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Anwar M, Rimsha G, Majeed MI, Alwadie N, Nawaz H, Majeed MZ, Rashid N, Zafar F, Kamran A, Wasim M, Mehmood N, Shabbir I, Imran M. Rapid Identification and Quantification of Adulteration in Methyl Eugenol using Raman Spectroscopy Coupled with Multivariate Data Analysis. ACS OMEGA 2024; 9:7545-7553. [PMID: 38405541 PMCID: PMC10882614 DOI: 10.1021/acsomega.3c06335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 01/09/2024] [Accepted: 01/26/2024] [Indexed: 02/27/2024]
Abstract
Identification of adulterants in commercial samples of methyl eugenol is necessary because it is a botanical insecticide, a tephritid male attractant lure that is used to attract and kill invasive pests such as oriental fruit flies and melon flies on crops. In this study, Raman spectroscopy was used to qualitatively and quantitatively assess commercial methyl eugenol along with adulterants. For this purpose, commercial methyl eugenol was adulterated with different concentrations of xylene. The Raman spectral features of methyl eugenol and xylene in liquid formulations were examined, and Raman peaks were identified as associated with the methyl eugenol and adulterant. Principal component analysis (PCA) and partial least-squares regression analysis (PLSR) have been used to qualitatively and quantitatively analyze the Raman spectral features. PCA was applied to differentiate Raman spectral data for various concentrations of methyl eugenol and xylene. Additionally, PLSR has been used to develop a predictive model to observe a quantitative relationship between various concentrations of adulterated methyl eugenol and their Raman spectral data sets. The root-mean-square errors of calibration and prediction were calculated using this model, and the results were found to be 1.90 and 3.86, respectively. The goodness of fit of the PLSR model is found to be 0.99. The proposed approach showed excellent potential for the rapid, quantitative detection of adulterants in methyl eugenol, and it may be applied to the analysis of a range of pesticide products.
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Affiliation(s)
- Muntaha Anwar
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Gull Rimsha
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Irfan Majeed
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Najah Alwadie
- Department
of Physics, College of Science, Princess
Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
| | - Haq Nawaz
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Zeeshan Majeed
- Department
of Entomology, College of Agriculture, University
of Sargodha, Sargodha 40100, Pakistan
| | - Nosheen Rashid
- Department
of Chemistry, University of Education, Faisalabad
Campus, Faisalabad 38000, Pakistan
| | - Fareeha Zafar
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Ali Kamran
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Wasim
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Nasir Mehmood
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Ifra Shabbir
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Imran
- Department
of Chemistry, Faculty of Science, King Khalid
University, P.O. Box
9004, Abha 61413, Saudi Arabia
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Liang J, He N, Xie L, Wang Z, Hu R, Deng G. Rapid assessment of residual solvent content in the TEGDN dual-base propellants by near-infrared reflectance spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 307:123648. [PMID: 37979537 DOI: 10.1016/j.saa.2023.123648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 11/09/2023] [Accepted: 11/12/2023] [Indexed: 11/20/2023]
Abstract
Excessive residual solvent (RS) levels in triethyleneglycol dinitrate (TEGDN) dual-base propellants can significantly impair combustion performance. This work aimed to develop a rapid and accurate model for detecting the RS content in the TEGDN dual-base propellants using near-infrared (NIR) spectroscopy in the reflectance mode. The optimal wavelength range for modelling, spanning from 1124.9-1230.2 nm and 1335.5-1527.5 nm, was identified based on absorption peaks characteristic of TEGDN dual-base propellant samples and RS. To enhance the quality of the data, we determined optimal window sizes for pre-processing methods: derivative pre-processing and Savitzky-Golay (S-G) smoothing pre-processing. After evaluating the performance of different pre-treatment methods, we found that the model employing multiple scattering corrections (MSC) in conjunction with first-order derivative (FD) pre-processing demonstrated superior results. The partial least squares (PLS) method was used to build the RS model with an optimal number of factors of 6. For the developed RS model, the root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) were 0.019 and 0.024, respectively. The determination coefficient of calibration (Rc2) and the determination coefficient of cross-validation (Rcv2) were 0.968 and 0.952, respectively. In assessing the validation set using the developed model, we observed a root mean square error of prediction (RMSEP) of 0.025 and a determination coefficient of prediction (Rp2) of 0.958. Importantly, the relative error between the predicted values obtained through the NIR method and the measured values from the reference method consistently remained below 2 % under all circumstances. Consequently, the NIR-based RS model developed in this study offers a rapid and efficient means of detecting RS content in TEGDN dual-base propellants, facilitating judgment regarding the qualification of RS content.
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Affiliation(s)
- Jinhua Liang
- National Special Superfine Powder Engineering Research Center, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China
| | - Narenchaogetu He
- Hubei Institute of Aerospace Chemistry and Technology, Qinghe Road, Xiangyang 441100, China
| | - Liang Xie
- National Special Superfine Powder Engineering Research Center, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China
| | - Zhaoxuan Wang
- National Special Superfine Powder Engineering Research Center, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China
| | - Rongjian Hu
- National Special Superfine Powder Engineering Research Center, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China
| | - Guodong Deng
- National Special Superfine Powder Engineering Research Center, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China.
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Ghafoor N, Kanwal N, Nawaz H, Irfan Majeed M, Rashid N, Ishtiaq S, Tariq R, Kainat K, Ali A, Anwar A, Shoukat Z, Amir A, Imran M. Quantitative analysis of cephalexin in solid dosage form by Raman spectroscopy and chemometric tools. Drug Dev Ind Pharm 2024; 50:1-10. [PMID: 38140860 DOI: 10.1080/03639045.2023.2290021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/27/2023] [Indexed: 12/24/2023]
Abstract
OBJECTIVE To use Raman Spectroscopy for qualitative and quantitative evaluation of pharmaceutical formulations of active pharmaceutical ingredient (API) of Cephalexin. SIGNIFICANCE Raman Spectroscopy is a noninvasive, nondestructive, reliable and rapid detection technique used for various pharmaceutical drugs quantification. The present study explores the potential of Raman Spectroscopy for quantitative analysis of pharmaceutical drugs. METHOD For qualitative and quantitative analysis of Cephalexin API, various standard samples containing less and more concentration of API than commercial tablet was prepared. To study spectral differences, the mean plot of all the samples was prepared. For qualitative analysis, Principal Component Analysis (PCA) and for quantitative analysis Partial Least Square Regression analysis (PLSR) was used. Both of these are Multivariate data analysis techniques and give reliable results as published in previous literature. RESULTS PCA model distinguished all the Raman Spectral data related to the various Cephalexin solid dosage formulations whereas the PLSR model was used to calculate the concentration of different unknown formulations. For the PLSR model, RMSEC and RMSEP were determined to be 3.3953 and 3.8972, respectively. The prediction efficiency of this built PLSR model was found to be very good with a goodness of the model value (R2) of 0.98. The PLSR model also predicted the concentrations of Cephalexin formulations in the blind or unknown sample. CONCLUSION These findings demonstrate that the Raman spectroscopy coupled to PLSR analysis could be regarded as a fast and effectively reliable tool for quantitative analysis of pharmaceutical drugs.
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Affiliation(s)
- Nida Ghafoor
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Naeema Kanwal
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Haq Nawaz
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | | | - Nosheen Rashid
- Department of Chemistry, University of Education, Faisalabad, Pakistan
| | - Shazra Ishtiaq
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Rabiah Tariq
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Kiran Kainat
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Arslan Ali
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Ayesha Anwar
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Zainab Shoukat
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Aiman Amir
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Muhammad Imran
- Department of Chemistry, Faculty of Science, King Khalid University, Abha, Saudi Arabia
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Rimsha G, Shahbaz M, Majeed MI, Nawaz H, Rashid N, Akram MW, Shabbir I, Kainat K, Amir A, Sultan E, Munir M, Imran M. Raman Spectroscopy for the Quantitative Analysis of Solid Dosage Forms of the Active Pharmaceutical Ingredient of Febuxostat. ACS OMEGA 2023; 8:41451-41457. [PMID: 37970040 PMCID: PMC10633866 DOI: 10.1021/acsomega.3c05243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/09/2023] [Accepted: 10/11/2023] [Indexed: 11/17/2023]
Abstract
Raman spectroscopy has been used to characterize and quantify the solid dosage forms of the commercially available drug febuxostat. For this purpose, different formulations consisting of the febuxostat (API) and excipients with different concentrations of the API are prepared and analyzed by Raman spectroscopy to identify different spectral features related to the febuxostat API and excipients. Multivariate data analysis tools such as principal component analysis (PCA) and partial least-squares regression (PLSR) analysis are used for qualitative and quantitative analyses. PCA has been found to be useful for the qualitative monitoring of various solid dosage forms. PLSR analysis has led to the successful prediction of API concentration in the unknown samples with a sensitivity and a selectivity of 98 and 99%, respectively. Moreover, the root-mean-square error (RMSE) of calibration and validation of the PLSR model has been found to be 2.9033 and 1.35, respectively. Notably, it is found to be very helpful for the comparison between the self-made formulations of febuxostat and commercially available febuxostat tablets (40 and 80 mg) of two different brands (Gouric and Zurig). These results showed that Raman spectroscopy can be a useful and reliable technique for identifying and quantifying the active pharmaceutical ingredient (API) in commercially available solid dosage forms.
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Affiliation(s)
- Gull Rimsha
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Shahbaz
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Irfan Majeed
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Haq Nawaz
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Nosheen Rashid
- Department
of Chemistry, University of Education, Faisalabad
Campus, Faisalabad 38000, Pakistan
| | - Muhammad Waseem Akram
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Ifra Shabbir
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Kiran Kainat
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Aiman Amir
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Eiman Sultan
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Mulja Munir
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Imran
- Department
of Chemistry, Faculty of Science, King Khalid
University, P.O. Box 9004, Abha 61413, Saudi Arabia
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Xie L, Deng H, Wang Z, Wang W, Liang J, Deng G. An approach to detecting diphenylamine content and assessing chemical stability of single-base propellants by near-infrared reflectance spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 285:121906. [PMID: 36179570 DOI: 10.1016/j.saa.2022.121906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 09/12/2022] [Accepted: 09/17/2022] [Indexed: 06/16/2023]
Abstract
Diphenylamine (DPA) as a stabilizer component plays an important role in maintaining the chemical stability of single-base propellants (SBPs). This work investigated the feasibility of rapidly detecting the content of DPA in SBP by near-infrared reflectance spectroscopy (NIRS). The quantitative NIR model was developed by intervals selection, spectral pretreatment and factor number optimization. The optimal spectral intervals were determined to be 1081 nm ∼ 1280 nm and 1378 nm ∼ 1602 nm based on the characteristic spectral peaks of DPA. By comparing the performance of the developed models with different preprocessing methods, the best preprocessing method was standard normal variate transformation (SNV) + de-trending (Dr) + Smoothing. The optimal number of factors was 6 for DPA model. Partial least squares (PLS) regression was used to establish the calibration models of DPA. For the developed model, the determination coefficients of calibration and prediction (Rc2, Rp2) were 0.9907 and 0.9884, respectively. The root mean square errors of calibration and prediction (RMSEC, RMSEP) were 0.0310 and 0.0342, respectively. The samples in the prediction set were predicted by the developed model, and the average absolute error of the proposed and reference method was only 0.0265. The developed model can be applied in rapid monitor the content of DPA in SBP. In addition, vieille test have demonstrated that the chemical stability of SBP became worse with the decrease of DPA content. The content of DPA contained in the SBP with qualified chemical stability is not less than 0.8753%. Thus, the developed model can be used to judge whether the chemical stability of SBP is qualified or unqualified.
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Affiliation(s)
- Liang Xie
- National Special Superfine Powder Engineering Research Center, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China
| | - Heying Deng
- Yongzhou Taozhu Middle School, Changhong Road, Qiyang County, Yongzhou City 426100, China
| | - Zhaoxuan Wang
- National Special Superfine Powder Engineering Research Center, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China
| | - Weibin Wang
- National Special Superfine Powder Engineering Research Center, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China
| | - Jinhua Liang
- National Special Superfine Powder Engineering Research Center, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China
| | - Guodong Deng
- National Special Superfine Powder Engineering Research Center, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China.
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