The safe use of AI in a GMP environment requires an understanding of how language models work and where their limitations lie. Models such as ChatGPT can structure content and formulate complex topics in an understandable way, but they are based on statistical probabilities rather than verified facts. This can lead to misinterpretations or fabricated statements – problematic in a highly regulated environment where traceability and sources are mandatory.
RAG (retrieval-augmented generation) technology addresses these weaknesses by combining verified knowledge sources with the formulation capabilities of a language model. A RAG system first searches for relevant content in a controlled, validated document base and allows the language model to respond exclusively on this basis. This maintains technical control and makes responses more transparent and reliable.