SOP 초안 작성, 감사 대응, CSV 및 21 CFR Part 11 규제 준수를 위한 특화 에이전트 연동 대화형 AI 인터페이스.
Saram Consulting바이오텍, 인공지능, 규제 컴플라이언스의 융합에 관한 심층 전략 및 실전 아키텍처 분석.
Every credible analysis of MCP in regulated environments converges on the same architecture — a centralized gateway proxy. But several widely-cited claims about this pattern are wrong. Here's what the evidence actually supports, what the regulators actually require, and what the vendor landscape actually offers.
글 읽기 →The Model Context Protocol turns LLMs into active agents that can query LIMS, QMS, and clinical databases. Raw MCP is a compliance liability in GxP environments. The protocol isn't the problem — the implementation is. Here's the architecture that makes MCP regulator-ready, backed by OWASP, GAMP 5, and the FDA's own CSA framework.
글 읽기 →Self-learning agents don't retrain their neural weights in production. They use externalized memory loops, self-reflection, and skill crystallization. Here's the verified architecture — and how to deploy it in a GxP environment without triggering an FDA warning letter.
글 읽기 →Whether an AI agent drafting SOPs in biopharma needs its own QMS account depends on your architecture. The service account vs. no-account debate maps directly to how deeply the AI integrates with your validated systems — and EU Annex 22, FDA CSA, and the incoming GxP-AI framework all have something to say about it.
글 읽기 →When files land in S3 or MinIO, they should automatically flow through parsing, chunking, embedding, and indexing. Six architectural approaches for automating this pipeline locally — from simple webhook scripts to orchestrated workflow engines — compared side by side.
글 읽기 →