A Multi-Criteria Decision-Making Approach for Ranking Antiepileptic Drugs Using Topological Indices

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Abstract
This study presents a novel approach to analyzing the physicochemical properties of five antiepileptic drugs through the integration of advanced multi-criteria decision-making techniques, specifically COPRAS and PROMETHEE. The innovation of this research lies in the combination of topological indices with multi-criteria decision-making methods for the ranking of drugs. By employing topological indices, we provide a comprehensive framework for ranking these drugs based on their chemical characteristics without reliance on laboratory experiments. Chemical compounds are typically represented as graphs, where atoms are depicted as vertices and the edges represent the bonds between them. Based on the correlation coefficients between topological indices and the physicochemical characteristics of the drugs, the Forgotten index is identified as a nonbeneficial measure that favors smaller values. In contrast, the Harmonic index, Second Modified Zagreb index, Randić index, and Sum-Connectivity index are considered beneficial, preferring larger values. Furthermore, we utilized Shannon’s entropy method to assign weights to the different criteria, resulting in compelling rankings of the drugs across both decision-making methods. In the COPRAS method, the drugs were ranked as follows: Carbamazepine in first place, followed by Phenytoin, Clonazepam, Clobazam, and Topamax, which were ranked second to fifth, respectively. Conversely, the PROMETHEE method yielded a different ranking order, placing Clonazepam at the top, followed by Clobazam, Carbamazepine, Phenytoin, and Topamax in subsequent positions.

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