
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39294224
71413
10.1038/s41598-024-71413-3
Article
UPLC-PDA factorial design assisted method for simultaneous determination of oseltamivir, dexamethasone, and remdesivir in human plasma
EL-Shorbagy Hanan I. PGS.202214@pharm.suez.edu.eg
Hananibrahimelshorbagy@gmail.com

1
Mohamed Mona A. 2
El-Gindy Alaa 1
Hadad Ghada M. 1
Belal Fathalla 3
1 https://ror.org/02m82p074 grid.33003.33 0000 0000 9889 5690 Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Suez Canal University, Ismailia, 41522 Egypt
2 Pharmaceutical Chemistry Department, Egyptian Drug Authority (EDA), Cairo, Egypt
3 https://ror.org/01k8vtd75 grid.10251.37 0000 0001 0342 6662 Department of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, Mansoura University, Mansoura, 35516 Egypt
18 9 2024
18 9 2024
2024
14 2175822 10 2023
27 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
A green and simple UPLC method was developed and optimized, adopting a factorial design for simultaneous determination of oseltamivir phosphate and remdesivir with dexamethasone as a co-administered drug in human plasma and using daclatasvir dihydrochloride as an internal standard within 5 min. The separation was established on UPLC column BEH C18 1.7 μm (2.1 × 100.0 mm) connected to UPLC pre-column BEH 1.7 μm (2.1 × 5.0 mm) at 50 °C with an injection volume of 10 μL. The photodiode array detector (PDA) was set at three wavelengths of 220, 315, and 245 nm for oseltamivir phosphate, the internal standard, and both dexamethasone and remdesivir, respectively. The mobile phase consisted of methanol and ammonium acetate solution (40 mM) adjusted to pH 4 in a ratio of 61.5:38.5 (v/v) with a flow rate of 0.25 mL min−1. The calibration curves were linear over 500.0–5000.0 ng mL−1 for oseltamivir phosphate, over 10.0–500.0 ng mL−1 and 500.0–5000.0 ng mL−1 for dexamethasone, and over 20.0–500 ng mL−1 and 500.0–5000.0 ng mL−1 for remdesivir. The Gibbs free energy and Van't Hoff plots were used to investigate the effect of column oven temperatures on retention times. Fluoride-EDTA anticoagulant showed inhibition activity on the esterase enzyme in plasma. The proposed method was validated according to the M10 ICH, FDA, and EMA’s bioanalytical guidelines. According to Eco-score, GAPI, and AGREE criteria, the proposed method was considered acceptable green.

Keywords

UPLC-PDA
Fluoride-EDTA plasma
Gibbs free energy
Green analysis
Subject terms

Environmental sciences
Bioanalytical chemistry
http://dx.doi.org/10.13039/501100003009 Science and Technology Development Fund Suez Canal UniversityOpen access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

issue-copyright-statement© Springer Nature Limited 2024
==== Body
pmcIntroduction

COVID-19 created a serious threat to economies and healthcare systems. SARS-CoV-2 viruses, which are encapsulated viruses with a single-stranded RNA genome, are the main cause of COVID-191,2. In the management protocol for COVID-19, oseltamivir phosphate (OSTP) (Fig. S1A) is indicated for mild cases, while remdesivir (REM) (Fig. S1C) is indicated for moderate-to-severe cases3–10. It was indicated that dexamethasone (DEX) (Fig. S1B), as an anti-infamatory glucocorticoid, is coadministered with OSTP or REM in COVID-19 viral infections. The U.S. Food and Drug Administration (FDA) authorized OSTP in August 201611. It stops viral budding from the host cell by inhibiting the neuraminidase enzyme on the surface of the virus. It is used to both treat and prevent influenza virus infections. The FDA authorized REM for the treatment of COVID-19 in October 20207–9. It is an analog of a nucleoside that inhibits the viral polymerase enzyme, preventing the replication of the virus.

According to literatures, OSTP was estimated by capillary zone electrophoresis (CE), chromatographic, mass spectrometric (MS), enzymatic, colorimetric, spectrophotometric, and spectrofluorimetric methods since its FDA authorization until 201112,13. Since 2011, OSTP has been determined by RP-HPLC14–16, UPLC17, LC–MS /MS18,19, spectrofluorimetric20, mass spectrometry (MS)21, potentiometric22, and spectrophotometric23 methods. DEX was estimated by spectrophotometric, UPLC-UV, HPLC–UV, and LC–MS/MS techniques since its FDA authorization until 202224. REM was determined by UPLC25, LC–MS/MS26, RP-HPLC27, electrochemical28, and spectrofluorimetric29 methods. No analytical method has yet been reported to determine OSTP, DEX, and REM simultaneously in human plasma. So, it was important to develop a method that is fast, accurate, and green to simultaneously separate OSTP, DEX, and REM from human plasma samples to ease the management of these drugs during the treatment of the huge numbers of COVID-19 patients.

The UPLC method was the first candidate method due to its several advantages, including its ability to increase chromatographic efficiency and sensitivity, improve analyte resolution, decrease run time, and lower solvent consumption30.

Several significant concerns were carefully investigated during this work. Before application to human plasma, this suggested method was initially optimized by means of the design of experiments (DOE) technique at a column oven temperature of 25 °C. Full factorial designs with one center-point experiment were used to determine the curvature possibilities (lack of fit) of the selected dependent responses, followed by multiple regression analysis. The Gibbs free energy (G°) of the solute interactions with the stationary phase was then used to investigate the effect of column oven temperatures of 25, 30, 45, and 50 °C on the retention times of the studied drugs in reversed-phase chromatography. The proposed method was validated according to the M10 ICH31, FDA32, and EMA’s33 bioanalytical method validation guidelines31. The bench-top (short-term) stability of each drug at room temperature for 2 h in different types of human plasma samples withdrawn into fluoride, K3EDTA, and fluoride-EDTA tubes was investigated. In addition, their matrix effect, extraction efficiency, process efficiency, and internal standard normalized values were estimated according to the M10 ICH's bioanalytical method validation guidelines31.

The proposed method has several advantages over other reported LC methods14,17,25,27. It is appropriate for UPLC-MS method development since the mobile phases utilized (methanol and ammonium acetate) are compatible with the ionization within mass detectors. In UPLC-MS, methanol is a safe solvent, while ammonium acetate is a volatile salt that is often used to buffer mobile phases. According to the lack of fit test of the factorial design experiments, the effects of methanol percentage, flow rate, or ammonium acetate concentration against k' (OSTP) or RS2 (DAC) are linear (no curvature possibilities), indicating good precision and easy robustness prediction of the proposed method. Fluoride-EDTA human plasma showed inhibition activity on the esterase enzyme in plasma, hence the highest stability results for the studied drugs. The proposed method is simple in sample preparation and extraction. Furthermore, the suggested method's greenness was evaluated using AGREE (Analytical GREEnness) analysis34, Eco-Scale35, and the Green Analytical Procedure Index (GAPI) criteria36.

Experimental

Apparatus and software

The developed method was carried out on an ACQUITY UPLC H-Class PLUS System (USA) equipped with a Waters quaternary solvent manager (M20QSP 471A), a Waters column heater (K20CHA 249G) with an UPLC column BEH C18 (1.7-μm, 2.1 × 100 mm) connected to an UPLC pre-column BEH (1.7-μm Van Guard, 2.1 × 5 mm), a Waters temperature-controlled sample manager-flow-through needle (SM-FTN-H), and a PDA detector (L20UPL 182A). The data was recorded and analyzed using the WatersEmpower3 chromatography software. For the preparation of the mobile phase, a water deionizer (Stakpure-OmniaLab, Germany), a balance (Sartorius, Germany), a pH meter (Jenway 3510, UK), an ultrasonicator (Elma, Germany), a vortex mixer (WiseMix, Portugal), a vacuum pump (Rocker 400, Taiwan), and nylon membrane filters (47 mm in diameter, 0.22 μm pore size, Chromtech, UK) were used. Pro manual Pipet4u micropipettes (Biotechnologie GmbH, Germany) were used for aliquot transfer during the preparation of the samples. An ultra-low-temperature freezer (Binder GmbH, Germany), a tabletop centrifuge (Harmonic series, Taiwan), and a thermostatic water bath (Gemmy Industrial Crop, Taiwan) were used for the preservation and preparation of plasma samples. All extracted samples were filtered using syringe filters (13 mm in diameter, 0.22 μm pore size, Chromtech PTFE, UK) before automatic injection into the UPLC chromatograph. Minitab Statistical Software (Release 1637, State College, Pennsylvania, USA) was used for the factorial design statistical analyses.

Materials and solvents

The standard powders of OSTP (purity: 99.976% w/w), DEX (purity: 99.307% w/w), REM (purity: 99.841% w/w), and the internal standard daclatasvir dihydrochloride (DAC) (purity: 101.171% w/w) were provided by NODCAR, Cairo, Egypt. Methanol (HPLC grade, Fisher Scientific, Germany, purity: ≥ 99.9%), ammonium acetate (AA) (Oxford laboratory reagent, India, purity: 96%), and diethyl ether (laboratory reagent grade, UK) were bought from Cornell Lab-Fine Chemicals & Lab Equipments, Cairo, Egypt. K3EDTA (Golden Vac, Turkey) and glucose/fluoride (Golden Vac, Turkey) blood tube kits were purchased from local laboratory stores. Human blood samples were kindly donated individually by four adult females: volunteer A (aged 21 years old, donated 10 mL of blood), volunteer B (aged 24 years old, donated 5 mL of blood), volunteer C (aged 30 years old, donated 5 mL of blood), and volunteer D (aged 37 years old, donated 135 mL of blood). From the collected blood, nearly 80 mL of plasma was obtained, from which nearly 155 samples were prepared. We confirm that all experiments were performed in accordance with relevant guidelines and regulations. The study was conducted according to the rules of the Ethics Committee at the Faculty of Pharmacy, Suez Canal University (number: 202009PHDH1). Informed consent was obtained from all subjects and/or their legal guardian(s).

Standard solutions

Four stock solutions of OSTP, DEX, REM, and DAC were each prepared in a volumetric flask (10 mL) and completed to the mark with methanol (HPLC grade, ≥ 99.9%) as a solvent. Each stock solution contained 500 μg mL−1 for each drug. Two different working ternary solutions of OSTP, DEX, and REM were prepared from their methanolic stock solutions. Each working ternary solution was prepared in 10-mL volumetric flasks and diluted with methanol (HPLC grade, ≥ 99.9%). The first methanolic working ternary solution contained 50.0 μg mL−1 of each drug, while the second methanolic working ternary solution contained 5.0 μg mL−1 of each drug. From the methanolic DAC stock solution, an internal standard (IS) (50.0 μg mL−1 DAC) was prepared in a volumetric flask (10 mL) and completed to the mark with methanol (HPLC grade, ≥ 99.9%) as a solvent. All prepared methanolic solutions were preserved in the freezer (from – 15 °C to − 28 °C) and protected from light.

General recommended procedures

We confirm that all experiments were performed in accordance with relevant guidelines and regulations. The study was conducted according to the rules of the Ethics Committee at the Faculty of Pharmacy, Suez Canal University (number: 202009PHDH1). Informed consent was obtained from all subjects and/or their legal guardian(s).

Preparation of human fluoride-EDTA plasma

Human blood samples were withdrawn into K3-EDTA tubes (2 mL per tube) and immediately transferred into sodium fluoride tubes to prepare human fluoride-EDTA plasma. The tubes were then left for 5 min, then centrifuged at 3000 rpm for 10 min. The layers of separated plasma were then transferred into Eppendorf tubes and preserved in an ultralow freezer (− 80 °C).

Construction of calibration curves in human plasma

Ternary standard concentrations of OSTP, DEX, and REM ranging from 10.0 ng mL−1 to 5000.0 ng mL−1 for each drug were first prepared to estimate the linearity ranges of each drug. Different aliquots (ranging from 1 to 50 μL by micropipette) of the methanolic working ternary solution (5 μg mL−1 of each drug) were transferred into a series of stoppered test tubes to prepare ternary standard mixtures ranging from 10.0 ng mL−1 to 500.0 ng mL−1 for each drug in human plasma. Also, ternary standard concentrations ranging from 500.0 ng mL−1 to 5000.0 ng mL−1 for each drug were prepared by transferring different aliquots (ranging from 5 to 50 μL by micropipette) of the working ternary solution (50.0 μg mL−1 of each drug) into a series of stoppered test tubes. After the evaporation of methanol solvent at room temperature, 500 μL of plasma samples were added to the residues in each stoppered test tube and vortexed for 30 s. To each tube, 5 μL aliquots of the internal standard (50.0 μg mL−1) were added to the spiked plasma, then vortexed for 30 s. Finally, 2 mL aliquots of diethyl ether (DEE) were added to each tube, tightly closed, and vortexed for 1 min. The tubes were centrifuged at 3500 rpm for 5 min, and then 1.5 mL aliquots of the supernatant from each stoppered test tube were separately transferred into tailed test tubes and evaporated in a water bath at 40 °C. Finally, the produced residue was reconstituted in 100 μL of 60% (v/v) methanol, vortexed for 30 s, and filtrated using a membrane filter (pore size of 0.22 μm). Volume (10 μL) was analyzed (n = 6) under the suggested chromatographic conditions. The regression equations were generated by plotting the drug peak area to IS peak area ratios against their respective final concentrations.

Assessment of bench-top (short-term) stability

Aliquots of the methanolic working ternary solutions (50.0 μg mL−1 and 5.0 μg mL−1 of each drug) were transferred into a series of stoppered test tubes to prepare ternary standard solutions containing 1000.0 ng mL−1 and 300.0 ng mL−1 of each drug in plasma, respectively. After evaporation of methanol solvent at room temperature, 500 μL of fresh human plasma samples were added to the residue in each stoppered test tube and vortexed for 30 s. Each concentration, consisting of nine stoppered test tubes, was divided into three groups depending on the time of analysis: 0, 1, and 2 h. At the recommended time interval for each group, 5 μL aliquots of the IS (50.0 μg mL−1) were added to each test tube, and then the test tubes were vortexed for 30 s. Then they were extracted by the same procedure under Section “construction of calibration curves in human plasma”. Volumes of 10 μL were injected under optimal chromatographic conditions after filtration using 0.22 μm membrane filters. The peak areas were obtained, and the stability was estimated.

Estimation of matrix effect, extraction and process efficiency and their IS normalized values

For this test, three groups of samples (n = 3 for each group) were analyzed using four blank plasma samples (plasma A, B, C, and D) collected from different sources. The first group, known as Pre-Extraction Samples (PrES), contained extracted spiked human plasma; the second group, known as Post-Extraction Samples (PoES), contained extracted blank human plasma that was then spiked with the tested drugs and IS at the predicted final concentrations; and the third group, known as Solvent Samples (SS), contained the tested drugs and IS diluted in 60% (v/v) methanol at the predicted final concentrations. Two quality control levels were tested (1000.0 ng mL−1 and 300.0 ng mL−1 for each drug) in human plasma samples.

In the first group (PrES), aliquots of the working ternary solution (50.0 μg mL−1 of each drug) were transferred into a series of stoppered test tubes to prepare ternary standard concentrations of OSTP, DEX, and REM of 1000.0 ng mL-1 for each drug in human plasma. After evaporation of methanol solvent at room temperature, 500 μL of human plasma was added to the residues in each stoppered test tube, which was then vortexed for 30 s. Then, 5 μL of the IS (50.0 μg mL−1) was added to each one, and all stoppered test tubes were vortexed for 30 s. Then they were extracted by the same procedure under Section “Construction of Calibration Curves in Human Plasma." Finally, the produced residue was reconstituted in 100 μL of 60% (v/v) methanol for each stoppered test tube and vortexed for 30 s. In the second group (PoES), 500 μL of human plasma was added to each stoppered test tube and then extracted by the same procedure described under Section “Construction of Calibration Curves in Human Plasma." Finally, aliquots of 10 μL from the working ternary solution (50.0 μg mL−1 of each drug) and 5 μL from the IS (50.0 μg mL−1) were transferred into each of the evaporated-tailed test tubes and then completed to 100 μL by 60% (v/v) methanol. The final reconstitutions were then vortexed for 30 s. The third group (SS) was for the tested drugs diluted in 60% (v/v) methanol. The concentrations of the drugs in this quaternary standard mixture were 5.0 μg mL−1 for OSTP, DEX, and REM and 2.5 μg mL−1 for IS (DAC). These previous steps were repeated for the preparation of pre-extracted, post-extracted, and solvent samples of the 300 ng mL−1 ternary human samples.

After filtering each prepared sample using a membrane filter (pore size of 0.22 μm), a volume of 10 μL was analyzed under the suggested chromatographic conditions. The peak areas were obtained, and the matrix effect, extraction efficiency, process efficiency, and their IS normalized values were estimated for each group.

Experimental design

The purpose of experimental design, also known as design of experimentation (DOE), is to collect as much data as possible from as few experimental trials as possible so that statistical models can be developed and significant conclusions are derived38. The full factorial design with/without one centerpoint, response optimizer, and optimization plot were studied in this work38,39.

Results and discussion

Method development

Selection of column and guard column

According to a previous study40, the UPLC Ethylene (-CH2-CH2-) Bridged Hybrid (BEH) C18 columns were the first choice for UPLC separations41. A UPLC column BEH C18 7 μm (2.1 × 100.0 mm) connected to the ultra-low volume guard column (2.1 x 5-mm-length) efficiently maintains UPLC column performance42.

Selection of the mobile phase

According to a previous study40, methanol (HPLC grade, ≥ 99.9%) was chosen as an eco-friendly organic mobile phase (pH 7–8.343), while ammonium acetate solution was chosen as the aqueous mobile phase. Ammonium acetate is commercially available at a low price. It is also a safe, chemically stable, and effective buffering medium with very high solubility in methanol. Ammonium acetate solution greatly enhances drug separations because of its excellent residual silanol masking effect on the chromatographic media, and it is harmonious with all LC detectors44.

Selection of the suitable wavelength

The PDA detector was theoretically required to be tuned above 215 nm because the UV cutoffs of both ammonium acetate and methanol are at 205 nm45,46. After the PDA scan of the tested drugs, 220 nm was set for OSTP, 315 nm was set for DAC (IS) (λmax of DAC = 315 nm), and 245 nm was set for DEX (λmax of DEX = 239 nm) and REM (λmax of REM = 245 nm) (Fig. S2 and Table S2)47. As a result, PDA was set at three wavelengths (λ) during the in vivo analysis, which gave the highest responses for the tested drugs and hence the highest sensitivities. On the other hand, 239 nm was chosen during method development and factorial design optimization for all drug detections.

The drug order of separation

The separation sequence of the compounds is dependent on their log P and pka values48. Log P (Table S3) suggests that these medications should ideally elute in the following order: OSTP, DEX, and REM. However, the retention time and tailing of the chromatographic peak of a drug are significantly influenced by the pH of the mobile phase, the drug ionization, and the interaction of the ionized drug molecules with the free silanols within the stationary phase. So, based on their pKa values (Table S3), DEX and REM would not be greatly affected by the fluctuation of pH from 8 to 2, as they would be unionized. At the same time, OSTP retention time would be greatly affected by the pH of the mobile phase, as it would be less ionized at high pHs than at low values. So, at pH 7, the predicted order would be DEX, OSTP, and then REM. At pH 4, however, with effectively masked silanol groups, the expected order is OSTP, DEX, and finally REM. This is due to the fact that ionizable compounds have significantly shorter retention times than un-ionizable ones in RP- HPLC48.

Chromatographic trials during method development

It was suggested to choose favipiravir (FAV)49, DAC50, or ledipasivir (LED)51 as the internal standard (IS). Several conditions were tried during the development of the UPLC method (Table S2, Trials 1–35). DAC as an internal standard was chosen (Table S2 notes). It was observed that the retention times of OSTP and DAC were significantly influenced by pH of the ammonium acetate aqueous mobile phase. So, it was concluded that ammonium acetate (10–50 mM) as an aqueous mobile phase solution adjusted at pH 4 with phosphoric acid showed the most suitable peak order (OSTP, DEX, DAC, and then REM) with good system suitability parameters. Finally, Trials 35–38 (Table S2) were established to determine the independent factors of the factorial design and their levels.

Method optimization by factorial design

Full factorial design with centerpoint experiment

Three independent factors affected the chromatographic performance: methanol percentage (MOH%) in the mobile phase at levels of 60 and 65%, flow rate (FR) at levels of 0.2 and 0.3 mL min−1, and ammonium acetate (AA) at levels of 10 and 50 mM (Table S2, Trials 35–38, and Table S4). The dependent responses obtained from the chromatograms at a UV wavelength of 239 nm were computerized. According to Table S4, k' (OSTP) and RS2 (DAC) as dependent responses were greatly affected by the selected independent factors (predictor variables). To determine the curvature possibility (lack of fit) of the selected dependent responses, 23 full factorial designs with one center point experiment (total experiments = 9) (Table S4 and Fig. S3) were first done, and then multiple regression analysis was estimated.

The results of k' (OSTP) and RS2(DAC) obtained from the nine factorial designs were within the (0.81–1.30) and (1.50–4.56) ranges, respectively. Theoretically, the acceptable limit for k' is more than 0.552, while the acceptable limit for RS is more than 1.553. However, the acceptable minimum limit in plasma analysis for k' is 1 and RS is 2 at 25 °C.

Multiple regression analysis

From the data obtained from the full factorial with center-point designs, a three-predictor model using multiple regression analyses for k' (OSTP) and RS2 (DAC) was evaluated.

The obtained regression equations were:1 k′(OSTP)=5.16710-0.06495×MOH\%-0.62680×FR+(0.00269×AA concentration)

2 RS2(DAC)=25.64900-0.33349×MOH\%-2.92800×FR-(0.03133×AA concentration)

Interpreting the P-value for intercept

The intercept term in the regression (Table S5) indicates the average expected value for the dependent factor when all the independent factors are equal to zero.

From Eqs. (1) and (2) and from Table S5, the regression coefficients for the intercepts are equal to 5.16710 and 25.64900 for k' (OSTP) and RS2 (DAC), respectively. This means that at chromatographic conditions of zero methanol percentage, 0.00 mL min-1 flow rate, and 0 mM ammonium acetate, the average expected k' (OSTP) and RS2 (DAC) values are 5.167 and 25.65, respectively. In conducting regression analyses, a p-value for each regression coefficient is estimated. From Table S5, the p-values are 0.000 (less than α-level (0.05)), which means that the intercept term is statistically different from zero.

Interpreting the P-value for methanol percentage predictor variable

From Eqs. (1) and (2) and from Table S5, methanol% is a predictor variable that ranges from 60 to 65%. The regression coefficients for methanol percentage are − 0.06495 and − 0.33349 for k' (OSTP) and RS2 (DAC), respectively. This means that, on average, each additional percentage of methanol is associated with a decrease of 0.06495 and 0.33349 values on k' (OSTP) and RS2 (DAC), respectively, assuming the predictor variables flow rate and ammonium acetate concentration are held constant.

From Table S5, the corresponding p-values are 0.000, which are statistically significant at an alpha level of 0.05. This means that the average change in k' (OSTP) and RS2 (DAC) for each additional percentage of methanol is statistically significantly different than zero (i.e., methanol percentage has a statistically significant relationship with the response variables k' (OSTP) and RS2 (DAC)).

Interpreting the P-value for flow rate predictor variable

From Eqs. (1) and (2) and from Table S5, the flow rate is a predictor variable that ranges from 0.2 to 0.3 mL min−1. The regression coefficients for the flow rate are − 0.62680 and − 2.92800 for k' (OSTP) and RS2 (DAC), respectively. This means that, on average, each additional mL min−1 of the flow rate is associated with a decrease of 0.62680 and 2.92800 values on k' (OSTP) and RS2 (DAC), respectively, assuming the predictor variables methanol percentage and ammonium acetate concentration are held constant.

From Table S5, the corresponding p-values are more than 0.05, which is not statistically significant at an alpha level of 0.05. This means that the average changes in k' (OSTP) and RS2 (DAC) for each additional mL min−1 of the flow rate are not statistically significantly different from zero (i.e., the flow rate does not have a statistically significant relationship with k' (OSTP) and RS2 (DAC)). This indicates that the effect of the flow rate on k' (OSTP) and RS2 (DAC) could have been due to random chance.

Interpreting the P-value for ammonium acetate concentration predictor variable

From Eqs. (1) and (2) and from Table S5, ammonium acetate concentration (mM) is a predictor variable that ranges from 10 to 50 mM. The regression coefficients for ammonium acetate concentration (mM) are 0.00269 and − 0.03133 for k' (OSTP) and RS2 (DAC), respectively. This means that, on average, each additional mM of ammonium acetate is associated with an increase of 0.00269 and a decrease of 0.03133 values on k' (OSTP) and RS2 (DAC), respectively, assuming the predictor variables methanol percentage and flow rate are held constant.

From Table S5, the corresponding p-values are less than 0.05, which is statistically significant at an alpha level of 0.05. This means that the average change in k' (OSTP) and RS2 (DAC) for each additional mM of ammonium acetate is statistically significantly different than zero (i.e., ammonium acetate concentration (mM) has a statistically significant relationship with the response variables k' (OSTP) and RS2 (DAC)).

From the previous interpretations of p-values, the optimized regression analyses for k' (OSTP) and RS2 (DAC) after removing the insignificant term (FR) from regression Eqs. (1) and (2) were evaluated to obtain Eqs. (3) and (4):3 k′(OSTP)=5.01040-0.06495×MOH\%+(0.00269×AA concentration)

4 RS2(DAC)=24.91700-0.33349×MOH\%-(0.03133×AA concentration)

Interpreting the data subsetting lack of fit test, the R2, predicted R2, and adjusted R2

Minitab calculates two types of lack of fit tests. The first test is the pure error lack of fit test. This test is used if the data contains replicates and the model needs to be reduced. Replicates represent "pure error" because only random variation can cause differences between the observed response values. If we are reducing our model and the resulting p-value for lack of fit is less than 0.05, then we should retain the term we removed from the model. The second test is the data subsetting lack of fit test. This test is used if the data does not contain replicates and we want to determine if we are accurately modeling the curvature. This method identifies curvature in the data and interactions among predictors that may affect the model fit. Whenever the data subsetting p-value is less than 0.05, Minitab displays the message "Possible curvature in variable X." If evidence exists that this curvature is not adequately modeled, a higher-order term to model the curvature may be tried after examining the raw data in a scatter plot.

According to Table S5, the data subsetting lack of fit test was done. There was no evidence of curvature in the regression lines of the methanol percentage, flow rate, or ammonium acetate concentration against k' (OSTP) or RS2 (DAC), indicating that the optimum condition can be obtained from the 23 full factorial design model without conducting a centerpoint experiment.

From Table S5, the R2 values indicate that the independent responses explain 96.4% and 96.8% of the variance in k' (OSTP) and RS2 (DAC), respectively. The adjusted R2 values were 94.3% and 95.0% for k' (OSTP) and RS2 (DAC), respectively, which accounts for the number of independent responses in the factorial design model. Both values indicate that the model fits the data well. The predicted R2 values were 90.50% and 91.28% for k' (OSTP) and RS2 (DAC), respectively. Because the predicted R2 values are close to the R2 and adjusted R2 values, the model does not appear to be overfit and has adequate predictive ability.

Interpreting the residual plots

The residual value is the difference between an observed value and its corresponding fitted value. The probability plot is used to evaluate the fit of a distribution to the data. The residual normal probability plots of k' (OSTP) and RS2 (DAC) show an approximately linear pattern consistent with a normal distribution (Fig. 1). The histogram is a graph used to assess the shape and spread of continuous sample data. The histogram can be created prior to or in conjunction with an analysis to help confirm assumptions and guide further analysis. To draw a histogram, minitab divides sample values into many intervals called bins. By default, bars represent the number of observations falling within each bin. According to Fig. 1, the residual histogram of k' (OSTP) demonstrated the presence of three negative residual observations (less than − 0.25), four positive residual observations (more than 0.25), and three residual values between − 0.25 and 0.25. On the other hand, the residual histogram of RS2 (DAC) demonstrated the presence of four negative residual observations (less than − 0.25), three positive residual observations (more than 0.25), and three residual values between − 0.25 and 0.25.Fig. 1 Residual plots for k' (OSTP) and RS2 (DAC).

In addition, the residual plot histograms of k' (OSTP) and RS2 (DAC) indicate that there are no outliers (unusual large or small observations) that may exist in the data, as shown by the continuous bars on the standardized residuals axis of the plot. The plots of residuals versus the fitted values (predicted values) of k' (OSTP) and RS2 (DAC) show a random pattern of residuals on both sides of 0 (reference line) (Fig. 1). The plot of residuals versus the run order is a plot of all residuals in the order that the data was collected in Table S4 and can be used to find non-random errors. The residuals versus order plots of k' (OSTP) and RS2 (DAC) display a random pattern, so the residuals are uncorrelated with each other (Fig. 1).

Optimum conditions determination by 23 FFD without center-point experiment

Using a 23 full factorial design (total experiments = 8), the response optimizer program was fed with the results of k' (OSTP) and RS2 (DAC) dependent responses with their desired lower, target, and upper values (Table S1). After program data analysis, an optimization plots (Table S1) was obtained and the optimum k' (OSTP) and RS2 (DAC) conditions with their desirability values and the highest composite desirability (D) value were evaluated39. According to Table S1, the final optimal UPLC conditions were 61.5% (v/v) methanol with 38.5% (v/v) AA (40 mM) as a mobile phase with a flow rate of 0.25 mL min-1 at a column oven temperature of 25 °C while adjusting the sample injection volume at 10 μL (Table S2, Trial 39).

Effect of column oven temperature

UPLC column BEH C18 1.7 μm (2.1 × 100 mm) can withstand elevated temperatures to 80 °C at low pH. Elevating the temperature of the column oven has many benefits. As the column oven’s temperature increases, the mobile phase’s viscosity decreases, and the column’s backpressure decreases. It was observed that raising the temperature from 25 to 50 °C reduced the column’s backpressure from 13,000 psi to 9000 psi. This enables higher flow rates to be used if needed. In addition, the lower pressure reduces the gradual damage to the UPLC instrumentation and thereby increases column life. Increased temperature improves column efficiency while decreasing operating pressure54. Also, as the temperature of the column oven is increased, the retention times of the peaks decrease (Fig. 2, Table 1, and Table S2, Trials 39–41).Fig. 2 UPLC Chromatograms of oseltamivir phosphate, dexamethasone, daclatasvir dihydrochrolide (IS), and remdesivir (500 ng mL−1 each) were simultaneously separated at different column champer’s temperatures (25, 30, 45, and 50 °C) (each peak labeled by (Rt-T-N)).

Table 1 Percentage increase ( +) or decrease ( −) in retention times (Rt), capacity factor (K’), resolution (R), peak height (H), peak width (W), and number of theoretical plates (N) during increasing column oven temperatures from 25 °C to 50 °C.

Drug	OSTP	DEX	DAC (IS)	REM	
Column oven temperature	30 °C	45 °C	50 °C	30 °C	45 °C	50 °C	30 °C	45 °C	50 °C	30 °C	45 °C	50 °C	
Percentage increase ( +) or decrease (-)a	Rt	 − 5.6	 − 12.1	 − 13.4	 − 5.9	 − 24.2	 − 26.7	 − 5.0	 − 13.0	 − 16.4	 − 4.5	 − 30.3	 − 33.6	
K’	 − 6.2	 − 28.0	 − 23.2	‒	‒	‒	‒	‒	‒	‒	‒	‒	
R	‒	‒	‒	 − 4.5	 − 28.3	 − 21.6	7.0	117.0	140.4	4.3	 − 38.7	 − 36.2	
Peak height (H)	 − 4.8	 + 24.0	 + 56.0	 + 9.1	 + 31.7	 + 54.5	 + 9.4	 + 100.6	 + 133.1	 + 6.1	 + 50.0	 + 70.3	
Peak width (W)	 − 15.8	 − 14.4	 − 36.9	 − 19.7	 − 28.3	 − 44.4	 − 16.5	 − 45.2	 − 58.9	 − 26.8	 − 45.0	 − 50.8	
N	 − 25.4	 + 4.6	 + 45.4	 + 4.7	 + 2.5	 + 32.4	 + 7.7	 + 214.6	 + 297.7	 + 1.6	 + 10.7	 + 28.7	
Significant values are in bold.

aPercentage increase ( +) or decrease (-) from Rt, K’, R, H, W, and N values obtained at a column chamber temperature of 25 °C.

Chromatography is a sequence of equilibrium reactions in which the analytes are either dissolved in the mobile phase or adsorbed to the column’s stationary phase. The higher the temperature, the faster the analytes exchange between the mobile and stationary phases. The overlay of the chromatograms at 25, 30, 45, and 50 °C (Fig. 2 and Table 1) reveals that peak heights are increasing while peak widths are decreasing. As a result, the number of theoretical plates (N) of the peaks and the sensitivity of the suggested method increase.

The effect of the column oven’s temperature on retention times in reversed-phase chromatography is largely determined by the Gibbs free energy (ΔG°) of the solute interaction with the stationary phase. The ΔG° energy is estimated from the slope of plots of log K' versus 1/T, called van't Hoff plots (Eq. (5)).5 lnK′=-ΔG∘RT+lnΦ

where K' is the capacity factor, R is the gas constant (8.3145 J mol−1K−1), T is the absolute temperature in kelvin, and Φ is the phase ratio of the column55–57. The phase ratio is defined as the ratio between the volume of the stationary phase (Vs) and the volume of the mobile phase (void volume, Vo) in a column58.

Van't Hoff plots were constructed for each drug (Fig. 3). In general, for components with identical stationary phase interactions, the Van't Hoff plots are linear with slightly different slopes as a result of minor differences in ΔG° values. If Van't Hoff plots deviate from linearity, the retention of the solute molecules in the stationary phase results from very different types of interactions, and the temperature in this case had a great influence on the selectivity57.Fig. 3 Van’t Hoff plots of oseltamivir phosphate, dexamethasone, daclatasvir dihydrochrolide (IS), and remdesivir.

From Table 2 and Fig. 3, it was observed that OSTP and DAC (IS) had identical stationary phase interactions as their Van't Hoff plots had slightly different slopes and minor differences in ΔG° values, as well as for DEX and REM. Furthermore, Van't Hoff plots for OSTP and DAC (R2 greater than 0.99) were linear, while those for DEX and REM deviated slightly from linearity (R2 lower than 0.99), which indicated differences in the retention mechanisms. The column oven temperature of 50 °C was the most suitable temperature according to Table 1, with good system suitability parameters (Fig. 4 and Table S2, Trial 42).Table 2 Gibbs’ free energy (ΔG, KJ mol−1) of each drug’s interaction with the stationary phase.

Drug	Coefficient of determination (R2)	Slope (b) = -ΔGoR	ΔG (KJ mol−1)	
OSTP	0.9963	1.55 × 103	 − 0.19	
DEX	0.9854	2.24 × 103	 − 0.27	
DAC (IS)	0.9916	1.17 × 103	 − 0.14	
REM	0.9770	2.33 × 103	 − 0.28	

Fig. 4 Chromatograms of 30% (v/v) aqueous methanol (blank), oseltamivir phosphate, dexamethasone, daclatasvir dihydrochrolide (IS), and remdesivir (500 ng mL−1 each) at different PDA channels (220, 245, and 315 nm) and column temperature of 50 °C.

The drug extraction technique from human plasma

OSTP, DEX, DAC (IS), and REM have high plasma protein binding of 42%59, 77%60, 99%50, and 88–93.6%7, respectively. They also have high log Ps of 1.3059, 1.9360, 3.4750, and 2.10–3.207, respectively. As a result, the most suitable and available method of extraction was liquid–liquid extraction (LLE). Unlike plasma protein precipitation techniques, LLE does not precipitate plasma proteins with the attached drugs. As a result, the drug recovery from plasma by LLE is greater than that achieved by protein precipitation techniques. Also, the high log Ps of the studied drugs permit good extraction of these nonpolar drugs into the organic phase. LLE allows the purification and pre-concentration of the evaporated residues in a small amount of the appropriate solvent, which increases the sensitivity of the method to detect small amounts of the studied drugs in plasma. So, this technique is suitable for drugs with a low plasma Cmax.

LLE is a separation technique that is frequently employed in industrial operations as well as on the laboratory scale due to its simplicity, low cost, and applicability for thermally labile and high-boiling chemicals61. However, the main disadvantages of LLE are the consumption of high volumes of organic solvents needed for the extraction of the drug, a time-consuming process when compared to other methods, the requirement of an evaporation step prior to analysis to remove excess organic solvent, and the possibility of emulsion formation when two immiscible phases are used in the extraction procedure. To overcome these disadvantages, one organic solvent was used to ease the extraction process. A low volume of 2 mL of the organic solvent per sample was used to minimize the pollution effect. Diethyl ether (DEE) as an extraction solvent was used. It is most commonly used in LLE. It has high volatility properties at low temperatures (boiling point: 34.6 °C). So, it is suitable for the extraction of thermolabile drugs. DEE is an inert compound with a high solvation capacity for nonpolar compounds because ethers do not have a hydrogen bonding network that would have to be broken up to dissolve the solute62.

Drugs extraction from human blood withdrawn in different types of blood withdrawing tubes

Samples of human blood were withdrawn in different tubes (K3EDTA, fluoride, and fluoride-EDTA) to study their effect on the stability of the studied drugs. The same procedure under Section “assessment of bench-top (short-term) stability” was adopted for this study. Under the final chromatographic conditions of Table 3, the stability of the tested drugs in these kits was studied at time intervals of 0, 1, and 2 h (Eq. (6) and Table S6).Table 3 Optimum chromatographic conditions for the RP-UPLC-PDA separation of the oseltamivir phosphate/dexamethasone/remdesivir mixture in human plasma.

Column	UPLC column BEH C18 1.7 μm (2.1 × 100 mm) connected with UPLC guard-column BEH 1.7 μm (2.1 × 5 mm)	
Mobile phase	Methanol : Ammonium acetate (40 mM) adjusted to pH 4 = 61.5:38.5 (v/v)	
Full run time	5 min	
Flow rate	0.25 mL min−1	
Temperature	50 °C at column oven and 25 °C at autoinjector part	
Injection volume	10 µL	
PDA detector	220 nm for OSTP, 315 nm for IS, and 245 nm for DEX and REM	

6 Stability at(x)hours=AUCDrugAUCISat(x)hoursAUCDrugAUCISat(0)hours×100

Where AUC is the area under the curve response obtained from the chromatogram.

It was observed that fluoride-EDTA plasma deactivated the esterase enzyme of human blood plasma more than EDTA or fluoride alone and hence increased the stability of the analyzed drugs, especially OSTP63–65 (Table S6).

Method characteristics

A methanolic quaternary mixture of 500 ng mL-1 of each drug was prepared to determine the independent factors. The 23 full factorial designs were applied at a column oven temperature of 25 °C. The effect of the temperature of the column oven on drugs’ separation was studied. Finally, the optimum conditions of the proposed method were developed for simultaneous determination of OSTP, DEX, and REM in human plasma using DAC as the IS (Table 3).

We confirm that all experiments were performed in accordance with relevant guidelines and regulations. The study was conducted according to the rules of the Ethics Committee at the Faculty of Pharmacy, Suez Canal University (number: 202009PHDH1). Informed consent was obtained from all subjects and/or their legal guardian(s).

Method validation

The proposed method was validated according to the bioanalytical method validation M10 ICH31, FDA32, and EMA’s33 guidelines. The validation parameters of linearity, limits of detection and quantitation, accuracy and precision, selectivity and specificity, system suitability parameters, stability of stock solutions, freeze–thaw cycles, short-term, long-term, and processed treated samples stability tests, matrix effect, extraction efficiency (recovery), and process efficiency and their IS normalized values were evaluated:

Linearity

Six concentrations were analyzed to evaluate the method's linearity for each drug (Table 4). The suggested method's calibration curves (n = 6) (Fig. S4) were plotted within the stated linearity limits for each drug, as shown in Table S7. The high coefficients of determination (R2 > 0.9930) suggested that the calibration curves were linear. Table 4 summarizes the quantitative statistical criteria for the studied drugs.Table 4 Statistical parameters of calibration curves of oseltamivir phosphate/dexamethasone/remdesivir in human plasma using the developed method (n = 6).

Parameter	Oseltamivir phosphate	Dexamethasone	Remdesivir	
Linearity range (ng mL−1)	200–5000	10–500	500–5000	20–500	500–5000	
Intercept (a)	− 0.029	− 0.002	− 0.038	0.274	0.490	
Slope (b)	1.56×10-4	11.69×10-4	15.15×10-4	25.37×10-4	24.46×10-4	
Coefficient of determination (R2)	0.9999	0.9996	0.9942	0.9980	0.9980	
SD of intercept (Sa)	0.001	0.003	0.132	0.015	0.135	
SD of slope (Sb)	5.85×10-7	120.60×10-7	579.91×10-7	572.49×10-7	590.66×10-7	
SD of residuals (Sy/x)	0.002	0.005	0.224	0.023	0.228	
Mean recovery ± SD, %	101.169 ± 3.856	101.613 ± 6.401	97.742 ± 8.905	100.877 ± 4.796	99.172 ± 9.927	
RSD, %a	3.812	6.300	9.111	4.754	10.010	
Error, %b	1.574	2.613	3.636	1.958	4.053	
aPercentage relative standard deviation for six samples.

bPercentage relative error for six samples.

These linearity ranges cover their concentrations in human plasma. Oral doses of 500- and 1000-mg OSTP have a Cmax of 564 (± 222) and 809 (± 216) ng mL−1, respectively66. The plasma Cmax of oral 1.5-mg DEX, intramuscular 3-mg DEX injection, and bolus intravenous 4-mg DEX injection are 13.9 ± 6.867, 34.6 ± 6.067, and nearly 100 ng mL−168, respectively. In high single doses of DEX in cancer patients, the plasma Cmax reaches 1000‒5000 ng mL−169,70. The intravenous infusion of 3-mg REM for two hours yields a plasma mean Cmax of 57.5 ng mL−171, while the intravenous infusion of 225-mg REM for two hours yields a plasma mean Cmax of 4420 ng mL−171.

Accuracy and precision

The suggested method's accuracy and precision for the within runs (n = 5) and for the between runs within three days (n = 3 per day) were evaluated using low (LQC), middle (MQC), and high (HQC) quality controls at each linearity range besides their lower limits of quantitation (LLOQ) (Table S8). The standard deviation (SD) and percentage relative standard deviation (% CV) of the obtained findings were calculated. The CV was found to be small (less than 8.31% for OSTP, 11.41% for DEX, and 11.01% for REM), indicating that the proposed method had appropriate accuracy and precision (Table S8).

Selectivity and specificity

Blank, OSTP, DEX, DAC (IS), and REM in human plasma were all investigated at different wavelengths. The blank chromatograms illustrated no peaks within the retention times of the studied drugs. Moreover, no peaks were noticed within any of the drug chromatograms except for their own. So, they were prepared in a quaternary solution (Fig. 5). The retention times of OSTP, DEX, the internal standard (DAC), and REM were 1.563 ± 0.006, 2.178 ± 0.017, 3.416 ± 0.016, and 3.826 ± 0.021 min (eight replicates), respectively.Fig. 5 Chromatograms of plasma extracted by the proposed method for specificity.

System suitability parameters

The system suitability parameters were determined by using “Equations (S1-S4)”39. According to Table 5, the RSD% of system suitability parameters obtained from eight chromatograms on four separate days suggested that the system was performing effectively.Table 5 System suitability parameters for RP-UPLC-PDA determination of oseltamivir phosphate/dexamethasone/daclatasvir dihydrochloride/remdesivir mixture in plasma.

Parameter	Oseltamivir phosphateat 220 nm	Dexamethasone at245 nm	Daclatasvirdihydrochloride (IS) at 315 nm	Remdesivir at245 nm	
Rt (mean ± SDa, RSD%)b	1.563 ± 0.006, 0.376%	2.178 ± 0.017, 0.766%	3.416 ± 0.016, 0.469%	3.826 ± 0.021, 0.555%	
k'c (mean ± SD, RSD%)	0.784 ± 0.012, 1.578%	‒	‒	‒	
RSd (mean ± SD, RSD%)	‒	7.557 ± 0.504, 6.663%	10.814 ± 1.062, 9.824%	4.096 ± 0.658, 16.057%	
Te (mean ± SD, RSD%)	1.023 ± 0.120, 11.724%	1.547 ± 0.127, 8.204%	1.304 ± 0.011, 0.824%	1.243 ± 0.021, 1.691%	
Nf (mean ± SD, RSD%)	12,856.391 ± 2066.184,16.071%	10,077.492. ± 1404.036,13.932%	11,575.463 ± 835.778, 7.220%	12,227.516 ± 855.264, 6.995%	
aStandard deviation (4–8 replicates at three different days).

bPercentage relative standard deviation (4–8 replicates).

cThe analyte peak's capacity factor.

dThe resolution between two successive analytes’ peaks.

eThe analyte peak's tailing factor.

fThe number of theoretical plates of the analyte peak.

Stability

Stability of the analyte and IS in stock and working solutions

According to a previous study40, the stock and working solutions were stable in the freezer for nearly three weeks for OSTP and DEX analysis but for only about one week in the case of DAC and REM analysis.

The freeze–thaw cycles, short-term, long-term, and processed treated samples stability tests

The freeze–thaw cycles, the short-term stability, the long-term stability for one week, and the stability in processed treated samples for 300 and 1000 ng mL-1 of each drug were estimated (Table 6). The tested quality control samples showed high percent recoveries within the range of 86.72% to 106.23% of the nominal concentration, which lies within the acceptable range. The relative standard deviation percentage (RSD% or CV%) of precision was not more than 12.15% (Table 6).Table 6 The stability data of oseltamivir phosphate/dexamethasone/remdesivir mixture in human plasma and processed treated samples under different storage conditions (n = 3).

Drug name	OSTP	DEX	REM	
Stability assessment test	Storage condition	300 ng mL−1	1000 ng mL−1	300 ng mL−1	1000 ng mL−1	300 ng mL−1	1000 ng mL−1	
Accuracya (Mean, %)	Precisionb (CV, %)	Accuracya (Mean, %)	Precisionb (CV, %)	Accuracya (Mean, %)	Precisionb (CV, %)	Accuracya (Mean, %)	Precisionb (CV, %)	Accuracya (Mean, %)	Precisionb (CV, %)	Accuracya (Mean, %)	Precisionb (CV, %)	
1- Freeze–thaw cycles	 − 80 °C then 25 °C (3 cycles)	103.44	3.42	100.00	4.74	105.18	4.49	99.31	10.78	99.59	1.48	97.62	12.15	
2- Short-term stability	Bench-top (25 °C) for 2 h	101.24	2.52	93.46	3.31	98.53	3.14	101.38	3.33	98.52	2.00	94.92	1.07	
Freezer (− 20 °C) for 24 h	96.29	4.31	99.71	0.83	100.73	0.69	106.23	3.53	106.06	0.32	104.70	8.27	
3- Long-term stability at − 80 °C	For one week	87.84	2.15	99.85	1.56	98.41	10.92	102.72	2.91	104.45	1.18	100.82	1.57	
4- Stability in processed treated samples at − 80 °C	For 24 h	86.72	6.35	100.58	2.37	99.86	7.10	94.77	0.63	99.58	2.47	90.38	6.06	
aThe acceptance criteria were ± 15% of the nominal concentration’s values for QC samples.

bThe acceptance criteria of the coefficient of variation (CV, %) values should not exceed 15% for QC samples.

Matrix effect, extraction efficiency, and process efficiency

They were estimated at low and high levels of QC. The 300 (LQC) and 1000 (HQC) ng mL-1 of each drug were analyzed using blank human plasma from four different sources (plasma A, B, C, and D).For each analyzed drug, the matrix effect (%ME), extraction efficiency or extraction coefficient (%Recovery efficiency, %RE), and process efficiency (%PE) and their IS normalized values were calculated.

The matrix effect (%ME) is defined as an alteration of the analyte response due to an interfering component (s) in the sample matrix (human plasma) (Eq. (7)). The IS normalized matrix effect (%) is defined as the difference percentage in the "response of the analyte/response of IS" ratio between the same analyte concentrations in the sample matrix (human plasma) spiked with the analyte after extraction and in pure solvents (Eq. (8))72. The accuracies of %ME and the IS normalized matrix effect (%) should be within ± 15% of the nominal concentration, and the %RSD should not be greater than 15%31. As indicated in Table S9, the %RSD of %ME and IS normalized ME (%) values were not more than 2.37%, 5.02%, and 4.67% for OSTP, DEX, and REM, respectively, at both concentration levels. Thus, the plasma matrix did not appear to interfere significantly with the method.

The extraction efficiency (%recovery efficiency, %RE) is the percentage of solute that moves into the extracting phase (Eq. (9)). The high extraction efficiency percentage indicates high extraction process effectiveness, high method sensitivity, and high drug stability in the matrix. The IS normalized extraction efficiency (%) is defined as the difference percentage in the "response of the analyte/response of IS" ratio between the same analyte concentrations in the sample matrix (human plasma) spiked with the analyte before extraction and in the sample matrix (human plasma) spiked with the analyte after extraction (Eq. (10)). As indicated in Table S9, the %RE and IS normalized RE (%) values were more than 93%, 88%, and 94% for OSTP, DEX, and REM, respectively, at both concentration levels. Thus, the proposed method appeared to have high extraction efficiency for the tested drugs.

The process efficiency (%PE) is expressed as the ratio of the response of an analyte spiked in the sample matrix (human plasma) before extraction to the response of the same analyte in pure solvents multiplied by 100 (Eq. (11)). It would be equivalent to the recovery as per M10 ICH Guidelines31. The RE% value represented the true recovery value that was not affected by the sample matrix (human plasma), while the PE% value represented the overall process efficiency that was unfortunately affected by the sample matrix (human plasma)73. The IS normalized process efficiency (%) is defined as the difference percentage in the "response of the analyte/response of IS" ratio between the same analyte concentrations in the sample matrix (human plasma) spiked with the analyte before extraction and in pure solvents (Eq. (12)).As indicated in Table S9, the %RSD of %PE and IS normalized PE (%) values were not more than 5.04%, 5.08%, and 5.02% for OSTP, DEX, and REM, respectively, at both concentration levels. Thus, the proposed method appeared to have good overall process efficiency.7 Matrix effect(\%ME)=AUCBlank sample of plasma spiked with the drug after extractionAUCPure drug solution in60\% aqueous methanol×100

8 IS normalized matrix effect(\%)=AUCBlank sample of plasma spiked with the drug after extractionAUCBlank sample of plasma spiked with the IS after extractionAUCPure drug solution in60\% aqueous methanolAUCPure IS solution in60\% aqueous methanol×100=\%MEDrug\%MEIS×100

9 Extraction efficiency(\%Recovery efficiency,\%RE)=AUCBlank sample of plasma spiked with the drug before extractionAUCBlank sample of plasma spiked with the drug after extraction×100

10 IS normalized extraction efficiency(\%)=AUCBlank sample of plasma spiked with the drug before extractionAUCBlank sample of plasma spiked with the IS before extractionAUCBlank sample of plasma spiked with the drug after extractionAUCBlank sample of plasma spiked with the IS after extraction×100=\%REDrug\%REIS×100

11 Process efficiency(\%PE)=AUCBlank sampleof plasma spiked with the drug before extractionAUCPure drug solution in60\% aqueous methanol×100

12 IS normalized process efficiency(\%)=AUCBlank sample of plasma spiked with the drug before extractionAUCBlank sample of plasma spiked with the IS before extractionAUCPure drug solution in60\% aqueous methanolAUCPure IS solution in60\% aqueous methanol×100=\%PEDrug\%PEIS×100

Greenness assessment

The greenness of the proposed method was assessed using the analytical Eco-Scale35, the Green Analytical Procedure Index (GAPI)36, and the AGREE method34. The analytical Eco-Scale35 is a semi-quantitative tool for greenness assessment of the analytical methods. The simultaneous analysis of OSTP, DEX, and REM in human plasma by the proposed method was an acceptable green analysis with low laboratory needs (Eco-score 68). Moreover, the suggested method provided acceptable green analysis when applied to the assessment of OSTP with DEX mixture, DEX with REM mixture, or each drug separately in human plasma (Eco-score greater than 50) (Table S10). Moreover, the suggested method provided acceptable green analysis when applied to the assessment of OSTP with DEX mixture, DEX with REM mixture, or each drug separately in human plasma (Eco-score greater than 50) (Table S10).

According to the Green Analytical Procedure Index (GAPI)36, the suggested method was an indirect procedure with a LLE extraction process (Fig. S5). It also used small volumes of safe chemicals with little waste due to the low flow rate (0.25 mL min−1). Furthermore, the suggested method was for qualitative and quantitative analyses.

The AGREE method (Analytical GREEnness Metric Approach and Software)34 is a comprehensive method that incorporates 12 significance principles for greenness assessment of the analytical methods. The obtained colorful pictogram shows the structure of weak and strong points of the analytical method. According to Fig. S6, the total score was illustrated in the center of the pictogram, with a number near one (0.62) and a light green color suggesting that the suggested method was acceptable green.

Conclusion

The proposed method was optimized and validated according to the M10 ICH's bioanalytical method validation guideline. The developed method is highly sensitive, accurate, and precise, with a wide range of linearity in human plasma. It is suitable for assaying OSTP, DEX, and REM in human plasma, as the linearity ranges cover their plasma Cmax. The PDA detector is used for OSTP, DEX, and REM analysis using three wavelengths. The full factorial designs with one centerpoint experiment were used to determine the curvature possibilities (lack of fit) of the selected dependent responses, followed by multiple regression analysis. There was no evidence of curvatures in the regression lines of the methanol percentage, flow rate, or ammonium acetate concentration against k' (OSTP) or RS2 (DAC), indicating that the optimum condition can be obtained from the 23 full factorial design without conducting a centerpoint experiment. The method was optimized at a column oven temperature of 25 °C. The effect of column oven temperatures at 25, 30, 45, and 50 °C on the drugs’ retention times was investigated by the Van't Hoff plots and Gibbs’ free energy (G°) of the tested drugs. OSTP and DAC (IS) have identical stationary phase interactions as their Van't Hoff plots had slightly different slopes and minor differences in ΔG° values, as well as for DEX and REM. The column oven temperature of 50 °C is the most suitable temperature with good system suitability parameters. The benchtop (short-term) stability of each drug at room temperature for 2 h in different types of human plasma was investigated. Fluoride-EDTA human plasma shows the highest stability results for the studied drugs. The matrix effect, extraction efficiency, process efficiency, and internal standard normalized values of the proposed method are high. The optimization by factorial method is the most eco-friendly technique. Because it consumes the least amount of instrumental energy and money and releases the least amount of hazardous waste into the environment. Furthermore, the analytical Eco-Scale, GAPI, and AGREE proved the greenness of the proposed method. It uses small volumes of safe chemicals with little waste due to the low flow rate (0.25 mL min−1).

Supplementary Information

Supplementary Information.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-71413-3.

Author contributions

H.I.: conceptualization and methodology; software and acquisition of data; validation; formal analysis and interpretation of data; and drafting the manuscript. F.B. and G.H.: conceptualization and methodology. All authors reviewed the manuscript critically for important intellectual content and approved its publication.

Funding

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare no competing interests.

Ethical approval

We confirm that all experiments were performed in accordance with relevant guidelines and regulations. The study was conducted according to the rules of the Ethics Committee at the Faculty of Pharmacy, Suez Canal University (number: 202009PHDH1). Informed consent was obtained from all subjects and/or their legal guardian(s). The duration of the study was within 1 month and parallel. The retention of the sample in the ultra-low deep freezer was for 7 days. The preparation of spiked solutions for validation was concurrent with the study. The preparation of spiked samples for analysis of the study sample was done after validation and preserved for 1 week.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
References

1. Gulyaeva AA Gorbalenya AE A nidovirus perspective on SARS-CoV-2 Biochem. Biophys. Res. Commun. 2021 538 24 34 10.1016/j.bbrc.2020.11.015 33413979
Gulyaeva, A. A. & Gorbalenya, A. E. A nidovirus perspective on SARS-CoV-2. Biochem. Biophys. Res. Commun. 538, 24–34 (2021).33413979
2. Malone B Urakova N Snijder EJ Campbell EA Structures and functions of coronavirus replication–transcription complexes and their relevance for SARS-CoV-2 drug design Nat. Rev. Mol. Cell Biol. 2022 23 21 39 10.1038/s41580-021-00432-z 34824452
Malone, B., Urakova, N., Snijder, E. J. & Campbell, E. A. Structures and functions of coronavirus replication–transcription complexes and their relevance for SARS-CoV-2 drug design. Nat. Rev. Mol. Cell Biol. 23, 21–39. 10.1038/s41580-021-00432-z (2022).34824452
3. Shabani M Sadegh Ehdaei B Fathi F Dowran R A mini-review on sofosbuvir and daclatasvir treatment in coronavirus disease 2019 New Microbes New Infect. 2021 42 100895 10.1016/j.nmni.2021.100895 33976895
Shabani, M., Sadegh Ehdaei, B., Fathi, F. & Dowran, R. A mini-review on sofosbuvir and daclatasvir treatment in coronavirus disease 2019. New Microbes New Infect. 42, 100895. 10.1016/j.nmni.2021.100895 (2021).33976895
4. Vafaei S Razmi M Mansoori M Asadi-Lari M Madjd Z Spotlight of remdesivir in comparison with ribavirin, favipiravir, oseltamivir and umifenovir in coronavirus disease 2019 (COVID-19) pandemic Lancet Infect. Dis. 2020 10.2139/ssrn.3569866
Vafaei, S., Razmi, M., Mansoori, M., Asadi-Lari, M. & Madjd, Z. Spotlight of remdesivir in comparison with ribavirin, favipiravir, oseltamivir and umifenovir in coronavirus disease 2019 (COVID-19) pandemic. Lancet Infect. Dis.10.2139/ssrn.3569866 (2020).
5. Tan Q Is oseltamivir suitable for fighting against COVID-19: In silico assessment, in vitro and retrospective study Bioorg. Chem. 2020 104 104257 10.1016/j.bioorg.2020.104257 32927129
Tan, Q. et al. Is oseltamivir suitable for fighting against COVID-19: In silico assessment, in vitro and retrospective study. Bioorg. Chem. 104, 104257. 10.1016/j.bioorg.2020.104257 (2020).32927129
6. Qiu T Chinese guidelines related to novel coronavirus pneumonia J. Mark. Access Health Policy 2020 8 1818446 10.1080/20016689.2020.1818446 33133431
Qiu, T. et al. Chinese guidelines related to novel coronavirus pneumonia. J. Mark. Access Health Policy 8, 1818446. 10.1080/20016689.2020.1818446 (2020).33133431
7. DrugBank. Remdesivir, https://go.drugbank.com/drugs/DB14761 (2019).
8. Hanafin PO A mechanism-based pharmacokinetic model of remdesivir leveraging interspecies scaling to simulate COVID-19 treatment in humans CPT Pharmacomet. Syst. Pharmacol. 2021 10 89 99 10.1002/psp4.12584
Hanafin, P. O. et al. A mechanism-based pharmacokinetic model of remdesivir leveraging interspecies scaling to simulate COVID-19 treatment in humans. CPT Pharmacomet. Syst. Pharmacol. 10, 89–99. 10.1002/psp4.12584 (2021).
9. EMA. Veklury, https://www.ema.europa.eu/en/documents/assessment-report/veklury-epar-public-assessment-report_en.pdf (2020).
10. Masoud, H. et al. Management protocol for COVID-19 patients MoHP protocol for COVID19 November 2020, https://www.researchgate.net/publication/345813633_Management_Protocol_for_COVID-19_Patients_MoHP_Protocol_for_COVID19_November_2020 (2020).
11. FDA, U. S. The FDA approves first generic version of widely used influenza drug, Tamiflu, https://www.fda.gov/drugs/postmarket-drug-safety-information-patients-and-providers/fda-approves-first-generic-version-widely-used-influenza-drug-tamiflu#:~:text=On%20August%203%2C%202016%2C%20the,and%20prevention%20of%20the%20flu (2016).
12. Navas M Jimenez A Analytical methods to determine anti-influenza drugs Crit. Rev. Anal. Chem. 2011 41 81 97 10.1080/10408347.2011.539416
Navas, M. & Jimenez, A. Analytical methods to determine anti-influenza drugs. Crit. Rev. Anal. Chem. 41, 81–97 (2011).
13. Bosch ME Ojeda CB Sánchez AJR Rojas FS Analytical methodologies for the determination of oseltamivir Res. J. Pharm. Biol. Chem. Sci. 2010 1 368
Bosch, M. E., Ojeda, C. B., Sánchez, A. J. R. & Rojas, F. S. Analytical methodologies for the determination of oseltamivir. Res. J. Pharm. Biol. Chem. Sci. 1, 368 (2010).
14. Junaidy MQ Haque MA Bakshi V RP-HPLC method development and validation for the estimation of oseltamivir phosphate in bulk form and pharmaceutical formulations Int. J. Innov. Pharma. Sci. Res. 2014 2 2786 2791
Junaidy, M. Q., Haque, M. A. & Bakshi, V. RP-HPLC method development and validation for the estimation of oseltamivir phosphate in bulk form and pharmaceutical formulations. Int. J. Innov. Pharma. Sci. Res. 2, 2786–2791 (2014).
15. Ramya VZ Gowda YN Simultaneous estimation of amantadine hydrochloride and oseltamivir phosphate using precolumn derivatization technique Int. J. Pharm. Sci. Res. 2019 10 5443 5449 10.13040/IJPSR.0975-8232.10(12).5443-49
Ramya, V. Z. & Gowda, Y. N. Simultaneous estimation of amantadine hydrochloride and oseltamivir phosphate using precolumn derivatization technique. Int. J. Pharm. Sci. Res. 10, 5443–5449. 10.13040/IJPSR.0975-8232.10(12).5443-49 (2019).
16. Al-Bagary RI El-Zaher AA Morsy FA Fouad MM Kinetic study of the alkaline degradation of oseltamivir phosphate and valacyclovir hydrochloride using validated stability indicating HPLC Anal. Chem. Insights 2014 9 41 48 10.4137/aci.S13878 24932100
Al-Bagary, R. I., El-Zaher, A. A., Morsy, F. A. & Fouad, M. M. Kinetic study of the alkaline degradation of oseltamivir phosphate and valacyclovir hydrochloride using validated stability indicating HPLC. Anal. Chem. Insights 9, 41–48. 10.4137/aci.S13878 (2014).24932100
17. Reddy G Pulipaka S Krishna R Narayanarao K Rapeti D Characterization of oseltamivir phosphate api and simultaneous quantification and validation of its impurities by UPLC Asian J. Pharm. Clin. Res. 2021 14 161 169 10.22159/ajpcr.2021.v14i4.40595
Reddy, G., Pulipaka, S., Krishna, R., Narayanarao, K. & Rapeti, D. Characterization of oseltamivir phosphate api and simultaneous quantification and validation of its impurities by UPLC. Asian J. Pharm. Clin. Res. 14, 161–169. 10.22159/ajpcr.2021.v14i4.40595 (2021).
18. Reddy S Development and validation of two LCMS/MS methods for simultaneous estimation of oseltamivir and its metabolite in human plasma and application in bioequivalence study Asian J. Pharm. Anal. 2016 6 91 101 10.5958/2231-5675.2016.00014.4
Reddy, S. et al. Development and validation of two LCMS/MS methods for simultaneous estimation of oseltamivir and its metabolite in human plasma and application in bioequivalence study. Asian J. Pharm. Anal. 6, 91–101 (2016).
19. Berendsen BJ Wegh RS Essers ML Stolker AA Weigel S Quantitative trace analysis of a broad range of antiviral drugs in poultry muscle using column-switch liquid chromatography coupled to tandem mass spectrometry Anal. Bioanal. Chem. 2012 402 1611 1623 10.1007/s00216-011-5581-3 22173207
Berendsen, B. J., Wegh, R. S., Essers, M. L., Stolker, A. A. & Weigel, S. Quantitative trace analysis of a broad range of antiviral drugs in poultry muscle using column-switch liquid chromatography coupled to tandem mass spectrometry. Anal. Bioanal. Chem. 402, 1611–1623 (2012).22173207
20. Omar MA Derayea SM Mostafa IM Selectivity improvement for spectrofluorimetric determination of oseltamivir phosphate in human plasma and in the presence of its degradation product Fluorescence 2017 27 1323 1330 10.1007/s10895-017-2066-6
Omar, M. A., Derayea, S. M. & Mostafa, I. M. Selectivity improvement for spectrofluorimetric determination of oseltamivir phosphate in human plasma and in the presence of its degradation product. Fluorescence 27, 1323–1330. 10.1007/s10895-017-2066-6 (2017).
21. Flick TG Leib RD Williams ER Direct standard-free quantitation of Tamiflu and other pharmaceutical tablets using clustering agents with electrospray ionization mass spectrometry Anal. Chem. 2010 82 1179 1182 10.1021/ac902277d 20092258
Flick, T. G., Leib, R. D. & Williams, E. R. Direct standard-free quantitation of Tamiflu and other pharmaceutical tablets using clustering agents with electrospray ionization mass spectrometry. Anal. Chem. 82, 1179–1182. 10.1021/ac902277d (2010).20092258
22. Jebali I Belgaied J-E A novel coated platinum electrode for oseltamivir determination in pharmaceuticals Mater. Sci. Eng. C 2014 37 90 98 10.1016/j.msec.2013.12.040
Jebali, I. & Belgaied, J.-E. A novel coated platinum electrode for oseltamivir determination in pharmaceuticals. Mater. Sci. Eng. C 37, 90–98. 10.1016/j.msec.2013.12.040 (2014).
23. Gungor S Bulduk I Sultan Aydın B Ilikci Sagkan R A comparative study of HPLC and UV spectrophotometric methods for oseltamivir quantification in pharmaceutical formulations Acta Chromatogr. 2022 34 258 266 10.1556/1326.2021.00925
Gungor, S., Bulduk, I., Sultan Aydın, B. & Ilikci Sagkan, R. A comparative study of HPLC and UV spectrophotometric methods for oseltamivir quantification in pharmaceutical formulations. Acta Chromatogr. 34, 258–266. 10.1556/1326.2021.00925 (2022).
24. Esposito MC Santos ALA Bonfilio R de Araújo MB A critical review of analytical methods in pharmaceutical matrices for determination of corticosteroids Crit. Rev. Anal. Chem. 2020 50 111 124 10.1080/10408347.2019.1581050 30869528
Esposito, M. C., Santos, A. L. A., Bonfilio, R. & de Araújo, M. B. A critical review of analytical methods in pharmaceutical matrices for determination of corticosteroids. Crit. Rev. Anal. Chem. 50, 111–124 (2020).30869528
25. Emam AA Abdelaleem EA Abdelmomen EH Abdelmoety RH Abdelfatah RM Rapid and ecofriendly UPLC quantification of remdesivir, favipiravir and dexamethasone for accurate therapeutic drug monitoring in Covid-19 Patient’s plasma Microchem. J. 2022 179 107580 10.1016/j.microc.2022.107580 35582001
Emam, A. A., Abdelaleem, E. A., Abdelmomen, E. H., Abdelmoety, R. H. & Abdelfatah, R. M. Rapid and ecofriendly UPLC quantification of remdesivir, favipiravir and dexamethasone for accurate therapeutic drug monitoring in Covid-19 Patient’s plasma. Microchem. J. 179, 107580. 10.1016/j.microc.2022.107580 (2022).35582001
26. Nguyen R Development and validation of a simple, selective, and sensitive LC-MS/MS assay for the quantification of remdesivir in human plasma J. Chromatogr. B 2021 1171 122641 10.1016/j.jchromb.2021.122641
Nguyen, R. et al. Development and validation of a simple, selective, and sensitive LC-MS/MS assay for the quantification of remdesivir in human plasma. J. Chromatogr. B 1171, 122641. 10.1016/j.jchromb.2021.122641 (2021).
27. Hamdy MM Abdel Moneim MM Kamal MF Accelerated stability study of the ester prodrug remdesivir: Recently FDA-approved Covid-19 antiviral using reversed-phase-HPLC with fluorimetric and diode array detection Biomed. Chromatogr. 2021 35 e5212 10.1002/bmc.5212 34227154
Hamdy, M. M., Abdel Moneim, M. M. & Kamal, M. F. Accelerated stability study of the ester prodrug remdesivir: Recently FDA-approved Covid-19 antiviral using reversed-phase-HPLC with fluorimetric and diode array detection. Biomed. Chromatogr. 35, e5212 (2021).34227154
28. Deniz E Özaltin N Yilmaz S A review on recent electroanalytical methods for the analysis of antiviral COVID-19 drugs Turk. J. Chem. 2021 3 1 8
Deniz, E., Özaltin, N. & Yilmaz, S. A review on recent electroanalytical methods for the analysis of antiviral COVID-19 drugs. Turk. J. Chem. 3, 1–8 (2021).
29. Elmansi H Ibrahim AE Mikhail IE Belal F Green and sensitive spectrofluorimetric determination of remdesivir, an FDA approved SARS-CoV-2 candidate antiviral; application in pharmaceutical dosage forms and spiked human plasma Anal. Methods 2021 13 2596 2602 10.1039/D1AY00469G 34019051
Elmansi, H., Ibrahim, A. E., Mikhail, I. E. & Belal, F. Green and sensitive spectrofluorimetric determination of remdesivir, an FDA approved SARS-CoV-2 candidate antiviral; application in pharmaceutical dosage forms and spiked human plasma. Anal. Methods 13, 2596–2602. 10.1039/D1AY00469G (2021).34019051
30. Gumustas M Kurbanoglu S Uslu B Ozkan SA UPLC versus HPLC on drug analysis: Advantageous, applications and their validation parameters Chromatographia 2013 76 1365 1427 10.1007/s10337-013-2477-8
Gumustas, M., Kurbanoglu, S., Uslu, B. & Ozkan, S. A. UPLC versus HPLC on drug analysis: Advantageous, applications and their validation parameters. Chromatographia 76, 1365–1427 (2013).
31. Bioanalytical method validation and study sample analysis M10. ICH Harmonised Guideline: Geneva, Switzerland (2022).
32. Meesters R Voswinkel S Bioanalytical method development and validation: From the USFDA 2001 to the USFDA 2018 guidance for industry J. Appl. Bioanal. 2018 4 67 73 10.17145/jab.18.010
Meesters, R. & Voswinkel, S. Bioanalytical method development and validation: From the USFDA 2001 to the USFDA 2018 guidance for industry. J. Appl. Bioanal. 4, 67–73 (2018).
33. Smith G European medicines agency guideline on bioanalytical method validation: What more is there to say? Bioanalysis 2012 4 865 868 10.4155/bio.12.44 22533559
Smith, G. European medicines agency guideline on bioanalytical method validation: What more is there to say?. Bioanalysis 4, 865–868 (2012).22533559
34. Pena-Pereira F Wojnowski W Tobiszewski M AGREE—Analytical greenness metric approach and software Anal. Chem. 2020 92 10076 10082 10.1021/acs.analchem.0c01887 32538619
Pena-Pereira, F., Wojnowski, W. & Tobiszewski, M. AGREE—Analytical greenness metric approach and software. Anal. Chem. 92, 10076–10082. 10.1021/acs.analchem.0c01887 (2020).32538619
35. Gałuszka A Migaszewski ZM Konieczka P Namieśnik J Analytical Eco-Scale for assessing the greenness of analytical procedures Trends Anal. Chem. 2012 37 61 72 10.1016/j.trac.2012.03.013
Gałuszka, A., Migaszewski, Z. M., Konieczka, P. & Namieśnik, J. Analytical Eco-Scale for assessing the greenness of analytical procedures. Trends Anal. Chem. 37, 61–72 (2012).
36. Płotka-Wasylka J A new tool for the evaluation of the analytical procedure: Green Analytical Procedure Index Talanta 2018 181 204 209 10.1016/j.talanta.2018.01.013 29426502
Płotka-Wasylka, J. A new tool for the evaluation of the analytical procedure: Green Analytical Procedure Index. Talanta 181, 204–209. 10.1016/j.talanta.2018.01.013 (2018).29426502
37. Yi, X., Shi, W., Yu, S. & Li, X. MINITAB ® release 16 statistical software for windows. https://www.minitab.com/en-us/products/minitab/ (2011).
38. Dejaegher B Heyden YV Experimental designs and their recent advances in set-up, data interpretation, and analytical applications J. Pharm. Biomed. Anal. 2011 56 141 158 10.1016/j.jpba.2011.04.023 21632194
Dejaegher, B. & Heyden, Y. V. Experimental designs and their recent advances in set-up, data interpretation, and analytical applications. J. Pharm. Biomed. Anal. 56, 141–158. 10.1016/j.jpba.2011.04.023 (2011).21632194
39. El-Shorbagy HI Elsebaei F Hammad SF El-Brashy AM Optimization and modeling of a green dual detected RP-HPLC method by UV and fluorescence detectors using two level full factorial design for simultaneous determination of sofosbuvir and ledipasvir: Application to average content and uniformity of dosage unit testing Microchem. J. 2019 147 374 392 10.1016/j.microc.2019.03.039
El-Shorbagy, H. I., Elsebaei, F., Hammad, S. F. & El-Brashy, A. M. Optimization and modeling of a green dual detected RP-HPLC method by UV and fluorescence detectors using two level full factorial design for simultaneous determination of sofosbuvir and ledipasvir: Application to average content and uniformity of dosage unit testing. Microchem. J. 147, 374–392. 10.1016/j.microc.2019.03.039 (2019).
40. El-Shorbagy HI Mohamed MA El-Gindy A Hadad GM Belal F Development of UPLC method for simultaneous assay of some COVID-19 drugs utilizing novel instrumental standard addition and factorial design Sci. Rep. 2023 13 5466 10.1038/s41598-023-32405-x 37016018
El-Shorbagy, H. I., Mohamed, M. A., El-Gindy, A., Hadad, G. M. & Belal, F. Development of UPLC method for simultaneous assay of some COVID-19 drugs utilizing novel instrumental standard addition and factorial design. Sci. Rep. 13, 5466. 10.1038/s41598-023-32405-x (2023).37016018
41. Waters. ACQUITY UPLC ® BEH C 18 and C 8 columns by Waters, https://www.selectscience.net/products/acquity-uplc-beh-c18-and-c8-columns/?prodID=79501#tab-2 (2020).
42. Waters. Column particle technologies, https://www.waters.com/waters/en_US/BEH-(Ethylene-Bridged-Hybrid)-Technology/nav.htm?cid=134618172&locale=en_US (2022).
43. Tindall GW Dolan JW The interpretation of pH in partially aqueous mobile phases LC GC Europe 2002 15 776 779
Tindall, G. W. & Dolan, J. W. The interpretation of pH in partially aqueous mobile phases. LC GC Europe 15, 776–779 (2002).
44. Lim CK Peters TJ Ammonium acetate: A general purpose buffer for clinical applications of high-performance liquid chromatography J. Chromatogr. A 1984 316 397 406 10.1016/S0021-9673(00)96168-5
Lim, C. K. & Peters, T. J. Ammonium acetate: A general purpose buffer for clinical applications of high-performance liquid chromatography. J. Chromatogr. A 316, 397–406. 10.1016/S0021-9673(00)96168-5 (1984).
45. Boyes B Dong M Modern trends and best practices in mobile-phase selection in reversed-phase chromatography LC GC Europe 2018 31 572 583
Boyes, B. & Dong, M. Modern trends and best practices in mobile-phase selection in reversed-phase chromatography. LC GC Europe 31, 572–583 (2018).
46. Wilson NS Morrison R Dolan JW Buffers and baselines LC GC Europe 2001 19 590 595
Wilson, N. S., Morrison, R. & Dolan, J. W. Buffers and baselines. LC GC Europe 19, 590–595 (2001).
47. Piórkowska E Kaza M Fitatiuk J Szlaska I Rudzki P Rapid and simplified HPLC-UV method with on-line wavelengths switching for determination of capecitabine in human plasma Die Pharmazie 2014 69 500 505 10.1691/ph.2014.3223 25073394
Piórkowska, E., Kaza, M., Fitatiuk, J., Szlaska, I. & Rudzki, P. Rapid and simplified HPLC-UV method with on-line wavelengths switching for determination of capecitabine in human plasma. Die Pharmazie 69, 500–505. 10.1691/ph.2014.3223 (2014).25073394
48. Soriano-Meseguer S Fuguet E Port A Rosés M Influence of the acid-base ionization of drugs in their retention in reversed-phase liquid chromatography Anal. Chim. Acta 2019 1078 200 211 10.1016/j.aca.2019.05.063 31358220
Soriano-Meseguer, S., Fuguet, E., Port, A. & Rosés, M. Influence of the acid-base ionization of drugs in their retention in reversed-phase liquid chromatography. Anal. Chim. Acta 1078, 200–211. 10.1016/j.aca.2019.05.063 (2019).31358220
49. DrugBank. Favipiravir, https://go.drugbank.com/drugs/DB12466 (2021).
50. DrugBank. Daclatasvir dihydrochloride, https://go.drugbank.com/salts/DBSALT001166 (2015).
51. DrugBank. Ledipasvir, https://www.drugbank.ca/drugs/DB09027 (2022).
52. Wadie MA Mostafa SM El Adl SM Elgawish MS Development and validation of a new, simple-hplc method for simultaneous determination of sofosbuvir, daclatasvir and ribavirin in tablet dosage form J. Pharm. Biol. Sci. 2017 12 60 68
Wadie, M. A., Mostafa, S. M., El Adl, S. M. & Elgawish, M. S. Development and validation of a new, simple-hplc method for simultaneous determination of sofosbuvir, daclatasvir and ribavirin in tablet dosage form. J. Pharm. Biol. Sci. 12, 60–68 (2017).
53. Ng, L. L. Reviewer guidance: Validation of chromatographic methods, https://www.fda.gov/regulatory-information/search-fda-guidance-documents/reviewer-guidance-validation-chromatographic-methods (1994).
54. Li, J. B. Effect of temperature on column pressure, peak retention time and peak shape, https://www.waters.com/webassets/cms/library/docs/watersamd30.pdf (2023).
55. Kowalczyk JS Herbut G Influence of temperature on separation processes in adsorption liquid chromatographic systems J. Chromatogr. A 1980 196 11 20 10.1016/S0021-9673(00)80355-6
Kowalczyk, J. S. & Herbut, G. Influence of temperature on separation processes in adsorption liquid chromatographic systems. J. Chromatogr. A 196, 11–20. 10.1016/S0021-9673(00)80355-6 (1980).
56. Hatsis P Lucy C Effect of temperature on retention and selectivity in ion chromatography of anions J. Chromatogr. A 2001 920 3 11 10.1016/S0021-9673(00)01226-7 11453014
Hatsis, P. & Lucy, C. Effect of temperature on retention and selectivity in ion chromatography of anions. J. Chromatogr. A 920, 3–11. 10.1016/S0021-9673(00)01226-7 (2001).11453014
57. Rosing H Doyle E Beijnen JH The impact of column temperature in the high performance liquid chromatographic analysis of topotecan in rat and dog plasma J. Pharm. Biomed. Anal. 1996 15 279 286 10.1016/0731-7085(96)01838-9 8933430
Rosing, H., Doyle, E. & Beijnen, J. H. The impact of column temperature in the high performance liquid chromatographic analysis of topotecan in rat and dog plasma. J. Pharm. Biomed. Anal. 15, 279–286. 10.1016/0731-7085(96)01838-9 (1996).8933430
58. Caiali E David V Aboul-Enein HY Moldoveanu SC Evaluation of the phase ratio for three C18 high performance liquid chromatographic columns J. Chromatogr. A 2016 1435 85 91 10.1016/j.chroma.2016.01.043 26818239
Caiali, E., David, V., Aboul-Enein, H. Y. & Moldoveanu, S. C. Evaluation of the phase ratio for three C18 high performance liquid chromatographic columns. J. Chromatogr. A 1435, 85–91. 10.1016/j.chroma.2016.01.043 (2016).26818239
59. DrugBank. Oseltamivir, https://go.drugbank.com/drugs/DB00198 (2024).
60. DrugBank. Dexamethasone, https://go.drugbank.com/drugs/DB01234 (2005).
61. Tshepelevitsh S Systematic optimization of liquid–liquid extraction for isolation of unidentified components ACS Omega 2017 2 7772 7776 10.1021/acsomega.7b01445 31457334
Tshepelevitsh, S. et al. Systematic optimization of liquid–liquid extraction for isolation of unidentified components. ACS Omega 2, 7772–7776. 10.1021/acsomega.7b01445 (2017).31457334
62. Ouellette RJ Rawn JD Ouellette RJ David Rawn J Principles of Organic Chemistry 2015 Elsevier 239 258
Ouellette, R. J. & Rawn, J. D. In Principles of Organic Chemistry (eds Ouellette, R. J. & David Rawn, J.) 239–258 (Elsevier, 2015).
63. Davies BE Pharmacokinetics of oseltamivir: An oral antiviral for the treatment and prophylaxis of influenza in diverse populations J. Antimicrob. Chemother. 2010 65 ii5 ii10 10.1093/jac/dkq015 20215135
Davies, B. E. Pharmacokinetics of oseltamivir: An oral antiviral for the treatment and prophylaxis of influenza in diverse populations. J. Antimicrob. Chemother. 65, ii5–ii10. 10.1093/jac/dkq015 (2010).20215135
64. Li Z Zhang J Zhang Y Zuo Z Role of esterase mediated hydrolysis of simvastatin in human and rat blood and its impact on pharmacokinetic profiles of simvastatin and its active metabolite in rat J. Pharm. Biomed. Anal. 2019 168 13 22 10.1016/j.jpba.2019.02.004 30776567
Li, Z., Zhang, J., Zhang, Y. & Zuo, Z. Role of esterase mediated hydrolysis of simvastatin in human and rat blood and its impact on pharmacokinetic profiles of simvastatin and its active metabolite in rat. J. Pharm. Biomed. Anal. 168, 13–22. 10.1016/j.jpba.2019.02.004 (2019).30776567
65. Kromdijk W Rosing H van den Broek MP Beijnen JH Huitema AD Quantitative determination of oseltamivir and oseltamivir carboxylate in human fluoride EDTA plasma including the ex vivo stability using high-performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 2012 891–892 57 63 10.1016/j.jchromb.2012.02.026 22418071
Kromdijk, W., Rosing, H., van den Broek, M. P., Beijnen, J. H. & Huitema, A. D. Quantitative determination of oseltamivir and oseltamivir carboxylate in human fluoride EDTA plasma including the ex vivo stability using high-performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 891–892, 57–63. 10.1016/j.jchromb.2012.02.026 (2012).22418071
66. Massarella JW The pharmacokinetics and tolerability of the oral neuraminidase inhibitor oseltamivir (Ro 64–0796/GS4104) in healthy adult and elderly volunteers J. Clin. Pharmacol. 2000 40 836 843 10.1177/00912700022009567 10934667
Massarella, J. W. et al. The pharmacokinetics and tolerability of the oral neuraminidase inhibitor oseltamivir (Ro 64–0796/GS4104) in healthy adult and elderly volunteers. J. Clin. Pharmacol. 40, 836–843. 10.1177/00912700022009567 (2000).10934667
67. Loew D Schuster O Graul EH Dose-dependent pharmacokinetics of dexamethasone Eur. J. Clin. Pharmacol. 1986 30 225 230 10.1007/bf00614309 3709651
Loew, D., Schuster, O. & Graul, E. H. Dose-dependent pharmacokinetics of dexamethasone. Eur. J. Clin. Pharmacol. 30, 225–230. 10.1007/bf00614309 (1986).3709651
68. Spoorenberg SMC Pharmacokinetics of oral vs. intravenous dexamethasone in patients hospitalized with community-acquired pneumonia Br. J. Clin. Pharmacol. 2014 78 78 83 10.1111/bcp.12295 24400953
Spoorenberg, S. M. C. et al. Pharmacokinetics of oral vs. intravenous dexamethasone in patients hospitalized with community-acquired pneumonia. Br. J. Clin. Pharmacol. 78, 78–83. 10.1111/bcp.12295 (2014).24400953
69. Brady ME Sartiano GP Rosenblum SL Zaglama NE Bauguess CT The pharmacokinetics of single high doses of dexamethasone in cancer patients Eur. J. Clin. Pharmacol. 1987 32 593 596 10.1007/bf02455994 3653229
Brady, M. E., Sartiano, G. P., Rosenblum, S. L., Zaglama, N. E. & Bauguess, C. T. The pharmacokinetics of single high doses of dexamethasone in cancer patients. Eur. J. Clin. Pharmacol. 32, 593–596. 10.1007/bf02455994 (1987).3653229
70. Nakade S Population pharmacokinetics of aprepitant and dexamethasone in the prevention of chemotherapy-induced nausea and vomiting Cancer Chemother. Pharmacol. 2008 63 75 83 10.1007/s00280-008-0713-y 18317761
Nakade, S. et al. Population pharmacokinetics of aprepitant and dexamethasone in the prevention of chemotherapy-induced nausea and vomiting. Cancer Chemother. Pharmacol. 63, 75–83. 10.1007/s00280-008-0713-y (2008).18317761
71. Humeniuk R Safety, tolerability, and pharmacokinetics of remdesivir, an antiviral for treatment of COVID-19, in healthy subjects Clin. Transl. Sci. 2020 13 896 906 10.1111/cts.12840 32589775
Humeniuk, R. et al. Safety, tolerability, and pharmacokinetics of remdesivir, an antiviral for treatment of COVID-19, in healthy subjects. Clin. Transl. Sci. 13, 896–906 (2020).32589775
72. Elawady T Khedr A El-Enany N Belal F LC-MS/MS determination of erdafitinib in human plasma after SPE: Investigation of the method greenness Microchem. J. 2020 154 104555 10.1016/j.microc.2019.104555
Elawady, T., Khedr, A., El-Enany, N. & Belal, F. LC-MS/MS determination of erdafitinib in human plasma after SPE: Investigation of the method greenness. Microchem. J. 154, 104555. 10.1016/j.microc.2019.104555 (2020).
73. Nouman EG Al-Ghobashy MA Lotfy HM Development and validation of LC-MS/MS assay for the determination of Butoconazole in human plasma: Evaluation of systemic absorption following topical application in healthy volunteers Bull. Fac. Pharm. Cairo Univ. 2017 55 303 310 10.1016/j.bfopcu.2017.04.003
Nouman, E. G., Al-Ghobashy, M. A. & Lotfy, H. M. Development and validation of LC-MS/MS assay for the determination of Butoconazole in human plasma: Evaluation of systemic absorption following topical application in healthy volunteers. Bull. Fac. Pharm. Cairo Univ. 55, 303–310. 10.1016/j.bfopcu.2017.04.003 (2017).
