9th ACT European Summit

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 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 today’s ACT Brief, we examine why community research needs lasting financing and infrastructure, how electronic outcome tools can strengthen neuroscience endpoints, and how Teva is licensing two biosimilars from Samsung Bioepis.

Neuroscience trials struggle to show benefit because symptoms are subjective and variable, and eCOA strengthens dossiers by standardizing ClinRO administration, capturing outcomes in real time to reduce recall bias, and adding patient and caregiver perspectives that clinician scales miss.

Community participation gaps look less like a question of patient willingness and more like a financing and infrastructure problem that no single bill has yet solved.

In today’s ACT Brief, we examine what changes when AI is embedded across clinical operations, why faster trial data isn’t yet producing faster decisions, and how FDA granted accelerated approval to a therapy for a rare airway disease.

Data capture is no longer the bottleneck, and whether the lag between a signal and a decision shrinks depends on signal design, AI governance, and vendor orchestration.

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.