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.
Highlights
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 [1]
The chemotherapy technique usually lacks efficacy on the specificity of targeting cancer cells without harming nearby healthy cells or tissues. is is harmful to the patient and may result in several side effects that may be active throughout the Journal of Healthcare Engineering patient’s lifespan. erefore, the need to increase the efficacy of chemotherapy and other cancer therapies is necessary to reduce the severity and adverse side effects of these treatment techniques. e classical anticancer drugs are characterized by poor control of the drug-releasing process and biodistribution in the body of the patient
Weight was assigned to each criterion of NPs depending on the importance of the criterion. e criteria size, shape, surface charge, biocompatibility, accumulation ratio, toxicity, efficacy, adverse effects, and safety were classified within the first-degree importance, and the maximum weight was assigned as “very high” with fuzzy number ranging within (0.75, 0.92, 1.00) because of the extreme importance to improvement of drug targeting, enhanced treatment efficiency, and patient safety, increasing survival rate and quality life
Summary
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 [1]. Ese excellent characteristics give NPs the ability to be linked and adsorbed with anticancer drug delivery agents at a wide range of modulation to improve high efficacy. Other liposomes that have been modified in desired size, shape, and surface functions can control efficacy and toxicity, changes in absorbance, and biodistribution, delivering and releasing the drug most desirably. Eir advantages include their unique size and shape, solubility, drug release at the targeted site, protection of drugs from degradation, surface functionalization’s property, and their ability to be modified to decrease toxicity ratio, increase targeting specificity, and improve efficacy, which makes them a proper choice for anticancer drug delivery purposes [48]. We applied the fuzzy PROMETHEE method to compare dominant criteria of NPs in anticancer drug delivery
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