Expert Insights On Data Management & Analysis

1. Clinical Trial Standards — What They Are And Why They're Indispensable 9/8/2026

   Clinical trial standards are essential. But to interpret changes, preserve meaning, and assess downstream impact, context is key.

2. The Promise Of MRD-Guided CAR-T Treatment 9/3/2026

   Minimal residual disease markers can reveal relapse before clinical signs appear, when off-the-shelf cell therapy may have its greatest advantage.

3. Lessons In Forecasting Discipline From A $40B Supply Chain 8/31/2026

   Forecasting errors rarely start with the algorithm. They start when protocol changes, enrollment and site data reach the supply plan too late to prevent waste and disruption.

4. Building The Execution Architecture For Real-World Data To Have Real-World Impact 8/20/2026

   RWE's next challenge is execution. Learn how life sciences orgns can turn evidence into sustained business and clinical impact.

5. Rare Disease Study Gets A Boost From Crowdsourced Patient Reported Data 8/18/2026

   Jen A. Levitt, MD, explains how crowdsourced patient-reported data and AI tools can compress rare disease research timelines and surface new signals.

6. 3 Ways To Solve Data Friction In Modern Clinical Data Management 8/4/2026

   Senior clinical data manager Shasidar Reddy Abbidi shares how to reduce data friction with targeted automation, early standards adoption, and clearer workflows that move data to decisions faster.

7. What Pistoia Alliance's AI Poll Reveals About Industry Readiness And Regulatory Confidence 7/17/2026

   Pistoia Alliance President Becky Upton, Ph.D., reviews findings from a poll about AI use in clinical research conducted at Clinical Trials Technology Congress (CTTC) that revealed barriers to adoption, early ROI, emerging use cases, and the role of patient-generated data.

8. Before AI Can Transform Clinical Trials, It Needs More Patient Data 7/7/2026

   King’s College London Professor Maddy Parsons says AI won't improve clinical trials — unless researchers begin collecting richer biological data, embracing diversity, and treating every clinical trial as learning opportunity.

9. i-Cubed Used End-To-End AI In A Proof-Of-Concept Trial. Here's What They Learned 7/2/2026

   Discover how well AI fared in document generation, patient engagement, data integration, and more in an end-to-end proof-of-concept study run by i-Cubed.

10. Understanding And Preserving Data Flow Integrity In AI-Assisted Clinical Trials 6/26/2026

    Learn from ex-FDA and ELIQUENT consultant Dawn Wydner, Ph.D.., how treating data integrity as an end-to-end clinical information flow issue, rather than a database-only concern, is essential to managing AI-related risk.