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Abstract
Malignant cancer angiogenesis has historically attracted enormous scientific attention. Although angiogenesis is requisite for a child’s development and conducive to tissue homeostasis, it is deleterious when cancer lurks. Today, anti-angiogenic biomolecular receptor tyrosine kinase inhibitors (RTKIs) to target angiogenesis have been prolific in treating various carcinomas. Angiogenesis is a pivotal component in malignant transformation, oncogenesis, and metastasis that can be activated by a multiplicity of factors (e.g., VEGF (Vascular endothelial growth factor), (FGF) Fibroblast growth factor, (PDGF) Platelet-derived growth factor and others). The advent of RTKIs, which primarily target members of the VEGFR (VEGF Receptor) family of angiogenic receptors has greatly ameliorated the outlook for some cancer forms, including hepatocellular carcinoma, malignant tumors, and gastrointestinal carcinoma. Cancer therapeutics have evolved steadily with active metabolites and strong multi-targeted RTK inhibitors such as E7080, CHIR-258, SU 5402, etc. This research intends to determine the efficacious anti-angiogenesis inhibitors and rank them by using the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE- II) decision-making algorithm. The PROMETHEE-II approach assesses the influence of growth factors (GFs) in relation to the anti-angiogenesis inhibitors. Due to their capacity to cope with the frequently present vagueness while ranking alternatives, fuzzy models constitute the most suitable tools for producing results for analyzing qualitative information. This research’s quantitative methodology focuses on ranking the inhibitors according to their significance concerning criteria. The evaluation findings indicate the most efficacious and idle alternative for inhibiting angiogenesis in cancer.
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1 Babu Banarasi Das University, Department of Computer Application, Lucknow, India (GRID:grid.449283.0) (ISNI:0000 0004 1779 9293)
2 Thapar Institute of Engineering and Technology, Department of Computer Science and Engineering, Patiala, India (GRID:grid.412436.6) (ISNI:0000 0004 0500 6866)
3 Majmaah University, Department of Computer Science, College of Computer and Information Sciences, Al Majmaáh, Saudi Arabia (GRID:grid.449051.d) (ISNI:0000 0004 0441 5633)
4 Chandigarh University, Department of Electronics and Communication Engineering, Mohali, India (GRID:grid.448792.4) (ISNI:0000 0004 4678 9721)
5 Bahir Dar University, Faculty of Electrical and Computer Engineering, Bahir Dar Institute of Technology, Bahir Dar, Ethiopia (GRID:grid.442845.b) (ISNI:0000 0004 0439 5951)