Applying Behavioral Science to Improve Clinical Trial Design and Execution

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, Kent Thoelke, CEO of Paradigm Health, explains why patient cost barriers and site infrastructure challenges must be solved together to close the participation gap in community and rural clinical trials.

Patients don’t experience primary endpoints, so trials that stop at biomarkers and rigid rating scales risk declaring success while leaving daily burden untouched, and digital tools only deliver meaningful evidence when they are co-designed with patients and deployed with restraint.

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.

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.

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.

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.