Big Data - How to Realize the Promise

Clin Pharmacol Ther. 2020 Apr;107(4):753-761. doi: 10.1002/cpt.1736. Epub 2020 Jan 27.

Abstract

The increasing volume and complexity of data now being captured across multiple settings and devices offers the opportunity to deliver a better characterization of diseases, treatments, and the performance of medicinal products in individual healthcare systems. Such data sources, commonly labeled as big data, are generally large, accumulating rapidly, and incorporate multiple data types and forms. Determining the acceptability of these data to support regulatory decisions demands an understanding of data provenance and quality in addition to confirming the validity of new approaches and methods for processing and analyzing these data. The Heads of Agencies and the European Medicines Agency Joint Big Data Taskforce was established to consider these issues from the regulatory perspective. This review reflects the thinking from its first phase and describes the big data landscape from a regulatory perspective and the challenges to be addressed in order that regulators can know when and how to have confidence in the evidence generated from big datasets.

MeSH terms

  • Big Data*
  • Data Science
  • Drug and Narcotic Control / methods*
  • Humans