Abstract:
In this article, we used M-polynomials to investigate the rela-tionships between topological indices and physicochemical properties of some blood cancer treatment drugs; we used the curvilinear regression method on drugs like azacitidine, buslfan, and mercaptopurine, among others. This article also includes M-polynomial proofs of the closed form of some topological indices of said drugs. The study could be a new at-tempt to improve QSPR model prediction analysis by utilizing the afore-mentioned molecular descriptors, which are used to investigate chemical, medical, and pharmacological properties. Finally, this work demonstrates that topological descriptors can be a cornerstone to designing and synthe-size new blood cancer treatments and other disease drugs. Cancer is a dangerous disease that belongs to the genetic disease family. It is the un-controlled magnification of abnormal blood cells in the body that stops normal functions and is prone to infection. Cancer that affects the blood cells is known as blood cancer and Leukemia is an example that belongs to it. This will prone to infection and creates tumors in bones. Annually 1.24 million people are affected by this perilous disease. Sci-entists and Medicos are searching for better treatments to tackle this fatal disease. Drug discovery is not an easy task because it is costly, time-consuming and in some cases difficult. Cancer can be treated in a variety of ways at the early stages of a life-threatening situation. Drug therapy tackles this in an efficient way it will stop the growth of abnor-mal cells. Anticancer drugs kill and halt the menacing disease and many drugs are being tested in order to combat the fatal disease. This necessitates prompt screening, diagnosis
Page(s):
27-43
DOI:
DOI not available
Published:
Journal: Punjab University Journal of Mathematics, Volume: 55, Issue: 1, Year: 2023
Keywords:
regression models
,
drugs
,
blood cancer
,
Mpolynomials