Metrics & Benchmarks

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How AI is Eliminating 'Dead Time' in Clinical Trials
0:47
How AI is Eliminating 'Dead Time' in Clinical Trials
5 hours ago
by
Raviv Pryluk, PhD(+1 more)
Why Execution is Never Just 'Plug and Play'
0:42
Why Execution is Never Just 'Plug and Play'
7 days ago
by
Elizabeth Walsh, PMP, ACRP-CP(+1 more)
No Wiggle Room: The New Reality of Patient Recruitment
0:36
No Wiggle Room: The New Reality of Patient Recruitment
14 days ago
by
Gaynor Anders(+1 more)
DIA 2026: The Reality of DCT, Technology Challenges at the Site Level
0:34
DIA 2026: The Reality of DCT, Technology Challenges at the Site Level
21 days ago
by
Joan Chambers
DIA 2026: Why Clinical Trials Were Stuck in the Past
0:49
DIA 2026: Why Clinical Trials Were Stuck in the Past
a month ago
by
Angie Maurer(+1 more)
DIA 2026: FDA's New Stance, Quality by Design in Clinical Trials
0:28
DIA 2026: FDA's New Stance, Quality by Design in Clinical Trials
a month ago
by
Kevin Bugin(+1 more)
2026 DIA Global Annual Meeting: Day 2 Recap
1:30
2026 DIA Global Annual Meeting: Day 2 Recap
a month ago
by
Andy Studna, Senior Editor
2026 DIA Global Annual Meeting: Day 1 Recap
1:33
2026 DIA Global Annual Meeting: Day 1 Recap
a month ago
by
Andy Studna, Senior Editor
Bringing Together Modern Infrastructure to Meet New FDA Standards
0:51
Bringing Together Modern Infrastructure to Meet New FDA Standards
2 months ago
by
Raj Indupuri(+1 more)
ACT Ops Take: Understanding the FDA's CNPV Program and Review Timelines
1:15
ACT Ops Take: Understanding the FDA's CNPV Program and Review Timelines
2 months ago
by
Andy Studna, Senior Editor

Applied Clinical Trials June 2026

Check out the latest features and columns!

Applied Clinical Trials June 2026

Revenue Recognition Risk in Contract Research Organizations

Managing financial integrity in a complex, milestone-driven operating model.

Revenue Recognition Risk in Contract Research Organizations

When Does Paper Make Sense for Clinical Outcome Assessment Data Collection?

Despite clear data quality and regulatory advantages, paper-based clinical outcome assessments persist due to cost asymmetry, trial complexity, startup timelines, and provider capability gaps.

When Does Paper Make Sense for Clinical Outcome Assessment Data Collection?

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AI agents operate only within workflows, but most organizations lack unified workflow management systems, making it difficult to identify where agents should be deployed or ensure they integrate effectively across connected business processes in clinical research.

AI churn—repeatedly restarting initiatives before scaling them—stems from organizational execution gaps rather than technology limitations, but agentic AI amplifies these gaps by requiring connected systems, trustworthy data, and disciplined governance from the start.