Saama Launches Deep Learning Intelligent Assistant

Trially CEO Kyle McAllister explains why transparent AI reasoning is essential for trial patient matching.

Trially Co-founder and CEO Kyle McAllister, explains how AI absorbing the bulk of clinical-trial chart reviews can free research sites to focus staff time on higher-value tasks.

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.

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.

In today’s ACT Brief, we examine who decides what trials measure, how designing for human thinking improves site execution, and how the FDA extended an immunotherapy to a new bladder cancer population.

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 Episode 3 of The Human Side of Clinical Trials, hosts Brian S. McGowan, PhD, FACEHP, chief learning officer and co-founder of ArcheMedX, Inc., and Kelly Ritch, chief operating officer of ArcheMedX, Inc., speak with Jason Riis, PhD, CEO and chief behavioral scientist at Behavioralize, about why a well-written protocol doesn’t always translate into consistent execution, and how designing for the way people actually think and learn can reduce site burden and the need for costly unlearning.

In today’s ACT Brief, we examine what it will take to scale EHR-to-EDC connections for real-time trials, how the FDA is reimagining rare disease drug development, and why oncology real-world evidence still faces persistent data barriers.