Roche Launches Automated Cobas HDV Test For Hepatitis D Detection And Monitoring, Expands Molecular Diagnostics Portfolio

Roche has launched the cobas® HDV test for use on its cobas® 5800, 6800 and 8800 systems in countries recognizing the CE mark. The new diagnostic assay is designed to detect and quantify Hepatitis D Virus (HDV) RNA, enabling healthcare providers to better identify infected patients and monitor treatment response as new therapies for the disease become increasingly available.

Hepatitis D is estimated to affect around 12 million people worldwide and is unique because it can only infect individuals who already carry the Hepatitis B virus (HBV). The virus may occur either as a co-infection, where HBV and HDV are acquired together, or as a super-infection, where HDV develops in patients already living with chronic hepatitis B. Super-infection is particularly serious, with more than 90% of cases progressing to chronic disease and increasing the risk of severe liver damage.

Until now, HDV testing has largely relied on manual procedures or laboratory-developed tests, which can vary in performance and consistency. Roche's new assay is the first fully automated, high-throughput HDV test available on the market, addressing the growing need for standardized and scalable diagnostic solutions as HDV-specific treatments enter clinical practice.

"This is an important advancement of our commitment to improving outcomes for people living with liver disease," said Matt Sause, CEO of Roche Diagnostics. "With the cobas HDV test, we are providing clinicians with a reliable tool to aid in the identification of infected individuals and to monitor their response to treatment."

The assay runs on Roche's widely adopted cobas molecular diagnostic platforms, allowing laboratories to integrate HDV testing into existing workflows without additional infrastructure investments. By automating the testing process, the company aims to improve laboratory efficiency, accelerate result delivery, and support clinicians in making faster treatment decisions for patients.