QbD Stressed Development and Validation of Stability-Indicating RP- HPLC Method for the Simultaneous Estimation of Linagliptin and Metformin HCl in Pharmaceutical Dosage Form
Khushbu Patel1,2*, Ujashkumar A. Shah3, Hirak V. Joshi3, Jayvadan K. Patel3, Chhaganbhai N. Patel1
1Department of Quality Assurance and Pharmaceutical Chemistry, Shri Sarvajanik Pharmacy College,
Near Arvind Bag, Mahesana - 384001, Gujarat, India.
2Research Scholar, Sankalchand Patel University, S. K. Campus, Kamana Cross Road,
Visnagar - 384315, Gujarat, India.
3Department of Quality Assurance and Pharmaceutical Chemistry, Nootan Pharmacy College,
Sankalchand Patel University, S. K. Campus, Kamana Cross Road, Visnagar-384315, Gujarat, India.
*Corresponding Author E-mail: khushbusspc@gmail.com
ABSTRACT:
A new simple stability indicating reverse phase liquid chromatography method was developed by employing Quality by Design (QbD) approach for the simultaneous determination of Linagliptin and Metformin HCl. Within QbD paradigm, the present study aimed to establish the optimization of the RP-HPLC (Reverse phase high performance liquid chromatography) by means of design of experiments and response surface mythology like, Centre composite design (CCD) in order to achieve a good separation and resolution. The developed method is effective to separate Linagliptin and Metformin HCl with a good chromatographic resolution of 6.4. Chromatographic separation was acquired with column Water C18 (250mm x 4.5mm x 5μm) at flow rate 1.0 ml/min with the mobile phase consists of acetonitrile and methanol (75:25 % v/v). The detection of Linagliptin and Metformin HCl was carried out at 245nm. The proposed method was validated according to ICH guidelines. The method was linear in range of 0.5-3μg/ml and 100-600μg/ml of Linagliptin and Metformin HCl respectively and recovery were in the range of 98% to 102%. The degradation product found in stress patterns were well separated among the drug compounds. The method was validated to be specific, rapid, precise and robust for routine analysis in its pharmaceutical dosage form.
KEYWORDS:. Quality by Design, Design of Experiments, Linagliptin, Metformin HCl, RP-HPLC, Stability indicating, Validation.
INTRODUCTION:
Linagliptin is used with diet, together with exercise and some time with other oral hypoglycemic agents. Linagliptin used for lowering blood sugar level in type – II diabetes, not in type-I diabetes.1 Metformin HCl is used as an oral antidiabetic agent in type – II diabetes. It helps to control blood sugar by decreasing the amount of glucose absorption in intestine and decrease the amount of glucose made by liver.2
Linagliptin (LINA), a Xanthine derivative is chemically described as 8-[(3R)-3-Aminopiperidin-1-yl]-7-(but-2-yn-1-yl)-3-methyl-1-[(4-methylquinazolin-2-yl) methyl]-3,7-dihydro-1H-purine-2,6-dione and molecular formula is C25H28N8 O2. (Fig.1a)3 Metformin Hydrochloride (MET) is chemically described as 1-carbamimidamido-N, N-dimethylmethanimidamide hydrochloride and molecular formula is C4H12ClN5 .(Fig.1b) 4 QbD is a tool that addresses the quality projected from the planning stage to throughout product life cycle.5 QbD delivers a better understanding of method capabilities, limitations and ensure a superior chance of successful downstream method validation and transfer. The understanding of method with predefined objectives and optimization is based on risk control.6 The ICH Q1A (R2)7 guideline entitled “Stability testing of new drug substances and products” requires stress testing to be carried out to elucidate the inherent stability characteristics of the active substance.
Fig. 1: Chemical structure of Linagliptin (a) and Metformin HCl (b)
Literature reveals various analytical methods have been reported such as, Ultraviolet Spectrophotometry,8,9 HPLC,10-17 HPTLC,18 LC-MS19 and stability indicating method20-25 for simultaneous estimation of Linagliptin and Metformin HCl26-27. In published literatures, none of these methods were used for the application of analytical Quality by design. The purpose of study was to optimize the HPLC method with quality by design (QbD) approach. Hence, it was thought to develop and validate a specific, linear and precise stability indicating RP-HPLC method for simultaneous estimation of Linagliptin and Metformin HCl in pharmaceutical dosage form by using QbD approach.
MATERIAL AND METHOD:
Linagliptin and Metformin HCl were obtained as gift samples from Shiva Health care, Mahesana, India, and fixed dosed combination of Linagliptin and Metformin HCl tablet (Trajenta Duo 2.5mg/500mg) were purchased from local pharmacy. HPLC-grade methanol, water and acetonitrile were purchased from Merck Life Science Private Limited, Mumbai, India. All the other chemicals and reagents used were of AR grade and purchased from Avantor Performance Material India Limited, Thane, India. The analysis was carried out on shimadzu HPLC (LC 2010 CHT) with photo diode array detector and the output signal was monitored and processed using LC solution software for chromatographic separation. Data acquisition was carried out using trial version of Design Expert version 12.0.
The separation of Linagliptin and Metformin HCl compounds were achieved using acetonitrile: methanol (75:25 % v/v) solutions as a mobile phase at a flow rate 1.0ml/min with isocratic elution method. Detection wavelength was selected for the estimation of the two drugs at 245nm with injection volume of 20μl. The run time optimized was found to be 10 min.
Preparation of Standard Solution:
Accurately weighed 2.5mg of Linagliptin and 500mg of Metformin HCl and transferred it into 100ml volumetric flask. 50ml of methanol was added into flask and sonicated for 5 min then made up to the mark with methanol. Working concentration was made with methanol to get a concentration of 0.5-3μg/ml of Linagliptin and 100-600μg/ml of Metformin HCl.
Preparation of Sample Solution:
Twenty tablets of marketed formulation, Trajenta duo 2.5mg/500mg was taken and weight of average content was determined. Weight equivalent to 500mg was transferred to 100ml volumetric flask and dissolved in methanol. Solution was sonicated and filtered through whatman filter paper no.42. Further diluted to get a concentration of 1μg/ml and 200μg/ml Linagliptin and Metformin HCl respectively.
Method Optimization:
The chromatographic optimization is the maximum selectivity with minimum analysis time. All obtained results were screened in design of experiments and main parameters were selected for optimization phase. The chosen variables with initial desired analysis conditions which is meet to the critical quality attributes specification. The independent variable was selected as a percentage of the organic phase (A) and flow rate (B), while the resolution of MET (Rs), retention time of LINA (tR LINA) and retention time of MET (tR MET) as a response. (Table 1)
Table 1: Variable selected in Centre Composite Design
|
Factors |
Lower level (-) |
Intermediate level (0) |
Higher level (+) |
|
Mobile Phase composition (ml) |
70:30 |
75:25 |
80:20 |
|
Flow rate (ml/min) |
0.8 |
1.0 |
1.2 |
The quadratic model was proposed for method optimization consisted of a central composite design (CCD) with 11 experiments (8 runs and 5 Centre points). The centre points of experiments were performed with 75% of acetonitrile and 1.0 ml/min flow rate. For an experimental design with two factors, including linear, quadratic and cross terms, the model can be expressed as Y= β0 + β1 X1 + β2 X2 + β12 X1 X2 + β11 X22 + β22 X22 where, Y is the response to be modelled, β0 is the coefficient constant, β1 and β2 are linear coefficients,
Table 2: Design of Experiments for the optimized chromatographic parameters
|
Standard Experiment No. |
Run |
Factor A % organic modifier (ml) |
Factor B flow rate (ml/min) |
Resolution |
Retention time for LINA (min) |
Retention time for MET (min) |
|
3 |
1 |
70 |
1.2 |
4.983 |
2.847 |
4.416 |
|
9 |
2 |
75 |
1 |
6.193 |
3.492 |
5.371 |
|
4 |
3 |
80 |
1.2 |
6.283 |
3.482 |
5.892 |
|
11 |
4 |
75 |
1 |
6.238 |
3.589 |
5.374 |
|
2 |
5 |
80 |
0.8 |
7.789 |
4.624 |
7.989 |
|
1 |
6 |
70 |
0.8 |
4.266 |
4.425 |
5.482 |
|
8 |
7 |
75 |
1.28 |
5.173 |
2.932 |
4.518 |
|
10 |
8 |
75 |
1 |
6.261 |
3.482 |
5.624 |
|
5 |
9 |
67.9 |
1 |
4.503 |
3.526 |
4.521 |
|
7 |
10 |
75 |
0.72 |
5.821 |
4.825 |
6.893 |
|
6 |
11 |
82.1 |
1 |
7.825 |
4.187 |
7.514 |
β12 is interaction coefficient between two factors, β11 and β22 are quadratic coefficients computed from the observed experiments value of Y from experimental runs and A and B are coded the levels of independent variables high (+), low (-) and centre point (0). The combination range of two factors used to prepare the 11 analytical trials and the respective observed responses are given in Table 2.
Method Validation:
Developed method was validated according to International Council for Harmonization Q2 (R1) guidelines.28
Linearity and Range:
Five standard LINA and MET solutions ranging between 0.5 – 3 μg/ml and 100 – 600 μg/ml were prepared. Each experiment was performed in triplicate and peak area was obtained from chromatograms. The graph was plotted against concentration verses peak area of LINA and MET respectively (Fig.2a, 2b).
Fig. 2 Calibration curve for Linagliptin (a) Metformin HCl (b)
Accuracy:
Accuracy is the closeness of the test results obtained by the method to the true value. Accuracy is performed at three levels 80%, 100% and 120%. The known amounts of working standard solutions of LINA (0.8, 1, 1.2 μg/ml) and MET (160, 200, 240μg/ml) were added to 1 ml sample solution of LINA (1μg/ml) and MET (200 μg/ml) in 10ml of volumetric flask and diluted up to mark with methanol. Each solution was injected triplicate and recovery was calculated from regression equation of calibration curve by measuring peak areas.
Precision:
Intraday and inter-day precision was determined by analysing of LINA and MET standard solutions in the range 1, 1.5, 2μg/ml and 200, 300, 400μg/ml, respectively. Percentage RSD for LINA and MET were calculated.
Limit of Detection (LOD) and Limit of Quantification (LOQ):
LOD and LOQ of the drugs were calculated using equations according to ICH guidelines. LOD = 3.3 σ/s and LOQ = 10 σ/s were found. Where, σ is the SD of the response and S is the slope of the calibration curve
Table 3: ANOVA data of Responses
|
Source |
Sum of Squares |
df |
Mean Square |
F-value |
p-value |
|
|
Resolution |
|
|||||
|
Model |
13.72 |
5 |
2.74 |
2153.05 |
< 0.0001 |
Significant |
|
A - % Organic modifier |
11.33 |
1 |
11.33 |
8887.86 |
< 0.0001 |
|
|
B - Flow rate |
0.3636 |
1 |
0.3636 |
285.16 |
< 0.0001 |
|
|
Retention time of LINA |
|
|||||
|
Model |
4.33 |
5 |
0.8650 |
453.17 |
< 0.0001 |
Significant |
|
A-% organic modifier |
0.3911 |
1 |
0.3911 |
204.88 |
< 0.0001 |
|
|
B-flow rate |
3.64 |
1 |
3.64 |
1907.54 |
< 0.0001 |
|
|
Retention time of MET |
|
|||||
|
Model |
14.55 |
5 |
2.91 |
212.07 |
< 0.0001 |
Significant |
|
A-% organic modifier |
8.44 |
1 |
8.44 |
614.78 |
< 0.0001 |
|
|
B-flow rate |
5.32 |
1 |
5.32 |
387.40 |
< 0.0001 |
|
Robustness:
The robustness was checked by small but deliberate changing in chromatographic conditions like organic phase (75±5ml), flow rate (1.0±0.2ml/min), injection volume (20±5μl). After each sample solution was injected and HETP, tailing factor and retention time were checked.
Analysis of marketed formulation:
An aliquot of 20μl from sample solution was injected under a chromatographic condition and peak area was measured and % assay was calculated from regression equation. Response was an average of six determinations.
Forced degradation studies:
Stress degradation studies were performed in according to ICH guidelines and studies were carried out with API. Forced degradation conditions like acidic (0.1 N HCl reflux at 60°C for 3 hr), basic (0.1 N NaOH reflux at 60°C for 3 hr), peroxide (3% v/v H2O2 at room temperature for 3 hr), thermal (at 60°C for 12 hrs), photolytic (254nm for 24hrs) were applied to the drug sample. The stressed samples were further diluted in methanol and evaluated the separation of LINA and MET from degraded products.
RESULTS AND DISCUSSION:
The Centre composite design of experiment was selected with the help of Design expert 12 trial version software and executed all the suggested experiments in a randomized manner. The designed model and obtained results with possible combination studies are shown in table 2. Two factors were found to be an effect on resolution and retention time of both drugs. The quadratic ANOVA data shown in table 3, depicting the model selected is significant (p-value<0.05) to recognize the effects of factors affecting the all 3 response.
The quadratic ANOVA data response 1 (Table 3) confirms that % organic modifier and flow rate are showing highly significant effect on resolution between LINA and MET. The quadratic ANOVA data of response 2 (Table 3) confirms that % organic modifier and flow rate are showing highly significant effect on Retention time of LINA. The quadratic ANOVA data response 3 (Table 3) confirms that % organic modifier and flow rate are showing highly significant effect on Retention time of MET. For the analysis of overall effect of all critical factors, 3D response surface plots were generated that shows simultaneous effect of critical factors on selected responses (Fig. 3). The overlay plot of all responses was shown in Fig. 3.
Fig. 3: 3D response surface plot
Effect on interaction of factor % organic phase and flow rate on Resolution (a), Retention time of LINA (b) and Retention time of MET (c) Overlay plot of optimized condition (d)
The final chromatographic conditions of the developed method were selected on the basis of retention time and the peak symmetry value using 3D-response surface plot. The optimized separation of LINA and MET were achieved on Water C18 column by using mobile phase composition 75:25% v/v (acetonitrile: methanol) at a flow rate 1.0ml/min and elutes were monitored at 245nm for the final RP-HPLC analysis (Fig 4).
Fig. 4: Chromatogram of blank (a) Standard LINA 1 μg/ml and MET 200 μg/ml (b) Test LINA 1 μg/ml and MET 200 μg/ml (c)
The optimized method was validated according to the ICH Q2 (R1) guidelines on the analytical process system suitability parameters of LINA and MET were found to be within acceptance criteria. The linear relationship between the analyte peak area and concentrations of LINA and MET were ranged from 0.5 – 3 μg/ml and 100 – 600 μg/ml respectively. The mean r2 for the standard curves of LINA and MET were 0.997 and 0.998 respectively, indicates good linearity. Precision is validated by studying the repeatability, inter-day precision. Repeatability results indicate the precision under same operating condition over a short interval of time. Inter-day precision study expresses within laboratory variation in different days. In both inter-day and intraday precision, data of LINA and MET were indicated as % RSD below 2, it was showed good precise of developed method. The calculated limit of detection and limit of quantification of LINA was 0.390 μg/ml and 1.182 μg/ml respectively while LOD and LOQ data of MET was 0.439 μg/ml and 1.332 μg/ml respectively. Value of LOD and LOQ indicates sensitivity of proposed RP-HPLC method. Accuracy was determined by means of percentage recovery study and results were obtained of LINA and MET in range of 98.33 - 101 % and 98.85 – 101.36 % respectively. The % recovery data showed that developed method is accurate. (Table 4)
Table 4: Recovery data of LINA and MET
|
Level |
Amount of test solution (µg/ml) |
Amount of Std. solution (µg/ml) |
Amount of Found (µg/ml)* ± SD |
% Recovery |
% RSD |
|
Linagliptin |
|||||
|
80 |
1 |
0.8 |
1.787 ± 0.02 |
98.33 |
1.16 |
|
100 |
1 |
1 |
2.013 ± 0.02 |
101 |
1.25 |
|
120 |
1 |
1.2 |
2.183 ± 0.03 |
98.61 |
1.61 |
|
Metformin HCl |
|||||
|
80 |
200 |
160 |
362.17 ± 1.67 |
101.36 |
0.46 |
|
100 |
200 |
200 |
398.97 ± 4.41 |
99.48 |
1.11 |
|
120 |
200 |
240 |
437.23 ± 1.51 |
98.85 |
0.35 |
*Average of three determinations
Table 5: Degradation studies
|
Sr.No |
Stress Type |
Condition |
No. of Degradation peaks |
% degradation |
||
|
LINA |
MET |
LINA |
MET |
|||
|
1 |
Acid hydrolysis |
10ml 0.1 N HCl reflux at 60°C for 3 hr |
1 |
1 |
11.63 |
13.18 |
|
2 |
Alkali hydrolysis |
10ml 0.1 N NaOH reflux at 60°C for 3 hr |
1 |
2 |
12.98 |
15.25 |
|
3 |
Peroxide |
10ml of 3 % H2O2 at room temperature for 3 hr. |
- |
- |
4.58 |
6.10 |
|
4 |
Thermal |
At 60˚C for 12 hr. |
- |
- |
7.34 |
2.95 |
|
5 |
Photolytic |
UV 254nm for 24 hr. |
- |
- |
8.12 |
6.26 |
The deliberate change in perfomed organic phase composition, flow rate and injection volume resulted in % RSD of less the 2, indicates good and satisfactory robustneass of proposed method. The percentage assay of LINA and MET from Trajenta Duo 2.5mg /500mg were in good agreement with the label claim. % Assay of LINA and MET were found to be 99.36 % and 98.67 % respectively. The stability studies were carried out on LINA and MET to establish how accuratly and specifically the analyte of interest is estimated in presence of other conditions. The acidic, basic, peroxide, thermal and photolytic stress conditions were studied out in drug substances. The percentage degradation of LINA and MET under different conditions are shown in table 5.
CONCLUSION:
A simple, rapid, accurate and precise stability indicating RP- HPLC method was developed and validated with QbD approach. An experiment of design was applied for two factors % organic phase and flow rate and achieved good separation of both drugs. The experimental central composite design was created for critical method attributes by using Design Expert 12.0 trial version software. All factor effect on responses were analysed and generated 3D response surface plot which indicates simultaneous effect of both drugs. The results of validated method gives a symmetry peak shape, good resolution and resonable retention time of LINA and MET. Drug substances were exposed stress conditions and degradation were founded of drug less than 20%. Hence, developed method seems to be suitable for the quality control in the pharmaceutical industry.
CONFLICT OF INTEREST:
The authors declare no conflict of interest.
ACKNOWLEDGMENTS:
I am thankful to Nootan Pharmacy College, Sankalchand Patel University, and Shri Sarvajanik Pharmacy college, Mahesana for providing research facilities and constant motivation.
REFERENCES:
1. Linagliptin, [cited 2020 Oct 17]. https://medlineplus.gov/druginfo/meds/a611036.html
2. Metformin, [cited 2020 Oct 17]. https://www.webmd.com/drugs/2/drug-11285-7061/metformin-oral/metformin-oral/details.
3. Linagliptin, Drug Bank. [cited 2020 Oct 17]. Available from: https://go.drugbank.com/drugs/DB08882.
4. Metformin, Drug Bank. [cited 2020 Oct 17]. Available from: https://go.drugbank.com/drugs/DB00331.
5. ICH, Q8(R2), Harmonized Tripartite Guideline, Pharmaceutical Development. Available from:https://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Quality/Q8_R1/Step4/Q8_R2_Guideline.pdf.
6. Astha P. Sanyal, Khushbu K. Patel, Ushma B. Patel and Dr. Chhaganbhai N. Patel. Analytical Method Development and Validation for Estimation of Saroglitazar Magnesium in Pharmaceutical Dosage Form by Quality by Design Approach. World Journal of Pharmaxy and Pharmaceutical Sciences, 2020; 9(4):1267-1281.
7. ICH, Q1A(R2): Stability Testing of New Drug Substance and Drug Product. Available from:https://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Quality/Q1A_R2/Step4/Q1A_R2__Guideline.pdf.
8. Saroj Gajare, Vedantika Das, Ashwini Sambherao, Amar Zalte, Ravindra B. Saudagar. Development and Validation of Linagliptin and Metformin hydrochloride in Bulk and Combined Tablet Dosage Form by using UV Spectrophotometric Method. Asian Journal of Pharmaceutical Analysis. 2017; 7(2): 141-144. 10.5958/2231-5675.2017.00022.9
9. M. Mallikarjuna, C. Guru Sudhakar, K. Siva Shankar, SK. Abid, P. Rameeja. Development and Validation of a New Method for the Simultaneous Estimation of Metformin and Linagliptin in Bulk and Dosage form by using UV–Spectrophotometry. Asian Journal of Chemistry and Pharmaceutical Research. 2018; 6(1):58-72.
10. Sivagami, B., Purushotham, A., Sikdar, P., Chandrasekar, R., & Babu, M. N. A Validated Method for The Simultaneous Estimation of Linagliptin and Metformin in Tablet Dosage Forms by RP-HPLC. Research Journal of Pharmaceutical Technology. 2020; 13(3): 1266-1270. 10.5958/0974-360X.2020.00233.4
11. A. Janardhan Swamy, K. Harinadha Baba. Analytical Method development and Method validation for the simultaneous estimation of Metformin HCL and Linagliptin in Bulk and tablet Dosage Form by RP-HPLC Method. International Journal of Pharmacy. 2013; 3(3): 594-600.
12. S. Hari Hara Kumar, S. Sai Kiran. Method development and validation of metformin and linagliptin by RP-HPLC method in pharmaceutical dosage form. International Journal of Innovative Pharmaceutical Sciences and Research, 2016; 4(4); 333-339.
13. El-Bagary RI, Elkady EF, Ayoub BM. Spectrophotometric Methods for the Determination of Linagliptin in Binary Mixture with Metformin Hydrochloride and Simultaneous Determination of Linagliptin and Metformin Hydrochloride using High Performance Liquid Chromatography. International Journal of Biomedical Sciences. 2013; 9(1): 41-47.
14. Sohan S. Chitlange, Mohammed Imran, Kiran Bagri, DM Sakarkar. A stability-indicating reverse phase high performance liquid chromatography method for the simultaneous determination of ramipril and valsartan in pharmaceutical dosage form. Research J. Pharm. and Tech. 2008;1(3): 215-217.
15. B. Thangabalan, M. Salomi, N. Sunitha, S. Manohar Babu. Development of validated RP-HPLC method for the estimation of Itraconazole in pure and pharmaceutical dosage form. Asian J. Pharm. Ana. 2013;3(4):119-123.
16. N. Sunitha, L. Sindhura, B. Thangabalan, S. Manohar Babu. Development and Validation of RP–HPLC Method for Simultaneous Estimation of Cefepime and Tazobactam in Injection Formulation. Asian J. Pharm. Ana. 2013; 3(4):131-137.
17. H.I. Pawar, Lata Kothapalli, Asha Thomas, R.K Nanda, Shivaji Mare. Simultaneous RP-HPLC Method for Estimation of Ezetimibe and Fenofibrate in Synthetic mixture. Research J. Pharm. and Tech. 2008;1(1):25-28.
18. Srivani, J., B. Umamahesh, and C. Veeresham. Development and Validation of Stability Indicating HPTLC Method for Simultaneous Determination of Linagliptin and Metformin. International Journal of Pharmacy and Pharmaceutical Sciences. 2015; 8(1): 112-115.
19. Abbas Moussa B, Mahrouse MA, Fawzy MG. A validated LC-MS/MS method for simultaneous determination of linagliptin and metformin in spiked human plasma coupled with solid phase extraction: Application to a pharmacokinetic study in healthy volunteers. Journal of Pharmaceutical Biomedical Analysis. 2019; 163: 153-161. 10.1016/j.jpba.2018.09.052
20. Kavitha. K. Y, Geetha. G., et.al. Development and validation of stability indicating RP-HPLC method for the simultaneous estimation of linagliptin and metformin in pure and pharmaceutical dosage form. Journal of Chemistry and Pharmaceutical Research. 2013; 5(1): 230-235.
21. Nagunath Sirigiri, Siva Subramanian N, Naveen Kumar Reddy G. Stability Indicating Method Development and Validation for Simultaneous Estimation of Linagliptin and Metformin HCl in Tablets by HPLC. Der Pharma Chemistry. 2017; 9(21):100-106.
22. Jadhav SB, Reddy PS, Narayanan KL, Bhosale PN. Development of RP-HPLC, Stability Indicating Method for Degradation Products of Linagliptin in Presence of Metformin HCl by Applying 2 Level Factorial Design; and Identification of Impurity-VII, VIII and IX and Synthesis of Impurity-VII. Sciences Pharma. 2017; 85(3): 25-28. 10.3390/scipharm85030025
23. T.M. Kalyankar, R.B. Kakde. Reversed-Phase Liquid Chromatographic Method for Simultaneous Determination of Metformin and Repaglinide in Pharmaceutical Preparations. Research J. Pharma. Dosage Forms and Tech. 2011; 3(5): 233-237.
24. Dhavale Sushant, Jagtap Rajesh, Kotkar Tushar, Bhosale AV, Hardikar SR. Formulation and Evaluation of Floating Sustained Drug Delivery for Metformin HCl Using Combination of Natural and Synthetic Polymers. Research J. Pharma. Dosage Forms and Tech. 2009; 1(3):244-249.
25. Ganesh S Shinde, Godge Rahul K , Ravindra Jadhav. Quantitative Estimation and Validation of Metformin Hydrochloride and Gliclazide in their Tablet Dosage Form by RP-HPLC. Research J. Science and Tech. 2019; 11(3):201-207. 10.5958/2349-2988.2019.00030.5
26. Rahul K. Godge, Ganesh S. Shinde, Shraddha Joshi. Simultaneous Estimation and Validation of Dapagliflozin and Saxagliptin in Bulk Drug and Dosage Form by RP-HPLC. Research J. Science and Tech. 2019; 11(1):59-63. 10.5958/2349-2988.2019.00008.1
27. Parthiban C., Bhagavan Raju M., Sudhakar M. A Novel Simultaneous Estimation of Metformin, Glimepiride and Rosiglitazone in Tablet Dosage Form by RP-HPLC Method. Research J. Pharm. and Tech. 2011; 4(10):1576-1580.
28. ICH, Q2(R1): Validation of Analytical Procedure: Text and Methodology. Available from: https://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Quality/Q2_R1/Step4/Q2_R1__Guideline.pdf.
Received on 03.02.2021 Modified on 19.06.2021
Accepted on 14.08.2021 © RJPT All right reserved
Research J. Pharm. and Tech. 2022; 15(5):1917-1923.
DOI: 10.52711/0974-360X.2022.00319