RP-HPLC Method Development and Validation for Simultaneous Estimation of Metformin, Dapagliflozin and Glimepiride in fixed dose Combinations

Sudhansu Ranjan Swain¹, Mandeep Kumar Gupta¹, Bhuvnesh Kumar Singh¹,

Anshika Bhatnagar¹*, Surya Nath Pandey²

¹Moradabad Educational Trust Group of Institutions Faculty of Pharmacy,

Moradabad-244001, Uttar Pradesh, India.

²Department of Pharmacology, Teerthanker Mahaveer College of Pharmacy,

Teerthanker Mahaveer University, Moradabad 244001, Uttar Pradesh, India.

*Corresponding Author E-mail: anshikabhatnagar1299@gmail.com

ABSTRACT:

For the concurrent assessment of Metformin (MET), Dapagliflozin (DAPA) and Glimepiride (GLIME) in fixed-dose combinations, a straightforward, exact, accurate, and unique method has been established. We utilized RP-HPLC, a sort of high-performance liquid chromatography, to accomplish this estimate. The method employs a mobile phase comprising 350 ml of buffer (pH 3, adjusted through ortho-phosphoric acid) and 650 ml of acetonitrile. A solution of 100 ml of water, 900 ml of methanol and 2 ml with triethylamine (TEA) is used for dissolution of standard compounds. A chromatographic column (250 × 4.6 mm) is used to separate the components of the mixture. The detection wavelength for MET, DAPA and GLIME is set at 248 nm. The mobile phase's discharge rate remains unchanged at 1 ml/min, with an amount of 20 μl for injection. The chromatographic analysis period is around 15 minutes, completing MET resolution (Retention time (RT) = 4.365 min), DAPA resolution (RT = 2.187 minutes) and GLIME resolution (RT = 7.269 min). The presented approach was validated using ICH (International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use) recommendations, evaluating variables like robustness, linearity, precision, limit of detection (LOD), accuracy, limit of quantification (LOQ), linearity, specificity as well as system adaptability. Under optimized chromatographic conditions, MET demonstrated linearity at concentrations of 1-120 μg ml^-1. DAPA demonstrated linearity at concentrations of 0.5-2.5 μg ml^-1. GLIME demonstrated linearity at concentrations of 0.2-1.2 μg ml^-1. The values for MET, DAPA and GLIME LOD and LOQ had been achieved at concentrations of (5.26 μg ml^-1 and 15.94 μg ml^-1), (0.06 μg ml^-1 and 0.17 μg ml^-1) and (0.02 μg ml^-1 and 0.08 μg ml^-1). The analytical method is confirmed to be appropriate for its intended purpose and to meet the criteria given in ICH guideline Q2 (R2) according to the validation results.

KEYWORDS: RP-HPLC, Metformin, Dapagliflozin, Glimepiride, Method development, Method validation.

INTRODUCTION:

Diabetes mellitus is an endocrine condition marked by consistently high blood sugar levels. The medical condition results from either insufficient insulin synthesis by the pancreas or the body's cells growing insensitive to insulin's effects¹. The triple-dose combination of MET, DAPA and GLIME is included in the CDSCO-approved list of fixed-dose combinations (FDCs)². An RP-HPLC method has been created and proven to work for testing this mix. DAPA, the first SGLT2 inhibitor approved for managing type 2 diabetes mellitus (T2DM)^3,4, enhances Adults' glycaemic regulation in conjunction with nutrition and activity. It works by preventing the proximal tubule of the nephron from reabsorbing glucose, leading to increased glucose excretion through urine (glycosuria)^5,6. GLIME, a second-generation sulfonylurea (SU), is widely used to manage T2DM by improving glycaemic control. Its primary action is to stimulate insulin release from pancreatic β-cells, provided residual β-cell function is present⁷. Additionally, sulfonylureas are thought to enhance peripheral glucose uptake mediated by insulin, offering extra-pancreatic benefits⁸. MET, a biguanide antihyperglycemic agent, serves as the first-line pharmacotherapy for T2DM management. Unlike many antidiabetic drugs, MET lowers blood glucose levels without causing hypoglycaemia, solidifying its classification as an antihyperglycemic agent^9,10. This fixed-dose combination offers a comprehensive therapeutic approach by combining complementary mechanisms to effectively manage T2DM^11,12. In Figure 1 we can see the three medications structures^13–15.

Figure 1: Chemical Structure (1) Metformin (2) Dapagliflozin (3) Glimepiride.

MATERIALS AND METHODS:

Analytes and Reagents:

Reference standards of MET, DAPA and GLIME was obtained as gift samples from the SYNOKEM pharmaceuticals Ltd used was OXRAMET G XR tablets containing (Label claim: 500 mg of MET, 10 mg of DAPA and 1 mg of GLIME) was procured from market. ACN, methanol (Merck). and water used were of HPLC grade.

Chromatographic conditions:^16–23

Chromatographic column  : Vertex C18 column

Column dimensions            : 250 X 4.6 mm

Run time                            :15 min.

Mobile phase                      :Acetonitrile: buffer

Injection volume                :  20 μl

Column temperature          :Ambient temperature

Flow rate                              :1.0 ml/min.

Diluent                                   :Methanol: Water: TEA (90: 10: 02)

Detection wavelength       :248 nm

Preparation of buffer:

Put 6.8 gm of KH₂PO₄ into a 1000 ml volumetric flask, dissolve it, add enough distilled water to reach 1000 ml, and use OPA to get the pH down to 3^{16,17,24–29}.

Preparation of mobile phase:

Mix 350 ml of buffer and 650 ml of acetonitrile thoroughly, using 0.45μm filter paper to filter mobile phase through filtration assembly and degas mobile phase in ultrasonic water bath^{16,18,27,30–32}.

Selection of Wavelength:

Put 10 mg of MET in a 10 ml volumetric flask, add adequate diluent and sonicate for 15 minutes. Use the diluent to get the volume to about 10 ml. Pour 1 ml of this solution into a second 10 ml volumetric flask and dilute it to 10 ml. For DAPA and GLIME, follow the same steps.

Mix equal amounts of each prepared solution thoroughly. Measure the absorbance of the mixture in the range of 200–300 nm using a UV             spectrophotometer^{17,18,25,26,30,31,33–38}. The maximum absorbance was observed at 248 nm.

Preparation of standard solutions:

MET, DAPA and GLIME stock solutions were made separately by dissolving precisely weighed 500 mg, 10 mg, and 1 mg of each medication in 100 ml of diluent to create a 5 mg ml^-1, 0.1 mg ml^-1, 0.01 mg ml^-1 stock solution of each drug²⁶. Take 1 ml of each stock solution dissolved with 10 ml diluent to create working standard solution of 500 mg ml^-1, 10 mg ml^-1 and 1 mg ml^-1.^32,39 further take 1 ml of each solution dissolved with 5 ml diluent to create working standard solution of 100 µg ml^-1, 2 µg ml^-1 and 0.2 µg ml^-1.³² Filter standard solution with 0.45µm filter paper.

Preparation of sample solution:

Take 20 tablets and crush it to convert into powdered form²⁷. Weigh 500 mg of powdered drug dissolve into 30 ml of diluent, sonicate for 15 min. subsequently use diluent to volume up to 100 ml. Dissolve 1 ml solution in 10 ml diluent. Take another 5 ml of diluent and dissolve 1 ml of solution. Use 0.45µm filter paper to filter the sample solution²⁷.

Method Optimization:

This study intended to refine and validate a method for the simultaneous detection of MET, DAPA and GLIME by systematically adjusting various parameters. These included modifications to the pH, wavelength, and flow rate as well as mobile phase^’s composition (ACN: Buffer). The goals were to achieve well-defined peaks, maximize the number of theoretical plates, minimize the tailing factor, and reduce separation times. The mobile phase consisted of a buffer and acetonitrile mixture in a 35:65 and the discharge rate is 1 ml/min The eluate was analysed using a UV detector set to 248 nm in wavelength. Example chromatograms, shown in Figure 2, included profiles for a placebo, individual components (MET, DAPA and GLIME) and their combination.

Figure 2: System suitability Chromatogram of Metformin, Dapagliflozin and Glimepiride.

RESULTS AND DISCUSSION:

Method development:

The primary goal of this research is to develop and validate a RP-HPLC method for the concurrent analysis of MET, DAPA and GLIME in active pharmaceutical ingredients (API) and various formulations. The method is designed to comply with ICH standards while being simple, precise, reliable, efficient, and effective. To achieve this, several parameters were adjusted, including pH levels, elution procedures, flow rates, mobile phase composition, and the selection of suitable columns, as part of a refined and validated methodology. The optimization process focuses on producing distinct peaks, maximizing theoretical plate counts, minimizing tailing factors, and reducing analysis time to enhance the overall efficiency and effectiveness of the analytical procedure⁴⁰.

Method validation:

The developed method for simultaneous estimation of MET, DAPA and GLIME has been validated in accordance with ICH guidelines⁴¹.

Accuracy:

Multiple-level recovery experiments, which employ standard adds at three distinct levels, are used to assess the method's accuracy. Sample solution of MET, DAPA and GLIME are prepared, the solution is supplemented with 50%, 100%, and 150% of the standard solution and the % recovery is determined⁴². Table 1 displays the results.

Table 1: Accuracy results for Metformin, Dapagliflozin and Glimepiride.

Name of the drug	% Level Spiking	Drug quantity (Std.) µg	Total Drug Conc. (µg)	Mean ± SD of total found (µg)	%RSD	% Recovery
Metformin	50%	50	150	150.09 ± 0.82	0.55	100.06
	100%	100	200	200.98 ± 0.91	0.45	100.49
	150%	150	250	249.58 ± 0.85	0.340	99.83
Dapagliflozin	50%	1	3	3.01 ± 0.03	0.930	100.22
	100%	2	4	3.99 ± 0.02	0.530	99.79
	150%	3	5	4.99 ± 0.05	0.950	99.73
Glimepiride	50%	0.1	0.3	0.29 ± 0.01	1.740	98.89
	100%	0.2	0.4	0.40 ± 0.01	1.280	99.12
	150%	0.3	0.5	0.50 ± 0.01	1.500	100.33

Table 2: System precision and Method precision studies of Metformin, Dapagliflozin and Glimepiride.

	System Precision			Method precision
Injection number	Peak areas			% Assay
	MET	DAPA	GLIME	MET	DAPA	GLIME
1	2101879	42382	4383	98.8	99.38	98.85
2	2110980	42629	4226	100.27	98.61	99.63
3	2013393	41176	4372	101.34	101.54	101.47
4	2103041	42022	4297	98.34	100.42	100.92
5	2100083	41295	4233	99.54	99.56	98.35
6	2110302	41764	4387	100.98	99.96	101.43
Mean	2089946	41878	4316	99.88	99.91	100.11
SD (±)	37772	580.42	74.85	1.20	1.00	1.35
RSD (%)	1.81	1.39	1.73	1.197	1.002	1.352
Reference value	The maximum allowable RSD should not exceed 2

Precision:

The precision was effectively achieved within the limit, as the total percent RSD of the system method precision for the precision research was less than 2. The results are summarized in Table 2.

Intermediate Precision (Ruggedness):

The system method precision in the precision study achieved an overall RSD < 2%, indicating accurate results well within the acceptable limit.

Linearity and range:

Appropriate aliquots of standard MET (100 μg ml^-1), DAPA (2 μg ml^-1) and GLIME (0.2 μg ml^-1), Different 10 ml volumetric flasks are used to make the solutions. To obtain the final concentration, the resultant solution is diluted using diluent until it reaches the appropriate level of 1-100 μg ml^-1, 0.5-2.5 μg ml^-1, and 0.2-1.2 μg ml^-1 respectively.

y=20778x-175.45, R²=0.9995, y=20807x-168.23, R²=0.9999 and y=21610x+32.446, R² = 0.9999 respectively, are the linear regression equations for MET, DAPA and GLIME.

Robustness by design of experiments:

Robustness relates to a method's ability to stay untouched by slight but deliberate changes in its circumstances and presents evidence that the approach is trustworthy. If a method remains unaffected by slight variations in operating conditions, it is considered robust. experimental circumstances are purposefully changed at four different levels to assess the robustness of this approach. Retention time, talling factor and % recovery is evaluated. The factors include variations in the rate of flow, pH, wavelength, and mobile phase to examine the effects⁴³. %RSD for all parameters should not more than 2%. The results of robustness studies are summarized in Table 3.

Table 3: Robustness studies of Metformin, Dapagliflozin and Glimepiride.

Condition		Metformin			Dapagliflozin			Glimepiride
		RT	TF	%R	RT	TF	%R	RT	TF	%R
Change in Flow rate	Normal Condition (1.0 ml per minute)	4.199	0.97	98.81	2.165	0.97	100.73	7.138	1.17	100.18
	Flow rate (0.8 ml per minute)	4.102	0.98	100.34	2.199	0.98	98.29	7.371	1.14	98.95
	Flow rate (1.2 ml per minute)	4.267	0.99	101.47	2.111	0.99	99.82	7.129	1.15	101.32
	Mean	4.19	0.98	100.21	2.16	0.98	99.61	7.21	1.15	100.15
	Standard deviation	0.08	0.01	1.34	0.04	0.01	1.23	0.14	0.02	1.19
	RSD%	1.98	1.02	1.33	2.06	1.02	1.24	1.90	1.32	1.18
Change in pH	Normal Condition (3.0)	3.987	1.05	98.92	2.155	1.06	98.28	7.268	1.05	100.91
	pH (4.0)	4.012	1.08	101.46	2.231	1.09	99.96	7.349	1.08	98.81
	pH (5.0)	3.909	1.06	100.37	2.225	1.06	101.49	7.129	1.06	101.14
	Mean	3.97	1.06	100.25	2.20	1.07	99.91	7.25	1.06	100.29
	Standard deviation	0.05	0.02	1.27	0.04	0.02	1.61	0.11	0.02	1.28
	RSD%	1.35	1.44	1.27	1.92	1.62	1.61	1.53	1.44	1.28
Change in Wave Length	Normal: Wave Length 248nm	4.036	1.14	100.39	2.271	1.15	101.12	7.098	1.14	100.95
	Wave Length 242 nm	4.098	1.16	99.81	2.349	1.16	98.58	7.115	1.15	99.11
	Wave Length 254 nm	4.161	1.12	101.85	2.287	1.12	100.78	7.261	1.12	101.24
	Mean	4.10	1.14	100.68	2.30	1.14	100.16	7.16	1.14	100.43
	Standard deviation	0.06	0.02	1.05	0.04	0.02	1.38	0.09	0.02	1.16
	RSD%	1.53	1.75	1.04	1.79	1.82	1.38	1.25	1.34	1.15
Variation in organic composition within the mobile phase	Normal Condition (ACN: Buffer) (65:35)	3.99	1.03	99.71	2.25	1.04	100.49	7.10	1.04	100.58
	(ACN: Buffer) (55:45)	4.12	1.06	100.91	2.34	1.06	99.32	7.37	1.06	101.92
	(ACN: Buffer) (75:25)	4.09	1.04	98.65	2.32	1.08	98.12	7.20	1.03	98.78
	Mean	4.07	1.04	99.76	2.30	1.06	99.31	7.22	1.04	100.43
	Standard deviation	0.07	0.02	1.13	0.05	0.02	1.19	0.13	0.02	1.58
	RSD%	1.77	1.46	1.13	2.03	1.89	1.19	1.85	1.46	1.57

Detection and quantitation limits:

The LOD is calculated through the analysis of samples containing known concentrations of the analyte, finding the lowest level at which they can be consistently recognized. The LOQ is found by analysing substances that have known amounts of the analyte. and by finding the minimal concentration necessary for precise measurement of the analyte.

The results of LOD and LOQ are shown in Table 4. The LOD and LOQ chromatograms are shown in Figure 3.

Table 4: LOD and LOQ studies of Metformin, Dapagliflozin and Glimepiride.

S. no.	Name of drugs	LOD (μg ml^-1)	LOQ (μg ml^-1)
01	Metformin	5.26	15.94
02	Dapagliflozin	0.06	0.17
03	Glimepiride	0.02	0.08

(A)

(B)

Figure 3: LOD (A) and LOQ (B) chromatogram of Metformin, Dapagliflozin and Glimepiride.

Solution Stability:

The MET, DAPA and GLIME containing solutions held up well for 24 hours at 25°C and for a week in a refrigerator between 2 and 8°C. Analysing the percentage difference in stability results revealed no degradation in the peak areas of MET, DAPA and GLIME under these specified conditions.

CONCLUSION:

We conducted an in-depth investigation to optimize chromatographic conditions for achieving the best separation and peak shapes for the compounds MET, DAPA and GLIME. Our proposed RP-HPLC method has been thoroughly validated, demonstrating exceptional accuracy and precision. It meets the stringent criteria for LOQ and LOD. The newly designed RP-HPLC method differentiates itself by its simplicity, rapidity, precision, and reliability, and sensitivity, making it an effective tool for systematic examination of MET, DAPA and GLIME in their pharmaceutical compositions. A key advantage of our method is its versatility, enabling its use in both routine and unfamiliar sample analyses across various sectors of the pharmaceutical industry. This approach is vital in maintaining product quality standards by allowing quick assessments of MET, DAPA and GLIME levels in pharmaceutical formulations. Implementing this method in pharmaceutical companies ensures thorough quality assurance, safeguarding the authenticity and efficacy of products for consumers. Future research could explore adapting this RP-HPLC method for different environmental conditions to improve its robustness and versatility. Future studies might also investigate its potential for real-time monitoring of pharmaceutical manufacturing processes, potentially leading to more efficient production and enhanced quality control.

ACKNOWLEDGEMENT:

The author is thankful to Moradabad Educational Trust, Group of Institutions, Faculty of Pharmacy, Moradabad, India for providing the necessary facilities to accomplish the work.

FUNDING:

No funding was received to assist with the preparation of this manuscript.

CONFLICT OF INTEREST:

All authors agree with the content of the manuscript and do not have any competing interests.

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Received on 05.05.2025      Revised on 04.10.2025

Accepted on 10.12.2025 Published on 20.05.2026

Available online from May 25, 2026

Research J. Pharmacy and Technology. 2026;19(5):2267-2272.

DOI: 10.52711/0974-360X.2026.00326

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