Data Characteristics
Medical affairs regulations and SOP (Standard Operating Procedure) documents are typically in PDF, Word, or rich text formats. Content covers drug development, clinical trials, compliance management, and medical information communication. These documents originate from internal quality management systems, regulatory guidelines, and industry consensus. Update frequency is stable, usually every few months to a year, but updates become more frequent with new drug launches or regulatory policy changes.
Document structure is rigorous, including definitions, flowcharts, approval records, version control information, and often references external regulations or guidelines. Common fields include document number, version number, effective date, revision history, scope, responsibilities, operating procedures, risk assessment, and attachment lists. Units are often dates, version numbers, personnel names, and department names.
Constraints on Deployment and Upgrades
The characteristics of medical affairs regulation documents impose specific requirements on knowledge base deployment and upgrades. First, document rigor and strong reliance on version control require precise version management capabilities to ensure users always access the latest and effective SOP. Second, external regulation references mean the knowledge base must handle complex internal and external links, maintaining their validity during content updates. Third, although document update frequency is not high, each update may involve linked revisions across multiple related documents. This requires efficient bulk import and update mechanisms, ensuring data consistency. Finally, the specialized content and terminology demand higher standards for text segmentation and embedding models, ensuring semantic accuracy and recall efficiency.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Medical affairs documents are often large, containing charts and attachments. This provides sufficient upload space. |
Chunk size (Segment Length) | 800 characters (characters) | Ensures each segment contains enough context while avoiding excessive length that could introduce irrelevant information, suitable for detailed SOP steps. |
Chunk Overlap Length (Segment Overlap Length) | 100 characters (characters) | Ensures necessary semantic continuity between segments, preventing critical information from being truncated. |
maxContext | 3000 Tokens | Regulation Q&A often requires a longer context to understand complex processes and conditions. |
Recall count (Recall Count) | Top 8 entries (top 8) | Regulation Q&A demands high accuracy. Increasing recall count improves relevance coverage. |
Similarity threshold (Similarity Threshold) | 0.75 | A strict threshold helps filter out irrelevant regulatory clauses, improving result precision. |
Common Pitfalls
- After uploading PDF files, some charts or complex tables may be missing from the knowledge base. This occurs because the PDF parser has limited capabilities for non-text elements.
- When users ask about specific regulatory clauses, the system returns too many results with low relevance. This usually happens when the segment length is set too long, causing individual segments to contain excessive irrelevant information.
- After updating some SOPs, user queries still return old content. This indicates the knowledge base did not correctly trigger or complete the version update process, leading to an inconsistency between the index and the actual document version.
Verification Steps
- Upload a PDF regulation document containing complex charts and tables. Verify that its content is fully parsed and retrievable.
- Ask questions about key terms and process steps within the document. Check the precision and contextual completeness of the returned results.
- Publish a new version of a regulation document, then immediately query it. Confirm the system accurately recalls the latest version.
- Simulate user queries involving multiple related regulations. Evaluate if the knowledge base can integrate information from different documents to provide coherent answers.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-21.