PoC-HCV Concept & Objectives

This Consortium federates the expertise of three SMEs (Epistem, Qlucore, Biosurfit) and one academic partner (Inserm), having a shared commitment to establish a stable, long-term mechanism to support “genetic-protein” biomarker development for the implementation of predictive and prognostic tests.

Point-of-Care (PoC) medical devices have the potential to revolutionise clinical practice. SMEs within our Consortium (Epistem & Biosurfit) have developed genetic and protein PoC devices to deliver on this promise. Results from these enabling technologies will be integrated using novel bioinformatics tools and algorithms (Qlucore) allowing for bedside analysis. This integrated genetic-protein approach will exploit recent biomarker discoveries from the FP7 project SPHINX, to improve the management of hepatitis C virus (HCV) infected patients. We will focus on two public health problems: (i) addressing the need to predict, pre-treatment, individuals in resource poor countries who will benefit from conventional treatment; and (ii) helping to limit treatment costs globally, where new therapies for HCV are anticipated to significantly increase health care expenditures.

Technology integration

• Quantification and genotyping of plasma HCV
• Host genetic polymorphisms
• Host protein and cellular responses

To date, the technologies required for the implementation of genetic and protein biomarkers have been developed as stand-alone assays. These technologies require integration in order to address key medically relevant questions with simple-to-use algorithms, and ensure rapid uptake by the medical community.

The technologies include :

1. a hand-held CE-IVD marked PCR platform, called Genedrive® that enables single nucleotide polymorphism (SNP) testing (Epistem); and
2. a microfluidics system, called Spinit®, which enables fluid management in a spinning compact disc format, applied for protein immunoassays (Biosurfit). In each case, biomarker datasets and clinical data will be integrated using novel bioinformatics tools and algorithms, implemented on a mobile device application (Qlucore).