The Future of Computer-Aided Drug Discovery Methods: Advancements and Opportunities

Abstract

The future of Computer-Aided Drug Discovery (CADD) methods is characterized by transformative innovations. Artificial intelligence and machine learning are enhancing accuracy in predicting drug-target interactions and pharmacokinetics, with deep learning models leading in performance. Quantum computing is poised to revolutionize molecular simulations. Big data and omics integration enable precision medicine, tailoring treatments to individual patient profiles. Cloud-based platforms democratize CADD tools and promote global collaboration. Ethical considerations, data privacy, and regulatory challenges are gaining prominence. With robust ethical guidelines and regulatory frameworks, the future of CADD promises safer and more efficient drug discovery, ensuring that novel therapies meet the diverse needs of patients worldwide.

Keywords: Applications, Artificial intelligence, Computer-aided, Drug discovery, Future, Quantum computing.

Cite as