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A topological index is a real number obtained from the chemical graph structure. It can predict the physicochemical and biological properties of many anticancer medicines like blood, breast and skin cancer. This can be done through degree-based topological indices.. In this article, the drugs, azacitidine, buslfan, mercaptopurine, tioguanine, nelarabine, etc. which are used in order to cure blood cancer are discussed and the purpose of the QSPR study is to determine the mathematical relation between the properties under investigation (eg, boiling point, flash point etc.) and different descriptors related to molecular structure of the drugs. It is found that topological indices (TIs) applied on said drugs have a good correlation with physicochemical properties in this context.

Due to significant advancements being made in the field of drug design, the use of topological descriptors remains the primary approach. When combined with QSPR models, descriptors illustrate a molecule’s chemical properties numerically. Numbers relating to chemical composition topological indices are structures that link chemical composition to physical characteristics. This research concentrates on the analysis of curvilinear regression models and degree-based topological descriptors for thirteen skin cancer drugs. The physicochemical characteristics of the skin cancer drugs are examined while regression models are built for computed index values. An analysis is performed for several significant results based on the acquired data.