Smarter Decisions.
AI Optimized Trials.
PhaseV empowers biopharma sponsors and CROs with AI/ML-driven solutions for fast, efficient, and accurate clinical development decisions.

Smarter Trials. Faster Results. Better ROI.
Higher Probability of Success
Increase your trial success rates with our AI-powered optimization tools.
Sharper Strategic Decisions
Make data-driven decisions backed by advanced analytics and predictive models.
Smarter Use of
Existing Data
Existing Data
Leverage historical data to inform and optimize your current trial designs.
Faster Trials with
Leaner Designs
Leaner Designs
Streamline operations and reduce time-to-market with efficient trial protocols.
Proven Results
40%
Reduced Enrollment
50%
Lower Trials Costs
40%
Shorter Trial Duration
30%+
Higher Probability of success
*The values shown are based on outcomes from real-world collaborations where PhaseV supported biopharma companies in optimizing trial design and operations.
Case Studies
Proven Outcomes: Transforming Clinical Trials
1. Causal-ML for HTE [Type II Diabetes]


Oramed is reinitiating a previously failed diabetes clinical trial after PhaseV's analysis identified a subset of patients who responded well to their oral insulin candidate
The subgroup results aligned with Oramed’s Phase 2 findings and were further validated by external studies, including data from multiple Phase 3 trials. The results underwent rigorous sensitivity testing and false discovery analysis to ensure robustness and reliability
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2. Trial Optimizer [Infectious Disease]

Phase 3 study redesign for biotech: Running extensive simulations across various designs, PhaseV presented alternative configurations and their impact, guiding client towards optimal design to meet trial objectives
Optimized Redesign Reduced Sample Size by 10-15% with Efficacy
3. Trial Optimizer [Rheumatic Disease]

Phase 2 simulations for biotech: Running extensive simulations across various designs, PhaseV presented alternative configurations and their impact, guiding client towards optimal design to meet trial objectives
4. ML Early Derived Endpoint Identification & Trial Optimizer [Systemic Lupus Erythematosus]

- PhaseV analyzed a Phase 2 randomized controlled trial (RCT) for a lupus drug, where the primary endpoint was BILAG score improvement at 24 weeks.
- PhaseV ML-based analysis showed BILAG data at week 8 could serve as a reliable early derived endpoint to predict improvement at week 24.
PhaseV then designed and simulated an adaptive trial using the early derived endpoint, demonstrating a significant reduction in required sample size and overall trial efficiency.
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5. Causal Disease Modeling [Oncology]

PhaseV’s PD-L1 blocker model closely recapitulates patient-level variability observed in the Atezolizumab trial (NCT02108652)

Publications
Discover the latest clinical development breakthroughs with insights and expertise from our thought leaders and friends