Volume-1 ,Issue-5, December-2025

The necessity for effective Knowledge Management Systems (KMS) has been brought to light by the exponential growth of biomedical data and the growing complexity of pharmacological research. In order to facilitate evidence-based decision-making and spur innovation, KMS offer an organized framework for gathering, combining, and applying knowledge from drug discovery, clinical research, and patient care. The possibilities of KMS have been greatly expanded by recent developments in Artificial Intelligence (AI) and Machine Learning (ML), enabling automated insight extraction, predictive modeling, and customized healthcare solutions. Interoperability, standardization, and computational reasoning across various datasets, including as electronic health records, scientific literature, and clinical trial data, are further facilitated by the incorporation of semantic web technologies and ontologies. The influence of KMS on drug discovery, pharmacovigilance, clinical decision support, and precision medicine is highlighted in this review, which examines the changing role of KMS in the pharmaceutical and healthcare industries. Unprecedented possibilities for enhancing medication safety, maximizing therapeutic results, and promoting patient-centered care are presented by the convergence of AI-driven analytics and semantic knowledge integration.

Keyword: Knowledge Management System (KMS), Artificial Intelligence (AI), Machine Learning (ML), Semantic Web.