A Non-Instrumental Green Analytical Method Based on Surfactant-Assisted Dispersive Liquid–Liquid Microextraction–Thin-Layer Chromatography–Smartphone-Based Digital Image Colorimetry(SA-DLLME-TLC-SDIC) for Determining Favipiravir in Biological Samples
Favipiravir (FAV) has become a promising antiviral agent for the treatment of COVID-19. Herein, a green, fast, high-sample-throughput, non-instrumental, and affordable analytical method is proposed based on surfactant-assisted dispersive liquid–liquid microextraction (SA-DLLME) combined with thin-la...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Molecules |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1420-3049/28/2/529 |
| _version_ | 1797438382974959616 |
|---|---|
| author | Bharti Jain Rajeev Jain Prashant Kumar Jaiswal Torki Zughaibi Tanvi Sharma Abuzar Kabir Ritu Singh Shweta Sharma |
| author_facet | Bharti Jain Rajeev Jain Prashant Kumar Jaiswal Torki Zughaibi Tanvi Sharma Abuzar Kabir Ritu Singh Shweta Sharma |
| author_sort | Bharti Jain |
| collection | DOAJ |
| description | Favipiravir (FAV) has become a promising antiviral agent for the treatment of COVID-19. Herein, a green, fast, high-sample-throughput, non-instrumental, and affordable analytical method is proposed based on surfactant-assisted dispersive liquid–liquid microextraction (SA-DLLME) combined with thin-layer chromatography–digital image colourimetry (TLC-DIC) for determining favipiravir in biological and pharmaceutical samples. Triton X-100 and dichloromethane (DCM) were used as the disperser and extraction solvents, respectively. The extract obtained after DLLME procedure was spotted on a TLC plate and allowed to develop with a mobile phase of chloroform:methanol (8:2, <i>v</i>/<i>v</i>). The developed plate was photographed using a smartphone under UV irradiation at 254 nm. The quantification of FAV was performed by analysing the digital images’ spots with open-source ImageJ software. Multivariate optimisation using Plackett–Burman design (PBD) and central composite design (CCD) was performed for the screening and optimisation of significant factors. Under the optimised conditions, the method was found to be linear, ranging from 5 to 100 µg/spot, with a correlation coefficient (R<sup>2</sup>) ranging from 0.991 to 0.994. The limit of detection (LOD) and limit of quantification (LOQ) were in the ranges of 1.2–1.5 µg/spot and 3.96–4.29 µg/spot, respectively. The developed approach was successfully applied for the determination of FAV in biological (i.e., human urine and plasma) and pharmaceutical samples. The results obtained using the proposed methodology were compared to those obtained using HPLC-UV analysis and found to be in close agreement with one another. Additionally, the green character of the developed method with previously reported protocols was evaluated using the ComplexGAPI, AGREE, and Eco-Scale greenness assessment tools. The proposed method is green in nature and does not require any sophisticated high-end analytical instruments, and it can therefore be routinely applied for the analysis of FAV in various resource-limited laboratories during the COVID-19 pandemic. |
| first_indexed | 2024-03-09T11:36:59Z |
| format | Article |
| id | doaj.art-67a932233fc849a193459364298d7418 |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-09T11:36:59Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-67a932233fc849a193459364298d74182023-11-30T23:41:08ZengMDPI AGMolecules1420-30492023-01-0128252910.3390/molecules28020529A Non-Instrumental Green Analytical Method Based on Surfactant-Assisted Dispersive Liquid–Liquid Microextraction–Thin-Layer Chromatography–Smartphone-Based Digital Image Colorimetry(SA-DLLME-TLC-SDIC) for Determining Favipiravir in Biological SamplesBharti Jain0Rajeev Jain1Prashant Kumar Jaiswal2Torki Zughaibi3Tanvi Sharma4Abuzar Kabir5Ritu Singh6Shweta Sharma7Central Forensic Science Laboratory, Dakshin Marg, Sector—36A, Chandigarh 160036, IndiaCentral Forensic Science Laboratory, Dakshin Marg, Sector—36A, Chandigarh 160036, IndiaSchool of Earth Sciences, Department of Environmental Sciences, Central University of Rajasthan, NH-8, Bandar Sindri, Ajmer 305817, IndiaDepartment of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi ArabiaInstitute of Forensic Science & Criminology, Panjab University, Chandigarh 160014, IndiaInternational Forensic Research Institute, Department of Chemistry and Biochemistry, Florida International University, Miami, FL 33199, USASchool of Earth Sciences, Department of Environmental Sciences, Central University of Rajasthan, NH-8, Bandar Sindri, Ajmer 305817, IndiaInstitute of Forensic Science & Criminology, Panjab University, Chandigarh 160014, IndiaFavipiravir (FAV) has become a promising antiviral agent for the treatment of COVID-19. Herein, a green, fast, high-sample-throughput, non-instrumental, and affordable analytical method is proposed based on surfactant-assisted dispersive liquid–liquid microextraction (SA-DLLME) combined with thin-layer chromatography–digital image colourimetry (TLC-DIC) for determining favipiravir in biological and pharmaceutical samples. Triton X-100 and dichloromethane (DCM) were used as the disperser and extraction solvents, respectively. The extract obtained after DLLME procedure was spotted on a TLC plate and allowed to develop with a mobile phase of chloroform:methanol (8:2, <i>v</i>/<i>v</i>). The developed plate was photographed using a smartphone under UV irradiation at 254 nm. The quantification of FAV was performed by analysing the digital images’ spots with open-source ImageJ software. Multivariate optimisation using Plackett–Burman design (PBD) and central composite design (CCD) was performed for the screening and optimisation of significant factors. Under the optimised conditions, the method was found to be linear, ranging from 5 to 100 µg/spot, with a correlation coefficient (R<sup>2</sup>) ranging from 0.991 to 0.994. The limit of detection (LOD) and limit of quantification (LOQ) were in the ranges of 1.2–1.5 µg/spot and 3.96–4.29 µg/spot, respectively. The developed approach was successfully applied for the determination of FAV in biological (i.e., human urine and plasma) and pharmaceutical samples. The results obtained using the proposed methodology were compared to those obtained using HPLC-UV analysis and found to be in close agreement with one another. Additionally, the green character of the developed method with previously reported protocols was evaluated using the ComplexGAPI, AGREE, and Eco-Scale greenness assessment tools. The proposed method is green in nature and does not require any sophisticated high-end analytical instruments, and it can therefore be routinely applied for the analysis of FAV in various resource-limited laboratories during the COVID-19 pandemic.https://www.mdpi.com/1420-3049/28/2/529favipiravirsurfactant-assisted dispersive liquid–liquid microextractiondigital image colourimetrythin-layer chromatography |
| spellingShingle | Bharti Jain Rajeev Jain Prashant Kumar Jaiswal Torki Zughaibi Tanvi Sharma Abuzar Kabir Ritu Singh Shweta Sharma A Non-Instrumental Green Analytical Method Based on Surfactant-Assisted Dispersive Liquid–Liquid Microextraction–Thin-Layer Chromatography–Smartphone-Based Digital Image Colorimetry(SA-DLLME-TLC-SDIC) for Determining Favipiravir in Biological Samples Molecules favipiravir surfactant-assisted dispersive liquid–liquid microextraction digital image colourimetry thin-layer chromatography |
| title | A Non-Instrumental Green Analytical Method Based on Surfactant-Assisted Dispersive Liquid–Liquid Microextraction–Thin-Layer Chromatography–Smartphone-Based Digital Image Colorimetry(SA-DLLME-TLC-SDIC) for Determining Favipiravir in Biological Samples |
| title_full | A Non-Instrumental Green Analytical Method Based on Surfactant-Assisted Dispersive Liquid–Liquid Microextraction–Thin-Layer Chromatography–Smartphone-Based Digital Image Colorimetry(SA-DLLME-TLC-SDIC) for Determining Favipiravir in Biological Samples |
| title_fullStr | A Non-Instrumental Green Analytical Method Based on Surfactant-Assisted Dispersive Liquid–Liquid Microextraction–Thin-Layer Chromatography–Smartphone-Based Digital Image Colorimetry(SA-DLLME-TLC-SDIC) for Determining Favipiravir in Biological Samples |
| title_full_unstemmed | A Non-Instrumental Green Analytical Method Based on Surfactant-Assisted Dispersive Liquid–Liquid Microextraction–Thin-Layer Chromatography–Smartphone-Based Digital Image Colorimetry(SA-DLLME-TLC-SDIC) for Determining Favipiravir in Biological Samples |
| title_short | A Non-Instrumental Green Analytical Method Based on Surfactant-Assisted Dispersive Liquid–Liquid Microextraction–Thin-Layer Chromatography–Smartphone-Based Digital Image Colorimetry(SA-DLLME-TLC-SDIC) for Determining Favipiravir in Biological Samples |
| title_sort | non instrumental green analytical method based on surfactant assisted dispersive liquid liquid microextraction thin layer chromatography smartphone based digital image colorimetry sa dllme tlc sdic for determining favipiravir in biological samples |
| topic | favipiravir surfactant-assisted dispersive liquid–liquid microextraction digital image colourimetry thin-layer chromatography |
| url | https://www.mdpi.com/1420-3049/28/2/529 |
| work_keys_str_mv | AT bhartijain anoninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT rajeevjain anoninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT prashantkumarjaiswal anoninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT torkizughaibi anoninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT tanvisharma anoninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT abuzarkabir anoninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT ritusingh anoninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT shwetasharma anoninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT bhartijain noninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT rajeevjain noninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT prashantkumarjaiswal noninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT torkizughaibi noninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT tanvisharma noninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT abuzarkabir noninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT ritusingh noninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples AT shwetasharma noninstrumentalgreenanalyticalmethodbasedonsurfactantassisteddispersiveliquidliquidmicroextractionthinlayerchromatographysmartphonebaseddigitalimagecolorimetrysadllmetlcsdicfordeterminingfavipiravirinbiologicalsamples |