Improving Drug Review with Data Standards Transcript

Janet Woodcock, M.D.—Director, Center for Drug Evaluation and Research (CDER)

A data standard is a set of rules on how a particular type of data should be structured, defined, formatted, and/or exchanged between computer systems.

In 2010, CDER began a concerted push toward implementing data standards across our pre- and postmarket programs. CDER now requires most study data to conform to standard formats and relevant terminologies.

Data standards make the exchange of data and the content within them predictable, consistent, and in a form that an information technology system or scientific tool can use. With data standards, reviewers can focus on their scientific review instead of spending precious time understanding and formatting huge amounts of less-structured data.

Data standards can help us make patient-centric decisions. With them, we can integrate real-world data into the drug development process and into some of our own processes, such as our postmarket safety monitoring.

FDA actively participates with the key standards development and maintenance organizations who develop standards in the health care and clinical research domains.

Traditionally, premarket safety and efficacy data comes from clinical trials, and safety data in the postmarket environment came from adverse event reports. Researchers now want to tap into health data available in electronic health records, insurance claims, mobile health, and even social media. This data, called real-world data, has the potential to answer important questions and provide new insights into drug safety and efficacy at all stages of the drug lifecycle, from development through its useful life and patient care. It also has the potential to make drug development and safety monitoring more efficient and faster.

We must figure out how to align previously existing data into standards and how to make sure future data is collected in a standardized way. The solution is to develop a Rosetta stone that will allow researchers to answer a question once and receive results from many different sources using a common agreed-upon structure or a common data or information model.

CDER is leading a multiagency effort to connect, or map, several of these different common data models through a single model and a set of query tools. You can expect CDER to be at the table for those discussions advocating for standards that facilitate efficient and effective data integration and sharing. It has helped us come a long way so far, and the future will be really powerful.