Knowledge Base Retrieval and Recall for Clinical Trial

Data Characteristics in this Domain

Regulatory affairs data for clinical trial pre-screening primarily originates from regulatory documents, guidelines, and technical review requirements published by global drug regulatory agencies (e.g., FDA, EMA, NMPA). It also includes internal historical submission cases, communication records, and expert opinions. This data updates infrequently, typically with regulatory revisions or new guideline releases. Document structures are predominantly hierarchical legal texts, technical specifications, and approval notices, often containing numerous tables, attachments, and references. Fields and units are highly standardized. Examples include drug names, indications, dosages, adverse reactions, manufacturing processes, and quality standards. Units strictly adhere to pharmaceutical or medical measurement norms, such as milligrams (mg), milliliters (ml), moles (mol), and percentages (%).

Constraints Imposed by these Characteristics on Knowledge Base Retrieval and Recall

The hierarchical structure of regulatory documents and guidelines requires knowledge base segmentation to identify and maintain the logical integrity of the original text, preventing context loss from over-segmentation. Low update frequency means knowledge base content remains relatively stable after initial construction, but each update requires accurate incremental or full synchronization. Numerous tables and attachments carry critical information, demanding high performance from parsers for table recognition and content extraction, directly impacting retrieval accuracy. Standardized fields and units make retrieval strategies based on exact matching and entity recognition more effective. This also requires robust semantic similarity calculations to accurately recall synonymous concepts expressed differently.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`Chunk size` (Segment Length)	`500–800 characters` (characters)	Balances the integrity of regulatory provisions with information density per segment, preventing context fragmentation.
`Recall count` (Recall Count)	`Top 10–15 entries` (top 10–15 items)	Regulatory affairs information is dense; increasing recall quantity covers potentially relevant provisions.
`Similarity threshold` (Similarity Threshold)	`0.78–0.85`	Balances recall rate and accuracy, adapting to the professional and rigorous nature of regulatory texts.
`Rerank result count` (Rerank Return Count)	`Top 5 entries` (top 5 items)	Selects the most relevant content, improving the efficiency and quality of the final presentation.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds` (seconds)	Addresses potential timeout issues when parsing large regulatory documents and complex tables.
`UPLOAD_FILE_MAX_SIZE`	`100 MB`	Accommodates uploading large PDF regulatory documents and historical submission materials.

Common Pitfalls

Garbled Chinese filenames after file upload: This typically results from file systems or encoding conversions failing to correctly handle UTF-8 character sets.
Missing or malformed table content in retrieval results: This occurs when the PDF parser cannot effectively recognize and extract complex table structures, leading to data loss or serialization errors.
Insufficient recall results, failing to cover all relevant clauses: This might be due to a Similarity threshold (Similarity Threshold) set too high, or a Chunk size (Segment Length) that is too short, fragmenting semantic units and affecting similarity calculations.

How to Verify Configuration

Upload a typical regulatory document (e.g., ICH E6(R2) guideline) and check if the knowledge base segment preview maintains the original paragraph and hierarchical structure.
For submission cases containing complex tables, perform a retrieval and verify the completeness and readability of table content in the recall results.
Use query statements containing specific regulatory clauses or technical terms. Through multiple tests, verify if Recall count (Recall Count) and Similarity threshold (Similarity Threshold) effectively recall all highly relevant key provisions while filtering out irrelevant content.
Monitor backend logs to confirm no timeout or encoding error messages related to PARSE_FILE_TIMEOUT_SECONDS appear during file upload and parsing.

The values provided are common starting points and should be measured against specific 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.