Zetyra: A Validated Suite of Statistical Calculators for Efficient Clinical Trial Design

Modern clinical trial design methods—such as covariate adjustment, group sequential monitoring, Bayesian predictive probability, adaptive sample size re-estimation, and survival analysis—can substantially improve trial efficiency. However, adoption remains limited due to fragmented software ecosystems, opaque validation practices, and high licensing costs. Zetyra is an integrated web-based platform providing 13 validated statistical calculators for clinical trial design across three methodological paradigms. Frequentist methods CUPED variance reduction for baseline-adjusted power and sample size calculations Group sequential design with O’Brien–Fleming, Pocock, and alpha-spending boundaries Survival power analysis using Schoenfeld and Freedman formulations Blinded sample size re-estimation (Kieser–Friede) Unblinded sample size re-estimation using promising-zone methodology (Mehta–Pocock) Bayesian methods Predictive probability of success (PPoS) for interim go/no-go decisions Prior elicitation tools Bayesian borrowing from external data (power priors, commensurate priors) Single-arm and two-arm Bayesian trial design Bayesian sequential monitoring Validation framework The platform was validated through 499 automated tests across 25 validation scripts, benchmarked against established statistical software (gsDesign, rpact), analytical solutions, Zhou & Ji (2024), and replications of published clinical trials (PACIFIC, MONALEESA-7, HPTN 083). The maximum observed numerical deviation was 0.034 in z-score scale for group sequential boundary calculations. All validation code and test cases are publicly available under an MIT license. Illustrative applications Example case studies demonstrate potential design efficiencies, including: ~30% sample size reduction through covariate adjustment (ρ ≈ 0.55) ~24% cost reduction via early stopping under group sequential monitoring improved Phase II decision-making using Bayesian predictive probability A Limitations and Future Directions section documents current methodological and operational constraints, including reliance on conjugate prior families, single-endpoint modeling assumptions, linearity assumptions for CUPED adjustment, exchangeability considerations for external-data borrowing, and the current status of regulatory compliance features (e.g., 21 CFR Part 11). This release includes: a 91-page technical white paper describing the statistical methods and validation framework a 47-page Bayesian Toolkit white paper detailing the Bayesian modules a 4-page executive brief summarizing the platform and use cases