De-Risking Clinical Trials

De-Risk Your Submission

And Protect Your Potential Blockbuster

Machine learning improves data quality and scales to meet increasing demand while identifying patterns across thousands of patients and millions of data points to increase confidence in clinical trial data quality and de-risk submissions. Learn more about how Trial Assurance can help you protect your path to approval.

How To Leverage Machine Learning In The Context of Achieving Good Data Quality?

Improve Data Quality and Inspection Readiness

by avoiding data inconsistencies and submission erros.

Trial Assurance is a managed service by Medidata Solutions that can identify issues with potential regulatory impact and regulatory delay. It combines statistical & machine learning power and the expertise of ex-FDA statistical reviewers to deploy outlier detection across your clinical data. We have deployed over 40 full-service Trial Assurance engagements in pivotal phase 2/3 studies intended for regulatory submission, across 28 Sponsors, 50K+ patients and millions of data points analyzed. 


Minimize risk of failure from errors unrelated to drug’s efficacy Image

Minimize risk of failure from errors unrelated to drug’s efficacy

Sponsors can refocus on other critical activities and rely on their submission’s data quality to Medidata’s Trial Assurance service.

Protect your path to approval with machine learning driven data quality Image

Protect your path to approval with machine learning driven data quality

Enhance data quality with machine learning to identify and address anomalies that manual review would not

Accelerate time to market using insights from former FDA statistical reviewers Image

Accelerate time to market using insights from former FDA statistical reviewers

See how Medidata found an average of 61 data quality issues per trial, 22% of which were most likely to delay regulatory approval.

Additional Resources: How To Avoid Data Inconsistencies and Submission Errors

Case Study: Top 25 Global Pharma Prevents Data Quality Issues with Trial Asssurance

Discover how one pharma company avoided an extra FDA data review cycle and beat its competition to market.

Webcast: De-Risk Clinical Trials Using Machine Learning

Discover how one pharma company avoided an extra FDA data review cycle and beat its competition to market and get an inside look at the approval process with former FDA statistical reviewer.