GMPilot: An Expert AI Agent For FDA cGMP Compliance

arXiv cs.AI / 2026/3/24

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要点

  • The paper introduces GMPilot, a domain-specific AI agent aimed at supporting FDA cGMP compliance in the pharmaceutical quality management process.
  • GMPilot uses a curated knowledge base of FDA regulations and historical inspection observations together with RAG and ReAct frameworks to deliver real-time, traceable decision support.
  • In a simulated inspection scenario, the agent is shown to help quality professionals respond faster and more professionally by returning structured, verifiable regulatory and case-based evidence.
  • The authors note limitations including incomplete regulatory scope coverage and weaker model interpretability, indicating areas for further improvement.
  • Overall, GMPilot is positioned as a specialized example of applying AI to highly regulated healthcare/pharma compliance workflows to improve decision-making.

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 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.