Qlucore has been awarded funding of €0.6 million over a three year period by the European

Commission’s 7th Framework Programme as part of a €6.0 million consortium project (Grant n° 601851)

for the development of mathematical and statistical algorithms focusing on integrating data from multiple

analytical platforms focusing on integrating genetic and proteomic data with clinical variables. On

receiving the award, Carl-Johan Ivarsson, CEO, Qlucore said, “Personalized medicine, and in

particular Hepatitis C patients, will benefit from the project outcome. One of the primary

objectives of the consortium is to provide predictive tests that will lead to improvements in the

health of these patients, which will simultaneously reduce the costs of medical treatment.”

The consortium, known as the PoC-HCV consortium*, aims to develop integrated genetic and protein

biomarker tests for use in treating and monitoring HCV patients, as well as in clinical research. Data and

algorithms will be tailored for analysis and treatment in a Point of Care environment for Hepatitis C. One

of the outputs from the consortium will be a mobile application prototype where the algorithms are

implemented. Establishing a path for validation and implementation of point-of-care medical devices is a

challenge, and the driving vision of the Consortium. The consortium additionally consists of the

coordinator Inserm (Institut Pasteur) (France), Inserm Transfert (France), Epistem (UK) and Biosurfit

(Portugal).

With the primary objective to provide Point of Care diagnostic and predictive tests and reduce costs, the

approach will capitalise on the consortium’s combined expertise spanning leading edge miniaturised

molecular testing, lab-on-a-chip systems and algorithm design. These enabling technologies will permit

the development and delivery of the first integrated genetic and protein biomarker tests, applied here to

Hepatitis C disease for: (i) making the decision to treat; (ii) selection of therapy; (iii) response-guided

monitoring; and (iv) clinical research practices.

Hepatatis-C is a global public health problem with over 150 million people infected worldwide,

representing a 15 billion Euro/year market. It is particularly prevalent in under-developed countries and

treatments can be very costly. One vision is to allow the physicians to make better treatment decisions

(selecting the correct drug) and hence lower the total cost of treatment. In countries with many infected

patients and limited healthcare budget this will provide an enormous improvement in quality of life for this

patient group. The algorithms developed by Qlucore will be based on classification techniques. They will also be

available in future versions of Qlucore Omics Explorer and hence enable researchers and physicians in

other areas to benefit from the results.

Qlucore has recruited and increased its engineering capacity in order to fulfil its role in the PoC HCV

consortium. This, combined with the recently announced grant to Qlucore from VINNOVA (Swedish

Governmental Agency for Innovation Systems) is additional validation of the high value being placed on

developments currently being undertaken by Qlucore.

*The The PoC-HCV consortium, includes Inserm (Institut Pasteur), Inserm Transfert, Qlucore, Epistem and Biosurfit,

and aims to provide PoC diagnostic and predictive tests that enable tangible improvements in the health and quality

of life of chronic hepatitis C patients

About Qlucore

Qlucore started as a collaborative research project at Lund University, Sweden, supported by researchers

at the Departments of Mathematics and Clinical Genetics, in order to address the vast amount of highdimensional data generated with microarray gene expression analysis. As a result, it was recognised that

an interactive scientific software tool was needed to conceptualise the ideas evolving from the research

collaboration.

The basic concept behind the software is to provide a tool that can take full advantage of the most

powerful pattern recogniser that exists – the human brain. The result is a core software engine that

visualises the data in 3D and will aid the user in identifying hidden structures and patterns. Over the last

two years the major efforts have been to optimise the early ideas and to develop a core software engine

that is extremely fast, allowing the user to interactively and in real time instantly explore and analyse highdimensional data sets with the use of a normal PC.

Qlucore was founded in early 2007 and the first product released was the “Qlucore Gene Expression

Explorer 1.0”. The latest version of this software, Version1.1, represents a major step forward with the

advanced statistics support. All user action is at most two mouse clicks away. The Company’s early

customers are mainly from the Life-science and Biotech industries, but solutions for other industries are

currently under development.

One of the key methods used by Qlucore Gene Expression Explorer to visualise data is dynamic principal

component analysis (PCA), an innovative way of combining PCA analysis with immediate user

interaction. Dynamic PCA is PCA analysis combined with instant user response, a combination which

provides an optimal way for users to visualise and analyse a large dataset. By presenting a

comprehensive view of the data set at the same time, the user is given full freedom to explore all possible

versions of the presented view.