Prasad Dillan, Khandeshi Aditya, Sartin Spencer, Jain Rishi, Dahdaleh Nader, Lesniak Maciej, Luo Yuan, Ahuja Christopher
Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Department of Molecular Engineering, University of Chicago, Chicago, IL, USA.
NPJ Digit Med. 2025 Jul 14;8(1):440. doi: 10.1038/s41746-025-01859-w.
Rapid advances in large language models (LLMs) are transforming the role of students and principal investigators (PIs) in biomedical research. This perspective examines how LLMs can reshape the laboratory model as de facto "Co-PIs" for tasks ranging from literature triage to hypothesis generation. By clarifying both opportunities and risks, we propose a framework for efficient AI collaboration which aims to guide investigators and trainees in harnessing LLMs responsibly.
大语言模型(LLMs)的迅速发展正在改变学生和首席研究员(PIs)在生物医学研究中的角色。本文观点探讨了大语言模型如何能够将实验室模式重塑为事实上的“联合首席研究员”,以完成从文献筛选到假设生成等一系列任务。通过阐明机遇和风险,我们提出了一个高效人工智能协作框架,旨在指导研究人员和受训人员负责任地利用大语言模型。