Data Characteristics for This Category
Phase I clinical research data primarily originates from Electronic Data Capture (EDC) systems, Laboratory Information Management Systems (LIMS), and paper or electronic Case Report Forms (CRF) from clinical trial sites. This data updates frequently, especially during the trial, with new subject data, adverse event reports, and biosample test results generated daily. Document structures typically follow the International Conference on Harmonisation (ICH) E3 Common Technical Document (CTD) format for clinical study reports. This includes protocols, informed consent forms, ethics approvals, subject screening logs, dosage records, vital signs, laboratory test results, adverse event records, and concomitant medication records. Data fields involve subject IDs, visit dates, various physiological indicators, drug dosages, AE terms, and units (e.g., mg, mL, bpm, ℃, mmol/L).
Constraints Imposed by These Characteristics on Deployment and Upgrade
Diverse data sources require FastGPT deployments to configure flexible data ingestion capabilities. This means supporting connectors for various data sources to handle data import from EDC systems, LIMS, and document management systems. High update frequency necessitates real-time synchronization and incremental update mechanisms to avoid redundant imports and data lag. The CTD document format demands robust document parsing capabilities during data preprocessing to accurately identify and extract key information from different sections and tables. Standardized fields and units require data cleaning and normalization features to ensure consistent processing of data from different sources and units, preventing misinterpretations due to unit discrepancies. Additionally, given the typically large data volume, deployments need sufficient storage space and computing resources. Upgrades must assess new version resource requirements to ensure a smooth transition.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Phase I clinical study reports, especially PDF files with numerous charts and raw data, can be large. Large file upload support is necessary. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large PDF or Word documents can be time-consuming. Increasing the timeout prevents parsing interruptions. |
maxContext | 8000 | Text passages in Phase I clinical trial registration documents are often long, containing detailed trial descriptions, results analysis, and discussions. A larger context window helps maintain information integrity. |
Chunk size (Segment Length) | 800–1200 characters (characters) | Clinical trial report paragraphs have high information density. Longer segment lengths help preserve the integrity of medical concepts and reduce semantic fragmentation. |
Recall count (Recall Count) | 10–15 entries (items) | Ensures enough relevant data snippets are recalled for complex queries to cover potentially dispersed key information in Phase I clinical reports. |
Similarity threshold (Similarity Threshold) | Calibrate based on actual measurements | Clinical terminology and expressions are precise. Accurate similarity matching improves retrieval accuracy. Adjust this based on actual data and query performance. |
Three Common Mistakes
- Model not found in workflow: This usually occurs when a model is configured but not refreshed within the FastGPT interface, or the specific workflow node does not correctly select an enabled model.
- Cannot access
https://ip:3000after local deployment: The browser displays a connection failure or certificate error. This might be due to incorrect HTTPS certificate configuration or firewall rules blocking the port. - "File too large" error when uploading large files: The logs show a
413 Request Entity Too Largeerror. This happens if theUPLOAD_FILE_MAX_SIZEparameter is not correctly configured when starting the container, or the web server's (e.g., Nginx)client_max_body_sizeis not adjusted accordingly.
How to Verify Configuration
- Upload a PDF file containing Phase I clinical trial protocols, CRF templates, and other content. Confirm successful file parsing and chunking into the knowledge base.
- On FastGPT's model configuration page, select a configured model. Confirm its status is "Enabled" and successfully use this model in a workflow for a Q&A test.
- Attempt to upload a clinical report file close to the
UPLOAD_FILE_MAX_SIZElimit. Confirm the upload and parsing process completes without errors. - Perform semantic retrieval for key fields in Phase I clinical research data (e.g., adverse event types, dosage units like mg, subject IDs). Verify the accuracy and completeness of the recalled results.
The values provided are common starting points. Measure them against your own samples to determine the most suitable configuration.
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.