Characterization of transdermal drug delivery using nondestructive visible spectrophotometry and artificial neural network / Aznida Alias
Assessment of drug content and matric characteristics, such as state of polymerpolymer and drug-polymer interaction are utmost important with respect the therapeutic effectiveness of transdermal drug delivery system. Conventional methods for analysis result in sample being unrecoverable from test, d...
Saved in:
| 主要作者: | |
|---|---|
| 格式: | Thesis |
| 语言: | English |
| 出版: |
2017
|
| 在线阅读: | https://ir.uitm.edu.my/id/eprint/93345/1/93345.pdf |
| 标签: |
添加标签
没有标签, 成为第一个标记此记录!
|
| 总结: | Assessment of drug content and matric characteristics, such as state of polymerpolymer and drug-polymer interaction are utmost important with respect the therapeutic effectiveness of transdermal drug delivery system. Conventional methods for analysis result in sample being unrecoverable from test, disposal of a large amount of solvents, reagents and accessories, as well as, restrict the analysis to statistically selected samples. This thesis present a new technique in drug content and drug concentration assessment of nifedipine and hyroxypropylmethyl cellulose films with 25%, 50% and 75% relative humidity using nondestructive testing technique of Visible Spectrophotometry. The crossed study of the polymeric films by Differential Scanning Calorimetry, Fourier Transform Infrared Spectroscopy, Ultraviolet Spectrophotometry and Visible Spectrophotometry indicated physicochemical changes as the drug and polymer varied. The significant wavelength and intensity of visible spectrophotometry associated with different polymeric films and relative humidity were determined. Correlation study of drug concentration from visible spectrophotometry and drug content were done using artificial neural network. This intelligent technique have presented the reliability of Visible Spectrophotometry in detecting drug content and identifying drug concentration at minimum and maximum of 0 to 20mg and 0 to 32.11 %w/w respectively. |
|---|