Overview
PhaseV Trial Optimizer is offered as a full-service costume solution, with PhaseV partnering with sponsors from start to finish to design and optimize clinical trials. Leveraging advanced AI/ML simulations and proprietary optimization algorithms, PhaseV balances cost, power, duration, adaptability, and probability of success to deliver a fully optimized trial design ready for implementation.
A cornerstone of this service is the Causal-to-Design workflow, which enables sponsors to harness insights from prior trials using advanced causal machine learning. By systematically analyzing historical trial data, PhaseV identifies patterns in treatment response, placebo effects, and patient heterogeneity, refines inclusion and exclusion criteria, and extracts evidence-based strategies that directly shape the next study. This ensures that each trial builds on the accumulated knowledge of past efforts, resulting in smarter protocols and higher probabilities of success.
Throughout the process, PhaseV collaborates closely with sponsors to define endpoints, recruitment strategies, and statistical assumptions, while running extensive Monte Carlo simulations to evaluate scenarios and provide data-driven recommendations on sample size, alpha allocation, and interim analysis schedules.
PhaseV applies its Custom Trial Optimizer workflow directly in customers’ AWS environment, enabling secure, compliant, and efficient study design optimization within their AWS Cloud.
Highlights
- Rapid Simulation Engine: PhaseV runs millions of simulations within minutes to optimize any trial design - fixed, adaptive, or Bayesian. For adaptive studies, we provide early insight into dynamic strategies such as response-adaptive randomization, sample size re-estimation, arm dropping, and group sequential BOIN, then compare scenarios to deliver a trial design tailored to each sponsor’s priorities.
- Causal-to-Design: Leverage PhaseV's Causal-to-Design to integrate insights from past trials to further optimize I/E criteria and inform other development considerations. Causal-to-Design feature draws insights from sponsor's past trial data while augmenting it with any relevant data (if and as available) within PhaseV's data lake.
- Placebo Response Estimation: PhaseV's algorithms can instantly model average placebo response rates by leveraging relevant study data and real-world data, all within a click of a button.
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To learn more or for issue resolution, customers can reach PhaseV support at support@phasevtrials.com or via our Contact Us page (https://www.phasevtrials.com/contact ). We provide assistance with service usage, troubleshooting, and issue resolution