skip to main content
Global Search Configuration

Listen to our presentation with ICON at the Bio-IT Conference & Expo event

Bio-IT presentation

Machine Learning Approach to Predicting Patient Enrollment, Managing Risk & Accelerating Timelines in Study Feasibility

Failure to enroll patients is one of the leading causes of clinical trial delays. As life science organizations adopt more data-driven approaches to determining trial feasibility and seek to improve operational performance, the use of machine learning and predictive models can accelerate cycle times, improve site selection, provide more accurate enrollment forecasts to base decisions on, and reduce manual effort involved in scenario modelling.

To learn more about Citeline Study Feasibility with your company integration, click here

Thank you for requesting a demo

We have received your request and we will get back to you soon.

By continuing, you accept Pharma Intelligence UK may contact you with updates, relevant promotions and information about products provided by Pharma Intelligence UK. You understand that your information will be used in accordance with our Privacy Policy, and that you may withdraw your permission to receive any of our communications at any time.

You can unsubscribe at any time by following the links in any emails we send to you or by emailing See our Privacy Policy.