HTTP Interface and External Systems for SMO

Data Characteristics

Site Management Organizations (SMOs) in pharmacovigilance and adverse event reporting primarily handle data from Clinical Research Coordinators (CRCs) and investigators. This includes Serious Adverse Event (SAE) / Adverse Event (AE) reports, concomitant medication records, laboratory results, and subject visit records. Data typically arrives in structured or semi-structured formats, such as EDC (Electronic Data Capture) system exports, XML reports, PDF reports, or custom JSON packets. Data updates frequently, especially during ongoing trials; SAE/AE reports may require submission within 24 hours. Document structures are complex, involving medical terminology, dosage units, timestamps, reporter information, and event descriptions. Field discrepancies and inconsistent units can occur across different trials or sponsors.

Constraints on HTTP Interface and External Systems

The time-sensitive nature of SMO pharmacovigilance data requires HTTP interfaces to offer low latency and high availability. This ensures timely delivery of SAE/AE reports. Diverse data sources (e.g., EDC systems, laboratories) necessitate support for multiple data formats, such as JSON and XML. Field discrepancies and inconsistent units challenge data preprocessing and mapping; flexible configuration is needed to handle varying data structures. Sensitive medical data, like subject information, mandates HTTPS for all HTTP transfers. Additional authentication mechanisms, such as OAuth2 or API Keys, may also be required. Frequent data updates can lead to high API call frequencies, requiring consideration of concurrent processing capabilities and rate limits.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`requestTimeout`	`60000 ms`	Accommodates network fluctuations and external system processing times, preventing data loss due to timeouts.
`maxRetries`	`3`	Ensures eventual data delivery during temporary network issues or transient external system failures.
`contentType`	`application/json` or `application/xml`	Matches data formats exported by common EDC and laboratory systems.
`headers.Authorization`	`Bearer <token>` or `API Key <key>`	Fulfills authentication requirements for medical data transmission, ensuring data security.
`dataMappingRules`	Calibrate based on actual measurements	Data fields can vary across sponsors and trials; flexible mapping rules are necessary.
`batchSize`	`50–100 records`	Balances the volume of data per request with external system processing capacity, preventing failures from excessively large requests.

Common Pitfalls

Symptom: API calls return empty content or unexpected data. Reason: Incorrect dataMappingRules configuration prevents the external system from recognizing or parsing sent data fields.
Symptom: HTTP requests frequently time out or return 503 Service Unavailable errors. Reason: requestTimeout is set too short, or the external system has rate limits, and the calling logic lacks retry or backoff strategies.
Symptom: The external system cannot authenticate requests. Reason: The authentication credentials in headers.Authorization are expired, malformed, or not transmitted correctly.

Validation Steps

Perform end-to-end testing with simulated data for core SAE/AE reporting interfaces. Verify that the external system successfully receives and correctly parses all fields.
Check FastGPT's HTTP interface logs. Confirm a 200 OK status code or another success code, and that the response body content is as expected.
Monitor the external system's receiving logs or database. Verify that data fields, units, and timestamps match the sent data, and confirm data integrity.
Conduct stress tests during peak or high-concurrency scenarios. Validate that interface stability and response times meet business requirements, paying close attention to requestTimeout and batchSize performance.

The values provided are common starting points. They should be measured against specific samples and adjusted for the reader's own environment.

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.