From Chaos To Clarity – How FAIR Data Principles Deliver Clinical Data Management And Analytics Success

By Philip Ross, Revvity

Human beings are physiologically complex, as are the diseases and conditions that afflict them. Therefore, the more scientists understand the body’s mechanisms, the more complex clinical trials become as pharmaceutical and biotechnology companies create innovative therapeutics to target disease and benefit the largest number of patients. During a trial, investigators must gather enormous amounts of data from each participant to ensure a drug’s safety and efficacy. Traditionally, that information is collected at a trial site, but when DCTs, wearable devices, telehealth, and third-party labs are factored into the mix, data management becomes even more cumbersome.

Managing, aggregating, and cleaning these data points can be so time-consuming that little time is left to create invaluable clinical analytics and visualizations that drive study decisions. To improve data management and reduce manual labor and delays, companies should adhere to the FAIR principles that data are:

• Findable
• Accessible
• Interoperable
• Reusable

When optimized, FAIR empowers companies to spend less time managing data and more time understanding and applying it. A centralized analytics platform can deliver fast, flexible, and scalable data preparation with safety, efficiency, and operational insights that empower companies to make quick decisions while safeguarding participants’ well-being.