Blog tagged as PACS

Clinical trial imaging de-identification and export remain manual, time-consuming, and error-prone for site teams. This article explores why the workflow is overdue for change and how Yunu De-ID & Export helps sites prepare sponsor-ready trial data with greater control and consistency.

Radiology departments have tried for years to “own” or “fix” clinical trials imaging assessment workflows by extending clinical tools (PACS, worklists, dictation systems) and habits (speed, seamlessness, few clicks) into the research world.

At DPHARM 2025, Patrick McNamara, Chief Commercial Officer at Yunu, shared how Yunu is redefining imaging in clinical research by solving site-level challenges first.

At DPHARM, Paul McCracken, Founder and Principal of RadiaNova Consulting, sheds light on the hidden challenges of clinical trial imaging and how radiopharmaceutical studies are transforming its role.

Moe Alsumidaie interviewed Jeff Sorenson, CEO of Yunu, and Steve Tolle, Chief Product & Technology Officer at Ignitedata, on how the updated ICH E6(R3) guidance is transforming imaging in clinical trials.

Site-level imaging errors affect up to 50% of oncology trial reads, delaying trials and potentially censoring patients. When quality is enforced at the point of capture, error rates drop by more than 80%, saving millions of dollars and months in trial timelines.

Moe Alsumidaie’s latest article explores how the updated ICH E6(R3) guidance raises the bar for imaging in clinical trials. With imaging as the primary endpoint in most oncology studies, sites and sponsors must now meet the same Good Clinical Practice (GCP) standards as other critical data types.

Imaging is essential to trials but remains one of the most broken workflows. Yunu CEO Jeff Sorenson shares how real-time, connected platforms improve accuracy, speed, and patient outcomes by replacing outdated imaging processes.

This interview with Yunu CEO Jeffrey Sorenson explores how elevating imaging data in clinical trials can improve data integrity, trial efficiency, and patient outcomes, highlighting tech innovations and structural shifts needed for modern oncology research.