Data Characteristics in This Category
Stability study data primarily originates from periodic test results of drug or raw material physical, chemical, and biological properties under long-term, accelerated, and intermediate conditions. Data typically exists as structured tables (e.g., Excel), unstructured text (e.g., Word or PDF reports), and charts. These documents record test batches, test items, test methods, result values, units, and judgment criteria at different time points and under various storage conditions. Document update frequency is usually low; data is generated and compiled at preset time points (e.g., 0, 3, 6, 9, 12, 18, 24, 36, 48, 60 months) after the study protocol is finalized. Document structure is rigorous, adhering to guidelines like ICH Q1A(R2), and includes sections such as cover, table of contents, study objectives, materials and methods, results, discussion, and conclusion. Fields are often standardized test parameter names, batch numbers, dates, numerical values, and units.
Constraints on "Document Parsing and Chunking" from These Characteristics
The structured and semi-structured nature of stability study documents demands high-precision document parsing. Documents contain extensive tabular data, requiring accurate identification of table boundaries, row and column relationships, and correct extraction of numerical values and units. Images (e.g., chromatograms, gel electrophoresis diagrams) are auxiliary information; their content is typically not a direct parsing target. The key lies in the chart titles and descriptive text. Low update frequency means initial parsing quality is critical, with less need for subsequent re-parsing. Document content is highly specialized, containing numerous biomedical terms, abbreviations, and specific units (e.g., mg/mL, IU, pH, %). Parsing must avoid separating numerical values from units and ensure the integrity of specialized terminology. During chunking, prioritize maintaining the completeness of tables and paragraphs to avoid splitting a single test result or logical unit, which would affect subsequent recall accuracy.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
Chunk size | 800–1200 characters | Balances table and paragraph integrity, preventing loss of context from overly small chunks. |
Chunk Overlap Length | 100–200 characters | Provides sufficient context to connect adjacent chunks, reducing information loss. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Accounts for the complexity of parsing large PDF reports, allowing ample processing time. |
Supported File Types | docx, pdf, xlsx | Covers common stability report formats, including structured data sources. |
Table Content Extraction | Enabled | Ensures accurate identification and extraction of batch, condition, and result data from tables. |
Image tabletsOCR识别 | Disabled | Images in stability studies are often auxiliary diagrams; key information is already in text descriptions, so additional OCR is unnecessary. |
Three Common Mistakes
- Table data in parsing results is garbled or missing: This occurs due to incorrect identification of table structures, leading to confusion in row or column data.
- After uploading a document containing images, the log shows an
Invalid image fileerror: This might be because the parser does not support the embedded image format, or the image is too large and exceeds memory limits. - After chunking, a complete test result is split across multiple chunks: This can happen if the chunk length is set too small, failing to preserve complete semantic units.
How to Verify Correct Configuration
- Upload a typical stability study report (containing text, tables, and a few images) and check if the parsed content is complete, especially tabular data.
- Randomly select chunks from the parsing results and check if each chunk contains one or more semantically complete logical units (e.g., data for a specific test time point of a batch).
- Check the parser's recognition of specific technical terms and units, confirming that numerical values and units are closely associated.
- Compare with the original document to verify that key test items, result values, and judgment criteria are accurately extracted.
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.