Data Characteristics
Site Management Organizations (SMOs) involved in clinical trial pre-screening primarily use data from multi-center clinical trial protocols, Investigator's Brochures (IB), Case Report Forms (CRF), and ethics approvals provided by sponsors. These documents are typically PDF or Word files. Content includes trial design, inclusion/exclusion criteria, visit schedules, and adverse event reporting procedures. Data update frequency is relatively low, occurring mainly during protocol revisions or version updates. Document structures are complex, containing numerous tables, nested lists, images, flowcharts, and specialized terminology. Fields and units are highly standardized, such as dose units (mg/kg), time units (weeks, days), and physiological indicators (mmHg, mmol/L). Abbreviations or specific codes are common.
Constraints on "Document Parsing and Chunking" from these Characteristics
The complex structure of SMO documents challenges parsing accuracy. This is especially true for tables and nested lists, where data integrity and hierarchical relationships must be correctly identified. Specialized terminology and abbreviations require the model to understand domain-specific vocabulary to avoid misinterpretations. Key information in images and flowcharts, such as trial flow diagrams or dose adjustment charts, must be effectively extracted. Failure to do so directly impacts pre-screening decisions. The low data update frequency means real-time processing is not critical, but robust historical version management and traceability are essential. Standardized fields and units are core to pre-screening. Parsing must precisely identify and retain their semantics. Any parsing error in units or values can lead to ineligible patient enrollment, with severe consequences.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 200 MB | Clinical trial protocols and similar documents can be large, requiring support for large file uploads. |
Chunk Length | 800–1200 characters | Balances semantic completeness and retrieval efficiency, adapting to complex paragraph structures. |
Overlap Length | 100 characters | Ensures context continuity and prevents critical information from being truncated by chunking. |
maxContext | 16000 tokens | Accommodates long document contexts, ensuring sufficient information coverage during RAG retrieval. |
PARSER_TIMEOUT_SECONDS | 600 seconds | Parsing complex PDF or Word documents can be time-consuming; this provides ample processing time. |
Enable Image OCR | True | Ensures key information in images, such as flowcharts and tables, is recognized and indexed. |
Common Mistakes
- Missing or misaligned table data in parsing results, where critical inclusion/exclusion criteria are not identified. This happens because the document parser fails to correctly recognize complex table borders and merged cells.
- "Invalid image file" errors in parsing logs after uploading DOCX files with embedded images. This occurs when the parser does not support the specific image format or encounters abnormal image data streams.
- Incorrect expansion or understanding of specialized abbreviations (e.g., "CRF", "SAE") in pre-screening results, leading to inaccurate information retrieval. This is due to a lack of domain-specific vocabulary or terminology assistance during parsing.
Verification Steps
- Upload a typical clinical trial protocol PDF file. Check if the parsed text content completely retains all sections, tables, and list structures.
- Randomly select key inclusion/exclusion criteria from the document. Verify if they can be accurately retrieved through search and if the retrieved snippets are semantically complete.
- Upload a document containing complex flowcharts or diagrams. Confirm that text information within images is recognized via OCR and integrated into the text content. Compare the information increment before and after parsing.
The values provided are common starting points and should be measured against your 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.