open access

https://hdl.handle.net/2115/96103

Multi-Omics and Artificial Intelligence-Guided Drug Repositioning : Prospects, Challenges, and Lessons Learned from COVID-19

英語

COVID-19

2022

Mary Ann Liebert

OMICS: A Journal of Integrative Biology

26(7)

361-371

Drug repurposing is of interest for therapeutics innovation in many human diseases including coronavirusdisease 2019 (COVID-19). Methodological innovations in drug repurposing are currently being empowered by convergence of omics systems science and digital transformation of life sciences. This expert review article offers a systematic summary of the application of artificial intelligence (AI), particularly machine learning (ML), to drug repurposing and classifies and introduces the common clustering, dimensionality reduction, and other methods. We highlight, as a present-day high-profile example, the involvement of AI/ML-based drug discovery in the COVID-19 pandemic and discuss the collection and sharing of diverse data types, and the possible futures awaiting drug repurposing in an era of AI/ML and digital technologies. The article provides new insights on convergence of multi-omics and AI-based drug repurposing. We conclude with reflections on the various pathways to expedite innovation in drug development through drug repurposing for prompt responses to the current COVID-19 pandemic and future ecological crises in the 21st century.

学術雑誌論文

Version of Record

Creative Commons Attribution 4.0 International

1557-8100