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On the path of personalized medicine
May 2009
by Amy Swinderman  |  Email the author
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BASEL, SwitzerlandóGenedata AG, a provider of in silico solutions for pharmaceutical and life sciences researchers, in April announced an informatics collaboration with TcLand Expression SA, a molecular diagnostics company focused on the field of immunology. The partnership marries Genedata's Phylosopher and Expressionist biomarker discovery platforms and TcLand Expressions' collection of pangenomic expression data on autoimmune diseases and organ transplantation. Financial terms of the deal were not disclosed.

Founded in 2002 in Nantes, France, as a spin-off from the Institut de Transplantation et de Recherche en Transplantation (ITERT), one of the world's leading research institutes in transplantation and immunology, TcLand Expression is collaborating with healthcare professionals and patients worldwide to develop gene expression signatures as part of its work in the field of personalized medicine for transplantation and autoimmune diseases.

The company turned to Genedata for a solution that would serve as a scalable, core infrastructure supporting interdisciplinary biomarker identification, validation and mode-of-action studies. Both Phylosopher and Expressionist enable scientists to process, integrate, analyze and manage large and complex experimental data sets generated by high-throughput technologies, with Phylosopher focused on target discovery and integrative biological data management, and Expressionist designed for biomarker discovery and personalized medicine.

The integration will enable TcLand Expression's researchers to take a cross-technology approach by using automated workflows and integrated analysis tools to streamline the research workflow from experimental design through to final results. The collaboration validates Genedata's strategy of delivering scalable and flexible research IT infrastructure solutions for biomarker discovery, monitoring and biological interpretation, says Genedata Managing Director Jens Hoefkens.

"TcLand Expression being a relatively young company, they approached us a couple of months ago because they were intrigued by our offerings and the capability of both Expressionist and Phylosopher to deliver important tools out of a single hand," Hoefkens says. "They are not a huge company, so it was important for them to work with a single partner who will be there to support them as they grow."

Genedata's integrated solution gives TcLand Expression the flexibility it needs in its R&D processes as well as the automation, traceability and 21 CFR part 11 compliance needed in its clinical studies, says Dr. Alain Huriez, chairman and CEO of TcLand Expression.

"Genedata has allowed us to accelerate and facilitate our biomarker identification procedures," Huriez says. "It has enabled us to perform fully automated and audited analyses, allowing us to analyze hundreds of pangenomic chips in a matter of minutes. The software is extremely powerful, yet very easy to use. We particularly valued all the quality checks, including the detailed visualization of the Affymetrix chips."

Genedata has also helped TcLand Expression to integrate all relevant gene information in a single platform, making the visualization of information extremely easy and bringing a biological context to the data, Huriez adds. Combining TcLand Expression's data with public expression data and centralizing it in one platform has enabled the company to validate the quantity of its identified biomarkers and to validate the specificity of its signatures, he says.

"For example, our scientists can visualize the precise location of the probes used on the pangenomic chips as well as the location of the Taqman probes used in our assays, along with all the gene information," Huriez says. "We have thus set up an informatics infrastructure that is not only of the highest quality and extremely fast, but also that allows us to really understand more about the genes making up our signatures."
The ultimate goal of the partnership is to enable TcLand Expression to identify to what degree or predict when a particular patient will need immunosuppressants following an organ transplant, Hoefkens says.

"This goal is on the way toward the point of personalized medicine," he says. "We're not there yet because we are still in the biomarker discovery phase. But once we get there, you can use expression data together with PCR data in a much more manageable way to cross-validate those two results and ultimately derive a simple test kit that can actually be used in clinics. It can be done, but we are not there yet."
 
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