KerusCloud®

• Visualize patient recruitment scenarios: Simulate recruitment rates and site numbers to understand how population choice impacts your study’s length and probability of success.
• Forecast study timelines more accurately: Analyze your recruitment strategies in silico to better understand the operational landscape and impact of potential adjustments to recruitment strategies, sample sizes, and decision criteria, ensuring your real trial stays on track.

Explore patient recruitment capabilities

• Stay ahead of regulatory requirements: Ensure study designs comply with ICH E9(R1) guidelines. Incorporate estimand strategies that align with FDA and EMA requirements, keeping your study compliant while delivering results ready for regulatory approval.
• Identify the most effective study design: Explore a range of fixed and adaptive study designs in silico to evaluate how they impact study outcomes and enable you to reduce costs, accelerate timelines, and minimize patient burden.
• Enhance trial flexibility and manage uncertainty: Use KerusCloud’s probabilistic framework to estimate the likelihood of different outcomes as new data emerges, and refine your development plan accordingly.

Explore design & analysis options

• Leverage virtual population data: Manage complex virtual datasets and simulate your study in a way that accurately mimics actual clinical trial dynamics.
• Access predefined data libraries: Rapidly set up simulations that include virtual patient populations, recruitment scenarios and various adaptive design options.
• Streamline trial execution: Save time and resources by creating external control arms, reducing the need for extensive recruitment in clinical trials.
• Maintain patient privacy: Enable the sharing of regulated or sensitive data while maintaining privacy and compliance through anonymization.
• Address imbalanced or missing data: Generate large, auto-labelled datasets to support predictive modelling, machine learning, and AI so you can address imbalanced data in clinical studies.

Explore dataset generation

• Choose the right study design the first time: Use the interactive heatmap to visualize how different decisions affect the study’s probability of success.
• Support transparent decision-making: Share synthetic data, recruitment profiles, simulation results, and reports with your team throughout your trial.
• Analyze patient populations, recruitment, and trial dynamics: Integrate with R and other analytics tools to create tailored visualizations.