Download PDFOpen PDF in browserLarge Language Models in Drug Discovery: Insights from Reasoning and Planning3 pages•Published: April 19, 2026AbstractRecent efforts have explored the use of large language models (LLMs) in drug discovery. As pioneers in this research line, we share our perspective on its current state and where it may lead. Our work, ChatDrug, demonstrates how LLM–human interaction, supported by a domain agent, can improve reliability: when LLMs generate incorrect or invalid outputs, the agent retrieves reference information to guide correction. While ChatDrug enhances answer accuracy and insight generation, a key limitation of current LLMs, their lack of direct perception of the physical world, remains. We believe that overcoming this boundary will require multi-modal tools integrating LLMs with domain-specific capabilities, an important direction for future research.Keyphrases: drug optimization, llms, reasoning and planning In: Jernej Masnec, Hamid Reza Karimian, Parisa Kordjamshidi and Yan Li (editors). Proceedings of AI for Accelerated Research Symposium, vol 3, pages 218-220.
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