INSIGHTS ON CLINICAL TRIAL TECHNOLOGIES

• The AI Paradox In Clinical Trials

  AI is advancing the way clinical trial results are analyzed and interpreted. But those advancements still depend on the quality and reliability of the data generated during the trial itself.

• Improving Clinical Trial Performance Through Central eSource

  See how a top five pharmaceutical company leveraged our esource platform to enhance site performance, improve data consistency, and enable remote monitoring.

• Notifications And Reminders

  Configurable alarms appear as banner alerts on subjects’ devices, while email notifications help sites monitor potential non-compliance and respond to newly uploaded symptom severity data.

• Virtual eConsent For Decentralized Trials

  Virtual eConsent improves accessibility and compliance in decentralized trials, streamlining enrollment with a secure, user-friendly process for informed consent in remote research.

• Clinical Trial Starts Rose At Slower Pace In 2024

  12/8/2025

  Clinical trial starts grew 5.5% to 10,503 in 2024, a slowdown from 2023’s 9.4% rise in trial starts. Sustained geopolitical and global regulatory pressures on pharma contributed to curbing momentum.

• Why Real-Time eCOA Data Matters More Than Ever

  10/16/2025

  Real-time eCOA data enables faster eligibility decisions, proactive issue alerts, and streamlined operations by unifying data, improving precision, responsiveness, and trial execution efficiency.

• Navigating The Waters Of Compliance In Clinical Research

  5/5/2026

  Strengthen your research processes by adopting secure systems, staying current with regulatory standards, and ensuring your team is consistently trained to manage data responsibly and efficiently.

• The Scoop On The SCOPE Summit

  2/19/2025

  From industry partnerships to patient recruitment to proprietary data, SCOPE 2025 was packed with informational sessions.

• How AI Can Accelerate Clinical Trial And Registry Builds

  6/29/2026

  AI tools speed study design — from protocol creation to validation and analysis — by automating complex tasks and generating intelligent data while preserving control, accuracy, and flexibility.