Brain tumors form when brain cells undergo DNA mutations and grow uncontrollably due to genetic, environmental, or combined factors. This study introduces novel distance-based topological indices derived from the proposed KP-polynomial, targeting drugs used in brain tumor treatment. The main goal of the QSPR (Quantitative Structure-Property Relationship) analysis is to link molecular descriptors with key drug properties like boiling point, flash point, and enthalpy of vaporization. A polynomial regression model assesses the predictive power of these indices, with correlation coefficients indicating the relationship between predicted and experimental values. This theoretical approach aids chemists and healthcare professionals in estimating drug properties without experimental testing and supports drug discovery and advanced decision-making techniques such as CRITIC, TOPSIS, VIKOR, and COPRAS for drug ranking and analysis.

A number of topological indices based on vertex eccentricity are already subject to various studies. In this paper, we obtain several upper and lower bounds for inverse connective eccentricity index of graphs in terms of other graph parameters