GMPilot: An Expert AI Agent For FDA cGMP Compliance
arXiv AIArchived Mar 24, 2026✓ Full text saved
arXiv:2603.20815v1 Announce Type: new Abstract: The pharmaceutical industry is facing challenges with quality management such as high costs of compliance, slow responses and disjointed knowledge. This paper presents GMPilot, a domain-specific AI agent that is designed to support FDA cGMP compliance. GMPilot is based on a curated knowledge base of regulations and historical inspection observations and uses Retrieval-Augmented Generation (RAG) and Reasoning-Acting (ReAct) frameworks to provide rea
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✦ AI Summary· Claude Sonnet
Computer Science > Artificial Intelligence
[Submitted on 21 Mar 2026]
GMPilot: An Expert AI Agent For FDA cGMP Compliance
Xiaohan Wang, Nan Zhang, Sulene Han, Keguang Tang, Lei Xu, Zhiping Li, Xiue (Sue)Liu, Xiaomei Han
The pharmaceutical industry is facing challenges with quality management such as high costs of compliance, slow responses and disjointed knowledge. This paper presents GMPilot, a domain-specific AI agent that is designed to support FDA cGMP compliance. GMPilot is based on a curated knowledge base of regulations and historical inspection observations and uses Retrieval-Augmented Generation (RAG) and Reasoning-Acting (ReAct) frameworks to provide real-time and traceable decision support to the quality professionals. In a simulated inspection scenario, GMPilot shows how it can improve the responsiveness and professionalism of quality professionals by providing structured knowledge retrieval and verifiable regulatory and case-based support. Although GMPilot lacks in the aspect of regulatory scope and model interpretability, it is a viable avenue of improving quality management decision-making in the pharmaceutical sector using intelligent approaches and an example of specialized application of AI in highly regulated sectors.
Comments: 14 pages, 1 figure
Subjects: Artificial Intelligence (cs.AI)
Cite as: arXiv:2603.20815 [cs.AI]
(or arXiv:2603.20815v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2603.20815
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Submission history
From: Xiaomei Han [view email]
[v1] Sat, 21 Mar 2026 13:21:24 UTC (246 KB)
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