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Trial DesignMedidata

Medidata Trial Design offers AI-powered solutions for safer, effective clinical trial designs using historical data and synthetic data generation.

Vendor

Vendor

Medidata

Company Website

Company Website

Trial Design Overview (Jun-23).pdf
Product details

Medidata Trial Design is a comprehensive software solution that leverages historical clinical trial data and advanced AI technologies to optimize clinical trial designs, predict therapeutic efficacy, enhance patient safety, and prevent trial failures. It also offers Simulants, a synthetic data tool that provides valuable insights while protecting patient privacy and intellectual property.

Key Features

Exclusive Historical Clinical Trial Data Access to data from over 30,000 cross-sponsored trials with 9 million patients

  • Patient-level data from 100+ countries
  • Complete with endpoints and covariate information

Synthetic Data Generation Simulants: A groundbreaking synthetic data product

  • Derived from Medidata's exclusive repository of clinical trial data
  • Meets rigorous regulatory and privacy constraints

Advanced AI Modeling Patented synthetic data generation models

  • Superior quality and privacy preservation
  • Outperforms leading synthetic data generators

Expert Collaboration Access to a team of industry experts

  • Includes former FDA members, pharma professionals, and researchers
  • Expertise in regulatory affairs, biostatistics, data science, and medical oncology

Benefits

Improved Trial Design Optimize protocols and predict obstacles before they become trial failures

  • Enhance patient selection and response prediction
  • Inform dosing strategies
  • Proactively mitigate serious adverse events

Enhanced Patient Safety Monitor and benchmark patients throughout the trial

  • Proactively identify patients at risk of adverse events
  • Implement preventive measures

Accelerated Medical Breakthroughs Leverage historical data to generate meaningful insights

  • Analyze unmet medical needs under existing standard of care
  • Model inclusion/exclusion criteria for optimal patient subpopulations
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