Document Parsing and Chunking for Phase I Clinical Research

Data Characteristics

Phase I clinical research documents originate from sponsors, Clinical Research Organizations (CROs), central laboratories, and hospitals. These documents typically include clinical trial protocols, informed consent forms, ethics committee approvals, investigator brochures, case report forms (CRFs), original medical records, laboratory examination reports, adverse event reports, and statistical analysis plans and reports.

Documents update frequently, especially during a trial. Protocol amendments, CRF updates, and safety reports generate new versions continuously. Most documents are in PDF format and often contain tables, figures, scanned images, and unstructured text. Fields include patient demographics, dosage information, medication records, vital signs, laboratory indicators, imaging data, and adverse event descriptions. Units cover both SI and traditional systems, such as mg/kg, mmol/L, mmHg, ℃, and kPa.

Constraints on Document Parsing and Chunking

Frequent updates to Phase I clinical documents require the parsing system to support efficient version management and incremental parsing. This avoids redundant processing and ensures data timeliness.

Mixed content, including structured (tables) and unstructured (descriptive text), demands a parser capable of text extraction, table recognition, and content association. Scanned images require integrating high-quality OCR technology to convert image content into processable text.

Diverse fields and units, particularly specialized medical terminology and abbreviations, necessitate chunking that maintains semantic integrity. This prevents truncation of critical information. Data compliance and privacy require identifying and redacting sensitive patient information during parsing.

Key information scattered across long documents, such as adverse event reports or specific indicator changes, requires chunking strategies that effectively capture these local semantics.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`UPLOAD_FILE_MAX_SIZE`	`500 MB`	Phase I clinical documents often contain many images and scanned pages, resulting in large file sizes. This ensures large PDFs can be uploaded.
`Chunk size` (Chunk Length)	`800–1200 characters` (characters)	Balances the integrity of table and text content, preventing truncation of critical medical terms or data, while ensuring recall efficiency.
`Chunk Overlap Length` (Chunk Overlap Length)	`150 characters` (characters)	Ensures contextual continuity, especially in narratives spanning multiple pages or paragraphs, aiding semantic understanding.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds` (seconds)	Processing large PDF files and performing OCR takes time. This prevents parsing failures due to timeouts.
`Enable Table Parsing`	Enable	Table data is critical in Phase I clinical documents and must be effectively extracted.
`OCR Service Threshold`	`0.85`	Ensures accurate text recognition for scanned documents, reducing parsing deviations caused by recognition errors.

Common Mistakes

Uploaded PDF files have misaligned tables or incomplete recognition. This occurs when the OCR service has insufficient capability for complex table structures or the OCR Service Threshold is set too low.
Document parsing times out, displaying "Custom parsing service interface timeout." This typically happens when PARSE_FILE_TIMEOUT_SECONDS is set too short, and processing large files exceeds the expected time.
After uploading a file during a conversation, critical information like drug dosages or laboratory indicators are not correctly extracted. This is often because Chunk size is set too small, breaking semantic integrity, or Yes noEnabledTable Parsing was not fully utilized, leading to lost table data.

How to Verify Configuration

Upload a typical Phase I clinical trial protocol PDF. Check the parsed text content to confirm that table data is complete and correctly formatted.
Upload original medical records containing complex scanned images. Check the accuracy of key medical terms and numerical values in the parsed results.
Upload a large investigator brochure exceeding 100 pages. Observe whether the parsing process times out. Check the number of parsed chunks and content coverage to ensure no critical sections are missed.

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.