AI-Driven Drug Discovery: Accelerating the Path to New Treatments

Abstract

AI is revolutionizing drug discovery by significantly reducing the time and cost associated with identifying and developing new treatments. This paper explores the use of machine learning algorithms to analyze vast chemical and biological datasets, predict drug-target interactions, and design novel compounds. Case studies on AI-driven breakthroughs in treatments for diseases such as cancer and neurodegenerative disorders are presented. The discussion also highlights challenges, including data quality, regulatory hurdles, and the need for interdisciplinary collaboration.