Commentary|Articles|August 21, 2026

When the Slack Runs Out: AI and the CRO Operating Model

Agentic AI will put the CRO operating model to the test—and force the efficiency and accountability questions the industry can no longer avoid.

The clinical research industry is entering another technology cycle, this time driven by agentic artificial intelligence (AI). Vendors, consultants and analysts are rushing to map out what these systems will automate, speed up, or eliminate. The discussion is dominated by capabilities: autonomous workflows, digital teammates, predictive analytics.

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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.

October 16th, 2026

Building Trust Into Oncology Real-World Evidence: Q&A with Saamir Pasha and Carole Berini, Ontada

In this Q&A, Saamir Pasha and Carole Berini, PhD, of Ontada discuss what it takes to harmonize fragmented oncology data into reliable real-world evidence, how lab markers can proxy for missing functional status data, and where the biggest remaining barriers to consistent RWE generation lie.

October 9th, 2026

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

Trialbee CEO Matt Walz explores the current impact of AI in delivering practical gains in clinical development and reflects on its future potential, where enrollment predictability may be the biggest prize of all.

October 8th, 2026

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.

October 20th, 2026

Where AI Governance in Clinical Development Falls Short

In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, identifies three recurring failure modes in AI governance frameworks—and explains why responsible AI must be an ongoing operating discipline, not a one-time approval gate.

October 19th, 2026

How Compressing Time From Data Capture to Insight Changes Trial Risk Management

In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, explains why the real advantage of faster data isn’t speed—it’s shortening the distance between signals, human judgment, and the next best action.

October 16th, 2026

What It Actually Means to Embed AI Across the Clinical Operating Model

In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, explains why the shift from narrow AI tools to a continuous learning clinical operating system is where the real operational value lies—and what it takes to get there.

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October 15th, 2026

Endpoints That Reflect What Patients Actually Value: Who Decides What Counts as Trial Success

Clinical trial endpoints define what success looks like, but patients and caregivers are rarely the ones setting that definition, and the gap between what trials measure and what patients actually value is showing up in post-approval evidence, regulatory submissions, and the design rooms where protocols are written.