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Large language models for drug discovery and development

Research output: Contribution to journal › Review Article › Research › peer-review

Abstract

The integration of large language models (LLMs) into the drug discovery and development field marks a significant paradigm shift, offering novel methodologies for understanding disease mechanisms, facilitating de novo drug 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.

Original languageEnglish
Article number101346
Number of pages27
JournalPatterns
Volume6
Issue number10
DOIs
Publication statusPublished - 10 Oct 2025

Keywords

  • drug development
  • drug discovery
  • large language models

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