In Episode 4 of The Human Side of Clinical Trials, host Brian S. McGowan, PhD, FACEHP, chief learning officer and co-founder of ArcheMedX, Inc., speaks with Jason Riis, PhD, CEO and chief behavioral scientist at Behavioralize, about how capturing friction closer to the moment it happens can reveal unclear instructions, technology friction, and workarounds that retrospective surveys and debriefs tend to miss.

In this Q&A, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, discusses what changes when AI is embedded across protocol strategy, data infrastructure, and workflow tools at once, where governance frameworks tend to fall short, and why CROs must orchestrate AI ecosystems rather than simply aggregate them.

Medical writing capacity pressure is fundamentally a talent development problem, not a technology problem, since hybrid resourcing and AI cannot substitute for the experienced judgment needed to review AI output and mentor the next generation of writers.

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 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.

Mistral and OpenAI produced identical overall eligibility labels across 200 synthetic patient-study assessments, with criterion-level disagreements concentrated in inclusion criteria where models switch between “Uncertain” and “Not included” when records lack sufficient evidence, so model choice should be driven by deployment architecture, control, and cost rather than assumed interchangeability.

In this Q&A, E.K. Koh, chief product officer at Suvoda, discusses what separates a trustworthy AI assistant from one that adds risk, why curated clinical knowledge matters more than general-purpose flexibility, and what safeguards must be in place when assistants move from answering questions to taking actions in clinical trial systems.

The FDA’s RTCT initiative transmits predefined, clinically meaningful signals to regulators during active trials, so its value depends entirely on the maturity of sponsors’ upstream RBQM signal intelligence, KRIs, QTLs, and root-cause context, rather than on data speed.