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Powering Clinical Development and Recruitment with Machine Learning

Ensure Clinical Trials Proceed Apace by Connecting Patient, Site, Demographic, and Principal Investigator Data 

By Lana Feng, Ph.D. and Dylan James Brock, MFA

Published Online: 14 October 2022

What’s Inside?

In clinical trials, discovering valuable yet hidden insights can prove advantageous to professionals aiming to improve trial design, feasibility, and enrollment.

Connecting multiple data sets can help with these goals. The same data that can enhance feasibility can also be used to find principal investigators with a track record of successful and all-inclusive trials and to recruit diverse patient groups.

Researchers may wish to pool all data sources under an analytical layer for higher chances of success in designing and running clinical trials.

  • The Key to Clinical Trial Success
  • Principal Investigators are Hard to Find
  • Meeting the Goal of Greater Patient Diversity
  • Agile Decision-Making with Connected Data
  • Deeper Insights for Clinical Development
  • References

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