Drillo Analytics

CHALLENGE

Sharing health data is laborious and burdened by barriers.

Balancing patient privacy, legal, compliance, and security issues often hinder individuals, teams, and organizations as a whole from working together to share data

Poor data access hinders innovation, research, and collaboration for healthcare and pharmaceutical companies.

All the while, insufficient data protection mechanisms put patient privacy at risk.

SOLUTION

Our synthetic data Hub for Healthcare is a safe, compliant, and efficient way to work with healthcare data while maintaining the highest level of patient privacy.

Fuel medical research, analyze patient data, and improve collaboration with ease.

Use Cases for AI and Synthetic Data in Healthcare

Innovative leaders in the life sciences use AI and synthetic data to manage their operations better and accelerate discovery.

Here are a few examples of how the healthcare sector uses AI to optimize performance:

Clinical trial analysis 
Clinician workflow optimization and decision support 
Digital/data security 
Disease diagnosis & analysis 
Drug discovery & development

Financial and business analysis 
Operations management 
Patient data analysis 
Physical security 
Targeted marketing 
Treatment development

Proven With Research

Published by Rambam Health Care Campus

Analyzing Medical Research Results Based on Synthetic Data and Their Relation to Real Data Results: Systematic Comparison From Five Observational Studies

Read the paper

Published by Washington University in St. Louis

Spot the Difference: Comparing Results of Analyses from Real Patient Data and Synthetic Derivatives