Data Characteristics
Regulatory affairs documentation in the biopharmaceutical sector primarily includes regulations, guidelines, technical review requirements, case studies, and internal Standard Operating Procedures (SOPs). Data sources are diverse, encompassing public documents from official bodies like the National Medical Products Administration (NMPA) and the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH), as well as internal submission materials and experience summaries from pharmaceutical companies. Update frequencies vary: regulatory documents are typically revised annually or irregularly, guidelines might be updated every few years, and internal SOPs iterate based on project progress and review feedback. Document structures usually feature hierarchical divisions such as chapters, clauses, and appendices, containing extensive specialized terminology, acronyms, and specific formatting requirements. Fields and units involve dosage units (mg, μg), concentration units (g/L, %), time units (year, month, day), and specific registration classification codes and review project numbers.
Constraints Imposed on Deployment and Upgrades by these Characteristics
The complexity and update pace of regulatory affairs documentation impose specific requirements on FastGPT's deployment and upgrade processes. First, the hierarchical structure and high density of specialized terminology in documents necessitate fine-grained segmentation and careful selection of embedding models during knowledge base construction to ensure accurate semantic understanding. Second, the periodic revisions of regulatory documents mean the knowledge base must support incremental update mechanisms, capable of rapidly identifying and integrating new version content while retaining the reference value of older versions. The specific formats and tabular data within documents require file parsers with robust structured information extraction capabilities to prevent critical data loss. Furthermore, considering the high data security and compliance requirements of some pharmaceutical companies, offline deployment and intranet upgrade capabilities become essential to support system iteration in environments without external network access.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk size (Chunk Size) | 800–1200 characters | Balances completeness of regulatory clauses with recall precision. |
Overlap Length | 100–200 characters | Ensures contextual continuity and minimizes information loss. |
Similarity threshold (Similarity Threshold) | 0.75 | Improves answer relevance and filters out irrelevant content. |
Recall count (Recall Count) | Top 5 | Balances recall efficiency with answer accuracy. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Accommodates the time required to parse large regulatory documents. |
UPLOAD_FILE_MAX_SIZE | 100 MB | Supports uploading large guideline and SOP documents. |
Three Common Mistakes
- System login failure or abnormal functionality after an upgrade. This typically occurs when core configuration files are modified directly without a complete backup during the upgrade process, leading to incorrect database connection parameters or service port configurations, which prevents the system from starting correctly.
- RAG question-answering results have too few items or poor relevance. This often results from improper document segmentation strategies, such as automatically segmenting multi-column Excel tables directly, causing each row of data to be incorrectly split or important context to be fragmented, affecting the accuracy of vector retrieval.
- Poor question-answering performance for certain specialized terms. This may stem from the default embedding model's insufficient understanding of biopharmaceutical professional vocabulary, failing to fully capture domain semantics and thus impacting similarity calculations.
How to Verify Correct Configuration
- Perform the version upgrade process in different network environments (e.g., intranet) to confirm that package download, installation, and service restart complete smoothly, and verify that all core functions operate normally.
- Select documents covering regulatory clauses, tabular data, and professional acronyms for knowledge base import. Check file parsing results to confirm reasonable segmentation and no loss of critical information, comparing with the original document content.
- Conduct multi-round question-answering tests for typical regulatory submission questions, such as "criteria for new drug classification" or "ethical review requirements for clinical trials." Evaluate the accuracy, completeness, and relevance of answers, and adjust recall and reranking parameters based on user feedback.
- Check system logs for any abnormal error messages, especially warnings or errors related to file parsing, database connections, and vector embedding.
The values given 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.