Using Clinical Trial Sites' Input to Select the Right Capabilities when Decentralizing Clinical Trials

A new white paper and public engagement process outline the FDA’s commitment to building fit-for-purpose evidentiary standards, stronger patient voice integration, and greater regulatory predictability across rare disease drug development and review.

Real-time clinical trials require standardized digital data capture at the point of care through scaled eSource-EDC-EHR integration, but progress stalls because competing standards lack regulatory enforcement and one-off system integrations cannot scale beyond single studies without industry-wide alignment and legal clarity on data ownership.

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.

The partnership gives RealTime's network of more than 3,000 research sites access to the Archer platform for direct, automated data transfer from eSource to any sponsor electronic data capture system or data destination.

In this video interview, Saamir Pasha and Carole Berini, PhD, of Ontada, identify three persistent obstacles to consistent real-world evidence generation in oncology—inconsistent data capture, structural data limitations that modeling alone can't fix, and the need for earned generalizability through deliberate multi-site validation.

How a phased CRO partnership built on ICH E6(R2) and E6(R3) principles supported a multi-indication biotech portfolio.

The second of a two-part perspective examining why clinical trial enrollment and representation outcomes are shaped long before the first patient is screened.

In this video interview, Saamir Pasha and Carole Berini, PhD, of Ontada, describe what operationalizing regulatory-grade quality frameworks requires—and why fit-for-purpose evidence generation is a transparency and documentation discipline, not just a data cleanliness exercise.