Data Characteristics for This Category
GMP-compliant clinical trial pre-screening data primarily comes from regulatory documents, guidelines published by drug administration authorities, Clinical Trial Application (CTA) documents submitted by pharmaceutical companies, and previous clinical trial reports. This data is typically unstructured, consisting of PDF regulatory texts, Word-format clinical protocols, and Excel-format patient inclusion/exclusion criteria lists. Update frequency is relatively low; regulatory documents are usually revised or new versions released annually, while clinical trial protocol revisions depend on project progress. Document structure is complex, containing extensive specialized terminology, tables, and figures. Fields and units involve dosages (e.g., mg/kg), time (e.g., hours, days), biomarker indicators (e.g., ng/mL), and various qualitative descriptive fields, such as adverse event classifications and subject screening criteria descriptions. The data also includes numerous references and cross-references, for example, between regulatory clauses or between protocols and appendices.
Constraints Imposed by These Characteristics on "Workflow Orchestration"
The unstructured nature of GMP-compliant data requires workflows to integrate document parsing and information extraction capabilities during the data preprocessing stage. The low frequency of regulatory updates means knowledge base updates can employ periodic full or incremental strategies, without requiring real-time updates. Complex document structures and specialized terminology demand higher accuracy for text segmentation and keyword extraction, necessitating fine-tuned models or domain-specific dictionaries. The diversity of fields and units requires considering unit conversion and standardization when matching and comparing different data sources, for example, unifying dosage units from different literature to mg/kg. Numerous references and cross-references require workflows to have context association and traceability capabilities, ensuring the traceability of pre-screening results for compliance. Additionally, compliance requirements mandate logging every workflow operation for audit purposes, which translates to detailed workflow execution logs.
Configuration Settings
| Configuration Item | Suggested Value | Rationale for This Value |
|---|---|---|
maxContext | 8000 tokens | Accommodates the context requirements of lengthy regulatory and clinical protocol documents. |
Chunk size (Segment Length) | 512 characters (characters) | Balances paragraph completeness with retrieval efficiency, improving knowledge recall accuracy. |
Recall count (Recall Count) | 10 entries (items) | Ensures coverage of relevant regulatory clauses and clinical standards, reducing omission risk. |
Similarity threshold (Similarity Threshold) | 0.78 | Filters out low-relevance results, focusing on high-confidence matches. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds (seconds) | Handles parsing large PDF documents, preventing file processing failures due to timeouts. |
Rerank result count (Reranked Return Count) | 5 entries (items) | Selects the most relevant regulatory or standard entries, enhancing the precision of pre-screening results. |
Three Common Mistakes
- Workflow execution times out, returning a
504 Gateway Timeouterror. This occurs when processing very large clinical protocols or regulatory files, where file parsing or model inference takes too long, exceeding gateway or service default timeout limits. - Key regulatory provisions are missing from pre-screening results. This happens when the text segmentation strategy is too aggressive, splitting a complete regulatory clause into multiple disconnected small segments, preventing the retrieval of the full context.
- After a global variable updates during a tool call, subsequent nodes do not receive the new value. This occurs when a global variable update operation happens within a sub-process, and its scope is not correctly passed to the main process or parallel branches during workflow design.
How to Confirm Correct Configuration
- Select a regulatory document containing complex tables and figures for parsing. Check whether the parsing results fully retain the table structure and key information.
- Upload a clinical trial protocol containing various dosage units. Use the retrieval function to verify whether numerical values with different units are correctly identified and standardized.
- Execute an end-to-end pre-screening workflow that includes tool calls. Check the workflow logs to confirm that all intermediate step outputs and global variable passing meet expectations.
The values provided are common starting points and should be measured against specific 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.