Data Characteristics
Bispecific antibody pharmacovigilance data primarily originates from clinical trial reports, real-world studies, post-market surveillance, and global pharmacovigilance databases (e.g., WHO VigiBase, FDA FAERS). This data often has a high update frequency, especially during initial market release and clinical study phases, with reports potentially generated weekly or monthly. The data document structure is complex, commonly including patient demographics, medical history, concomitant medications, adverse event descriptions (MedDRA coding), adverse event onset time, severity, outcome, causality assessment, and batch numbers. Specific fields include target combinations, mechanism of action codes, and antibody types (e.g., IgG1-bsAb, IgG4-bsAb). Units involve dosage (mg/kg), frequency (q2w), and duration (days).
Constraints Imposed by These Characteristics on "HTTP Interface and External Systems"
The high update frequency of bispecific antibody data requires HTTP interfaces to support efficient incremental synchronization mechanisms. This avoids performance burdens associated with full data pulls. The complex data document structure means that interface responses can be large, necessitating support for pagination or streaming. Unique fields like MedDRA codes for adverse events and antibody types require external systems to accurately identify and process them during data parsing. Additionally, unit information for dosage and frequency needs standardized conversion during data validation and integration. Semi-structured or free-text fields, such as causality assessments, demand robust character encoding and text processing capabilities from the interface to ensure data integrity. Traceability information like batch numbers requires the interface to support precise queries.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
requestTimeout | 60000 ms | Handles complex queries and large data transfers, preventing data synchronization failures due to timeouts. |
maxConnections | Calibrate by actual measurement | Ensures stable concurrent connections during peak data retrieval, preventing connection pool exhaustion. |
batchSize | 500–1000 entries | Balances the amount of data per request with processing efficiency, reducing memory consumption. |
encoding | UTF-8 | Ensures correct parsing of free-text fields like adverse event descriptions, supporting multi-language characters. |
retryAttempts | 3 times | Addresses network fluctuations or temporary external system failures, increasing data synchronization success rates. |
pollingInterval | 3600 seconds | Suitable for regular incremental synchronization, balancing data real-time needs with external system load. |
Common Pitfalls
- Symptom: Adverse event description fields received by the external system appear garbled or partially missing. Reason: The character encoding settings of the HTTP interface and the external system are inconsistent, leading to text parsing errors.
- Symptom: During incremental synchronization, some newly reported adverse event data is not retrieved. Reason: The external system does not correctly parse or utilize timestamp/sequence number fields like
lastModifiedDateorsequenceIdprovided by the HTTP interface for incremental queries. - Symptom: When retrieving bispecific antibody-related data, the interface returns
HTTP 429 Too Many Requests. Reason: Request frequency is not set appropriately, resulting in too many requests to the external system in a short period, triggering rate limiting.
How to Confirm Correct Configuration
- Simulate high-concurrency requests and observe the HTTP interface's response time and success rate. This ensures stable operation under expected load.
- Randomly select a batch of adverse event reports containing multiple languages and special characters. Verify that the external system can parse all fields completely and correctly.
- After configuring incremental synchronization in the external system, compare the newly added data in the external system and the source database for a specified period. This confirms data synchronization completeness.
Note: The values provided are common starting points. Measure them against your 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.