AI-based language models powering drug discovery and development. Issue 11 (November 2021)

• Record Type: Journal Article
• Authors: Liu, Zhichao; Roberts, Ruth A.; Lal-Nag, Madhu; Chen, Xi; Huang, Ruili; Tong, Weida
• Is Part Of: Drug discovery today. Volume 26:Issue 11(2021)
• Page Start: 2593
• Page End: 2607
• Publication Date: 2021-11
• Subjects: Artificial intelligence -- Language models -- Natural language processing -- Drug discovery -- Drug development -- COVID-19; Drugs -- Design -- Periodicals; Drugs -- Research -- Periodicals; 615.1
• DOI: 10.1016/j.drudis.2021.06.009
• Languages: English
• ISSNs: 1359-6446

Abstract

Highlights: AI-powered Language models are promising in drug discovery and development. A 'fit-for-purpose' selection the key to positioning AI-powered language models in drug discovery and development. The AI-powered could facilitate and accelerate COVID-19 treatment development. Abstract: The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.