What Data for This Category Looks Like
Biopharmaceutical research data primarily comes from CDE review public documents, pharmaceutical company clinical study reports, patent databases, NMPA-approved package inserts, and industry annual reports.
Data update cadence follows multiple schedules: CDE review documents update in real time alongside approval progress, pharmaceutical company annual reports are released quarterly or annually, and patent data is synced and published daily.
Document structures include standardized fields:
- Clinical data fields include administration dose, trial duration, and adverse reaction indicators, with units including mg, week, and %
- Patent documents include application number, publication date, and claim items
- Package inserts clearly list indications, dosage and administration, and contraindicated populations
Constraints Imposed on Conversation Logging and Auditing
Multi-source updates and complex field structures of biopharmaceutical research data require conversation logs to bind document version numbers and hit fields. This prevents audit traceability failure caused by data iteration.
For long document and multi-field recall scenarios, logs must only record recalled fragments, not full documents. Logs must also record precise timestamps for inference latency.
Compliance requirements mandate that logs fully retain core fields for user identifiers, request parameters, and return results. Logs must support aggregating historical conversations by custom user ID.
Additionally, the sensitivity of biopharmaceutical data requires logs to avoid disclosing undisclosed clinical or patent information. Sensitive fields must be desensitized before storage.
Configuration Settings
The following table outlines configuration items, recommended settings, and supporting rationale:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
logRetentionDays | 180 days | Biopharmaceutical research data requires long-term compliance auditing. 180 days meets standard industry regulatory cycle requirements |
enableCustomUidLog | Enabled | Supports binding custom business user IDs, which matches the needs of research teams to group audits by project or account |
logRecordFragmentOnly | Enabled | Prevents excessive storage usage from long document logs. Only records valid recalled document fragments during conversations |
sensitiveFieldMaskList | ["administration dose", "subject number", "undisclosed indications"] | Biopharmaceutical clinical data includes sensitive fields. Specified fields must be desensitized before being stored in logs |
autoLogQueryTime | Enabled | Accurately records inference latency for each question-and-answer interaction, which supports performance auditing for research scenarios |
versionBindLog | Enabled | Associates recalled documents with their version numbers, ensuring audit teams can trace back to the data source version used at the time |
The parameter values provided on this page are common recommendations for initial configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: User historical conversation records cannot be saved in guest-only scenarios, and conversation content from different visitors is mixed. Cause: The
enableCustomUidLogconfiguration is not enabled, and no temporary session ID is bound, so logs cannot associate visitor identifiers. - Phenomenon: Full document content is stored in logs, leading to excessive storage resource usage. Cause: The
logRecordFragmentOnlyconfiguration is not enabled, and full long clinical reports are stored in log entries. - Phenomenon: Inference latency fields are empty, making it impossible to count question-and-answer performance. Cause: The
autoLogQueryTimeconfiguration is not enabled, or the configured timeout threshold is too low, causing latency statistics to fail.
How to Verify Proper Configuration
- Initiate a test conversation with a custom user ID, and check whether the log details page displays the passed custom user identifier.
- View the content of a single conversation log, confirm that only recalled document fragments are displayed, and no full clinical reports or full patent documents are included.
- Check the performance metrics section in the log details, confirm that there is a recorded field for inference latency.
- Verify sensitive fields such as administration dose, confirm that the log displays desensitized placeholders instead of original values.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.