A newly published review highlights the evolution of Hepatitis C Virus (HCV) diagnostics, detailing key technological breakthroughs that have improved detection and management. The review traces the field’s progress from traditional liver biopsies to cutting-edge artificial intelligence (AI) and machine learning (ML) applications.
HCV, a major cause of chronic liver disease, presents significant public health challenges. The review examines the transition from early antibody-based tests to more precise enzyme immunoassays (EIAs) and nucleic acid tests (NATs), which have enhanced accuracy in identifying the virus. The addition of genotyping further refined treatment strategies by distinguishing between different HCV strains.
More recent innovations, such as next-generation sequencing (NGS) and point-of-care testing (POCT), have offered faster and more cost-effective diagnostic options. While these developments improve early detection and patient outcomes, the study notes that AI and ML remain limited to well-resourced settings. In contrast, rapid diagnostic tests (RDTs) are proving valuable in low- and middle-income countries, where affordability and accessibility are crucial.
The review also identifies future challenges, including the high cost of diagnostics in resource-limited areas. It suggests that microfluidic platforms, which enable miniaturized and portable testing, could play a key role in making HCV detection more widely available. Continued research and investment in novel diagnostic tools will be essential to achieving global HCV elimination.
This new article underscores the remarkable progress in HCV diagnostics while highlighting the need for ongoing innovation to bridge healthcare disparities.
Reference: Sharma K et al. A review of historical landmarks and pioneering technologies for the diagnosis of Hepatitis C Virus (HCV). Eur J Clin Microbiol Infect Dis. 2025. doi: 10.1007/s10096-025-05110-y.
Anaya Malik | AMJ
