Technology Trends Shaping Clinical Trial Execution in 2026

Standardized measurement across five oncology centers found that clinical research coordinators rated eSource-enabled workflows positively (Overall Mean Satisfaction 5.79 of 7), with reduced manual entry and electronic data transfer earning strong marks, while perceived reduction in sponsor and monitor queries lagged as the one domain below threshold.

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.

In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, describes the industry’s trajectory toward a unified intelligence orchestration environment—and explains why the future isn’t one model that knows everything, but a trusted system that brings the right evidence to the right human decision.

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.

Pacing obesity trial enrollment, anchoring eligibility to stable real-world therapies, and building site and physician relationships improve retention and data quality more than aggressive recruitment or restrictive exclusion criteria do.

In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, argues that CROs must act as orchestrators rather than aggregators—and that the real test of any AI ecosystem is whether it reduces sponsor coordination burden or just hands it back to them.

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.

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.