Feature|Articles|September 22, 2026

Is Decentralization Actually Reducing Site Burden, or Just Moving It?

Decentralized trial models have demonstrated real gains in enrollment performance and patient access, but operational switching costs, fragmented technology stacks, and unresolved gaps in the patient-site relationship raise a question the industry has been slow to confront directly.

Decentralization has reshaped the conversation around clinical trial access and efficiency, but the question of what it actually does to site burden has received far less scrutiny than what it does for patients. Three distinct voices, arriving at the same unresolved question across the course of a year, suggest the industry may be optimizing for the wrong metric.

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Real-Time Clinical Trials Depend on a Scalable EHR-to-EDC Connection

Real-time clinical trials require standardized digital data capture at the point of care through scaled eSource-EDC-EHR integration, but progress stalls because competing standards lack regulatory enforcement and one-off system integrations cannot scale beyond single studies without industry-wide alignment and legal clarity on data ownership.

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AI and Patient Recruitment: Can Predictive Promise Drive True Transformation?

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What It Takes to Harmonize AI Across Fragmented Oncology Health Systems

In this video interview, Saamir Pasha and Carole Berini, PhD, of Ontada, explain how building trust into the data foundation—through source lineage, standardization, and reconciliation—is what makes reliable real-world evidence generation in oncology possible.

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October 6th, 2026

Beyond the Molecule: Why Radiopharmaceutical Trials Require a New Operating Model

Radiopharmaceutical therapy is exposing a broader challenge for clinical development: scientific innovation can advance only as fast as the infrastructure, data, and cross-functional decisions required to deliver it.

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What an AI-Informed Approach Means for How Sponsors Think About Risk

In this video interview, Claire Riches, VP of clinical solutions at Citeline, explains how AI is shifting trial risk management from reactive to proactive—enabling sponsors to pressure-test protocols and anticipate pivots before a single patient is enrolled.

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September 29th, 2026

Real-World Evidence Is Moving Upstream: Is the Data Infrastructure Ready?

RWE is finding a role earlier in drug development than ever before, but the data quality, integration, and organizational alignment required to make it regulatory-grade are still catching up to the ambition.

October 13th, 2026

The Biggest Remaining Barriers to High-Quality RWE Across Oncology Data Platforms

In this video interview, Saamir Pasha and Carole Berini, PhD, of Ontada, identify three persistent obstacles to consistent real-world evidence generation in oncology—inconsistent data capture, structural data limitations that modeling alone can't fix, and the need for earned generalizability through deliberate multi-site validation.

October 7th, 2026

Using AI to Design Better Trials Before the First Patient Enrolls: Q&A with Claire Riches, Citeline

In this Q&A, Claire Riches, VP of clinical solutions at Citeline, discusses how AI is transforming endpoint selection and protocol pressure-testing, what data inputs matter most for realistic enrollment planning, and why the tools are more accessible than most sponsors assume.