AI Platform for Clinical Trial Design, Risk Forecasting & Decision Support

Build transformative clinical intelligence powered by causal modeling and predictive analytics. Understand why trials fail before they start.

The Challenge

Most drug candidates fail in the clinic, not discovery, due to:

  • Poor patient stratification
  • Protocol complexity
  • Unanticipated safety or efficacy signals
  • AI models exist, but they rarely integrate into trial design decisions

Complete Clinical Intelligence Pipeline

From data integration to decision support, our platform provides end-to-end capabilities for clinical trial optimization

Data Integration

Integrate biomarkers, omics data, prior trial outcomes, and real-world evidence into a unified platform

Patient Stratification

Predict responder vs non-responder subgroups and identify optimal inclusion/exclusion criteria

Causal Modeling

Build causal graphs linking patient characteristics, dosing, endpoints, and adverse events

Trial Simulation

Run counterfactual simulations to test protocol modifications before implementation

Risk Forecasting

Predict probability of efficacy failure, safety signals, and enrollment delays

Decision Support

Protocol options ranked by Expected Trial Success with full explainability

Executive Insights

"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

Ready to transform your clinical trials?

Join leading pharmaceutical companies using AI to predict trial outcomes and optimize protocols

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