Determination of Gefitinib Using Routine and Greener Stability-Indicating HPTLC Methods: A Comparative Evaluation of Validation Parameters
Abstract
:1. Introduction
2. Materials and Methods
2.1. Materials
2.2. Instrumentation and Chromatographic Procedures
2.3. Calibration Curves and Quality Control (QC) Sample for GFT
2.4. Sample Preparation for the Determination of GFT in Marketed Tablet Dosage Forms
2.5. Validation Studies
2.6. Forced Degradation Studies
2.7. Application of Routine and Greener HPTLC Assays in the Determination of GFT in Marketed Tablets
2.8. Greenness Estimation
3. Results and Discussion
3.1. Method Development and Optimization
3.2. Validation Studies
3.3. Forced Degradation Studies
3.4. Application of Routine and Greener HPTLC Assays in GFT Estimation in Marketed Tablets
3.5. Greenness Estimation
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Trummer, B.J.; Iyer, V.; Balu-Iyer, S.V.; Connor, R.O.; Straubinger, R.M. Physicochemical properties of EGF receptor inhibitors and development of nanoliposomal formulation of gefitinib. J. Pharm. Sci. 2012, 101, 2763–2776. [Google Scholar] [CrossRef] [Green Version]
- Srinivas, N.S.K.; Verma, R.; Kulyadi, G.P.; Kumar, L. A quality by design approach on polymeric nanocarrier delivery of gefitinib: Formulation, in vitro, and in vivo characterization. Int. J. Nanomed. 2017, 12, 15–18. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Arora, E.M.; Scholar, E.M. Role of tyrosine kinase inhibitors in cancer therapy. J. Pharmacol. Exp. Ther. 2005, 315, 971–979. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Schaeybroeck, S.V.; Karaiskou-McCaul, A.; Kelly, D.; Longley, D.; Galligan, L.; van Cutsem, E.; Johnston, P. Epidermal growth factor receptor activity determines responses of colorectal cancer cells to gefitinib alone and in combination with chemotherapy. Clin. Cancer Res. 2005, 11, 7480–7489. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhang, G.; Xie, X.; Liu, T.; Yang, J.; Jiao, S. Effects of pemetrexed, gefitinib and their combination on human colorectal cancer cells. Cancer Chemother. Pharmacol. 2013, 72, 767–775. [Google Scholar] [CrossRef]
- Li, X.; Wang, J.; Li, S.; Liu, Z.; Zheng, Z.; Zhang, Y. Development and evaluation of multifunctional poly(lactic-co-glycolic acid) nanoparticles embedded in carboxymethyl β-glucan porous microcapsules as a novel drug delivery system for gefitinib. Pharmaceutics 2019, 11, 469. [Google Scholar] [CrossRef] [Green Version]
- Alshehri, S.; Alanazi, A.; Elzayat, E.M.; Altamimi, M.A.; Imam, S.S.; Hussain, A.; Alqahtani, F.; Shakeel, F. Formulation, in vitro and in vivo evaluation of gefitinib solid dispersions prepared using different techniques. Processes 2021, 9, 1210. [Google Scholar] [CrossRef]
- Sordella, R.; Bell, D.W.; Haber, D.A.; Settleman, J. Gefitinib-sensitizing EGFR mutations in lung cancer activate anti-apoptotic pathways. Science 2004, 305, 1163–1167. [Google Scholar] [CrossRef]
- Alanazi, A.; Alshehri, S.; Altamimi, M.; Shakeel, F. Solubility determination and three dimensional Hansen solubility parameters of gefitinib in different organic solvents: Experimental and computational approaches. J. Mol. Liq. 2020, 299, 112211. [Google Scholar] [CrossRef]
- Varansi, M.B.; Khan, M.A.; Jangala, V.R.; Teja, B.B. Visible spectrophotometric determination of gefitinib in bulk drug and pharmaceutical formulations. Int. J. Chem. Sci. 2009, 7, 2449–2454. [Google Scholar]
- Patra, S.R.; Bali, A.; Saha, M. Derivative spectrophotometric methods for determination of gefitinib in bulk and in formulation. J. Appl. Spectroscop. 2021, 88, 1088–1094. [Google Scholar] [CrossRef]
- Sreedevi, A.; Rao, A.L.; Kalyani, L. Development and validation of stability indicating HPLC method for estimation of gefitinib in bulk and its pharmaceutical formulations. Int. J. Pharm. Chem. Biol. Sci. 2013, 3, 1305–1314. [Google Scholar]
- Varasala, S.M.; Mangamma, K. Analytical method development and validation for the estimation of gefitinib by RP-HPLC method in tablet dosage form. Int. J. Pharm. Biol. Sci. 2013, 3, 198–201. [Google Scholar]
- Siva Kumar, R.; Yogeshwara, K.R.; Gangrade, M.; Kanyawar, N.; Ganesh, S.; Jayachandran, J. Development and validation of stability indicating HPLC method for gefitinib and its related compounds and characterization of degradation impurities. J. Pharm. Drug Deliv. Res. 2017, 6, 1000161. [Google Scholar]
- Aluri, S.G.; Annapurna, M.M. A new stability indicating RP-HPLC method for the estimation of gefitinib tablets using an ion pairing agent. Res. J. Pharm. Technol. 2021, 14, 5449–5456. [Google Scholar] [CrossRef]
- Chandrashekara, K.A.; Udupi, A.; Reddy, C.G. Separation and estimation of process-related impurities of gefitinib by reverse-phase high-performance liquid chromatography. J. Chromatogr. Sci. 2014, 52, 799–805. [Google Scholar] [CrossRef] [Green Version]
- Reddy, C.N.; Prasad, P.R.; Sredhar, N.Y. Voltametric behavior of gefitinib and its adsorptive stripping voltametric determination in pharmaceutical formulations and urine samples. Int. J. Pharm. Pharm. Sci. 2011, 3, 141–145. [Google Scholar]
- Verma, N.; Rai, A.K.; Kaushik, V.; Brunner, D.; Chahar, K.R.; Pandey, J.; Goyal, P. Identification of gefitinib off-targets using a structure-based systems biology approach; Their validation with reverse docking and retrospective data mining. Sci. Rep. 2016, 6, 33949. [Google Scholar] [CrossRef] [Green Version]
- Bai, F.; Iacono, L.C.; Johnston, B.; Stewart, C.F. Determination of gefitinib in plasma by liquid chromatography with a C12 column and electrospray tandem mass spectrometry detection. J. Liq. Chromatogr. Rel. Technol. 2004, 27, 2743–2758. [Google Scholar] [CrossRef]
- Wang, L.-Z.; Lim, M.Y.-X.; Chin, T.-M.; Thuya, W.-L.; Nye, P.-L.; Wong, A.; Chan, S.-Y.; Goh, B.-C.; Ho, P.C. Rapid determination of gefitinib and its main metabolite, o-desmethyl gefitinib in human plasma using liquid chromatography tandem-mass spectrometry. J. Chromatogr. B 2011, 879, 2155–2161. [Google Scholar] [CrossRef]
- Hayashi, H.; Kita, Y.; Iihara, H.; Yanase, K.; Ohno, Y.; Hirose, C.; Yamada, M.; Todoroki, K.; Kitaichi, K.; Minatoguchi, S.; et al. Simultaneous and rapid determination of gefitinib, erlotinib and afatinib plasma levels using liquid chromatography/tandem mass spectrometry in patients with non-small-cell lung cancer. Biomed. Chromatogr. 2016, 30, 1150–1154. [Google Scholar] [CrossRef] [PubMed]
- Zheng, N.; Zhao, C.; He, X.-R.; Jiang, S.-T.; Han, S.-Y.; Xu, G.-B.; Li, P.-P. Simultaneous determination of gefitinib and its major metabolites in mouse plasma by HPLC-MS/MS and its application to a pharmacokinetics study. J. Chromatogr. B 2016, 1011, 215–222. [Google Scholar] [CrossRef] [PubMed]
- Liu, Y.; Liu, H.; Xia, Z.; Wang, Z.; Yun, Y.; Zhang, G.; Huang, L.; Gao, S.; Chen, W. Simultaneous and rapid determination of six tyrosine kinase inhibitors in patients with non-small cell lung cancer using HPLC-MS/MS. Int. J. Anal. Chem. 2021, 2021, 5524361. [Google Scholar] [CrossRef]
- Wang, C.; Zhang, J.; Zhou, S.; Yu, L.; Han, F.; Ling, R.; Ling, J. Tentative identification of gefitinib metabolites in non-small-cell lung cancer patient plasma using ultra-performance liquid chromatography coupled with triple quadrupole time-of-flight mass spectrometry. PLoS ONE 2020, 15, e0236523. [Google Scholar] [CrossRef] [PubMed]
- Borg, H.; Zambo, D.; Elmansi, H.; Hashem, H.M.; Nasr, J.J.; Walash, M.I.; Bigall, N.C.; Belal, F. Preconcentration and detection of gefitinib anti-cancer drug traces from water and human plasma samples by means of magnetic nanoparticles. Nanomaterials 2020, 10, 1196. [Google Scholar] [CrossRef]
- Abdelrahman, M.M.; Abdelwahab, N.S.; Hegazy, M.A.; Fares, M.Y.; El-Sayed, G.M. Determination of the abused intravenously administered madness drops (tropicamide) by liquid chromatography in rat plasma; An application to pharmacokinetic study and greenness profile assessment. Microchem. J. 2020, 159, 105582. [Google Scholar] [CrossRef]
- Duan, X.; Liu, X.; Dong, Y.; Yang, J.; Zhang, J.; He, S.; Yang, F.; Wang, Z.; Dong, Y. A green HPLC method for determination of nine sulfonamides in milk and beef, and its greenness assessment with analytical eco-scale and greenness profile. J. AOAC Int. 2020, 103, 1181–1189. [Google Scholar] [CrossRef]
- Pena-Pereira, F.; Wojnowski, W.; Tobiszewski, M. AGREE-Analytical GREEnness metric approach and software. Anal. Chem. 2020, 92, 10076–10082. [Google Scholar] [CrossRef]
- Alam, P.; Salem-Bekhit, M.M.; Al-Joufi, F.A.; Alqarni, M.H.; Shakeel, F. Quantitative analysis of cabozantinib in pharmaceutical dosage forms using green RP-HPTLC and green NP-HPTLC methods: A comparative evaluation. Sus. Chem. Pharm. 2021, 21, 100413. [Google Scholar] [CrossRef]
- Foudah, A.I.; Shakeel, F.; Alqarni, M.H.; Alam, P. A rapid and sensitive stability-indicating green RP-HPTLC method for the quantitation of flibanserin compared to green NP-HPTLC method: Validation studies and greenness assessment. Microchem. J. 2021, 164, 105960. [Google Scholar] [CrossRef]
- International Conference on Harmonization (ICH), Q2 (R1): Validation of Analytical Procedures–Text and Methodology; ICH Secretariat: Geneva, Switzerland, 2005.
- Alam, P.; Shakeel, F.; Alqarni, M.H.; Foudah, A.I.; Faiyazuddin, M.; Alshehri, S. Rapid, sensitive, and sustainable reversed-phase HPTLC method in comparison to the normal-phase HPTLC for the determination of pterostilbene in capsule dosage form. Processes 2021, 9, 1305. [Google Scholar] [CrossRef]
Routine HPTLC | |||
Mobile Phase | As | N/m | Rf |
Ch/MOH (45:55, v/v) | 1.248 ± 0.0300 | 1585 ± 1.183 | 0.4400 ± 0.0200 |
Ch/MOH (50:50, v/v) | 1.247 ± 0.0300 | 1598 ± 1.194 | 0.4300 ± 0.0200 |
Ch/MOH (55:45, v/v) | 1.246 ± 0.0200 | 1642 ± 2.014 | 0.4200 ± 0.0200 |
Ch/MOH (60:40, v/v) | 1.245 ± 0.0300 | 1692 ± 2.112 | 0.4100 ± 0.0200 |
Ch/MOH (65:35, v/v) | 1.244 ± 0.0300 | 1763 ± 2.162 | 0.4000 ± 0.0100 |
Ch/MOH (70:30, v/v) | 1.243 ± 0.0200 | 1854 ± 2.182 | 0.3900 ± 0.0100 |
Ch/MOH (75:25, v/v) | 1.042 ± 0.0300 | 1985 ± 2.192 | 0.3800 ± 0.0100 |
Ch/MOH (80:20, v/v) | 1.241 ± 0.0300 | 2014 ± 2.213 | 0.3700 ± 0.0100 |
Ch/MOH (85:15, v/v) | 1.041 ± 0.0200 | 4972 ± 4.141 | 0.3600 ± 0.0100 |
Ch/MOH (90:10, v/v) | 1.240 ± 0.0300 | 2278 ± 2.321 | 0.3500 ± 0.0100 |
Greener HPTLC | |||
EOH/CYH (45:55, v/v) | 1.267 ± 0.0300 | 1498 ± 1.844 | 0.5000 ± 0.0200 |
EOH/CYH (50:50, v/v) | 1.266 ± 0.0300 | 1512 ± 1.854 | 0.4900 ± 0.0200 |
EOH/CYH (55:45, v/v) | 1.265 ± 0.0300 | 1591 ± 1.922 | 0.4800 ± 0.0200 |
EOH/CYH (60:40, v/v) | 1.264 ± 0.0200 | 1666 ± 2.101 | 0.4700 ± 0.0200 |
EOH/CYH (65:35, v/v) | 1.263 ± 0.0200 | 1723 ± 2.115 | 0.4600 ± 0.0200 |
EOH/CYH (70:30, v/v) | 1.262 ± 0.0200 | 1852 ± 2.171 | 0.4500 ± 0.0100 |
EOH/CYH (75:25, v/v) | 1.261 ± 0.0200 | 1977 ± 2.202 | 0.4400 ± 0.0100 |
EOH/CYH (80:20, v/v) | 1.080 ± 0.0200 | 4768 ± 3.972 | 0.4300 ± 0.0100 |
EOH/CYH (85:15, v/v) | 1.269 ± 0.0300 | 2042 ± 2.542 | 0.4200 ± 0.0100 |
EOH/CYH (90:10, v/v) | 1.268 ± 0.0300 | 2128 ± 2.612 | 0.4100 ± 0.0100 |
Parameters | Routine HPTLC | Greener HPTLC |
---|---|---|
Linearity range (ng/band) | 30–700 | 20–1400 |
Regression equation | y = 15.29x + 895.96 | y = 21.31x + 614.79 |
R2 | 0.9945 | 0.9964 |
R | 0.9972 | 0.9981 |
SE of slope | 0.3838 | 0.3389 |
SE of intercept | 4.589 | 2.213 |
95% CI of slope | 13.63–16.94 | 19.85–22.76 |
95% CI of intercept | 876.2–915.7 | 605.2–624.3 |
LOD ± SD (ng/band) | 11.14 ± 0.4100 | 6.720 ± 0.1000 |
LOQ ± SD (ng/band) | 33.42 ± 1.230 | 20.16 ± 0.3000 |
Conc. (ng/Band) | Conc. Found (ng/Band) ± SD | Recovery (%) | CV (%) |
---|---|---|---|
Routine HPTLC | |||
50 | 51.71 ± 1.640 | 103.4 | 3.171 |
400 | 384.5 ± 9.510 | 96.13 | 2.473 |
700 | 718.5 ± 16.14 | 102.6 | 2.246 |
Greener HPTLC | |||
50 | 49.68 ± 0.54 | 99.36 | 1.086 |
400 | 406.3 ± 3.840 | 101.5 | 0.9450 |
1400 | 1384.3 ± 12.31 | 98.88 | 0.8892 |
Conc. (ng/Band) | Intraday Precision | Inter-Day Precision | ||||
---|---|---|---|---|---|---|
Conc. (ng/Band) | SE | CV (%) | Conc. (ng/Band) | SE | CV (%) | |
Routine HPTLC | ||||||
50 | 48.13 ± 1.610 | 0.6574 | 3.345 | 52.21 ± 1.71 | 0.6982 | 3.275 |
400 | 418.5 ± 11.31 | 4.618 | 2.702 | 382.4 ± 11.94 | 4.875 | 3.122 |
700 | 681.4 ± 15.64 | 6.386 | 2.295 | 721.3 ± 16.58 | 6.770 | 2.298 |
Greener HPTLC | ||||||
50 | 50.31 ± 0.4200 | 0.1714 | 0.8348 | 48.98 ± 0.4600 | 0.1878 | 0.9391 |
400 | 388.9 ± 3.130 | 1.278 | 0.8047 | 406.2 ± 3.610 | 1.474 | 0.8886 |
1400 | 1411 ± 11.14 | 4.548 | 0.7893 | 1392 ± 11.92 | 4.867 | 0.8559 |
Conc. (ng/Band) | Mobile Phase Composition (Chloroform-Methanol) | Results | ||||
---|---|---|---|---|---|---|
Original | Used | Conc. (ng/Band) | CV (%) | Rf | ||
Routine HPTLC | ||||||
87:13 | +2.0 | 385.4 ± 10.58 | 2.745 | 0.3500 | ||
400 | 85:15 | 85:15 | 0.0 | 392.6 ± 11.69 | 2.977 | 0.3600 |
83:17 | −2.0 | 412.5 ± 12.12 | 2.937 | 0.3700 | ||
Greener HPTLC | ||||||
Mobile phase composition (ethanol-cyclohexane) | ||||||
82:18 | +2.0 | 391.2 ± 3.740 | 0.9559 | 0.4200 | ||
400 | 80:20 | 80:20 | 0.0 | 402.3 ± 3.820 | 0.9495 | 0.4300 |
78:22 | −2.0 | 406.9 ± 3.920 | 0.9632 | 0.4400 |
Stress Condition | Number of Degradation Products (Rf) | GFT Rf | GFT Remaining (ng/Band) | GFT Recovered (%) |
---|---|---|---|---|
1M HCl | 0 | 0.3700 | 400.0 | 100.0 ± 0.0000 |
1M NaOH | 0 | 0.3700 | 400.0 | 100.0 ± 0.0000 |
30% H2O2 | 3 (0.0700, 0.2100, 0.2400) | 0.3600 | 208.9 | 52.23 ± 1.740 |
Thermal | 0 | 0.3700 | 400.0 | 100.0 ± 0.0000 |
Stress Condition | Number of Degradation Products (Rf) | GFT Rf | GFT Remaining (ng/Band) | GFT Recovered (%) |
---|---|---|---|---|
1M HCl | 0 | 0.4300 | 400.0 | 100.0 ± 0.0000 |
1M NaOH | 0 | 0.4300 | 400.0 | 100.0 ± 0.0000 |
30% H2O2 | 3 (0.0500, 0.1200, 0.6900) | 0.4100 | 190.7 | 47.68 ± 1.630 |
Thermal | 0 | 0.4300 | 400.0 | 100.0 ± 0.0000 |
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Alam, P.; Shakeel, F.; Mahdi, W.A.; Foudah, A.I.; Alqarni, M.H.; Aljarba, T.M.; Alshehri, S.; Ghoneim, M.M. Determination of Gefitinib Using Routine and Greener Stability-Indicating HPTLC Methods: A Comparative Evaluation of Validation Parameters. Processes 2022, 10, 762. https://doi.org/10.3390/pr10040762
Alam P, Shakeel F, Mahdi WA, Foudah AI, Alqarni MH, Aljarba TM, Alshehri S, Ghoneim MM. Determination of Gefitinib Using Routine and Greener Stability-Indicating HPTLC Methods: A Comparative Evaluation of Validation Parameters. Processes. 2022; 10(4):762. https://doi.org/10.3390/pr10040762
Chicago/Turabian StyleAlam, Prawez, Faiyaz Shakeel, Wael A. Mahdi, Ahmed I. Foudah, Mohammed H. Alqarni, Tariq M. Aljarba, Sultan Alshehri, and Mohammed M. Ghoneim. 2022. "Determination of Gefitinib Using Routine and Greener Stability-Indicating HPTLC Methods: A Comparative Evaluation of Validation Parameters" Processes 10, no. 4: 762. https://doi.org/10.3390/pr10040762