Executive Summary
The ability to access, analyze, and manage vast volumes of data while rapidly evolving the Information Architecture has long been critical to pharmaceutical and life sciences companies as they improve business efficiency and performance. While accelerated drug development that drives improved drug pipelines and more complete clinical trials and the ability to predict failure early remain keys to success, better analysis of patient adherence and improving time to market for new drugs helps to maximize overall profitability. Big Data solutions help improve the efficiency of the drug discovery and development process.
A Big Data based architecture enables the inclusion of a greater variety of data sources so that more data can be analyzed. This, in turn, broadens the analytics and predictive options leading to better outcomes. Today these data sources can include:
» Traditional enterprise data from operational systems
» Life Science Real World Data (RWD)
» EMR data along with integrated healthcare systems data » Clinical data from:
» Clinical trials
» Sensors within pills
» Connected medical devices
» Research data including genome and biomarker identification data
» Manufacturing & supply chain data from sensors » Marketing data from
» Sales campaigns
» Advertising response
» Demand and price realization
» Financial business forecast data » Web site browsing pattern data » Social media data
These new large datasets accessible in a Big Data architecture enable pharmaceutical and life science companies to:
» Accelerate drug innovation
» Improve determination of clinical trial outcomes sooner » Gain access to new markets
» Identify unmet medical needs
» Defend pricing and improved margins