Download: Kinapse on New Data Analytics for Pharma and Healthcare


An interview with Stephen Doogan on data integration and analytics for drug evaluation and patient experience

McKinsey has predicted big data could reduce research and development costs for pharmaceutical makers by $40 billion to $70 billion. New analytics strategies are now changing companies’ ability to integrate, harmonize, derive and cross-validate insights from disconnected data at scale. Pharma companies who team up with big data analytics companies to exploit their own data efficiently will reduce their costs and improve their competitiveness, especially in the research and development of new products.

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Key topics include:

  • What major challenges companies face when transitioning to a data-driven and collaborative approach (sharing clinical trials and patient’s experiences data) ?
  • What are the benefits of implementing big data analytics strategies for case record review, pharmacovigilance, and real world observational research?
  • Why and how to analyse data from patient communities and social networks to gain insight into the entire consumer experience?
  • How to better communicate with patients and meet the growing information needs of patients

Stephen’s interview is a taster for the Big Data in Pharma Briefing, taking place on 23 September 2014 in London. The Briefing will explore how you can make the most of your data to boost innovation and efficiency in the entire R&D process through analytics strategies and collaboration.


data pharma R&D