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China will be the next big step for us: QluCore
Jahanara Parveen

 Carl-Johan Ivarsson, President, Qlucore, Sweden
Bangalore, Jan 07, 2010: The Swedish company Qlucore was founded in early 2007 and the first product released was the “Qlucore Gene Expression Explorer”.  The bioinformatics software developer has recently entered the Indian market by signing an agreement with JH BIO Innovations, a specialist Indian  distribution company that caters to major pharmaceutical companies, research institutes, and universities in India. Qlucore has already experienced a strong interest from the Indian market, with many companies downloading trial versions of its data analysis software. Qlucore's latest software, called Qlucore Omics Explorer, has been developed for the life science, agricultural and biotech industry. With its highly intuitive user interface, Qlucore Omics Explorer allows researchers to shorten analysis time and add more creativity to research, thanks to the product's instant response and statistical analysis capabilities. In an interview with BioSpectrum Carl-Johan Ivarsson, President, Qlucore, Sweden shares more insights.

1. Can you tell us about your product, Qlucore Omics Explorer, and its applications?

Qlucore Omics Explorer is an enhanced data analysis tool that has been developed for the life science and biotech industries. Because it is highly intuitive, very fast, and also easy to use, Qlucore Omics Explorer allows scientists and biologists to explore different hypotheses and alternative scenarios within seconds. The software is therefore invaluable for unveiling important new discoveries, as it allows the actual researchers – the people with the most biological insight – to study the data and to look for patterns and structures, without needing to be a statistics or computer expert.

Qlucore Omics Explorer can be used on basically any multivariate data, including data from Gene Expression, protein array, DNA Methylation and proteomics experiments.

2. Who funded the product's development?

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 high-dimensional data generated with microarray gene expression analysis. Today, Qlucore remains a privately-owned company that is committed to achieving this same goal through a dedicated programme of product development.
 
3. Can you elaborate on Qlucore's growth plan?

Qlucore currently has customers in eight different countries, and we are doubling our sales each year. We expect to sustain this rate of growth for the next few years, since we are still a young company.

4. What is the company's strategy for growth?

The first step is to create a broader awareness of Qlucore. This can be achieved by working closely with our distributors, agents and other strategic partners in selected countries.

5. You have recently signed an agreement with an Indian distributor. Why is India an important market for Qlucore?

India has a vibrant and fast-growing biotech and pharmaceutical sector. As such, India is currently educating a lot of researchers in these and other related areas, and the Qlucore software will play an important role in their research.

6. Which are the other Asian regions you are looking at for marketing your products? And what steps has Qlucore taken to expand into those regions?

China will be the next big step for us, and we are already speaking to a number of distributors and agents in this area.

7. Who are your major clients?

A number of well-known research institutions are currently using our software, including the National Cancer Institute in the USA, King’s College London in the United Kingdom, France's National Health Institute (INSERM), as well as leading universities in both Sweden and Germany.
 
8. What are your main focus areas? And are there any new areas that you plan to enter into?

At the moment, we typically focus on data that is derived from life sciences industry, but future possibilities could include virtually any project where the amount of data being produced is very large, such as complex financial applications, for example.

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