Chemical graph theory, in its theoretical forms, is important for designing and developing medicines because it looks at the structure of molecules. Topological descriptors are used to mathematically represent a chemical structure's topological properties, thereby enhancing the development of quantitative structure-activity relationship (QSPR) models for drugs and evaluating the efficacy of medications. The modified reverse degree is an innovative approach because it depends on the maximum degree of the graph and encompasses both the reverse and reduced reverse degrees of a graph as well. These are also effective for the examination of intricate molecular structures, but they also limit the analysis of analogous structures. The attributes enhance the sensitivity of the modified reverse degree-based topological indices, precisely predicting certain physicochemical aspects of various molecular structures. In this paper, we examine 17 drugs used to treat cancer. These include amathaspiramide E, aminopterin, aspidostomide E, carmustine, caulibugulone E, convolutamine F, melatonin, perfragilin A, podophyllotoxin, pterocellin B, raloxifene, tambjamine K, convolutamide A, convolutamydine A, daunorubicin, deguelin, and minocycline. QSPR analysis is performed using an innovative approach, using modified reverse degree-based topological descriptors, and estimates five physicochemical properties of these medicines. This study also provides an excellent correlation between the physicochemical properties and topological descriptors.