Technical blueprint explaining how incoming FDA eCTD v4.0 XML payloads are parsed, processed via Large Language Models, and converted into fully compliant outbound HL7 RPS response packages.
The system parses incoming submissionunit.xml files conforming to the HL7 Regulated Product Submission (RPS) standard. It isolates the FDA's original Message ID, target document UUID, Context of Use (CoU) concepts, and raw query narrative.
The payload is evaluated against regulatory guidance databases and ICH guidelines. The AI engine classifies the query's impact level (High/Medium/Low) and maps relevant Module 3 or Module 5 regulatory references.
Using Together AI's high-capacity language models, a formal, audit-ready GxP response draft is authored, incorporating required scientific justification, batch data citations, and compliance language.
The final narrative is embedded into a newly synthesized outbound submissionunit.xml structure, configured with a relatesTo node targeting the agency's original request ID for full lifecycle traceability.