Use of big data for drug development and for public and personal health and care

Lada Leyens, Matthias Reumann, Nuria Malats, Angela Brand

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)


The use of data analytics across the entire healthcare value chain, from drug discovery and development through epidemiology to informed clinical decision for patients or policy making for public health, has seen an explosion in the recent years. The increase in quantity and variety of data available together with the improvement of storing capabilities and analytical tools offer numerous possibilities to all stakeholders (manufacturers, regulators, payers, healthcare providers, decision makers, researchers) but most importantly, it has the potential to improve general health outcomes if we learn how to exploit it in the right way. This article looks at the different sources of data and the importance of unstructured data. It goes on to summarize current and potential future uses in drug discovery, development, and monitoring as well as in public and personal healthcare; including examples of good practice and recent developments. Finally, we discuss the main practical and ethical challenges to unravel the full potential of big data in healthcare and conclude that all stakeholders need to work together towards the common goal of making sense of the available data for the common good.

Original languageEnglish
Pages (from-to)51-60
Number of pages10
JournalGenetic Epidemiology
Issue number1
Publication statusPublished - 01-01-2017

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Genetics(clinical)


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