Clinical Trial Technology Editorial

  1. Unlocking Biopharma Innovation With Real-World Evidence 3/30/2026

    Discover how how federated data networks, platform aggregators, and collaborative partnerships have evolved to meet the data demands of modern product development, regulatory strategy, and commercial success.

  2. Bayesian Digital Twins Show Potential For Predicting Prognosis And Treatment Response 3/30/2026

    Learn how Bayesian digital twins are trained, validated, and trusted in clinical settings and explore the potential for integrating these models into interventional trials.

  3. Elsa's AI Model Migration: Technical, Compliance, And Regulatory Risks For Sponsors (Part 2) 3/26/2026

    In the second part of their series on Elsa AI model migration, Kimberly Chew, Esq., and Michael Yang, Esq., analyze the risks to compliance and data residency, as well as the integrity of the regulatory record.

  4. A Clinical Machine Learning Operations (MLOps) Maturity Framework For Biopharma 3/24/2026

    Pharma has invested substantially in machine learning applications, but investment in the operational infrastructure — the MLOps layer — has lagged. The time to build that infrastructure is now — not after your next trial fails.

  5. How Deep Learning Is Changing Clinical Trial Design, Execution, And Analysis In 2026 3/10/2026

    Deep learning is reshaping clinical trial design, execution, and analysis. Learn how to deploy it safely, measurably, and at scale with help from life sciences consultant and MIT industry advisor Partha Anbil.

  6. The Uncomfortable Conversation: AI And Data Use In Clinical Trials 3/2/2026

    AI is quietly transforming clinical trials at the site level, boosting efficiency while creating hidden risks for patient data, protocols, and sponsor intellectual property.

  7. When A Clinical Trial Surfaces In An AI Chat, What Happens Next? 3/2/2026

    AI is soon becoming the first interpreter of your clinical trial. Understand its implications for enrollment design, screening efficiency, and ultimately program predictability.

  8. Pick The Right PV Technology With Help From A Safety Data Management Expert 2/27/2026

    Otsuka's Head of U.S. GPV Safety Data Management Vikalp Khare shares how smart governance should inform pharmacovigilance (PV) technology choices.

  9. Enabling Cloud Computing In DCTs For Remote Data Capture, Monitoring, And More (Part 1) 2/25/2026

    Understand why cloud infrastructure is foundational to hybrid and decentralized trials and what critical trial activities it enables with reduced operational friction.

  10. Safe And Sustainable DCTs and Hybrid Trials (Part 2) 2/25/2026

    In part two of this series, learn practical cloud architectural patterns, governance structures, and operating mechanisms that allow sponsors to run hybrid and decentralized trials.