In this video interview, Amélie Lothe, global medical community head for rare epilepsies at UCB Pharma, explains why the full burden of developmental and epileptic encephalopathies extends far beyond clinical symptoms—and why endpoints must reflect what families are actually hoping for.

In this video interview, Sylviane de Viron of CluePoints and Abigail Dirks of Tufts CSDD discuss what the RBQM financial model left out—reduced rework, improved data integrity, and inspection readiness—and why those excluded factors could represent even greater value than what was modeled.

Why clinical development’s next AI bottleneck is not the model, but the system around it.

Regulatory expectations for patient input in drug development have shifted from aspiration to documented methodology across three major jurisdictions.

This episode of The Human Side of Clinical Trials, hosted by Brian S. McGowan, PhD, FACEHP, chief learning officer and co-founder of ArcheMedX, Inc., and Kelly Ritch, chief operating officer of ArcheMedX, Inc., explores why training completion metrics like attendance and quiz scores fail to capture true study readiness, and how measuring both competence and confidence can reveal trial risks before enrollment even begins.

In this video interview, Amélie Lothe, global medical community head for rare epilepsies at UCB Pharma, outlines what it takes to move beyond transactional engagement and treat patient advocacy organizations as long-term partners in the science and the care.

In this video interview, Amélie Lothe, global medical community head for rare epilepsies at UCB Pharma, shares what she has learned firsthand from families living with Dravet syndrome and CDKL5 deficiency disorder about what makes trial participation possible—and what makes it not.

Clinical trials have spent decades perfecting data capture, but the execution layer underneath it, including decision workflows, data collection design, and lab connectivity, remains fragmented in ways that limit what AI can realistically deliver and that quietly compromise the scientific validity of the data itself.