Development and Validation of UV Spectrophotometric Method for Determination of Chrysin and Its Solubility Studies
Abstract
The present work is based on the method development and validation of the UV-spectrophotometric method for the quantitative estimation of chrysin. We studied how the nature of the solvent affects chrysin solubility. The stock and diluted solutions were scanned using a UV visible spectrophotometer to obtain the λmax. The absorbance of the samples was recorded to obtain a calibration curve, which was followed by regression using MS Excel and Sigma stat software. The method developed by this process was further validated using parameters such as linearity, precision, limit of detection, limit of quantification, accuracy, and ruggedness. The solubility of chrysin was checked at 35oC in different oils, solvents, and co-solvents. The λmax of chrysin in methanol was found to be 367 nm. The calibration curve of the drug follows linearity (2–10 μg/mL) with a correlation coefficient of 0.991. At three different levels, i.e., 80, 100, and 120%, the method’s accuracy was checked utilizing the percent recovery (97–99.5%). The precision studies were carried out in terms of intraday and interday variations. The ruggedness of the proposed method was studied by taking two. The solubility of chrysin was found to be the maximum in methanol (216.80±0.0097 μg/mL) among the oils, solvents, and co-solvents used. Thus, based on the experiments done, the developed method was observed to be accurate, precise, and reproducible. The viscosity of the solvent and the possibility of hydrogen bonding are two crucial factors that affected the solubility of chrysin in the solvents.
Keywords
About the Authors
A. BansalIndia
Noida
N. Srivastava
India
Noida
K. Nagpal
India
Noida
References
1. H. Kaur, A. Thakkar, K. Nagpal, JPTRM, 7, 1–5 (2019).
2. S. Nagdev, M. Bhurat, R. Usman, K. Gupta, U. Gandagulae, A Textbook of Pharmaceutical Quality Assurance, S. Vikas and Company, India, 97–99 (2019).
3. H. Zhu, Y. Wang, Y. Liu, Y. Xia, T. Tang, Food Anal. Methods, 3, 90–97 (2010).
4. K. N. Prashanth, K. Basavaiah, C. M. Xavier, JAAUBAS, 1, 43–52 (2014).
5. Y. U. Yuan, L. U. Houding, C. H. Lijuan, Chin. J. Anal. Chem., 26, 489–493 (2008).
6. S. Roy, A. Sil, T. Chakraborty, J. Cell. Physiol., 4, 4888–4909 (2019).
7. S. Lin, L. Zeng, G. Zhang, Y. Liao, D. Gong, Spectrochim. Acta A: Mol. Biomol. Spectrosc., 178, 71–78 (2017).
8. X. Liang, Y. Zhang, W. Chen, P. Cai, S. Zhang, X. Chen, S. Shi, J. Chromatogr. A, 1385, 69–76 (2015).
9. S. Feizi, M. Jabbari, A. Farajtabar, J. Mol. Liq., 1, 478–483 (2016).
10. A. Panche, A. Diwan, S. Chandra, JNS, 5, 1–15 (2016).
11. F. Bonetti, G. Brombo, G. Zuliani, In: Nootropics, Functional Foods, and Dietary Patterns for Prevention of Cognitive Decline. In Nutrition and Functional Foods for Healthy Aging, Ed. R. R. Watson, Academic Press, 211–232 (2017).
12. H. Cho, C. W. Yun, W. K. Park, Pharm. Res., 1, 37–43 (2004).
13. U.S. National Library of Medicine, National Center for Biotechnology Information, https://pubchem.ncbi.nlm.nih.gov/#query=chrysin.
14. V. Nikolovska, L. J. Klisarova, L. Suturkova, K. Dorevski, Anal. Lett., 29, 97–115 (1996).
15. L. Zhou, P. Zhang, G. Yang, R. Lin, W. Wang, T. Liu, L. Zhang, J. Zhang, J. Chem. Eng. Data, 59, 2215–2220 (2014).
16. G. T. Castro, F. H. Ferretti, S. Blanco, Spectrochim. Acta A: Mol. Biomol. Spectrosc., 62, 657–665 (2005).
17. L. Zhou, P. Zhang, G. Yang, R. Lin, W. Wang, T. Liu, J. Zhang, J. Chem. Eng. Data, 59, 2215–2220 (2014).
18. G. M. Sulaiman, M. S. Jabir, A. H. Hameed, Artif. Cells Nanomed. Biotechnol., 46, 708–720 (2018).
19. R. Chadha, Y. Bhalla, A. Nandan, K. Chadha, M. Karan, J. Pharm. Biomed. Anal., 134, 361–371 (2017).
20. S. M. Kim, J. I. Jung, C. Chai, J. Y. Imm, Nutrients, 11, 25–49 (2019).
21. N. Bolourchian, M. M. Mahboobian, S. Dadashzadeh, IJPR, 12, 11–15 (2013).
22. S. H. Lee, Y. S. Lee, J. G. Song, H. K. Han, Curr. Drug. Deliv., 16, 86–92 (2019).
23. M. Maleque, M. R. Hasan, F. Hossen, S. Safi, J. Pharm. Anal., 2, 454–457 (2012).
24. S. H. Patil, M. V. Janjale, J. Pharm. Anal., 2, 470–477 (2012).
25. National Center for Biotechnology Information. PubChem Database. Methanol, CID=887, https://pubchem.ncbi.nlm.nih.gov/compound/Methanol, accessed on Mar. 8, 2020 (2020).
26. G. M. Sulaiman, M. S. Jabir, A. H. Hameed, Artif. Cells Nanomed. Biotechnol., 46, 708–720 (2018).
27. L. A. Javid, P. Soltanahmadi, M. Dadashpour, A. Shahriar, F. Raana, S. Javidfar, N. Zarghami, Nutr. Cancer, 69, 1–10 (2017).
28. ICH guidelines for Validation of analytical procedures: text and methodology Q2(R1).
29. A. Azeem, M. Rizwan, F. J. Ahmad, AAPS Pharm. Sci. Technol., 10, 69–76 (2009).
30. P. Jain, A. Chaudhari, S. Patel, Z. Patel, D. Patel, Pharm. Methods, 2, 198–202 (2011).
31. S. K. Vashist, H. J. T. Luong, In: Handbook of Immunoassay Technologies, Ch. 4, Academic Press, 81–95 (2018).
32. M. Cheze, J. M. Gaulier, In: Toxicological Aspects of Drug-Facilitated Crimes, Ed. P. Kintz, Ch. 8, Academic Press, 181–222 (2014).
33. S. Song, K. Gao, R. Niu, J. Wang, J. Zhang, C. Gao, B. Yang, X. Liao, Mater. Sci. Eng. C. Mater. Biol. Appl., 106, 110–161 (2020).
34. S. Song, K. Gao, R. Niu., W. Yi, J. Zhang, C. Gao, B. Yang, X. Liao. J. Mol. Liq., 296, 111993 (2019).
35. H. W. Xiang, A. Laesecke, M. L. Huber, J. Phys. Chem. Ref. Data, 35, 1597–1620 (2006).
36. I. Kaur, S. Wakode, H. Singh, Pharm. Methods, 6, 82–86 (2015).
37. E. Yeom, Y. J. Kang, S. J. Lee, Biomicrofluidics, 8, 34–110 (2014).
38. N. Siddiqui, A. Ahmad, Int. J. Sci. Environ. Technol., 2, 1318–1326 (2013).
39. A. B. Mandal, S. Gupta, S. P. Moulik, Indian J. Chem., 24, 670–673 (1985).
Review
For citations:
Bansal A., Srivastava N., Nagpal K. Development and Validation of UV Spectrophotometric Method for Determination of Chrysin and Its Solubility Studies. Zhurnal Prikladnoii Spektroskopii. 2022;89(1):134-142.
Email this article 