Editorial Perspectives On Data Management & Analysis

1. How The FDA, MHRA, & EMA Differ On Externally Controlled Trials 10/23/2025

   As the FDA, MHRA, and EMA release draft frameworks on externally controlled trials, sponsors face differing expectations. The U.K. leans pragmatic, the U.S. remains cautious, and Europe’s guidance is still evolving — leaving global trial planners to navigate regulatory gray zones.

2. RWE Is Growing Up, And Here's Why That Matters 9/29/2025

   Real-world evidence is shifting from the margins to the mainstream of drug development, but data quality, trust, and regulatory clarity remain hurdles. ISPOR is helping set the standards to guide its future.

3. Seriously … Are We Making Any Progress? 9/25/2025

   Ken Getz’s DPHARM talk revealed how ballooning data collection in trial protocols drives costs, delays, and site burden. New ICH E6 R3 guidance pushes for simpler, more flexible designs, but real progress will require collaboration — and restraint.

4. Clinical Trials Get A Council For AI Oversight 7/14/2025

   AI in clinical trials is moving fast — but without clear standards for ethics, transparency, or oversight. Advarra's new Council for Responsible Use of AI in Clinical Trials aims to change that. Founding members Sanofi, Recursion, and Velocity Clinical Research are stepping up to define what “responsible” really looks like.

5. What ClinOps Wants To Know About AI 2/13/2025

   Registrants for our recent Clinical Leader Live, “AI In Action: Transforming Clinical Trials,” were asked what they wanted to learn after watching the webinar. We thought it would be interesting to look at the five general themes to the types of questions they were asking.

6. Can Better Data Management Save Clinical Trials? 11/25/2024

   In this summary of our 10/31/24 Clinical Leader Live, we talk about the current ICH M11 guideline, which focuses on a clinical electronic harmonized protocol, as well as the need for data standardization and the benefits of the resulting automation. Our panelists include Jessica Jolly, a data science expert with 25 years of experience, and Hassan Kahlid, senior engineer, machine learning and data science at AstraZeneca.

7. AI Can't Help Bad ClinOps/Health Equity Data 9/25/2024

   Brian Johnson, Ph.D., VP, R&D Technology at Takeda discusses the huge opportunity of connecting disparate ClinOps data and leveraging generative AI to reduce costs and labor during the clinical process. 

8. Why We Need Technology Consolidation In Clinical Trials 8/16/2024

   As more and more trial designs incorporate technologies that generate an immense amount of data, data managers struggle to continuously interconnect disparate systems and standardize data. All of this fuels the need for technology consolidation.

9. Dear Data Analysts, AI Is Not Replacing You 4/2/2024

   Deep beneath the ongoing narrative of AI’s potential use cases in clinical trials is the same fear that persists in other industries facing a technology revolution. Will jobs be lost and replaced by machines? So, I thought I’d ask an expert — a machine.

10. It's Hard To Predict AI's Real Value To Clinical Trials 2/1/2024

    Sunny Kumar, a partner at GSR Ventures, plans to talk about AI and ML use in clinical trials during the SCOPE Summit panel, “The Future of Clinical Trial Tech: Perspectives from Different Investors.”