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Dr. Arndt Rolfs talks at ECRD about speeding up the rare disease knowledge and information eco-system based on proteomic screening tools

This year´s European Conference on Rare Diseases and Orphan Products (ECRD 2018 Vienna) gathered over 800 participants from patient organizations, academics, health care professionals, industry, payers, regulators and policy makers to approach the topic of “Rare diseases 360°: Collaborative strategies to leave no one behind”. Currently, it is estimated that in Europe a total number of 29 million people are affected by rare diseases.

Dr. Arndt Rolfs, CENTOGENE´s CEO and Founder, presented in a panel discussion at ECRD the company´s vision within the rare disease knowledge and information network. The discussion was part the theme “Global Rare Equity: Are we there yet?” and addressed the challenges in achieving global equity for rare diseases from policy and research to products and practical solutions. Dr. Rolfs underlined the importance of transferring the rare disease diagnostics burden from the physicians’ shoulders in the laboratory environment. In order to achieve this ambitious goal, the laboratories need to support the process by implementing cheaper and robust proteomic based screening systems. Such a global proteomic concept will have a high importance in the early identification of rare diseases and is the key to shortening the diagnostic odyssey of the patients.  

CENTOGENE, positioned uniquely at the intersection of genetic testing and multilayer proteomic/metabolomics strategies, relies on CentoMD®, the world´s largest mutation database of rare diseases. CentoMD® bridges the gap between genetic variants and clinical interpretation.

“At CENTOGENE, we have understood the importance of genetic and proteomic knowledge in transforming modern medicine and helping clinicians taking more informed medical decisions. We are dedicated to improve the lives of rare disease patients by supporting pharma companies in developing next-generation medicines. We achieve this by creating knowledge value products based on genetic, proteomic and metabolomic big data” said Dr. Rolfs.

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