Transform Drug Discovery and Development With Generative Artificial Intelligence

In the past decade, artificial intelligence (AI) has significantly reshaped drug discovery, offering a wide range of tools to expedite the identification of new therapeutics. This review meticulously examines AI's pivotal role, detailing common data resources, molecule representations, and benchmark platforms crucial for molecular property prediction and molecule generation. In addition, it provides a comprehensive analysis of AI techniques, categorizing them by model architectures and learning paradigms. Success stories underscore AI's transformative impact on clinical candidate advancement. Despite progress, formidable challenges persist, demanding innovative solutions. By addressing these challenges and charting future directions, the review aims to deepen understanding and foster innovation in AI-driven drug discovery and development, serving as a valuable resource for researchers and practitioners.