Text Mining Techniques for the Analysis of Me...

Text Mining Techniques for the Analysis of Medical Literature in Drug Discovery and Development

Author Name : Sharda Kumari

ABSTRACT

Text mining techniques have emerged as a powerful tool for the analysis of vast amounts of medical literature, significantly impacting the process of drug discovery and development. In this paper, we systematically review the state-of-the-art text mining methodologies and their applications in pharmaceutical research. The focus of our review includes natural language processing (NLP), machine learning algorithms, and data visualization techniques to extract valuable information from medical literature, such as drug-target interactions, molecular pathways, and potential side effects. We discuss the challenges faced in implementing these techniques, such as the diversity of data sources, terminological variations, and the need for domain-specific knowledge. Our review highlights the potential of text mining in addressing these challenges and providing researchers with insights that can facilitate the drug discovery and development process. By harnessing the power of text mining, researchers can better understand complex biological systems, streamline the identification of novel drug targets, and accelerate the translation of new therapies from the bench to the bedside.

Keywords: text mining, natural language processing, drug discovery, drug development, medical literature