Last month, Cambridge Semantics held its inaugural Life Sciences Smart Data Discovery and Analytics Forum in Boston. At this forum, leaders in Life Sciences and Big Data met to discuss the application of smart data technology to research and development, clinical trial and healthcare data to gain more actionable insights and shorten the overall product lifecycle.
In the pharmaceutical world, clinical trials are essential to any medical research study, such as testing the benefits and risks of a specific medical treatment or drug. But because massive amounts of data is collected, analyzed and reported, investigators and doctors running these trials require a comprehensive set of standards to support the exchange of confidential information.
Data integration projects can be time consuming, expensive and difficult to manage.Traditional data integration methods require point to point mapping of source and target systems. This effort typically requires a team of both business SMEs and technology professionals. These mappings are time consuming to create and code and errors in the ETL (Extract, Transform, and Load) process require iterative cycles through the process.
The FDA has adopted the CDISC SDTM standard for clinical trial submission. While the standard has the potential to simplify the reporting processes, adoption poses challenges to and raises questions for pharma companies testing their medicines in the clinic. In response, organizations have tasked groups with managing clinical trial metadata in compliances with these standards.
We at Cambridge Semantics have been working with these groups to address these challenges with Anzo Pharma SmartBench, a user-driven platform for developing flexible data collaboration, integration and analytics solutions. Anzo Pharma SmartBench is based on Semantic Web Technology – the same standards used by CDISC to represent SDTM.
Anzo Pharma SmartBench features –
As FDA outlines, “the submission of standardized study data enhances a reviewer’s ability to more fully understand and characterize the efficacy and safety of a medical product,” and adopted CDISC standards based on semantic technology to be the standards for submitting and using study data. They further “envision a semantically interoperable and sustainable submission environment that serves both regulated clinical research and health care.”