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Genedata Launches Data Science Services for Precision Medicine

By   /  January 24, 2017  /  No Comments

by Angela Guess

A recent press release states, “Genedata, a leading provider of advanced software solutions for pharmaceutical research and development (R&D), today announced the launch of Data Science Services, offering on-demand, project-based expertise in omic data analysis and interpretation for the rapidly evolving field of precision medicine. Data Science Services allows pharmaceutical R&D organizations to quickly derive scientifically- and commercially-critical conclusions from their omics-based patient profiling projects, without having to invest in software infrastructure or data analysis resources. Extensive experience of 20 years working with leading R&D organizations and the world’s top biopharmaceutical companies, coupled with the industry-leading Genedata Profiler™ platform, ensures that data science projects are executed efficiently and cost-effectively. Data Science Services clients will benefit from the transparent reporting of actionable results, enabling informed decision-making for biopharmaceutical R&D.”

The release goes on, “Genedata recognized that many companies need sophisticated analyses of their omic data in their precision medicine projects. To meet this need, Genedata has extended its business model to offer access to its scientific expertise via Data Science Services. Genedata’s experienced team of Ph.D. level biologists, bioinformaticians, and statisticians now offers in-depth analyses of omic data in close collaboration with scientists from client organizations. Data Science Services helps pharma, biotech and other organizations to integrate and analyze complex and challenging omics-related projects such as mode-of-action, large-scale genotyping, pharmacogenomics, patient stratification, and biomarker discovery studies. The service offers detailed analyses and scientifically founded results interpretation of data from next-generation sequencing, microarray, real time-PCR, and other genomic technologies, as well as other omics such as proteomics and metabolomics, in conjunction with clinical and phenotypic data.”

Read more at PRweb.

Photo credit: Genedata

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