Each life science company generates terabytes of data and keeps it hidden behind a firewall. This is due partly to strict regulatory and compliance standards and partly to the extremely competitive environment in which these companies operate. Most of this information sits in silos, and for a long time, companies did not actually consider it suitable for retrospective or predictive analysis. The objective of this paper is to establish the benefits of using simulated data to overcome the challenges posed by real world data and to test the prediction accuracy of a machine learning model that was trained on a simulated EMR dataset.
With the intent of bridging the gap between the healthcare industry and the rising data exchange needs, Virtusa is providing enterprise clients with simulated data to meet their testing requirements. In a strategic move in November 2018, Virtusa partnered with Indiana Biosciences Research Institute (IBRI) to accelerate life sciences research and development. This collaborative project will focus on a comparative analysis of simulated data with real-world data to study diabetes patients. With its signature vLife platform, Virtusa will also try to address the challenges of healthcare and life sciences companies by analyzing numerous information that is placed in silos and speed up the testing process to develop next-level treatments and patient cure.
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