INSIGHTS ON CLINICAL TRIAL TECHNOLOGIES

• Rescue Studies: Get Patient Recruitment Back On Track

  What is a rescue study, and how can direct-to-patient digital recruitment be employed to rapidly boost recruitment and enrollment?

• Applied AI For Enhanced Data Operations

  Explore practical AI applications to enhance clinical trial operations through improved data interoperability, automation, and data surveillance.

• Why Data Integrity Still Matters — Even As Clinical Trials Evolve

  Data integrity remains essential for compliance and patient safety. Learn strategies to maintain accuracy and reliability as clinical research evolves toward more connected, technology-driven models.

• The Tale Of Two Clinical Supply Chains: The Risks Of Fragmented Systems

  Here we examine two contrasting approaches to showcase how a centralized inventory management system is an effective tool for supporting a robust supply chain.

• Dive Into Core Topic Areas Of The HEOR field

  10/1/2025

  Join us to see how HEOR drives impact across the global healthcare landscape.

• The Evolution Of Communication In Healthcare And Clinical Trials For A Diverse Patient Population

  10/31/2024

  Educational animation in clinical trials enhances patient understanding, health literacy, and retention, addressing diverse literacy needs by simplifying complex information into engaging visual content.

• Demystifying AI: The Fundamentals And Applications In Drug Development

  9/17/2024

  Explore the history of AI, gain clarity on key concepts, address common questions, and discover its transformative role in drug development, with insights into its current and future impact on the industry.

• FDA Pushes For Patient Voice: ePRO In Oncology Trials

  1/8/2026

  FDA urges sponsors and CROs to include patient voices in oncology trials. Discover why it matters and how to start integrating this approach.

• Digital Advancements In Clinical Development - What's Next?

  1/17/2024

  Review this year's predictions for improving digital biomarkers and data analytics, bettering endpoint sensitivity and specificity, and reducing timelines and costs of clinical development.