Medable for Data Insights

Medable for data insights uses machine learning to bring intelligence to the data you collect from patients, devices, sites and integrated systems like EMRs, third-party APIs, imaging centers and central labs. It assists trial teams in understanding and identifying risks to patient safety and overall trial performance. The use of deep learning unlocks associations in the massive datasets captured that can not be identified by standard human methods.

Key Features

360-degree view of patients: View patients by therapeutic area, demographics, or locations.

Site performance: Create site performance measures and forecast site performance.

Forecasting: Conduct in silico trials, forecast study performance and predict roadblocks before they occur.

Real time insight: no delays in data collection or display.

Apply intelligence to multi-sponsor, de-identified datasets.

Autonomous optimization: research process dynamically optimizes for efficiency.

Highly customizable: Configurable, role-based alerts, notifications and tasks.

Real-time predictive, prescriptive and autonomous functionality.

Adaptive trials: increased flexibility.

Multiple machine learning algorithms supported:

  • Deep learning
  • k-means clustering
  • Random forests
  • Neural networks
  • Bayesian inference and querying
  • Dimensionality reduction using principal component analysis
  • Time series analysis through window sampling
  • Various statistical tests that produce p-values
  • Data normalizations
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Our Capabilities

Medable’s technology is currently being used by over 750,000 patients across 5 continents. We are the only enterprise cloud purpose built for life sciences with dedicated AI and machine learning. We have experience with registry studies and Phase I-IV clinical trials as well as in the following areas and more.

  • eConsent
  • ePRO
  • eCOA
  • eSource
  • Connected Devices
  • Patient Engagement
  • Global Device Provisioning
  • Multi-language
  • Data Management and Reporting
  • 21 CFR Part 11 Compliance
  • Hybrid Trials
  • Direct to Patient
  • Virtual Trials
  • Software as a Medical Device