Unlock Trial Success with Causal-ML
Uncover key drivers of heterogeneity, predict outcomes, and optimize recruitment with causal ML—helping sponsors rescue trials, improve success rates, and maximize asset value.
No obligations. Just insights.
Rescue. Refine. Realize Potential.
Smarter Trials Through Causal Inference
Leverage advanced machine learning to detect hidden heterogeneity, predict treatment outcomes, and drive smarter, evidence-based decisions across every stage of the clinical trial process.
Detect heterogeneity across multiple covariates and complex biological signals
Identify the main drivers behind patient variability
Predict treatment effects and success probabilities
Recommend optimal subgroups or biomarkers for targeted trials
Inform smarter site selection and refined recruitment strategies
Optimize Clinical Trials with Advanced Analytics
Causal-ML evidence enables sponsors to:
Rescue failed trials
Increase probability of success
Harness each asset’s full potential
Trial Navigator
Causal-ML HTE Workflow
Causal-ML evidence enables sponsors to...
Data Ingestion and Processing
Clinical Knowledge
Feature Selection
HTE Estimation
Subgroup Detection
Validation, Sensitivity Analysis & Robustness
