Featured Article
Maximizing the value of data from wearable medical devices
Time series data plays an essential role in safety and efficacy measurements. Data from electrocardiograms, MRIs, and other medical devices provides prima facie evidence of disease states. Deeper understanding of medical device data can give practitioners considerable insight into disease mechanisms and potentially predictive insights. This paper shows how a scientific database management system can enable maximizing the utility and value of biomedical device data.
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Featured Article
Foundation Medicine
Recent estimates cite the risk-adjusted cost of bringing a new drug to approval north of $2.5 billion. This is a staggering amount, particularly when less than 10 percent of newly innovated therapeutics survive the clinical development process. Indeed, drug development is fraught with high costs and even higher risk. Biopharma companies need a way to change the cost-risk equation and ensure the balance is tipped toward returns.
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Featured White Paper
Industrialize Safety and Efficacy Biomarker Discovery
Today’s biopharmaceutical companies face a critical need to move beyond first generation bioinformatics tools. New scientific information technology solutions can be a discovery engine for precision medicine programs, enabling data-driven hypothesis generation and patient stratification to accelerate the discovery of safety and efficacy biomarkers from molecular, clinical, image, and RWE data. By simplifying the day-to-day challenge of working with multiple lines of evidence, a scientific database management system can support clinical guidance for programs such as precision gemcitabine treatment.
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Featured Paper
Accelerating bioinformatics research: turning Big Data into knowledge
Biological data is flooding the pharmaceutical and medical sectors. Advances in sequencing technology are making it possible to create the world of precision medicine-except for one problem: first generation bioinformatics software tools do not readily allow data to be searchable or sharable, thus precluding easy analysis. By separating data storage from computing too much time is spent moving data instead of analyzing data. What's needed is a new paradigm for scientific data management and analysis.
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