• SKIP TO CONTENT
  • SKIP NAVIGATION
  • Patient Resources
    • COVID-19 Patient Resource Center
    • Clinical Trials
    • Search Clinical Trials
    • Patient Notification System
    • What is Clinical Research?
    • Volunteering for a Clinical Trial
    • Understanding Informed Consent
    • Useful Resources
    • FDA Approved Drugs
  • Professional Resources
    • Research Center Profiles
    • Clinical Trial Listings
    • Market Research
    • FDA Approved Drugs
    • Training Guides
    • Books
    • eLearning
    • Events
    • Newsletters
    • White Papers
    • SOPs
    • eCFR and Guidances
  • White Papers
  • Trial Listings
  • Advertise
  • COVID-19
  • iConnect
  • Sign In
  • Create Account
  • Sign Out
  • My Account
Home » Florida Atlantic University Creates Model to Predict Success of COVID-19 Trials

Florida Atlantic University Creates Model to Predict Success of COVID-19 Trials

August 2, 2021

Researchers at Florida Atlantic University’s College of Engineering and Computer Science have become the first to model the probability of COVID-19 trials finishing, terminating, pausing or being withdrawn using machine learning algorithms.

Their study, published in PLOS ONE, downloaded 4,441 COVID-19 trials listed on ClinicalTrials.gov for analysis. According to the study findings, their model was accurate in predicting success or failure for COVID clinical trials, and the results showed computational methods were effective at helping to understand differences between completed and ceased trials. They also showed that such models can predict the status of a COVID trial with sufficient accuracy and help in planning and reducing costs for trials.

They used four feature types (statistical features, study keywords, drug features and embedding features) to understand trial administration, eligibility, study information, criteria, drug types, study keywords and embedding features frequently used in machine learning. Using those categories, the researchers generated 693 dimensions to represent each clinical trial pulled from ClinicalTrials.gov. The study found that while drug features and study keywords were the most informative of the feature types, all were needed to accurately predict a trial’s success or failure.

The researchers said they will conduct further evaluation of features found to be associated with trial completion vs. cessation and plan to deliver interpretable results experts can use to understand what types of trials are more and less likely to make it past the finish line.

Read the full study here: https://bit.ly/3leTqXF.

Upcoming Events

  • 16Feb

    Fundamentals of FDA Inspection Management: Reduce Anxiety, Increase Inspection Success

  • 21May

    WCG MAGI Clinical Research Conference – 2023 East

Featured Products

  • Spreadsheet Validation: Tools and Techniques to Make Data in Excel Compliant

    Spreadsheet Validation: Tools and Techniques to Make Data in Excel Compliant

  • Surviving an FDA GCP Inspection

    Surviving an FDA GCP Inspection: Resources for Investigators, Sponsors, CROs and IRBs

Featured Stories

  • Revamp-360x240.png

    Califf Calls for Major Evidence Generation Revamp, Experts’ Opinions Differ

  • AskTheExpertsGreen-360x240.png

    Ask the Experts: Managing Investigational Products

  • SurveywBlueBackground-360x240.png

    Survey Outlines Site Challenges, Successes on Diversity

  • PatientCentricity-360x240.png

    Site Spotlight: DM Clinical Shows Patient Centricity Doesn’t Have to Break the Bank

Standard Operating Procedures for Risk-Based Monitoring of Clinical Trials

The information you need to adapt your monitoring plan to changing times.

Learn More Here
  • About Us
  • Contact Us
  • Privacy Policy
  • Do Not Sell or Share My Data

Footer Logo

300 N. Washington St., Suite 200, Falls Church, VA 22046, USA

Phone 617.948.5100 – Toll free 866.219.3440

Copyright © 2023. All Rights Reserved. Design, CMS, Hosting & Web Development :: ePublishing