Automated Clinical Trial Data Analysis
Accelerate research with AI that extracts trial outcomes, identifies adverse events, detects protocol deviations, and automates safety monitoring
Clinical research generates massive volumes of structured and unstructured data from case report forms, clinical notes, lab results, and imaging studies. Manual data abstraction, safety monitoring, and outcome assessment require dedicated research staff to review thousands of pages of documentation per study, creating bottlenecks that extend trial timelines and increase costs.
The Problem
Clinical research coordinators spend 60-70% of their time on data abstraction, source document verification, and query resolution. Manual processing delays safety reporting, slows enrollment and analysis, and increases trial costs by hundreds of thousands of dollars per study due to extended timelines.
Source Document Review Burden
Verifying case report form accuracy against source documents including clinical notes, lab reports, and imaging requires line-by-line manual comparison for regulatory compliance.
Adverse Event Detection Delays
Identifying and categorizing adverse events from clinical narratives is time-intensive, delaying safety reporting to IRBs and FDA, and potentially missing serious events.
Protocol Deviation Identification
Detecting protocol deviations including inclusion/exclusion violations, procedure timing errors, and concomitant medication conflicts requires constant vigilance across all visits.
How OpenClaw Solves This
OpenClaw analyzes clinical trial documentation to automatically extract outcomes, identify adverse events, detect protocol deviations, and validate data accuracy. The system processes clinical notes, lab results, imaging reports, and CRFs to accelerate data abstraction, improve safety monitoring, and reduce research coordinator workload.
Automated Outcome Extraction
Extracts primary and secondary endpoints from clinical documentation including efficacy measures, lab values, imaging assessments, and patient-reported outcomes with temporal tracking.
Adverse Event Identification & Coding
Identifies adverse events from clinical narratives, categorizes by MedDRA terms, assesses severity and causality signals, and flags events requiring expedited reporting.
Protocol Deviation Detection
Monitors study conduct against protocol specifications, detecting inclusion/exclusion violations, visit window deviations, prohibited medication use, and procedure timing errors.
Source Document Verification
Compares case report form entries against source documentation to identify discrepancies, missing data, and transcription errors requiring query resolution.
How Clinical Trial Analysis Works
Data Ingestion & Normalization
System ingests CRFs, clinical notes, lab results, imaging reports, and informed consents, normalizing data formats and linking to trial protocols and study timelines.
Clinical Entity Extraction
AI extracts efficacy endpoints, safety events, lab values, vital signs, procedures, and concomitant medications from structured and unstructured documentation.
Protocol Compliance Analysis
System validates data against protocol criteria, detecting deviations, identifying adverse events requiring reporting, and flagging data quality issues for query generation.
Report Generation & Quality Review
AI generates safety reports, data quality reports, and query lists for research coordinator review. Validated outputs feed into EDC systems and regulatory submissions.
Measurable Results
Faster Data Processing
Reduce data abstraction and source document verification time from weeks to days, accelerating trial timelines and database locks.
Fewer Missed Events
Automated adverse event detection ensures no safety signals are missed in clinical narratives, improving participant safety and regulatory compliance.
Research Team Capacity
Free research coordinators from manual data entry and verification to focus on participant recruitment, protocol compliance, and study quality.
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Enterprise & Advanced
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Frequently Asked Questions
Accelerate Your Clinical Research
Stop letting manual data processing delay your trials. Automate clinical trial data analysis with AI that understands research protocols and regulatory requirements.
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