HTTP Interface and External Systems for CRO Quality

Data Characteristics

Contract Research Organizations (CROs) generate many quality documents throughout clinical trial phases. These include trial protocols, informed consent forms, ethics approval documents, case report forms (CRFs), data management plans, statistical analysis reports, and Standard Operating Procedures (SOPs). These documents typically store as PDF, Word, and Excel files within internal Document Management Systems (DMS) or Electronic Data Capture (EDC) platforms. Data update frequency is high during key milestones such as project initiation, protocol amendments, data lock, and report writing. It remains relatively stable during routine operations. Document structures are highly standardized, adhering to industry guidelines like ICH-GCP. Field content includes trial numbers, subject IDs, visit dates, drug dosages, laboratory indicators (with units such as mg/kg, mmol/L), and adverse event codes.

Constraints Imposed by These Characteristics on "HTTP Interface and External Systems"

The standardization and regulatory nature of CRO quality documents require HTTP interfaces to precisely match specific fields during data extraction. For example, the system must identify and extract Trial Number or Subject ID from PDF reports. Document update frequency dictates the strategy for external system synchronization, whether scheduled or trigger-based, to prevent stale data. The prevalence of PDF and Word documents means HTTP interfaces calling external parsing services require robust file type support and parsing stability. The diversity of laboratory indicator units necessitates that the RAG system understands and matches values across different units during retrieval, such as converting mg to g. Furthermore, integration with DMS or EDC systems typically involves authentication mechanisms like OAuth2.0 or API Keys and adherence to specific RESTful API specifications.

Configuration Guidelines

Configuration Item	Suggested Value	Rationale
`HTTP_REQUEST_TIMEOUT_SECONDS`	`60 seconds`	Most CRO internal DMS or EDC system interfaces respond within seconds to tens of seconds. This allows sufficient time for parsing and data transfer.
`MAX_FILE_SIZE_MB`	`200 MB`	CRO quality documents, especially PDFs containing images or charts, can be large.
`EXTERNAL_API_AUTH_TYPE`	`OAuth2.0`	Most modern DMS or EDC systems use OAuth2.0 for secure authentication, ensuring data access permissions.
`DOCUMENT_PARSE_CONCURRENCY`	`Calibrate by actual measurement` (Calibrated based on actual measurements)	This ensures balanced resource utilization between external parsing services and the FastGPT server when processing many document parsing requests, preventing overload.
`KNOWLEDGE_BASE_UPDATE_INTERVAL`	`Once daily`	Considering the update frequency of CRO documents, daily scheduled updates reflect the latest data promptly while avoiding resource consumption from frequent updates.
`FIELD_MAPPING_RULES`	`JSON` format	Clearly defines the mapping between external system fields (e.g., `protocol_id`) and FastGPT internal fields (e.g., `Trial Protocol Number` - Trial Protocol Number).

Common Pitfalls

HTTP request returns 401 Unauthorized or 403 Forbidden: Typically due to incorrect EXTERNAL_API_AUTH_TYPE configuration, such as an expired API Key, invalid OAuth2.0 token, or insufficient permission scope.
Some fields are empty or incorrectly formatted after document content parsing: This often occurs when FIELD_MAPPING_RULES do not precisely match the actual text structure in the document or when regular expressions are incorrect, especially for fields with complex units or multi-line descriptions.
System experiences 504 Gateway Timeout when processing many documents: This indicates that HTTP_REQUEST_TIMEOUT_SECONDS is set too short, or DOCUMENT_PARSE_CONCURRENCY is too high, leading to slow responses from the external parsing service.

Verification Steps

Manually call the target DMS or EDC system's API via FastGPT's HTTP request module. Confirm successful retrieval of raw data in the expected format, such as a JSON object containing Trial Protocol ID and Document URL.
Upload a typical CRO quality document (e.g., a PDF trial protocol). Check the parsing results of this document in the knowledge base. Ensure that key fields like Trial Number, Subject ID, and Visit Date are correctly extracted and populated.
After configuring a scheduled synchronization task, verify the number of documents and their last modification times in the FastGPT knowledge base after the next synchronization cycle. Compare these with the source system to confirm data update timeliness and completeness.

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.