50% Imaging Error Rate in Clinical Trials Discussed by Expert Panelists from 5 NCI-Designated Cancer Centers

Data points to a broader industry-wide imaging accuracy crisis

CHICAGO, IL / ACCESSWIRE / July 23, 2024 / Yunu, a provider of medical research technology and services to life sciences companies and clinical research environments, hosted a recent panel at the Association for American Cancer Institutes’ (AACI) Cancer Research Innovation (CRI) symposium that shed light on the alarming error and non-compliance rates for imaging assessments in clinical trials.

Panelists discussed a recently released abstract that documented half of all imaging assessments had non-conformities in the site’s active trials. Details and findings were discussed by the panel and corroborated by two other panelists whose sites had also implemented Yunu’s (www.yunu.io) trial imaging platform and tracked their findings.

The three abstracts, each conducted with similar methodologies, found 25%, 30%, and 50% error rates within their oncology clinical trials imaging endpoints, which were successfully reduced to less than two percent. ¹ The discussion among panelists and audience members strongly supported imaging as a widespread issue creating downstream impacts such as delayed trial activation, incorrect patient enrollments, increased costs, audit findings, and data loss. ² A recent study noted that the financial impact of imaging on ineligible patients superseded the entire imaging costs of the trial. ³

The Yunu platform is a crucial tool in the quest for improved imaging accuracy and efficiency in clinical trials. It is now used to ensure day-forward trial imaging compliance, delivering up to 80% workflow efficiencies for study staff, 50% reading team acceleration, seamless cross-site resource sharing, audit-ready imaging data management, trial- and patient-level reporting, reader training and scheduling, and configurable dashboards overseeing all trials and sites in the operation.

Jeff Sorenson, Yunu co-founder and CEO, said, “Increasingly, Yunu is being adopted by research site networks, national cancer centers, and community oncology practice groups, with many sites spanning wide geographic areas. The current model of in-house radiology research cores attempting to use non-fit-for-purpose tools and manual error-prone processes has reached its breaking point. These data presented by the panelists demonstrate that imaging assessments cannot be done well in leading cancer centers this way, so it surely cannot be expected to work for community oncology, where 80% of Americans get their care.”

With over 4,200 active clinical trials on the platform with data from 800 sponsors, including 400-plus pharma sponsors, the company is transforming imaging accuracy and efficiency at scale, maximizing visibility to early therapeutic signals and extending trials to broader and more diverse populations.

1. Cruz A, Lankhorst B, McDaniels H, Weihe E, Correa E, Nacamuli D, Somarouthu B, Harris GJ. The complete workflow solution for quantitative imaging assessment of tumor response for oncology clinical trials. Presented at AACI-CRI Conference, Chicago, IL, 2024.

2. https://www.yunu.io/the-clinical-trial-imaging-accuracy-crisis-aaci-cri-panel-discussion

3. Borys L, Marini M, Lu E, Ford R. The influence of blinded independent central review on subject eligibility in oncology studies. American Society of Clinical Oncology. 2022; e13603. https://ascopubs.org/doi/pdfdirect/10.1200/JCO.2022.40.16_suppl.e13603

About Yunu
Yunu provides medical research technology and services to life sciences companies and clinical research environments that perform precision imaging assessments. Yunu’s aim is to ensure breakthrough therapies are accessible to everyone by unifying medical imaging insights and connecting clinical communities. With thousands of clinical trials relying on the platform daily, Yunu is delivering a new standard for clinical trial imaging workflow. Learn more at https://www.yunu.io.

Contact Information
Lindsay Fleming
Chief Marketing Officer
press@yunu.io

SOURCE: Yunu

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