sebaiy et al. 2019)
GLM 4.33 5–100 1.2 4.0
MTF 2.57 20–200 - - (Ramesh and Habibuddin 2014)
GLM 9.39 10–150 - -
MTF 3.70 25–250 2.92 8.72 (Priya et al. 2016)
GLM 4.47 25–250 2.92 8.72
MTF 2.9 20–80 0.6 2.0 (Kavitha et al. 2017)
STG 3.9 20–80 0.4 1.2
MTF 2.4 50–150 - - (Sirigiri et al. 2018)
STG 17.0 50–150 - -
MTF 2.11 10–80 0.4 1.4 (Sharma et al. 2019)
STG 5.30 1–8 0.08 0.28
MTF 2.4 50–150 0.03 10.3 (Bhende et al. 2012)
STG 3.01 50–150 0.03 10.1
Determination of studied compounds in biological matrices
RDV 9.1 0.01–0.07 - 0.01 (Kishore et al. 2021)
RDV 2.4 1–5000 0.5 1.0 (Alvarez et al. 2020)
DXM - - - 10 (Song et al. 2004)
DXM 9.9 0.25–6.0 - - (Kumar et al. 2006)
RDV 3.65 0.1–10 0.1 10 (Emam et al. 2022)
DXM 3.08 0.1–10 0.1 10
MTF 9.93 0.125–2.5 0.062 0.125 (Chhetri et al. 2014)
MTF 3.36 10–140 2.0 6.0 (Shakoor et al. 2020)
GLM - 0.01–1 - 0.01 (Rabbaa-Khabbaz et al. 2005)
GLM 4.66 0.125–12.5 0.04 0.1 (El-Enani et al. 2012)
STG 6.1 0.01–1 1×10-3 0.01 (Dubala et al. 2012)
STG 6.7 0.12–31 - 0.12 (Iqbal et al. 2018)
MTF 1.24 2.5–100 0.05 - (Sebaiy et al. 2020)
GLM 2.77 2.5–100 0.1 -
MTF - 0.5×10-3- 0.17×10-3 - (Al Bratty et al. 2017)
STG - 0.4 1.76×10-3 -
0.01–0.5

Regarding the recovery rate (Table 6) for RDV, DXM, and GLM from the biological samples, the obtained results can be considered similar to the published reports. In the available literature, the recovery rates for RDV range from 97% to 103% (Kishore et al. 2021; Emam et al. 2022), for DXM from (77%–82%) (Kumar et al. 2006) to (97%–103%) (Emam et al. 2022), and for GLM from 80% to 98%) (El-Enany 2012; Sebaiy et al. 2020).

However, the obtained results can hardly be compared due to the lack of published methods dealing with the simultaneous separation and quantification of the studied medicinal substances.

Conclusion

A simple and accurate liquid chromatographic method was developed and validated for the simultaneous determination of RDV and DXM in the presence of MTF, STG, and GLM in their laboratory-prepared mixture. The proposed method allows separation and quantification of RDV, DXM, and GLM in biological matrix. The method offers simple sample preparation and a recovery rate of 85% to 108% for the biological matrix. Despite some limitations and drawbacks, the proposed method provides opportunities to expand research on the simultaneous separation and determination of RDV, DXM, and other antidiabetic drugs, in routine quality control and clinical laboratory practice.

Acknowledgements

This work was kindly supported by Medical University-Sofia, Medical Science Council [Grant № 157/ 14.06.2022].

References

  • Abu-Farha M, Al-Mulla F, Thanaraj TA, Kavalakatt S, Ali H, Abdul Ghani M, Abubaker J (2020) Impact of diabetes in patients diagnosed with COVID-19. Frontiers in Immunology 11: e576818. https://doi.org/10.3389/fimmu.2020.576818
  • Akbariqomi M, Hosseini MS, Rashidiani J, Sedighian H, Biganeh H, Heidari R, Moghaddam MM, Farnoosh G, Kooshki H (2020) Clinical characteristics and outcome of hospitalized COVID-19 patients with diabetes: a single-center, retrospective study in Iran. Diabetes Research and Clinical Practice 169: e108467. https://doi.org/10.1016/j.diabres.2020.108467
  • Al Bratty M, Alhazmi HA, Javed SA, Lalitha KG, Asmari M, Wolker J, El Deeb S (2017) Development and validation of LC–MS/MS method for simultaneous determination of metformin and four gliptins in human plasma. Chromatographia 80: 891–899. https://doi.org/10.1007/s10337-017-3288-0
  • Alvarez JC, Moine P, Etting I, Annane D, Larabi IA (2020) Quantification of plasma remdesivir and its metabolite GS-441524 using liquid chromatography coupled to tandem mass spectrometry. Application to a Covid-19 treated patient. Clinical Chemistry and Laboratory Medicine 58(9): 1461–1468. https://doi.org/10.1515/cclm-2020-0612
  • Bhende SD, Varanasi MB, Abbulu K, Swetha MD, Shravnthi V, Kumari JK, Shayamala T (2012) RP-HPLC method for the simultaneous estimation of sitagliptin phosphate and metformin hydrochloride in combined tablet dosage forms. Oriental Journal of Chemistry 28(1): 463–469. https://doi.org/10.13005/ojc/280158
  • Chakraborty C, Sharma AR, Bhattacharya M, Sharma G, Agoramoorthy G, Lee SS (2020) Diabetes and COVID-19: a major challenge in pandemic period? European Review for Medical and Pharmacological Sciences 24(21): 11409–11420. https://doi.org/10.26355/eurrev_202011_23634
  • Chhetri HP, Thapa P, Schepdael A Van (2013) HPLC method for the quantification of metformin hydrochloride in bulk and dosage forms. International Journal of Pharmaceutical Sciences and Research 4(7): 2600–2604. https://doi.org/10.13040/IJPSR.0975-8232.4(7).2600-04
  • Chhetri HP, Thapa P, Van Schepdael A (2014) Simple HPLC-UV method for the quantification of metformin in human plasma with one step protein precipitation. Saudi pharmaceutical journal 22(5): 483–487. https://doi.org/10.1016/j.jsps.2013.12.011
  • Conway J, Gould A, Westley R, Raju SA, Oklopcic A, Broadbent A, Abdelhafiz AH, Sinclair AJ (2020) Characteristics of patients with diabetes hospitalised for COVID-19 infection-a brief case series report. Diabetes Research and Clinical Practice 169: e108460. https://doi.org/10.1016/j.diabres.2020.108460
  • Czupryniak L, Dicker D, Lehmann R, Prázný M, Schernthaner G (2021) The management of type 2 diabetes before, during and after Covid-19 infection: what is the evidence? Cardiovascular Diabetology 20(1): e198. https://doi.org/10.1186/s12933-021-01389-1
  • Dennis JM, Mateen BA, Sonabend R, Thomas NJ, Patel KA, Hattersley AT, Denaxas S, McGovern AP, Vollmer SJ (2021) Type 2 diabetes and COVID-19-related mortality in the critical care setting: a national cohort study in England, March-July 2020. Diabetes care 44(1): 50–57. https://doi.org/10.2337/dc20-1444
  • Dubala A, Khatwal R, Kosaraju JS, Meda V, Samanta MK (2012) Bioanalytical method development and validation of sitagliptin phosphate by RP-HPLC and its application to pharmacokinetic study. Interntional Journal of Pharmacy and Pharmaceutical Sciences 4(2): 691–694.
  • El-Enany NM, Abdelal AA, Belal FF, Itoh YI, Nakamura MN (2012) Development and validation of a repharsed phase – HPLC method for simultaneous determination of rosiglitazone and glimepiride in combined dosage forms and human plasma. Chemistry Central Journal 6(1): 1–9. https://doi.org/10.1186/1752-153X-6-9
  • Emam AA, Abdelaleem EA, Abdelmomen EH, Abdelmoety RH, Abdelfatah RM (2022) Rapid and ecofriendly UPLC quantification of remdesivir, favipiravir and dexamethasone for accurate therapeutic drug monitoring in Covid-19 patient‘s plasma. Microchemical Journal 179: e107580. https://doi.org/10.1016/j.microc.2022.107580
  • Fleming N, Sacks LJ, Pham CT, Neoh SL, Ekinci EI (2021) An overview of COVID-19 in people with diabetes: Pathophysiology and considerations in the inpatient setting. Diabetic Medicine 38(3): e14509. https://doi.org/10.1111/dme.14509
  • Garcia CV, Breier AR, Steppe M, Schapoval EES, Oppe TP (2003) Determination of dexamethasone acetate in cream by HPLC. Journal of Pharmaceutical and Biomedical Analysis 31(3): 597–600. https://doi.org/10.1016/S0731-7085(02)00695-7
  • Ibrahim AE, Deeb SE, Abdelhalim EM, Al-Harrasi A, Sayed RA (2021) Green stability indicating organic solvent-free HPLC determination of remdesivir in substances and pharmaceutical dosage forms. Separations 8(12): e243. https://doi.org/10.3390/separations8120243
  • Iqbal Q, Bashir S, Jan SU, Malik MZ, Afzal I, Khalid A (2018) Development of a rapid resolution HPLC method for the quantitative determination of sitagliptin in human plasma. Pakistan Journal of Pharmaceutical Sciences 31(3): 795–799.
  • Jain D, Jain S, Jain D, Amin M (2008) Simultaneous estimation of metformin hydrochloride, pioglitazone hydrochloride, and glimepiride by RP-HPLC in tablet formulation. Journal of Chromatographic Science 46(6): 501–504. https://doi.org/10.1093/chromsci/46.6.501
  • Jitta SR, Salwa Kumar L, Gangurde PK, Verma R (2021) Development and validation of high-performance liquid chromatography method for the quantification of remdesivir in intravenous dosage form. Assay and Drug Development Technologies 19(8): 475–483. https://doi.org/10.1089/adt.2021.074
  • Kar M, Choudhury PK (2009) HPLC method for estimation of metformin hydrochloride in formulated microspheres and tablet dosage form. Indian Journal of Pharmaceutical Sciences 71(3): 318–320. https://doi.org/10.4103/0250-474X.56031
  • Kavitha D, Sahoo SK, Venkateswara Rao P, Nagamani M, Bhagyalaxmi Ch (2017) Development and validation of RP-HPLC method for determination of metformin and sitagliptin in bulk and pharmaceutical dosage form. Journal of Applied Pharmaceutical Research 5(2): 34–39.
  • Khunti K, Knighton P, Zaccardi F, Bakhai C, Barron E, Holman N, Kar P, Meace C, Sattar N, Sharp S, Wareham NJ, Weaver A, Woch E, Young B, Valabhji J (2021) Prescription of glucose-lowering therapies and risk of COVID-19 mortality in people with type 2 diabetes: a nationwide observational study in England. The Lancet. Diabetes & Endocrinology 9(5): 293–303. https://doi.org/10.1016/S2213-8587(21)00050-4
  • Kishore D, Prasad KRS, Darapureddy C, Phani RSCH (2021) Development and validation of a new HPLC bioanalytical internal standard method for the analysis of remdesivir in human plasma. Rasayan Journal of Chemistry 14(4): 2639–2644. https://doi.org/10.31788/RJC.2021.1446373
  • Kumar A, Arora A, Sharma P, Anikhindi SA, Bansal N, Singla V, Khare S, Srivastava A (2020) Is diabetes mellitus associated with mortality and severity of COVID-19? A meta-analysis. Diabetes & Metabolic Syndrome 14(4): 535–545. https://doi.org/10.1016/j.dsx.2020.04.044
  • Kumar V, Mostafa S, Kayo MW, Goldberg EP, Derendorf H (2006) HPLC determination of dexamethasone in human plasma and its application to an in vitro release study from endovascular stents. Die Pharmazie 61(11): 908–911.
  • Landstra CP, de Koning EJP (2021) COVID-19 and diabetes: understanding the interrelationship and risks for a severe course. Frontiers in Endocrinology 12: e649525. https://doi.org/10.3389/fendo.2021.649525
  • Lin HXJ, Cho S, Meyyur Aravamudan V, Sanda HY, Palraj R, Molton JS, Venkatachalam I (2021) Remdesivir in coronavirus disease 2019 (COVID-19) treatment: a review of evidence. Infection 49(3): 401–410. https://doi.org/10.1007/s15010-020-01557-7
  • Liu Z, Bai X, Han X, Jiang W, Qiu L, Chen S, Yu X (2020) The association of diabetes and the prognosis of COVID-19 patients: A retrospective study. Diabetes Research and Clinical Practice 169: e108386. https://doi.org/10.1016/j.diabres.2020.108386
  • Maddaloni E, D‘Onofrio L, Alessandri F, Mignogna C, Leto G, Coraggio L, Sterpetti S, Pascarella G, Mezzaroma I, Lichtner M, Pozzilli P, Agrò FE, Rocco M, Pugliese F, Mastroianni CM, Buzzetti R (2020) Clinical features of patients with type 2 diabetes with and without Covid-19: A case control study (CoViDiab I). Diabetes Research and Clinical Practice 169: e108454. https://doi.org/10.1016/j.diabres.2020.108454
  • Mohd AB, Sanka K, Gullapelly R, Diwan PV, Shastri N (2014) Development and validation of RP-HPLC method for glimepiride and its application for a novel self-nanoemulsifying powder (SNEP) formulation analysis and dissolution study. Journal of Analytical Science and Technology 5: e27. https://doi.org/10.1186/s40543-014-0027-0
  • Morris AM, Jüni P, Odutayo A, Bobos P, Andany N, Barrett K, Betts M, Healey A, Langford B, Maltsev A, Miller KJ, Morgenstern J, Munshi L, Razak F, Stall NM, Pai M (2021) Remdesivir for hospitalized patients with COVID-19. Science Briefs of the Ontario COVID-19 Science Advisory Table 2: 1–27. https://doi.org/10.47326/ocsat.2021.02.27.1.0
  • Muniangi-Muhitu H, Akalestou E, Salem V, Misra S, Oliver NS, Rutter GA (2020) Covid-19 and diabetes: a complex bidirectional relationship. Frontiers in Endocrinology 11: e582936. https://doi.org/10.3389/fendo.2020.582936
  • Pak A, Adegboye OA, Adekunle AI, Rahman KM, McBryde ES, Eisen DP (2020) Economic consequences of the COVID-19 outbreak: the need for epidemic preparedness. Frontiers in Public Health 8: e241. https://doi.org/10.3389/fpubh.2020.00241
  • Priya MV, Madhavan P, Kumar P, Kumar R (2016) RP-HPLC method for simultaneous estimation of metformin HCl, ramipril and glimepiride in bulk and their combination tablet dosage form. Journal of Pharmaceutical and Biological Science 11(3): 16–23.
  • Qureshi QH, Ashraf T, Rehman K, Khosa MK, Akash MSH (2021) Therapeutic interventions of remdesivir in diabetic and nondiabetic COVID-19 patients: A prospective observational study conducted on Pakistani population. Journal of Medical Virology 93(12): 6732–6736. https://doi.org/10.1002/jmv.27256
  • Rabbaa-Khabbaz L, Daoud RA, Karam-Sarkis D, Atallah C, Zoghbi A (2005) A simple and sensitive method for determination of glimepiride in human serum by HPLC. Journal of Liquid Chromatography & Related Technologies 28(20): 3255–3263. https://doi.org/10.1080/10826070500330935
  • Ramesh D, Habibuddin M (2014) Stability indicating RP-HPLC method for the simultaneous determination of atorvastatin calcium, metformin hydrochloride, and glimepiride in bulk and combined tablet dosage form. International Scholarly Research Notices 754695. https://doi.org/10.1155/2014/754695
  • Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, Colagiuri S, Guariguata L, Motala AA, Ogurtsova K, Shaw JE, Bright D, Williams R (2019) Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas (9th edn.). Diabetes Research and Clinical Practice 157: e107843. https://doi.org/10.1016/j.diabres.2019.107843
  • Samad HA, Ali SN, Qayoom A, Haroon U, Saad M, Alavi GM (2023) Development, validation and forced degradation studies of green liquid chromatographic method for determination of remdesivir in bulk drug and pharmaceutical formulation. Pakistan Journal of Pharmaceutical Sciences 36(1): 159–170.
  • Sebaiy MM, El-Adl SM, Baraka MM, Hassan AA (2019) Rapid RP-HPLC method for simultaneous estimation of some antidiabetics; metformin, gliclazide and glimepiride in tablets. Egyptian Journal of Chemistry 62(3): 429–440. https://doi.org/10.21608/ejchem.2018.4394.1388
  • Sebaiy MM, El-Adl SM, Baraka MM, Hassan AA (2020) Rapid RP-HPLC method for simultaneous estimation of metformin, pioglitazone, and glimepiride in human plasma. Acta Chromatographica 32(1): 16–21. https://doi.org/10.1556/1326.2018.00515
  • Shakoor A, Ahmed M, Ikram R, Hussain S, Tahir A, Jan BM, Adnan A (2020) Stability-indicating RP-HPLC method for simultaneous determination of metformin hydrochloride and vildagliptin in tablet and biological samples. Acta Chromatographica 32(1): 39–43. https://doi.org/10.1556/1326.2019.00555
  • Sharma H, Madhuri B, Reddy YP, Kumar KV, Bhatta NK, Giri BL (2019) HPLC method for simultaneous determination of metformin and sitagliptin in pharmaceutical dosage forms and its applications to dissolution study. International Journal of Medical and Biomedical Studies 3(7): 166–177. https://doi.org/10.32553/ijmbs.v3i7.406
  • Sirigiri N, Subramanian NS, Reddy GNK (2018) Stability indicating method development and validation for simultaneous estimation of sitagliptin phosphate and metformin HCl in tablets by HPLC. International Journal of Pharmaceutical Sciences and Research 9(10): 4294–4302. https://doi.org/10.13040/IJPSR.0975-8232.9(10).4294-02
  • Smerikarova M, Bozhanov S, Maslarska V (2023) Validation of rapid and simple HPLC-UV method for diflunisal determination in bulk drug and human plasma. Indian Journal of Pharmaceutical Education and Research 57(1): 278–285. https://doi.org/10.5530/001954641926
  • Smit J, Nacer E, Sikorski A, Godard C, Magdziarz W (2023) Social and Economic Consequences of COVID-19, Publication for the special committee on COVID-19 pandemic: lessons learned and recommendations for the future (COVI). Policy Department for Economic, Scientific and Quality of Life Policies, European Parliament, Luxembourg.
  • Song YK, Park JS, Kim JK, Kim CK (2004) HPLC determination of dexamethasone in human plasma. Journal of Liquid Chromatography & Related Technologies 27(14): 2293–2306. https://doi.org/10.1081/JLC-200025726
  • Spinner CD, Gottlieb RL, Criner GJ, Arribas López JR, Cattelan AM, Soriano Viladomiu A, Ogbuagu O, Malhotra P, Mullane KM, Castagna A, Chai LYA, Roestenberg M, Tsang OTY, Bernasconi E, Le Turnier P, Chang SC, SenGupta D, Hyland RH, Osinusi AO, Cao H (2020) Effect of remdesivir vs standard care on clinical status at 11 days in patients with moderate COVID-19: a randomized clinical trial. JAMA 324(11): 1048–1057. https://doi.org/10.1001/jama.2020.16349
  • Sultana S, Hossain MS, Islam MS, Rouf ASS (2018) Quantitation of sitagliptin in drug product by validated reversed phase liquid chromatographic technique. The Dhaka University Journal of Pharmaceutical Sciences 17(1): 123–129. https://doi.org/10.3329/dujps.v17i1.37128
  • Tadic M, Cuspidi C, Sala C (2020) COVID-19 and diabetes: Is there enough evidence? Journal of Clinical Hypertension 22(6): 943–948. https://doi.org/10.1111/jch.13912
  • Varikasuvu SR, Dutt N, Thangappazham B, Varshney S (2021) Diabetes and COVID-19: A pooled analysis related to disease severity and mortality. Primary care diabetes 15(1): 24–27. https://doi.org/10.1016/j.pcd.2020.08.015
  • Wallia A, Prince G, Touma E, El Muayed M, Seley JJ (2020) Caring for hospitalized patients with diabetes mellitus, hyperglycemia, and COVID-19: bridging the remaining knowledge gaps. Current Diabetes Reports 20(12): e77. https://doi.org/10.1007/s11892-020-01366-0
  • Wong CKH, Lau KTK, Au ICH, Xiong X, Lau EHY, Cowling BJ (2022) Clinical improvement, outcomes, antiviral activity, and costs associated with early treatment with remdesivir for patients with coronavirus disease 2019 (COVID-19). Clinical Infectious Diseases 74(8): 1450–1458. https://doi.org/10.1093/cid/ciab631
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