AI-HEART Lab Platform
SENTINEL: AI-Augmented Endpoint Adjudication for Clinical Trials
SENTINEL is an AI-augmented adjudication system designed to assist Clinical Event Committees (CECs) in determining trial endpoints with greater consistency, efficiency, and auditability. By combining natural language processing with structured evidence extraction, SENTINEL surfaces the clinical evidence adjudicators need — in the format they need it — without replacing the expert judgment at the heart of the process.
Six-Layer Adjudication Pipeline
Each case traverses a structured, auditable pipeline from raw document ingestion to a final, regulator-ready adjudication record.
Case Packet Ingestion
Structured and unstructured source documents — discharge summaries, imaging reports, ECGs, and lab data — are ingested and normalized into a standardized case dossier.
AI Pre-Processing & NLP
Natural language processing models parse free-text clinical narratives, resolve abbreviations, and map terminology to standardized ontologies (SNOMED CT, ICD-10).
Evidence Extraction
Relevant clinical evidence is identified and surfaced against the trial's pre-specified endpoint definitions, with traceability back to the source document.
Preliminary Classification
A trained classification model generates a preliminary endpoint determination with supporting rationale and a calibrated confidence score for each case.
CEC Review Interface
Adjudicators access a structured review interface presenting the AI-generated summary alongside source documents, enabling efficient, informed human oversight.
Final Adjudication & Audit Trail
Physician decisions are recorded with timestamps and rationale, generating an immutable, audit-ready record compliant with regulatory and sponsor requirements.
Development Status
SENTINEL is currently in active development. The platform architecture, six-layer pipeline, and CEC review interface have been designed and are undergoing iterative refinement. Formal validation — including concordance metrics, time-to-adjudication analyses, and inter-rater reliability data — will be conducted prior to launch and submitted for peer-reviewed publication. If you are a CRO, sponsor, or CEC physician interested in learning more or exploring early collaboration, reach out directly.