Data Characteristics for This Category
Hematologic oncology registration documents include clinical trial reports, non-clinical study reports, drug manufacturing and quality control documents, and risk management plans. Data sources primarily consist of internal clinical data management systems from sponsors, trial data from CROs, pharmaceutical research laboratory data, and guidelines and regulatory documents issued by regulatory bodies. Data update frequencies vary; clinical trial data is continuously generated during trials, non-clinical data is relatively stable, and regulatory documents are updated periodically based on policy adjustments. Document structures are complex, often in formats such as PDF, Word, and Excel, containing large amounts of unstructured text, tabular data, images, and charts. Key fields include disease staging, treatment regimens, adverse event codes (e.g., MedDRA), and laboratory test result units (e.g., ng/mL, pg/mL).
Constraints on "Deployment and Upgrade" Due to These Characteristics
The data characteristics of hematologic oncology registration documents impose specific requirements on deployment and upgrades. First, the multi-source heterogeneous data formats and complex document structures require FastGPT to be configured with robust file parsing capabilities during deployment, especially support for nested tables and image recognition within PDFs. Second, the high update frequency of clinical trial data and the large volume of unstructured text mean that knowledge base indexing and incremental update strategies must be efficient to ensure information timeliness. Standardization of key fields like adverse event codes and laboratory test units requires strict cleansing and mapping during the data preprocessing stage to prevent semantic ambiguity. Furthermore, periodic updates to regulatory documents necessitate support for version control and difference comparison features to ensure the knowledge base always complies with the latest regulatory requirements. The deployment environment must consider storage and computing resources for handling large-scale data and ensure compliance with data transfer regulations.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Hematologic oncology clinical reports often contain numerous images and detailed data, resulting in large individual file sizes. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing complex PDF documents can be time-consuming; this avoids parsing failures due to timeouts. |
maxContext | 800–1200 characters | Ensures important contextual information, such as key trial results from clinical reports, is covered during queries. |
Chunk size (Segment Length) | 500 characters | Balances semantic completeness with retrieval efficiency, preventing loss of context due to excessive segmentation. |
Similarity threshold (Similarity Threshold) | Calibrate by actual measurement | Registration documents demand high accuracy; adjust based on actual recall performance to balance recall and precision. |
Rerank result count (Reranked Return Count) | Top 5 | Focuses on the most relevant core information, reducing interference from irrelevant data and improving answer accuracy. |
Three Common Mistakes
- After a knowledge base update, new data is not retrieved or retrieval results are inaccurate because incremental indexing tasks were not triggered correctly or parsing configurations do not match the new document structure.
- After a user query, the system returns results lacking critical data or with incorrect units because not all key fields were standardized and cleansed during the data preprocessing stage, leading to semantic inconsistencies.
- Inability to access or upload files correctly in the browser due to an outdated browser version or cross-origin security policy restrictions.
How to Verify Correct Configuration
- Upload a hematologic oncology clinical trial report PDF containing complex tables and charts. Check if the file is successfully parsed and if key data points from the report can be retrieved.
- Update a regulatory guidance document with new regulatory clauses. Then, query to verify if the knowledge base provides accurate answers based on the latest clauses.
- Randomly select multiple registered submission documents already in the knowledge base. Attempt to query key information such as disease staging, adverse event reports, and drug dosages. Check the accuracy and completeness of the system's returned results and compare them with the original documents.
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.