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The Efficiency of AuNPs in Cancer Cell Targeting Compared to Other Nanomedicine Technologies Using Fuzzy PROMETHEE
Safa Anmar Albarwary1,2, Ayse Gunay Kibarer2,3, Mubarak Taiwo Mustapha1,3
1Department of Biomedical Engineering, Innovation and Information Technologies Center, Near East University, Nicosia, Cyprus.
Abstract:
Cancer is a disease with rare, diverse symptoms, causing abnormal cell growth in an uncontrolled way, leading to cell damage, apoptosis, and eventually death of the patient. This study uses the Fuzzy PROMETHEE technique to develop a new path for cancer treatment based on nanoparticles (NPs) applications, used in controlled anticancer drug delivery (drug release, toxicity, and unspecific site targeting) to enhance patient safety. The different nanoparticles employed in the drug delivery analysis are gold nanoparticles (AuNPs), liposomes, dendrimers, polymeric micelles (PMs), and quantum dots (QDs). Fuzzy predictable preference organization mode and evaluation multicriteria choice were used as tactics in making the best decision using the data from the factors of cost, size, shape, surface charge, ligand type, pH and temperature stimuli, biocompatibility, accumulation ratio, toxicity, specificity, stability, efficacy, adverse effect, and safety factor of the NPs. The results obtained from the total net flow of the visual PROMETHEE scenario for anticancer drug delivery, based on NPs data analysis, show that AuNPs are ranked the highest among the other NPs. The Phi values obtained for the NPs are as follows: AuNPs (0.1428), PMs (0.0280), QDs (-0.0467), dendrimers (-0.0593), and liposomes (-0.0649). This study highlights the optimal choice of NPs as an intelligent drug delivery system that facilitates therapeutic efficiency, where cancer cells are accurately targeted to enhance treatment quality and patient safety.
Insights
Gold nanoparticles (AuNPs) are the top choice for cancer treatment drug delivery systems. This study used the Fuzzy PROMETHEE technique to rank nanoparticles, enhancing patient safety and therapeutic efficiency.
Area of Science:
- Biomedical Engineering
- Nanotechnology
- Oncology
Background:
- Cancer is a complex disease characterized by uncontrolled cell growth and potential patient mortality.
- Current cancer treatments face challenges with drug delivery, toxicity, and targeting specificity.
- Nanoparticles (NPs) offer potential for controlled anticancer drug delivery, improving safety and efficacy.
Purpose of the Study:
- To develop an optimal nanoparticle-based drug delivery system for cancer treatment.
- To evaluate and rank various nanoparticles for their suitability in targeted anticancer drug delivery.
- To enhance patient safety and therapeutic outcomes through intelligent drug delivery.
Main Methods:
- Utilized the Fuzzy PROMETHEE technique for multi-criteria decision-making.
- Analyzed nanoparticles including gold nanoparticles (AuNPs), liposomes, dendrimers, polymeric micelles (PMs), and quantum dots (QDs).
- Evaluated NPs based on factors like cost, size, toxicity, biocompatibility, stability, and efficacy.
Main Results:
- Gold nanoparticles (AuNPs) were ranked highest (Phi value: 0.1428) among the evaluated nanoparticles.
- Polymeric micelles (PMs) ranked second (Phi value: 0.0280), followed by QDs, dendrimers, and liposomes.
- The Fuzzy PROMETHEE method provided a clear ranking for NPs in anticancer drug delivery applications.
Conclusions:
- Gold nanoparticles (AuNPs) represent the optimal choice for intelligent anticancer drug delivery systems.
- Nanoparticle-based drug delivery can significantly enhance therapeutic efficiency and patient safety in cancer treatment.
- Accurate targeting of cancer cells using optimized NPs improves treatment quality.
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