Data Characteristics
Phase I clinical research data originates primarily from Investigator's Brochures (IB), Clinical Study Protocols (CSP), Informed Consent Forms (ICF), and Case Report Forms (CRF). These documents typically exist as PDFs, Word files, or scanned images. Update frequency varies: IB and CSP documents may update due to protocol revisions during a study, while CRF data is recorded in real-time as subjects are visited. Document structures are highly standardized, adhering to ICH GCP guidelines. Fields include subject screening criteria, dose escalation data, pharmacokinetic (PK) parameters, pharmacodynamic (PD) indicators, and adverse event (AE) records. Units are diverse; for example, plasma drug concentrations are often in ng/mL, doses in mg or μg/kg, and time points in hours or days.
Constraints Imposed by These Characteristics on "Dialog Logging and Auditing"
The highly standardized and sensitive nature of Phase I clinical R&D documents imposes strict requirements on dialog logging and auditing. First, while document update frequency is not high, each update may involve critical safety or efficacy data. Logs must trace back to the document version, ensuring conversations are based on the latest approved version. Second, the accuracy of key fields like PK/PD data and AE records is paramount. Dialog logs need to record the AI's extraction process for this structured information and its confidence level, facilitating manual review. Third, the sensitivity of subject data requires the logging system to have strict access control and anonymization capabilities to prevent sensitive information leakage. Queries and answers regarding critical information like dosage and AE must precisely match the original text; any deviation can lead to severe consequences. Auditing must quickly pinpoint the source of issues. Finally, due to multiple units and data types, logs must record unit conversions and data aggregation processes to ensure result consistency.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale for Recommendation |
|---|---|---|
maxContext | 8 | Phase I documents are highly interconnected; a moderate context avoids irrelevant information interference. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large files take time to parse; sufficient time prevents timeout interruptions. |
tokenLimit | 4096 | Balances document length with model processing capability, preventing context truncation. |
logRetentionDays | 365 days | Clinical trials have long durations; regulations require long-term log traceability. |
Sensitive Word Filter List | custom I 期相关词汇 | Ensures inappropriate queries or answers are recorded and flagged. |
Dialogue Log Storage Path | /var/log/fastgpt/clinical_dialogs | Centralized log management for easier auditing and backup. |
Common Mistakes
- Some critical data fields in dialog records are empty because extraction rules for specific PK/PD data formats in documents are incomplete.
- Audit reports cannot link to specific document versions because the
document_version_idwas not enforced during document upload. - When multiple users query simultaneously, some dialog logs are out of order or lost because the log writing mechanism did not adequately consider data consistency in high-concurrency scenarios.
Verification Steps
- Upload a simulated Phase I clinical study protocol containing dose escalation data and adverse event records. Confirm the AI correctly extracts and answers related queries, and the dialog log completely records the query content, AI response, and cited document snippets.
- In the audit interface, search for specific PK parameters or AE reports using keywords. Verify the log indexing function works correctly and accurately locates relevant dialogs.
- Simulate a document update, then perform a comparative query between the old and new documents. Check if the dialog log clearly displays the
document_version_idand if the AI's answers are based on the latest document version.
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.