Prediction of suitable drug for keloid through analytic hierarchy process and topological indices.

The aim of the study is to identify the most suitable drug in treating Keloid, from the considered drugs using Multi Criteria Decision Making (MCDM) technique, Analytic Hierarchy Process (AHP) via degree-based topological indices. Topological indices play a vital role in predicting the biological and physicochemical properties of chemical compounds by deriving them from the molecular structure using specific rules. Given the growing prevalence of keloid cases, there is an increasing need for safer and more effective drugs. This study investigates 12 keloid drugs by applying the QSPR technique with respect to their physicochemical properties. The drugs are ranked using the AHP with specific criteria, allowing for the identification of the most effective drug combinations to help in the development of improved treatments for keloids. From the analysis, it is observed that the most effective and suitable drug is Doxorubicin while the least effective drug is 5-Fluorouracil.