Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain
A novel mucoadhesive buccal tablet containing flurbiprofen (FLB) and lidocaine HCl (LID) was prepared to relieve dental pain. Tablet formulations (F1-F9) were prepared using variable quantities of mucoadhesive agents, hydroxypropyl methyl cellulose (HPMC) and sodium alginate (SA). The formulations w...
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| Format: | Article |
| Language: | English |
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Sciendo
2016-06-01
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| Series: | Acta Pharmaceutica |
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| Online Access: | https://doi.org/10.1515/acph-2016-0020 |
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| author | Hussain Amjad Syed Muhammad Ali Abbas Nasir Hanif Sana Arshad Muhammad Sohail Bukhari Nadeem Irfan Hussain Khalid Akhlaq Muhammad Ahmad Zeeshan |
| author_facet | Hussain Amjad Syed Muhammad Ali Abbas Nasir Hanif Sana Arshad Muhammad Sohail Bukhari Nadeem Irfan Hussain Khalid Akhlaq Muhammad Ahmad Zeeshan |
| author_sort | Hussain Amjad |
| collection | DOAJ |
| description | A novel mucoadhesive buccal tablet containing flurbiprofen (FLB) and lidocaine HCl (LID) was prepared to relieve dental pain. Tablet formulations (F1-F9) were prepared using variable quantities of mucoadhesive agents, hydroxypropyl methyl cellulose (HPMC) and sodium alginate (SA). The formulations were evaluated for their physicochemical properties, mucoadhesive strength and mucoadhesion time, swellability index and in vitro release of active agents. Release of both drugs depended on the relative ratio of HPMC:SA. However, mucoadhesive strength and mucoadhesion time were better in formulations, containing higher proportions of HPMC compared to SA. An artificial neural network (ANN) approach was applied to optimise formulations based on known effective parameters (i.e., mucoadhesive strength, mucoadhesion time and drug release), which proved valuable. This study indicates that an effective buccal tablet formulation of flurbiprofen and lidocaine can be prepared via an optimized ANN approach. |
| format | Article |
| id | doaj-art-709dbf5358eb41b19be3ab63b1bce3dd |
| institution | Kabale University |
| issn | 1846-9558 |
| language | English |
| publishDate | 2016-06-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Acta Pharmaceutica |
| spelling | doaj-art-709dbf5358eb41b19be3ab63b1bce3dd2025-02-02T09:44:22ZengSciendoActa Pharmaceutica1846-95582016-06-0166224525610.1515/acph-2016-0020acph-2016-0020Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental painHussain Amjad0Syed Muhammad Ali1Abbas Nasir2Hanif Sana3Arshad Muhammad Sohail4Bukhari Nadeem Irfan5Hussain Khalid6Akhlaq Muhammad7Ahmad Zeeshan8 University College of Pharmacy, University of the Punjab, Lahore, Pakistan University College of Pharmacy, University of the Punjab, Lahore, Pakistan University College of Pharmacy, University of the Punjab, Lahore, Pakistan University College of Pharmacy, University of the Punjab, Lahore, Pakistan Department of Pharmacy, Bahauddin Zakariya University, Multan, Pakistan University College of Pharmacy, University of the Punjab, Lahore, Pakistan University College of Pharmacy, University of the Punjab, Lahore, Pakistan Department of Pharmacy, Gomal University, Dera Ismail khan, Pakistan Leicester School of Pharmacy, De Montfort University, Leicester, LE1 9BH, UKA novel mucoadhesive buccal tablet containing flurbiprofen (FLB) and lidocaine HCl (LID) was prepared to relieve dental pain. Tablet formulations (F1-F9) were prepared using variable quantities of mucoadhesive agents, hydroxypropyl methyl cellulose (HPMC) and sodium alginate (SA). The formulations were evaluated for their physicochemical properties, mucoadhesive strength and mucoadhesion time, swellability index and in vitro release of active agents. Release of both drugs depended on the relative ratio of HPMC:SA. However, mucoadhesive strength and mucoadhesion time were better in formulations, containing higher proportions of HPMC compared to SA. An artificial neural network (ANN) approach was applied to optimise formulations based on known effective parameters (i.e., mucoadhesive strength, mucoadhesion time and drug release), which proved valuable. This study indicates that an effective buccal tablet formulation of flurbiprofen and lidocaine can be prepared via an optimized ANN approach.https://doi.org/10.1515/acph-2016-0020dental painmucoadhesion timemucoadhesive strengthbuccal tabletartificial neural network |
| spellingShingle | Hussain Amjad Syed Muhammad Ali Abbas Nasir Hanif Sana Arshad Muhammad Sohail Bukhari Nadeem Irfan Hussain Khalid Akhlaq Muhammad Ahmad Zeeshan Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain Acta Pharmaceutica dental pain mucoadhesion time mucoadhesive strength buccal tablet artificial neural network |
| title | Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain |
| title_full | Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain |
| title_fullStr | Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain |
| title_full_unstemmed | Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain |
| title_short | Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain |
| title_sort | development of an ann optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain |
| topic | dental pain mucoadhesion time mucoadhesive strength buccal tablet artificial neural network |
| url | https://doi.org/10.1515/acph-2016-0020 |
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