A green approach for the determination of selected anti-diabetic drugs in pharmaceutical formulation by transmission FTIR spectroscopy

ARTICLE

A green approach for the determination of selected anti-diabetic drugs in pharmaceutical formulation by transmission FTIR spectroscopy

Faiza Fahim^I; Ayesha Naseer^I; Shakil Ahmed^I; Syed Tufail H. Sherazi^II; Muhammad I. Bhanger^{*, I}

^IHEJ Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, 75270 Karachi, Pakistan

^IINational Centre of Excellence in Analytical Chemistry, University of Sindh, 76080 Jamshoro, Pakistan

ABSTRACT

Fourier transform infrared spectroscopy (FTIR) based methods for the determination of two anti-diabetic drugs, i.e., metformin HCl and glimepiride in tablet formulation are described. The methods involve the use of carefully prepared KBr discs with standards and samples of metformin HCl and glimepiride. FTIR spectra were acquired in the mid IR region. Extraction and pre concentration procedures were totally avoided. For quantification of metformin HCl, a prominent IR band appearing at fixed location height 3173 cm^-1 with two point baseline between 3550-2850 cm^-1 and for glimepiride IR band at fixed location height 1708 cm^-1 with two point baseline between 1800-1600 cm^-1 were selected for Beer's law calibrations. For metformin HCl, calibrations were developed using standards in the range between 0.300 mg to 3.100 mg whereas for glimepiride, calibrations were developed using standards in the range between 0.400 mg to 2.450 mg. Accuracy and reproducibility of proposed methods were evaluated and found to be satisfactory with excellent regression coefficients, acceptable recoveries and low standard deviations. The FTIR methods were successfully applied for the quantification of pharmaceutical tablets formulation containing metformin HCl and glimepiride as active substances and the results were found to be comparable with the quoted values.

Keywords: transmission FTIR spectroscopy, metformin HCl, glimepiride, tablet formulations

RESUMO

Métodos baseados em espectroscopia de infravermelho com transformada de Fourier (FTIR) para a determinação de duas drogas anti-diabetes, i.e., metformina HCl e glimepirida em formulações de comprimidos, são descritos. Os métodos envolvem o uso de discos de KBr, cautelosamente preparados, com padrões e amostras de metformina HCl e glimepirida. Espectros de FTIR foram adquiridos na região de infravermelho média. A extração e pré-concentração foram evitadas. Para a quantificação da metformina HCl, uma banda de IR proeminente, com localização fixa em 3173 cm^-1 com dois pontos na linha base, entre 3550-2850 cm^-1 e para a glimepirida, uma banda com localização fixa em 1708 cm^-1, com dois pontos na linha base, entre 1800-1600 cm^-1 foram selecionados para a calibração usando a lei de Beer. Para a metformina HCl, desenvolveu-se calibrações usando padrões na faixa entre 0,300 mg a 3,100 mg, enquanto que para a glimepirida, as calibrações foram desenvolvidas usando padrões na faixa entre 0,400 a 2,450 mg. Precisão e reprodutibilidade dos métodos propostos foram avaliadas e classificadas como satisfatórias com coeficientes de regressão excelentes, recuperação aceitável e baixos desvios do padrão. Os métodos de FTIR foram aplicados com sucesso na quantificação de formulações de fármacos contendo metformina HCl e glimepirida como substâncias ativas e os resultados comparáveis aos valores citados.

Introduction

Type II diabetes is a metabolic disease, which is characterized by high blood sugar level. It is a life threatening disorder and prevalence of diabetes in developing countries are penetrating very fast. One of the surveys reveals that 366 million cases will be predicted in 2030 and number of cases will be doubled from 2000 to 2030 in developing countries.¹ The initial development of type II diabetic condition is managed with the following key factors diet, life style modification, inherit, mental stress, and exercise. Oral therapy is initiated if the non-pharmacological means fail to control the disease. Metformin HCl (imidodicarbonimidicdiamide, N,N-dimethyl-monohydrochloride) is the first line of therapy in the case of overweight patients.² If blood glucose levels remains inadequate, so other oral hypoglycemic agents [sulfonylureas usually glimepiride (3-ethyl-4-methyl-N-(4-[N-((1r,4r)-4-methylcyclohexylcarbamoyl)-sulfamoyl]phenethyl)-2-oxo-2,5-dihydro-1H-pyrrole-1-carboxamide)] may be added in the therapy or review the dose of the metformin HCl² will be the strategy for controlling the levels of glucose in blood. Chemical structures of metformin HCl and glimepiride are presented in Figure 1a and 1b, respectively.

Different analytical methods, including chromatographic^3-10 and spectroscopic,^11-20 are reported for determination of metformin HCl and glimepiride in pharmaceutical dosage. Official methods for the determination of metformin HCl and glimepiride are available in British , ²¹ and US²² Pharmacopeia. A review of the use of various analytical techniques for analysis of glimepiride has also been published in the past.²³ Most of these methods are lengthy, expensive, time consuming and laborious besides requiring a toxic solvents thus resulting in retardation in the pace of quantification. Moreover for betterment of human health, USP recommended that there should be a less use of chemicals and reagents in pharmaceutical analysis, so as all the above mentioned methods for detection of active will be less favorable for daily analysis of pharmaceutical dosage form.

Fourier transform infrared spectroscopy (FTIR), in recent years, has proved to be a simple, rapid and green method for the quantification of many active constituents in pharmaceutical samples,^24-33 as in most of the cases, no prior sample preparation is required. In the present work, metformin HCl and glimepiride, the two well-known anti-diabetic drugs, have been evaluated directly by transmission FTIR in dosage form by preparing accurately weighed amount of KBr pellets with standards and samples.

Experimental

Material and methods

Chemical and reagents

Pure analytical grade standard sample of metformin HCl and glimepiride were obtained with courtesy of local Pharmaceutical Suppliers. Spectroscopic grade KBr (Merck Company) was used for drawing pellet of standards and samples to analyse on the FTIR. Locally manufactured pharmaceutical formulations containing metformin HCl and glimepiride as an active ingredient are used for analysis. The method is outlined as follow:

Preparation of sample for analysis

Calibration and validation samples of metformin HCl and glimepiride were grinded in a mortar to homogenize the powders properly. Suitable weight ratios (such as 1 mg of metformin HCl and 0.500 mg of glimepiride with 99 mg of KBr) were transferred to 13 mm die and pressed near 12000 lbs for 5 min to obtain a pellet. The pellet was then placed in the FTIR for recording the spectra. The commercial tablets were first ground and then processed further in the same way as the calibration samples.

FTIR parameters

FTIR spectrometer of Thermo Nicolet 6700 with removable KBr optics and equipped with Deuterated Tri Glycine Sulfate (DTGS) detector was used to analyze pellets of standards and sample with KBr. All spectra were taken in mid infrared (IR) region of 4000-400 cm^-1 accumulating 32 scans per spectrum at an optimum resolution of 4 cm^-1. Software named as OMNIC version 7.3 (Thermo Nicolet Analytical Instruments, Madison, WI) was used to record and operate FTIR spectra. Before each analysis, fresh background spectrum was taken with same instrumental conditions.

Calibrations

For metformin HCl

A set of eight standards with KBr in the form of pellet were prepared in concentration range of 0.300 mg to 3.100 mg for Beer's law calibration. Linear calibrations were obtained with chemometric software, Turbo Quant (TQ) Analyst.

For glimepiride

Similarly for glimepiride, a set of nine standards in the concentration range of 0.400 mg to 2.450 mg were prepared. Calibration was carried out by focusing on carbonyl band at 1708 cm^-1 to achieve best linearity and regression results. Although other bands were also selected for the calibration but statistical results of selected bands were excellent.

Software and data treatment

Nicolet TQ Analyst chemometric software was used to construct Beer's law. To evaluate the predictive ability of the developed models and to compare it, the relative standard errors of prediction (RSEP) were calculated. The RSEP_CAL and RSEP_VAL errors were determined for the calibration and validation data sets, respectively, which are shown in Figure 3 and ⁵. To check the performance of the developed model the cross-validation technique, leave-one-out, was applied.

Figure 4

Interday and intraday precision

The intra and interday precision were checked assay of the samples on the same day and on different days at different time intervals, respectively.

Roughness of methods

The robustness of the method was evaluated by assay of the sample, by a different analyst on same instrument on a different day.

Efficiency and recovery

Through standard addition method, the recovery was determined to check the efficiency of method. In this method, varying quantities of the standards were added to the known concentration of pharmaceutical sample and then by the proposed method total concentration was evaluated. Then this concentration is compared with the actual concentration. The recovery and efficiency was calculated by using equation 1.

where R is concentration of glimepiride recovered, C is total concentration after addition, B is the concentration of sample taken before addition and A is concentration of standard added.

Limit of detection and quantification

The analytical parameters, limit of detection (LOD) and quantification (LOQ) for the current method were determined by calculating the peak height of the IR bands at 3173 cm^-1 for metformin HCl and at 1708 cm^-1 in glimepiride at a fairly low concentration until the band just disappeared. The lowest amount from which the substantial signal was produced was analyzed eleven times and calculated using the equation 2. Likewise, LOQ of this method was determined with the equation 3.

where SD is standard deviation, C is the lowest concentration of standards that could be detected and P is the peak height.

Similarly:

In this study, AOAC Guidelines for Single Laboratory Validation of Chemical Methods for Dietary Supplements and Botanicals,³⁴ were used to calculate the coefficient of variation (CV, %) of the data set and used as relative standard deviation (RSD, %).

Results and Discussion

Metformin HCl and glimepiride have been successfully determined in this study by transmission FTIR using KBr pellets. Proposed methods for assessment of metformin HCl and glimepiride will be a worthwhile addition to the quality control and quality assurance in pharmaceutical industry.

FTIR spectra of pure standard and a drug sample containing metformin hydrochloride are shown in Figure 2a and 2b, respectively. Two characteristic bands of metformin hydrochloride were observed at 3370 cm^-1 and 3292 cm^-1 relative to the N–H primary stretching vibration. While a band at 3173 cm^-1 due to the N–H secondary stretching, and characteristic bands at 1622 cm^-1 and 1568 cm^-1 are assigned to C-N stretching. As the amount of metformin hydrochloride in the tablet was above 95%, there is no major interference of the matrix substances. Both spectra related to standard and drug sample of metformin hydrochloride were found to be comparable which is very obvious from Figure 2a and 2b.

Many bands and spectral regions were selected for the calibrations. However, selected bands and spectral regions provided best results for Beer's law calibrations. KBr disks with various concentrations of the metformin HCl standards in ranging between 0.300 mg to 3.100 mg were prepared. A band showing best results at 3173 cm^-1 for Beer's law with R² value of 0.996 and spectral region between 3550 cm^-1 to 2850 cm^-1 (the absorbance of N–H primary and secondary stretching vibrations).

The Beer's law calibration model was developed through computed fixed height in the TQ analyst program. Following achieved regression equation (equation 4) was applied on tablets obtained from the local commercial drug stores to calculate actual amount of metformin HCl.

The quantitative results of metformin HCl were also checked by selecting another relatively sharp band at 936.46 cm^-1, which is very clear in Figure 2a and 2b, but calibration was not so linear as compared to calibration of 3173 cm^-1 band.

An additional advantage of the comparison of Figure 2a and 2b is that it provides an opportunity to check the presence of impurity in drug samples as several substandard or expired drugs may be present in the market; hence it is well suited to distinguish even counterfeit drugs from the original sample. This quality is specific for a direct FTIR method, such as present one, over the generally used spectrophotometric and chromatographic methods.

Characteristic stretching bands at 3369 cm^-1 correspond to amine (-N-H), a band at 2931 cm^-1 relates to aromatic (-C-H) while bands at 1708, 1079 and 1544 cm^-1 correspond to amide (C=O), sulfoxides and aromatic (C=C), respectively.

From various selected bands, a specific band at 1708 cm^-1 with baseline from 1800 to 1600 due to carbonyl group of glimepiride was selected for Beer's law calibration because bands due to amine groups are not so intensive. Therefore, it has not provided good calibration for our selected range of standards. The concentration range of glimepiride standards for Beer's law was ranged between 0.400 mg to 2.450 mg in KBr pellets with the regression coefficient R² = 0.960. The result of calibration was found to be acceptable. As concentration of standards was increased, absorbance was found to increase accordingly. So, without any doubt, such calibrations could be boldly used for accurate quantification of active component in pharmaceutical dosage. The Beer's law calibration model is shown in ^{Figure 5}.

Following regression equation (equation 5) was achieved through Beer's law calibration plot, which was applied on the real pharmaceutical samples to calculate actual amount of glimepiride in tablet formulation.

The LOD and LOQ for metformin HCl were determined and found to be 0.138 mg and 0.572 mg, respectively. Similarly, for glimepiride these values were calculated as 0.001 and 0.006 respectively.

Beer's law calibrations were applied on real pharmaceutical samples containing metformin HCl and glimepiride as active ingredients. FTIR predictions given in Table 1 indicated that amount of active ingredient is almost comparable with quoted values on the packet of tablets.

The FTIR methods were further evaluated by standard addition method and results obtained from the study are summarized in Table 2. These were calculated in triplicate and mean values are quoted with standard deviation (SD). These results revealed excellent precision and accuracy of developed methods.

Results of intermediate precision and ruggedness are shown in Table 3 and 4, respectively. The standard deviation and recoveries for the both methods were found to be excellent indicating high degree of precision of the methods. The % recovery was between 97-102% indicating high degree of accuracy.

Conclusions

The present study reported simple, rapid and green methods for the analysis of two antidiabetic drugs, i.e., metformin HCl and glimepiride. Proposed methods are suitable for QC process in pharma industry. Therefore, as compared to other spectroscopic or chromatographic method, this is a direct, inexpensive and green approach in which costly chemicals and toxic solvents are totally avoided. Such types of FTIR applications have a strong potential to replace classical methods in quality assurance /quality control (QA/QC) for the analysis of active contents in pharmaceutical preparations.

Acknowledgements

The authors acknowledge with thanks to Prof M. Iqbal Chaudhary, Director, International Center for Chemical and Biological Sciences, University of Karachi, Karachi for providing the necessary laboratory facilities to accomplish this work.

Submitted on: June 2, 2014

Published online: August 12, 2014

• 1. Wild, S.; Roglic, G.; Green, A.; Sicree, R.; King, H.; Diabetes Care 2004, 27, 1047.
• ²
  http://www.nice.org.uk/nicemedia/pdf/cg66niceguideline.pdf accessed in July 2014.
  » link
• 3. Karthik, A.; Subramanian, G.; Mallikarjuna, R. C.; Krishnamurthy, B.; Ranjithkumar, A.; Musmade, P.; Surulivelrajan, M.; Karthikeyan, K.; Udupa, N.; Pak. J. Pharm. Sci. 2008, 21, 421.
• 4. Sakuntala, M. S. V.; Prasad, S. V. U. M.; Devi, S. S.; Kishore, Yadav; S. K.; Reddy, K. S.; J. Chem and Pharm. Res. 2012, 4 , 154.
• 5. Al-Rimawi, F.; Talanta 2009, 79, 1368.
• 6. Jain, D.; Jain, S.; Jain, D.; Amin, M.; J. Chromatogr. Sci. 2008, 46 , 501.
• 7. Cheng, C. L.; Chou, C. H.; J. Chromatogr. B. Biomed. Sci. App. 2001, 762, 51.
• 8. Vesterqvist, O.; Nabbie, F.; Swanson, B.; J. Chromatogr. B. Biomed. Sci. Appl. 1998, 716, 299.
• 9. Melis, V.; Usach, I.; Peris, J.-E. In High-Performance Liquid Chromatography (HPLC): Principles, Practices and Procedures, Zuo, Y., ed.; Nova Science Publishers, Inc.: New York, 2014, ch. 4.
• 10. onfilio, R.; Araújo, M. B.; Salgado, H. R. N.; J. AOAC Int. 2013, 96, 960.
• 11. Mubeen, G.; Noor, K.; Indian. J. Pharm. Sci. 2009, 71, 100.
• 12. Bhamare, P. C.; Bari, S. B.; Natarajan, S.; Patil, A. A.; Patil, S. H.; Shirode, P. T.; Asian J. Biochem and Pharm. Res. 2011, 1, 115.
• 13. Loni, A. B.; Ghante, M. R.; Sawant, S. D.; Pharma Chem. 2012, 4, 854.
• 14. Arayne, M. S.; Sultana, N.; Zuberi, M. H.; Siddiqui, F. A.; Indian J. Pharm. Sci. 2009, 71, 331.
• 15. Umapathi, P.; Ayyappan, J.; Quine, S. D.; Trop. J. Pharm. Res. 2012, 11, 107.
• 16. Bonfilio, R.; Araújo, M. B.; Salgado, H. R. N.; J. Braz. Chem. Soc. 2011, 22, 292.
• 17. Induri, M.; Bhagavan, R. M.; Rajendra, P. Y.; Pavankumar, R. K.; E-J. Chem. 2012, 9, 993.
• 18. Madhuri, D. G.; Res. J. Pharm. Tech. 2011, 4, 1865.
• 19. Bhargavi, S.; Suryasagar, G.; Sowmya, D. K.; Ashok, K.; Nama, S.; Int. J. Pharm. Sci. Rev. Res. 2013, 21, 131.
• 20. Kishore, L.; Kaur, N.; Der Pharmacia Lettre 2011, 3, 276.
• 21. British Pharmacopoeia; Stationery Office: London, 2009.
• ²²
  The United States Pharmacopoeia, USP 25 rev., The United States Pharmacopoeia Convention: Rockville, 2002.
• 23. Bonfilio, R.; de Araújo, M. B.; Salgado, H. R.; Ther. Drug Monit 2010, 32, 550.
• 24. Ayala, C.; Brunetto, M. R.; Ovalles, F. Y.; Gallignani, M.; Rev. Téc. Ing. Univ. Zulia 2009, 32, 238.
• 25. Konoz, E.; Hossein, A.; Sarrafi, M.; Samadizadeh, M.; Boreiri, S.; E-J. Chem. 2012 , 9, 2232.
• 26. Mallah, M. A.; Sherazi, S. T. H.; Mahesar, S. A.; Rauf, A.; Pak. J. Anal. Environ. Chem. 2011, 12, 61.
• 27. Mallah, M. A.; Sherazi, S. T. H.; Mahesar, S. A.; Rauf, A.; J. Chem. Soc. Pak . 2012, 34, 556.
• 28. Zuo, Y.; Zhang, L.; Wu, J.; Johnathan, W.; Suzanne, F. M., Christopher, R.; Abstracts of Papers of the American Chemical Society, 2005, 229, 130.
• 29. Prasad, P. R.; Murarilal, K. B.; Rajani, K.; J. Chem. Pharm. Res. 2012, 4, 180.
• 30. Kogawa, A. C.; Salgado, H. R. N.; Phys. Chem. 2013, 3, 1.
• 31. Moreno, A. H.; Salgado, H. R. N.; Phys. Chem. 2012, 2, 6.
• 32. Tótoli, E. G.; Salgado, H. R. N.; Phys. Che m. 2012, 2, 103.
• 33. Vieira, D. C. M.; Ricarte, P. C.; Salgado, H. R. N.; Adv. Anal. Chem. 2012, 2, 80.
• ³⁴
  http://www.eoma.aoac.org/app_k.pdf, accessed in August 2014.
  » link

Publication Dates

• Publication in this collection
  13 Nov 2014
• Date of issue
  Nov 2014

History

• Accepted
  12 Aug 2014
• Received
  02 June 2014