A greener RP-HPLC method for quaternary estimation of caffeine, paracetamol, levocetirizine, and phenylephrine acquiring AQbD with stability studies

Vineetha Rosireddy; Manikandan Krishnan

doi:10.1515/gps-2024-0003

Article Open Access

A greener RP-HPLC method for quaternary estimation of caffeine, paracetamol, levocetirizine, and phenylephrine acquiring AQbD with stability studies

Vineetha Rosireddy and Manikandan Krishnan

Published/Copyright: April 30, 2024

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From the journal Green Processing and Synthesis Volume 13 Issue 1

Abstract

The main objective of this article was to develop method and validate quaternary estimation of caffeine (CFE), paracetamol (PCM), levocetirizine (LEV), and phenylephrine (PHE) and to conduct degradation experiments using reverse-phase high-performance liquid chromatography (RP-HPLC). This was the first innovative approach to this drug combination, combining analytical quality by design with green analytical chemistry. This method was developed using HPLC Agilent 1220 Infinity II, a binary solvent delivery pump, an automatic sampling device injector, and a photodiode array detector. Agilent Inertsil ODS 3 (250 mm × 4.6 mm, 5 μm) was used for separation. The mobile phase is composed of ethanol and 10 mM phosphate buffer (pH 3). To adjust the pH, 1% of orthophosphoric acid was used. The flow rate was set to 0.8 ml·min⁻¹, the injection volume was 10 μl, and the detecting wavelength was 220 nm. The analytes were eluted via gradient elution. The retention time for PCM was 3.5 min, CFE was 8.1 min, PHE was 15.9 min, and LEV was 20.5 min. Green evaluation tools used in this research include Green Analytical Procedure Index, analytical eco-scale, analytical greenness, analytical method greenness score, and carbon footprint analysis. The developed method was greener than the previously reported method, as per the results of the greenness evaluation tools.

Graphical Abstract

Keywords: RP-HPLC; central composite design; GAPI; AES; and carbon footprint analysis

1 Introduction

Developments in dosage forms lead to the use of multi-drug regimens for treating various diseases, in which numerous medications are administered in a single tablet/capsule or multiple pills. Combination medicines offer benefits such as decreased drug resistance, increased responsiveness, and fewer adverse reactions [1]. Over the past decade, fixed-dose medication combination therapy has gained popularity for numerous disorders [2,3]. Many attempts have been made to develop a fixed-dose combination for migraines, muscle discomfort, tooth pain, and menstrual cramps [4].

Caffeine (CFE) is a central nervous system stimulant that contains 1,3,7-trimethyl-3,7-dihydro-1H-purin-2,6-dion. CFE has the potential to boost analgesic efficacy due to its stimulating effect on the central nervous system, alleviating frequent pain-related depression [5,6,7,8]. CFE mixed with paracetamol (PCM) in a fixed combined dosage form is used to treat various disorders such as migraine headaches, dysmenorrhea, cancer pain, postpartum discomfort, sore throat, and dental post-surgery pain [9]. CFE is soluble in chloroform, water, methanol, ethanol, and carbon tetrachloride.

PCM is N-(4-hydroxyphenyl)-acetamide. It decreases the temperature and is used to treat gout, pain in the teeth, and migraine [10]. It is a key component of many medications for colds and flu. PCM may also be used to control unbearable pain, like pain after surgery, especially when mixed with nonsteroidal anti-inflammatory drugs or opioid painkillers [11]. The official methods of PCM are available in the British Pharmacopeia [12]. It is a white crystalline powder with a bitter taste that is soluble in alcohol, acetone, and NaOH. It has low water solubility [13].

Levocetirizine (LEV) is [2-[4-[(r)-(4-chlorophenyl)phenylmethyl]ethoxy]-1-piperazinyl] acetic acid. LEV is a non-sedative third-generation antihistamine derived from the second-generation antihistamine cetirizine. It is the Levo enantiomer that inhibits histamine receptors. It does not prevent histamine from being released from mast cells, but it does prevent it from binding to its receptors. It inhibits hay fever symptoms [14], long-term urticaria [15], and produces less sedation compared to cetirizine [16]. Cetirizine is highly soluble in water and organic solvents like ethanol and methanol.

Phenylephrine (PHE) is (R)-3-[1-hydroxy-2-(methylamino)ethyl] phenol. PHE works on α-adrenoreceptors to open up blocked noses and help sinus spaces drain better. PHE is combined with CFE, PCM, and LEV. It is used in the treatment of allergy symptoms, relieve congestion, and lower the temperature [17,18,19,20,21]. PHE is mildly soluble in water and ethanol and sparingly soluble in methanol (Figure 1).

Figure 1

Structure of CFE, PCM, LEV, and PHE.

Quality by Design (QbD) is a systematic development technique that starts with pre-established goals, is based on rigorous scientific principles, prioritizes quality risk reduction, and emphasizes process control and understanding of both products and processes. As a means of increasing the effectiveness and dependability of analytical methodologies, QbD concepts are becoming increasingly popular [22,23,24]. Analytical Quality by Design (AQbD) is utilized in product development and analytical procedures. AQbD is an approach to ensure that the analytical processes are valuable and consistently produce outcomes that precisely address goals. The QbD solution effectively circumvents the issues with the conventional approach by allowing numerous variables to influence the method’s answers simultaneously [25,26,27,28].

Green analytical chemistry (GAC) aims to replace ecologically harmful chemicals with safe substitutes in order to develop a multi-green analytical approach for sustainable development [29,30,31]. The GAC guideline gives the procedure for the use of the solvents [32,33]. Ethanol is a safe solvent that is an excellent substitute for hazardous methanol and acetonitrile. The proposed study demonstrates a novel chromatographic method utilizing ethanol, which is thought to be a more environmentally friendly solvent than acetonitrile and methanol and is also less hazardous. Therefore, the main goal of this study was to present a novel method for practically combining GAC concepts with the idea of AQbD.

There is no literature evidence on reverse-phase high-performance liquid chromatography (RP-HPLC) stability-indicating method for simultaneously determining CFE, PCM, LEV, and PHE in a combination tablet dose form to the best of our knowledge. As a result, we sought to develop and confirm an RP-HPLC stability-indicating method for four analytes for highly reproducible, accurate, cost-effective, and reliable routine analysis.

2 Materials and methods

2.1 Chemicals and reagents

The active pharmaceutical ingredient (API) of CFE, PCM, LEV, and PHE was obtained from Yarrow Chem Products in Mumbai, India. HPLC-grade ethanol was purchased from Merck India Life Sciences. Sodium hydroxide (NaOH) was obtained from Ranbaxy, New Delhi, India. Potassium dihydrogen orthophosphate (KH₂PO₄) was purchased from Sisco Research Laboratories Pvt. Ltd., Mumbai, and concentrated hydrochloric acid (HCl) was procured from Rankem, India. A 3% v/v solution of hydrogen peroxide (H₂O₂) was obtained from Carbanio. A Milli Q filter device from ELGA Lab Water, based in the UK, was used for filtering HPLC-grade water. A 0.45 μm membrane filter was provided by Pall Life Sciences, Bengaluru, India. The combination of Winto-cold tablets containing CFE 30 mg, PCM 325 mg, LEV 2.5 mg, and PHE 10 mg was purchased from the nearest pharmacy. (The trade name is MS [Medisun Square™], and the production company was Gromore Laboratories).

2.2 Instruments used

To conduct the analysis, the HPLC system was used. Agilent 1220 Infinite II (Agilent Technologies), photodiode array (PDA) detector (Santa Clara, California), ultra sonicator (Labman, Chennai, India)], vacuum filter (Eimco-k.c. p Ltd, Chennai, India), and oven (Guna Enterprises, Chennai, India).

2.3 Solvent preparation

2.3.1 Preparation of buffer

About 0.025 M of phosphate buffer is prepared by taking 3.4 g of potassium dihydrogen orthophosphate and transferring it into a 1,000 ml standard flask, then dissolved with distilled water. A further 1% OPA was added to adjust the pH. Finally, makeup with water up to the mark. The solution was filtered and sonicated for degassing.

2.3.2 Preparation of standard

A stock solution containing 1,000 μg·ml⁻¹ of CFE, PCM, LEV, and PHE was prepared. Dissolve and make up with ethanol up to the mark. Sonicate nearly for 15 min and filter using the membrane filter, followed by making further dilutions to achieve the final concentration of 10 μg·ml⁻¹.

2.3.3 Preparation of sample

Accurately weigh 20 tablets of CFE, PCM, LEV, and PHE, which were then ground to a fine powder mass. An equivalent amount of CFE 30 mg, PCM 325 mg, LEV 2.5 mg, and PHE 10 mg was added to a standard flask and diluted with ethanol. After sonicating for approximately 25 min, the filtrate was filtered through a 0.45 μm membrane filter and diluted to produce the final concentration of CFE 30 µg·ml⁻¹, PCM 325 µg·ml⁻¹, LEV 2.5 µg·ml⁻¹, and PHE 10 µg·ml⁻¹.

2.4 Chromatographic conditions

Method development and validation were done using an HPLC Agilent 1220 Infinity II, a binary solvent delivery pump, an automatic sampling device injector, and a PDA detector. Separation was achieved using an Agilent Inertsil ODS 3 (250 mm × 4.6 mm, 5 µm). The solutions were filtered using a 0.45 µm membrane filter obtained from Pall Life Sciences in Bengaluru, India. The solvents were degassed using an ultra sonicator from Labman, Maharashtra, India. The mobile phase comprises ethanol and phosphate buffer (pH 3); to adjust the pH, 1% orthophosphoric acid was added. The flow rate was set to 0.8 ml·min⁻¹, the injection volume was 10 µl, and the detecting wavelength was 220 nm. The column oven temperature was set to 35°C. The analytes were eluted at the gradient elution. The data were processed using Open LAB CDS Agilent software version 2.6.

2.5 System suitability studies

For the system’s suitability parameters, the standard solutions of CFE, PCM, LEV, and PHE were injected six times. Percentage RSD was calculated for retention time (Rt), peak area, tailing, and theoretical plates. They were automatically created by software (Figure 2).

Figure 2

Chromatogram of CFE, PCM, LEV, and PHE.

2.6 Degradation conditions

A decrease in peak area or the emergence of new peaks was considered as degradation. The level of degradation was ascertained by the recovery percentages. A variety of stress conditions that were applied were explained below.

2.6.1 Forced degradation

Forced degradation was carried out with the goal of purposely degrading the active drugs. These tests were conducted to evaluate the extent to which a technique of analysis would perform to quantify an active ingredient and its breakdown products without generating interference. The drug is exposed to an acid, a base, an oxidizing agent, and photolytic and thermal degradation.

2.6.1.1 Acid degradation

Acid degradation was carried out using 0.1 M hydrochloric acid (HCl). About 1 ml of 100 μg·ml⁻¹ of stock solution was transferred into 10 ml of a standard flask, and then 1 ml of 0.1 M HCl was added. The solution was kept aside at room temperature for 60 min. Pipette out 1 ml of the solution, neutralize it with alkali, and then add ethanol up to the mark. Then, it was filtered using a 0.45 μm syringe filter before injection (Figure 3).

Figure 3

Acid degradation of CFE, PCM, LEV, and PHE.

2.6.1.2 Alkali degradation

Alkali degradation was carried out using 0.1 M NaOH. About 1 ml of 100 μg·ml⁻¹ of stock solution was transferred into 10 ml of a standard flask, and then 1 ml of 0.1 M NaOH was added. The solution was kept aside at room temperature for 60 min. Pipette out 1 ml of the solution, neutralize it with acid, and then add ethanol up to the mark. Then, it was filtered using a 0.45 μm syringe filter before injection (Figure 4).

Figure 4

Alkali degradation of CFE, PCM, LEV, and PHE.

2.6.1.3 Oxidative degradation

Hydrogen peroxide (H₂O₂) 3% v/v was used for oxidative degradation. About 100 μg·ml⁻¹ of stock solution was transferred into 10 ml of a standard flask, then 1 ml of H₂O₂ was added, and then made up with ethanol up to the mark at room temperature for nearly 8 h. Then, it was filtered using a 0.45 μm syringe filter before injection (Figure 5).

Figure 5

Oxidative degradation of CFE, PCM, LEV, and PHE.

2.6.1.4 Photolytic degradation

For photolytic degradation, 100 µg·ml⁻¹ of stock solution was transferred into 10 ml of a standard flask, made up of the desired volume of ethanol up to the mark. Over a period of time, the stock solution was kept in the photostability chamber and was subjected to being exposed to UV light at 254 nm for nearly 8 h, which was then filtered through a 0.45 µm syringe filter before injection (Figure 6).

Figure 6

Photolytic degradation of CFE, PCM, LEV, and PHE.

2.6.1.5 Thermal degradation

For thermal degradation, 100 µg·ml⁻¹ of stock solution was transferred into 10 ml of a standard flask, made up with the desired volume of ethanol up to the mark. The stock solution was kept at a temperature of 60°C for 8 h, which was then filtered through a 0.45 µm syringe filter before injection (Figure 7).

Figure 7

Thermal degradation CFE, PCM, LEV, and PHE.

3 Results

3.1 QbD

QbD is based on the concept that products should be built with quality; they cannot come without testing; they should begin with intentional design. The ICH guideline Q8 (R2) gives a well-defined, clear explanation of QbD about method development and validation, beginning with predefined goals. The method is based on good scientific principles and risk management.

3.2 AQbD

AQbD is mostly used for method development plans; it includes the whole analytical process, from assessing risks to managing projects throughout its entire lifecycle. Implementing the improved (AQbD) approach has been shown to significantly minimize the time by reducing the trails and resources developed by the strong analytical procedures.

Method development and validation for CFE, PCM, LEV, and PHE were done using AQbD principles. When designing an approach, describing the analytical target profile (ATP) is essential. The ATP was very helpful in developing an HPLC method that was very precise, specific, accurate, and robust. The trial was used to conduct preliminary tests to improve the performance of the method and find important independent parameters and their effects on dependent variables. The Ishikawa fishbone diagram was used to identify and assess the most significant variables that might impact the overall performance of the method. The Ishikawa fishbone diagram is a schematic representation of the parameters adopted. The trial design method was used to ensure that each methodology aspect worked most effectively in its own area (Figure 8).

Figure 8

Ishikawa fishbone diagram.

3.3 Central composite design (CCD)

A CCD has been developed for the process of adopting response surface methodology principles. It builds a second-order (quadratic) model for the variable using the CCD. One of the advantages about this approach is that it eliminates the need to conduct a full three-level factorial experiment. The results of the experiment are found using linear regression, possibly in an iterative way, after the trial is over. When a strategy comes together, coded variables are often used. Often, central compound design is used to improve HPLC methods.

3.4 Execution of CCD

CCD is frequently used in response surface methodology because it works well with standard methods, is adaptable, and can predict nonlinear responses that provide useful information regarding the way factors interact and the primary effects. It performs well enough to select alpha-values in less runs. The variables used in the experiment were ethanol content at (−alpha at 5, mid value 10, and +alpha 15) as factor 1 and flow rate (−alpha at 0.8, mid value 1, and +alpha 1.2) as factor 2. Thirteen runs with five centre points were performed to determine whether the factors and responses interacted and to determine the suitable HPLC criteria.

3.5 Responses in CCD

3.5.1 Response 1: Retention time

The resulting F-value was 4.21. It shows the design’s significance. Due to the background noise, there was only a 4.37% likelihood that an F-value this high would occur. The parameters of the model are significant if the P-value is lower than 0.0500. The variance was less than 0.2. The signal-to-noise ratio is determined by Adeq Precision. A ratio in excess of four is desirable. The representations have been verified by performing tests on these. An obtained ratio of 4.996 suggests a strong signal.

Retention time = −3.63039 + −0.133218 * Mobile phase A + 0.432751 * Mobile phase B + 0.008 * Mobile phase A* Mobile phase B + (−0.014425) * Mobile phase A² + (−0.005725) * Mobile phase B²

3.5.2 Response 2: Tailing factor

The resultant F-value was 4.39. It shows the design’s significance. Due to the background noise, there was only a 4.28% likelihood that an F-value this high would occur. The parameters of the model are significant if the P-value is lower than 0.0500. The variance was less than 0.2. The signal-to-noise ratio is determined by Adeq Precision. A ratio in excess of four is desirable. The representations have been verified by performing tests on these. An obtained ratio of 4.963 suggests a strong signal.

Tailing factor = −12.1065 + 0.258385 * Mobile phase A + 0.535072 * Mobile phase B + (−0.0033) * Mobile phase A Mobile phase B + (−0.002915) * Mobile phase A² + (−0.005315) * Mobile phase B²

3.5.3 Response 3: Resolution

The resultant F-value was 6.48. It shows the design’s significance. Due to the background noise, there was only a 1.47% likelihood that an F-value that high would occur. The parameters of the model are significant if the P-value is lower than 0.0500. The variance was less than 0.2. The signal-to-noise ratio is determined by Adeq Precision. A ratio in excess of four is desirable. The representations have been verified by performing tests on these. An obtained ratio of 8.746 suggests a strong signal.

Resolution = 10.8079 + 0.397713 * Mobile phase A + 0.869216 * Mobile phase B + (−0.007) * Mobile phase A Mobile phase B + (−0.00045) * Mobile phase A² + (−0.00845) * Mobile phase B²

3.6 Derringer’s desirability

A method for factor optimization called Derringer’s desirability combines all the solutions to a number that does not depend on the scale at different levels. The values of the desirability functions range from 0 to 1. A score of 0 indicates inadequate performance from the components, whereas a score of 1 indicates the highest level of performance. It is used to define different goals in order to optimize the three replies. It provides a 63 range of solutions with a desirability score of 1. The table listed the criteria for desirability. Practical implementation of a single randomly chosen solution revealed a slight difference between the expected and actual outcomes of less than 10%. Validating the same solution in accordance with ICH (Q14) standards comprised the conclusive stage. In order to achieve the required degree of quality assurance, an elaborate arrangement and interaction between the input parameters and the process parameters is known as a design space. The design space with the greatest probability of achieving the desired result is represented by the yellow-coloured area in the overlay plot.

3.7 Development and optimization using AQbD

Various buffers, such as phosphate, acetate, and formate, were tested at different pH levels. Different solvents were used in the experiment. Finally, to adhere to the principles of green chemistry, environmentally friendly solvents are chosen. Separation was done using an Agilent Inertsil ODS 3 (250 mm × 4.6 mm, 5 μm). Ethanol was used as the organic phase, and phosphate buffer (pH 3) was used as the aqueous phase. To adjust the pH, 1% of orthophosphoric acid was used. The gradient elution technique was used to elute the analytes given in Table 1, with a flow rate of 0.8 ml·min⁻¹ and an injection volume of 10 μl. The detection wavelength is 220 nm. The column oven temperature was set to 35°C. The drug was dissolved and diluted with ethanol. The method was developed and optimized using the Central Composite Design Qbd Design-Expert® Software, specifically Version 22.0. Adoption of the AQbD reduces the number of trails to be performed, reduces solvent consumption, saves time, and yields accurate results. Performing AQbD is the robustness of the study (Tables 2–5) (Figure 9).

Table 1

Mobile phase in gradient elution

Time (min)	Mobile phase
Time (min)	Mobile phase A: ethanol	Mobile phase B: phosphate buffer (pH 3):1% ortho phosphoric acid
0–9	10	90
10–15	50	50
15–20	20	80
20–25	10	90

Table 2

System suitability studies

Parameters	Retention time				Tailing				Capacity factor				Theoretical plates				Resolution
Parameters	CFE	PCM	PHE	LEV	CFE	PCM	PHE	LEV	CFE	PCM	PHE	LEV	CFE	PCM	PHE	LEV	R_S 1–2	R_S 2–3	R_S 3–4
Mean	2.37	6.52	9.1	12.3	1.69	1.60	1.39	1.80	0.68	2.90	5.25	6.64	2,578.6	3,374.16	5,772.83	3761	12	8.01	7.43
S. D	0.02	0.08	0.12	0.12	0.02	0.02	0.01	0.02	0.01	0.04	0.05	0.08	44.858	37.82	79.032	37.46	0.12	0.11	0.08
% RSD	1.11	1.35	1.31	1.0	1.27	1.65	1.05	1.14	1.76	1.65	1.07	1.21	1.739	1.032	1.369	0.996	1.0	1.4	1.09

Table 3

Degradation results

S.NO	Factors	Drug recovered IN %				Drug degraded IN %
S.NO	Factors	CFE	PCM	LEV	PHE	CFE	PCM	LEV	PHE
1	NaOH (0.1 M NaOH) in 1 h	99.4	92.21	98.7	93.4	0.6	7.79	1.3	6.6
2	HCl (0.1 M HCl) in 1 h	98.1	88.23	94.67	86.43	1.9	11.77	5.33	13.57
3	H₂O₂ (3% v/v) in 1 h	99.2	98.6	84.1	93.2	0.8	1.4	15.9	6.8
4	Photolytic (in UV for 8 h)	98.2	98.4	98.96	93.6	1.8	1.6	1.04	6.4
5	Thermal at ambient temperature for 8 h	99.1	96.34	99.12	97.8	0.9	3.66	0.88	2.2

Table 4

Factors and responses of QbD

Std	Run	Factors		Responses
Std	Run	A: Mobile Phase A	B: Mobile Phase B	1. Retention Time	2. Tailing	3. Resolution
7	1	110	42.9289	5	2.1	12
2	2	15	45	4.4	2	12.2
12	3	10	50	4.8	2.1	12.1
4	4	15	55	4.1	1.6	11.5
8	5	10	57.0711	4.3	1.6	11.2
1	6	5	45	5.1	1.6	11.5
9	7	10	50	5.3	2	11.6
6	8	17.0711	50	4.12	2.3	12.3
13	9	10	50	5.1	2.2	12.1
11	10	10	50	5.1	2	11.9
10	11	10	50	4.3	1.71	12.1
5	12	2.92893	50	4.31	1.64	11.7
3	13	5	55	4	1.53	11.5

Table 5

ANOVA table for quadratic model fit statistics

S. No.	Factors	P-value	F-value	SD	Mean	% CV	R ²	Adjusted R ²	Predicted R ²	Adequate precision
1	Retention time	0.0389	17.41	0.5872	6.61	8.89	0.4776	0.3732	0.1109	6.1124
2	Tailing	0.0892	3.05	0.1969	1.88	10.50	0.6853	0.4606	0.3752	5.0315
3	Resolution	0.0043	6.48	0.1887	11.82	1.60	0.8223	0.6954	0.4959	8.7460

Figure 9

Qbd peaks of perturbation, contour, 3D surface, and overlay of three factors. The factors are 1. Rt, 2. tailing, and 3. resolution.

4 Discussion

4.1 Stability of the solutions

Stability of the standard drug solution of citicoline was tested at room temperature for 72 h. The percentage of assay values was calculated by comparing the standard to the test samples.

4.2 Validation parameters

Validation is the process of getting written proof that a certain process will always produce a result that meets its quality standards and requirements. Determining a drug's appropriateness for its intended application is the most essential requirement for drug validation. The guidelines stated in ICH Q14 were applied to validate the proposed method.

4.2.1 Linearity, limit of detection (LOD), and limit of quantification (LOQ)

For simultaneous estimation of quaternary compounds, the linearity was calculated. The concentrations of CFE were 2–12 μg·ml⁻¹, PAR 5–30 μg·ml⁻¹, LEV 1–6 μg·ml⁻¹, and PHE 2–12 μg·ml⁻¹. Ethanol was used to prepare each solution. Every solution was analysed three times. The calibration graph was plotted using the Y-axis as peak area and the X-axis as concentration. The correlation coefficient R ² was found to be 0.999, 0.998, 0.998, and 0.999. These values show that the developed method was precise and accurate. The regression equations of CFE, PCM, PHE, and LEV are y = 181.07x + 2625.8, y = 51.968x + 3452.6, y = 184.05x + 2430.9, and y = 213.92x + 2412.4.

4.2.2 Accuracy and precision

The accuracy was calculated for drug concentration – 80%, 100%, and 120% – was analysed thrice with the formulation to calculate the percentage of the recovery. Each and every concentration produced good yields. The % RSD values were obtained in an accuracy of less than 2.

As per the follow-up of ICH guidelines Q2(R2) for the validation, system precision was followed. System precision means the precision of a determining system, which is related to reproducibility and repeatability. It is the degree to which repeated measurements under the same conditions obtain the same results. Repeating the concentration six times, the interday and intraday precision were calculated, and the obtained value of % RSD was less than 2. The obtained precision values for interday and intraday are given in Table 6.

Table 6

Validation parameters

S. No.	Parameters	CFE	PCM	PHE	LEV
1	Concentration (µg·ml⁻¹)	2–12	5–30	2–12	1–6
2	Regression equation	y = 181.07x + 2625.8	y = 51.968x + 3452.6	y = 184.05x + 2430.9	y = 213.92x + 2412.4
3	Correlation coefficient (R ²)	0.999	0.998	0.998	0.999
4	LOD (µg·ml⁻¹)	0.16	0.7	0.66	0.13
5	LOQ (µg·ml⁻¹)	0.48	2.1	1.98	0.39
6	Accuracy (in %)	97.2–98.6	97.4–98.5	96.8–98.1	96.1–97.8
7	Interday (in % RSD)	0.68	0.88	0.72	0.65
8	Intraday (in % RSD)	0.57	0.82	0.66	0.61

4.3 Benefits of HPLC in solvent reduction make the method greener

For the green method of analysis, the HPLC is a suitable instrument for method development and validation. Because of cross-linked columns, it speeds up elution due to the small particle size. Higher column temperatures make solvents less viscous and improve their polar characteristics, which reduces the need for organic modifiers. High pressure in HPLC reduces waste output.

4.4 Ecological analysis

The environmentally conscious method follows the 12 GAC principles with specific guidelines. Every concept has a specific function in aiding in the method development. This technological primary benefit is that it is not harmful to the environment or public health. By diluting the sample, it can prevent the reduction of waste during sample preparation. Using HPLC has advantages because it uses less energy than other instruments. The reduction of occupational hazards is the priority when converting to eco-friendly solvents; it is beneficial to analysts’ well-being. Derivatization is entirely avoided, and environmentally friendly reagents are used.

4.5 Evaluation of green techniques

Thoroughly evaluating a proposed approach for environmental sustainability is crucial. There are numerous evaluation techniques for evaluating the Green Method of Analysis. Each technique has limitations specific to Green Architecture Certification (GAC). In regard to GAC, a number of green evaluation tools can be employed.

4.6 Green analytical procedure index (GAPI)

GAPI includes all components of an analytical technique, from collecting samples, transportation, conservation, and preservation through sample preparation and conclusion of analysis, including pre-analytical procedures. Use the NFPA list to check GAPI for toxic solvents. Red, yellow, and green are the colour indication used in the pictogram. Red should indicate the most dangerous material, yellow moderately poisonous, and green least harmful. The GAPI follows the principles of analytical eco-scale (AES) [34] and eco-scale [35]. This is a qualitative technique. Because colour representation determines outcome, combining the standard GAPI and E-factor generates the complex GAPI. The GAPI concerned with chemical usage and yield is denoted by the E-factor. The examination is primarily focused on building analytical tools and assessing their greenness. Because ethanol is employed as a solvent, an environmentally favourable solvent. GAPI offers a green pictogram as a result. It shows the method is environmentally acceptable.

4.7 AES

The eco-scale is mainly focused on factors that influence sustainability, i.e. reaction process, preservation, technical process, and energy consumption. Penalty points are assigned to factors in the technique when an analytical procedure departs from the intended parameters of environmentally friendly analysis. It is a semi-quantitative tool for finding the punishment points (PP) for the method. Within the analytical process, this methodology compares a number of measurements and procedures. This tool generates numerical values with an eco-scale score of “100.” For the suggested approach, the AES value is 91.

4.8 Analytical greenness (AGREE)

AGREE is a tool that is often used to measure environmental sustainability. This is a software-based tool that consists of 12 green analytical principles. Each principal gets a number between 0 and 1. A number that is closer to 1 shows the method is greener. Many factors are taken into consideration including reagent toxicity and amount, waste generation, energy consumption, number of process stages, and automation and miniaturization considerations. The execution of greenness criteria necessitates the use of specialized technologies. The analytical reliability is a thorough, flexible, and clear evaluation approach. It is designed to deliver a simple and useful outcome.

4.9 Analytical method greenness score (AMGS)

AMGS, a spreadsheet-based simulator, was created specifically for chromatographic processes. Environmental assessment (SHE), which uses a geometric mean to determine solvent safety, and analytical mass volume intensity (AMVI), which analyses solvent waste and cumulative energy demand (CED), with a primary focus on well-being and safety, comprise the majority of the environmental assessment tool. At the moment, the active spreadsheet evaluates the method’s information in order to reduce the output value and deliver the most ecologically friendly solutions. The AMGS is divided into three categories: instrument energy, solvent energy, and solvent environmental health and safety. To enhance environmental sustainability, the method’s composite score, which is calculated by summing the three scores, should be as low as possible. The proposed method had an overall AMGS score, suggesting that it has positive environmental benefits. This indicates that the method is greener. The data were computed using the ACS Green Institute. The obtained AMGS score was 1173.58 (Figure 10).

Figure 10

AMGS calculator.

4.10 Carbon footprint analysis

The carbon footprint analysis is an important concept in determining the rise in greenhouse gas emissions in the Earth’s atmosphere as a result of the burning of energy sources such as fossil fuels. Determining the total carbon footprint of a process is critical for determining the total quantity of carbon dioxide emissions into the environment. Analysis of CFE, PCM, LEV, and PHE using RP-HPLC is examined in this article. The equipment uses considerably fewer watts of energy, with the HPLC consuming around 1.5 kW h. Another instrument, used for the method development and validation, emits more carbon dioxide. It requires more energy. In HPLC, energy use reduces carbon dioxide emissions significantly, resulting in low environmental implications. This confirmed that the developed method is more environmentally friendly. This indicates the method is greener.

To evaluate and acquire the best ecologically friendly method, the aforementioned assessment tools were employed to demonstrate the environmental friendliness of the provided methodology for the study of CFE, PCM, LEV, and PHE. Although every greenness assessment tool adopts a different approach to analysing the greenness profile, the final results aid in visualizing and distinguishing the approach that has the least negative impact on the environment. Evaluation techniques were used in this study to examine the environmental friendliness of the methodology report.

4.11 Comparison of proposed method vs previously available method with green evaluation tools

Green chemistry is often referred to as sustainable chemistry. It reduces or eliminates the presence of hazardous chemicals. The method has been developed and validated in accordance with the 12 GAC principles. The developed technique has been evaluated by employing Green Assessment Tools. The proposed method for this combination is compared to the previously available method [36] (Table 7). The proposed method demonstrates a favourable effect and a high score achieved by the tools, indicating that the method is green (Table 8).

Table 7

Statistical comparisons of proposed and previously reported method

Parameters	CFE		PCM		PHE		LEV
Parameters	Proposed method	Reported method	Proposed method	Reported method	Proposed method	Reported method	Proposed method	Reported method
Mean	2967.2	—	3699.9	—	2767.2	—	2845.5	—
Variance	0.992	—	0.983	—	0.875	—	0.995	—
M−H	0	—	0	—	0	—	0	—
Df	3	—	4	—	3	—	3	—
F-test	0.8 (3.1)^a	1.0001 (6.38)^a	0.82 (3.1)^a	1.002 (6.38)^a	0.78 (3.1)^a	1.001 (6.38)^a	0.79 (3.1)^a	1.001 (6.38)^a
T-test	0.4 (1.2)^a	0.5 (2.13)^a	0.42 (1.2)^a	0.50 (2.13)^a	0.4 (1.2)^a	0.49 (2.13)^a	0.41 (1.2)^a	0.50 (2.13)^a

^Adenotes the theoretical value of F-test and T-test at 95% confidence level. • Df means degrees of freedom. • M−H means mean difference.

Table 8

Comparison of the suggested HPLC method versus the previously published HPLC method in terms of sustainability assessment

S. No	Reference	Conditions	AES
1	Anil p. Dewani, srdhanjali patra	HPLC: methanol:10 mM phosphate buffer (pH 3)	Reagent = 15
			Instrument = 1
			Occupational hazard = 0
		In gradient method	Occupational hazard = 0
			Waste = 0
			Total = 100-16
			AES = 84
2	Proposed method	HPLC: ethanol:10 mM phosphate buffer (pH 3)	Reagent = 8
			Instrument = 1
			Occupational hazard = 0
		In gradient method	Occupational hazard = 0
			Waste = 0
			Total = 100-5
			AES = 91

5 Conclusion

This was the first innovative approach for this drug combination, combining AQbD and GAC. A new green method of analysis has been enhanced and validated in order that it may be basically employed in QC laboratories in nations that are less developed. The analytical method was developed by reducing the column diameter, thereby lowering the analysis time and reducing solvent consumption. For statistical optimization, the CCD was adapted; this is the robustness of the study. The effective application of ethanol, a biodegradable and non-toxic solvent, was a specific highlight of our research. CFE, PCM, LEV, and PHE might all be quantified through this method.

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Acknowledgement

The authors thank SRM College of Pharmacy for constant support.

Funding information: Authors state no funding involved.
Author contributions: Vineetha Rosireddy: writing – original draft, writing – review and editing, methodology, software, formal analysis, data curation, and validation. Manikandan Krishnan: writing – original draft, conceptualization, software, methodology, formal analysis, visualization, validation, and project administration.
Conflict of interest: Authors state no conflict of interest.
Data availability statement: The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Received: 2024-01-03

Accepted: 2024-04-01

Published Online: 2024-04-30

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

https://doi.org/10.1515/gps-2024-0003

Keywords for this article

RP-HPLC; central composite design; GAPI; AES; and carbon footprint analysis

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