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.
To help pharmaceutical companies with secure data collection and analysis, standards development organization Clinical Data Interchange Standards Consortium (CDISC) provides standards for the support of electronic acquisition, exchange and archival of clinical trials data and metadata for medical and biopharmaceutical product development.
But every study has exceptions, and being able to manage those exceptions has become a challenge. If a trial is not standards-based, there is a significant amount of time and manual preparation that goes into setting up for that trial. For example, participants are required to fill out online forms about their background and medical history, including gender, age and location, and each field on the form has a variable associated with it. Pharmaceutical companies develop these forms for the doctors to use for trials, yet the process for creating these forms is intensive and requires in-depth training.
That’s where Cambridge Semantics steps in.
Cambridge Semantics provides the services needed to assist customers with building these front-end setups. Because many system formats are not standards-based, the company uses its Anzo Smart Data Lake™ (ASDL) solution to collect patient data for rapid analysis and discovery, eliminating the lengthy time previously needed for pulling data. Using the ASDL, Cambridge Semantics is efficiently able to collect, analyze and extract meaning and insight from this data for its pharmaceutical customers, turning their assumptions of the sampled population into valuable information.
Essential to the growth and development of medical research studies, CDISC standards recognize the ultimate goal of creating scientific content that is easily interpreted, understood and navigated by researchers. The ASDL aligns with this same approach, simplifying the process even further.
To learn more about Smart Data Lakes, download the whitepaper: "Anzo Smart Data Lake: Enterprise Graph-based Data Discovery, Analytics and Governance".