Large language models for drug discovery and development
Yizhen Zheng, Huan Yee Koh, Jiaxin Ju, Madeleine Yang, Lauren Therese May, Geoffrey I. Webb, Li Li, Shirui Pan and 1 more
Why it has this license class
AChecked 1 Oct 2026. Open license (CC-BY, CC-BY-SA, CC0, public domain): full text indexed and used in synthesis.
| Source | License | Open-access status | Read as |
|---|---|---|---|
| openalex | cc-by | gold | Green |
| crossref | http://creativecommons.org/licenses/by/4.0/ | — | Green |
| unpaywall | cc-by | gold | Green |
| europepmc | cc by | — | Green |
Abstract
Bdrug discovery, and optimizing clinical trial processes. This review highlights the expanding role of LLMs in revolutionizing various stages of the drug development pipeline. We investigate how these advanced computational models can uncover target-disease linkage, interpret complex biomedical data, enhance drug molecule design, predict drug efficacy and safety profiles, and facilitate clinical trial processes. In this paper, we aim to provide a comprehensive overview for researchers and practitioners in computational biology, pharmacology, and AI4Science by offering insights into the potential transformative impact of LLMs on drug discovery and development.
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