A Simple Liquid Chromtographic Method for the Simultaneous Estimation of Antidiabetic Drugs in Spiked Human Plasma: Heteroscedasticity Study

Prakashkumar B¹, Bhagyalakshmi C¹, Pulak Majumder², Koushik Nandan Dutta³,

Manoj Kumar Deka⁴, Bhargab Jyoti Sahariah⁴, Manish Majumder⁵*

¹Department of Pharmaceutical Analysis, Sri Adichunchanagiri College of  Pharmacy,

Adichunchanagiri University, BG Nagara - 571448, Karnataka, India.

²Department of Pharmacognosy, Sri Adichunchanagiri College of Pharmacy,

Adichunchanagiri University, BG Nagara - 571448, Karnataka, India.

³Department of Pharmacognosy, NETES Institute of Pharmaceutical Sciences,

Nemcare Group of Institution, Mirza, Kamrup, Assam 781125.

⁴Department of Pharmaceutics, NETES Institute of Pharmaceutical Sciences,

Nemcare Group of Institution, Mirza, Kamrup, Assam 781125.

⁵Department of Pharmaceutical Chemistry, NETES Institute of Pharmaceutical Sciences,

Nemcare Group of Institution, Mirza, kamrup, Assam 781125.

*Corresponding Author E-mail: prakashkumar_007@yahoo.co.in, bhagyachandran31@gmail.com, pulakmajumder@accp.co.in, koushik5dutta@gmail.com, manojpharmacy86@gmail.com, bhargabjyoti@gmail.com, manishphar33@gmail.com

ABSTRACT:

A precise and accurate liquid chromatography method was developed to simultaneously determine linagliptin and empagliflozin in spiked human plasma. The method utilized a C8 Eclipse Plus column (25cm X 5mm and 4.6µm) packed with L1 material, with a flow rate of 1mL/min. The mobile phase consisted of a mixture of acetonitrile, methanol, and 20mM potassium dihydrogen orthophosphate (pH 3.5) in a ratio of 26:19:55% (v/v). Detection was performed at 230nm, and the total run time was 15minutes. The retention time for linagliptin was 4.30 minutes, while for empagliflozin it was 10.35 minutes. The linear range for quantification was found to be 50-750 ng/mL for linagliptin and 30-960ng/mL for empagliflozin. The regression equations for linagliptin and empagliflozin were y = 181.24x+11241 and y = 393.64x+19552, respectively, with high regression coefficients (R²) of 0.9997 and 0.9995. Protein precipitation using a mixture of acetonitrile and methanol (70:30) was employed for extraction. The method demonstrated good recovery percentages ranging from 89.728±5.010 to 95.806±2.828 for linagliptin and 85.593±5.661 to 95.150±1.593 for empagliflozin. Extensive validation was conducted to assess linearity, accuracy, precision, recovery, and stability of the method.

KEYWORDS: Diabetes mellitus, Linagliptin, Empagliflozin, HPLC, Protein precipitation, Human Plasma.

INTRODUCTION: 

Diabetes is a second most common human cause of death in the global population, according to statistics. Diabetis mellitus is altered metabolic condition associated with persistent hyperglycemia and poor digestion of carbohydrates, lipids, and proteins as a result of abnormalities in insulin emission, insulin activity, or both.¹ It is a chronic illness that affects the body when the islets of pancreatic beta cells are unable to produce insulin or when tissues are unable to use insulin.² The most prevalent form of diabetes in adults is non-insulin-dependent diabetic mellitus (T2DM), which is brought on by the body's increased sensitivity to the hormone insulin and is closely associated with a sedentary lifestyle^.3 Sodium-glucose cotransporter-2 inhibitor (SGLT-2) protein overexpression, which increases glucose reabsorption and plasma glucose levels at the proximal tubule of the nephrons, is a characteristic of T2DM. Increased insulin requirements in the body as a result of insulin resistance in T2DM; over time, the cells' underlying causes are gradually destroyed in conjunction with other contraindications like obesity, nephropathy, dyslipidaemia, low HDL levels, and hypertension, etc.^4,5 For metabolic abnormalities that cannot be managed with a single pharmacological therapy, such many physiological deficiencies may require focused therapy.⁶ Given this contrast, combination treatment would be the best option for treating T2DM because it has various target mechanisms and does not merely aim to reduce glycated haemoglobin levels.⁷ The first-line treatment for type 2 diabetes is metformin, with sulfonylurea, SGLT-2 inhibitors, such as Empagliflozin, and DPP-4 medicines, such as Linagliptin, being added.⁸

First of all, Empagliflozin (Empa) is a dynamic class of antidiabetics known as SGLT-2 inhibitors. Mechanistically, they play a unique role in boosting glucose excretion in the renal system by taking a separate approach to cell activity. Although SGLT-2 inhibitors have also shown that they have a direct impact on lowering cardiovascular risks, this makes them a perfect candidate for combination treatment.⁹  Hence empa, an SGLT-2 inhibitor chemically known as (2S,3R,4R,5S,6R)-2-[4-chloro-3-i[[4-[(3S)-oxolan-3yl ]ioxy phenyl]methyl]phenyl]i-6-(hydroxymethyl)oxane-3,4,5-triol, (molecular formula: C₂₃H₂₇ClO₇ and molecular weight: 450.91g/mol) is one of the choices for combination with linagliptin or MET in the treatment of type 2 diabetes mellitus.¹⁰

Linagliptin (Lina), another drug from the group of dipeptidyl peptidase-4 inhibitors (DPP-4), potentially lowers blood sugar levels through the reversible enzyme inhibition mechanism of dipeptidyl peptidase-4 in the enterohepatic system. It mainly prevents the breakdown of incretin hormones, i.e. glucagon-like peptide-1 (GLP1), and helps reduce hyperglycaemia, and more importantly, they are not associated with weight gain.¹¹ Linagliptin is chemically known as (i8-[(3R)-3-aminopiperidin-1-yl]-7-but-2-ynyl-3-methyl-1-ii[(4-methyiquinazolin-2-iyl)imethyl]ipurine-2,6-dione with the molecular formula C₂₅H₂₈N₈O₂ and a molecular weight of 1472.553 g/mol each. Consequently, it would be the most suggested alternative to sulfonylurea derivatives.¹²

Hence, in management of better glycaemic control and associated side effects, the use of both   DPP-4 inhibitors and SGLT-2 inhibitors will provide higher complementary effects in add on therapy of diabetes.¹³ Despite of having such potential therapeutic applications, most of the Preclinical and clinical studies were engaged with the evaluation of such potent drugs (i.e. Empagliflozin and Linagliptin) for safety and efficacy by using very sophisticated bioanalytical methods like LC-MS/MS because of the lacuna of proper cost-effective methods like HPLC or other chromatographic methods.    However, few analytical methods such as UV spectroscopy^14,15, LCMS^16–29,  HPTLC³⁰,    and HPLC^31–36 were reported for estimation of both  drug individually or other formulation.  But due to unsafficient specificity and selectivity, all those approaches are failed to quantify the both drugs (i.e., Linagliptin and Empagliflozin) concurrently in  humanplasma. Hence, it’s a need of the hour to develop new advanced bio analytical methods for quantification of both the drugs simultaneously in human plasma. On this contrast, the present investigation aimed to develop a validated bio analytical method for quantification of both drugs (Linagliptin and Empagliflozin) concomitantly in human plasma. Bioanalytical US-FDA guidelines for validation parameters are strictly followed throughout this development process. Both the drugs from human plasma were extracted with  diluent (a mixer of methanol and acetonitrile) by using simple protein precipitation technique.

MATERIAL AND METHODS:

Initial Chromatographic Condition:

Chromatographic development has been performed on Ultra Performance Liquid Chromatography, Shimadzu, Japan, with LC-20AD pump and PDA detector. The data processing and integration was executed with LC-Real time analysis software. The separation was attained on an Eclipse plus C8 (25cm x 5mm x 4.6µm) with L1 packing. The mobile phase is a mixture of acetonitrile, methanol and 20mM potassium dihydeogenortho phosphate (pH 3.5) (26: 19: 55)% v/v. The flow rate was maintained at 1ml/min in isocratic mood with a15min rum time. The limit of detection and qualification of lina and empa was performed at 230mn at ambient temperature. The retention time (Rt) was 5.064min  (lina) and 10.090min (empa)and chromatogram shown in figure 1.

Figure 1: Representative Chromatogram of Lina and Empa in human plasma

Stock solution preparation:

The stock solution (10, 000ng/mL) has been prepared by dissolving requisite in diluent (a mixer of acetonitrile and methanol, 70:30v/v). Similarly working standard was made by diluting stock solution in same diluent. All solution solutions were stored at 2-8⁰C.

Calibrator (CC) and Quality Control (QC) Sample preparation:

The serial dilutions for calibration  were prepared by spiking  600µL of the above stock dilutions, 300µL plasma and 600µL of a mixture of Acetonitrile and methanol (70:30v/v) to get the concentration (50, 150, 300, 450, 600 and 750)ng/mL and (30, 60, 120, 240, 480 and 960) ng/mL for Linaand Empa respectively. The QC samplesof lina and empa for LLOQ (50ng/Ml and 30 ng/mL), LQC (150ng/mL and 100ng/mL), MQC (450 ng/mL and 300ng/mL) and HQC (750ng/mL and 600 ng/mL) have been prepared separately in similar way. After vortexing for one minute, all standardswere centrifuged at 5000rpm at 4⁰C. Finally supernatant was filtered fhrough 0.22µm filter before injection.

Preparation of plasma sample:

As for plasma sample, 600µL of drug solution and 600 µL diluent (a mixture of Acetonitrile and methanol, 70:30 v/v) were added to 300µL plasma in 2ml centrifuge tube. The solutions are centrifuged at 5000 rpm for five minutes at 4⁰C. The supernatants were filtered using 0.22µm filter before injection. The animal study was approved by Institutional Human Ethical committee (IHEC) of Sri Adichunchanagiri College of Pharmacy, B G Nagara with ethical clearance No. 0009/PP/SACP/2019.

Method validation:

The developed method was subjected for validation such as specificity, accuracy, precision, linearity, and recovery and stability study according to US FDA guideline for the bio-analytical method.³⁷

Specificity:

The specificity was assessed by analysing blank plasma and blank plasma matrices spiked with both analytes (lina and empa). Any interference from unwanted component was evaluated at retention time of the lina and empa as well as blank plasma.

Calibration Curve:

The calibration curve of lina andempa were constructed using six calibrators and one blank plsma at triplicate level. The graph was plotted using concentration on x-axis and area of the response peak on y-axis. The fit test of calibration curve was performed by using weighting least square linear regression model.

Recovery:

The extraction recovery of the method were determined by comparing peak area of lina and empa at QC level (LLOQ, LQC, MQC and HQC) in standard spiked before extraction and standard spiked after extraction.

Accuracy Precision:

The accuracy study was performed by using six calibrators in three replicate levels. The Intra and inter- day precision were evaluated at three level of Quality control samples (LQC, MQC, HQC). Percentage relative Error (%RE) and relative standard deviation (5RSD) are the attributes for the accuracy and precision study.

Stability studies:

The stability studies of lina and empa was assessed under different storage condition at three QC level (LQC, MQC and HQC). The duration of stability studies was 24 hours short termstability and 45 days (-80⁰C) for long term stability. The freeze and thaw study was tested after 3 cycles of freezed (-80⁰C) and thawed of QC sample at three level.

RESULT AND DISCUSSION:

Chromatographic parameters optimization:

A simple and fast RP-UFLC method was designed and developed through a scientific approach to get a optimized chromatographic condition. In view of this aim, the optimizations of chromatographic parameters (composition of mobile phase, column selection and flow rate) have been performed. The pH of the mobile phase and column have been investigated and selected on the basis of log –D curve plotted by chem Axon log-d predictor (demo version). The log-D curve shows flat (relatively robust) in the pH range 3-5 for both analytes. This suggest that the retention time (Rt) of the both drugs remain stable and constant in this range of pH. The log-D plots of both analytes arecurved and unstady in the range of pH (9-13 for empa and 6-12 for lina). It gives conclusion that pH range 3-5 is optimal and stable for the chromatographic development.³⁸ With this fact and figure Eclipse plus C18 column (25cm x 5mm x 4.6 µm) with L1 packing have been selected for the chromatographic separation. Initially in mobile phase, mixer of water and organic modifier has tested for the separation. But both the druge are not efficiently retained in water. Therefore 20mM potassium dihydrogen phosphate buffer was used in place of water. A blender of acetonitrile, methanol and 20mM potassium dihydrogen phosphate buffer (26:19:55% v/v) have been found the optimized mobile phase for the separation of both analytes in isocratic mode. The elution flow rate was maintained at 1mL/min for the quantitation of lina and empa, with 15 min  run time. The PDA detector is used for recording the responses at 230nm due to chromospheres and auxochromes present in both drugs. Since the log P of Lina and Empa are 2.8 and 1.7 (predicted by the demo version of Chem Axon) and moderately hydrophobic in nature, so the protein precipitation method is best choice for the extraction for drugs from plasma. In this regard mixer of methanol and acetonitrile in different ratio have been evaluated and a combination of methanol and acetonitrile (30:70) was found the best extraction diluent for the maximum recovery of the drugs from the human plasma³⁹

Method Validation:

Specificity:

Figure 2 shows chromagrams of blank human plasma and spiked drugs in human plasma.  As observed in the figure 2, there is no obvious interferences under developed chromatographic condition. There the proposed method has capacity for quantification of both analytes individually in human plasma.³⁹

Figure 2: Chromatogram of Blank human plasma and both drugs spiked in human plasma

Accuracy and precision:

The accuracy as well as intra and inter day precision was shown in table 1 and 2. The accuracy and precision study was evaluated incalibrators and QC sample in tem of %RE and %CV.  The accuracy study was found in tem of %RE  (-14.842 to+3.378) for lina and (-14.143 to +6.321) for empa. The intradayprecision was found in term of %CV (0.511 to 5.584 ) for lina and (0.598 to 6.614) for empa. The %CV  of inter day precision was (0.647 to 4.051) for lina and (0.657 to 7.387) for empa.⁴⁰

Table 1: Accuracy Data of Linagliptin and Empagliflozin (n = 6)

	Lina(ng/mL)			Empa(ng/mL)
S. No	Nominal concentration	Mean concentration	%RE	Nominal concentration	Mean concentration	%RE
CC1	50	57.421	14.842	30	25.757	-14.143
CC2	150	148.940	-0.706	60	53.386	-11.022
CC3	300	292.496	-2.501	120	119.657	-0.285
CC4	450	435.897	-3.133	240	255.172	6.321
CC5	600	620.271	3.378	480	478.462	-0.320
CC6	750	744.940	-0.674	960	957.567	-0.253

CC: Calibration Curve Standard %RE: Percentage of Relative Error

Table 2 Intra and Inter- day Precision of Linagliptin and Empagliflozin (n = 6)

Analyte	QC Level	Nominal Concentration^* (ng/mL)	Intraday Precision			Interday Precision
			Measured Concentration (Mean ± SD)	%CV	%RE	Measured Concentration (Mean ± SD)	% CV	%RE
Lina	LLOQ LQC MQC HQC	50 150 450 750	44.864±2.505 139.563±3.278 431.130±3.730 744.506±3.808	5.584 2.349 0.865 0.511	-10.271 -6.958 -4.193 -0.732	42.541±3.725 135.675±4.519 428.640±4.650 741.836±4.801	4.051 3.330 1.084 0.647	-14.918 -9.55 -4.746 -1.088
Empa	LLOQ LQC MQC HQC	30 100 300 600	25.678±1.698 89.757±1.825 284.990±6.573 594.900±3.559	6.614 2.033 2.306 0.598	-14.406 -10.243 -5.003 -0.849	24.500±1.810 87.645±2.305 282.016±6.989 593.360±3.901	7.387 2.629 2.478 0.657	-18.333 -12.355 -5.994 -1.106

QC Level: Quality Control Level, CV: coefficient of variation, SD: Standard Deviation, LLOQ: Lower limit of quantification, LQC: Low Quality control, MQC: Mid Quality control, HQC: High Quality control

Linearity and sensitivity:

The plasma calibration curves have been constructed in the range of  (50-750)ng/mL for lina and (30-960) ng/mL for empa respectively. The fitness of calibration was test using weighing factor of 1/x⁰, 1/x, 1/√x and 1/x² and best weighing factor was found to be 1/ x⁰ with R² and %RE. and shown in table 3 and 4.⁴¹ Optimized R² and %RE are 0.9997 and 1.8674 for lina as well as 0.9995 and -3.283 for empa.The figure 3 shows about the plot of residuals vs concentration and tells about the random distribution of error around the concentration axis.⁴² It includes that method is sufficiently sensitive to estimate the concentration of analytes in human plasma.

Table 3: weighting least square linear regression of Linagliptin

weight factor(w)	1/x^0	1/x	1/√x	1/x^2
R^2	0.9979	0.5962	0.7271	0.4446
% RE	1.8674	-81.901	-3.146	-2725.066

%RE: Percentage of Relative Error R²: Correlation Coefficient

Table 4: weighting least square linear regression of Empagliflozin

weight factor(w)	1/x^0	1/x	1/√x	1/x^2
R^2	0.9995	0.4572	0.631	0.2752
% RE	-3.283	- 289.022	- 17.379	-16269.436

%RE: Percentage of Relative Error R²: Correlation Coefficient

Figure 3: Diagnostic Plot of residuals vs concentration

Recovery study:

The extraction method is optimized under developed chromatographic condition to get maximum recovery from the human plasma. In this study the percentage recoveries were 89.728±5.010 - 95.806±2.828 (Lina) and 85.593±5.661 to 95.150±1.593 (Empa) for QC samples (LQC, MQC and HQC) respectively.⁴³

Stability Study: The stability result (Table 6) demonstrates the both analytes (lina and empa) shows sufficient stability under different experimental condition.⁴⁴

Table 5: Percentage Recovery Studies of Linagliptin and Empagliflozin (n = 3)

Analyte	QC Level	Nominal Concentration (ng/mL)	% Recovery
			Mean ± SD	%CV	%RE
Lina	LLOQ LQC MQC HQC	50 150 450 750	89.728± 5.010 93.042±2.185 95.806±2.828 95.267±2.507	5.584 2.349 1.865   1.511	-10.271 -6.958 -4.193 -1.732
Empa	LLOQ LQC MQC HQC	30 100 300 600	85.593±5.661 89.757±2.825 94.996±2.191 95.150±1.593	6.614 2.033 2.306 1.598	-14.406 -10.243 -5.003 -1.849

CV: Coefficient of variation SD: Standard Deviation

Table 6: Stability of analytes in rat plasma in three QC level (n = 6)

Stability	Measured Concentration  (Mean ± SD)		% CV
	Lina(ng/mL)	Empa (ng/mL)	Lina	Empa
0 hour	139.563±3.278 431.130±3.730 744.506±3.808	89.757±1.825 284.990±6.573 594.900±3.559	2.349 2.865 2.511	2.033 2.306 2.598
Bench Top (24 h) Rt	138.363±3.907 429.990±4.313 743.101±4.980	88.973±2.904 283.009±7.430 592.605±4.389	2.823 1.003 1.670	3.263 2.625 1.740
Freeze and Thaw (- 80^0C for 3 three cycles)	132.623±8.017 421.490±8.830 737.841±9.081	84.042±6.119 278.160±9.640 588.416±8.480	6.044 2.094 2.230	6.044 2.094 2.230
Long term (-80^0 45 days)	128.016±9.107 419.014±9.583 731.014±10.010	79.140±8.809 272.616±9.989 583.024±10.714	7.113 2.287 2.369	11.130 3.664 2.837

CV: coefficient of variation SD: Standard Deviation

CONCLUSION:

A simple, fast and inexpensive liquid chromatographic method is developed for the quantitation of lina and empa in human plasma. The proposed method offers the advantages of smaller sample volumes, use of simple extraction procedures, and simultaneous evaluation of concomitant medications. The sensitivity of this new method is useful for conducting clinical studies such as therapeutic drug monitoring, pharmacokinetics and pharmacodynamics studies. This HPLC-UV technique was validated as per US FDA bio analytical guideline. This method is also useful in simultaneously analysing of lina and empain pharmaceutical formulations.

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this investigation.

ACKNOWLEDGEMENT:

The Authors thank Sri Adichunchanagiri College of Pharmacy, B G Nagara for their support.     

REFERENCES:

1. Virendra Singh Choudhary, Geeta Chaudhary. A Descriptive Study to Assess the Knowledge Regarding Diabetes Mellitus, Its Risk Factors and Complication among the Rural Community Sadiq, Faridkot (Punjab). Asian J. Nur. Edu. and Research. 2015; April-June; 5(2): 251-253.

2. Hazaratali Panari, Vegunarani.M. Study on Complications of Diabetes Mellitus among the Diabetic Patients. Asian J. Nur. Edu. and Research. 2016; 6(2): 171-182.

3. Sindhu L, Jaya Kumar B. Effectiveness of Educational Intervention on Body Mass Index (BMI) of Patients with Type 2 Diabetes Mellitus in South Indian Population. Asian J. Nursing Education and Research. 2018; 8(3): 434-436.

4. Parisa Parsa, Roya Ahmadinia-Tabesh, Younes Mohammadi. Assessment of the risk of Coronary Heart Disease in Diabetes Patients Type-II. Asian J. Nursing Education and Research. 2019; 9(2): 267-270.

5. Pushpendra Kumar, Titi Xavier Mangalathil, Vikas Choudhary. An experimental study to assess the effectiveness of structured teaching programme on knowledge regarding the management of diabetes mellitus among G.N.M. students in selected nursing school at Sikar, Rajasthan. Asian J. Management. 2014; 5(3): July-September: 329-331.

6. Himani Patel, Daxaben P. Patel. A Descriptive Study to Assess the Knowledge and Attitude regarding Self Administration of Insulin Injection among Diabetes Mellitus patient in selected Hospital of Visnagar City, in view of Information Booklet. Asian Journal of Nursing Education and Research. 2021; 11(4): 499-2.

7. Don Jose K, Femi Sebastian, Fiby Franklin, Divya Davis, Iriene B. Padanilath, Jeena Johnson. A study to assess the Knowledge regarding glycemic control and self- management among diabetic patients in Amala Institute of Medical Sciences, Thrissur. Asian Journal of Nursing Education and Research. 2021; 11(4): 571-6.

8. Gepsi Jain, Nahomi Clement. A Study to assess the knowledge regarding self management behaviour among Type II Diabetes Mellitus patients in prevention of COVID-19 at selected area, Alappuzha District, Kerala, India. Asian Journal of Nursing Education and Research. 2022; 12(4): 449-3.

9. Frampton JE. Empagliflozin: A Review in Type 2 Diabetes. Drugs [Internet]. 2018; 78(10): 1037–48. Available from: https://doi.org/10.1007/s40265-018-0937-z

10. Neumiller JJ. Empagliflozin: A new sodium-glucose co-transporter 2 (SGLT2) inhibitor for the treatment of type 2 diabetes. Drugs Context. 2014; 2(June).

11. Neumiller JJ. Revisión de la farmacología, eficacia y seguridad de linagliptina en el tratamiento de pacientes con diabetes mellitus tipo 2. Ann Pharmacother. 2012; 46(3): 358–67.

12. Neumiller JJ, Setter SM. Review of Linagliptin for the Treatment of Type 2 Diabetes Mellitus. Clin Ther [Internet]. 2012; 34(5): 993–1005. Available from: http://dx.doi.org/10.1016/j.clinthera.2012.02.029

13. Ingelfinger JR, Rosen CJ. Clinical credence — SGLT2 inhibitors, diabetes, and chronic kidney disease. N Engl J Med. 2019; 380(24): 2371–3.

14. Elmasry MS, Hassan WS, Merey HA, Nour IM. Simple mathematical data processing method for the determination of sever overlapped spectra of linagliptin and empagliflozin in their pure forms and pharmaceutical formulation: Fourier self deconvulated method. Spectrochim Acta - Part A Mol Biomol Spectrosc [Internet]. 2021; 254: 119609. Available from: https://doi.org/10.1016/j.saa.2021.119609

15. Moussa BA, Mahrouse MA, Fawzy MG. Smart spectrophotometric methods for the simultaneous determination of newly co-formulated hypoglycemic drugs in binary mixtures. Spectrochim Acta - Part A Mol Biomol Spectrosc [Internet]. 2021; 257: 119763. Available from: https://doi.org/10.1016/j.saa.2021.119763

16. Suresh PS, Srinivas NR, Mullangi R. A concise review of the bioanalytical methods for the quantitation of sitagliptin, an important dipeptidyl peptidase-4 (DPP4) inhibitor, utilized for the characterization of the drug. Biomed Chromatogr. 2016; 30(5): 749–71.

17. 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. J Pharm Biomed Anal [Internet]. 2019; 163: 153–61. Available from: https://doi.org/10.1016/j.jpba.2018.09.052

18. Kobuchi S, Ito Y, Yano K, Sakaeda T. A quantitative LC-MS/MS method for determining ipragliflozin, a sodium-glucose co-transporter 2 (SGLT-2) inhibitor, and its application to a pharmacokinetic study in rats. J Chromatogr B Anal Technol Biomed Life Sci [Internet]. 2015; 1000: 22–8. Available from: http://dx.doi.org/10.1016/j.jchromb.2015.07.013

19. Li X, Liu L, Deng Y, Li Y, Zhang P, Wang Y, et al. Pharmacokinetics and bioequivalence of a generic empagliflozin tablet versus a brand-named product and the food effects in healthy Chinese subjects. Drug Dev Ind Pharm [Internet]. 2020; 46(9): 1487–94. Available from: http://dx.doi.org/10.1080/03639045.2020.1810263

20. 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. Sci Pharm. 2017; 85(3): 1–17.

21. Shah PA, Shrivastav PS, Sharma V, Yadav MS. Challenges in simultaneous extraction and chromatographic separation of metformin and three SGLT-2 inhibitors in human plasma using LC–MS/MS. J Pharm Biomed Anal [Internet]. 2019; 175: 112790. Available from: https://doi.org/10.1016/j.jpba.2019.112790

22. Dietrich N, Kolibabka M, Busch S, Bugert P, Kaiser U, Lin J, et al. The dpp4 inhibitor linagliptin protects from experimental diabetic retinopathy. PLoS One. 2016; 11(12): 1–17.

23. van der Aart-van der Beek AB, Wessels AMA, Heerspink HJL, Touw DJ. Simple, fast and robust LC-MS/MS method for the simultaneous quantification of canagliflozin, dapagliflozin and empagliflozin in human plasma and urine. J Chromatogr B Anal Technol Biomed Life Sci [Internet]. 2020; 1152: 122257. Available from: https://doi.org/10.1016/j.jchromb.2020.122257

24. Zhang H, Uthman L, Bakker D, Sari S, Chen S, Hollmann MW, et al. Empagliflozin Decreases Lactate Generation in an NHE-1 Dependent Fashion and Increases α-Ketoglutarate Synthesis From Palmitate in Type II Diabetic Mouse Hearts. Front Cardiovasc Med. 2020; 7(December): 1–10.

25. Mourad SS, El-Kimary EI, Barary MA, Hamdy DA. Pharmacokinetic interaction between linagliptin and tadalafil in healthy Egyptian males using a novel LC-MS method. Bioanalysis. 2019; 11(14): 1321–36.

26. Suda M, Shimizu I, Yoshida Y, Hayashi Y, Ikegami R, Katsuumi G, et al. Inhibition of dipeptidyl peptidase-4 ameliorates cardiac ischemia and systolic dysfunction by up-regulating the FGF-2/EGR-1 pathway. PLoS One. 2017; 12(8): 1–18.

27. Kobuchi S, Yano K, Ito Y, Sakaeda T. A validated LC-MS/MS method for the determination of canagliflozin, a sodium–glucose co-transporter 2 (SGLT-2) inhibitor, in a lower volume of rat plasma: application to pharmacokinetic studies in rats. Biomed Chromatogr. 2016; 30(10): 1549–55.

28. Kobuchi S, Matsuno M, Fukuda E, Ito Y, Sakaeda T. Development and validation of an LC-MS/MS method for the determination of tofogliflozin in plasma and its application to a pharmacokinetic study in rats. J Chromatogr B Anal Technol Biomed Life Sci [Internet]. 2016; 1027: 227–33. Available from: http://dx.doi.org/10.1016/j.jchromb.2016.05.053

29. Airapetian V, Glocer A, Gronoff G. The early Earth under a superflare and super-CME attack: Prospects for life. Proc Int Astron Union. 2015; 11(S320): 409–15.

30. Bhole RP, Wankhede SB, pandey M. Stability Indicating HPTLC Method for Simultaneous Estimation of Empagliflozin and Linagliptin in Pharmaceutical Formulation. Anal Chem Lett. 2017; 7(1): 76–85.

31. Ayoub BM. UPLC simultaneous determination of empagliflozin, linagliptin and metformin. RSC Adv. 2015; 5(116): 95703–9.

32. Donepudi S, Achanta S. Validated HPLC-UV method for simultaneous estimation of linagliptin and empagliflozin in human plasma. Int J Appl Pharm. 2018; 10(3): 56–61.

33. Marie AA, Salim MM, Kamal AH, Hammad SF, Elkhoudary MM. Analytical quality by design based on design space in reversed-phase-high performance liquid chromatography analysis for simultaneous estimation of metformin, linagliptin and empagliflozin. R Soc Open Sci. 2022; 9(6).

34. Patel IM, Chhalotiya UK, Jani HD, Kansara D, Kachhiya HM, Shah DA. Simultaneous quantification of empagliflozin, linagliptin and metformin hydrochloride in bulk and synthetic mixture by RP–LC method. Futur J Pharm Sci [Internet]. 2021; 7(1): 1–10. Available from: https://doi.org/10.1186/s43094-021-00332-1

35. Patel IM, Chhalotiya UK, Jani HD, Kansara D, Shah DA. Densitometric simultaneous estimation of combination of empagliflozin, linagliptin and metformin hydrochloride used in the treatment of type 2 diabetes mellitus. J Planar Chromatogr - Mod TLC. 2020; 33(2): 109–18.

36. Vankalapati KR, Alegete P, Boodida S. Stability-indicating ultra performance liquid chromatography method development and validation for simultaneous estimation of metformin, linagliptin, and empagliflozin in bulk and pharmaceutical dosage form. Biomed Chromatogr. 2021; 35(4): 5–15.

37. FDA F and DA. Bioanalytical Method Validation Guidance. Food Drug Adm. 2018; 1043(May): 25.

38. Analytical Method Development and Method Validation for the Simultaneous Estimation of Metformin hydrochloride and Pioglitazone hydrochloride in Tablet Dosage Form by RP-HPLC. Asian J. Pharm. Ana. 2012; 2(3): July-Sept. 85-89.

39. Swapnil J. Dengle, Shriram M. Pathak, Chandra Mohan, Arumugam Karthik, Prashant Musmade, Krishnamurthy Bhat, Nayanabhirama Udupa. Analysis of Midazolam in Small Volumes of Plasma Using High Performance Liquid Chromatography and UV-Detection Method: Pharmacokinetics of Midazolam in Rats. Asian J. Research Chem. 2011; 4(3): March 406-414.

40. Niraj Vyas, Sangita Panchal. Development and Validation of RP-HPLC Method for Simultaneous Estimation of Nebivolol and Indapamide in Pharmaceutical Dosage Form. Asian J. Pharm. Ana. 2014; 4(3): July-Sept. 98-102.

41. Almeida AM, Castel-Branco MM, Falcão AC. Linear regression for calibration lines revisited: Weighting schemes for bioanalytical methods. J Chromatogr B Anal Technol Biomed Life Sci. 2002; 774(2): 215–22.

42. Sonawane SS, Chhajed SS, Attar SS, Kshirsagar SJ. An approach to select linear regression model in bioanalytical method validation. J Anal Sci Technol. 2019; 10(1): 1–7.

43. Mercolini L, Mandrioli R, Finizio G, Boncompagni G, Raggi MA. Simultaneous HPLC determination of 14 tricyclic antidepressants and metabolites in human plasma. J Sep Sci. 2010; 33(1): 23–30.

44. Donepudi S, Achanta S. Simultaneous estimation of saxagliptin and dapagliflozin in human plasma by validated high performance liquid chromatography - Ultraviolet method. Turkish J Pharm Sci. 2019; 16(2): 227–33.

Received on 29.05.2023            Modified on 10.10.2023

Accepted on 19.01.2024           © RJPT All right reserved

Research J. Pharm. and Tech 2024; 17(7):3197-3203.

DOI: 10.52711/0974-360X.2024.00500