Prescreening
Prescreening
Analyze patient notes against protocol criteria to find eligible participants and extract structured data from unstructured charts.
Revolutionizing healthcare with artificial intelligence since 2020.
Meet MAIA™ - the Medical AI Assistant - specially designed to address unmet needs through the entire clinical trial life cycle
Analyze patient notes against protocol criteria to find eligible participants and extract structured data from unstructured charts.
An interactive, document-aware AI that answers questions and guides staff or patients through workflows.
Analyze population data to optimize eligibility criteria and forecast enrollment outcomes.
Translate and back-translate clinical content with certificates of translation in 40+ languages.
Reconcile EDC, imaging, lab inventory, and testing data to ensure protocol compliance.
Draft and review protocols, lab manuals, investigator brochures, budgets, contracts, and invoices.
Automatically detect and remove protected health information across documents.
Compare EDC and lab data to protocol requirements to flag potential deviations.
Tailored software solutions built for your workflows and data landscape.
Patient charts processed
Clinical sites
Clinical Trials
80% of clinical trials report enrollment issues, often due to prescreening constraints.
Many trials require screening 10,000+ patients for eligibility, a task well suited to AI augmentation.
With 43,677 new trials registered in 2024 and increasingly complex protocols, teams need AI to keep pace.
An oncology site implements MAIA™ prescreening in February 2024
Moved from prescreening 250 out of 500 monthly patients to prescreening all incoming patients.
Enrollment increased by >80%, representing a ~$5M annual revenue lift.
MAIA™ accuracy has been measured at >95%.
We aim to revolutionize healthcare through MAIA™, our flagship Medical AI Assistant, and a growing suite of applied solutions.
Clinical AI is committed to delivering real value by addressing specific unmet needs. We believe in under-promising and over-delivering.