Oracle promises streamlined end to end clinical data flow with new cloud service

28 March 2017
News
Planning and managing clinical trials has become more complex as additional data is being generated, collected and analysed to demonstrate clinical efficacy, ensure successful regulatory approval and ultimately bring more therapies to market faster. The new data management cloud service Oracle introduced should enable pharmaceutical companies and contract research organizations to integrate, reconcile and analyze the growing variety and volume of clinical and healthcare data.

Oracle states the workbench provides enhanced standardization, reusability and traceability among disparate clinical data sources by enabling data managers to aggregate, clean and transform data into submission-ready deliverables. By automating data flow and standardizing data for review, clinical researchers have near real time access to insights for clinical trial decision making—all at a lower total cost of ownership as a result of it being offered as a cloud service.

Massive increase, complexity of data

Steve Rosenberg, general manager, Oracle Health Sciences, says the volume and complexity of data in healthcare and life sciences has increased on a massive scale as more data is captured from sources such as electronic health records, wearables and genomics. Clinical data managers and data scientists are now integrating more of this data into their clinical research and trials to improve the odds of more therapies making it to market and faster.

“The industry has been looking for a purpose-built data management solution that supports the clinical data flow from source to submission, with a lightweight, cloud-based solution. Oracle’s new cloud-based data management platform is able to manage all of this new information while ensuring FDA data compliance—at a dramatically lower cost.”

Oracle Data Management Workbench Cloud Service has been pre-integrated with Oracle Health Sciences InForm, which enables two-way real time data flow. Additionally, the combination should bring new levels of standardization, reusability and traceability among disparate clinical data sources by enabling clinical data managers to aggregate, clean and transform data into submission-ready deliverables more quickly than ever before.