Data Characteristics for This Category
II-III clinical trial data originates primarily from Clinical Trial Management Systems (CTMS), Electronic Data Capture (EDC) systems, Statistical Analysis Systems (SAS), and Laboratory Information Management Systems (LIMS). This data updates frequently, typically with staged data locks weekly or monthly during trials. Document structures are complex, including clinical study protocols, Case Report Forms (CRFs), Informed Consent Forms (ICFs), Statistical Analysis Plans (SAPs), and Clinical Study Reports (CSRs). Fields cover patient demographics, medication adherence, adverse events (AEs), serious adverse events (SAEs), laboratory results, imaging data, and biomarkers. Units are highly standardized; for example, dosage units are commonly mg or µg, time units are days or weeks, and biomarker concentrations are ng/mL or U/L.
Constraints Imposed by These Characteristics on "Deployment and Upgrades"
The complexity and high update frequency of II-III clinical data require FastGPT instances to have efficient data ingestion capabilities and flexible knowledge base update mechanisms. Large volumes of structured and semi-structured documents necessitate robust document parsing to ensure accurate information extraction, especially for key fields within tables and figures. Diverse and heterogeneous data sources demand higher stability from data connectors and ETL processes. Standardized but numerous fields and units mean knowledge base construction requires precise semantic understanding and entity recognition to prevent confusion or misinterpretation during Q&A. Additionally, high data security and compliance requirements mandate that the deployment environment supports strict access control, audit logging, and encrypted data transmission.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Clinical Study Reports (CSRs) and other documents can be large, requiring sufficient upload space. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large files takes time; increase timeout to prevent interruptions. |
maxContext | 8000 tokens | Complex clinical questions often require a longer context window for understanding and answering. |
Chunk size | 1000–1200 characters | Ensures semantic completeness of key paragraphs in clinical trial protocols or study reports. |
Similarity threshold | 0.78 | Improves recall precision, reduces irrelevant information interference, and enhances answer accuracy. |
Rerank result count | Top 5 entries | Refines the ranking of retrieved results, prioritizing the most relevant clinical data. |
Common Pitfalls
- After a knowledge base update, the model answers still reference old data because knowledge base index rebuilding did not fully trigger or the cache did not refresh in time.
- Some clinical data fields are not recognized or matched in Q&A because critical entities and their corresponding units were not correctly extracted during data cleaning or document parsing.
- After restarting with
docker-compose up, FastGPT cannot connect to the oneAPI service because the oneAPI container's IP address changed, but FastGPT's configuration was not updated accordingly.
How to Verify Correct Configuration
- Upload a typical Clinical Study Report (CSR) document. Confirm it parses completely and key information, such as primary endpoints and adverse event rates, is retrievable in the knowledge base.
- Use FastGPT's Web interface to test with clinical trial data-related queries, such as "What are the primary efficacy indicators for drug X in Phase II clinical trials?" Check if the model accurately cites data from the knowledge base.
- Check FastGPT deployment logs to confirm the connection status with the oneAPI service is normal, with no connection timeout or authentication failure errors.
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.