Build transformative clinical intelligence powered by causal modeling and predictive analytics. Understand why trials fail before they start.
Most drug candidates fail in the clinic, not discovery, due to:
From data integration to decision support, our platform provides end-to-end capabilities for clinical trial optimization
Integrate biomarkers, omics data, prior trial outcomes, and real-world evidence into a unified platform
Predict responder vs non-responder subgroups and identify optimal inclusion/exclusion criteria
Build causal graphs linking patient characteristics, dosing, endpoints, and adverse events
Run counterfactual simulations to test protocol modifications before implementation
Predict probability of efficacy failure, safety signals, and enrollment delays
Protocol options ranked by Expected Trial Success with full explainability
"Restricting enrollment to Biomarker-Positive Group A increases probability of success from 32% → 54%, while reducing sample size by 20%."
Generated from causal trial simulation on Protocol NCT-2024-045
Join leading pharmaceutical companies using AI to predict trial outcomes and optimize protocols
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