Query Anomaly Detection uses generative AI to find contextual, cross-domain data anomalies — and automatically generates the queries to resolve them.
Detect patterns and anomalies that rule-based and manual review never anticipate
Catch contradictions between treatments, symptoms, labs, and findings.
Turn anomalies into actionable queries, including cascading flags across dependent domains.
Layer study-specific requirements on top, with dynamically evolving rules.
Out-of-the-box anomaly scenarios
Across safety domains, with sponsor-specific scenarios on top — plus automated query generation
QAD applies layered AI analysis to incoming data, then drafts the query.
QAD checks inter- and intra-domain relationships to detect contextual anomalies.
AI pattern analysis evaluates lab results and adverse events, including timeline validation.
QAD validates relationships across domains and flags treatment/symptom contradictions.
Actionable queries are created automatically, with cascading flags across dependent domains.
Tuned to your study. Out-of-the-box scenarios cover the common cases; sponsor-specific scenarios and dynamically evolving rules adapt QAD to your protocol, and ongoing fine-tuning reduces false negatives over time.
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