Sana Hanif

Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain

Abstract 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.

Computer Aided Formulation and Characterization of Propranolol Hcl Buccal Tablet Using Polymeric Blend

The current study was aimed to formulate a continuous release mucoadhesive buccal tablet containing propranolol HCl. The type and quantities of polymers as well as method of compression were set in a preliminary study (F1-F13). Direct compression method was employed in the main study (F14-F24) using Carbopol 934P (CP), ethylcellulose (EC), sodium alginate (SA), hydroxypropyl methylcellulose (HPMC k4M) and carboxymethylcellulose (CMC) as mucoadhesive polymers and were tested for physicochemical tests i.e. swellability, surface pH, mucoadhesive time, mucoadhesive strength, in vitro release etc. Results obtained from the study were optimized using NeuralPower 3.1, an artificial intelligence approach. Against the desirability of physicochemical parameters, the software optimized the ingredients as HPMC (150mg), CMC (25mg), CP (20mg) and EC (20mg). Outcome revealed that HPMC primarily contributed to the physicochemical properties of mucoadhesive formulation. To compare prediction, optimized ingredients were formulated (F25) and tested. The swellability index of confirmation formulation (F25) was 102% at 6 h. As predicted, similar release pattern was of F25 was obtained as 26% (0.5h), 34% (1h), 40% (2h), 45% (3h), 50% (4h), 62% (5h), 76% (6h), 85% (7h) and 97% (8h) respectively. For release kinetics, DD solver suggested the release of the drug to be non-Fickian.

Screening of diverse germplasms for genetic studies of drought tolerance in rice (Oryza sativa L.)

Twenty different rice lines were analyzed based on various genotypic and phenotypic seedling traits. Correlation and principal component analysis (PCA) were used to study these traits. The mean value of the root shoot traits of each genotype was analyzed at different levels of significance. The highest correlation was found in root length, shoot length (r = 0.856, r = 0.896) and shoot length and root number (r = 0.825, r = 0.818) in stress and normal condition respectively. The principal component exhibited more than one eigenvalue considered to be more important due to variation. The principal components (PC1 and PC2) having more than one eigenvalue for various traits were considered very important due to variation. The PC1 and PC2 for root length and shoot length same for both conditions showed variability of 76.2% and 78.5%, respectively. Different SSR markers were used to study the genetic diversity and screening of the rice genotypes for developing new breeding lines. The mean number of alleles per locus was 3.70, showing that the average polymorphism information content (PIC) was 0.500. A total of 63 alleles were also identified from the microsatellite marker loci. The overall objective of the study was to screen out the diverse parents, on the basis of different simple sequence repeats (SSR) primers and root morphological desirable traits, for a future cross breeding program for development of new rice varieties that are equally beneficial for farmers and the scientific community.