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.

The concept of "topological index" refers to a numerical value determined by the structure of a chemical network. It serves to determine the physicochemical and biological properties of diverse medications, offering a more precise depiction of the theoretical properties of organic materials, this is achieved through the utilization of degree-based topological indices. Because of the development of resistance to existing treatments and the unpleasant side effects associated with some current drugs, the hunt for new drugs remains a priority. In drug discovery, QSPR approaches are widely used to predict, from a chemical structure, the biological activity of potential novel drugs. Researchers can prioritize compounds for synthesis and optimize them to improve potency, preference, and other desired attributes by establishing a correlation between chemical features and biological activity. Rational drug design approaches incorporate research methodologies such as quantitative structure-activity relationships (QSAR) and quantitative structure-property relationships (QSPR), along with decision-making strategies. The goal of these strategies is to improve the biological activity and physicochemical qualities of existing leads. This research includes mathematical modeling of drug mechanisms utilizing multiple-criteria decision analysis and QSPR analysis. Furthermore, using decision-making techniques, I can determine the order of production for various drugs used to treat bone cancer based on their examination using QSPR analysis and topological indices.