Typically used in the field of drug discovery and development, computer-aided drug design (CADD) is the process of designing and finding new pharmaceutical compounds using computational techniques and tools. To comprehend the molecular interactions between possible therapeutic compounds and biological targets, computer modelling, experiments, and data analysis are used.
Published in Chapter:
Applications of AI in Drug Discovery: Its Challenges, Opportunities, and Strategies
Kalpana Pravin Rahate (Galgotias University, India) and Ritam Mondal (Galgotias University, India)
Copyright: © 2024
|Pages: 35
DOI: 10.4018/979-8-3693-2238-3.ch005
Abstract
This study conducts a critical analysis of the state of artificial intelligence uses for drug discovery, highlighting important obstacles, unrealized potential, and tactical routes for successful adoption. The chapter emphasizes the noteworthy advancements in target identification, compound screening, and molecule design using AI-driven algorithms. It also covers the ethical ramifications that arise from the combination of AI and drug discovery, as well as the accessibility of AI models and regulatory issues. The significance of interdisciplinary collaborations, advances in computational power, and the creation of strong validation frameworks are emphasized as key strategies to address these problems. This study sheds light on the complex environment of AI in drug discovery by offering a thorough summary of the difficulties encountered, the opportunities that arise, and the strategic frameworks that are necessary to fully utilize AI's potential to transform the pharmaceutical sector.