Unprecedented Early-Stage Cancer Detection Presented at AACR 2026

Dxcover Highlights Liquid Biopsy Platform Performance in Multiple Settings

GLASGOW, Scotland--(BUSINESS WIRE)--Dxcover, a global leader in AI-enabled technologies, today announced the presentation of multiple studies at the American Association for Cancer Research (AACR) Annual Meeting taking place in San Diego, California this month.

The company will present data as part of key sessions focused on Early Detection Approaches – specifically Stage I and II cancers, which can be treated when detected, but are elusive to other screening protocols. Matthew Baker, PhD, CEO & co-Founder of Dxcover, commented: “Cancer is detected too late because early signals are invisible to current clinical tools. The Dxcover approach analyzes the body’s earliest reactions to malignancy – a perfect complement to existing high specificity diagnostics.”

Data presented at the conference represent results from studies designed to investigate the Dxcover platform’s clinical feasibility and performance capabilities:

• 90+% sensitivity reported consistently across stage I-IV colorectal (CRC), pancreatic, and ovarian cancers
• Integration, comparative performance and considerations of CRC biomarkers and screening modalities

“It’s exciting to share our latest findings at the AACR conference," says James Cameron, PhD, Dxcover Clinical Program Manager and co-author on each presentation. “These data demonstrate our commitment to improving patient outcomes with continued progress toward earlier cancer detection.”

Dxcover AACR presentations: #5115, #5116, #7616, #7617

About Dxcover

Dxcover is changing how early, how accurately, and how efficiently cancer can be detected. The company’s platform integrates infrared spectroscopy data with proprietary algorithms to support earlier and more actionable clinical insights from a small amount of blood, yielding results in hours instead of weeks. AI-powered insight, delivered at light speed.

Further Information: https://www.dxcover.com/