EMR to CTMS That Works for Trialists

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.

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.

In today's ACT Brief, we examine how representation gaps in trials are shaped by structural design decisions, how new partnerships automate data transfer from site systems to sponsor platforms, and how Roche is licensing a novel obesity target from a biotech pioneer.

Trialbee CEO Matt Walz explores the current impact of AI in delivering practical gains in clinical development and reflects on its future potential, where enrollment predictability may be the biggest prize of all.

In today's ACT Brief, we examine proportionate analysis frequency in RBQM, how to build trust into real-world evidence foundations for cancer trials, and how rare disease developers monetize regulatory success.

In today's ACT Brief, we examine how AI surfaces design flaws before enrollment, why site training readiness depends on learning science, and the priorities defining next-generation weight-loss therapies.

In today's ACT Brief, we examine the FDA's multi-domain transparency priorities, why radiopharmaceutical trials need redesigned infrastructure, and how AI can make enrollment more predictable.