Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/387344
Title: Development and Evaluation of Lipidic Nanocarriers for the Treatment of Lung Carcinoma
Researcher: Shah, Akshat Narendra
Guide(s): Patel, Asha S
Keywords: Clinical Pre Clinical and Health
Cytotoxicity studies
EGFR inhibitor
Gefitinib
Nano-structured lipid carriers
PEGylation
Pharmacology and Pharmacy
Pharmacology and Toxicology
Solid Lipid Nanoparticles
University: Parul University
Completed Date: 2022
Abstract: Lung cancer is the chief main cause of cancer-related deaths worldwide. Non small-cell lung cancer (NSCLC) is the most among them. Among all the agents Endothelial Growth Factor Receptor (EGFR inhibitors) are actively expressed in tumor cells by blocking EGFR signalling and thereby controlling the tumor cell growth. In the most prominent causes of death, these days like cancer, cytotoxic drugs hold the first place in treatment (Breast cancer is an exception newlinewere immunotherapy is used). Gefitinib (Gef) is the first-line drug for the treatment of non-small lung cancer (NSCLC) with activating endothelial growth factor receptor mutations (EGFR). Gefitinib belongs to the BCS Class II molecule. The objective of this research work was to increase the solubility of Gefitinib by encapsulating it into the lipidic matrix and thereby increasing its bioavailability at the target site. These nanocarriers are the small-sized particles that contain the scaffold (Lipids) which can entrap the lipophilic drug moiety in it, forming a lipid-drug matrix ensuring high solubility of the drug and enhanced permeability. These nanocarrier entrapped drugs attack the tumor proliferative cells and gets embedded in it newline(Passive targeting) also called permeation with retention effect. Response surface methodology is used with the purpose to create the best performance system by optimizing the levels of these variables collectively. The systematic formulation designs are involved in the optimization newlineprocedure to substantially reduce the number of trails and analyze the response surfaces so that the effects of casual factors can be realized and appropriate formulations with the target goals can be obtained.
Pagination: xi,143
URI: http://hdl.handle.net/10603/387344
Appears in Departments:Department of Pharmaceutics

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01_title.pdfAttached File289.92 kBAdobe PDFView/Open
02_declaration.pdf272.97 kBAdobe PDFView/Open
03_certificate.pdf461.9 kBAdobe PDFView/Open
04_acknowledgement.pdf123.99 kBAdobe PDFView/Open
05_content.pdf486.87 kBAdobe PDFView/Open
06_list of graph and tables.pdf436.17 kBAdobe PDFView/Open
07_abstract.pdf407.2 kBAdobe PDFView/Open
08_chapter 1.pdf1.6 MBAdobe PDFView/Open
09_chapter 2.pdf1.01 MBAdobe PDFView/Open
10_chapter 3.pdf455.66 kBAdobe PDFView/Open
11_chapter 4.pdf884.23 kBAdobe PDFView/Open
12_chapter 5.pdf2.27 MBAdobe PDFView/Open
13_chapter 6.pdf565.36 kBAdobe PDFView/Open
14_references.pdf556.6 kBAdobe PDFView/Open
15_appendix.pdf1.2 MBAdobe PDFView/Open
80_recommendation.pdf852.28 kBAdobe PDFView/Open
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